Incorporation of digital elevation models with Landsat-TM data to improve land cover classification accuracy

Effective management of natural resources and sound decision making require accurate information. Extraction of accurate information from remotely sen sed data has been limited by several factors, most importantly the effect o f topography, particularly in rugged terrain. Digital elevation models (DEM s) have proved to be an effective aid to improving landcover classification . The principal objective of this study is to evaluate the contribution and quantify the effectiveness of DEMs in improving landcover classification u sing Landsat-TM data over a rugged area in the Atlas Mountains, Morocco. Th is study showed that DEM data considerably improved the classification accu racy by reducing the effect of relief on satellite images. The variation co efficient (standard deviation divided by the mean) for homogeneous cover ty pe areas was substantially reduced for all the spectral bands on the correc ted image. consequently, the overall accuracy, the Kappa coefficient, and t he Tau coefficient were notably improved on the corrected image. The indivi dual accuracies of the different classes also increased by up to 60%. (C) 2 000 Elsevier Science B.V. All rights reserved.