Using MISR to Map Woody Plant Canopy Crown Cover, Height, and Biomass
Mark
Chopping, Montclair State University, chopping@pegasus.montclair.edu
(Presenting)
John
Martonchik, NASA/JPL, john.v.martonchik@jpl.nasa.gov
Michael
Bull, NASA/JPL, michael.a.bull@jpl.nasa.gov
Gretchen
Moisen, USDA Forest Service, Ogden, UT, gmoisen@fs.fed.us
Barry
Wilson, USDA Forest Service, St. Paul, MN, barrywilson@fs.fed.us
Albert
Rango, USDA, ARS Jornada Experimental Range, alrango@nmsu.edu
Multiangle remote sensing data from NASA's MISR instrument were interpreted through a modified geometric-optical (GO) model with a priori empirical separation of the canopy and background contributions to the signal to map woody plant distributions (crown cover, mean canopy height, and aboveground woody biomass) for large parts of Arizona and New Mexico. The results for forest were assessed against Forest Service maps and showed a good agreement with strong relationships (R^2> 0.7); and against Forest Inventory Analysis data with less strong but positive relationships (R^2>0.4), largely as a result of the disparity in scales. The results for shrubs were assessed against Ikonos-derived maps of crown cover and are promising for this approach, noting that spectral measures are often confounded and that it is difficult for lidar to map woody plants with crown heights < 3 m. Work applying the GO model to a heterogeneous, managed boreal forest in Maine (Howland) and without the a priori canopy-background separation showed a moderately strong relationship to Laser Vegetation Imaging Sensor (LVIS) canopy heights and reasonable matches with obvious surface features (roads, rivers, clearcuts); over larger parts of Maine the matches for crown cover and canopy height were less consistent with Forest Service mapped data but the match was better for height than cover. The height estimates are based on retrievals of crown aspect ratio that could be useful in improving the accuracy of height estimates from lidar.
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