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This document is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 732064. It is the property of the DataBio consortium and shall not be distributed or reproduced without the formal approval of the DataBio Management Committee.
Project Acronym: DataBio
Grant Agreement number: 732064 (H2020-ICT-2016-1 – Innovation Action)
Project Full Title: Data-Driven Bioeconomy
Project Coordinator: INTRASOFT International
DELIVERABLE
D2.1 – Forestry Pilot Definition
Dissemination level PU -Public
Type of Document Report
Contractual date of delivery M06 – 30/6/2017
Deliverable Leader Renne Tergujeff, VTT
Status - version, date Final – v1.0, 30/6/2017
WP / Task responsible WP2 / T2.1
Keywords: Forestry, pilot, big data, modelling, user analysis,
user requirements, stakeholders
D2.1 – Forestry Pilot Definition H2020 Contract No. 732064 Final – v1.0, 30/6/2017
Dissemination level: PU -Public Page 2
Executive Summary The objective of WP2 Forestry Pilot is to demonstrate through real life applications how Big
Data can boost the forestry sector. The three main pilots, carried out in four countries, are
built around practical cases from forestry.
Task 2.1 Co-innovative preparations specifies the needs of users and other stakeholders. Its
main objective is to come up with requirements by analysing each pilot case. A user and
stakeholder study is produced to specify the most beneficial areas of interest from different
points of view. Alternative solution technologies are reviewed together with pilot
stakeholders and users. Based on this, a set of scenarios are constructed for the forestry
sector. Functional requirements are defined from the scenarios and used as input for the case
specification, development and piloting. Subtasks concerning scenarios and use cases are
organized iteratively around working cycles. The results are the pilot cases definitions
including requirements specifications, implementation and evaluation plans.
The organizations that were planned to participate in this task, and their respective planned
work effort in person-months, are VTT (6), SPACEBEL (2), METSAK (4), IBM (2), MHGS (6),
Fraunhofer (4), Tragsa (6), FMI (2) CSEM (2), OGCE (6) and e-geos (6).
The deliverable D2.1 Forestry Pilot Definition specifies the pilot case definitions, requirement
specifications, as well as implementation and evaluation plans.
D2.1 – Forestry Pilot Definition H2020 Contract No. 732064 Final – v1.0, 30/6/2017
Dissemination level: PU -Public Page 3
Deliverable Leader: Renne Tergujeff (VTT)
Contributors:
Anu Kosunen (METSAK), Petr Lukeš (FMI), Philippe Ledent
(SPACEBEL), Jesús Estrada Villegas (TRAGSA), Asunción Roldán
Zamarrón (TRAGSA), Laura Maria Luquero Ramos (TRAGSA),
Seppo Huurinainen (MHGS), Veli-Matti Plosila (MHGS)
Reviewers: Seppo Huurinainen (MHGS), Jorge Casado Álvarez (TRAGSA),
William Ouellette (SPACEBEL)
Approved by: Athanasios Poulakidas (INTRASOFT)
Document History
Version Date Contributor(s) Description
0.1 31/03/2017 Initial TOC draft
0.2 03/05/2017 Updated draft
0.3 31/05/2017 Updated draft
0.4 09/06/2017 Updated draft based on the cross-WP
deliverable templates
0.5 16/06/2017 First complete draft for review
0.6 21/06/2017 Second complete draft for review
0.7 26/06/2017 Reviewed draft
0.8 26/06/2017 Reviewed and edited draft
0.9 29/06/2017 Updated to enhance clarity and to
harmonize between D1.1/D2.1/D3.1
1.0 30/06/2017 Compliance to submission format and
minor changes
D2.1 – Forestry Pilot Definition H2020 Contract No. 732064 Final – v1.0, 30/6/2017
Dissemination level: PU -Public Page 4
Table of Contents EXECUTIVE SUMMARY ..................................................................................................................................... 2
TABLE OF CONTENTS ........................................................................................................................................ 4
TABLE OF FIGURES ........................................................................................................................................... 6
LIST OF TABLES ................................................................................................................................................ 7
DEFINITIONS, ACRONYMS AND ABBREVIATIONS ............................................................................................. 9
INTRODUCTION .................................................................................................................................... 10
1.1 PROJECT SUMMARY ..................................................................................................................................... 10 1.2 DOCUMENT SCOPE ...................................................................................................................................... 13 1.3 DOCUMENT STRUCTURE ............................................................................................................................... 13
SUMMARY ............................................................................................................................................ 14
2.1 OVERVIEW ................................................................................................................................................. 14 2.2 PILOT MODELLING FRAMEWORK ..................................................................................................................... 15 2.3 PILOT INTRODUCTIONS ................................................................................................................................. 18
2.3.1 Wuudis .......................................................................................................................................... 21 2.4 PILOT CASE DEFINITIONS ............................................................................................................................... 21 2.5 BIG DATA ASSETS ......................................................................................................................................... 22 2.6 EVALUATION PLANS ..................................................................................................................................... 23 2.7 IMPLEMENTATION PLANS .............................................................................................................................. 23
PILOT 2.2.1: EASY DATA SHARING AND NETWORKING ......................................................................... 27
3.1 PILOT OVERVIEW ......................................................................................................................................... 27 3.1.1 Pilot introduction .......................................................................................................................... 27 3.1.2 Pilot overview................................................................................................................................ 27
3.2 PILOT CASE DEFINITION ................................................................................................................................. 32 3.2.1 Stakeholders and user stories ....................................................................................................... 32 3.2.2 Motivation and strategy ............................................................................................................... 34 3.2.3 Scope and limitations .................................................................................................................... 35
3.3 PILOT MODELLING WITH ARCHIMATE .............................................................................................................. 35 3.3.1 DataBio forestry pilot 2.2.1 motivation view ................................................................................ 35 3.3.2 DataBio forestry pilot 2.2.1 strategy view .................................................................................... 36
3.4 BIG DATA INFRASTRUCTURE: COMPONENTS AND BDVA CLASSIFICATION ............................................................... 39 3.5 PILOT EVALUATION PLAN ............................................................................................................................... 40
3.5.1 High level goals and KPIs .............................................................................................................. 40 3.6 INITIAL ROADMAP ........................................................................................................................................ 40
PILOT 2.2.2: MONITORING AND CONTROL TOOLS FOR FOREST OWNERS ............................................. 42
4.1 PILOT OVERVIEW ......................................................................................................................................... 42 4.1.1 Pilot introduction .......................................................................................................................... 42 4.1.2 Pilot overview................................................................................................................................ 42
4.2 PILOT CASE DEFINITION ................................................................................................................................. 45 4.2.1 Stakeholders and user stories ....................................................................................................... 45 4.2.2 Motivation and strategy ............................................................................................................... 48 4.2.3 Scope and limitations .................................................................................................................... 49
4.3 PILOT MODELLING WITH ARCHIMATE .............................................................................................................. 49 4.3.1 DataBio forestry pilot 2.2.2 motivation view ................................................................................ 49
D2.1 – Forestry Pilot Definition H2020 Contract No. 732064 Final – v1.0, 30/6/2017
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4.3.2 DataBio forestry pilot 2.2.2 strategy view .................................................................................... 51 4.4 BIG DATA INFRASTRUCTURE: COMPONENTS AND BDVA CLASSIFICATION ............................................................... 53 4.5 PILOT EVALUATION PLAN ............................................................................................................................... 54
4.5.1 High level goals and KPIs .............................................................................................................. 54 4.6 INITIAL ROADMAP ........................................................................................................................................ 54
PILOT 2.3.1: FOREST DAMAGE REMOTE SENSING ................................................................................. 57
5.1 PILOT OVERVIEW ......................................................................................................................................... 57 5.1.1 Pilot introduction .......................................................................................................................... 57 5.1.2 Pilot overview................................................................................................................................ 57
5.2 PILOT CASE DEFINITION ................................................................................................................................. 60 5.2.1 Stakeholders and user stories ....................................................................................................... 60 5.2.2 Motivation and strategy ............................................................................................................... 63 5.2.3 Scope and limitations .................................................................................................................... 64
5.3 PILOT MODELLING WITH ARCHIMATE .............................................................................................................. 64 5.3.1 DataBio forestry pilot 2.3.1 motivation view ................................................................................ 64 5.3.2 DataBio forestry pilot 2.3.1 strategy view .................................................................................... 66
5.4 BIG DATA INFRASTRUCTURE: COMPONENTS AND BDVA CLASSIFICATION ............................................................... 68 5.5 PILOT EVALUATION PLAN ............................................................................................................................... 69
5.5.1 High level goals and KPIs .............................................................................................................. 69 5.6 INITIAL ROADMAP ........................................................................................................................................ 69
PILOT 2.3.2-FH: MONITORING OF FOREST HEALTH ............................................................................... 71
6.1 PILOT OVERVIEW ......................................................................................................................................... 71 6.1.1 Pilot introduction .......................................................................................................................... 71 6.1.2 Pilot overview................................................................................................................................ 71
6.2 PILOT CASE DEFINITION ................................................................................................................................. 75 6.2.1 Stakeholders and user stories ....................................................................................................... 75 6.2.2 Motivation and strategy ............................................................................................................... 76 6.2.3 Scope and limitations .................................................................................................................... 77
6.3 PILOT MODELLING WITH ARCHIMATE .............................................................................................................. 77 6.3.1 DataBio forestry pilot 2.3.2-FH motivation view .......................................................................... 77 6.3.2 DataBio forestry pilot 2.3.2-FH strategy view ............................................................................... 79
6.4 BIG DATA INFRASTRUCTURE: COMPONENTS AND BDVA CLASSIFICATION ............................................................... 81 6.5 PILOT EVALUATION PLAN ............................................................................................................................... 82
6.5.1 High level goals and KPIs .............................................................................................................. 82 6.6 INITIAL ROADMAP ........................................................................................................................................ 82
PILOT 2.3.2-IAS: INVASIVE ALIEN SPECIES CONTROL AND MONITORING .............................................. 84
7.1 PILOT OVERVIEW ......................................................................................................................................... 84 7.1.1 Pilot introduction .......................................................................................................................... 84 7.1.2 Pilot overview................................................................................................................................ 84
7.2 PILOT CASE DEFINITION ................................................................................................................................. 88 7.2.1 Stakeholders and user stories ....................................................................................................... 88 7.2.2 Motivation and strategy ............................................................................................................... 89 7.2.3 Scope and limitations .................................................................................................................... 89
7.3 PILOT MODELLING WITH ARCHIMATE .............................................................................................................. 90 7.3.1 DataBio forestry pilot 2.3.2-IAS motivation view .......................................................................... 90 7.3.2 DataBio forestry pilot 2.3.2-IAS strategy view .............................................................................. 90
7.4 BIG DATA INFRASTRUCTURE: COMPONENTS AND BDVA CLASSIFICATION ............................................................... 92 7.5 PILOT EVALUATION PLAN ............................................................................................................................... 93
7.5.1 High level goals and KPIs .............................................................................................................. 93
D2.1 – Forestry Pilot Definition H2020 Contract No. 732064 Final – v1.0, 30/6/2017
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7.6 INITIAL ROADMAP ........................................................................................................................................ 93
PILOT 2.4.1: WEB-MAPPING SERVICE FOR GOVERNMENT DECISION MAKING ...................................... 95
8.1 PILOT OVERVIEW ......................................................................................................................................... 95 8.1.1 Pilot introduction .......................................................................................................................... 95 8.1.2 Pilot overview................................................................................................................................ 95
8.2 PILOT CASE DEFINITION ................................................................................................................................. 97 8.2.1 Stakeholders and user stories ....................................................................................................... 97 8.2.2 Motivation and strategy ............................................................................................................... 98 8.2.3 Scope and limitations .................................................................................................................... 98
8.3 PILOT MODELLING WITH ARCHIMATE .............................................................................................................. 99 8.3.1 DataBio forestry pilot 2.4.1 motivation view ................................................................................ 99 8.3.2 DataBio forestry pilot 2.4.1 strategy view .................................................................................. 100
8.4 BIG DATA INFRASTRUCTURE: COMPONENTS AND BDVA CLASSIFICATION ............................................................. 101 8.5 PILOT EVALUATION PLAN ............................................................................................................................. 102
8.5.1 High level goals and KPIs ............................................................................................................ 102 8.6 INITIAL ROADMAP ...................................................................................................................................... 102
PILOT 2.4.2: SHARED MULTIUSER FOREST DATA ENVIRONMENT ........................................................ 104
9.1 PILOT OVERVIEW ....................................................................................................................................... 104 9.1.1 Pilot introduction ........................................................................................................................ 104 9.1.2 Pilot overview.............................................................................................................................. 104
9.2 PILOT CASE DEFINITION ............................................................................................................................... 107 9.2.1 Stakeholders and user stories ..................................................................................................... 107 9.2.2 Motivation and strategy ............................................................................................................. 107 9.2.3 Scope and limitations .................................................................................................................. 108
9.3 PILOT MODELLING WITH ARCHIMATE ............................................................................................................ 108 9.3.1 DataBio forestry pilot 2.4.2 motivation view .............................................................................. 108 9.3.2 DataBio forestry pilot 2.4.2 strategy view .................................................................................. 109
9.4 BIG DATA INFRASTRUCTURE: COMPONENTS AND BDVA CLASSIFICATION ............................................................. 111 9.5 PILOT EVALUATION PLAN ............................................................................................................................. 112
9.5.1 High level goals and KPIs ............................................................................................................ 112 9.6 INITIAL ROADMAP ...................................................................................................................................... 113
REFERENCES ....................................................................................................................................... 115
Table of Figures FIGURE 1: ARCHIMATE 3.0 MODELLING FRAMEWORK. ..................................................................................................... 15 FIGURE 2: RELATIONSHIPS OF THE MOTIVATION ELEMENTS ................................................................................................ 18 FIGURE 3: RELATIONSHIPS OF THE STRATEGY ELEMENTS .................................................................................................... 18 FIGURE 4: TIMELINE OF PILOT 2.2.1, EASY DATA SHARING AND NETWORKING ....................................................................... 23 FIGURE 5: TIMELINE OF PILOT 2.2.2, MONITORING AND CONTROL TOOLS FOR FOREST OWNERS ............................................... 24 FIGURE 6: TIMELINE OF PILOT 2.3.1, FOREST DAMAGE REMOTE SENSING ............................................................................. 24 FIGURE 7: TIMELINE OF PILOT 2.3.2-FH, MONITORING OF FOREST HEALTH .......................................................................... 25 FIGURE 8: TIMELINE OF PILOT 2.3.2-IAS, INVASIVE ALIEN SPECIES CONTROL AND MONITORING ................................................ 25 FIGURE 9: TIMELINE OF PILOT 2.4.1, WEB-MAPPING SERVICE FOR THE GOVERNMENT DECISION MAKING ................................... 26 FIGURE 10: TIMELINE OF PILOT 2.4.2, SHARED MULTIUSER FOREST DATA ENVIRONMENT ........................................................ 26 FIGURE 11: PILOT ESTATE FORESTRY DATA TRANSFERRED INTO WUUDIS FROM THE FORESTRY AUTHORITY SYSTEM (METSAAN.FI) .... 28 FIGURE 12: DATA SHARING IN WUUDIS ......................................................................................................................... 29 FIGURE 13: FORESTRY A1 MOTIVATION VIEW ................................................................................................................. 36
D2.1 – Forestry Pilot Definition H2020 Contract No. 732064 Final – v1.0, 30/6/2017
