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EC/FAO Programme on Information Systems to Improve Food Security Decision-Making in
the European Neighbourhood Policy (ENP) East Area
Training on introduction of Geographic Information System (GIS) to improve crop-
forecasting system in Armenia
Armenian State Agrarian University, Yerevan, Armenia
January 25 – February 7, 2012
- REPORT -
1. Background
A two week training was jointly organized by the ARMSTATEHYDROMET (hereinafter:
Hydromet) and FAO under the “EC/FAO Programme on Information Systems to Improve Food
Security Decision-Making in the European Neighbourhood Policy (ENP) East Area” from January
25 to February 7, 2012. The Programme is financed by the European Commission and implemented
by FAO. The Programme aims at improving food security by enhancing the national capacity to
generate, analyse, communicate and mainstream more relevant and reliable information into policies
and programmes. The training took place at the Armenian State Agrarian University.
2. Training objectives
Objective of the training was to get participants acquainted with geographic information systems
and their application in agriculture. The training provided both theoretical and practical knowledge
and skills in data collection, database management and computer mapping in order to work
independently with ArcGIS software, GIS project design and management. The knowledge and
skills acquired will be immediately applied to used for the improvement of Agromet Bulletin. The
training was conducted by a national consultant, Hovik Sayadyan (Professor, Lecturer of GIS at
Yerevan State University).
3. Participation
The training was attended by 15 participants.
Training was organised for the stakeholders of the Programme concerned with crop forecasting,
including mainly staff from Hydromet (Agrometeorological and Climatology Units, 13 participans),
Ministry of Agriculture (Agricultural Planning Department, 2 participants). The training was also
attended by some members of the Crop Forecasting Working Group, 2 members. The objective of
Crop Forecasting Working group is to provide decision-makers with reliable information on crop
forecasting through improving crop forecasting system in Armenia.
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The list of participants is provided in Annex 1.
Figure 1. Training session
Figure 2. Group picture
4. Process
Introductory speeches
The participants were welcome by the Country Coordinator of the EC/FAO Food Security
Information Systems to improve decision-making. The Country Coordinator noted the importance to
improve crop-forecasting system in Armenia taking into account the problems related to climate
change and the importance of producing the Agromet Bulletin to provide timely information to
stakeholders, including farmers.
The training itself was very technical. Course was composed of 10 lectures, which include
theoretical part and exercises. Each lecture/exercise was composed of 4 hours-1 hour lecture and 3
hours of exercises, in total it made 10 hours of lecture and 30 hours of exercises.
Before the initiation of the training Armstatehydromet provided the following information on:
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- Data set of rainfall data on 38 stations for 1 month during the crop season.
- Data set of crop yield on one cereal crop.
Main topics of the training were:
Fundamentals of GIS: Introduction, defining of GIS, Components of GIS;
Displaying map data: navigating a map, looking at feature attributes; Symbolizing and
classifying features and rasters, Labeling features;
Database management: Database data models, creating a database, GIS database
applications, developments in database;
Spatial data analyses: Spatial data models and structures, modeling surfaces and networks;
Data input and editing (Presenting data): Methods of data input, data editing, towards an
integrated database; production and export of thematic maps including labeling and legend
insertion into Agromet Bulletin, production of color tables to assign legend to the thematic
maps;
Data analysis: Measurements in GIS-lengths, perimeters and areas, queries, reclassification,
calculations; performing interpolation of the main agrometeorological variables (rainfall,
temperature, crop yield) using Inverse of Distance method, Overlay the DEM layers into
maps;
Analytical modeling in GIS: Process models, modeling physical and environmental
processes, modeling human processes; starting a model, building a model, enhancing a
model;
Remote sensing and GIS: Fundamentals of remote sensing, satellite imagery, aero-photos,
satellites for the study of natural resources, links between remote sensing and GIS; raster
data, raster analysis, storing raster, import NDVI from METEOR-AVHRR
(http://www.metops10.vito.be/metop-S10_pages/main.html#distribution), produce a mask to
mask-out areas that are not interesting (e.g. non agricultural areas);
Global positioning systems (GPS) and GIS: Principals of global positioning systems,
different GPS systems, GPS link to GIS environment;
GIS project design and management: Problem identification, designing a data model,
project management, implementation problems, project evaluation.
