Incorporating geospatial techniques in modelling of land use and land cover to aid prediction of future sites for water reservoirs

Abstract

To enable effective and reliable planning for development, understanding patterns in land use and land cover is very important. Earth observations and geospatial technologies have gone a long way to provide tools that can solve knowledge gaps in this regard. The aim of this study to produce maps that show suitable future sites for water reservoirs based on land use land cover prediction of future demand. Multi-temporal satellite image data from Landsat for the years 1995, 2010, and 2016 were used for this purpose. The study applied a hybrid method of image classification, by applying a combination of both unsupervised and supervised classification methods and cartogerising the study area into four themes (classes). The study then went ahead to simulate and predict future trends of urban growth using the Cellular Automata-Markov Model using the outputs from the classification processes and land use land cover change drivers. The study used the classified images of 1995 and 2010 to simulate and optimize the prediction model in TerrSet’s Land change Modeler and the 2016 image to validate the prediction model. The predicted land use land cover map output represented future service demand for National Water and Sewerage Corporation. This map was then used as one of the criteria in a weighted overlay model to determine the best locations for water reservoirs in the future (2040) that satisfied a certain set of rules. The study identified three locations falling in villages of Nsasa (Wakiso District), Bukerere, and Natonko (Mukono District) as actionable sites for immediate response.