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ARS Home » Plains Area » Las Cruces, New Mexico » Range Management Research » Research » Publications at this Location » Publication #276026

Title: Forest structure and aboveground biomass in the southwestern United States from MODIS and MISR

Author
item CHOPPING, MARK - Montclair State University
item SCHAAF, CRYSTAL - Boston University
item ZHAO, FENG - Boston University
item WANG, ZHUOSEN - Boston University
item NOLIN, ANNE - Oregon State University
item MOISEN, GRETCHEN - Us Forest Service (FS)
item MARTONCHIK, JOHN - National Aeronautics Space Administration (NASA) - Jet Propulsion Laboratory
item BULL, MICHAEL - National Aeronautics Space Administration (NASA) - Jet Propulsion Laboratory

Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/18/2010
Publication Date: 5/11/2011
Citation: Chopping, M., Schaaf, C.B., Zhao, F., Wang, Z., Nolin, A.W., Moisen, G.G., Martonchik, J.V., Bull, M. 2011. Forest structure and aboveground biomass in the southwestern United States from MODIS and MISR. Remote Sensing of Environment. 115:2943-2953.

Interpretive Summary: NASA’s Earth Orbiting Satellites carry numerous sensors that detect difference aspects of light reflected by the earth’s surface back into the atmosphere. Several of these sensors detect reflected light that can be used to estimate basic characteristics of the earth’s vegetation, including productivity and ground cover amounts. This research project compared model-based estimates for ground cover from two different sensors to actual ground cover data from a field research in southern New Mexico. The modeling techniques were effective and could be used in place of field data.

Technical Abstract: Red band bidirectional reflectance factor data from the NASA MODerate resolution Imaging Spectroradiometer (MODIS) acquired over the southwestern United States were interpreted through a simple geometric–optical (GO) canopy reflectance model to provide maps of fractional crown cover (dimensionless), mean canopy height (m), and aboveground woody biomass (Mg ha-1) on a 250 m grid. Model adjustment was performed after dynamic injection of a background contribution predicted via the kernel weights of a bidirectional reflectance distribution function (BRDF) model. Accuracy was assessed with respect to similar maps obtained with data from the NASA Multiangle Imaging Spectroradiometer (MISR) and to contemporaneous US Forest Service (USFS) maps based partly on Forest Inventory and Analysis (FIA) data. MODIS and MISR retrievals of forest fractional cover and mean height both showed compatibility with the USFS maps, with MODIS mean absolute errors (MAE) of 0.09 and 8.4 m respectively, compared with MISR MAE of 0.10 and 2.2 m, respectively. The respective MAE for aboveground woody biomass was ~10 Mg ha-1, the same as that from MISR, although the MODIS retrievals showed a much weaker correlation, noting that these statistics do not represent evaluation with respect to ground survey data. Good height retrieval accuracies with respect to averages from high resolution discrete return lidar data and matches between mean crown aspect ratio and mean crown radius maps and known vegetation type distributions both support the contention that the GO model results are not spurious when adjusted against MISR bidirectional reflectance factor data. These results highlight an alternative to empirical methods for the exploitation of moderate resolution remote sensing data in the mapping of woody plant canopies and assessment of woody biomass loss and recovery from disturbance in the southwestern United States and in parts of the world where similar environmental conditions prevail.