Each presentation was followed by practical exercises to strengthen the capacities of the trainees in
using the new technique.
The training was designed and organized in order to engage all participants in discussions and
reflect on appropriate recommendations for all state institutions involved in crop forecasting in
Armenia.
The training agenda is provided in Annex 2.
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The participants were very much interested in the materials provided by the Lecturer. They agreed
that, the duration of the training was insufficient taking into account the complexity and volume of
information provided More time was needed for practical exercises. The Lecturer confirmed his
readiness to assist the trainees in further practical work upon a request. The manual on GIS was
provided to Hydromet for reference.
5. Evaluation of the training
Participants were asked to assess the relevance and effectiveness of the training at the end of the
training. The evaluation forms and the results of the surveys are presented in Annex 3.
6. Conclusions and follow-up actions
The training was successful in meeting its objectives. At the end of the two week training,
participants were able to use the models and to perform analytical modelling of GIS independently,
in particular:
- Produce and export thematic maps including labeling and legend insertion into Agromet
Bulletin.
- Perform interpolation of the main agrometereological variables (rainfall, temperature, crop
yield) using the Inverse of Distance method.
- Extract area of statistics for specific shp. Files (Marz administrative division)
- Overlay the Digital Evaluation Model layers into maps.
- Produce a Mask to mask-out areas that are not interesting. (i.e. non agricultural areas)
- Import data from Excel files.
- Import NDVI from METOP-AVHRR (http://www.metops10.vito.be/metop-
S10_pages/main.html#distribution) into GIS.
- Produce colour table to assign legend to the thematic maps.
The discussions during the training demonstrated that there is strong interest from the national
institutions in improving crop forecasting in Armenia. The training was successful in gathering both
users and producers of information. It is worthwhile noting that the Ministry of Agriculture (MoA)
is both producer of information (providing operational data) and user of the Agromet Bulletin for
policy-making. There was excellent collaboration between the institutions involved in crop
forecasting, in particular Hydromet and MoA. The training clearly demonstrates that this
collaboration is indispensable for improving crop forecasting and will need to be institutionalized
for sustainable results.
Follow up actions agreed by the participants are the following:
Trainees, in particular Hydromet staff, will use the newly acquired capacity in GIS for
compiling the Agromet Bulletin. The first draft of the updated Bulletin is planned to be
issued and disseminated to Marz support centres end of March.
The Programme will organize a number of other training sessions for improving crop
forecasting
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Annex 1. List of participants
Two-week GIS training to improve crop forecasting, in particular to assist in development of
Agromet Bulletin
1. Armine Sahakyan, Agrometeorological forecast division, leading specialist-
2. Nelli Arakelyan, Agrometeorological forecast division, first class specialist
3. Susanna Shindyan, Climate research division, first class specialist [email protected]
4. Ashkhen Iritsyan, Climatology division, first class specialist [email protected]
5. Azat Safaryan, Climatology division, first class specialist – [email protected]
6. Narine Saghoyan, Hydro meteorological information service division, senior specialist -
7. Lusine Yeritsyan, Hydro meteorological information service division, leading specialist -
8. Marine Beluyan, Meteorological forecast division, leading specialist -
9. Andryusha Avagyan, Meteorological forecast division, leading specialist – [email protected]
10. Mariam Mkhitaryan, Agrometeorological division, leading specialist –
11. Lilit Aghajanyan, Hydrography division, senior specialist – [email protected]
12. Edgar Yeganyan – Hydrography division, first class specialist – [email protected]
13. Diana Hovhanissyan, Applied Climatology Division - [email protected]
14. Heriknaz Lemberyan, MoA, Agricultural Planning Dpt. - [email protected]
15. Artur Petrossyan, MoA, Agricultural Planning Dpt - [email protected]
16. Valentina Grigoryan, Advisor to Director of Armstatehydromet Service -
17. Zara Petrossyan, Head of Hydrometereological Operation Centre of Armstatehydromet
Service - [email protected]
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Annex 2. Training agenda
EC/FAO Food Security Information Systems to improve decision-making
TRAINING TOPIC: GIS application in Agro-meteorology
Instructor: Dr.Hovik Sayadyan
E-mail: [email protected]
Phone: +374 91382978
Training objective
The objective of the training is to provide assistance to Armstatehydromet in application of the GIS
to improve crop forecasting system in Armenia. The application of GIS could bring all different
aspects of agriculture and agro-meteorology together and enhance effective decision making
through different analyses and data processing.
