Landform Classification for Digital Soil Mapping in the Chongwe-Rufunsa Area, Zambia

Abstract

This paper presents results of a landform classification of a section of the Chongwe-Rufunsa area, Zambia. The objective of the study was to separate the landscape into landform classes that indicate or suggest marked differences with respect to soil properties and agricultural suitability. Terrain attributes derived from a digital elevation model were overlaid using cell statistics to generate a landform map with five classes. The generated landform map had an overall classification accuracy of 73.51%. The landform map provided a base for benchmark soil sampling for ongoing research on digital soil mapping.