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No. de sistema: 000034896

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040 _ _ a| ECO
c| ECO
043 _ _ a| n-mx-cp
044 _ _ a| xx
100 1 _ a| Castillo Santiago, Miguel Ángel
245 1 0 a| Estimation of tropical forest structure from SPOT-5 satellite images
520 1 _ a| 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.
650 _ 4 a| Bosques tropicales
650 _ 4 a| Imágenes por satélite
650 _ 4 a| Análisis de regresión
651 _ 4 a| Marqués de Comillas (Chiapas, México)
651 _ 4 a| Selva Lacandona (Chiapas, México)
700 1 _ a| Ricker, Martin
e| coaut.
700 1 _ a| De Jong, Bernardus Hendricus Jozeph
e| coaut.
773 0 _
t| Journal International Journal of Remote Sensing
g| Vol. 31, no. 10 (March 2010), p. 2767-2782
x| 0143-1161
902 _ _ a| GOG/Brenda
904 _ _ a| Abril 2011
905 _ _ a| Artecosur
905 _ _ a| Artfrosur
905 _ _ a| CRIIS
905 _ _ a| Biblioelectrónica
LNG eng
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Estimation of tropical forest structure from SPOT-5 satellite images
Castillo Santiago, Miguel Ángel (autor)
Ricker, Martin (autor)
De Jong, Bernardus Hendricus Jozeph (autor)
Contenido en: Journal International Journal of Remote Sensing. Vol. 31, no. 10 (March 2010), p. 2767-2782. ISSN: 0143-1161
No. de sistema: 34896
Tipo: Artículo


Inglés

"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."