Comparing Landsat ETM+ imagery with
LiDAR data when classifying suburban
              areas


               Lesley Bross...
Research Question
Can LiDAR elevation/intensity data be used to generate landcover
     maps comparable to those sourced f...
Study Area




Approximately 296 ha includes portions of Beaverton and
          unincorporated Washington county
Landsat ETM+ Data

• Landsat 7 images acquired from April 6, 2007 and
  May 8, 2007
• P46R28
• SLC failure 
• Data proces...
Landsat ETM+ Data
LiDAR Data

       • Portland LiDAR Consortium
       • Acquired March 16 - April
         15, 2007
       • Ground Pulse ...
LiDAR Data
• ESRI tools for processing .LAS
  files
   •   Point Information
   •   LAS to Multipoint
   •   Point to Rast...
Unsupervised classification

• Landsat data
  • 6 color bands + NDVI band
  • PCA (output 3 PCA bands)
• LiDAR data
  • St...
Landsat classification

                  Level 2
                  Kappa: 0.48
                  Overall accuracy: 55%


...
LiDAR classification

                 Level 2
                 Kappa: 0.40
                 Overall accuracy: 50%


     ...
Conclusions
• LiDAR did not generate maps comparable to Landsat
   • Missed water and wetlands classes
   • Could not dist...
Conclusions




LiDAR picks out two specific buildings at St. Mary’s school in
two of fifty spectral clusters. Perhaps bet...
Data sources
• Metro RLIS. (2007). Bare earth DEM. Retrieved May 18, 2010, from PSU
  I:/resources/Students/Data/GIS/RLIS/...
References
• Duh, Geoffrey, Associate Professor, Geography Department, Portland
  State University. Contributed expert opi...
References
• Shackelford and Davis. 2003. A hierarchical fuzzy classification approach
  for high-resolution multispectral...
Questions ?
Land-Use codes
LU_CODE         Land Use Descriptions
1               Urban or Built-up Land
          112   High Density R...
Erdas recode
L1_CODE   L2_CODE   LU_CODE   Description
1         1         111       Low density residential
1         2  ...
Landsat accuracy report
              Level 1                                   Level 2
                    Producer's Use...
LiDAR accuracy report
          Level 1                                      Level 2
                    Producer's User's...
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Comparing Landsat ETM+ imagery with LiDAR data

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Results from remote sensing research conducted in Spring 2010.

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Comparing Landsat ETM+ imagery with LiDAR data

