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Research Progress in Spatiotemporal Dynamic Simulation of LUCC

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  • Wenhao Wan

    (Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China
    Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China
    Daotian Science and Technology Limited Company, Chongqing 400715, China)

  • Yongzhong Tian

    (Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China
    Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China
    Daotian Science and Technology Limited Company, Chongqing 400715, China)

  • Jinglian Tian

    (Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China
    Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China
    Daotian Science and Technology Limited Company, Chongqing 400715, China)

  • Chengxi Yuan

    (Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China
    Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China
    Daotian Science and Technology Limited Company, Chongqing 400715, China)

  • Yan Cao

    (POWERCHINA GUIYANG Engineering Corporation Limited, Guiyang 550081, China)

  • Kangning Liu

    (Chongqing Geomatics and Remote Sensing Center, Chongqing 400715, China)

Abstract

Land Use and Land Cover Change (LUCC) represents the interaction between human societies and the natural environment. Studies of LUCC simulation allow for the analysis of Land Use and Land Cover (LULC) patterns in a given region. Moreover, these studies enable the simulation of complex future LUCC scenarios by integrating multiple factors. Such studies can provide effective means for optimizing and making decisions about the future patterns of a region. This review conducted a literature search on geographic models and simulations in the Web of Science database. From the literature, we summarized the basic steps of spatiotemporal dynamic simulation of LUCC. The focus was on the current major models, analyzing their characteristics and limitations, and discussing their expanded applications in land use. This review reveals that current research still faces challenges such as data uncertainty, necessitating the advancement of more diverse data and new technologies. Future research can enhance the precision and applicability of studies by improving models and methods, integrating big data and multi-scale data, and employing multi-model coupling and various algorithmic experiments for comparison. This would support the advancement of land use spatiotemporal dynamic simulation research to higher levels.

Suggested Citation

  • Wenhao Wan & Yongzhong Tian & Jinglian Tian & Chengxi Yuan & Yan Cao & Kangning Liu, 2024. "Research Progress in Spatiotemporal Dynamic Simulation of LUCC," Sustainability, MDPI, vol. 16(18), pages 1-18, September.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:18:p:8135-:d:1480218
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    References listed on IDEAS

    as
    1. Dang, Anh Nguyet & Kawasaki, Akiyuki, 2017. "Integrating biophysical and socio-economic factors for land-use and land-cover change projection in agricultural economic regions," Ecological Modelling, Elsevier, vol. 344(C), pages 29-37.
    2. Britaldo Silveira Soares-Filho & Daniel Curtis Nepstad & Lisa M. Curran & Gustavo Coutinho Cerqueira & Ricardo Alexandrino Garcia & Claudia Azevedo Ramos & Eliane Voll & Alice McDonald & Paul Lefebvre, 2006. "Modelling conservation in the Amazon basin," Nature, Nature, vol. 440(7083), pages 520-523, March.
    3. Hanchen Wang & Tianfan Fu & Yuanqi Du & Wenhao Gao & Kexin Huang & Ziming Liu & Payal Chandak & Shengchao Liu & Peter Katwyk & Andreea Deac & Anima Anandkumar & Karianne Bergen & Carla P. Gomes & Shir, 2023. "Scientific discovery in the age of artificial intelligence," Nature, Nature, vol. 620(7972), pages 47-60, August.
    4. Hanchen Wang & Tianfan Fu & Yuanqi Du & Wenhao Gao & Kexin Huang & Ziming Liu & Payal Chandak & Shengchao Liu & Peter Katwyk & Andreea Deac & Anima Anandkumar & Karianne Bergen & Carla P. Gomes & Shir, 2023. "Publisher Correction: Scientific discovery in the age of artificial intelligence," Nature, Nature, vol. 621(7978), pages 33-33, September.
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