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A Multi-Angle Approach to Mapping Forest and Shrub Canopy Structure in the Southwestern United States

Mark James Chopping, Montclair State University, chopping@pegasus.montclair.edu (Presenting)
Lihong Su, Montclair State University, sul@pegasus.montclair.edu
Andrea Laliberte, USDA, ARS Jornada Experimental Range, alaliber@nmsu.edu
Albert Rango, USDA, ARS Jornada Experimental Range, alrango@nmsu.edu
Gretchen G. Moisen, USDA Forest Service, Rocky Mountain Research Station, gmoisen@fs.fed.us
John V. Martonchik, NASA Jet Propulsion Laboratory, John.V.Martonchik@jpl.nasa.gov

Red wavelength data from NASA's Multi-angle Imaging SpectroRadiometer (MISR) acquired at a nominal 275 m and in nine viewing directions were used to invert a simple geometric-optical (GO) model to retrieve canopy structure parameters over parts of S.E. Arizona and S. New Mexico (>159,556 km2). This area encompasses desert grassland, often with woody shrub encroachment; riparian woodland; and upland forest. The combined soil and understory signal - represented by the Walthall model - was estimated a priori using regression relationships with MISR nadir data and the red band isotropic, geometric, and volume scattering kernel weights of the LiSparse-RossThin kernel-driven model, using measurements extracted from Ikonos panchromatic imagery over 19 locations in a grass-shrub transition zone with contrasting upper/lower canopy configurations. The GO model was adjusted using the Praxis minimization algorithm and the merit function min(|RSME|), with no constraints. Distributions of crown cover and mean canopy height for forested areas show good matches with maps from the USDA Forest Service developed from field survey as part of the Forest Inventory Analysis (FIA). Within upland forest, the mean canopy height map shows a better match with the corresponding FIA map than the cover map. Some areas with known shrub cover are predicted to have low or no woody plant cover, indicating a need to adjust the background calibration. Retrievals are very rapid - almost 3 million inversions were completed in < 15 minutes - allowing application of this method over very large areas.

Presentation Type:  Poster

Abstract ID: 141

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