Land Use and Cover Change Assessment and Dynamic Spatial Modeling in the Ghara-su Basin, Northeastern Iran
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RESEARCH ARTICLE
Land Use and Cover Change Assessment and Dynamic Spatial Modeling in the Ghara-su Basin, Northeastern Iran Sharif Joorabian Shooshtari1 • Tatiana Silva2 • Behnaz Raheli Namin1 • Kamran Shayesteh1 Received: 22 November 2018 / Accepted: 8 October 2019 Ó Indian Society of Remote Sensing 2019
Abstract This study predicts land cover dynamics in Ghara-su Basin, northeastern Iran, using GIS modeling and landscape metrics. Land use/land cover (LULC) mapping for the years 1988, 2002, and 2008 was classified from remotely sensed imagery to monitor and predict future LULC changes. FRAGSTATS was used to quantify landscape structure by a series of landscape indices extracted from LULC data. Principal component analysis was performed on 28 landscape indexes to explore the degree of redundancy. A predicted LULC map for the year 2022 was created based on multilayer perceptron artificial neural network and the past trends of land variations. The predicted model accuracy assessment was accomplished by comparing the actual LULC map of 2008 with a predicted map for the year 2008. Results of change analysis showed a reduction of forest (12% of forest area) and bare land (20% of bare land area). Agricultural land, waterbodies, urban areas, and grassland increased about 8%, 11%, 27%, and 35%, respectively, between 1988 and 2008. Bare land and agricultural land are the main contributors to increased residential zones. Landscape metrics indicate an increase in fragmentation and diversity during the study period. The predicted map for 2022 shows that forest is becoming degraded and residential areas, agricultural lands, and grassland will increase compared with those under the 2008 land cover. The results of this study, where areas prone to change are mapped, are expected to support environmental planning and management initiatives and, in doing so, prevent further negative changes in landscape function and structure. Keywords Simulating land use change Landscape metrics GIS-based modeling Artificial neural network Iran
Introduction
& Sharif Joorabian Shooshtari [email protected]; [email protected] Tatiana Silva [email protected] Behnaz Raheli Namin [email protected] Kamran Shayesteh [email protected] 1
Department of Environment, Faculty of Natural Resources and Environment, Malayer University, Malayer, Hamedan 65719-95863, Iran
2
Basin Modeling Laboratory, Institute of Geosciences, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
Landscape structure is the spatial relationship between land use and landscape elements. Variation in land use and landscape processes has accelerated during recent decades mostly because of increases in population density, infrastructure, rapid urbanization, and other anthropogenic factors (Deng et al. 2009; Fichera et al. 2012). Understanding how and why LULC changes can occur is fundamental for assessing and monitoring landscape dynamics. Fragmentation and transformation are typical processes of landscape change. Lan
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