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Stem volume of tropical forests from polarimetric radar

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In this study, we investigated the potential of polarimetric synthetic aperture radar (PolSAR) data for the estimation of stem volume in tropical forests. We used calibrated L-band, high incidence angle data from the airborne system SAR-R99B, acquired over an experimental area in the Tapajos National Forest, Para, Brazil. To evaluate the potential of PolSAR data for this application we used regression analysis, in which first-order models were fit to predict stem volume per hectare, as determined from field measurements. Unlike previous studies in tropical forests, the set of potential explanatory variables included a series of PolSAR attributes based on phase information, in addition to power measurements. Model selection techniques based on coefficient of determination (R2) and mean square error (MSE) identified several useful subsets of explanatory variables for stem volume estimation, including backscattering coefficient in HH polarization, cross-polarized ratio, HH-VV phase difference, polarimetric coherence, and the volume scatter component of the Freeman decomposition. Evaluation of the selected models indicated that PolSAR data can be used to quantify stem volume in the study site with a root mean square error (RMSE) of about 20-29 m3 ha-1, corresponding to 8-12% of the mean stem volume. External validation using independent data showed average prediction errors of less than 14%. Saturation effects in measured versus modelled volume were not observed up to volumes of 308 m3 ha-1 (biomasses of ∼357 Mg ha-1). However, no formal assessment of saturation was possible due to limitations of the volume range of the dataset.
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Document Type: Research Article

Affiliations: 1: Department of Forest Ecosystems and Society, Oregon State University, Corvallis, USA 2: Remote Sensing Division, National Institute for Space Research, Sao Jose dos Campos, Brazil 3: Jet Propulsion Laboratory, California Institute of Technology, Pasadena, USA

Publication date: 2011-01-01

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