GIS-Based Assessment of Land Suitability for Industrial Crops (Cotton, Sesame and Groundnut) in the Abyan Delta, Yemen

Abstract

We investigated the potential and capability of GIS as a technique for integrating spatial and biophysical attribute data to produce land suitability maps of the main industrial irrigated cropland (cotton, groundnut, and sesame) cultivated in the Abyan, Yemen Delta, In order to improve decision-maker strategies. We collected 64 soil samples in a systematic, georeferenced soil survey. Spatial overlay of detailed soil site characteristics, physical site qualities, and crop specific requirements was performed to reveal areas suitable for crop production. Our results of the land suitability classification for cotton, sesame and groundnut indicated that the highly suitable class (S1) accounts 22.2%, 22.6% and 22.8%, while moderately suitable (S2) constitutes 36.7%, 37.2% and 37.4% and the marginally suitable (S3) are 13.1%, 13.1% and 12.5% respectively. Whereas, currently not suitable (N1) accounts 1.9%, 1.7% and 1.3% and the permanently not suitable constitutes 26.1%, 26.1% and 26.1% respectively. However, our results also reveal the total land suitability for the mentioned crops comprise 14862 ha (27.7%) is unsuitable (N1 & N2) and 38739 ha (72.3%) represent S1, S2 and S3 of the total land area. This study provides an approach to identify and classify land in relation to the suitability to support selected industrial cropland. It also provides insights for proper land use planning and appropriate management, which could help policy makers, planners, and decision-makers align development projects with the concurrent goal of improving long-term agricultural productivity. A GIS based approach for evaluating land is useful for sustainable agricultural planning.