Research Progress in Spatiotemporal Dynamic Simulation of LUCC

Wenhao Wan, Yongzhong Tian (), Jinglian Tian, Chengxi Yuan, Yan Cao and Kangning Liu
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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
Yongzhong Tian: Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China
Jinglian Tian: Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China
Chengxi Yuan: Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China
Yan Cao: POWERCHINA GUIYANG Engineering Corporation Limited, Guiyang 550081, China
Kangning Liu: Chongqing Geomatics and Remote Sensing Center, Chongqing 400715, China

Sustainability, 2024, vol. 16, issue 18, 1-18

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.

Keywords: LUCC; change simulation; driving factors; spatiotemporal scale; artificial intelligence; large language models (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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