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Mobile Bay Water Quality Assessment Using NASA Spaceborne Data Products

Mobile Bay Water Quality Assessment Using NASA Spaceborne Data Products. Jenny Q. Du Mississippi State University. Outline. Project Objectives Current Research Status Proposed Approaches Images with higher resolution Classification methods Preliminary Results Ongoing Efforts.

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Mobile Bay Water Quality Assessment Using NASA Spaceborne Data Products

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  1. Mobile Bay Water Quality Assessment Using NASA Spaceborne Data Products Jenny Q. Du Mississippi State University

  2. Outline • Project Objectives • Current Research Status • Proposed Approaches • Images with higher resolution • Classification methods • Preliminary Results • Ongoing Efforts

  3. Project Objectives • To use NASA Spaceborne Imagery (i.e., Landsat, ASTER, Hyperion) in the study of water quality and sediment dynamics in Mobile Bay, AL. • To compare with the NASA research products in Mobile Bay using MODIS imagery and assess the improvements.

  4. This MODIS satellite image shows sediment plumes moving into the Gulf of Mexico from the main branch of the Mississippi River and through the bayous in its Delta region (visibleearth.nasa.gov)

  5. Landsat 11/27/1999

  6. Landsat 11/27/1999 (Mobile bay)

  7. Landsat 10/15/2001

  8. Landsat 10/15/2001 (Mobile Bay)

  9. Landsat 2/17/2001

  10. Landsat 2/17/2001 (Mobile Bay)

  11. Current Research Status • MODIS (Aqua/Terra) • Pros: wide spatial coverage, high temporal resolution (covers the entire globe almost everyday) • Con: low spatial resolution (250m-1000m) • Hard classification • K-means clustering • ISODATA

  12. Proposed Approaches • Satellite Images with Higher Resolutions • LANDSAT • 30 m spatial resolution (can be enhanced to 15m); 4 VNIR bands • ASTER • 15m spatial resolution; 3 VNIR bands • Hyperion • 30m spatial resolution; 220 bands • Fine Classification • Statistical Classifiers • Correlation Study with Ground Truth • In situ sampling (Nov. 2007 – Sep. 2008) • Historic data

  13. Preliminary Results • Satellite Images with Higher Resolutions • LANDSAT • Classification • ISODATA • Correlation Study with Ground Truth • Historic data (e.g., Water Resources Database)

  14. Landsat 9/26/1991 (Mobile Bay)

  15. Observation Stations Class 5 Class 4 Class 3 Class 2 Class 1 Land (Hard) Classification Result

  16. Observation Stations Class 5 Class 4 Class 3 Class 2 Class 1 Land Turbidity Stations1=5.1 Stations2=4.7

  17. Observation Stations Class 5 Class 4 Class 3 Class 2 Class 1 Land Turbidity Stations3=20 Stations4=25

  18. Observation Stations Class 5 Class 4 Class 3 Class 2 Class 1 Land Turbidity Stations5=9.8 Stations6= 10.3

  19. Observation Stations Class 5 Class 4 Class 3 Class 2 Class 1 Land Turbidity Stations7=27

  20. Satellite Image 09/26/1991Ground Truth(Turbidity) 09/27/1991

  21. Landsat 11/27/1999 (Mobile Bay)

  22. Observation Stations Class 5 Class 4 Class 3 Class 2 Class 1 Land (Hard) Classification Result

  23. Observation Stations Class 5 Class 4 Class 3 Class 2 Class 1 Land Turbidity Stations1=5.1 Stations2=5.5 Stations3=3.3 Stations4=4.4 Stations5=4.0 TSS Stations1=24 Stations2=22 Stations3=17 Stations4=19 Stations5=16 CHL-A Stations1=5.5 Stations2=7.0 Stations3=6.8 Stations4=4.4 Stations5=7.9

  24. Observation Stations Class 5 Class 4 Class 3 Class 2 Class 1 Land Turbidity Stations6=7.9 TSS Stations6=43 CHL-A Stations6=37

  25. Satellite Image 11/27/1999Ground Truth 11/27/1999

  26. Landsat 2/17/2001 (Mobile Bay)

  27. Observation Stations Class 5 Class 4 Class 3 Class 2 Class 1 Land (Hard) Classification Result

  28. Observation Stations Class 5 Class 4 Class 3 Class 2 Class 1 Land Turbidity Stations1=18

  29. Satellite Image 02/17/2001Ground Truth(Turbidity) 02/08/2001

  30. Proposed Approaches (Cont’d) • Classification Approaches r = Ma • Unsupervised Linear Mixture Analysis • Endmember signature extraction • Fully constrained linear unmixing • Blind Source Separation • Independent Component Analysis

  31. Original Image

  32. Linear unmixing result (soft Classification)

  33. The (soft) endmember classification map that can be used for detailed water quality mapping

  34. ICA result (soft classification)

  35. The independent component (soft classification map) that can be used for detailed water quality mapping

  36. Ongoing Efforts • More detailed correlation analysis • Images and ground truth data collected at the same time. • Images collected during Nov. 2007 and Sep. 2008.

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