Evaluating the Effect of Land use Land Cover Changes on Land Suitability for Crop Production Using Remote Sensing and GIS

Abstract

The impact of Land Use Land Cover Changes (LULCC) on agricultural land from 1986 to 2016 was examined using Remote Sensing (RS) and Geographic Information System (GIS) in Kwara State, Nigeria. The aim of the study was to show how a GIS tool could be incorporated into a Multi Criteria Analysis (MCA) and an Analytical Hierarchy Process (AHP) model to assess the suitability of land. Under several conditions which define suitable land for arable cropping, the structural design of an integrated GIS-MCA-AHP was anticipated to correspond with the decision maker's preferences. Additionally, the integration was anticipated to quantify the extent of land cover modifications and assess how removal of vegetation would affect the soil. As a major factor in the analysis, the Normalized Differential Vegetation Index (NDVI) was employed with GIS and Remote Sensing (RS) technologies, and as secondary, MCA and AHP models. In Arc-Map (GIS) 10.3.1, the RS data imagery from 2016 was used and recognized by NDVI satellite images. The images were categorized according to RS data, field study data, and geographical factors. The variables were soil texture, depth, pH, organic carbon, rainfall, temperature, slope, elevation, and land use land cover. To examine the extent of land use and land cover changes in relation to soil types and land suitability, the MCA-AHP model employed a weighted sum overlay. The results showed that farming accounted for 46% of all land use, and that LULCC was primarily to blame for the loss of arable land and environmental degradation. The proportion of the total land area used for farming (farmland), the built up area, bare land, and water bodies increased from 34 to 46, 15 to 30.4, 5 to 10, and 3 to 4%, respectively. Forest land, on the other hand, saw a drop from 43 to 9.6%. While 11.40% of the total land area was highly suitable for arable cultivation, 19.30% was moderately suitable, 30.40% was marginally suitable, 23.12% was currently unsuitable, and 15.78% was permanently unsuitable. The study shows that the AHP model was useful for calculating land use weights that were comparable to those calculated using other techniques. The model was helpful in making planning decisions for land use, and thus could be useful in managing sustainable agriculture. It was concluded that in addition to the fast rate of deforestation, increasing anthropogenic activities were degrading arable land at the study site.