Two week training on GIS basic course and its application in agro-meteorology, will assist the
trainees:
to understand GIS and its application for the analyses of agromet and phoenological data
to have both theoretical and practical knowledge in data collection, database management
and computer mapping
to work independently with ArcGIS software, GIS project design and management
Target group
15 staff of Armstatehydromet Service and other national stakeholders.
The list and positions were provided by Armstatehydromet Service.
Venue and resources
Training will take place in the Armenian State Agrarian University (ASAU). The room is furnished
with tables, whiteboard, 4 PCs with GIS software etc. The trainees will ensure the availability of
personal computers. All this is provided by Armenian State Agrarian University free of charge.
Some other technical staff, e.g. stationery, memory sticks are provided by the Programme.
Training outline
The course is offering an understanding of geographic information systems and their application for
the study of agricultural issues.
Course is composed of 10 lectures, which include theoretical part and exercises. Each
lecture/exercise is composed of 4 hours-1 hour lecture and 3 hour of exercises, in total it makes 10
hour of lecture and 30 hours of exercises.
Before the initiation of the training Armstatehydromet is supposed to provide the following
information:
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- Data set of rainfall data on 38 stations for 1 month during the crop season.
- Data set of crop yield on one cereal crop.
Lecture 1 (January 25): Fundamentals of GIS: Introduction, defining of GIS, Components of
GIS
Exercise 1: Displaying map data, navigating a map, looking at feature attributes
Lecture 2 (January 26): Displaying data: Symbolizing and classifying features and rasters,
Labeling features
Exercise 2: Changing symbology, symbolizing features and rasters, classification by standard and
manual methods, using graduated and chart symbols
Lecture 3 (January 27): Database management: Database data models, creating a database, GIS
database applications, developments in database
Exercise 3: Overview of tables, database management systems, queries on tables, joining and
relating tables, summarizing tables, import data from Excel files
Lecture 4 (January 30): Spatial data analyses: Spatial data models and structures, modeling
surfaces and networks.
Exercise 4: Using location queries, preparing data for analyses (dissolve features, clipping layers,
etc.), buffering features, overlaying data, calculating attribute values, extract area of statistics for
specific shp. files (Marz administrative division)
Lecture 5 (January 31): Data input and editing (Presenting data): Methods of data input, data
editing, towards an integrated database
Exercise 5: Basic elements of map design, choosing symbols, labels and titles, setting up scale bars,
choosing coordinate system. Production and export of thematic maps including labeling and legend
insertion into Agromet Bulletin. How to produce color table to assign legend to the thematic maps
Lecture 6 (January 1): Data analysis: Measurements in GIS-lengths, perimeters and areas,
queries, reclassification, calculations
Exercise 6: Perform interpolation of the main agrometeorological variables (rainfall, temperature,
crop yield) using Inverse of Distance method, Overlay the DEM layers into maps
Lecture 7 (February 2): Analytical modeling in GIS: Process models, modeling physical and
environmental processes, modeling human processes
Exercise 7: Starting a model, building a model, enhancing a model
Lecture 8 (February 3): Remote sensing and GIS: Fundamentals of remote sensing, satellite
imagery, aero-photos, satellites for the study of natural resources, links between remote sensing and
GIS
Exercise 8: Raster data, raster analysis, storing raster, import NDVI from METEOR-AVHRR
(http://www.metops10.vito.be/metop-S10_pages/main.html#distribution), produce a mask to mask-
out areas that are not interesting (e.g. non agricultural areas)
8
Lecture 9 (February 6): Global positioning systems (GPS) and GIS: Principals of global
positioning systems, different GPS systems, GPS link to GIS environment
Exercise 9: Obtaining GPS points, Input of GPS data into GIS environment, link GPS data with
other GIS layers
Lecture 10 (February 7): GIS project design and management: Problem identification,
designing a data model, project management, implementation problems, project evaluation
Exercise 10: Examples of GIS project design and management
Note: Copies of lecture handouts and related materials, as well as copies of exercises that trainees
did during the training will be distributed to the trainees on memory sticks.
