Land Use Changes Monitoring over 30 Years and Prediction of Future Changes Using Multi-Temporal Landsat Imagery and the Land Change Modeler Tools in Rafsanjan City (Iran)

Abstract

The purpose of this study is predicting and modeling of future changes in the Rafsanjan area, using remote sensing and GIS. The multispectral satellite data obtained from Landsat 5 (TM), 7 (ETM+) and 8 (OLI) for the years 1986, 1992, 1998, 2004, 2010 and 2016, were used respectively. The supervised classification technique was applied to multitemporal Landsat images. Rafsanjan city was classified into four major LU classes including urban areas, pistachio gardens, bare-land, and salt. Change detection analysis was performed to compare the quantities of land use class variation between time intervals. The results revealed both increase and decrease of the different LU classes from 1986 to 2016. enerally, the conclusions indicate that during the study period, Urban areas and pistachio gardens have increased by 6.89% (18.47 km2) and 12.76% (34.18 km2) while bare-land and salt have decreased by 13.43% (35.97 km2) and 9.96% (26.68 km2), respectively. In order to predict the future land use changes map, we used the Land change modeler tools of IDRISI software. Consequently, the predicted land use map of 2022 was prepared based on the trend of 30 years of land use changes and effective variables.

Keywords: Urban Expansion, Change Detection, Remote Sensing, Geosciences, Kerman