Modelling of Agricultural Land Use Changes Under Different Development Scenarios in Greater Kampala Metropolitan Area

Abstract

It is imperative to have a retrospective comprehension of the scale and speed at which agricultural lands are being converted in metropolitan areas in order to ensure the future of local food production. This study aimed at understanding agricultural land use changes under different development scenarios in Greater Kampala Metropolitan Areas (GKMA). The analysis employed remote sensing and GIS technologies. Landsat data from 6 distinct years from 1995 to 2020 was used for analysis. The application of remote sensing techniques encompassed image pre- processing and processing operations. Subsequently, a supervised classification methodology using maximum likelihood method was executed. Land change Modeler was utilized for change analysis. The study utilized a combination of Cellular Automata (CA) and Markov Chain to forecast the future of Agricultural lands by the year 2050. This prediction considered two growth scenarios, the planned growth scenario and the Business-As-Usual (BAU) growth scenario. The modelling technique integrated land use and land cover (LULC) maps along with four explanatory factors, namely slope, proximity to roads, proximity to built-up areas, and elevation. The results indicate that, by 2050, agricultural lands are projected to increase by 3.6% under the BAU scenario covering northwestern part of GKMA in the districts of Mpigi and Wakiso. Under the planned growth scenario Agricultural lands are expected to increase by 7.2% covering the northern part of GKMA but evenly distributed across the areas of Kawanda, Namulonge, Nakagere in the districts of Mukono, Wakiso and Mpigi. Ultimately, based this comprehensive evaluation of the results, planned growth scenario is crucial for ensuring preservation of Agricultural lands across the Greater Kampala Metropolitan Area.