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Spatial modeling of land use and land cover change in Sulaimani, Iraq, using multitemporal satellite data
Spatial modeling of land use and land cover change in Sulaimani, Iraq, using multitemporal satellite data
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Spatial modeling of land use and land cover change in Sulaimani, Iraq, using multitemporal satellite data
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Spatial modeling of land use and land cover change in Sulaimani, Iraq, using multitemporal satellite data
Spatial modeling of land use and land cover change in Sulaimani, Iraq, using multitemporal satellite data

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Spatial modeling of land use and land cover change in Sulaimani, Iraq, using multitemporal satellite data
Spatial modeling of land use and land cover change in Sulaimani, Iraq, using multitemporal satellite data
Journal Article

Spatial modeling of land use and land cover change in Sulaimani, Iraq, using multitemporal satellite data

2021
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Overview
Land use/land cover (LULC) change is an important indicator used for assessing the function and health of ecosystems. Understanding the patterns of LULC change assists in managing natural resources effectively, especially for regions where there are minimal or no reported data on the status of LULC. In this study, remotely sensed Landsat satellite imagery from 5 years (i.e., 1988, 1996, 2002, 2008, and 2017), geographic information systems (GIS), and the hybrid cellular automata (CA)-Markov model were used to (i) quantify the past and present LULC changes and (ii) model the future changes in Sulaimani Province in the Kurdistan region of Iraq (KRI). To accomplish these objectives, five LULC maps with various class categories were generated using the maximum likelihood classifier (MCL). The classified maps for 1996, 2002, 2008, and 2017 were used in the hybrid model to simulate LULC maps for 2017 and 2037. The map simulated for 2017 was validated with the classified 2017 LULC map. The change analysis demonstrated that between 1988 and 2017, the built-up areas and agricultural fallow land increased by 419% and 226%, respectively. In the future predictions for 2037, built-up areas and agricultural fallow land showed increasing trends of 5.5% and 26.5%, respectively. In contrast, agricultural land, plantation land, and sparse vegetation areas were predicted to decrease by 29.4%, 65.8%, and 36.9%, respectively. In addition, in 2008, waterbodies shrank by 43.36% in comparison with their status in 1988, suggesting that 2008 was a severe drought year. These findings provide invaluable baseline information with which conservation biologists, agricultural engineers, urban planners, and decision makers can better manage natural resources and monitor environmental changes. Based on these results, sustainable development actions and an early warning system can be established.