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
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Institut für Photogrammetrie und GeoInformation
Table of content
• Introduction
• Updating GIS databases from images
• A case study - WiPKA-QS
• Conclusions
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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
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Institut für Photogrammetrie und GeoInformation
Change of coast lines
Juist, Westteil
© Thorenz,
NLWK 2005 Coast line approx.
1960
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Institut für Photogrammetrie und GeoInformation
Glacier movement
Landsat images of Jakobshavn Isbrae, Greenland
Maas et al., PFG 2006
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Institut für Photogrammetrie und GeoInformation
Coherence-based results - example www.irea.cnr.it/webgis
Height changes
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Institut für Photogrammetrie und GeoInformation
High resolution satellite imagery (1)
Ikonos, EROS, Quickbird, OrbView, ...
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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
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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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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
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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
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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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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
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Institut für Photogrammetrie und GeoInformation
Updating GIS databases
from images
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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