Assessment of Land Use Land Cover Changes and Future Predictions Using CA-ANN Simulation for Selangor, Malaysia

Land use land cover (LULC) has altered dramatically because of anthropogenic activities, particularly in places where climate change and population growth are severe. The geographic information system (GIS) remote sensing widely used techniques for monitoring LULC changes. This study aimed to assess the changes predict future trends Selangor, Malaysia. satellite images from 1991–2021 were classified develop maps using support vector machine (SVM) classification ArcGIS. image was based on six different classes, i.e., (i) water, (ii) developed, (iii) barren, (iv) forest, (v) agriculture, (vi) wetlands. resulting illustrated area 1991 2021 water lands increased by 15.54%, 1.95%, 0.53%, respectively. However, agricultural, wetlands decreased 3.07%, 14.01%, 0.94%, cellular automata-artificial neural network (CA-ANN) technique 2031–2051. percentage correctness simulation 82.43%, overall kappa value 0.72. prediction 2031–2051 decreasing agricultural 3.73%, forest 1.09%, barren 0.21%, 0.06%, 0.04% increasing developed 5.12%. outcomes this provide crucial knowledge that may help developing sustainable planning management, as well assist authorities making informed decisions improve environmental ecological conditions.