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According to the Intergovernmental Panel on Climate Change Good Practice Guidance (IPCC GPG), remote sensing techniques are suitable for estimation of vegetation biophysical variables. In this work we used a Landsat time series to estimate canopy water content (CWC) in a pasture area Northeast of the province of Caceres, from 1985 to 2010. Field sampling of canopy water content (CWC) were performed, as well as radiometry, in four plots located within the study site for the model calibration. We applied a linear regression model using field data and spectral indices for estimating the variables. NDII5 was the best index for CWC estimation (R2=0.85). The average values of CWC were sensitive to extreme changes in time series of precipitation and temperature. Revista Ciencias Espaciales, Vol.5(1) 2012, 66-84

Análisis temporal del contenido de humedad en pasto en un ecosistema de DEHESA mediante imágenes Landsat, y su relación con factores climáticos