9
Annex 3. Evaluation results
Evaluation Form
A. What is, according to you, the level of concordance between the training programme and the
objectives of EC/FAO Programme on food security Information Systems?
Excellent very good good average bad
1.Fundamentals of GIS: Introduction, Components of GIS, Displaying map data, navigating a map,
looking at feature attributes
Excellent very good good average bad
2:Displaying data: Symbolizing and classifying features and rasters, Labelling features classification
by standard and manuall methods, using graduated and chart symbols
Excellent very good good average bad
3.Database management: Database data modelsGIS database applications, developments in
database, queries on tables, joining and relating tables
Excellent very good good average bad
4.Spatial data analyses: Spatial data models and structures, modeling surfaces and networks, using
location queries, preparing data for analyses, buffering features, overlaying data, calculating atttribute
values, extract area of statistics for specific shp. files (Marz administrative division)
Excellent very good good average bad
5: Data input and editing: Methods of data input, data editing, towards an integrated database,
choosing coordinate system. Production and export of thematic maps including labeling and legend
insertation into Agromet Bulletin.
Excellent very good good average bad
6: Data analysis: Measurements in GIS-lengths, perimeters and areas, queries, reclassification,
calculations, perform interpolation of the main agrometeorological variables (rainfall, temperature,
crop yield).
Excellent very good good average bad
7: Analytical modeling in GIS: Process models, modeling physical and environmental processes,
modeling human processes, building a model, enhancing a model
Excellent very good good average bad
10
8: Remote sensing and GIS: Fundamentals of remote sensing, satellite imagery, aero-photos, links
between remote sensing and GIS, raster analysis, import NDVI from METEOR-AVHRR
(http://www.metops10.vito.be/metop-S10_pages/main.html#distribution)
Excellent very good good average bad
9: Global positioning systems (GPS) and GIS: Principals of global positioning systems, different
GPS systems, GPS link to GIS environment
Excellent very good good average bad
10: GIS project design and management.
Excellent very good good average bad
Give your comments:
…………………………………………………………………………………………………..
B. Do you estimate that your training will be beneficial to the activities of your Service or
Institution?
Yes No
C. Estimate how this training programme will serve in your activities in your country?
……………………………………………………………………….
D. Evaluate the level of this training according to your own instruction level and your
experience.
appropriate level too high level too low
If the level did not suit you, give explanations: ……………………………………………….
E. Do you estimate that the length of your training was sufficient?
Yes No
If no, what is according to you, the length that is the more suitable?
………………………………………………………………………………………………….
F. How do you estimate the organization of the training programme?
Excellent very good good middle mediocre
Comments: ……………………………………………….
…………………………………………………………………………………………………..
G. Please indicate any comments that appear important and relevant on any non-didactical
aspects that were not mentioned above.
…………………………………………………………………………………………………...
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H. Do you have some recommendation for FAO and EC for the improvement of such kind of
training session?
…………………………………………………………………………………………………...
Date ………………………
Results of the evaluation
17 participants have participated at the training and 15 of them filled out the questionnaire. The
results of the survey among the respondents were as follows:
The majority of the respondents (80%) acknowledged that the relevance of training and level of
concordance between the training program and the objectives of EC/FAO Programme on Food
Security Information Systems was very high (excellent and very good) and only three respondents
considered that the level was good (Figure 1). Figure 2 illustrates the answers provided by the
respondents regarding the relevance of the specific sections of the training.
Figure 1. Level of concordance
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Figure 2. Relevance of specific sections of the
training
All respondents considered that their service or institution will benefit from the training. Almost all
respondents (14 out of 15) estimated that the level of the training was appropriate taking into
account their knowledge and experience.
However, as illustrated in Figure 3, about two-thirds of the respondents considered that the length of
the training was insufficient. This issue was discussed during break-time discussions: a number of
trainees estimated that more time was needed for practice as many aspects of the training were very
technical.
Figure 3. Duration of the training (sufficient or not)
The organization of the training was appraised positively. As shown in Figure 4, all respondents
found that it was very good or excellent.
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Figure 4. Organization of the training
In addition, all trainees were very satisfied with the Lecturer’s training capacity and teaching
methods. They highly appreciated the trainer’s skill and experience.
All trainees considered that it will be very useful to have the continuity of the training and as a
recommendation they suggested to organize this kind of trainings more often.
