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Evaluation and Prediction of Ecological Quality Based on Remote Sensing Environmental Index and Cellular Automata-Markov

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  • Weirong Qin

    (College of Resources and Environment, Beibu Gulf University, Qinzhou 535011, China
    Faculty of Forestry and Environment, Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia
    These authors contributed equally to this work.)

  • Mohd Hasmadi Ismail

    (Faculty of Forestry and Environment, Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia
    These authors contributed equally to this work.)

  • Mohammad Firuz Ramli

    (Faculty of Forestry and Environment, Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia)

  • Junlin Deng

    (Key Laboratory of Beibu Gulf Offshore Engineering Equipment and Technology, Beibu Gulf University, Qinzhou 535011, China)

  • Ning Wu

    (Key Laboratory of Beibu Gulf Offshore Engineering Equipment and Technology, Beibu Gulf University, Qinzhou 535011, China)

Abstract

The evaluation and prediction of ecological environmental quality are essential for sustainable development and environmental management, particularly in regions experiencing rapid urbanization and industrial growth like Johor in southern Peninsular Malaysia. This study evaluates the temporal and spatial changes in ecological environmental quality in Johor from 1990 to 2020 using the Remote Sensing Environmental Index (RSEI) and Cellular Automata-Markov (CA-Markov). A CA-Markov model was employed to predict ecological environmental quality for the next 12 months based on historical data. The results reveal significant changes over the 30 years, highlighting the dynamic nature of ecological conditions. The prediction results indicate that areas with excellent ecological quality are primarily focused in the central and northern regions, while the southern and eastern edges show mixed ecological conditions. The western region, characterized by intensive land use, shows significant environmental degradation. The poorest ecological points are mainly distributed in urban and semiurban areas with frequent human activities, such as cities, ports, and villages. These findings highlight the need for targeted environmental policies and management strategies to mitigate ecological degradation and promote sustainable development in Johor State of Peninsular Malaysia.

Suggested Citation

  • Weirong Qin & Mohd Hasmadi Ismail & Mohammad Firuz Ramli & Junlin Deng & Ning Wu, 2025. "Evaluation and Prediction of Ecological Quality Based on Remote Sensing Environmental Index and Cellular Automata-Markov," Sustainability, MDPI, vol. 17(8), pages 1-26, April.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:8:p:3640-:d:1636986
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    References listed on IDEAS

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    Cited by:

    1. Yiquan Song & Zhengwei Li & Baoquan Wei, 2025. "Regional Ecological Environment Quality Prediction Based on Multi-Model Fusion," Land, MDPI, vol. 14(7), pages 1-23, July.
    2. Yuanyuan Chen & Shaohua Lei & Qiang Yang & Jie Zhu & Yunfei Xiang, 2025. "Deep Learning-Driven Transformation of Remote Sensing Education for Ecological Civilization and Sustainable Development," Sustainability, MDPI, vol. 17(17), pages 1-24, September.

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