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FIGURE 14: FORESTRY A1 FOREST USER MOTIVATION VIEW .............................................................................................. 36 FIGURE 15: FORESTRY A1 STRATEGY VIEW ..................................................................................................................... 37 FIGURE 16: FORESTRY A1 FOREST USER STRATEGY VIEW .................................................................................................. 37 FIGURE 17: BIG DATA COMPONENTS AND ASSETS IN PILOT 2.2.1: EASY DATA SHARING AND NETWORKING ................................. 39 FIGURE 18: TIMELINE OF PILOT 2.2.1, EASY DATA SHARING AND NETWORKING ..................................................................... 41 FIGURE 19: FORESTRY A2 MOTIVATION VIEW ................................................................................................................. 50 FIGURE 20: FORESTRY A2 FOREST OWNER MOTIVATION VIEW ........................................................................................... 50 FIGURE 21: FORESTRY A2 STRATEGY VIEW ..................................................................................................................... 51 FIGURE 22: FORESTRY A2 FOREST OWNER STRATEGY VIEW ............................................................................................... 52 FIGURE 23: BIG DATA COMPONENTS AND ASSETS IN PILOT 2.2.2: MONITORING AND CONTROL TOOLS FOR FOREST OWNERS .......... 53 FIGURE 24: WUUDIS MOBILE APP FOR OBSERVATION REPORTING ........................................................................................ 55 FIGURE 25: TIMELINE OF PILOT 2.2.2, MONITORING AND CONTROL TOOLS FOR FOREST OWNERS ............................................. 56 FIGURE 26: PILOT FORESTY, RANGUNKORPI COOPERATIVE FORESTY, ON THE WUUDIS SERVICE ................................................. 58 FIGURE 27: FORESTRY B1 MOTIVATION VIEW ................................................................................................................. 65 FIGURE 28: FORESTRY B1 STRATEGY VIEW ..................................................................................................................... 66 FIGURE 29: BIG DATA COMPONENTS AND ASSETS IN PILOT 2.3.1 FOREST DAMAGE REMOTE SENSING ....................................... 68 FIGURE 30: TIMELINE OF PILOT 2.3.1, FOREST DAMAGE REMOTE SENSING ........................................................................... 70 FIGURE 31: FORESTRY B1-FH MOTIVATION VIEW ........................................................................................................... 78 FIGURE 32: FORESTRY B1-FH STRATEGY VIEW ................................................................................................................ 79 FIGURE 33: BIG DATA COMPONENTS AND ASSETS IN PILOT 2.3.2-FH: MONITORING OF FOREST HEALTH .................................... 81 FIGURE 34: TIMELINE OF PILOT 2.3.2-FH, MONITORING OF FOREST HEALTH ........................................................................ 83 FIGURE 35: FORESTRY B2-IAS MOTIVATION VIEW .......................................................................................................... 90 FIGURE 36: FORESTRY B2-IAS STRATEGY VIEW ............................................................................................................... 91 FIGURE 37: BIG DATA COMPONENTS AND ASSETS IN PILOT 2.3.2-IAS: INVASIVE ALIEN SPECIES CONTROL AND MONITORING ......... 92 FIGURE 38: TIMELINE OF PILOT 2.3.2-IAS, INVASIVE ALIEN SPECIES CONTROL AND MONITORING .............................................. 94 FIGURE 39: FORESTRY C1 MOTIVATION VIEW ................................................................................................................. 99 FIGURE 40: FORESTRY C1 STRATEGY VIEW ................................................................................................................... 100 FIGURE 41: BIG DATA COMPONENTS AND ASSETS IN PILOT 2.4.1 WEB-MAPPING SERVICE FOR THE GOVERNMENT DECISION MAKING
.................................................................................................................................................................. 101 FIGURE 42: TIMELINE OF PILOT 2.4.1, WEB-MAPPING SERVICE FOR THE GOVERNMENT DECISION MAKING ............................... 103 FIGURE 43: FORESTRY C2 MOTIVATION VIEW ............................................................................................................... 109 FIGURE 44: FORESTRY C2 STRATEGY VIEW ................................................................................................................... 110 FIGURE 45: BIG DATA COMPONENTS AND ASSETS IN PILOT 2.4.2 SHARED MULTIUSER FOREST DATA ENVIRONMENT ................... 111 FIGURE 46: TIMELINE OF PILOT 2.4.2, SHARED MULTIUSER FOREST DATA ENVIRONMENT ...................................................... 114
List of Tables TABLE 1: THE DATABIO CONSORTIUM PARTNERS ............................................................................................................. 10 TABLE 2: ARCHIMATE MOTIVATION AND STRATEGY VIEWS................................................................................................ 15 TABLE 3: ELEMENTS USED IN THE ARCHIMATE MOTIVATION AND STRATEGY VIEWS ................................................................ 16 TABLE 4. PILOTS IN DATABIO WP2 FORESTRY ................................................................................................................ 19 TABLE 5: THE IDENTIFIED STAKEHOLDERS IN EACH PILOT .................................................................................................... 22 TABLE 6: SUMMARY OF PILOT 2.2.1: EASY DATA SHARING AND NETWORKING (ISO JTC1 WG9 USE CASE TEMPLATE) .................. 30 TABLE 7: STAKEHOLDERS AND USER STORIES OF PILOT 2.2.1: EASY DATA SHARING AND NETWORKING ....................................... 32 TABLE 8: EXPLANATION OF SPECIFIC ELEMENTS IN THE FORESTRY A1 FOREST USER STRATEGY VIEW .......................................... 38 TABLE 9: SUMMARY OF PILOT 2.2.2: MONITORING AND CONTROL TOOLS FOR FOREST OWNERS (ISO JTC1 WG9 USE CASE TEMPLATE)
.................................................................................................................................................................... 43 TABLE 10: STAKEHOLDERS AND USER STORIES OF PILOT 2.2.2: MONITORING AND CONTROL TOOLS FOR FOREST OWNERS.............. 46 TABLE 11: SUMMARY OF PILOT 2.3.1 FOREST DAMAGE REMOTE SENSING (ISO JTC1 WG9 USE CASE TEMPLATE) ...................... 58 TABLE 12: STAKEHOLDERS AND USER STORIES OF PILOT 2.3.1 FOREST DAMAGE REMOTE SENSING ........................................... 61
D2.1 – Forestry Pilot Definition H2020 Contract No. 732064 Final – v1.0, 30/6/2017
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TABLE 13: EXPLANATION OF SPECIFIC ELEMENTS IN THE FORESTRY B1 MOTIVATION VIEW ....................................................... 65 TABLE 14: LIST OF THE ELEMENTS DEFINED IN THE FORESTRY B1 STRATEGY VIEW ................................................................... 66 TABLE 15: SUMMARY OF PILOT 2.3.2-FH: MONITORING OF FOREST HEALTH (ISO JTC1 WG9 USE CASE TEMPLATE) ................... 73 TABLE 16: STAKEHOLDERS AND USER STORIES OF PILOT 2.3.2-FH: MONITORING OF FOREST HEALTH ........................................ 76 TABLE 17: EXPLANATION OF SPECIFIC ELEMENTS IN THE FORESTRY B1-FH MOTIVATION VIEW ................................................. 78 TABLE 18: EXPLANATION OF SPECIFIC ELEMENTS IN THE FORESTRY B1-FH STRATEGY VIEW ...................................................... 80 TABLE 19: LISTING OF THE COMPONENTS USED OR PRODUCED IN THE PILOT 2.3.2-FH: MONITORING OF FOREST HEALTH.............. 81 TABLE 20: SUMMARY OF PILOT 2.3.2-IAS: INVASIVE ALIEN SPECIES CONTROL AND MONITORING (ISO JTC1 WG9 USE CASE TEMPLATE)
.................................................................................................................................................................... 85 TABLE 21: STAKEHOLDERS AND USER STORIES OF PILOT 2.3.2-IAS: INVASIVE ALIEN SPECIES CONTROL AND MONITORING ............. 88 TABLE 22: LISTING OF THE COMPONENTS USED OR PRODUCED IN THE PILOT 2.3.2-IAS: INVASIVE ALIEN SPECIES CONTROL AND
MONITORING................................................................................................................................................... 92 TABLE 23: SUMMARY OF PILOT 2.4.1 WEB-MAPPING SERVICE FOR THE GOVERNMENT DECISION MAKING (ISO JTC1 WG9 USE CASE
TEMPLATE)...................................................................................................................................................... 95 TABLE 24: STAKEHOLDERS AND USER STORIES OF PILOT 2.4.1 WEB-MAPPING SERVICE FOR THE GOVERNMENT DECISION MAKING ... 97 TABLE 25: LISTING OF THE COMPONENTS USED OR PRODUCED IN THE PILOT 2.4.1 WEB-MAPPING SERVICE FOR THE GOVERNMENT
DECISION MAKING .......................................................................................................................................... 101 TABLE 26: SUMMARY OF PILOT 2.4.2 SHARED MULTIUSER FOREST DATA ENVIRONMENT (ISO JTC1 WG9 USE CASE TEMPLATE) .. 105 TABLE 27: STAKEHOLDERS AND USER STORIES OF PILOT 2.4.2 SHARED MULTIUSER FOREST DATA ENVIRONMENT ....................... 107 TABLE 28: EXPLANATION OF SPECIFIC ELEMENTS IN THE FORESTRY C2 STRATEGY VIEW ......................................................... 110 TABLE 29: LISTING OF THE COMPONENTS USED OR PRODUCED IN THE PILOT 2.4.2 SHARED MULTIUSER FOREST DATA ENVIRONMENT
.................................................................................................................................................................. 112
D2.1 – Forestry Pilot Definition H2020 Contract No. 732064 Final – v1.0, 30/6/2017
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Definitions, Acronyms and Abbreviations Acronym/
Abbreviation Title
BDVA Big Data Value Association
EO Earth Observation
FMI Forest Management Institute (DataBio partner)
ICT Information and communication technologies
KPI Key Performance Indicator
LIPS Land Parcel Identification System
METSAK Finnish Forest Centre (DataBio partner)
MHGS MHG Systems Oy (DataBio partner)
NIR Near-InfraRed
PPP Public-Private Partnership
RGB Red-Green-Blue
RPAS Remotely Piloted Aerial System
RS Remote Sensing
UAV Unmanned Aerial Vehicle
UI User Interface
VNIR Very Near-InfraRed
VTT VTT Technical Research Centre of Finland Ltd (DataBio partner)
WFS Web Feature Service
WMS Web Map Service
WMTS Web Map Tile Service
WWF World Wildlife Foundation
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Introduction 1.1 Project Summary The data intensive target sector on which the
DataBio project focuses is the Data-Driven
Bioeconomy. DataBio focuses on utilizing Big
Data to contribute to the production of the
best possible raw materials from agriculture,
forestry and fishery (aquaculture) for the
bioeconomy industry, as well as their further
processing into food, energy and
biomaterials, while taking into account various accountability and sustainability issues.
DataBio will deploy state-of-the-art big data technologies and existing partners’ infrastructure
and solutions, linked together through the DataBio Platform. These will aggregate Big Data
from the three identified sectors (agriculture, forestry and fishery), intelligently process them
and allow the three sectors to selectively utilize numerous platform components, according
to their requirements. The execution will be through continuous cooperation of end user and
technology provider companies, bioeconomy and technology research institutes, and
stakeholders from the big data value PPP programme.
DataBio is driven by the development, use and evaluation of a large number of pilots in the
three identified sectors, where associated partners and additional stakeholders are also
involved. The selected pilot concepts will be transformed to pilot implementations utilizing
co-innovative methods and tools. The pilots select and utilize the best suitable market-ready
or almost market-ready ICT, Big Data and Earth Observation methods, technologies, tools and
services to be integrated to the common DataBio Platform.
Based on the pilot results and the new DataBio Platform, new solutions and new business
opportunities are expected to emerge. DataBio will organize a series of trainings and
hackathons to support its uptake and to enable developers outside the consortium to design
and develop new tools, services and applications based on and for the DataBio Platform.
The DataBio consortium is listed in Table 1. For more information about the project see [REF-
01].
Table 1: The DataBio consortium partners
Number Name Short name Country
1 (CO) INTRASOFT INTERNATIONAL SA INTRASOFT Belgium
2 LESPROJEKT SLUZBY SRO LESPRO Czech Republic
3 ZAPADOCESKA UNIVERZITA V PLZNI UWB Czech Republic
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4 FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER
ANGEWANDTEN FORSCHUNG E.V.
Fraunhofer Germany
5 ATOS SPAIN SA ATOS Spain
6 STIFTELSEN SINTEF SINTEF ICT Norway
7 SPACEBEL SA SPACEBEL Belgium
8 VLAAMSE INSTELLING VOOR TECHNOLOGISCH
ONDERZOEK N.V.
VITO Belgium
9 INSTYTUT CHEMII BIOORGANICZNEJ POLSKIEJ
AKADEMII NAUK
PSNC Poland
10 CIAOTECH Srl CiaoT Italy
11 EMPRESA DE TRANSFORMACION AGRARIA SA TRAGSA Spain
12 INSTITUT FUR ANGEWANDTE INFORMATIK (INFAI) EV INFAI Germany
13 NEUROPUBLIC AE PLIROFORIKIS & EPIKOINONION NP Greece
14 Ústav pro hospodářskou úpravu lesů Brandýs nad
Labem
UHUL FMI Czech Republic
15 INNOVATION ENGINEERING SRL InnoE Italy
16 Teknologian tutkimuskeskus VTT Oy VTT Finland
17 SINTEF FISKERI OG HAVBRUK AS SINTEF
Fishery
Norway
18 SUOMEN METSAKESKUS-FINLANDS SKOGSCENTRAL METSAK Finland
19 IBM ISRAEL - SCIENCE AND TECHNOLOGY LTD IBM Israel
20 MHG SYSTEMS OY - MHGS MHGS Finland
21 NB ADVIES BV NB Advies Netherlands
22 CONSIGLIO PER LA RICERCA IN AGRICOLTURA E
L'ANALISI DELL'ECONOMIA AGRARIA
CREA Italy
23 FUNDACION AZTI - AZTI FUNDAZIOA AZTI Spain
24 KINGS BAY AS KingsBay Norway
25 EROS AS Eros Norway
26 ERVIK & SAEVIK AS ESAS Norway
27 LIEGRUPPEN FISKERI AS LiegFi Norway
28 E-GEOS SPA e-geos Italy
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29 DANMARKS TEKNISKE UNIVERSITET DTU Denmark
30 FEDERUNACOMA SRL UNIPERSONALE Federu Italy
31 CSEM CENTRE SUISSE D'ELECTRONIQUE ET DE
MICROTECHNIQUE SA - RECHERCHE ET
DEVELOPPEMENT
CSEM Switzerland
32 UNIVERSITAET ST. GALLEN UStG Switzerland
33 NORGES SILDESALGSLAG SA Sildes Norway
34 EXUS SOFTWARE LTD EXUS United
Kingdom
35 CYBERNETICA AS CYBER Estonia
36 GAIA EPICHEIREIN ANONYMI ETAIREIA PSIFIAKON
YPIRESION
GAIA Greece
37 SOFTEAM Softeam France
38 FUNDACION CITOLIVA, CENTRO DE INNOVACION Y
TECNOLOGIA DEL OLIVAR Y DEL ACEITE
CITOLIVA Spain
39 TERRASIGNA SRL TerraS Romania
40 ETHNIKO KENTRO EREVNAS KAI TECHNOLOGIKIS
ANAPTYXIS
CERTH Greece
41 METEOROLOGICAL AND ENVIRONMENTAL EARTH
OBSERVATION SRL
MEEO Italy
42 ECHEBASTAR FLEET SOCIEDAD LIMITADA ECHEBF Spain
43 NOVAMONT SPA Novam Italy
44 SENOP OY Senop Finland
45 UNIVERSIDAD DEL PAIS VASCO/ EUSKAL HERRIKO
UNIBERTSITATEA
EHU/UPV Spain
46 OPEN GEOSPATIAL CONSORTIUM (EUROPE) LIMITED
LBG
OGCE United
Kingdom
47 ZETOR TRACTORS AS ZETOR Czech Republic
48 COOPERATIVA AGRICOLA CESENATE SOCIETA
COOPERATIVA AGRICOLA
CAC Italy
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1.2 Document Scope This deliverable document D2.1 Forestry Pilot Definition (due M06) specifies the pilot case
definitions, requirement specifications, as well as implementation and evaluation plans.
The specification of KPIs and business models is primarily left for inclusion in WP7
deliverables.
Reporting the results of the pilots is out of the scope of this document, and will instead be
included in D2.2 Forestry Pilots Intermediate Report (M24) and D2.3 Forestry Pilots Final
Report (M36).
1.3 Document Structure
This document is comprised of the following chapters:
Chapter 1 presents an introduction to the project and the document.
Chapter 2 presents the chosen pilot modelling framework and gives an overview on all the
pilots and their associated plans and requirements, making note of the commonalities and
differences between them.
Chapters 3 to 9 give a detailed view on each pilot respectively. Provided first for each pilot
are pilot overview and pilot case definition - including stakeholders, user stories, motivation
and strategy, as well as the scope and limitations. This is followed by a number of selected
outputs from pilot modelling, which is an ongoing work that will be continued and extended
in the context of WP4. Here, the focus is to provide Motivation and Strategy views for each
pilot. Finally, big data related components and assets created or used in the project are
described, followed by pilot evaluation plans and initial roadmaps.
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Summary 2.1 Overview The objective of WP2 Forestry Pilot is to demonstrate through pilots how Big Data will boost
the forestry sector. The pilots, carried out in four countries, are built around practical cases
from forestry. They will validate the use of Big Data technologies and how well the
expectations of user communities are met. In order to do this, the WP will:
● Specify the requirements for the three pilots based on the DataBio platform
● Implement the pilots giving access to all tools developed
● Gather experiences from the pilots
Detailed reports of the design and experiences from the pilots are provided as deliverables.
Big Data technologies will be tested and validated in three main cases: Multisource
crowdsourcing services (Task 2.2), Forest Health (Task 2.3) and Forest Data Management
Services (Task 2.4).
The forest pilots will aim to:
1. Improve identification of forest damages from biotics - such as pest and diseases - or
abiotics - such as snow, thunderstorms (wind), dryness, rains, fires - using remote
sensors.
2. Optimize the use of tree resources: Detailed characterization of trees through e.g.
airborne laser scanning (knottiness, carvery) for determining the optimal use of trees
for a given output, e.g. pulp, paper, textile, biofuels, etc., in order to guarantee that
supply meets demand.
3. Provide forest health maps to forest owners or public administrators, based on
remote sensing data. Later on, maps of implemented cuttings will be provided for
verification and reforestation control.
Integrated tools are developed and new management plans are implemented that take into
account non-wood products and conservation areas while at the same time maximising
timber production and economic yield.
In most European countries, traditional methods for forest management are based on “static”
management plans, created at the planting stage and reviewed every 10 years. In recent
years, these management plans have become a declaration of intentions, including objectives
for multifunctional forests (non-wood products and services). However, these plans often lack
effective implementation and monitoring methods that allow forest owners, managers and
regulators to validate the progress in achieving the target objectives set out in the
management plan.
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2.2 Pilot modelling framework The pilot cases are modelled using the ArchiMate 3.0 modelling framework. Figure 1
summarizes the overall ArchiMate 3.0 framework. The figure also depicts the input provided
by the domain WPs (WP1, WP2, WP3 and their pilots) and that provided by the technology
WPs (WP4, WP5), which will be correlated in the next stages of modelling process.
Figure 1: ArchiMate 3.0 modelling framework.
The modelling presented in this deliverable focuses on the “Motivation” and “Strategy” views.
The “Motivation” view models the reasons that guide the design of the architecture. The
“Strategy” view adds how the course of action is realized. Table 2 provides an extended
description of the two views. After the completion of this deliverable, the plan is to extend
the modelling with other views, while investigating the correlations with the technology WP
input.
Table 2: ArchiMate Motivation and Strategy views.
View name Description
Motivation
view
Motivation elements are used to model the motivations, or reasons, that guide the
design or change of an Enterprise Architecture. It is essential to understand the
factors, often referred to as drivers, which influence other motivation elements.
They can originate from either inside or outside the enterprise. Internal drivers, also
called concerns, are associated with stakeholders, which can be some individual
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human being or some group of human beings, such as a project team, enterprise, or
society. Examples of such internal drivers are customer satisfaction, compliance to
legislation, or profitability.
Strategy
view
The immediate decision support system is built on top of a data collection and
distribution system. The data collection and distribution system is used to collect
sensor data from the on-board systems and makes them available in a single system.
The data distribution system ensures that the decision support system only interface
with a single system, instead of multiple sensors. The decision support system
presents the data from the data distribution system and collect them in an internal
storage system for presentation of current performance vs. historic performance.
The main elements used in the above views are explained in Table 3. Their relationships are
shown in Figure 2 and Figure 3. For further information see [REF-02].
Table 3: Elements used in the ArchiMate Motivation and Strategy views
Element Definition Notation
Stakeholder The role of an individual, team,
or organization (or classes
thereof) that represents their
interests in the outcome of the
architecture.
Driver An external or internal condition
that motivates an organization
to define its goals and
implement the changes
necessary to achieve them.
Assessment The result of an analysis of the
state of affairs of the enterprise
with respect to some driver.
Goal A high-level statement of intent,
direction, or desired end state
for an organization and its
stakeholders.
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Outcome An end result that has been
achieved.
Principle A qualitative statement of intent
that should be met by the
architecture.
Requirement A statement of need that must
be met by the architecture.
Constraint A factor that prevents or
obstructs the realization of
goals.
Meaning The knowledge or expertise
present in, or the interpretation
given to, a core element in a
particular context.
Value The relative worth, utility, or
importance of a core element or
an outcome.
Resource An asset owned or controlled by
an individual or organization.
Capability An ability that an active
structure element, such as an
organization, person, or system,
possesses.
Course of
action
An approach or plan for
configuring some capabilities
and resources of the enterprise,
undertaken to achieve a goal.
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Figure 2: Relationships of the Motivation elements
Figure 3: Relationships of the Strategy elements
2.3 Pilot introductions Within the three overall cases outlined above - Multisource crowdsourcing services, Forest
Health and Forest Data Management Services - the work is arranged into seven pilots. The full
pilot descriptions and plans are given in chapters 3 to 9 of this document. Below is a summary
table, giving also linking between the pilot IDs and the chapters in this document. The table
is followed by a brief introduction of each pilot.
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Table 4. Pilots in DataBio WP2 Forestry
Pilot ID Pilot title Pilot leader Project partners D2.1 chapter
2.2.1 Easy data sharing and networking MHGS VTT, SPACEBEL, METSAK
3
2.2.2 Monitoring and control tools for forest owners
MHGS FMI, TRAGSA, METSAK
4
2.3.1
Forest damage remote sensing MHGS VTT, SENOP, METSAK, SPACEBEL
5
2.3.2-FH
Monitoring of forest health TRAGSA SENOP, CSEM, CiaoT, FMI, VTT
6
2.3.2-IAS Invasive alien species control and monitoring
TRAGSA SENOP, CSEM, CiaoT, FMI, VTT
7
2.4.1 Web-mapping service for the government decision making
FMI VTT, SPACEBEL 8
2.4.2 Shared multiuser forest data environment
METSAK VTT 9
Pilot 2.2.1 - Easy data sharing and networking - aims to develop and pilot standardized
procedures for collecting and transferring data utilizing the Wuudis Service and DataBio
platform from silvicultural activities executed in the forest. Wuudis, developed by MHGS, is a
commercial service for forest owners, timber buyers and forestry service companies for
management of forestry activities and forest resource management. The goal is to develop
and validate Wuudis’ collaboration features, quality monitoring and social forest platform
features in selected pilot areas. In addition, one important goal is also to integrate the Wuudis
Service to external services such as map services and authority systems. In Finland, there are
two estates selected for this pilot, called Rangunkorven yhteismetsä and Taipale.
Pilot 2.2.2 - Monitoring and control tools for forest owners - aims to develop standardized
procedures and apps for collecting, monitoring and transferring data utilizing the Wuudis
Service and the DataBio platform, to be exported to 3rd party IT systems through standard
interfaces. In this pilot, an end-to-end data transfer solution will be developed between the
Wuudis Service and METSAK´s metsaan.fi eService. Forest damage (like storms, snow, pests,
insects, fungi) monitoring through standardized procedures will be developed together with
METSAK as well as easy-to-use mobile tools for these damage monitoring needs and non-
wood product monitoring needs.
