A GIS based land suitability analysis for sustainable agricultural planning in Gelda catchment, Northwest Highlands of Ethiopia

Abstract

The present study was carried out to examine the suitability status of plots of land for selected land utilization types (teff -Eragrostis tef, maize -Zea mays and finger millet -Eleusine coracana). The land mapping units of the study area, prepared from land resource survey, were used for the purposes of land evaluation. The methodology used for land suitability evaluation was GIS-based multi-criteria evaluation following FAO (1976) guidelines involving matching diagnostic land qualities against crop requirements and assigning suitability rates for each land qualities. The weighted overlay analysis combining diagnostic soil, climate and topographic factors showed that the largest coverage (76.04, 69.52 and 67.79%) of the study area is classified as moderately suitable for teff, maize, and finger millet cultivation, respectively. The vector overlay analysis results revealed that about 20.25 and 63.92% of the catchment are moderately suitable and marginally suitable for cultivation of all selected land utilization types. This showed that competitions for the same parcel of land by different uses were possible. Thus, farmers could have freedom to choose a range alternative land utilization types with the same suitability level and allocate land utilization type that best meet his/her interest. Therefore, land suitability analysis for agricultural crops using multi-criteria evaluation in a GIS environment is a strong tool for measuring and valuating land in terms of the varying importance to decision makers for sustainable rainfed agriculture.

Studying Patterns of Rainfall and Topographical Clustering for Kingdom of Bahrain: An Application of Big Data

“…GIS is a platform which provides integration between the spatial data of an area and its non-spatial characteristics. GIS is a popular platform to analyze spatial data based on non-spatial attributes [30]. Its advantages include integration of data from different sources and the ability to generate quarries and filters for the feature of interest.…”

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