Estimation of tropical forest structure from spot-5 satellite images
Por:
Castillo-Santiago M.A., Ricker M., de Jong, BHJ
Publicada:
1 ene 2010
Categoría:
Earth and Planetary Sciences (miscellaneous)
Resumen:
Predictions of tropical forest structure at the landscape level still present relatively high levels of uncertainty. In this study we explore the capabilities of high-resolution Satellite Pour l'Observation de la Terre (SPOT)-5 XS images to estimate basal area, tree volume and tree biomass of a tropical rainforest region in Chiapas, Mexico. SPOT-5 satellite images and forest inventory data from 87 sites were used to establish a multiple linear regression model. The 87 0.1-ha plots covered a wide range of forest structures, including mature forest, with values from 74.7 to 607.1 t ha-1. Spectral bands, image transformations and texture variables were explored as independent variables of a multiple linear regression model. The R2s of the final models were 0.58 for basal area, 0.70 for canopy height, 0.73 for bole volume, and 0.71 for biomass. A leave-one-out cross-validation produced a root mean square. error (RMSE) of 5.02 m2 ha-1 (relative RMSE of 22.8%) for basal area; 3.22 m (16.1%) for canopy height; 69.08 m3 ha-1 (30.7%) for timber volume, and 59.3 t ha-1 (21.2%) for biomass. In particular, the texture variable ‘variance of near-infrared’ turned out to be an excellent predictor for forest structure variables. © 2010 Taylor & Francis Group, LLC.
Filiaciones:
Castillo-Santiago M.A.:
Laboratorio de Análisis de Información Geográfica, El Colegio de la Frontera Sur, San Cristóbal de las Casas, Chiapas, Mexico
Ricker M.:
Univ Nacl Autonoma Mexico, Inst Biol, Dept Bot, Mexico City 04510, DF, Mexico
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