Modelling and mapping the suitability of land for crop production using a combination of GIS and remote sensing in the Eastern Cape: a case study of Mbashe and Mquma local municipalities-South Africa

In order to achieve sustainable agriculture, decision makers require appropriate and fully detailed spatial information on land resources. Crop-land suitability analysis is a prerequisite to achieve optimum utilization of the available land resources for sustainable agriculture rural production (T.R. Nisar Ahamed et al., 2000). It is indeed of paramount importance to identify suitable land for cropping while causing minimum impact to the environment. The Food and Agriculture Organization (FAO, 1976), recommended an approach of land suitability evaluation for crops in terms of suitable land based on climatic and terrain data and soil properties. In this study, an attempt was made to identify suitable areas for massive crop production using remote sensing and GIS methodologies and the knowledge from extension officers. The primary method aims at generating land cover data using SPOT 5 satellite imagery and modeling with the existing land capability. The research purpose was to map the map the number hectares suitable areas for crop production number hectares suitable areas for crop production number hectares suitable areas for crop production number hectares suitable areas for crop production. Spatial modeling techniques were utilized to model land suitability model in an effective and efficiently way. The spatial modeling extension from ESRI product was used to model the crop suitability areas. The model run on ArcGIS platform and due to the fact that modeling only uses raster formats, all the data sets were projected and converted to raster format. The weighted overlay model was used to create land suitability map. The model results revealed that 4046251.79 hectares were suitable for cropping in the study area. The final outputs of suitable areas were calculated and each ward was given a value of suitable area as well as unsuitable area. The validation of the final maps compliments the 500 000 hectares that were mapped by Dept of Agriculture EC using 8% slope as the best potential areas. The method provides a cheap, effective and efficient way to map suitable areas over a large area and it also uses remote sensing data. It is hoped that decision makers will make use of the information produced in this paper as the whole world is in crisis of food security