Estimation of tropical forest structure from SPOT-5 satellite images |
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| Authors: | Miguel Angel Castillo-Santiago Martin Ricker Bernardus H. J. de Jong |
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| Affiliation: | 1. Laboratorio de Análisis de Información Geográfica, El Colegio de la Frontera Sur, San Cristóbal de las Casas , Chiapas , Mexico mcastill@ecosur.mx;3. Departamento de Botánica , Instituto de Biología, Universidad Nacional Autónoma de México , Mexico , D.F. , Mexico;4. Departamento de Agroecología , El Colegio de la Frontera Sur , Villahermosa , Tabasco , Mexico |
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| Abstract: | 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. |
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