Pilot 2.3.1 - Forest damage remote sensing - aims to develop a Forest Inventory system on
the Wuudis Service based on remote sensing (satellite, aerial, UAV) and field surveys. Selected
Big Data partners will integrate their existing market-ready or almost market-ready
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technologies onto the Wuudis Service, and the resulted solutions are piloted with Wuudis
users, forestry sector partners, associated partners and other stakeholders. The pilot will
develop a comprehensive and near real-time quantitative assessment of forest cover, forest
aboveground carbon stock and carbon stock change over the project pilot area (Rangunkorpi
cooperative forestry). This allows detecting and measuring damages, deforestation and forest
degradation, which is a major cause of loss of biomass and carbon stores.
Pilot 2.3.2-FH - Monitoring of forest health - aims to set up a methodology based on remote
sensing images (satellite + aerial + UAV) and field data for the monitoring of the health status
of forests in large areas of the Iberian Peninsula. The work will focus, particularly, in the
monitoring of the health of Quercus sp. forests affected by the fungus Phytophthora
cinnamomi Rands and of the damage in eucalyptus plantations affected by the coleoptera
Gonipterus scutellatus Gyllenhal. EO-based solutions will provide Public Bodies with valuable
information and tools to help decision making. An EO-based system for monitoring the health
of big forest areas will be set up (mapping + assessment tools), so Authorities will be able to
optimise forest management resources. A mapping and assessment tool will be developed
for monitoring the damages caused by Gonipterus in eucalyptus plantations, as well as for
damage assessment, in order to adapt management and minimise economic losses.
Pilot 2.3.2-IAS - Invasive alien species control and monitoring - aims to develop a simple
model for assessing invasion risk in Spain based on a set of factors that strongly influence the
geographic pattern and level of invasion: 1) Environmental similarity, calculated from
bioclimatic variables; 2) Biodiversity similarity, approached through biogeographic
information; 3) Propagule pressure, estimated from data on trade, tourism, immigration,
population and terrestrial transport network; and 4) Ecosystem disturbance, measured from
land use and fire frequency. The pilot case is linked to prevention, which is both an effective
and efficient way of dealing with the problem of biological invasions. Indeed, the pilot will
identify the areas in Spain at greatest risk of invasion and the most likely source regions of
IAS, thus providing crucial information for resource prioritization and for a much better
management of these species.
Pilot 2.4.1 - Web-mapping service for the government decision making - aims to develop a
new methodology for forest health assessment based on Copernicus satellite data. This allows
assessing the forest health of the entire area of Czech Republic and other temperate forest
regions in Europe, while reducing costs for field surveys and highly effective identification of
forest owners eligible for subsidies / tax relief. This pilot focuses on technological
development of the processing of Sentinel-2 optical data. Utilizing the great potential of high-
spatial and temporal resolution satellite data for forestry, with special focus on forest health
trends is the main goal of the pilot. In addition, the forest owners will benefit from publicly
available map server and implementation of the layers on the Wuudis platform, where all
forest health status maps will be published to allow pro-active management of their forest
properties.
Pilot 2.4.2 - Shared multiuser forest data environment - aims to pilot presenting
crowdsourced forest data and possible new functionalities related to it in Metsään.fi eService
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and therefore enhance the use of Metsään.fi and METSAK’s forest resource data. Metsään.fi
is an eService provided by the governmental body, the Finnish Forest Centre (METSAK), to
make forest resource information available for citizens free of charge. Metsään.fi eService is
constantly developed by METSAK. The collecting methods are also aimed to increase the
amount of METSAK’s forest resource data. The plan is to pilot presenting crowdsourced forest
data and possible new functionalities related to it in Metsään.fi eService and therefore
enhance the use of Metsään.fi and METSAK’s forest resource data.
2.3.1 Wuudis
Several of the pilots are linked with the Wuudis platform and services by MHGS. The Wuudis
Service developed by MHGS is a unique commercial service on the market for forest owners,
timber buyers and forestry service companies. It enables the management of forestry
activities and forest resource management through a single tool. The cloud-based platform,
with a mobile interface and data in XML and JSON formats, connects forest owners directly
with local contractors and timber buyers. With it, forest owners and other stakeholders can
effectively manage their forest resources remotely in real-time. It can be used to obtain real-
time information about the forest and its timber resource, track executed silvicultural and
harvest activities, plan the needed forest management activities, and bid for care works and
timber sales online.
The Wuudis Networking feature allows users to create a group inside the Wuudis Service and
share forestry information flawlessly with the people of choice. The user can define a different
level of access for each user, for example a view-only access or an access to do both viewing
and editing. Access to the information increases the transparency and effect of mutual
decision-making, for example in timberland investment companies.
The Wuudis Monitoring feature allows users to collect various data including non-wood
products and to monitor any changes in the forest on the Wuudis Service and share this
information flawlessly with the people of choice. The user can define a different level of
access for each user, for example the view-only access or the access to do both. Access to the
realtime information - situation view - improves real time guidance, for example for
harvesting operations in high biodiversity sites, while decreasing risks for operational
damages due to miscommunication. It also improves bidding through marketplaces, for
example for care works or harvesting operations, in particular after storm damage occurred,
enabling faster and more organized exploitation operations than at present.
2.4 Pilot case definitions The pilot case definitions in the respective chapters of this deliverable include identification
of stakeholders, their goals and expected benefits (sections X.2.1), as well as explanation of
pilot motivation and strategy (sections X.2.2). These form the requirement specifications for
the pilot and are used in subsequent sections in pilot modelling. Finally, the scope and
limitations of each pilot are given (sections X.2.3). The identified stakeholders in each pilot
are listed in the below table.
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Table 5: The identified stakeholders in each pilot
Pilot ID Pilot title Stakeholders
2.2.1 Easy data sharing and networking Forest owner Forestry contractor Timber buyer Forest authority expert
2.2.2 Monitoring and control tools for forest owners
Forest owner Forestry contractor Timber buyer Forest authority expert Forest insurance company MHGS service provider
2.3.1
Forest damage remote sensing Forest owner Forestry contractor Timber buyer Forest authority expert Forest insurance company MHGS service provider
2.3.2-FH
Monitoring of forest health End user (Junta de Extremadura) End user (Xunta de Galicia) End user (Public Administrations) TRAGSA Technician Generic user
2.3.2-IAS Invasive alien species control and monitoring
End user (MAPAMA-Policy Makers)
End user (Public Administrations)
TRAGSA Technician Generic user
2.4.1 Web-mapping service for the government decision making
Ministry of Agriculture of the Czech Republic Local forest owners, including Forests of the Czech Republic and Wallonia
2.4.2 Shared multiuser forest data environment
Forest owner Forestry operator METSAK user
2.5 Big data assets For each pilot described in chapters 3 to 9, section X.4 introduces the usage and development
of Big Data assets and components, via a supporting figure that is based on a reference
classification developed by the Big Data Value Association (BDVA). For most pilots, it has been
possible at this stage to take the presentation to the level of identifying the type of assets
used or developed in various layers. On a number of the pilots it has been possible already to
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uniquely name each component. In all cases, the presentation gives the best estimate at this
point in pilot preparation.
2.6 Evaluation plans The evaluation plans for each pilot are given in sections X.5 in chapters 3 to 9. These are
presented as lists of identified Key Performance Indicators (KPIs) that will be used in
evaluation of the results of each pilot. Depending on how advanced the discussions are with
the external stakeholders, the KPIs are presented either with target values or with more
general descriptions.
2.7 Implementation plans The implementation plans with the actions and schedule for each pilot are given in sections
X.6 (Initial roadmap) in Chapters 3 to 9. The schedules are designed to align with both the
project overall schedule and the development plans of external associated partners and
stakeholders in each pilot.
Timeline figures regarding each pilot are presented jointly below.
Figure 4: Timeline of pilot 2.2.1, Easy data sharing and networking
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Figure 5: Timeline of pilot 2.2.2, Monitoring and control tools for forest owners
Figure 6: Timeline of pilot 2.3.1, Forest damage remote sensing
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Figure 7: Timeline of pilot 2.3.2-FH, Monitoring of forest health
Figure 8: Timeline of pilot 2.3.2-IAS, Invasive alien species control and monitoring
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Figure 9: Timeline of pilot 2.4.1, Web-mapping service for the government decision making
Figure 10: Timeline of pilot 2.4.2, Shared multiuser forest data environment
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Pilot 2.2.1: Easy data sharing and networking 3.1 Pilot overview
3.1.1 Pilot introduction
This pilot aims to develop and pilot standardized procedures for collecting and transferring
data utilizing the Wuudis Service and DataBio platform from silvicultural activities executed
in the forest. The Wuudis Service and the Wuudis Networking features are applied in the pilot;
see section 2.3.1 for explanation on these.
Data sharing and a collaborative environment enables improved tools for sustainable forest
management decisions and operations. Data becomes accessible to forest owners and other
end users interfacing with market place, e-contracting, online purchase and sales of timber
and biomass. Higher data volumes and better data accessibility increase the probability that
the data will be updated and maintained.
In the DataBio project, selected Big Data partners will integrate their existing market-ready
or almost market-ready technologies onto the Wuudis Service, and the resulted solutions will
be piloted with the Wuudis users, forestry sector partners, as well as associated partners and
other stakeholders, e.g. NGOs related to nature conservation. This integration also applies to
the pilot 2.4.2 Shared multiuser forest data environment in WP2.
This pilot is developed in Task 2.2.1 Easy data sharing and networking and the task 2.4.2
Shared multiuser forest data environment, in the context of the WP2 Forestry pilot. The
involved partners are: MHGS, VTT, SPACEBEL and METSAK.
3.1.2 Pilot overview
All current real estate data is integrated from METSAK´s metsaan.fi eService to the Wuudis
platform for DataBio pilots. Data is transferred via the Finnish forestry standard XML format.
This initial forestry data is very crucial for the pilot because every update will affect the initial
data directly. Modified and updated data should also go back to the authorities via integration
interfaces. In this pilot, the Wuudis Service will work as a data sharing platform between
authorities and end users providing mobility and data modification tools for the users.
We develop and use a work quality monitoring app (available for Microsoft, iOS and Android
mobile platforms) in order to feed the forest inventory master data in real time operations
into the METSAK´s databases, metsaan.fi and METSAK’s forest resource data. High quality
updates are provided for strategic planning through the Wuudis platform and for paying
subsidies for cleaning and treating young seedling and young forest stands in a controlled way
by METSAK. The collecting methods are aimed to improve work quality and customer
satisfaction, and increase competition between contractors resulting in decreasing care work
costs paid by forest owners.
The goal is to develop and validate Wuudis’ collaboration features, quality monitoring and
social forest platform features in selected pilot areas. In addition, one important goal is also
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to integrate the Wuudis Service to external services such as map services and authority
systems. In Finland, there are two estates selected for this pilot, called “Rangunkorven
yhteismetsä” and “Taipale”, both located in Central Finland.
Figure 11: Pilot estate forestry data transferred into Wuudis from the forestry authority system (metsaan.fi)
This pilot specifies the requirements for refining and showing the crowdsourced forest data
to metsaan.fi users. The implementation of the new functionalities will be carried out in
collaboration with the Metsään.fi development team and other METSAK's projects. This pilot
gives specifications to other projects and follows up the implementation according to these
specifications in Czech Republic and Belgium by WP2 partners (FMI and SPACEBEL
respectively), which will be specified at a later stage.
To summarize, the following improvements will be developed for the Wuudis Service:
1. Development of data sharing features for more flexible data sharing
2. Development of more flexible collaboration features
3. Development of the Wuudis mobile app to enable work quality monitoring in a
standardized way (sample plots “kemera”)
The work quality monitoring data consists of the following information: forest estate,
geometry of compartments, type of the forest work, sample plot locations, measured data
per sample plot, measurement averages per compartment, measurement date and user
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information. The quality control data will be added to the existing forest data standard during
2017.
4. Development of a feature that allows the user to decide what data he/she wants to
send back to the authority.
5. Development of an interface to the authority system (for example metsaan.fi), which
requires a strong user identification. Other requirements need to be defined during
the pilot.
6. Send quality data back to the authority system.
7. Development of sharing features to the existent market places if needed.
8. Specify all data sources and formats that are needed to accomplish all user
requirements (maps, reports, tables, etc.).
9. Execution of all integrations that are specified.
Figure 12: Data sharing in Wuudis
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Table 6: Summary of pilot 2.2.1: Easy data sharing and networking (ISO JTC1 WG9 use case
template)
Use case title Easy data sharing and networking
Vertical (area) Forestry
Author/company/email Seppo Huurinainen & Veli-Matti Plosila / MHGS [email protected] [email protected]
Actors/stakeholders and their roles and
responsibilities
Forest owners and forestry operators as Wuudis Service users. The Wuudis (MHGS) admin users who use and refine the forest resource data and make it available for Wuudis users.
Goals To increase the use of Wuudis freemium and commercial Services and in parallel use METSAK’s forest resource data.
Use case description Specifying the requirements for new information and functionalities of Metsään.fi’s eService and implementing them in collaboration with the Metsään.fi development team and other METSAK projects. Developing a work quality monitoring app (MS, IoS, Android), further developing networking features for the Wuudis service to facilitate easy and real-time communication.
Current solutions
Compute(System) MHGS´s internal systems related to forest resource data.
Storage Databases for MHGS’s internal forest resource data and map systems, for publishing forest resource data for Wuudis and Metsään.fi.
Networking Web based and mobile solution for Wuudis and Metsään.fi users
Software Wuudis service
Big data characteristics
Data source (distributed/centralized)
Mobile data service, modern smartphone/tablet, web browser, open API to the authority and 3rd party systems
Volume (size) Scalable through international service provider
Velocity (e.g. real time)
Real time updates from field measurements, quality control, forest owners’ forest management plans and other notifications from forest owners, forestry operators and other stakeholders
Variety (multiple datasets,
mashup)
Multiple datasets: tree stand basic data, tree stand strata, growth place (site quality)
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Variability (rate of change) Same as above (velocity).
Big data science (collection, curation,
analysis, action)
Veracity (Robustness Issues, semantics)
The data source must be saved within the forest resource data (e.g. data from forest owner vs. measured and analyzed data)
Visualization The user interface is the existing Wuudis Service and its map views. For MHGS admin users there are also existing internal systems with which the data is browsed and handled.
Data quality (syntax) Collected forest operative and quality data must be consistent with the specific standards.
Data types Tree stand basic data, tree stand strata data, growth place data (site quality), location data, time and user stamps.
Data analytics National averages of work quality.
Big data specific challenges (Gaps)
To balance between data publicity and privacy; To adapt to the new Finnish Forest Act being revised at the moment; To take into account the users of the Wuudis service, public authorities’ and Metsään.fi eService user needs.
Big data specific challenges in bio-
economy
To maintain the consistency of data and the usability of new data, functionalities and services from the Wuudis service users’ point of view to better support clients´ forests and their related business development and decision-making, and therefore bio-economy.
Security and privacy technical considerations
There are both public and private data in the Wuudis Service. Personal and forest estate specific information are private. National Forest Acts set demands on data publicity and privacy issues.
Highlight issues for generalizing this Use case (e.g. for ref. architecture)
Using data standards in the interfaces. Visualizing complex data in a logical and understandable way.
More information (URLs) https://www.databio.eu/en/
Notes: - Spacebel: The Wuudis service will be integrated in the EO Regions! multi-thematic EO
services platform in Wallonia.The forestry services developed in the framework of the EUGENIUS projects will reciprocally be integrated in the Wuudis service for the Finnish market.
- MHGS: Development of features for strategic planning in order to promote forest property management and timber sales (automated alarms, request for automated bidding, group sales etc.)
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3.2 Pilot case definition
3.2.1 Stakeholders and user stories
Table 7: Stakeholders and user stories of pilot 2.2.1: Easy data sharing and networking
Who I want to Why
Forest
owner
I want to report care works (with pictures,
video & positioning) easily with mobile
application
I want to get quality reports from my
contractor
I want that work quality reports and work
integrate with the authority central
database
I want to get real time information from
the contractor
I want to share my forest estate data to
contractors easily
I want the service to offer me guidance
To prove to METSAK, who is paying the
subsidies, that the job was done
according to guidelines and
recommendations
To see and control what happens in my
forest
To be sure that information from my
forest is accurate for growth
simulations
To maintain my forest data updated,
and to follow and evaluate the quality
of work of the contractor I have made
contract with
For the contractor to easily find the site
and understands what to do there
To follow harvesting and care works
time frame to maximize my incomes,
minimize costs and control significant
vegetation changes, such as clear-cuts
and forest damage areas to act in time
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Forestry
contractor
I want to easily share and report forest
estate data with the forest owner
I want to receive forest data
I want to get more deals doing business
directly with forest owners
I want to make winning offers for group
offer requests
I want to network with my subcontractors
I want to know if, where and when
significant vegetation changes, such as
damages, occur in the forests I’m working
on
I want to know what are the major tree
species in the forests I’m working on and
where they are
To provide a superior customer service
to my clients
To receive conveniently the forest data
to my standard interface, smart phone
or tablet
For better profit and less work
without principals and middle men
To win deals thanks to precise data
available for cost analysis
To outsource part of my deals by
networking smoothly with my
subcontractors
To be ready to act as soon as possible to
win deals in any business environment
To focus on the most profitable sites
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Timber
buyer
Forest
authority
expert
I want to receive forest data easily to my
smart phone or tablet
I want that my contractors do work quality
controls
I want to get more matching deals for my
purchase targets
I want that work quality reports are
reliable and integrate automatically with
the central authority database
I want to report work quality inspections
easily and in a reliable manner through
mobile application
I want to know when and where significant
vegetation changes, such as clear-cuts,
occur
To receive conveniently the forest data
to my standard interface, smart phone
or tablet
For customer satisfaction, it is
important to report to forest owners
and my supervisors. In addition, the
reporting method must interface with
our IT system
To close deals with fewer expenses by
understanding better in
site/compartment level available tree
species and assortments etc.
To develop and implement new
business practices with minimum
paperwork to become more cost
efficient
For simple and compatible solutions
everyone is ready to learn and use
To use my standard interface, smart
phone, as a reporting tool because I
take care of daily routines like banking
through apps
It is of utmost importance to act as soon
as possible if something unusual
happens in the forest in order to
prevent additional damages while
ensuring e.g. harvesting operations
3.2.2 Motivation and strategy
New features will be delivered/deployed continuously. All new bigger features are split into
small parts to enable fast deployment and testing cycles. The most important thing is to
prioritize and understand these development requirements correctly first.
After the developed features are tested by the development team and deployed to the
production environment, these features are ready for the DataBio pilot case to be tested in
practical operations by committed Wuudis users, associate partners and other possible
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Wuudis users (Kemera work quality documentation service). In Wallonia, Belgium, the
integration of the Wuudis service with EO Regions! will be planned and executed together
with SPACEBEL and its network.
The key advantage is that forest contractors can better respond to forest owners and
authority expectations about work quality concerning subsidy payments by METSAK. Forest
owners are able to follow the quality of care work in their forests and in the meantime get
real time updates for their forest management plan. METSAK will save tax payers´ money
because field inspections will not be needed any more thanks to reliable e-reporting by
contractors and forest owners.
Wuudis users are able to update the forest resource data not only to the Wuudis Service but
to the Metsään.fi eService too, thus providing better customer service and satisfaction than
competitor solutions. This should bring more paying customers to MHGS, being the first
service provider with such a complete service package from forest to authority database.
3.2.3 Scope and limitations
This pilot operates in an existing service environment of MHGS producing new data and
functionalities related to the Wuudis Service. The pilot scope is to:
- develop a work quality monitoring app seamlessly interfacing with METSAK´s
metsään.fi eService
- test the app in the field operations with associate partners and other stakeholders
The limitations in this pilot may be caused by:
- Operating in METSAK’s system environment and its development: this sets both
content and schedule limitations when specifying and testing changes in Metsään.fi.
- The forest data standard: all the forest data interfaces must be consistent with the
forest data standard.
3.3 Pilot modelling with ArchiMate In this pilot, there is an existing technical environment of the Wuudis Service. Any data
modelling or architecture design is done by MHGS´s internal Wuudis development team. Pilot
modelling in this section is therefore applicable to a limited extent only.
