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Remote sensing of biological soil crusts

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This was my presentation for my advanced remote sensing course in which I researched and applied methods for mapping biological soil crusts in arid environments.

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Remote sensing of biological soil crusts

  1. 1. Remote Sensing of Biological Soil Crusts Jonathan A. Key M.S. Environmental Science University of Colorado Denver
  2. 2. Moab, Utah Small patches of vascular plant growth
  3. 3. Morphology and Structure Cyanobacterial microfilamentsBiological soil crust macrostructure Arches NPS Arches NPS Also known as cryptogamic, microbiotic, and microphytic soils. Consist of photosynthetic cyanobacteria, lichens, green algae, fungi, nonvascular plants, and various bacteria.
  4. 4. Geographic Extent • Occupy a wide range of climates • Species composition of alpine tundra is similar to that of cool desert • Constitute up to 75 percent of the living ground cover www.ArcheaologySouthWest.org
  5. 5. Selection of Data Sets Landsat 5 Thematic Mapper • Multispectral imagery using 7 bands • Large enough temporal range to do an analysis spanning more than ten years • Decent spatial resolution • Data acquired was from May 18, 1996 and May 6, 2009
  6. 6. Study Scene Colorado Plateau May 18, 1996
  7. 7. Workflow Process Image Acquisition User Analysis • NDVI, Tasseled Cap, BSCI • Contrast Adjust Preprocessing • Band layer stacking • Mosaicking Unsupervised Classification Supervised Classification • Training sites • Max likelihood • Determination of # of classes Error Analysis • 2nd set of training sites • Confusion matrix Report Class Statistics Class Change Analysis Repeat for Later Image • USGS EarthExplorer • ISODATA
  8. 8. NDVI Spectral Transformation BSCI May 18, 1996
  9. 9. Biological Soil Crust Index • Analysis of this technique with ground truth data suggests that BSCs can be detected as long as they cover approximately one third of the pixel (10 m for Landsat) (Chen et al. 2005)
  10. 10. Supervised Classification Desert Vegetation Biological Soil Crust Panchromatic background image May 18, 1996
  11. 11. Class Change Analysis • Pixel-based class change analysis indicates that there was a 124 percent increase in microbiotic soil coverage from May 1996 to 2009 Class Change Analysis (Percentage) Class Alpine Veg Biological Soil Crust Snowcap Bedrock/Dry Soil Clouds Desert Veg Water Rural Dev Crops Biological Soil Crust 0.079 72.318 3.981 24.878 0.607 21.889 3.2 0.492 0.362 Desert Veg 8.562 1.248 2.136 3.684 1.097 40.586 0.146 37.235 4.206 Alpine Veg 45.824 0.075 15.212 0.049 2.75 1.305 2.993 1.712 6.347 Water 0.031 0 0.588 0.001 0 0.001 70.224 0 0 Clouds 2.038 1.295 42.073 1.917 73.967 0.893 10.2 2.558 1.285 Snowcap 4.359 0 13.788 0.05 0.468 0.023 0.093 0.01 1.332 Bedrock/Dry Soil 11.967 21.803 16.786 66.11 17.694 18.23 10.259 9.769 3.098 Rural Dev 25.711 2.776 5.104 3.122 3.254 14.351 2.751 41.048 14.082 Class Changes 54.176 27.682 86.212 33.89 26.033 59.414 29.776 58.952 30.712 Image Difference -45.058 124.896 -24.829 20.702 -20.19 -40.162 -27.59 205.334 704.3
  12. 12. Error Matrix (Percent) Class Alpine Veg Biological Soil Crust Snowcap Clouds Desert Veg Water Crops Bedrock/Dry Soil Rural Development Total Alpine Veg 96.58 0 7.35 0.01 5.45 0.11 13.06 0.03 18.28 21.3 Biological Soil Crust 0.04 88.88 0 0 0.11 0 0 5.78 0.94 14.67 Snowcap 0.36 0 89.32 12.37 0.02 0.43 0 0 0 3.84 Clouds 0.19 0.01 3.27 87.62 0.23 0.03 0 0.41 0.57 6.61 Desert Veg 1.23 4.24 0.04 0 93.69 0 0.71 0.32 5.71 17.23 Water 0 0 0 0 0 99.36 0 0 0 3.67 Crops 0.34 0 0 0 0.03 0 65.17 0 3.66 0.37 Bedrock/Dry Soil 0 6.83 0.02 0 0.47 0.07 0 93.46 2.97 28.91 Rural Development 1.26 0.04 0 0 0.01 0 21.06 0 67.86 3.39 Error Report and Uncertainties Potential sources of error • BSCI was developed while studying Gobi Desert with ETM+ • Landsat 5 has relatively low radiometric resolution • Overlap of desert vegetation and microbiotic soils and season variation • Training site selection not based on ground truth data
  13. 13. Climatic Influence • Soil stability reduces wind-blown dust • Dust deposited on snowcapped mountains will decrease the albedo of the surface Painter et al. 2007 www.panoramio.com
  14. 14. Closing Statements • Ground truth data is required for this study to mean anything • Based on this analysis there has been a substantial increase in biological soil crust coverage from 1996 to 2006 in the Colorado Plateau region. • This technique provides a cost-effective method for continued monitoring of microbiotic soils Any thoughts or questions?
  15. 15. References Belnap, J., & Gardner, J. S. (1993). Soil microstructure in soils of the Colorado Plateau: the role of the cyanobacterium Microcoleus vaginatus. Great Basin Naturalist, 53(1), 40-47. Belnap, J., & Eldridge, D. (2003). Disturbance and recovery of biological soil crusts. In Biological soil crusts: structure, function, and management (pp. 363-383). Springer Berlin Heidelberg. Chen, J., Yuan Zhang, M., Wang, L., Shimazaki, H., & Tamura, M. (2005). A new index for mapping lichen-dominated biological soil crusts in desert areas. Remote Sensing of Environment, 96(2), 165-175. Harper, K. T., & Belnap, J. (2001). The influence of biological soil crusts on mineral uptake by associated vascular plants. Journal of Arid Environments, 47(3), 347-357. Karnieli, A., Kidron, G. J., Glaesser, C., & Ben-Dor, E. (1999). Spectral characteristics of cyanobacteria soil crust in semiarid environments. Remote Sensing of Environment, 69(1), 67-75. Painter, T. H., Barrett, A. P., Landry, C. C., Neff, J. C., Cassidy, M. P., Lawrence, C. R., & Farmer, G. L. (2007). Impact of disturbed desert soils on duration of mountain snow cover. Geophysical Research Letters, 34(12). Peterson, P. (Ed.). (2001). Biological soil crusts: ecology and management. US Department of the Interior, Bureau of Land Management, National Science and Technology Center, Information and Communications Group. Van der Meer, F. D., van der Werff, H., van Ruitenbeek, F. J., Hecker, C. A., Bakker, W. H., Noomen, M. F., ... & Woldai, T. (2012). Multi-and hyperspectral geologic remote sensing: A review. International Journal of Applied Earth Observation and Geoinformation, 14(1), 112-128. Weber, B., Olehowski, C., Knerr, T., Hill, J., Deutschewitz, K., Wessels, D. C. J., & Büdel, B. (2008). A new approach for mapping of biological soil crusts in semidesert areas with hyperspectral imagery. Remote Sensing of Environment, 112(5), 2187-2201.

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