Assessment and prediction of land use land cover changes: A case of Lake Kijanebalola watershed in Rakai district, Uganda
Abstract
This research focused on the assessment of historical trends and prediction of future land use land cover changes in Lake Kijanebalola Watershed in Rakai district in Uganda using remote sensing (RS) and geographical information system (GIS). Land use is a threat to environment conservation and this is evident as farmers in the Lake Kijanebalola watershed have taken on large scale cultivation. Lake Kijanebalola watershed was delineated using a Digital Elevation model (DEM) and the district boundary data for Uganda (2018 datasets). Landsat images for 2000, 2010 and 2020 were processed to map land use and land cover changes. Multispectral images from Landsat Thematic Mapper (TM), Enhanced Thematic Mapper plus (ETM+) and OLI were used as a source for satellite images. The data was downloaded from United States Geological Survey (USGS) Earth Explorer which is an open source. The imageries were classified in ArcGIS using the Maximum likelihood classification method (supervised classification technique) into seven (7) classes (Built up areas, Agricultural land, Water bodies, Forest/shrub land, bare land, wetland and Glass land). The future land use maps for 2030 was predicted using the Markov chain model using the Idrisi Selva software by using the results of the land use change maps for the years 2010 and 2020. The overall supervised classification accuracy was 83 % for 2000, 77 % for 2010 and 83 % for 2020 with kappa coefficient values of 0.88, 0.78, and 0.86 for 2000, 2010, and 2020 respectively. The results indicated that within the study period of 20 years (2000 to 2020), agriculture land, shrub land, built up area, bare land and water body increased by 14.14 %, 5.71 %, 0.48 %, 0.39 % and 0.14 % respectively. In the same period (2000 to 2020), grassland and wetland decreased by 17.62 % and 3.23 % respectively. A prediction for 2030 results showed that agriculture land, shrub land and water body will decrease by 5.59 %, 4.25 % and 0.49 % respectively whereas an increase in grassland, wetland, built up area and bare land of 7.66 %, 0.61 %, 0.26 %, and 1.79 % respectively. The study results are important to the research institutes, Ministry of Agricultural, Animal Industries and Fisheries (MAAIF), and the Ministry of Water and Environment (MWE) to guide their decisions on the Lakes catchment management measures and for future planning.