This section presents the "Forestry A1 Easy data sharing and networking modelling with
ArchiMate" view point described using the ArchiMate standard.
3.3.1 DataBio forestry pilot 2.2.1 motivation view
Figure 13 describes the "Forestry A1 Motivation view" defined in the "Forestry A1 Easy data
sharing and networking modelling with ArchiMate" view point.
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Figure 13: Forestry A1 Motivation view
Figure 14 below is the "Forestry A1 Forest User Motivation view" defined in the "Forestry A1
Easy data sharing and networking modelling with ArchiMate" view point.
Figure 14: Forestry A1 Forest User Motivation view
The goal “Prove conformance to recommendation and guidelines” is further explained with
this description: “Prove to myself and to METSAK who is paying subsidies that the job was
done according to guidelines and recommendations.”
3.3.2 DataBio forestry pilot 2.2.1 strategy view
Figure 15 describes the "Forestry A1 Strategy view" defined in the "Forestry A1 Easy data
sharing and networking modelling with ArchiMate" view point.
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Figure 15: Forestry A1 Strategy view
Figure 16 below is the "Forestry A1 Forest User Strategy view" defined in the "Forestry A1
Easy data sharing and networking modelling with ArchiMate" view point. Table 8 provides
further explanations to a number of the view's elements.
Figure 16: Forestry A1 Forest User Strategy view
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Table 8: Explanation of specific elements in the Forestry A1 Forest User Strategy view
Name Description
Action: Integrate work and its quality
reports with authority central database
Get quality reports from my contractor
Action: Report care works Report care works (with pictures, video & positioning)
easily with mobile application
Goal: Prove conformance to
recommendations and guidelines
Prove to myself and to METSAK who is paying subsidies
that the job was done according to guidelines and
recommendations
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3.4 Big Data infrastructure: Components and BDVA classification The existing technical environment of the Wuudis Service concerning big data components
and assets is described in Figure 17 below. This pilot is about further development of the
Wuudis Service features in order to better serve all its customers and partner groups: forest
owners, contractors, timber buyers and authorities.
Figure 17: Big data components and assets in pilot 2.2.1: Easy data sharing and networking
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3.5 Pilot evaluation plan
3.5.1 High level goals and KPIs
There are several KPIs for this pilot to evaluate the results yearly and in the end of the project.
Perhaps the most logical approach to evaluate these innovations is through real customer use
cases in forestry operations. These will be identified, specified and agreed with piloting clients
in business practicalities during the project.
The KPIs identified for this pilot include:
● %Increase in contract work productivity following the e-tools available/developed
vs. what would be the time spent following standard contracting practices based on
paper documents and paper maps
○ Quantify %increase in productivity for example for young seedling stand
cleaning (contractor and authority).
● %Decrease in operational costs for performing the same contracting activities
(through accurate site information and better management of resources) following
the e-tools available/developed vs. what would be the revenue (per hour) following
standard practices based on data on paper form
○ Quantify %Decrease in operational costs for example for young seedling
stand cleaning (contractor and authority).
● %Increase customer satisfaction following the networking e-tools
available/developed vs. what would be the satisfaction following standard
communication practices based on contractor's present practicalities (phone, SMS,
work quality report if any)
○ Quantify %increase in satisfaction for example for young seedling stand
cleaning work quality reporting (contractor and forest owner).
The amount of forest owners and other users as Wuudis Service users is now around 2 700.
The amount is expected to increase as follows: 5 000 in the end of 2017, 10 000 in the end of
2018 and 50 000 in the end of 2019.
The final KPIs will be specified with associate partners and other stakeholders based on
selected study cases.
3.6 Initial roadmap The Wuudis Service roadmap and implementation plan for this pilot is as follows:
1. Wuudis mobile app development: Work quality monitoring
2. Development of data sharing and collaboration features to become more flexible
3. Export work quality data in standard XML format
4. Interface/integration development with the metsaan.fi service
5. Evaluate developed features with real end users (like associate partners and other
Wuudis users)
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All forest resource data from the Wuudis Service is saved in a centralized forest resource data
system. The Wuudis Service uses that data through a publishing database and other existing
interfaces.
The app will be developed, implemented and integrated with Metsään.fi eService in Q4/2017.
The implementation and further development schedule described in Figure 18 is partially
dependent on the schedule of Metsään.fi’s development plans.
Figure 18: Timeline of pilot 2.2.1, Easy data sharing and networking
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Pilot 2.2.2: Monitoring and control tools for
forest owners 4.1 Pilot overview
4.1.1 Pilot introduction
This pilot aims to develop standardized procedures and apps for forest owners for collecting,
monitoring and transferring data utilizing the Wuudis Service and the DataBio platform. The
Wuudis Monitoring feature is applied in the pilot; see section 2.3.1 for introduction on
Wuudis. This data can be exported to third party IT systems through standard interfaces. In
this pilot, an end-to-end data transfer solution will be developed between the Wuudis Service
and METSAK´s metsaan.fi eService.
In the DataBio project, selected Big Data partners will integrate their existing market-ready
or almost market-ready technologies onto the Wuudis Service and the resulted solutions will
be piloted with the Wuudis users, forestry sector partners, associated partners and other
stakeholders such as NGOs and authorities related to nature conservation. This integration
also applies to the pilot 2.4.2: Shared multiuser forest data environment in WP2.
This pilot is developed in Task 2.2.2 Monitoring and control tools for forest owners, under
WP2 Forestry pilot and Task 2.2 Multisource and data crowdsourcing /e-services. The involved
partners are MHGS, FMI, METSAK and TRAGSA.
4.1.2 Pilot overview
Forest damage (such as storms, snow, pests and diseases) monitoring through standardized
procedures will be developed together with METSAK, as well as easy-to-use mobile tools for
these damage monitoring needs and non-wood product monitoring needs. Finally, the data
will be integrated with METSAK´s metsaan.fi eService. This allows forest owners and forest
specialists willing to monitor and report forest damage information to authorities a direct
access to metsaan.fi’s master database.
The Finnish Forest Centre will launch a campaign in 2017 targeted at private forest owners
and forest specialists to collect and report observations from forest damages through the
Wuudis app seamlessly interfacing with metsaan.fi’s eService. Similar monitoring service will
be implemented and tested in Czech Republic in the third year of the DataBio project with
FMI.
WWF Finland and numerous private forest owners strive to manage their forests favouring
multiple use and high biodiversity values. WWF Finland has an ongoing campaign targeted at
private forest owners to collect data from high nature value sites and other important flora
and fauna that forest owners want to preserve in coming care work activities and harvesting
operations. This campaign, called “Forest Challenge”, aims to secure biodiversity of forest
nature. WWF has launched a guidebook to illustrate measures to preserve biodiversity. All
contracting and timber buying committed to the challenge promise to respect the measures
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described in the guidebook of WWF Finland. In this pilot, a database and communication
procedure will be further developed on the Wuudis Service for supporting Forest Challenge´s
objectives together with WWF Finland pilot users.
Table 9: Summary of pilot 2.2.2: Monitoring and control tools for forest owners (ISO JTC1 WG9 use case template)
Use case title Monitoring and control tools for forest owners
Vertical (area) Forestry
Author/company/email Seppo Huurinainen & Veli-Matti Plosila / MHGS [email protected] [email protected]
Actors/stakeholders and their roles and
responsibilities
Forest owners and forestry operators as Wuudis Service users. The Wuudis (MHGS) admin users who use and refine the forest resource data and make it available for Wuudis users.
Goals To increase the use of Wuudis freemium and commercial Services and in parallel the use of METSAK’s forest resource data.
Use case description Specifying the requirements for forest damage data and non-wood data collection through Wuudis apps to Metsään.fi’s eService and implementing them in collaboration with Metsään.fi’s development team and other METSAK projects. Developing forest damage and non-wood monitoring app (Microsoft, iOS, Android mobile platforms), further developing networking features for the Wuudis service in order to interface with marketplaces.
Current solutions
Compute(System) MHGS´s internal systems related to forest resource data.
Storage Databases for MHGS’s internal forest resource data and map systems, for publishing forest resource data for Wuudis and Metsään.fi.
Networking Web based and mobile solution for Wuudis and Metsään.fi users
Software Wuudis service
Big data characteristics
Data source (distributed/centralized)
Mobile data service, modern smart phone/tablet, web browser, open API to the authority and 3rd party systems
Volume (size) Scalable through international service provider
Velocity (e.g. real time)
Real time updates from field measurements, quality control, forest owner’s forest management plans and other notifications from forest owners
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and forestry operators and other stakeholders
Variety (multiple datasets,
mashup)
Multiple datasets: tree stand basic data, tree stand strata, growth place (site quality)
Variability (rate of change) Same as above (velocity).
Big data science (collection, curation,
analysis, action)
Veracity (Robustness Issues, semantics)
The data source must be saved within the forest resource data (e.g. data from forest owner vs. measured and analyzed data)
Visualization The user interface is the existing Wuudis Service and its map views. For MHGS admin users there are also existing internal systems with which the data is browsed and handled.
Data quality (syntax) Collected forest damage and non-wood product data must be consistent with the specific standards.
Data types Tree stand basic data and strata data, growth place data (site quality), location data, time and user stamps.
Data analytics
Big data specific challenges (Gaps)
To balance between data publicity and privacy, to adapt to the new Finnish Forest Act being revised at the moment and to take into account Wuudis service users, public authorities’ and Metsään.fi’s eService user needs.
Big data specific challenges in bio-
economy
To maintain the consistency of data and the usability of new data, functionalities and services from the Wuudis service user point of view to support better clients´ forest related business development and decision making, and therefore bio-economy.
Security and privacy technical considerations
There are both public and private data in the Wuudis Service. Personal and forest estate specific information are private. National Forest Acts set demands on data publicity and privacy issues.
Highlight issues for generalizing this Use case (e.g. for ref. architecture)
Using data standards in the interfaces. Visualizing complex data in a logical and understandable way.
More information (URLs) https://www.databio.eu/en/
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4.2 Pilot case definition
4.2.1 Stakeholders and user stories
This pilot aims to solve the following needs/problems as a Wuudis user:
1. Share data/information and communicate easily between different stakeholders
with mobile and web application.
2. Different kinds of forest damages will be monitored in real time operations through
a mobile application to be defined and built up.
3. Forest owners are able to monitor different kinds of damage and share the data with
authorities/forest experts for consultation and reporting through a mobile app.
4. Service providers/contractors/timber buyers are able to monitor different kind of
damages and share the data with authorities/forest experts for consultation and
reporting through a web service.
5. All monitoring data has to be integrated with the authority databases through
standardized procedures. A specific standard for forest damage monitoring will be
developed in the pilot.
6. Forest authority experts are able to use a specific app for biodiversity monitoring
(instead of paper sheets or user-unfriendly solutions).
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Table 10: Stakeholders and user stories of pilot 2.2.2: Monitoring and control tools for forest
owners
Who I want to Why
Forest
owner
I want to report damage (with pictures,
video & positioning) easily with a mobile
application to authorities
I want to share damage (with pictures,
video & positioning) easily with a mobile
application to my contracting
company/timber buyer
I want to get a situation view through an
easy-to-use and cost-effective web service
I want damage monitoring reports to
integrate with the authority’s central
database
I want damage monitoring reports to
integrate with the 3rd party’s database
I want the service to offer me
guidance/advice about what should be
done in my forest
I want to receive an alert on my mobile or
tablet
To get consultancy about the damage
and how to treat it to avoid further risks
To get injured trees harvested as soon
as possible
It´s important for me to know that my
forest property is doing well
To maintain my forest data updated in
the authority service
It´s important for me to electronically
share information with my contractor
and timber buyer
It´s important for me to know and be
prepared for further harvesting needs in
order to prevent further damages
(fungi, insects).
To be aware of the probability of a
damage occurring in my forest and I
want to receive an indication of the
level of probability
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Forestry
contractor
I want to easily share forest estate data
with the forest owner
I want to easily receive forest data to my
smart phone or tablet
I want to report my work in details and
easily
I want to get detailed information about
damaged sites/compartments
I want to network with my subcontractors
I want to receive on my mobile or tablet an
alert if a probability that a damage occurs
in the forest I’m working on exists
To provide a superior customer service
to my clients
To conveniently receive the forest data
to my standard interface, smart phone
or tablet
To provide a superior, real-time
customer service to my clients
To win deals thanks to the availability of
precise data and to better manage
available machine and operator
resources
To outsource part of my deals by having
tools for smooth networking with my
subcontractors
To be ready to act as soon as possible
and I want to receive an indication of
the level of probability
Timber
buyer
I want to receive forest data easily
I want my contractors to do top quality
harvesting operations and report to forest
owners and my supervisors
I want to get more matching deals for my
purchase targets with less expenses
To conveniently receive the forest data
to my standard interface, smart phone
or tablet
For customer satisfaction, it is
important to report to forest owners
and my supervisors. In addition, the
reporting method must interface with
our IT system
To close deals with less expenses by
understanding better in-site /
compartment level available tree
species, timber quality, assortments etc.
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Forest
authority
expert
I want damage monitoring reports to be
reliable and integrate automatically with
the central authority database
I want to report work damage inspections
easily and in a reliable manner through a
mobile application
I want to report biodiversity features easily
and in a reliable manner through mobile
application
I want to better define the places for field
visits
I want to be able to detect infections in
early stages so that I can apply control
measures before they spread
For simple and compatible solutions
everyone is ready to learn and use
To use my standard interface or
smartphone as a reporting tool because
I take care of daily routines like banking
through apps
To use my standard interface or
smartphone as a reporting tool because
I take care of daily routines like banking
through apps
To be efficient and focus on most risky
sites in the field inspections, to
concentrate efforts and save costs [KPI]
It is of utmost importance to act as soon
as possible if something unusual
happens in the forest, in order to
prevent additional damages while
ensuring e.g. harvesting operations
Forest
insurance
company
I want to access damages produced by e.g.
storm, insects, fungi
To quantify economic losses for
compensation payment in a cost-
efficient way
MHG
service
provider
I want to provide real time monitoring
services
To provide a superior, real-time
customer service to my clients
interfacing with the authority service,
unlike my competitors
4.2.2 Motivation and strategy
New features will be delivered and deployed continuously. All new bigger features are split
into small parts to enable fast deployment and testing cycles. The most important thing is to
prioritize and understand these development requirements correctly first.
After the developed features are tested by the development team and deployed to the
production environment, the features are ready for the DataBio pilot case to be tested in
practical operations by committed Wuudis users, WWF Finland users, associate partners and
other possible Wuudis users.
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The key advantage is that forest contractors can better respond to forest owners and
authority expectations about work quality in regards with biodiversity and nature
conservation, and plan and execute harvesting operations as soon as possible after significant
forest damage occurred. Forest owners and timber buyers are able to guide and give
instructions to contractors remotely through the Wuudis Service and follow the quality of
harvesting operations performed in the forests and, in the meantime, get real time updates
for forest management plans.
Wuudis users are able to update the forest resource data not only on the Wuudis Service but
on Metsään.fi’s eService too, providing better customer service and satisfaction than
competitor solutions. This should bring more paying customers to MHGS, being the first
service provider with such a complete service package in the market interfacing with the
authority database.
4.2.3 Scope and limitations
This pilot operates in an existing service environment of MHGS producing new data and
functionalities related to the Wuudis Service. The pilot scope is to:
- develop forest damage monitoring app seamlessly interfacing with METSAK´s
metsään.fi eService
- test the app in the field operations with associate partners and other stakeholders
The limitations in this pilot may be caused by:
- Ongoing standardization process regarding forest damages
- Operating in METSAK’s system environment and its development: this sets both
content and schedule limitations when specifying and testing changes in Metsään.fi.
- The forest data standard: all the forest data interfaces must be consistent with the
forest data standard.
4.3 Pilot modelling with ArchiMate In this pilot, there is an existing technical environment of the Wuudis Service. Any data
modelling or architecture design is done by MHGS´s internal Wuudis development team. Pilot
modelling in this section is therefore applicable to this pilot to limited extent only.
This section presents the "Forestry A2 Monitoring and control tools for forest owners
modelling with ArchiMate" viewpoints described using the ArchiMate standard.
4.3.1 DataBio forestry pilot 2.2.2 motivation view
Figure 19 describes the "Forestry A2 Motivation view" defined in the "Forestry A2 Monitoring
and control tools for forest owners modelling with ArchiMate" view point.
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Figure 19: Forestry A2 Motivation view
The goal “Real-time monitoring of different forest damages” is further explained by this
description: “Different kinds of forest damages will be monitored in near real-time operations
through the RS service to be defined and interfaced with Wuudis.”
Figure 20 describes the "Forestry A2 Forest owner Motivation view" defined in the "Forestry
A2 Monitoring and control tools for forest owners modelling with ArchiMate" view point.
Figure 20: Forestry A2 Forest owner Motivation view
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4.3.2 DataBio forestry pilot 2.2.2 strategy view
Figure 21 describes the "Forestry A2 Strategy view" defined in the "Forestry A2 Monitoring
and control tools for forest owners modelling with ArchiMate" view points.
Figure 21: Forestry A2 Strategy view
The goal “Real-time monitoring of different forest damages” is further explained by this
description: “Different kinds of forest damages will be monitored in near real-time operations
through the RS service to be defined and interfacing with Wuudis.”
Figure 22 describes the "Forestry A2 Forest owner Strategy view" defined in the "Forestry
A2 Monitoring and control tools for forest owners modelling with ArchiMate" view points.
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Figure 22: Forestry A2 Forest owner Strategy view
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4.4 Big Data infrastructure: Components and BDVA classification The existing technical environment of the Wuudis Service concerning big data is described in
Figure 23. This pilot is about further development of the Wuudis Service features in order to
better serve all its customers and partner groups: forest owners, contractors, timber buyers
and authorities.
Figure 23: Big data components and assets in pilot 2.2.2: Monitoring and control tools for forest owners
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4.5 Pilot evaluation plan
4.5.1 High level goals and KPIs
There are several KPIs for this pilot to evaluate the results yearly and in the end of the project.
Perhaps the most logical approach to evaluate these innovations is through real customer use
cases in forestry operations. These will be identified, specified and agreed with piloting clients
in business practicalities during the project.
Some of the KPIs in this pilot are as follows:
● %decrease in damages in high biodiversity site following the networking e-tools
available/developed for communication and monitoring vs. what would be damage
level based on working instructions on paper documents and paper maps
○ Quantify %decrease in damages.
● %Increase customer satisfaction following the networking e-tools
available/developed vs. what would be the satisfaction following standard
communication practices based on contractor's present practicalities (phone, SMS,
work quality report if any)
○ Quantify %increase in satisfaction for example for high biodiversity stand
harvesting work quality reporting (contractor and forest owner).
● %decrease in costs following the monitoring tools available/developed for
monitoring and reporting vs. what would be costs based on monitoring and
reporting practices currently
○ Quantify %decrease in costs.
● The amount of forest owners and other users as Wuudis Service users is now around
2 700. The amount is expected to increase as follows: 5 000 in the end of 2017, 10
000 in the end of 2018 and 50 000 in the end of 2019.
The final KPIs will be specified and selected later on based on study cases agreed with
associate partners and other stakeholders.
4.6 Initial roadmap The goal of this pilot is to develop and test the forest damage monitoring service to Wuudis
and integrate reported forest damage data to the authority service, Metsaan.fi’s eService.
The Wuudis mobile app will be used as a reporting tool of various forest damages (Figure 24).
The Wuudis mobile app includes all important forest data, maps and geolocation. The Wuudis
mobile app runs on Windows 10 Mobile, Apple iOS, as well as Android smartphones and
tablets.
The implementation process for the app will go on in sprint cycles:
1. Specify
2. Develop
3. Test
4. Deploy
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New features will be delivered/deployed continuously. All new bigger features are split into
small parts to enable fast deployment and testing cycles. The most important thing is to
prioritize and understand these development requirements correctly first.
