Prediction of Land Use Change in Katsina-Ala through a Geospatial Approach

Abstract

The objective of this study was to quantify land use and land cover (LULC) changes and predict future urban growth in Katsina-Ala. Three Landsat satellite images TM, ETM+ and OLI for 1987, 2007 and 2017 respectively were classified using maximum likelihood classifier in Idrisi Selva to detect the land cover changes and a classification accuracy of 87.18%, 89.32% and 91.6 for 1987, 2007 and 2017 maps was achieved. The result of the classification revealed that between 1987 and 2017, urban area increased by 80.38ha (102.17%) at the rate of 3.41%, farmland increased by 88453ha (133.56%) at the rate of 4.45% per year, forest declined by -4219ha (-5.92%) at the rate of -0.2% and grassland declined by 53656ha (-44.54%) at the rate of -1.48%. The study found that evidence likelihood and the distance from rivers. urban areas and elevation were the most important factors shaping urban growth in Katsina-Ala. Thereafter, a Multilayer Perceptron Markov (MLP-Markov) model was used to model transition potentials of various LULC types to predict future changes in 2030. The model had a reliability of 85.8% after validation. The results of the prediction show that urban area will increase from 5.92% to 6.35% with forest declining from 10.8% to 9.46%. It reveals that Katsina-Ala will grow at the rate of 0.46%. Analysis of the prediction revealed that the rate of urban growth will continue and would certainly threaten forest areas in the area. Katsina-Ala stands the risk of extreme deforestation if appropriate measures are not taken.