Earth observation systems for quality control and update ... · Earth observation systems for...

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Institut für Photogrammetrie und GeoInformation

Earth observation systems for quality

control and update of geospatial

databases

Christian Heipke

IPI - Institut für Photogrammetrie

und GeoInformation

Leibniz Universität Hannover

Institut für Photogrammetrie und GeoInformation

Table of content

• Introduction

• Updating GIS databases from images

• A case study - WiPKA-QS

• Conclusions

Institut für Photogrammetrie und GeoInformation

Kansas Speedway, Kansas City, USA, Z/I Imaging Kalender 2002,

© M.J. Harden Associates Inc., Kansas City, Missouri, USA

Change due to land development

Institut für Photogrammetrie und GeoInformation

Change of coast lines

Juist, Westteil

© Thorenz,

NLWK 2005 Coast line approx.

1960

Institut für Photogrammetrie und GeoInformation

Glacier movement

Landsat images of Jakobshavn Isbrae, Greenland

Maas et al., PFG 2006

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Coherence-based results - example www.irea.cnr.it/webgis

Height changes

Institut für Photogrammetrie und GeoInformation

High resolution satellite imagery (1)

Ikonos, EROS, Quickbird, OrbView, ...

Institut für Photogrammetrie und GeoInformation

High resolution satellite imagery (2)

Space

platform

Launch

date

Orbital

height

Swath

width

No. of

pixels

GSD

pan

GSD

MS

Poin-

ting

along

Poin-

ting

across

[km] [km] [m] [m] [º] [º]

Ikonos Sep 24-99 680 11 13500 1 4 45 45

Eros A Dec 5-00 480 12,5 7800 1,8 - yes 45

Quickbird Oct 18-01 450 16,6 27000 0,6 2,4 30 30

Orbview 3 Jun 26-03 460 8 8000 1 4 45 45

Eros B Apr 25-06 600 16 20000 0,7 - yes 45

Cartosat-2 Jan 10-07 630 9,6 12000 1 - 45 45

Worldview 1 Sep 18-07 496 17,6 35000 0,5 - 45 45

Geoeye-1 Sep 6-08 680 15,2 35000 0,41 1,65 60 60

Worldview 2 Oct 8-09 770 16,4 35000 0,45 1,8 45 45

Pléiades 1 Dec 16-11 700 20 30000 0,65 2,6 yes yes

Institut für Photogrammetrie und GeoInformation

Some of the first Pléiades images

Paris, Louvre et Place de la Concorde - „naturellement“

1st P

léia

des s

ate

llite

, la

uched

Dec-1

6,

2011

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Small satellites

system launch GSD [m]

pan / MS

swath

[km]

remarks

UOSAT 12, UK 1999 10 / 20 10 / 30 CCD arrays

KITSAT 3,

South Korea

1999 15 MS 50

SunSAT,

South Africa

2000 15 52

Alsat 1, Algeria 2002 32 MS 600 DMC

BilSat 1, Turkey 2003 12 / 28 24 / 53 DMC arrays

BNSCSat, UK 2003 32 MS 600 DMC

NigeriaSat, Nigeria

TopSat, UK

Beijing-1, China

2003

2005

2005

32 MS

2.5 / 6.5

4 / 32

640

17

24

DMC

no TDI

DMC

Use of “off-the-shelf”

components, partially

CCD arrays instead

of CCD-lines

Cooperation in

disaster monitoring

constellation (DMC) –

in case of natural

disasters, mapping

within 24 hours

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1:25 000 1:50 000 1:100 000 1:200 000

World 33.5 % 65.6 % 55.7 % 95.1

%

%

from U.N. Cartographic Conference, Beijing 1993

State of world-wide mapping I

Institut für Photogrammetrie und GeoInformation

3,30,72,1

5

1,2

4,12,52

2,200,8

4

0,50,1

1,8

2,2

8,376,4

7,5

6,303,1

4,8

0,40

0,8

0

0 1 2 3 4 5 6 7 8 9 10

World

Afr

ica

Asia

Austr

alia

and O

ceania

Euro

peN

ort

h A

mericaSouth

Am

erica

1:25 000 1:50 000 1:100 000

1:200 000

%

global annual

updating rates U.N. Cartographic Conference,

Beijing 1993

State of world-

wide

mapping II

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Mapping and monitoring from space