Figure 24: Wuudis mobile app for observation reporting
After the developed features are tested by the development team and deployed to the
production environment, the features are ready for the DataBio pilot.
The Wuudis implementation plan for this pilot is presented in the following:
1. Wuudis mobile app development: Extend the observation feature to support all kind
of damage reporting
2. Specify and implement a visibility model for the damage reports
3. Export damage report data in a standardized format supported by and compatible
with authority systems
4. Data interface/integration development
5. Evaluate implementation with real end users
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All Wuudis Service forest resource data are saved in a centralized forest resource data system.
The Wuudis Service uses that data through a publishing database and other existing
interfaces.
The Wuudis app expansion with damage reporting features will be developed and
implemented (Q1/2018), piloted and feedback collected (Q2-Q3/2018) for further
development of the platform (Q3/2018). The complete implementation schedule is described
in Figure 25 below. It is partially dependent on the schedule of Metsään.fi’s standardization
progress regarding forest damage monitoring and the development plan timeframe.
Figure 25: Timeline of pilot 2.2.2, Monitoring and control tools for forest owners
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Pilot 2.3.1: Forest Damage Remote Sensing 5.1 Pilot overview
5.1.1 Pilot introduction
The goal of this pilot is to develop a Forest Inventory system for damage identification on the
Wuudis Service based on remote sensing (satellite, aerial, UAV) and field surveys. The Wuudis
Monitoring feature is applied in the pilot; see section 2.3.1 for introduction on Wuudis. In the
DataBio project, selected Big Data partners will integrate their existing market-ready or
almost market-ready technologies onto the Wuudis Service and the resulted solutions will be
piloted with the Wuudis users, forestry sector partners, associated partners and other
stakeholders. This integration also applies to the pilot 2.4.2 Shared multiuser forest data
environment in WP2.
This pilot is developed in Task 2.3.1 “Forest damage remote sensing”, under WP2 Forestry.
The involved partners are MHGS, VTT, SENOP, METSAK and SPACEBEL.
5.1.2 Pilot overview
Earth Observation (EO) data from multispectral optical aerial, unmanned aerial vehicles (UAV)
and satellite sensors present the optimal way to timely collect information on land cover over
areas of various sizes. Particularly the availability of the Copernicus Sentinel-2 data and the
applicable data policy present a great opportunity for developing low cost commercial
applications of EO downstream services in monitoring of the environment.
In parallel, FMI is developing a new methodology for forest health assessment based on
Copernicus satellite data focusing on technological development of the processing of
Sentinel-2 optical and Sentinel-1 radar data. This allows us to assess the forest health of the
entire area of Czech Republic. In addition, the forest owners will benefit from publicly
available map servers and implementation of the layers on the Wuudis platform, where all
forest health status maps will be published to allow proactive management of their forest
properties.
Forest damage (from e.g. storms, snow, pests and diseases) monitoring standardized
procedures will be developed together with METSAK as well as easy-to-use RS-based tools
and services for the damage monitoring needs of various stakeholders, and finally the data
will be integrated with METSAK´s metsaan.fi eService. However, these activities are partially
dependent on further funding through a “Spearhead project” with national funding support,
managed by METSAK.
The pilot aims to develop a comprehensive and near real-time quantitative assessment of
forest cover, forest aboveground carbon stock and carbon stock change over the project pilot
area (Rangunkorpi cooperative forestry). This allows detecting and measuring damages,
deforestation and forest degradation, which is a major cause of loss of biomass and carbon
stores. The data collected will provide a comprehensive and near real-time quantitative
assessment of forest vegetation indexes and monitoring spatial changes related to forest
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degradation and deforestation over the project pilot areas. A challenging aspect is the
integration of numerous heterogeneous data sources into distributed systems. This is a
prerequisite for genuinely exhaustive information systems for strategic management.
Figure 26: Pilot foresty, Rangunkorpi cooperative foresty, on the Wuudis service
For easy integration of satellite maps and analysed (highlighted) theme maps, standard WMS
or WMTS interfaces will be used. The Wuudis Service is using OpenLayers 3/4 as the mapping
client library. For the phase I development Wuudis needs all the data provided in a ready to
use format (for the end users), so no calculations need to be done in the Wuudis platform.
Wuudis will just serve as a user interface for the end users and display specific important
information provided by the Remote Sensing (RS) services. All the developed RS map layers
should be available in the Wuudis web UI and in the Wuudis mobile app.
Table 11: Summary of pilot 2.3.1 Forest Damage Remote Sensing (ISO JTC1 WG9 use case
template)
Use case title Forest Damage Remote Sensing
Vertical (area) Forestry
Author/company/email Seppo Huurinainen & Veli-Matti Plosila / MHGS [email protected] [email protected]
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Actors/stakeholders and their roles and
responsibilities
Forest owners and forestry operators as Wuudis Service users. The Wuudis (MHGS) admin users who use and refine the RS- and forest resource data and make it available for Wuudis users.
Goals To increase the use of Wuudis freemium and commercial Services in Finland and piloting countries, Belgium and Czech Republic.
Use case description Specifying the requirements for forest damage collection through the Wuudis Service to Metsään.fi eService and implementing them in collaboration with the Metsään.fi development team and other METSAK projects. Developing forest damage monitoring services for the Wuudis service in order to interface with marketplaces.
Current solutions
Compute(System) MHGS´s internal systems related to forest resource data.
Storage Databases for MHGS’s internal forest resource data and map systems, for publishing forest resource data for Wuudis and Metsään.fi.
Networking Web-based and mobile solution for Wuudis and Metsään.fi users
Software Wuudis service
Big data characteristics
Data source (distributed/centralized)
Mobile data service, modern smartphone/tablet, web browser, open API to the authority and 3rd party systems
Volume (size) Scalable through international service provider
Velocity (e.g. real time)
Near real time updates from remote sensing services and other notifications for forest owners and other stakeholders
Variety (multiple datasets,
mashup)
Multiple datasets: tree stand basic data, tree stand strata, growth place (site quality)
Variability (rate of change) Same as above (velocity).
Big data science (collection, curation,
analysis, action)
Veracity (Robustness Issues, semantics)
The data source must be saved within the forest resource data (e.g. data from forest owner vs. measured and analyzed data)
Visualization The user interface is the existing Wuudis Service and its map views. For MHGS admin users there are also existing internal systems with which the data is browsed and handled.
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Data quality (syntax) Collected forest damage and other inventory data should be consistent with the specific standards.
Data types Tree stand basic data, tree stand strata data, growth place data (site quality), location data, time stamps.
Data analytics
Big data specific challenges (Gaps)
To take into account Wuudis service users, public authorities’, marketplaces´, and Metsään.fi eService users’ needs.
Big data specific challenges in bio-
economy
To maintain the consistency of data and the usability of new data, functionalities and services from the Wuudis service user point of view to support better clients´ forest related business development and decision making, and therefore bio-economy.
Security and privacy technical considerations
There are both public and private data in the Wuudis Service. Personal and forest estate specific information through authority sources like metsaan.fi eService are private.
Highlight issues for generalizing this Use case (e.g. for ref. architecture)
Using data standards in the interfaces. Visualizing complex data in a logical and understandable way.
More information (URLs) https://www.databio.eu/en/
NOTEs - Spacebel: The Wuudis service will be integrated in the EO Regions! multi-thematic EO services platform in Wallonia. The forestry services developed in the framework of the EUGENIUS projects will reciprocally be integrated in the Wuudis service for the Finnish market.
- Development of features for strategic planning in order to promote forest property management and timber sales (automated alarms, request for automated bidding, group sales etc.)
5.2 Pilot case definition
5.2.1 Stakeholders and user stories
This pilot aims to solve the following needs/problems as a Wuudis user:
1. Share data/information and communicate easily between different stakeholders
with a mobile and web application.
2. Different kinds of forest damage will be monitored in near real-time operations
through RS-services to be defined and interfacing with Wuudis.
3. Forest owners, service providers/contractors, timber buyers, authorities and other
end-users are able to monitor different kinds of damages and share the data for
consultation and reporting through a web service.
4. Near real-time situation view from forest estate (RS-service integrated with Wuudis)
guides forest owners to make decisions for harvesting of damaged/contaminated
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timber in time thus preventing further expansion of insect damages, for example.
Also harvesting operations after storm damage should take place immediately to
avoid fungi attack (saw logs) and a couple of months later (coniferous biomass) to
prevent insect invasion and damages.
5. The service is grouping forest owners having damages in their forest, asking
permission for timber sales tendering, and enabling efficient group sales of timber in
damage areas to prevent further insect/fungi spoilage.
Table 12: Stakeholders and user stories of pilot 2.3.1 Forest Damage Remote Sensing
Who I want to Why
Forest
owner
I want to get a situation view on my
forestry through an easy to use and cost
effective web service
I want to share damage observations
easily to my contracting company/timber
buyer
I want damage monitoring reports to be
integrated with the authority central
database
I want damage monitoring reports to be
integrated with the 3rd party database
I want the service to offer me guidance
about what should be done in my forest
regarding harvesting needs in order to
prevent further damages (fungi, insects).
I want to receive on my mobile or tablet
an alert if a probability that a damage
occurs in my forest exists and I want to
receive an indication of the level of that
probability
To know that my forest property is doing
well
To act as soon as possible after any
damage to prevent further injuries
To maintain my forest data updated
It´s important to me to electronically
share information with my contractor and
timber buyer
It´s important to me to know and be
prepared for further harvesting needs in
order to prevent further damages (fungi,
insects).
To be aware of probability that a damage
occurs in my forest and I want to receive
an indication of the level of that
probability
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Forestry
contractor
I want to share forest estate data with
the forest owner easily
I want to receive forest data easily to my
smart phone or tablet
I want to report my work in details and
easily
I want to get detailed information about
damaged sites/compartments in order to
better manage available machine and
operator resources
I want to network with my
subcontractors
I want to receive on my mobile or tablet
an alert if a probability that a damage
occurs in the forest I’m working on exists
and I want to receive an indication of the
level of that probability
To provide a superior customer service to
my clients
To receive conveniently the forest data to
my standard interface, smart phone or
tablet
For better profit and less work
without principals and middle men
To win deals thanks to precise data
available for cost analysis
To outsource part of my deals by
networking smoothly with my
subcontractors
I want to be ready to act as soon as
possible to win deals in any business
environment
Timber
buyer
I want to receive forest data easily to my
smart phone or tablet
I want my contractors to do top quality
harvesting operations and report to
forest owners and my supervisors
interfacing with our IT system
I want to get more matching deals for my
purchase targets with less expenses
To receive conveniently the forest data to
my standard interface, smart phone or
tablet
For customer satisfaction, it is important
to report to forest owners and my
supervisors. In addition, the reporting
method must interface with our IT system
To close deals with fewer expenses,
understanding better in site /
compartment level the available tree
species, assortments, etc.
To develop and implement new business
practices with minimum paperwork to
become more cost efficient
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Forest
authority
expert
I want damage monitoring reports to be
reliable and integrate automatically with
the central authority database
I want to report work damage
inspections easily and in a reliable
manner through mobile applications
I want to better define the places for
field visits so that I can concentrate
efforts and save costs [KPI]
I want to be able to detect infections in
early stages so that I can apply control
measures before they spread
For simple and compatible solutions
everyone is ready to learn and use
To use my standard interface or my
smartphone as a reporting tool because I
take care of daily routines like banking
through apps
To be efficient and focus on most risky
sites in the field inspections, to
concentrate efforts and save costs [KPI]
It is of utmost importance to act as soon
as possible if something unusual happens
in the forest in order to prevent
additional damages while ensuring e.g.
harvesting operations
Forest
insurance
company
As an end user, I want to access damages
produced by e.g. storm or insects so that
I can cost efficiently quantify economic
losses for compensation payment
To quantify economic losses for
compensation payment in a cost-efficient
way
MHG
service
provider
I want to provide real-time monitoring
services
To provide a superior, real-time customer
service to my clients interfacing with the
authority service unlike my competitors
5.2.2 Motivation and strategy
New features will be delivered/deployed continuously. All new bigger features are split into
small parts to enable fast deployment and testing cycle. The most important thing is to
prioritize and understand these development requirements correctly first.
After the developed features are tested by the development team and deployed to the
production environment, these features are ready for the DataBio pilot case to be tested in
practical operations by committed Wuudis users, associate partners and other possible
Wuudis users. In Wallonia, FMI, with the support of Spacebel, aims to develop a remote
sensing service to provide a spatial distribution of the vulnerability and risk exposure to
diseases and other potential hazards and Sentinel-2 or S1+S2 identification of most vulnerable
areas, identification of dominant risk factors in forest. In addition, an integration of the
Wuudis service with EO Regions! is planned to expand the market of Wuudis to Wallonia.
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As underlined by FMI, the forest owners will benefit from publicly available map servers and
implementation of the layers in the Wuudis Service, where all forest health status maps will
be published to allow pro-active management of their forest properties.
The key advantage is that timber buyers and forest contractors can better respond to
harvesting needs of vastly damaged forest sites through smooth monitoring, networking,
communication and the bidding system of the Wuudis Service and its market place.
Wuudis users are able to update the forest resource data not only on the Wuudis Service but
also to the Metsään.fi eService, thus providing better customer service and satisfaction than
competitor solutions. This should bring more paying customers to MHGS, being the first
service provider with such a complete service package in the market.
5.2.3 Scope and limitations
The scope of the pilot extends to provide a useful tool on the Wuudis Service for accurate
monitoring forest cover and forest damages caused by storms and insects for example.
Limitations that could be encountered are:
● Technical difficulties for accessing different data sources
● Technical difficulties derived from managing big volumes of data
● Technical difficulties derived from managing many different data sources and
formats, with different spatial resolution and precision
5.3 Pilot modelling with ArchiMate Any data modelling or architecture design is done by MHGS´s internal Wuudis development
team. Pilot modelling in this section is applicable to this pilot to limited extent only.
This section presents the "Forestry B1 Forest damage remote sensing modelling with
ArchiMate" view point described using the ArchiMate standard.
5.3.1 DataBio forestry pilot 2.3.1 motivation view
Figure 27 describes the "Forestry B1 Motivation view" defined in the "Forestry B1 Forest
damage remote sensing modelling with ArchiMate" view point. The three assessments in the
view are explained via the KPIs in section 5.5.1. A number of other elements in the view are
further explained in Table 13.
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Figure 27: Forestry B1 Motivation view
Table 13: Explanation of specific elements in the Forestry B1 Motivation view
Name Description
Goal: Easy data
sharing between
stakeholders
Share data/information and communicate easily between different
stakeholders with mobile and web application.
Goal: Near real
time situation view
from forest estate
Near real time situation view from a forest estate (RS service integrated
with Wuudis) guides forest owners to make decisions for harvesting of
damaged/contaminated timber in time preventing further expansion of for
example insect damages. Also harvesting operations after storm damage
should take place immediately to avoid fungi attack (saw logs) and a couple
of months later (coniferous biomass) to prevent insect invasion and
damages.
Goal: Real-time
monitoring of
different forest
damages
Different kind of forest damages will be monitored in near real time
operations through RS-services to be defined and interfacing with Wuudis.
Stakeholder:
Wuudis user
The amount of forest owners and other users as Wuudis Service users is
now around 2 700. The amount is expected to increase as follows: 5 000 in
the end of 2017, 10 000 in the end of 2018 and 50 000 in the end of 2019.
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5.3.2 DataBio forestry pilot 2.3.1 strategy view
Figure 28 describes the "Forestry B1 Strategy view" defined in the "Forestry B1 Forest damage
remote sensing modelling with ArchiMate" view point. A number of elements in the view are
further explained in Table 14.
Figure 28: Forestry B1 Strategy view
Table 14: List of the elements defined in the Forestry B1 Strategy view
Name Description
Action: Provide real
time situation view
from forest estate
Near real-time situation view from a forest estate (RS service integrated
with Wuudis) guides forest owners to make decisions for harvesting of
damaged/contaminated timber in time preventing further expansion of for
example insect damages. Also harvesting operations after storm damage
should take place immediately to avoid fungi attack (saw logs) and a couple
of months later (coniferous biomass) to prevent insect invasion and
damages.
Forest damage
monitoring
Forest damage (like storms, snow, pests, diseases) monitoring standardized
procedures will be developed together with METSAK as well as easy-to-use
remote sensing based tools and services for the damage monitoring needs
of various stakeholders
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Forest health
assessment
FMI is developing a new methodology for forest health assessment based
on Copernicus satellite data focusing on technological development of the
processing of Sentinel-2 optical and Sentinel-1 radar data.
Goal: Easy data
sharing between
stakeholders
Share data/information and communicate easily between different
stakeholders with mobile and web applications.
Integrated user
interface for map
layers
For the easy integration of satellite maps and analysed (highlighted) theme
maps, standard WMS or WMTS interfaces will be used. The Wuudis Service
is using OpenLayers 3/4 as mapping client library.
Invasion danger
index
TRAGSA is developing an “invasion danger index” (ecology + transit +
ecosystem disturbance) for mapping and setting up of an alert system for
early warning of risk presence.
Quantitative
assessment of forest
cover
The pilot will develop a comprehensive and near real-time quantitative
assessment of forest cover, forest aboveground carbon stock and carbon
stock change over the project pilot area.
Spatial risk
distribution
In Wallonia, FMI, with the support of Spacebel, aims to develop a remote
sensing service to provide a spatial distribution of the vulnerability and risk
exposure to diseases and other potential hazards based on Sentinel-2 or
S1+S2
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5.4 Big Data infrastructure: Components and BDVA classification The existing technical environment of the Wuudis Service concerning big data is described in
Figure 29 below. This pilot is about further development of the Wuudis Service Set in order
to better serve all its customers and partner groups: forest owners, contractors, timber
buyers, authorities and other end-user like market places and insurance companies.
Figure 29: Big data components and assets in pilot 2.3.1 Forest Damage Remote Sensing
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5.5 Pilot evaluation plan
5.5.1 High level goals and KPIs
There are several KPIs for this pilot to evaluate the results yearly and in the end of the project.
Perhaps the most logical approach to evaluate these innovations is through real customer use
cases in forestry business operations. These will be identified, specified and agreed with
piloting clients in business practicalities during the project.
Some of the KPIs in this pilot are as follows:
● %Decrease in operational costs for performing the same contracting activities
(through accurate site information and better management of resources) following
the e-tools available/developed vs. what would be the revenue (per hour) following
current practices based
○ Quantify %Decrease in operational costs for example for harvesting
(contractor)
● %Increase customer satisfaction following the monitoring e-tools and services
available/developed vs. what would be the satisfaction following forest asset
monitoring practices based on forest owners present practicalities (forest
management plan (10 years interval) on paper or in electronic form in own/authority
IT systems)
○ Quantify %increase in satisfaction for example for forestry level reporting
(forest owner)
● %decrease in costs following the monitoring tools available/developed for
monitoring and reporting vs. what would be costs based on monitoring and
reporting practices currently
○ Quantify %decrease in costs (authority and/or insurance company?)
● The amount of forest owners and other users as Wuudis Service users is now around
2700. The amount is expected to increase as follows: 5 000 in the end of 2017, 10
000 in the end of 2018 and 50 000 in the end of 2019.
The final KPIs will be specified together with relevant stakeholders based on study cases to
be selected later on.
Big Data methods bring the possibility to both increase the value of the forests as well as to
decrease the costs within sustainability limits set by natural growth and ecological aspects.
The key technology is to gather more and more accurate information about the trees from a
range of sensors including new generation of satellites, UAV images, laser scanning, mobile
devices through crowdsourcing and machines operating in the forests. This enables a
characterization of even single trees, not to mention accurate monetary value of the forestry.
5.6 Initial roadmap The goal of this pilot is to develop, visualize and test forest damage monitoring services made
available through the Wuudis Service.
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Wuudis implementation plan for this pilot proceeds as follows:
1. Specify and develop needed map layers with partners (SPACEBEL, FMI)
2. Integrate those map layers with Wuudis web UI and Wuudis mobile app
3. Gather all data available and show it on the user interface
4. Evaluate usability in the pilot
New features will be delivered/deployed continuously. All new bigger features are split into
small parts to enable fast deployment and testing cycles. The most important thing is to
prioritize and understand these development requirements correctly first. After the
developed features are tested by the development team and deployed to the production
environment, the features are ready for the DataBio pilot case.
