Land Use Change Simulation in Rapid Urbanizing Regions: A Case Study of Wuhan Urban Areas
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- Mansour, Shawky & Al-Belushi, Mohammed & Al-Awadhi, Talal, 2020. "Monitoring land use and land cover changes in the mountainous cities of Oman using GIS and CA-Markov modelling techniques," Land Use Policy, Elsevier, vol. 91(C).
- Rahel Hamad & Heiko Balzter & Kamal Kolo, 2018. "Predicting Land Use/Land Cover Changes Using a CA-Markov Model under Two Different Scenarios," Sustainability, MDPI, vol. 10(10), pages 1-23, September.
- Brian Pickard & Joshua Gray & Ross Meentemeyer, 2017. "Comparing Quantity, Allocation and Configuration Accuracy of Multiple Land Change Models," Land, MDPI, vol. 6(3), pages 1-21, August.
- Xueru Zhang & Jie Zhou & Wei Song, 2020. "Simulating Urban Sprawl in China Based on the Artificial Neural Network-Cellular Automata-Markov Model," Sustainability, MDPI, vol. 12(11), pages 1-13, May.
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- Weiwei Zhang & Wanqian Zhang & Jianwan Ji & Chao Chen, 2024. "Urban Ecological Quality Assessment Based on Google Earth Engine and Driving Factors Analysis: A Case Study of Wuhan City, China," Sustainability, MDPI, vol. 16(9), pages 1-23, April.
- Auwalu Faisal Koko & Zexu Han & Yue Wu & Siyuan Zhang & Nan Ding & Jiayang Luo, 2023. "Spatiotemporal Analysis and Prediction of Urban Land Use/Land Cover Changes Using a Cellular Automata and Novel Patch-Generating Land Use Simulation Model: A Study of Zhejiang Province, China," Land, MDPI, vol. 12(8), pages 1-21, August.
- Jing Liu & Chunchun Hu & Xionghua Kang & Fei Chen, 2023. "A Loosely Coupled Model for Simulating and Predicting Land Use Changes," Land, MDPI, vol. 12(1), pages 1-19, January.
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Keywords
remote sensing image interpretation; dynamic land use change; Markov–ANN–CA model; driving force; simulation-based prediction;All these keywords.
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