Document Type : Practical- case study
Authors
1 Ferdowsi
2 *
3 Department of Geography, Ferdowsi University of Mashhad, Mashhad, Iran
Abstract
This research aims to simulate land use and land cover (LULC) changes in Herat City. The research method is applied in terms of purpose and descriptive-analytical in terms of nature and method. Using the neural network and Markov chain model (CA Markov) and Land Change Modeler, land use changes were examined for 2000, 2010, and 2021, and predictions were made for 2021-2030. First, Landsat satellite images for 2000, 2010, and 2021 were downloaded for the study area from the USGS website. After extracting the area using ArcGIS and TerrSet software, the images were classified into seven land use categories using the Supervised Classification Method and Maximum Likelihood Estimation technique. During the 2000-2010 period, the percentage changes in barren land along riverbeds (2386%), water bodies (72%), and built-up land (57%) were positive. These years coincide with the period of Afghanistan's liberation from the Taliban, during which the influx of internal and external migrants to Herat city increased significantly. Additionally, during the 2010-2021 period, the percentage changes in clay barren land (134%), sandy barren land (40%), and built-up land (3.7%) were positive, corresponding with the growth of Herat City. The land use change prediction for the 2021-2030 period, using the Land Change Modeler and CA Markov Chain Models, indicates that clay barren land (15.7%) and built-up land (2.8%) will experience positive changes and increase in area. Only green space land use will face negative changes and a decrease in area (2.8%-). Spatial and temporal analysis shows that land use changes in Herat city are shifting from agricultural land, green spaces, water, and riverbank areas towards built-up and barren lands.
Keywords
Main Subjects
Send comment about this article