The first components of the forest damage RS service will be implemented and integrated in
Q1/2018. Feedback will be collected from field users, analyzed and used for development of
the second version of the platform in Q2-Q3/2018. A more detail roadmap is given below in
Figure 30.
Figure 30: Timeline of pilot 2.3.1, Forest damage remote sensing
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Pilot 2.3.2-FH: Monitoring of forest health 6.1 Pilot overview
6.1.1 Pilot introduction
Spain has to face alarming situations due to several pests which are big threats affecting the
health of very important species in the Iberian Peninsula, among others: Quercus ilex, Quercus
suber and Eucaliptus sp.
Spanish Public Bodies and forest owners need updated information about the health status
of forests to be able to perform sustainable forest management. The optimal combination of
different EO data, together with field data, will provide new products for monitoring, and
effective tools for decision-making, with a good balance between success and cost of
detection. Tools need to be very adapted to user requirements and needs. All this will result
in improved forest management.
In the DataBio project, Big Data partners will integrate their existing market-ready or almost
market-ready technologies to the forest databases and new datasets obtained by processing
state of the art Remote Sensing products. The resulted solutions will be piloted with the
forestry sector partners, with associated partners and other stakeholders. Final users affected
(policy makers, public administration, forest owners) will be involved in the pilot. The main
aim of this pilot is fully aligned with pilots 2.2.2 and 2.3.1. Therefore, this integration applies
to the pilot 2.2.2: Monitoring and control tools for forest owners and pilot 2.3.1: Forest
damage remote sensing in WP2.
6.1.2 Pilot overview
The goal of this pilot is to set up a methodology based on remote sensing images (satellite +
aerial + UAV) and field data for the monitoring of the health status of forests in large areas of
the Iberian Peninsula. The work will focus, particularly, in the monitoring of the health of
Quercus sp. forests affected by the fungus Phytophthora cinnamomi Rands and of the damage
in eucalyptus plantations affected by the coleoptera Gonipterus scutellatus Gyllenhal.
6.1.2.1 Monitoring of the health of Quercus sp. forests affected by the fungus Phytophthora
cinnamomi Rands
Main user: JUNTA DE EXTREMADURA – CICYTEX
Current situation: Phytophthora cinnamomi affects very severely several tree species, among
them Quercus ilex and Q. suber, in different areas in Spain (Extremadura, Andalucia, Castilla
y León, Castilla La Mancha, Madrid), causing a great ecological and economic problem.
Detection is currently performed through direct observations or through data sampling and
analysis in the laboratory.
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Pilot solution: The pilot aims at developing EO-based monitoring tools at different scales:
• Orthophotos (RGB + NIR) will be used to identify dead trees from different dates and locate possible affected areas of Quercus forests, as well as their evolution. Sampling plots will be selected in those areas.
• Detailed RPAS (RGB + multispectral + thermal sensors) and field data will be collected in the selected sampling plots and analysed (in-situ or in the lab); RPAS will be employed for intensive monitoring of affected and control areas, to establish the relationships between satellite-derived indexes (from multispectral images) and biophysical parameters from field data, and select the most adequate parameters to be measured, as well as the optimal spatial resolutions and sensors for an effective monitoring.
• A more general health status monitoring for big areas of Quercus forests could be developed based on satellite-derived Vegetation indices using freely distributed Sentinel 2/Landsat 8 data. Ancillary information about environmental conditions and management would be combined with EO data to detect areas under stress and, consequently, more prone to be affected by Phytophtora and/or other plagues and diseases.
All the information will be combined and analysed to:
• define an optimal methodology for data acquisition and analysis
• develop efficient tools for health status monitoring at different spatial, temporal and economic levels.
• optimize efforts by focusing resources (intensive monitoring and field work) on the most affected / vulnerable areas and on those that show anomalies in their evolution.
Key problem-solving capacity: EO-based solutions will provide Public Bodies with valuable
information and tools to help decision-making. An EO-based system for monitoring the health
of big forest areas will be set up (mapping + assessment tools), so authorities will be able to
optimise forest management resources.
6.1.2.2 Monitoring of the damage in eucalyptus plantations caused by the coleoptera
Gonipterus scutellatus Gyllenhal
Main users: XUNTA DE GALICIA & ENCE
Current situation: Gonipterus scutellatus defoliates eucalyptus plantations very severely.
Eucaliptus is one of the main commercial species in the North of Spain (Galicia, Asturias and
Cantabria), where Gonipterus produces huge economic losses by impeding the development
and growth of trees. Authorities (Xunta de Galicia), industrial companies from the paper
sector (ENCE) and forest owners need an economic, systematic and objective tool for affected
areas identification and damage assessment.
Pilot solution: Sentinel 2-derived vegetation indices will be used for a systematic monitoring
(weekly) of the health status in the selected study areas; anomalies will show areas where
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Gonipteurs can be defoliating, which will be checked on the field, either visually or using RPAS.
This information will be combined to define an optimal methodology for data acquisition and
analysis. The rate of defoliation that can be detected must be analysed and established for
different EO data.
Key problem-solving capacity: A mapping and assessment tool will be developed for
monitoring the damages caused by Gonipterus in eucalyptus plantations, as well as for
damage assessment, in order to adapt management and minimise economic losses.
Table 15: Summary of pilot 2.3.2-FH: Monitoring of forest health (ISO JTC1 WG9 use case template)
Use case title Pilot 2.3.2-FH: Monitoring of forest health
Vertical (area) Forestry
Author/company/email
Asunción Roldán & Jesús Estrada / TRAGSA Group [email protected] & [email protected]
Actors/stakeholders and their roles and
responsibilities
Actors / roles:
- Final Users (public administrations, policy makers, forest
companies, forest owners) / define users’ needs and requirements;
validate the new products and services.
- Forestry Technicians and developers from Tragsa Group / develop
EO-based tools and methodologies
Goals Set up a methodology (satellite + aerial + UAV + field data) for the monitoring of pests affecting forests (Phytophthora cinnamomi Rands affecting Quercus ilex and Q. suber) and Gonipterus scutellatus Gyllenhal affecting Eucaliptus plantations.
Use case description
Refer to the pilot case definition section and diagrams in the pilot modelling sections
Current solutions
Compute(System) Dedicated server 2 processors Intel(R) Xeon(R) CPU E5606 @ 2.13GHz, 8 cores, with 96 GB ECC of Memory
Storage Dedicated server Hard Disks: 2 disks - 2 TB (RAID). Total: 2 TB
Networking 250 MBps
Software OS: Debian 8.8 Apache web server 2.4.10 Tomcat: 7.0.56 and 8.0.14 R: 3.3.3. PostGres: 9.4 MySQL: 5.5.55 Python: 2.7.9 Virtuoso: 07.20.3212
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Big data characteristics
Data source (distributed/centraliz
ed)
Combination of both types: Centralized: Remote sensing data such as Sentinel 2A and 2B data provided by ESA at Sentinel Data Hub (https://cophub.copernicus.eu/) Orthophotos (Spanish Coverage). RGB and NIR bands provided by Spanish National Geographic Institute at http://centrodedescargas.cnig.es/CentroDescargas/catalogo.do Surveys and field data: Direct observations and lab measurements as Chlorophyll content, morphology, green and dry weight, hydric potential, leaf area index, visual classification of damages or other features according to pilot needs Spanish Forestry Map (MFE50) on forest types and forest status (scale 1:50.000) available at http://www.mapama.gob.es/es/biodiversidad/servicios/banco-datos-naturaleza/informacion-disponible/mfe50_descargas_comunidad_madrid.aspx Likely, GEOSS open sources available at GEOSS portal (http://www.geoportal.org) will be used as testing and validation data Distributed/local: LPIS system is provided in a distributed way by NUTS2-Level Administration. TRAGSA Drones produce JPEG and LAS files using thermal and multispectral sensors. More information is available in the DataBio deliverable D6.2 – Data Management Plan
Volume (size) Remote sensing data such as Sentinel 2A and 2B have an average size of tens of TB per year over pilot zone. The Spanish LPIS system has a size of hundreds of Gigabytes, likewise for the Spanish Orthophoto project (PNOA). MFE50 weighs several megabytes in the ESRI Shapefile format. TRAGSA Drones produce information (TB per year) on demand. Field data information has a size of MB per year.
Velocity (e.g. real time)
Sentinel 2A and 2B have the highest revisit within the Pilot’s data sources (5 days). All external sources have several-years updating ratio.
Variety (multiple datasets,
mashup)
The formats to be used will be imagery, digital terrain models and ESRI Shapefiles for vector information.
Variability (rate of change)
Forestry information, typically, depends on seasons. Highest variability rate is some months (4-6)
Big data science (collection,
curation,
Veracity (Robustness Issues, semantics)
All data sources are official and trusted ones: European Space Agency (ESA) and Spanish Public Administration.
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analysis, action)
Visualization Standard imagery visualization services. Spanish Public Administration usually provides WMS services for information visualization.
Data quality (syntax) Even though the data providers are supposed to produce good quality information, all datasets are processed by TRAGSA to produce improved images. Specifically, orthophotos will be transformed by an orthorectification method developed under WP5.
Data types TIFF or JPEG for images, .LAS for terrain models. Text document for surveys and field data.
Data analytics EO-based solutions will provide Public Bodies with valuable information and tools to help decision-making. This EO-based system for monitoring the health of big forest areas will be set up to optimize forest management resources concerning specific diseases and plagues.
Big data specific challenges (Gaps)
TRAGSA Group is currently able to process, manage and submit results about a high number of forestry parcels. Processes will be scaled to provincial, regional and national levels.
Big data specific challenges in bio-
economy
TRAGSA Group is currently able to process, manage and submit results about a high number of forestry parcels. With regard to forestry surfaces, the initial aim is to process two study sites (one for each pest - variable surface depending on the affection of trees) in which field + RPAS data will be collected. Processes will be scaled to provincial/regional levels, taking into account a multi-temporal approach.
Security and privacy technical
considerations
None of the datasets of this pilot are considered sensitive or related to personal data.
Highlight issues for generalizing this
Use case (e.g. for ref. architecture)
Main technical problems are related to data storage and resulting maps transmission.
More information (URLs)
ESA: https://sentinel.esa.int/web/sentinel/sentinel-data-access PNOA: http://www.ign.es/web/ign/portal/obs-portal-pnoa As auxiliary source of information, Possibly GEOSS platform could be used GEOSS: https://www.earthobservations.org/index.phphttps://www.earthobservations.org/index.php
6.2 Pilot case definition
6.2.1 Stakeholders and user stories
The users involved in the pilot are:
- JUNTA DE EXTREMADURA – CICYTEX (Main user)
- XUNTA DE GALICIA (Main user)
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- ENCE (Empresa Nacional de Celulosas) (Main user)
- MAPAMA - Ministry of Agriculture (Subdirección General de Sanidad e Higiene
Vegetal y Forestal de la Dirección General de Sanidad de la Producción Agraria)
- Other public administrations (Junta de Andalucía, Junta de Castilla y León, Junta
de Castilla La Mancha, Comunidad de Madrid, Principado de Asturias, Gobierno
de Cantabria).
- Forestry and environmental Technicians
Table 16: Stakeholders and user stories of pilot 2.3.2-FH: Monitoring of forest health
Who (type of user) I want to (perform some task) Why (to achieve some goals)
As an end user
(Junta de Extremadura)
I want to know the current status
of P. Cinnamomi distribution
To visualize updated maps
As an end user
(Xunta de Galicia)
I want to know the current status
of G. Scutellatus distribution
To visualize updated maps
As an end user
(Xunta de Galicia)
I want to assess damages produced
by G. Scutellatus
To quantify economic losses
As an end user
(Public Administrations)
I want to accurately assess the
temporal evolution of forest health
To concentrate efforts and
avoid unnecessary field visits
As an end user
(Public Administrations)
I want to better define the places
for RPAS visits
To concentrate efforts and
save costs
As an end user
(Public Administrations)
I want to be able to detect
infections in early stages
To apply control measures
before they spread
As a TRAGSA Technician I want to produce and provide
updated Forest Health maps
To send them to customers
[Period to be defined]
As a generic user I want to use all standard GIS
features
To pan, change scales, go to
specific coordinates and places
and so on
6.2.2 Motivation and strategy
The main motivations for this pilot are:
● to set up an optimised EO-based system for monitoring the health of Quercus ilex
and Q. suber forest areas (mapping + assessment tools), so authorities and forest
owners will be able to optimise forest management resources and decision making.
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● to develop an efficient mapping + assessment tool for monitoring the damages
caused by Gonipterus in eucalyptus plantations, as well as for damage assessment, in
order to adapt management and minimise economic losses.
The pilot motivation and strategy is summarized using ArchiMate diagrams in the next
section, while goals and KPIs are addressed in the succeeding evaluation plan.
6.2.3 Scope and limitations
The scope of the pilot extends to providing final users with useful tools for the monitoring of
health of forests affected by Phytophthora or damages caused by Gonipterus, within a local
or regional geographical range.
Limitations that could be encountered are:
● Difficulties for finding suitable filled sites (adequate conditions for RPAS + field
operations, representativeness, range of affection by pests etc.)
● Difficulties in performing RPAS + field operations (complex terrain, permissions etc.)
● Meteorological issues that can affect the acquisition of RPAS/satellite images and
field data
● Lack of correlation between EO-derived spectral information and biophysical
parameters measured on the ground.
● Possible interaction in the study area of other pests and diseases, as well as of
abiotic factors, in the study area that may interfere with the results obtained.
● The monitoring of damage caused by living organisms, especially in the case of
insects, is limited to a specific period of the year, more or less concrete depending
on its biological cycle and the climate conditions.
6.3 Pilot modelling with ArchiMate This section presents the "Forestry B1-FH Monitoring of forest health modelling with
ArchiMate" view point described using the ArchiMate standard.
6.3.1 DataBio forestry pilot 2.3.2-FH motivation view
Figure 31 describes the "Forestry B1-FH Motivation view" defined in the "Forestry B1-FH
Monitoring of forest health modelling with ArchiMate" view point. A number of elements in
the view are further explained in Table 17.
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Figure 31: Forestry B1-FH Motivation view
Table 17: Explanation of specific elements in the Forestry B1-FH Motivation view
Name Description
Health of important species are
threatened
In the Iberian Peninsula, quercus ilex, quercus suber and
eucaliptus sp.
Monitor health of Quercus forests Monitor the health of Quercus forests affected by the
fungus Phytophtora cinnamoni Rands.
Monitor the damage of eucalyptus
plantations
Monitor the damage in eucalyptus plantations affected
by the coleoptera Gonipterus scutellatus Gyllenhal
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Monitor the health status of forest Monitor the health status of forests in large areas of the
Iberian Peninsula.
6.3.2 DataBio forestry pilot 2.3.2-FH strategy view
Figure 32 describes the "Forestry B1-FH Strategy view" that is defined in the "Forestry B1-FH
Monitoring of forest health modelling with ArchiMate" view point. A number of elements in
the view are further explained in Table 18.
Figure 32: Forestry B1-FH Strategy view
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Table 18: Explanation of specific elements in the Forestry B1-FH Strategy view
Name Description
Monitor health of Quercus forests Monitor the health of Quercus forests affected by the
fungus Phytophtora cinnamoni Rands.
Monitor the damage of eucalyptus
plantations
Monitor the damage in eucalyptus plantations affected by
the coleoptera Gonipterus scutellatus Gyllenhal
Monitor the health status of forest Monitor the health status of forests in large areas of the
Iberian Peninsula.
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6.4 Big Data infrastructure: Components and BDVA classification Figure 33 presents the big data components and assets used or developed in the pilot, using
the BDVA classification. The components are explained in Table 19.
Figure 33: Big data components and assets in pilot 2.3.2-FH: Monitoring of forest health
Table 19: Listing of the components used or produced in the pilot 2.3.2-FH: Monitoring of
forest health
Used in this pilot: Produced in this pilot:
1. Centralized Datasources: 1. Imagery classification system
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a. Sentinel 2A, 2B
b. PNOA
c. Field Data
d. MFE50
2. Distributed Datasources:
a. LPIS
b. NUTS2
c. TRAGSA Drones
2. Machine learning classification to
produce a “Changes Layer”
3. Imagery Optimization. Maps Evolution.
Temporal changes
4. Remote Sensing imageries download
system: Synchronous and Asynchronous
connection system. Real time data
access and batch
processes
5. Visualization and Querying system:
viewer and data access
6.5 Pilot evaluation plan
6.5.1 High level goals and KPIs
The following technical KPIs (Key Performance Indicators) have been identified so far:
● Surface processed: number of hectares of forest land monitored using different
EO data sources (satellite/aircraft/RPAS) for the two assessed pests (Phytophtora
& Gonipterus).
● Field visits saved: an assessment of how much fieldwork (number of hours) can
be saved by using an adequate EO-based methodology will be performed.
● Economic improvements: an economic ratio will be obtained to assess the
performance of the new methodologies (€/ha) and compare it with traditional
methods.
● Accuracy of cartography obtained from different EO-data sources (% )
● Generation of new protocols for detection and monitoring of Gonipterus &
Phytophtora using EO & field data (yes/no).
● Generation of new products & services available for final users (yes/no).
● Estimation of potential users (number)
Target figures for each KPI will be established later in the project, as they need to be
established in collaboration with the end users.
6.6 Initial roadmap Pilot implementation starts on M5 with the first campaign of RPAS flights and field work. RPAS
flights + field work will take place in spring-summer-autumn periods during 2017, 2018 and
2019 (M5-M10, M17-M22, M25-M34). Gonipterus will be monitored in 2017 and 2018 and
Phytophtora in 2018 and 2019. In parallel, the necessary satellite images will be acquired.
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A data processing period will take place after each field campaign (M6-M16, M18-M28, M29-
M34). In parallel, the implementation of services in Databio platform will be performed in two
periods: M18-M28 (first implementation), M30-M34 (final implementation + trial with end
users). EO services will be ready on M35.
KPIs will be measured in two moments: M12 (baseline measurement) and M35 (final
measurement). Deliverables will be produced on M6, M24 and M36, according to the general
planning.
Figure 34: Timeline of pilot 2.3.2-FH, Monitoring of forest health
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Pilot 2.3.2-IAS: Invasive Alien Species control
and monitoring 7.1 Pilot overview
7.1.1 Pilot introduction
Invasive alien species (IAS) are a big threat for biodiversity in the Iberian Peninsula, the Canary
Islands and the Balearic Islands, and cause significant economic losses. Resources are limited
and eradication measures are complex and very expensive, so early warning and monitoring
are key points for Spanish Public Bodies to be more efficient. The model developed is
expected to identify the geographic origin of the biological invasions that will likely affect
terrestrial Spain in the next future, to provide a detailed generic spatial assessment of
invasion risk within Spain and, eventually, to serve for a better management of IAS by
increasing the efficiency of preventive measures.
In the DataBio project, Big Data partners will integrate their existing market-ready or almost
market-ready technologies to the forest databases and, in this specific case, with datasets
related to trade movements and migratory flows. The target of this pilot is directly related to
pilot 2.2.2, although the technical tools to be used will be slightly different. Therefore, this
integration applies to the pilot 2.2.2: Monitoring and control tools for forest owners and, due
to it will be developed by similar teams, pilot 2.3.2: Forest monitoring health status.
7.1.2 Pilot overview
The pilot aims at developing a simple model for assessing invasion risk in Spain based on a set
of factors that strongly influence the geographic pattern and level of invasion:
1) Environmental similarity, calculated from bioclimatic variables
2) Biodiversity similarity, approached through biogeographic information
3) Propagule pressure, estimated from data on trade, tourism, immigration,
population and terrestrial transport network
4) Ecosystem disturbance, measured from land use and fire frequency.
