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Drainage Analysis Using DEM from Different Sources

Drainage Analysis Using DEM from Different Sources. Larry W. Teng Center for Space Research, UT-Austin teng@csr.utexas.edu. Components. Exercise 5 and Exercise 4 in GIS class. Stream network using NHD. Drainage line processing using DEMs. Data sources and processing. Research work at CSR.

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Drainage Analysis Using DEM from Different Sources

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  1. Drainage Analysis Using DEM from Different Sources Larry W. Teng Center for Space Research, UT-Austin teng@csr.utexas.edu

  2. Components • Exercise 5 and Exercise 4 in GIS class. • Stream network using NHD. • Drainage line processing using DEMs. • Data sources and processing. • Research work at CSR. • Data fusion. • Remove vegetation from DEMs.

  3. DEM Sources • Topographic maps • NED (1arcsec) resampled to 30m • Radar Interferometry • SRTM (1arcsec) resampled to 30m • TOPSAR (10m) • LIDAR (Laser Altimetry) • LIDAR (1.25m) resampled to 5m • Integrated DEM at 5m

  4. Data Stack

  5. Drainage Lines by NED (30m)

  6. Drainage Lines by SRTM (30m)

  7. Drainage Lines by TOPSAR (10m)

  8. LIDAR DEM (5m, bottom)

  9. LIDAR DEM (5m, top)

  10. Integrated DEM at 5m

  11. Comparison to the Drainage Lines

  12. Comparison to the Drainage Lines

  13. Data Fusion • “Data fusion is the seamless integration of data from disparate sources.” ~ NOAA National Data Center. • Each technique has strengths and weaknesses. Data fusion tries to extract the advantages from each source to optimize the integrated result. • Update existing optimized data with the newly developed techniques.

  14. Multiscale Algorithm • Fine-to-coarse process • Bring details to coarser level. • Compare noises at finer level to coarser level. • Coarse-to-fine process • Reconstruct the details at the finer level with the broader view at the coarser level.

  15. INSAR DEM

  16. LIDAR DEM

  17. Data Fusion Result

  18. More on Data Fusion

  19. Sequential Data Fusion • ERS DEM at 20m and three TOPSAR DEMs at 5m. • Suppose the TOPSARs are acquired in different time, this demonstration shows that the updating using multiscale algorithm results in lower uncertainty in the final estimates.

  20. Works to do… • Overcome the computational expense in computing drainage lines using the five-meter LIDAR DEM and fused DEM. • Evaluate the drainage networks generated by the fused data. • Integrate the drainage networks generated by the different DEMs.

  21. Summary • Drainage lines generated from different DEM can be quite different. • Coarse DEM results in inaccurate drainage lines. • Artifacts in a fine DEM brings errors in resulting stream networks. • Integrated DEM can be a solution to compromise among different DEM data.

  22. Future Works • Removing vegetation and artifacts on the DEM to obtain a better flow accumulation map. • Removing unwanted artifacts in the stream networks.

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