Land Suitability Analysis for Maize Cultivation Using Remote Sensing Data and Multicriteria Decision Process

Résumé

The increase in population, urbanisation, mining of solid minerals, excavation, and sand mining for construction purposes are increasingly shrinking and reducing land sizes and shapes for agricultural purposes. However, the identification, location, and suitability of the study area for maize crop production have not been fully explored or documented. Remote sensing data from Landsat 8 OLI were processed to produce layers for the Normalised Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), Land Surface Temperature, Slope, Land Cover, Digital Elevation Model (DEM), Soil Texture, and Rainfall. These were considered for obtaining the criteria maps, which were used as input into the multicriteria analysis algorithm. The weighted overlay analysis was conducted in a Geographic Information Systems (GIS) environment. The maize suitability map shows that 18.92% of the land is highly suitable, 58.80% is moderately suitable, 12.57% is marginally suitable, and 9.71% is marginally unsuitable. The methodology enabled the identification of land suitable for maize farming and can be considered for sustainable agricultural planning and management. Though the approach provides meaningful insight into maize crop suitability, other methodologies can be explored and compared. In sum, the paper provides a guide for future land-suitability analyses of other crops to ensure food security.

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