Simulation Analysis of Land Use Change via the PLUS-GMOP Coupling Model

Ligang Wang, Dan Liu, Xinyi Wu, Xiaopu Zhang, Qiaoyang Liu, Weijiang Kong, Pingping Luo and Shengfu Yang ()
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Ligang Wang: School of Public Administration, China University of Geosciences (Wuhan), Wuhan 430074, China
Dan Liu: Ningxia Natural Resources Information Center, Yinchuan 750002, China
Xinyi Wu: Tibet Datang International Upper Nujiang River Hydropower Development Co., Ltd., Lhasa 850001, China
Xiaopu Zhang: State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
Qiaoyang Liu: Ningxia Natural Resources Information Center, Yinchuan 750002, China
Weijiang Kong: School of Earth Science and Engineering, Southwest Jiaotong University, Chengdu 610097, China
Pingping Luo: School of Water and Environment, Chang’an University, Xi’an 710054, China
Shengfu Yang: School of Public Administration, China University of Geosciences (Wuhan), Wuhan 430074, China

Land, 2025, vol. 14, issue 4, 1-26

Abstract: It is crucial to simulate land use change and assess the corresponding impact on ecosystem services to develop informed land management policies and conservation strategies. To comprehensively simulate the patterns of land use change under different management policies and evaluate the corresponding ecological service values (ESV), a method for coupling the Generalized Multi-Objective Programming (GMOP) model and Patch-generating Land Use Simulation (PLUS) model is proposed in this study. First, the GMOP model is used to obtain optimized land use solutions under different scenarios. Then, the PLUS model is used to analyze the mechanism driving land expansion, explore land conversion patterns, and, ultimately, achieve spatial expression of land use quantity changes. The uncertain parameters in the coupled model are processed by intuitionistic fuzzy numbers. The coupled model successfully integrates the outstanding spatiotemporal dynamic simulation capability of the PLUS model and the multiobjective optimization advantages of the GMOP model, effectively overcoming the limitations of applying a single model in land use analysis. Finally, four different scenarios are established for land use change, namely, business as usual (BAU), economic efficiency priority (RED), ecological protection priority (ELP), and coordinated economic and ecological development (EEB), to predict land use change trends and ecological service values. A case study of the Ningxia Hui Autonomous Region demonstrates that the area of agricultural land exhibits a stable growth trend in the four different scenarios, with the majority of the expansion occurring through the conversion of grassland. Concurrently, the rate of expansion of construction land is highest in the BAU scenario at 31.72%, compared with the area in 2020. This is notably higher than the rates observed in the RED (10.10%) and EEB (9.47%) cases. With the expansion of construction land, the ESV decreased by 3.485 billion, 1.514 billion, and 1.658 billion yuan in the BAU, RED, and ELP scenarios, representing 41.72%, 24.96%, and 34.05% decreases in ESV, respectively. The proposed integrated methodology accounts for various spatial constraints and land conversion behaviors, thereby ensuring a true and accurate reflection of land use dynamics. This methodology supports the quantification of ESV under different land management strategies, thereby providing policymakers with effective support for data-driven sustainable land use planning and conservation.

Keywords: land use change; ecosystem services; PLUS model; GMOP model; sustainability; spatial planning (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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