Land use classification in mountainous areas : integration of image processing, digital elevation data and field knowledge : application to Nepal: Integration of image processing, digital elevation data and field knowledge (application to Nepal)

Remote sensing data help in mapping land resources, especially in mountainous areas where accessibility is limited. In such areas, land degradation is a main concern. Land is degraded not only by natural processes but also by human activities through inappropriate land use practices. Land cover and land use mapping is thus very important for evaluating natural resources. Classification of remote sensing data in mountainous terrain is problematic because of variations in the sun illumination angle. This results in biased reflectance data, the distribution of which does not fulfil normality as required by the maximum likelihood classifier. In the present work the topographic effect is corrected by normalising the spectral bands by the total intensity. Classification results are further refined by using ancillary data and expert knowledge of the area. The integration of image processing and spatial analysis functions in GIS improves the overall classification result from 67 to 94 percent (a 27 percent increase).