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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
Institut für Photogrammetrie und GeoInformation
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
Institut für Photogrammetrie und GeoInformation
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
Institut für Photogrammetrie und GeoInformation
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
Institut für Photogrammetrie und GeoInformation
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
Institut für Photogrammetrie und GeoInformation
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
Institut für Photogrammetrie und GeoInformation
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
Institut für Photogrammetrie und GeoInformation
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
Institut für Photogrammetrie und GeoInformation
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
Institut für Photogrammetrie und GeoInformation
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
Institut für Photogrammetrie und GeoInformation
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
Institut für Photogrammetrie und GeoInformation
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
Institut für Photogrammetrie und GeoInformation
... 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
Institut für Photogrammetrie und GeoInformation
Institut für Photogrammetrie und GeoInformation
Conclusions
Institut für Photogrammetrie und GeoInformation
• 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