Predicting and detecting the trend of temporal and spatial changes of land use using land change modeler

The purpose of this study is to investigate land use changes in the past and predict future land use using land change modeler in Halil River watershed. The detection of land use changes was performed using Landsat satellite images (L5-TM-1991, L7- ETM+-2003 and L8-OLI-2020). Transition potential modeling was done using MLP neural network method and eight variables including altitude, slope, aspect, distance to road, distance to river, distance to agricultural lands, distance to urban and Normalized Difference Vegetation Index (NDVI). Finally, the Markov chain was used to predict future land use changes. Investigating the calibration periods using kappa statistics showed that the period of 1991-2020 had the highest accuracy to predict land use for 2041. The results of land use changes indicated that during the calibration period, among the six categories namely rangeland, agricultural land, residential land, barren land, rock and orchard, the highest increase and the highest decrease in area was related to agricultural lands and rangelands by 293.7 and 382.6 km2, respectively. Also, the area of barren lands, orchard and residential lands has increased and rocky lands have remained unchanged. The degradation of rangelands has been more in line with the conversion of these lands into agricultural, orchard and residential lands. Also, the prediction of future land use map (2041) using land change modeler showed that , the area of rangelands will decrease by 201.1 km2 and the area of agricultural lands, residential lands, orchards and barren lands will increase by 158.01, 22.38, 20.2 and 0.53 km2, respectively.