Kolhapur City Urban Growth Modeling Using ANN Based on Multitemporal Remote Sensing

Abstract

A QGIS plugin called MOLUSCE and an Artificial Neural Network (ANN) model were used to simulate the prediction of urban expansion in this study. This study's objectives are to illustrate Kolhapur City's urban growth during a 20-year period and to
forecasting future urban growth through the use of an ANN model for year 2031. Remote sensing images from Landsat ETM+ and OLI were used to produce land cover maps for the years 2001 and 2021, respectively. The kappa coefficient and overall accuracy for all identified maps were above 82 and 85 percent, respectively. The simulation's findings show that in 2021, -269.58 ha of
vegetation would be lost, whereas -1256.85 ha of bare land will be turned into populated areas in 2031.