  1. 1. Comparing Landsat ETM+ imagery with LiDAR data when classifying suburban areas Lesley Bross, June 7, 2010 Geography 582
  2. 2. Research Question Can LiDAR elevation/intensity data be used to generate landcover maps comparable to those sourced from Landsat spectral data?
  3. 3. Study Area Approximately 296 ha includes portions of Beaverton and unincorporated Washington county
  4. 4. Landsat ETM+ Data • Landsat 7 images acquired from April 6, 2007 and May 8, 2007 • P46R28 • SLC failure  • Data processing 1. Histogram match (b/w and color) 2. Model maker interleaves bands (b/w and color) 3. Resolution merge (pan-sharpen) color from panchromatic data (15m) 4. Subset to match LiDAR tiled area
  5. 5. Landsat ETM+ Data
  6. 6. LiDAR Data • Portland LiDAR Consortium • Acquired March 16 - April 15, 2007 • Ground Pulse Density: 1.28 points per sq meter • LiDAR tiles 45122D7103 and 45122D7104
  7. 7. LiDAR Data • ESRI tools for processing .LAS files • Point Information • LAS to Multipoint • Point to Raster (15m cell size) • VBA script copies i-values to z- values so they are accessible • ESRI-to-ERDAS gotchas • No nullData values -> raster calculator with con statement • Recalculate statistics in IMAGINE
  8. 8. Unsupervised classification • Landsat data • 6 color bands + NDVI band • PCA (output 3 PCA bands) • LiDAR data • Standard deviation of first returns • Mean feature height (first returns – last returns) • Mean intensity of all returns • Generate 50 spectral clusters with ISODATA algorithm • Accuracy assessment • 100 random stratified points shared between scenes • Ground-truth data: 4 ft infrared photo, tax lots, THPRD map
  9. 9. Landsat classification Level 2 Kappa: 0.48 Overall accuracy: 55% Level 1 Kappa: 0.62 Overall accuracy: 77%
  10. 10. LiDAR classification Level 2 Kappa: 0.40 Overall accuracy: 50% Level 1 Kappa: 0.57 Overall accuracy: 76%
  11. 11. Conclusions • LiDAR did not generate maps comparable to Landsat • Missed water and wetlands classes • Could not distinguish between built-up level 2 classes • Some technologies better for some land covers • LiDAR detected isolated tree stands • Higher accuracy for roads; Higher overall %? • Accuracy of ArcMap LiDAR toolset? • LiDAR i-values should be normalized and filtered (Song et all) • LiDAR more susceptible to ‘mixels’? Data at smaller grain.
  12. 12. Conclusions LiDAR picks out two specific buildings at St. Mary’s school in two of fifty spectral clusters. Perhaps better for smaller areas or identifying distinct features? Segmentation?
  13. 13. Data sources • Metro RLIS. (2007). Bare earth DEM. Retrieved May 18, 2010, from PSU I:/resources/Students/Data/GIS/RLIS/RLIS_Extra_DEM. • Metro RLIS. (2006). NIR aerial photo. Retrieved May 1, 2010, from PSU I:/resources/Students/Data/GIS/RLIS/Photo_2006/Color_Infrared/4ft. • Metro RLIS. (2009 November). Taxlot shapefiles. Retrieved May 21, 2010, from PSU I:/resources/Students/Data/GIS/RLIS/2009_Nov/ESRISHAPEFILES/TAXLOTS. • Portland LiDAR Consortium (2007). LAS files received from Geoffrey Duh. • Tualatin Hills Park and Recreation District(2010). Nature Park Trail Map. Retrieved May 5, 2010 from http://www.thprd.org/pdfs/document49.pdf . • USGS (2007). EarthExplorer. Landsat 7 imagery. Retrieved April 27, 2010 from http://edcsns17.cr.usgs.gov/EarthExplorer/.
  14. 14. References • Duh, Geoffrey, Associate Professor, Geography Department, Portland State University. Contributed expert opinion and technical assistance. • ERDAS. September 2008. ERDAS IMAGINE Professional Tour Guides. p. 149-155 • Jensen, J. R. 2005. Introductory Digital Image Processing (3rd edition). Prentice Hall. p. 343-344. • Martin, Kevin S, Adjunct Instructor, Geography Department, Portland State University. Contributed expert opinion and technical assistance. • McCauley, S. and Goetz, S.J. 2004. Mapping residential density patterns using multi-temporal Landsat data and a decision-tree classifier. International Journal of Remote Sensing. 25(6): 1077-1094.
  15. 15. References • Shackelford and Davis. 2003. A hierarchical fuzzy classification approach for high-resolution multispectral data over urban areas. IEEE Transactions on geosciences and remote sensing, 41(9): 1920 – 1932. • Short Sr., Nicholas M.. 2009. Last accessed May 5, 2010. Vegetation Applications – Agriculture, Forestry, and Ecology. The Remote Sensing Tutorial, Last accessed May 5, 2010 at http://rst.gsfc.nasa.gov/Sect3/Sect3_5.html. • Song, J.H., Han, S.H., Yu, K., Kim, Y. 2002. Assessing the possibility of land-cover classification using LiDAR intensity data, IAPRS, 9-13 September, Graz, vol. 34: 1-4. Last accessed May 27, 2010 at http://www.isprs.org/proceedings/XXXIV/part3/papers/paper128.pdf.
  16. 16. Questions ?
  17. 17. Land-Use codes LU_CODE Land Use Descriptions 1 Urban or Built-up Land 112 High Density Residential (multi-family DU) 111 Low Density Residential (single-family DU) 12 Commercial and Services 14 Transportation/Communications/Utilities (impervious) 16 Mixed Urban or Built Up Land 17 Urban/Recreation (park, lawn) 3 Rangeland 31 Herbaceous (Pasture/grass/bushes) 4 Forest Land 41 Deciduous Forest 42 Evergreen Forest 43 Mixed forest 5 Water 51 Streams and Canals 52 Lakes and Ponds 6 Wetland 61 Forested 62 Non-forested
  18. 18. Erdas recode L1_CODE L2_CODE LU_CODE Description 1 1 111 Low density residential 1 2 112 High density residential 1 3 12 Commercial 1 4 14 Transportation 1 5 16 Mixed urban 1 6 17 Recreation 2 7 31 Herbaceous 3 8 41 Deciduous 3 9 42 Evergreen 3 10 43 Mixed forest 4 11 61 Forested wetland 4 12 62 Non-forested wetland
  19. 19. Landsat accuracy report Level 1 Level 2 Producer's User's Producer's User's Accuracy Accuracy Accuracy Accuracy Class 1 87.3% 87.3% Class 1 33.3% 25.0% Class 2 66.7% 76.9% Class 2 14.3% 33.3% Class 3 78.3% 72.0% Class 3 50.0% 71.4% Class 4 14.3% 14.3% Class 4 69.2% 62.1% Class 5 0.0% 0.0% Overall Accuracy: 55.0% Class 6 62.5% 100.0% KAPPA: 0.4783 Class 7 66.7% 76.9% Class 8 58.3% 46.7% Class 9 57.1% 57.1% Class 10 75.0% 100.0% Class 11 0.0% 0.0% Class 12 25.0% 14.3% Overall Accuracy: 77.0% KAPPA: 0.6264
  20. 20. LiDAR accuracy report Level 1 Level 2 Producer's User's Producer's User's Accuracy Accuracy Accuracy Accuracy Class 1 94.5% 74.3% Class 1 0.0% 0.0% Class 2 33.3% 50.0% Class 2 0.0% 0.0% Class 3 82.6% 95.0% Class 3 30.0% 100.0% Class 4 0.0% 0.0% Class 4 96.2% 59.5% Class 5 0.0% 0.0% Overall Accuracy: 76.0% Class 6 62.5% 50.0% KAPPA: 0.5668 Class 7 33.3% 50.0% Class 8 73.3% 61.1% Class 9 16.7% 50.0% Class 10 0.0% 0.0% Class 11 0.0% 0.0% Class 12 0.0% 0.0% Overall Accuracy: 50.0% KAPPA: 0.4008

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