Updating topographic map G100V
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Transcript of Updating topographic map G100V
INUTEK Nytårskur
Updating topographic map G100V
Table of contents:
1. Introduction2. 2-D updating of ice and water
2.1 Satellite data2.2 Method2.3 Examples
3. 3-D updating of G100V3.1 Satellite data3.2 Method3.3 Examples
4. Conclusion5. Perspective
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1. Introduction
Project title: Development of capacity and methods for a test production of new accurate and adequate G100V maps in Greenland
Project funded by: Dancea (Danish Cooperation for Environment in the Arctic)
The aim of the project:A test production of new topographic vector maps in scale 1:100.000 based on raw vectors from aerial photos produced by KMS (Danish Cadastre) in the period 1978-1987Update of the ice margin and proglacial lakes by remote sensing due to the changes in glacier size .
Cooperation:Asiaq, KMS, DTU Space, GRAS A/S DK
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1. Introduction
Project Areaca. 13’000 km²
2 different glacier types
A) Ice shield with calving glaciers, relatively smooth topology
B) Ice caps with valley glaciers in alpine terrain (Nuussuaq Halvø)
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2. 2-D updating of ice and water2.1 Satellite data:
11-07-2009 12-08-2009
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LANDSAT 7Benefits: Free of charge, fine resolution (30m), full coverage of project area, 16-days Earth coverage cycle (end of March – beginning of October)Optimal images: At the end of melting season, before new snow falls, free of lake ice and clouds
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2. 2-D updating of ice and water2.2 Method:Decision Tree classificationAll image pixels are classified by the use of an automatic workflow called “Decision Tree”
Input data:
Tasseled Cap Brightness indexTasseled Cap Wetness indexNDVILANDSAT DN Band 4LANDSAT DN Band 5LANDSAT Temp Band 6SPIRIT DEM (ASTER GDEM)SPIRIT slope (ASTER slope)
Algorithms inspired by GLIMS (Global Land Ice Measurements from Space)www.glims.org
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2. 2-D updating of ice and water2.2 Method:
Decision Tree classification
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Post classification VectorizingGIS analysisVerification analysisManual correction Attribute creationData fusion
3-D updating
ice water sea land bare soil
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2. 2-D updating of ice and water2.2 Examples:
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KMS glacier 1985Light blue: glacier 2009Dark blue: lakes 2009
Map detail of Nuussuaq Halvø
Mapping lakes: 2 km buffer around the ice
ca. 20 km
ca. 600 m retreat
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2. 2-D updating of ice and water2.2 Examples:
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KMS glacier 1985Light blue: glacier 2009Dark blue: lakes 2009
Map detail of Jakobshavn Bræ20 km
1–2 km
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3. 3-D updating of G100V
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3.1 Satellite data:SPIRIT DEM (SPOT 5 HRS sensor)
2 telescopes, pointing 20° toward the rear, respectively 20° toward the front relative to nadir
Images with a swath of 120 km along a segment up to 600 km are acquired within 180 seconds
Spatial resolution: 10m (5m along track)
Acquisition mode: panchromatic (0.48 µm – 0.71 µm)
Vertical accuracy: 90% < 10m on surface slopes < 20%Absolute location: RMS < 30m
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3. 3-D updating of G100V13-01-2012
3.1 Satellite data:
ERS-2: synthetical aperture radar (SAR)
InSAR (Interferomtric Aperture Radar) Data delivered from DTU Space, DK
InSAR uses two or more SAR images to generate digital elevation, using differences in the phase of the waves returning to the satellite
Radar uses electromagnetic radiation with microwave frequencies meaning observations are not prevented by cloud cover or day light.
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3. 3-D updating of G100V13-01-2012
3.1 Satellite data:
ERS-2 synthetic aperture radar (SAR)
24 images between March 12th – June 28th 2011Images cover the SE part of the project area
Spatial resolution: 60mVertical accuracy: < 21m
Results: large errors due to poor interferometric coherence on steep slopes and in areas with high glacier velocityThe predicted height measurement error standard deviation shows discontinuities
Data not suitable for this project
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3. 3-D updating of G100V13-01-2012
3.2 Method:
New contour generation within updated glacier outline, including a 2 km buffer zone
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3. 3-D updating of G100V13-01-2012
3.2 Method:
Updating within a 50 X 50 Km index using FME (Feature Manipulating Engine)
• Clipping and merging DEMs• Raster to vector (points) transformation• Breaklines: coastline, rivers, river beds, calving glacier front• Additional point data within KMS DEM: Spot heights• Contour generation• Smoothing• Attributes
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3. 3-D updating of G100V13-01-2012
3.3 Examples:
KMS
SPIRIT
ca. 5 km
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3. 3-D updating of G100V
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2009 1985
Map detail: N of Saqqaq, Nuussuaq Peninsula
15 Km 15 Km
1150 m1125 m
1300 m1325 m
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4. Conclusion
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• Landsat 7 data are suitable to classify glacier and lakes for topographic maps 1:100.000. Minimum area: 0.001 km2
• Optimal image properties achieves after snow melt season, before new snow falls, without lake ice, and without clouds; i.e. mid-August in project area.
• A semi-automatic classification method was developed and tested successfully. Main challenges remain in areas with heavily debris-covered ice, on steep northern flanks due to cast shadow, and on ice covered lakes. Those areas require manual interference, and classification is time- consuming.
I. 2-D updating of ice and water:
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5. Conclusion
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II. 3-D updating of G100V
• 3-D updating of G100V requires a high resolution, coherent DEM, with an explicit acquisition date.
• SAR data are not suitable to extract height information in area with rough terrain, or in areas with high glacier velocity. Both is the case in the project area.
• SPIRIT data proved to be successful for extracting contour lines with equidistance of 25m and 100m. The result is very satisfying, but the data are expensive.
• Challenges remain in areas with high glacier velocity, especially in case of using two independent satellite sensors to update topographic maps, as it is the case in this project.
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5. Perspective
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During this Dancea Project, an appropriate method has been developed to update G100V maps in Greenland by remote sensing.
• Adding place names
• Upgrading outwash plain/ bare soil (“Sandområder”)
• To benefit of adequate and updated maps, this project should expend over the entire coastal area of Greenland. Continue work will require further foundation to co-finance DEM data, as well as working time.
• Continue cooperation with KMS, DTU Space, Gras A/S
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