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<p>Due to the significant industrial growth, this study was conducted to classify, analyze, and predict land use and land cover (LULC) changes in Bazian using Landsat imagery from 2004, 2014, and 2024. LULC maps were generated and classified using the Maximum Likelihood Classifier (MLC), and future scenarios were modeled using the Cellular Automata-Markov (CA-Markov) model. Validation of the 2024 simulated map against the actual classified map showed strong agreement, with accuracy indices of Kno = 0.8241, K<sub>location</sub> = 0.7362, and K<sub>standard</sub> = 0.7051. According to this validation, future LULC scenarios were predicted for 2034, 2044, and 2074. The projections expose significant trends in land transformation and industrial growth, with continued urban growth and an increase in cement industry areas. Sparse vegetation and barren land are expected to show gradual shifts over the long term. Between 2024 and 2034, agricultural land increased by 41.2%, dense vegetation by 1.8%, and built-up area by 27.2%, while sparse vegetation, barren land, and cement fields declined by 17.2%, 13.2%, and 6.2% respectively. From 2024 to 2044, further increases were projected in agricultural land (47.1%), dense vegetation (10.4%), cement fields (5.3%), and built-up areas (44.3%), whereas greenhouse areas (-18.1%), sparse vegetation (-21.4%), and barren land (-18.7%) are expected to shrink. Long-term projections for 2024–2074 indicate continued increases in agricultural land (53.5%), dense vegetation (17.9%), cement fields (16.8%), and built-up area (65.8%). These findings offer critical insights for decision-makers, stakeholders, policymakers, and urban planners to better understand and manage land use trends in Bazian.</p>

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Spatiotemporal dynamics of land use land cover changes and future prediction using CA–Markov model: a case study of Bazian, Sulaimani district, Kurdistan region Iraq

  • 期刊论文

  • 发表日期：

    2026年2月10日

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  • Kwestan O. Abdalkarim,
  • Peshawa M. Najmaddin,
  • Nabaz R. Khwarahm

摘要

Due to the significant industrial growth, this study was conducted to classify, analyze, and predict land use and land cover (LULC) changes in Bazian using Landsat imagery from 2004, 2014, and 2024. LULC maps were generated and classified using the Maximum Likelihood Classifier (MLC), and future scenarios were modeled using the Cellular Automata-Markov (CA-Markov) model. Validation of the 2024 simulated map against the actual classified map showed strong agreement, with accuracy indices of Kno = 0.8241, Klocation = 0.7362, and Kstandard = 0.7051. According to this validation, future LULC scenarios were predicted for 2034, 2044, and 2074. The projections expose significant trends in land transformation and industrial growth, with continued urban growth and an increase in cement industry areas. Sparse vegetation and barren land are expected to show gradual shifts over the long term. Between 2024 and 2034, agricultural land increased by 41.2%, dense vegetation by 1.8%, and built-up area by 27.2%, while sparse vegetation, barren land, and cement fields declined by 17.2%, 13.2%, and 6.2% respectively. From 2024 to 2044, further increases were projected in agricultural land (47.1%), dense vegetation (10.4%), cement fields (5.3%), and built-up areas (44.3%), whereas greenhouse areas (-18.1%), sparse vegetation (-21.4%), and barren land (-18.7%) are expected to shrink. Long-term projections for 2024–2074 indicate continued increases in agricultural land (53.5%), dense vegetation (17.9%), cement fields (16.8%), and built-up area (65.8%). These findings offer critical insights for decision-makers, stakeholders, policymakers, and urban planners to better understand and manage land use trends in Bazian.