Linear regressions for canopy cover estimation in Acacia woodlands using Landsat-TM, -MSS and SPOT HRV XS data

Abstract The aim of the study was to establish remote sensing models for the estimation of canopy cover in Acacia woodlands. The models were established using Landsat-TM and MSS data and SPOT HRV XS data and based on field data from eastern Sudan. The models were derived using the Reduced Major Axis (RMA) method. Correlation coefficients between NDVI and canopy cover are for Landsat-TM 0-552, for Landsat-MSS 0-698 and for SPOT HRV XS 0-718. The confidence intervals of predicted canopy cover are also presented.

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