The model is expected to identify the geographic origin of the biological invasions that will
likely affect terrestrial Spain in the next future, to provide a detailed generic spatial
assessment of invasion risk within Spain and, eventually, to serve for a better management
of IAS by increasing the efficiency of preventive measures.
Pilot solution
It has been demonstrated that prevention is the most effective way to face the problem of
biological invasions. Consequently, it is important to know the invasion risk in different areas
and ecosystems for a better management of this problem. Moreover, targeting areas and
ecosystems at highest risk makes preventive measures most efficient. The pilot case, by
providing a detailed spatial assessment of invasion risk and by identifying the geographic
origin of the biological invasions that will likely affect Spain in the next future, is expected to
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serve for increasing the efficiency of preventive measures and so to contribute to a better
management of IAS. Sensitive areas, i.e. those with the highest risk of invasion, will be
identified and mapped.
Invasion risk is assessed by quantifying climatic similarity (based on climatic distances) and
‘propagule pressure’ (addressed by information on tourism, immigration and trade) between
Spain and the rest of the world. Finally, the degree of disturbance of the arrival ecosystems
will also be incorporated, as well as the biogeographic regions of the territories that act as
sources of IAS.
Key problem-solving capacity
The pilot case is linked to prevention, which is both an effective and efficient way of dealing
with the problem of biological invasions. Indeed, the pilot will identify the areas in Spain at
greatest risk of invasion and the most likely source regions of IAS, thus providing crucial
information for resource prioritization and for a much better management of these species.
For instance, more resources and sensible measures could be addressed to the survey of areas
at highest risk and products coming from specific countries or regions.
In addition, because of the use of public and periodically updated databases, a dynamic tool
will be provided, with which future invasion risk assessments will be possible.
Table 20: Summary of pilot 2.3.2-IAS: Invasive Alien Species control and monitoring (ISO
JTC1 WG9 use case template)
Use case title Pilot 2.3.2-IAS: Invasive Alien Species control and monitoring
Vertical (area) Forestry
Author/company/email
Laura Luquero & Jesús Estrada / TRAGSA Group [email protected] & [email protected]
Actors/stakeholders and their roles and
responsibilities
Actors / roles:
- Final Users (public administrations, policy makers, forest companies, forest owners) / define users’ needs and requirements; validate the new products and services.
- Forestry Technicians and developers from Tragsa Group / develop EO-based tools and methodologies
Goals Set up a methodology for modelling IAS invasion risk in Spain.
Use case description Refer to the pilot case definition section and diagrams in the pilot modelling sections.
Current solutions
Compute(System) Dedicated server 2 processors Intel(R) Xeon(R) CPU E5606 @ 2.13GHz, 8 cores with 96 GB ECC of Memory
Storage Dedicated server Hard Disks: 2 disks - 2 TB (RAID). Total: 2 TB
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Networking 250 MBps
Software OS: Debian 8.8 Apache web server 2.4.10 Tomcat: 7.0.56 and 8.0.14 R: 3.3.3. PostGres: 9.4 MySQL: 5.5.55 Python: 2.7.9 Virtuoso: 07.20.3212
Big data characteristics
Data source (distributed/centralized)
All 2.3.2-IAS sources will be Centralized: WORLDCLIM provided by the International Journal of Climatology. 19 bioclimatic raster layers with a resolution of 1km. Foreign trade database from Spanish Finance Ministry. Foreign trade disaggregated by months, products, origin and destination. Available at http://www.icex.es/icex/es/navegacion-principal/que-es-icex/index.html Immigration Database by Spanish Statistical Institute. Migration to/from Spain disaggregated by year, province, country, sex and age. Available at http://www.ine.es/dynt3/inebase/index.htm?type=pcaxis&path=/t20/p277/prov/e01/&file=pcaxis Tourism dataset from Ministry of Energy, Tourism and Digital Agenda. Tourism to Spain disaggregated by month, country, destination and type of transport. Available at http://estadisticas.tourspain.es/es-es/estadisticas/frontur/paginas/default.aspx GHS – population Grid developed by JRC. Population density raster based on population census and human settlements. Available at http://ghsl.jrc.ec.europa.eu/datasets.php Spanish terrestrial transport network. ESRI Shapefile provided by the National Geographic Institute. NUTS-2, NUTS-3 and Municipalities maps from
Global Administrative Areas
(http://www.gadm.org/)
Volume (size) WORLDCLIM .TIFF images and the results obtained from them have a typical size of hundreds of Gigabytes. All the statistical information (CSV) provided by Spanish Public Administrations have an average size of several Megabytes. GHS population grid (versions 1975, 1990, 2000 and 2015) size is likely to be in the order of Terabytes.
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Velocity (e.g. real time)
All external sources have several years updating ratio, but touristic information datasets are updated monthly.
Variety (multiple datasets,
mashup)
The formats to be used will be imagery, ESRI Shapefiles for vector information and CSV for text information.
Variability (rate of change)
Highest variability rate is monthly.
Big data science (collection, curation,
analysis, action)
Veracity (Robustness Issues, semantics)
All data sources are official and trusted ones: Spanish Public Administration and Global and European Institutions.
Visualization Standard imagery visualization services. Spanish Public Administration usually provides WMS services for information visualization. Tabular and text information is usually provided as HTML pages.
Data quality (syntax) Even though data providers are supposed to produce good quality information, this pilot will develop R-Statistics process to improve and transform them.
Data types TIFF or JPEG for images. Text document for statistics.
Data analytics The pilot aims at developing a simple model for assessing invasion risk in Spain based on the set of factors that strongly influence the geographic pattern and level of invasion: Environmental similarity, Biodiversity similarity, Propagule pressure and Ecosystems disturbance.
Big data specific challenges (Gaps)
Processes will be scaled to provincial, regional and national levels.
Big data specific challenges in bio-
economy
The number of zones to be processed will be defined later. The aim is to process ecological variables (bioclimatic and biogeographic variables), data on flows (trade, tourism and immigration), and the degree of ecosystem disturbance (from land use, fire frequency or terrestrial transport network) from global scale to developing a model for assessing invasion risk in the Iberian Peninsula, Canary Islands and Balearic islands (approximate surface: 596.270 km2). The model will serve to improve management of IAS of Spanish Public Bodies (NUTS 2 level, Ministry, national parks...) in order to prioritize activities and increase the efficiency of preventive measures established.
Security and privacy technical
considerations
None of the datasets of this pilot are considered sensitive or related to personal data.
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Highlight issues for generalizing this Use
case (e.g. for ref. architecture)
Main technical problems are related to data storage and resulting maps transmission.
More information (URLs)
Spanish administration: http://www.icex.es/icex/es/navegacion-principal/que-es-icex/index.html http://www.ine.es/dynt3/inebase/index.htm?type=pcaxis&path=/t20/p277/prov/e01/&file=pcaxis http://estadisticas.tourspain.es/es-es/estadisticas/frontur/paginas/default.aspx European administration: http://ghsl.jrc.ec.europa.eu/datasets.php Global Institutions: http://www.gadm.org/
7.2 Pilot case definition
7.2.1 Stakeholders and user stories
The users in the pilot are:
- MAPAMA - Ministry of Agriculture
- OAPN - National Parks Authority
- Public Administrations - NUTS2 Level
Table 21: Stakeholders and user stories of pilot 2.3.2-IAS: Invasive Alien Species control and
monitoring
Who (type of user) I want to (perform some task) Why (achieve some goals)
As an end user
(MAPAMA-Policy Makers)
I want to know current status of
the distribution of specific AIS
To visualize updated maps
As an end user
(Public Administrations)
I want to have accurate
information about the temporal
evolution of AIS
To concentrate efforts and
save field visits
As an end user
(Public Administrations)
I want to know the invasion risk of
new AIS in Spain every 1-2 years
For strategic planning
As an end user
(Public Administrations)
I want to establish priority areas
based on an invasion risk index
For a better management of
IAS by increasing the efficiency
of preventive measures
As an end user
(Public Administrations)
I want to better know in advance
the most suitable places for AIS
To concentrate efforts and
save costs
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As an end user
(Public Administrations)
I want to set up an alert system for
early warning of AIS presence
To allow to act as quickly as
possible
As a TRAGSA Technician I want to develop, manage and
update an early warning system
every 1-2 years
To provide my customers with
a timely service
As a generic user I want to use all standard GIS
features
To pan, change scales, go to
specific coordinates and places
and so on
7.2.2 Motivation and strategy
The main motivations for this pilot are:
● to develop a model capable to identify the geographic origin of the biological
invasions that will likely affect terrestrial ecosystems in Spain in the next future
● to provide a detailed generic spatial assessment of invasion risk within Spain
● to provide a dynamic tool based on public and periodically updated databases with
which future invasion risk assessments will be possible
● to serve for a better management of IAS by increasing the efficiency of preventive
measures
The pilot motivation and strategy are summarized using ArchiMate diagrams in the next
section, while goals and KPIs are addressed in the succeeding evaluation plan.
7.2.3 Scope and limitations
The scope of the pilot extends to providing final users with a useful tool for the monitoring
and prevention of IAS presence in the Iberian Peninsula within a regional/national
geographical range.
Limitations that could be encountered are:
● Lack of detail/updating in the information contained in the databases which will be
employed for the development of the “danger of invasion index”
● Complexity in combining “static” (climate) & “dynamic” (flows: commercial,
tourism) variables
● Need for capacity of adapting to changes in laws affecting IAS
● Lack of updating of the risk maps
● Technical difficulties for accessing different data sources
● Technical difficulties derived from managing big volumes of data (world from all
around the world, at a 1x1 km spatial resolution)
● Technical difficulties derived from managing many different data sources and
formats, with different spatial resolution and precision
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7.3 Pilot modelling with ArchiMate This section presents the "Forestry B2-IAS Invasive alien species control and monitoring
modelling with ArchiMate" view point described using the ArchiMate standard.
7.3.1 DataBio forestry pilot 2.3.2-IAS motivation view
Figure 35 describes the "Forestry B2-IAS Motivation view" defined in the "Forestry B2-IAS
Invasive alien species control and monitoring modelling with ArchiMate" view point.
Figure 35: Forestry B2-IAS Motivation view
7.3.2 DataBio forestry pilot 2.3.2-IAS strategy view
Figure 36 describes the "Forestry B2-IAS Strategy view" defined in the "Forestry B2-IAS
Invasive alien species control and monitoring modelling with ArchiMate" view point.
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Figure 36: Forestry B2-IAS Strategy view
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7.4 Big Data infrastructure: Components and BDVA classification Figure 37 presents the big data components and assets used or developed in the pilot, using
the BDVA classification. The components are explained in Table 22.
Figure 37: Big data components and assets in pilot 2.3.2-IAS: Invasive Alien Species control and monitoring
Table 22: Listing of the components used or produced in the pilot 2.3.2-IAS: Invasive Alien Species control and monitoring
Used in this pilot: Produced in this pilot:
1. Centralized data sources:
a. WorldClim
b. Immigration database
1. R-based Data classification system
2. Data Optimization. Temporal changes
3. Interactive data access and process
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c. Tourism dataset
d. Others
4. Visualization and Querying system:
viewer and data access
7.5 Pilot evaluation plan
7.5.1 High level goals and KPIs
The following technical KPIs (Key Performance Indicators) have been identified so far:
• Surface processed: has of land monitored (related to the whole of Iberian Peninsula, Canary Islands and Balearic islands, approximate surface: 596.270 km2) using the methodology developed within the pilot.
• Invasion risk maps generation: Risk assessment at a geographical level with cells of 1 km per 1 km for the surface processed.
• Reports of risk level: at least NUTS2 level
• Field visits saved: an assessment of how much fieldwork can be saved by using the methodology developed within the pilot will be performed. The goal is to save at least 10 % of field visits.
• Economic improvements: an assessment of how much money can be saved by using the methodology developed within the pilot will be performed. The goal is to save at least 10 %.
More precise target figures for each KPI will be established later in the project, as they need to be established in collaboration with the end users.
7.6 Initial roadmap Pilot implementation starts on M4 with data sources selection and acquisition and will last
until M12. On M12 all data will be acquired and data processing period will start. Data
processing and information analysis will be ready on M19 and start the generation of Risk
maps. Invasion Risk Maps will be finished on M24.
After having completed the analysis phase of the data and having the information collected
and with the risk maps generated, status reports will be elaborated at NUTS2 level (M27).
Deliverables will be produced on M6, M24 and M27, according to the general planning. KPIs
will be measured at two points in time: M12 (baseline measurement) and M35 (final
measurement).
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Figure 38: Timeline of pilot 2.3.2-IAS, Invasive alien species control and monitoring
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Pilot 2.4.1: Web-mapping service for
government decision making 8.1 Pilot overview
8.1.1 Pilot introduction
A central database (FMI) of forestry and hunting provides a range of services regarding the
information on forests for various governmental bodies and forest owners. For the
development of the service, it is necessary to develop and validate the processing chain based
on the DataBio platform and big data environment. The outputs of the service (e.g. the map
server) should serve both to streamline the implementation of forestry-related measures, and
for redistribution of subsidies and tax relief for forest owners, and ultimately for forest
monitoring activities.
8.1.2 Pilot overview
In the recent years, there's significant forest health decrease in Czech Republic. It is caused
by various factors, both biotic and abiotic. These are independent on the forest owner and
his management practices, resulting in loss of forest value compared to unaffected forests.
The government compensates this loss to forest owner by the means of subsidies and tax
reliefs. In order to correctly identify the affected forest owners and their eligibility for
subsidies/tax relief, the Ministry of Agriculture of Czech Republic must precisely spatially
locate the affected areas. For this purpose, the field surveys are used. These are however
local, costly and subjective.
Table 23: Summary of pilot 2.4.1 Web-mapping service for the government decision making
(ISO JTC1 WG9 use case template)
Use case title 2.4.1 Web-mapping service for the government decision making
Vertical (area) Forestry
Author/company/email Petr Lukeš / FMI [email protected]
Actors/stakeholders and their roles and
responsibilities
Primary end-user of the pilot is the Ministry of Agriculture of Czech Republic, secondary users include forest owners in Czech Republic and Wallonia, Belgium
Goals To provide forest health service based on Sentinel-2 data
Use case description 1. Ministry of Agriculture needs relevant and timely information about current forest health status and its trends. Forest owners are looking for plot-level information about the condition of his/her property.
2. Ministry/forest owner access dedicated map servers, where forest health status and its trends are visualized in an easily accessible form.
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3. The ministry will use the information for better distribution of financial aid for worst affected forest owners, and forest owners will better allocate his/her resources
Current solutions
Compute(System) FMI’s computer hardware, single PC with 8 cores and 64 GB RAM, multi-platform (Windows and Unix)
Storage Local storage
Networking Map server of FMI and Ministry of Agriculture of the Czech Republic (eAGRI)
Software Opensource technologies (GDAL, Python), in-house development
Big data characteristics
Data source (distributed/centralized)
Sentinel-2 satellite data, distributed by European Space Agency. Local storage for the area of Czech Republic established at FMI, and local storage for Wallonia established at Spacebel
Volume (size) 1-2 TB annually for Czech Republic 800 GB annually for Wallonia
Velocity (e.g. real time)
New satellite data being acquired every 5 days, cloud-free mosaics generated annually for vegetation growing season from all-available Sentinel-2 acquisitions
Variety (multiple datasets,
mashup)
Surface reflectance in 9 spectral channels covering visible and infrared wavelengths Set of vegetation indices generated from a combination of the surface reflectance spectral channels of S-2
Variability (rate of change) Same as above (velocity).
Big data science (collection, curation,
analysis, action)
Veracity (Robustness Issues, semantics)
Derived forest health products must be sensitive to observed ground truth
Visualization FMI’s internal map server. Visualization of raster layers together with other vector and raster products (e.g. forest management plans); WMS/WFS service for third-party applications
Data quality (syntax) Surface reflectances used as an input for forest health interpretation (atmospheric corrections), sensitivity of derived products on forest health
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Data types Forest reflectances and its derived products
Data analytics Forest health trends based on reflectance data, vegetation indices and forest quantitative products
Big data specific challenges (Gaps)
To generate seamless cloud-free mosaics of Czech Republic and Wallonia, consistent and comparable in time. Increased performance of atmospheric corrections of L2A product (sen2cor vs MAJA-MACCS)
Big data specific challenges in bio-
economy
To establish a robust methodology for forest health trends assessment based on the interpretation of Sentinel-2 satellite data. Feedback from end-users is needed in order to set the decision rules on forest health trends
Security and privacy technical considerations
All Sentinel-2 satellite data are provided free of charge, several internal products will be used (e.g. forest mask, forest management plan) which won’t be shared publicly
Highlight issues for generalizing this Use case (e.g. for ref. architecture)
Automated production of cloud-free synthetic mosaics for Czech Republic and Wallonia; Retrieval of forest parameters from satellite data; Interpretation of forest health trends
More information (URLs) https://www.databio.eu/en/
8.2 Pilot case definition
8.2.1 Stakeholders and user stories
Table 24: Stakeholders and user stories of pilot 2.4.1 Web-mapping service for the government decision making
Who I want to Why
Ministry of
Agriculture
of the
Czech
Republic
The ministry of Agriculture of the Czech
Republic wants to have objective and
timely tool for the assessment of forest
health status, systematically for the
entire area of the country. Based on the
analysis of the outputs, subsidies shall
be distributed to target the most
affected forest owners. Local forest
owner want to know current extend,
spatial and temporal trends of forest
health status decay in order to plan the
forest activities.
Outdated forest health monitoring
programme using static forest damage
zones established 20 years ago, strong
focus on abiotic sulphur dioxide emissions,
which are no longer prevailing damage
factor of Czech forests. Forest health
monitoring using Landsat data with
limited spectral and temporal
performance. Subsidies for forest owners
affected by the reduction in forest value
doesn’t correspond to actual salvage
felling volumes on municipality levels.
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Local forest
owners,
including
Forests of
the Czech
Republic
and
Wallonia
Web-based service for both the
Ministry of Agriculture and local forest
owners. The service will provide both
municipality-level information on forest
health (each municipality will be
assigned to one of four classes) for the
purpose of subsidies re-distribution and
several thematic layers describing the
actual forest health and its trends on
forest compartment level (i.e. pixel size
of 20m x 20m). Local forest owners in
Czech Republic and pilot sites in Finland
and Wallonia will also benefit from the
availability of thematic layers on forest
health on the Wuudis platform, where
both forest management plan and the
forest health layers can be used in a
mobile environment.
Limited knowledge on timely forest
health information for pro-active forest
management – e.g. current extent of
decaying forests and their spatial
trajectory
8.2.2 Motivation and strategy
Our main motivation for this pilot is to develop a new methodology for forest health
assessment based on Copernicus satellite data. This allows us to assess the forest health of
the entire area of Czech Republic and other temperate forest regions in Europe, while
reducing costs for field surveys and highly effective identification of forest owners eligible for
subsidies / tax relief. This pilot focuses on technological development of the processing of
Sentinel-2 optical data. Although the first pair of Sentinel-2 satellites has been launched
already in 2015 and 2017, there is no settled methodology for satellite data processing and
interpretation available for the Ministry of Agriculture and its associated organizations.
Utilizing the great potential of high-spatial and temporal resolution satellite data for forestry,
with special focus on forest health trends is thus the main goal of the pilot. In addition, the
forest owners will benefit from publicly available map server and implementation of the
layers on the Wuudis platform, where all forest health status maps will be published to allow
pro-active management of their forest properties.
8.2.3 Scope and limitations
The scope of this pilot is to provide timely and accurate information on forest health status
and its trends. By utilizing advanced methods of spatio-temporal data analysis of big satellite
data, the pilot will generate wall-to-wall cloud-free maps of forest health.
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The following limitations has been identified:
● satellite products retrieved from Sentinel-2 satellite data may not be sensitive to
describe forest health of heterogeneous, highly mixed forest plots (e.g. mixture of
broadleaved and coniferous forests, multi-layered forest canopies).
● spatial resolution of 20 m is too coarse to observe tree-level change in forest health.
