Document Type
Article
Publication Date
11-10-2025
Keywords
cellular automata, Markov chain, CA–Markov, NLCD, Land use/cover change, land surface temperature, Cohen’s Kappa, Arkansas
Abstract
Land use and land cover (LULC) changes significantly shape urban environments and directly impact ecological and socioeconomic systems. This study aims to explore these interconnections by employing the Cellular Automata–Markov (CA–Markov) model to assess and predict LULC dynamics in Arkansas. Historical LULC datasets from 2001 to 2021, obtained from the National Land Cover Database, were simplified from 11 into 5 classes to facilitate analysis and effectively map transitions. The model was validated by predicting LULC for 2016 and 2021 and comparing the predictions with the real maps, achieving an overall accuracy of approximately 91.9%, using model validation metrics, including precision, recall, F1-score, and Kappa Coefficient, and highlighting the strength of the predictions. Predictions for 2026 and 2031 reveal a continuous increase in built-up areas at the expense of vegetation cover, underscoring ongoing urbanization trends. Specifically, built-up areas are projected to increase from 28.39% in 2021 to 30.15% in 2031, while vegetation cover is expected to decline from 49.30% to 47.48%. This research demonstrates the utility of the CA–Markov model in simulating urban growth patterns and provides actionable insights into sustainable urban planning and land management strategies.
Citation
Vahid, R.; Aly, M.H. An Integrated CA–Markov Modeling Framework for Forecasting Land Use and Land Cover Dynamics in Arkansas, USA. Geomatics 2025, 5, 62. https://doi.org/10.3390/geomatics5040062
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
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Environmental Health Commons, Environmental Sciences Commons, Environmental Studies Commons
Comments
Web of Science
MDPI