• ... is needed

– terrestrial and airborne mapping cannot deliver up-to-

date information necessary for sustainable

development on a global scale

• ... is possible

– civilian remote sensing satellites available since 1972

– high resolution satellites (resolution in m-range and

below) available since 1999

– today many different systems in orbit

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Updating GIS databases

from images

Institut für Photogrammetrie und GeoInformation

Updating GIS databases from images

• need for high quality geospatial data in many areas of

the world

• aerial and satellite images provide high resolution views

of the world (implicit geospatial information)

• key task: how can users employ this valuable data

source, given

– their tasks

– existing geospatial data

– today’s digital technology

… automatic QC,

update and refinement

of existing GIS data-

bases using images

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Image: IKONOS, Space Imaging On the necessity of QC

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Completeness

Built-up Area

Grasland

Cropland

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Built-up Area

Grasland

Cropland

Correctness

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Positional Accuracy

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Currentness

Built-up Area

Grasland

Cropland

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geospatial data reality

(orthophoto)

Automatic comparison …

Concept for quality control and update

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A case study –

WiPKA-QS

WiPKA-QS: Wissensbasierter Photogrammetrisch-

Kartographischer Arbeitsplatz - Qualitätssicherung

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WiPKA-QS

• A cooperation between Leibniz Universität Hannover and

the Federal Agency for Cartography and Geodesy (BKG)

• A prototype software system for quality control and

update of ATKIS BasisDLM from images, installed at

BKG

• A semi-automatic design: the human operator stays in

control

• Use of regularly available data sources only

• GOAL: reduction of time for manual interaction by a

factor of 2

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GeoDataCentre of BKG

Background

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Reality

i.e. orthoimage

Automatic comparison ...

GIS database

Concept ...

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Adopted workflow

Orthophoto Decision by

human

operator

Automatic image

analysis

GeoDB

Visualisation

o.k.

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Example: orthophoto

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Example (ctd.): orthophoto and ATKIS

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Example (ctd.): areas with incorrect label

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selected for manual

processing

accepted

satellite image with

verification result

LU

H

knowledge-based

image analysis

part

ner

GIS

Example roads

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image analysis

GeoDB

visualisation

orthophoto

traffic light diagnosis

decision by human operator

o.k.

... back to the workflow - how good is it?

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System

(automatic)

Human

operator

(reference)

Accepted Rejected

Correct

Efficiency Interactive

Final Check

Incorrect

Undetected

Errors

Interactive

Final Check

Confusion matrix for diagnostics

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system

reference

accepted rejected

correct 72% 21%

incorrect 2% 5%

• Area objects

(2974)

• Roads

(816)

system

reference

accepted rejected

correct 62% 33%

incorrect 1% 4%

Results: Germany, 3 IKONOS scenes

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system

reference

accepted rejected

correct 64% 18%

incorrect 4% 14%

• Area objects

(375)

• Roads

(1117)

system

reference

accepted rejected

correct 59% 36%

incorrect 1% 4%

Results: North Africa, 3 IKONOS scenes

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system

reference

accepted rejected

correct 86% 8%

incorrect 4% 1%

• cropland

(2974)

• grassland

(816)

System

Referenz

accepted rejected

correct 81% 10%

incorrect 9% 0%

Results: Germany, 1 IKONOS scene

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system

reference

accepted rejected

correct 69% 22%

incorrect 5% 4%

• Area objects

(32 km2)

• Roads and

paths (2300) system

reference

accepted rejected

correct 65% 32%

incorrect 1% 2%

Results: Germany, RGB aerial images, 0.3m GSD

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... for one orthophoto, 2km 2km

• time for completely manual processing

4 h

• time for semi-automatic approach

1 h 20 min

Results: time

productivity increase

by factor of 3

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Conclusions

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• semi-automatic approach

– significant efficiency gain (factor 3)

– decisions remain with human operator

• “circular” approach, linking image and vector data

– enhance existing vector data using new image data

• useful approach, e. g. for

– internal data base quality control

– periodic data base update

– quality control of externally acquired data

• operational approach, implemented at BKG and another

federal German agency

– also part of DeCOVER, the German part of GMES

Conclusions

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