Change in forest health of individual tree will result in sub-pixel change of observed
forest reflectance which may not be detectable. The minimum spatial unit of forest
health attribution is forest stand.
● it is challenging to separate different forest management activities (e.g. logging of old-
growth forest in its felling age vs. sanitation felling due to forest health decay). In the
pilot, we will use rich database of forest structural information to interpret the
intermediate satellite-based forest health maps.
● interpretation of forest health trends will be based on observed satellite reflectances.
Since the forest is an extremely heterogeneous environment where reflectances
change both in time (vegetation phenology) and space (vegetation structure), it may
be difficult to obtain cloud-free image of larger areas normalized to single observation
period. Through the use of advanced spatio-temporal analysis of the data, some
periods with high cloud cover (e.g. winter and spring months) may be unavailable for
the analysis due to lack of high quality data.
8.3 Pilot modelling with ArchiMate This section presents the "Forestry C1 Web-mapping service for the government decision
making modelling with ArchiMate" view point described using the ArchiMate standard.
8.3.1 DataBio forestry pilot 2.4.1 motivation view
Figure 39 describes the "Forestry C1 Motivation view" defined in the "Forestry C1 Web-
mapping service for the government decision making modelling with ArchiMate" view point.
Figure 39: Forestry C1 Motivation view
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8.3.2 DataBio forestry pilot 2.4.1 strategy view
Figure 40 describes the “Forestry C1 Strategy view” defined in the “Forestry C1 Web-mapping
service for the government decision making modelling with ArchiMate” view point.
Figure 40: Forestry C1 Strategy view
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8.4 Big Data infrastructure: Components and BDVA classification Figure 41 presents the big data components and assets used or developed in the pilot, using
the BDVA classification. The components are explained in Table 25.
Figure 41: Big data components and assets in pilot 2.4.1 Web-mapping service for the government decision making
Table 25: Listing of the components used or produced in the pilot 2.4.1 Web-mapping service
for the government decision making
Used in this pilot: Produced in this pilot:
• 1, 2 FMI map server, Wuudis platform
• 3 QGIS, NumPy
• 1 Lookup tables for product retrievals
• 2, 3, 4, 5 Processing chain of S2 data
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• 4 Matlab
• 5 Python, GDAL, SNAP
• 6 QGIS, SNAP
• 7 FMI map server
• 8 Sentinel-2 satellite images
• 9 Thematic raster maps
• 10 In-situ validation data
• 6 Cloud-free Sentinel-2 images
• 7 Forest health maps
8.5 Pilot evaluation plan
8.5.1 High level goals and KPIs
There are five KPI’s related to the pilot:
• Systematic production of Sentinel-2 L3 product / spatio-temporal analysis using all available Sentinel-2 data to yield cloud-free data for user-defined dates.
• Production of thematic layers of forest health status, and its trajectories between 2015 and 2018. Thematic layers will be based on vegetation indices and forest quantitative products, which will be identified as sensitive to forest health.
• Validation and interpretation of forest health status and its trends based on extensive in-situ data collection and feedback from users
• Publication of forest health maps on dedicated map server
• Distribution to third parties via WMS/WFS service (e.g. Wuudis)
8.6 Initial roadmap Pilot implementation will start with the establishment of wall-to-wall data archive of
atmospherically corrected Sentinel-2 observations for the Czech Republic and Wallonia
(Q1/2018) and systematic production of cloud-free country mosaics using advanced spatio-
temporal analysis (Q2/2018).
In the next phase, interpretation of cloud-free surface reflectances will be performed via
vegetation indices and forest quantitative products (Q4/2018) and its validation against both
in-situ data collection and feedback from users (Q1/2019).
Finally, the thematic products of forest health and its trends will be published on a dedicated
map server (Q2/2019) and published to third parties (e.g. Wuudis platform) via WMS/WFS
services (Q4/2019).
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Figure 42: Timeline of pilot 2.4.1, Web-mapping service for the government decision making
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Pilot 2.4.2: Shared multiuser forest data
environment 9.1 Pilot overview
9.1.1 Pilot introduction
The Finnish Forest Centre has an important role to activate the different actors of the forestry
sector to utilize Big Data and the third parties to develop new solutions and applications for
forest owners and other actors. Currently about 80 percent of private Finnish forestry estates
have laser scanned and analysed forest resource data available online. The coverage will be
100 percent by 2020. To make use of this information, the governmental body Finnish Forest
Centre (METSAK) provides an eService called Metsään.fi to make this forest resource
information available for citizens free of charge. Metsään.fi eService is in constant
development by METSAK.
The plan is to pilot presenting crowdsourced forest data and possible new functionalities
related to it in Metsään.fi eService and therefore enhance the use of Metsään.fi and
METSAK’s forest resource data. The collecting methods are also aimed to increase the amount
of METSAK’s forest resource data.
In the DataBio project, Big Data partners will integrate their existing market-ready or almost
market-ready technologies to the forest databases with METSAK and the resulted solutions
will be piloted with the forestry sector partners, with associated partners and other
stakeholders e.g. public policies related to nature conservation, infrastructure or landscape
or town plans. This integration applies to the pilot 2.2.1: Easy data sharing and networking.
This pilot is developed in Task 2.4.2 “Shared multiuser forest data environment”, under WP2
Forestry pilot and Task 2.4 “Forest data management services (forecast/predict)”. The
involved partners are METSAK, VTT.
9.1.2 Pilot overview
At the moment, there are two recognized areas on crowdsourcing solutions to be piloted:
showing quality control data for young stand improvement and early tending for seedling
stand, and storm damage data. Other possible crowdsourced data, such as other forest
damage than storm damage data, will be evaluated during the project. Another pilotable topic
is the open-data interface to environmental and other public data in Metsään.fi databases.
This topic is highly dependable of development of the Finnish forest legislation and piloting it
will also be evaluated later during this project.
This pilot specifies the requirements for refining and showing the crowdsourced forest data
to Metsään.fi users. The implementation of the new functionalities and data-presenting will
be carried out in collaboration with Metsään.fi’s development team and other METSAK’s
projects. This pilot gives specifications to other projects and follows up the implementation
according to these specifications.
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Table 26: Summary of pilot 2.4.2 Shared multiuser forest data environment (ISO JTC1 WG9
use case template)
Use case title 2.4.2 Shared multiuser forest data environment
Vertical (area) Forestry
Author/company/email
Anu Kosunen / METSAK [email protected]
Actors/stakeholders and their roles and
responsibilities
Forest owners and forestry operators as Metsään.fi eService users. The Finnish Forest Centre (METSAK) admin users who use and refine the forest resource data and make it available for Metsään.fi users.
Goals To enhance the use of Metsään.fi eService and the use of METSAK’s forest resource data.
Use case description Specifying the requirements for new information and functionalities of Metsään.fi eService and implementing them in collaboration with Metsään.fi development team and other METSAK’s projects. This pilot gives specifications to other projects and follows up the results of implementation.
Current solutions
Compute(System) METSAK’s internal systems related to forest resource data.
Storage Databases for METSAK’s internal forest resource data system, for publishing forest resource data for Metsään.fi and Metsään.fi. File system for map materials.
Networking Web based solution for Metsään.fi users
Software Metsään.fi eService
Big data characteristics
Data source (distributed/centralized)
Centralized forest resource data system as main data source. Original data source for forest resource data can be laser scanning, field measurement, growth modelling or notification from forest owner or forestry operator. Other data sources for Kemera financing data, forest use declarations, access and authorization.
Volume (size) 200 GB of forest resource data in the beginning of 2017
Velocity (e.g. real time)
New forest inventory once in a decade per area. Constant other updates from field measurements, quality control, forest owners’ forest management plans and other notifications from forest owners and forestry operators.
Variety (multiple datasets,
mashup)
Multiple datasets: tree stand basic data, tree stand strata, growth place (site quality)
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Variability (rate of change)
Same as above (velocity).
Big data science (collection, curation,
analysis, action)
Veracity (Robustness Issues, semantics)
The data source must be saved within the forest resource data (e.g. data from forest owner vs. measured and analyzed data)
Visualization The user interface is the existing Metsään.fi eService and its map views. For METSAK admin users there are also existing internal systems with which the data is browsed and handled.
Data quality (syntax) Collected forest damage data and quality control data must be consistent with the specific standards.
Data types Tree stand basic data, tree stand strata data, growth place data (site quality), location data, time stamps.
Data analytics Storm damage generalization, national averages of work quality.
Big data specific challenges (Gaps)
To balance between data publicity and privacy, to adapt to the new Finnish Forest Act being revised at the moment and to take into account both public authorities’ and Metsään.fi eService users’ needs.
Big data specific challenges in bio-
economy
To maintain the consistency of data and the usability of new data and functionalities from the Metsään.fi user point of view to support better forest management and therefore bio-economy.
Security and privacy technical
considerations
There are both public and private data in Metsään.fi eService. Personal and forest estate specific information are largely private. The Finnish Forest Act sets demands on data publicity and privacy issues.
Highlight issues for generalizing this Use
case (e.g. for ref. architecture)
Using data standards in the interfaces. Visualizing complex data in a logical way for every “straw man”.
More information (URLs)
https://www.databio.eu/en/
Note: The Finnish Forest Act influences significantly this pilot, especially regulations on open and private forest data and demands for METSAK on offering specific forest data to the private forest owners.
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9.2 Pilot case definition
9.2.1 Stakeholders and user stories
Table 27: Stakeholders and user stories of pilot 2.4.2 Shared multiuser forest data environment
Who I want to Why
Forest owner I want to see relevant storm damage
observations and possible forest
damage areas on map, and to see the
quality control data concerning my
forests and the national average of
the quality control data.
To take the action needed to diminish the
damage and prevent further damages in
my forest.
To follow and evaluate the quality of
work of the forest operator I have made a
contract with.
Forestry
operator
I want to see storm damage
observations and possible storm
damage areas on map, to see my
quality control data in one place and
to see the national averages on
quality control data.
To contact the forest owners in the area
to offer silvicultural work to diminish the
damage or prevent future damages.
To follow my quality of work more easily
and compare my quality of work to the
national level.
METSAK user
as data and
system
administrator
I want to refine the crowdsourced
data (storm damage data, quality
control data), have the new storm
damage observations in METSAK's
internal system and increase the
amount of quality control data.
To show Metsään.fi users the possible
storm damage areas, update the forest
resource data according to storm damage
observations, calculate more precise
national averages on quality control and
offer it to Metsään.fi users.
9.2.2 Motivation and strategy
This pilot aims to enhance the use of the Metsään.fi eService and the amount and use of
METSAK’s forest resource data through collaboration between Metsään.fi development team
and other METSAK’s projects. The pilot consists of producing requirement specifications for
showing new data and functionalities in Metsään.fi. A possible new way to collect forest
resource data is crowdsourcing. At the moment, there are two recognized solutions for this:
collecting storm damage data and collecting quality control data for young stand
improvement and early tending for seedling stand. Other solutions might come up later
during the project.
The user interfaces for presenting quality control and storm damage data and possible new
functionalities related to them are defined in this pilot. The interfaces between information
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systems or applications are defined in other METSAK’s projects. For example, if some mobile
applications for collecting data are to be developed, the interfaces between the mobile
application and METSAK’s internal services and systems are defined in other projects.
The key problem-solving capacity is that forest owners can better respond to storm damages
according to new information and diminish the damages and prevent further or future
damages in their forests. Forest owners can follow the quality of work being done in their
forests and compare it to the national quality averages. This supports better forest
management and the bio-economy.
Forest operators can offer forest owners silvicultural work in storm damage areas, follow the
quality of their own work and compare it to the national quality averages.
METSAK users are able to update the forest resource data according to storm damages and
to offer Metsään.fi users more information and tools on storm damages and quality control
to support better forest management.
9.2.3 Scope and limitations
This pilot operates in an existing system environment of METSAK’s producing new data and
functionalities related to that data for Metsään.fi users. The pilot scope is to:
• create requirement specifications for Metsään.fi updates concerning crowdsourced data
• create testing plans for Metsään.fi updates specified in this pilot
• carry out acceptance testing of Metsään.fi update specified in this pilot
• review the requirement and interface specifications of new data collection methods for collecting crowdsourced data
• review forest data standardization updates concerning quality control data
• evaluate other possible crowdsourced data and open data to be piloted
The limitations in this pilot are caused by:
• Operating in METSAK’s system environment and its development: this sets both content and schedule limitations when specifying and testing changes in Metsään.fi.
• The legislation (The Finnish Forest Act) and its changes: data sensitivity and access must be taken into account.
• The forest data standard: all the forest data interfaces must be consistent with the forest data standard.
9.3 Pilot modelling with ArchiMate
9.3.1 DataBio forestry pilot 2.4.2 motivation view
Figure 43 describes the "Forestry C2 Motivation view" defined in the "Forestry C2 Shared
multiuser forest data environment modelling with ArchiMate" view point.
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Figure 43: Forestry C2 Motivation view
The element “Improve forest management” is further explained by the following description:
“In Finland, there are vast amounts of passively owned forests that could serve both financial
and environmental needs for forest management more effectively. Also, many novel forest
health problems are likely to occur in the future without innovative forest management
solutions that can enable appropriate management activities. A major concern of forest
authorities is how to encourage forest owners to better manage their assets. The Finnish
Forest Centre provides Metsään.fi eService for forest owners and forestry operators to
support the management of privately owned forests and to enhance the use of forest
resource data. Metsään.fi eService is constantly improved by means of increasing the forest
data and functionalities related to it.”
9.3.2 DataBio forestry pilot 2.4.2 strategy view
Figure 44 describes the "Forestry C2 Strategy view" defined in the "Forestry C2 Shared
multiuser forest data environment modelling with ArchiMate" view point. Table 28 further
specifies some of the view's elements.
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Figure 44: Forestry C2 Strategy view
Table 28: Explanation of specific elements in the Forestry C2 Strategy view
Name Description
Analyse and present data The ability to process acquired data using a set of rules and
algorithms. Present the result to the user in a preferred format on
the preferred devices, e.g. map layer on a chart plotter.
Collect sensor data The ability to collect measurements from a sensor device through a
robust interface
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9.4 Big Data infrastructure: Components and BDVA classification The existing technical environment of Metsään.fi eService concerning big data is described in
Figure 45. The components are explained in Table 29. This pilot is about further development
of Metsään.fi eService and adding new forest resource data to METSAK’s forest resource data
system to be utilized.
Figure 45: Big data components and assets in pilot 2.4.2 Shared multiuser forest data environment
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Table 29: Listing of the components used or produced in the pilot 2.4.2 Shared multiuser
forest data environment
Used in this pilot: Produced in this pilot:
• 1, 2 Metsään.fi user interface
• 3, 4, 5, 6, 7 Processing chain of forest resource data
• 8, 9 Exchanged data with Metsään.fi users related to
Metsään.fi services and data from other forestry
operators
• 10 Laser scanning, aerial photographing, field
inventories, notifications from Metsään.fi users
• 11 Combining data from different sources
• 12 Integration to METSAK’s other internal systems
• 13 Access control and strong authentication (Vetuma,
KATSO)
• 14 METSAK’s system databases: forest resources,
customer information, publishing, financing and forest
use (Oracle DB, SQL Server)
• 15 METSAK’s map server (ArcGIS) and file server
• 16 Forest resource data, customer information,
financing, forest use
• 17 Laser scanned data
• 18 Geometry: compartments, forest estates, nature
objects, flow models.
• 19 Thematic raster maps, aerial photographs
• 20 Descriptions of forest resource data, suggested
operations, forest estate data, Instructions etc.
• 1 New maps and
functionalities to
Metsään.fi concerning
crowdsourced data
• 2 Prescriptions of
quality control for
Metsään.fi users
• 3 Bringing generalized
storm damage data to
Metsään.fi
• 4 Producing needed
updates on forest data
standard to collect
quality control data
with mobile devices
• 5 Producing new map
materials to Metsään.fi
concerning
crowdsourced data
9.5 Pilot evaluation plan
9.5.1 High level goals and KPIs
There are several KPIs for this pilot to evaluate the results yearly and in the end of the project.
They were defined in the project proposal phase and updated in the beginning of this project
based on the Finnish Forest Act at the time being. The Forest Act is being revised at the
moment. The pilot evaluation plan will be updated based on the coming Forest Act.
The KPIs in this pilot are as follows:
● The present amount (in the beginning of 2017) of METSAK's forest resource data is
around 200 GB. The amount is expected to increase by approximately 100 GB per
year during this project, amounting to around 500 GB by the end of 2019.
D2.1 – Forestry Pilot Definition H2020 Contract No. 732064 Final – v1.0, 30/6/2017
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● The coverage of forest resource data in Metsään.fi eService is now around 11 million
hectares. The amount is expected to increase by 800 000 hectares per year,
amounting to around 13.4 million hectares by the end of 2019.
● The amount of data available to be downloaded for forestry operators' own
information systems is now around 1.5 million hectares. The amount is expected to
increase by one million hectares per year, amounting to around 4.5 hectares by the
end of 2019.
● The amount of forest owner as Metsään.fi end users is now around 70 000. The
amount is expected to increase as follows: 85 000 in the end of 2017, 100 000 in the
end of 2018 and 110 000 in the end of 2019.
● The amount of forestry service providers (FSPs) as end user groups is now around
380. The amount is expected to increase as follows: 550 in the end of 217, 650 in the
end of 2018 and 750 in the end of 2019. Note: The forestry operator is the actual
end user level under the FSPs.
9.6 Initial roadmap The technical design and implementation of bringing the new forest data available for
Metsään.fi eService is carried out in other METSAK’s projects and the further development of
Metsään.fi. All METSAK’s forest resource data is saved in a centralized forest resource data
system. Metsään.fi eService uses that data through a publishing database and other existing
interfaces. The data is not saved in Metsään.fi eService itself.
The implementation schedule follows the schedule of Metsään.fi development plans. The
development is constant and the publishing schedule is updated regularly due to a large
amount of dependencies with other system development and technical environment issues
in METSAK.
The implementation plan for this pilot proceeds on as follows. The milestones listed appear
in the following figure.
1. Create initial plans and descriptions for the pilot (Q3/17)
Milestone: Initial plans and descriptions ready. Components identified.
2. Specify and develop the needed data with METSAK’s other parties (Q3/17).
3. Specify the detailed use cases for the pilot system (Q4/17).
4. Assist implementing new data to the pilot environment (Q2/18).
5. Take part into standardizing work (Q3/17-Q3/18).
6. Collect other pilot topics under crowdsourcing and open data issues (Q3/17-Q3/18).
7. Carry out the intermediate KPI follow-up.
Milestone: Detailed use cases ready. Standard changes ready.
8. Follow the implementation of the new features to the pilot system.
9. Assist gathering all data available and show it on the user interface.
10. Carry out the acceptance testing of the pilot implementation.
Milestone: Pilot implementation ready.
D2.1 – Forestry Pilot Definition H2020 Contract No. 732064 Final – v1.0, 30/6/2017
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11. Evaluate additional pilot topics collected.
Milestone: Additional pilot features planned and scheduled.
12. Iterate the needed steps 2-10 for the additional pilot features and the KPI follow-up.
Milestone: Final implementation completed.
13. Evaluate and report the results in the pilot.
Milestone: Pilot results documented. Final pilot KPI measurement done.
Possible new crowdsourcing or open data features are evaluated continuously in the project
and will be implemented in an iterative way to the pilot if applicable. All new bigger features
are split into small parts to enable fast deployment and testing cycles. After developed
features are tested by the development team and deployed to the production environment,
these features are ready for the DataBio pilot case.
Figure 46: Timeline of pilot 2.4.2, Shared multiuser forest data environment
D2.1 – Forestry Pilot Definition H2020 Contract No. 732064 Final – v1.0, 30/6/2017
Dissemination level: PU -Public Page 115
References
Reference Name of document (include authors, version, date etc. where applicable)
[REF-01] DataBio website. www.databio.eu. Retrieved 2017-06-20.
[REF-02] ArchiMate® 3.0 Specification. http://pubs.opengroup.org/architecture/ArchiMate3-
doc/toc.html. Retrieved 2017-06-29.