Simulation analysis of rural land use using rate of change driven by population and economic dynamics - A case study of Huangguashan village in Chongqing, China

Hong Jin, Heping Li, Jia Lee and Weitong Sun

Ecological Modelling, 2023, vol. 475, issue C

Abstract: The conflicts between various types of land use in rural areas of China are becoming more and more obvious, therefore, how to more accurately simulate and predict the future land cover changes in rural areas has become an important topic of current academic research. In this research, the dynamic multi-year data was used to replace the static one-year data and brought into the future land use simulation (FLUS) model for the simulation of land use in Huangguashan village, Chongqing, China. The accuracy results of the two sets of simulations are compared in terms of accuracy kappa coefficient and Overall Accuracy (OA). Next, using the improved FLUS model, four different future development scenarios of priority ecological conservation, priority economic development, priority farmland conservation and priority integrated development were set up to simulate the land use data of Huangguashan village in 2030. The results of the research found that (1) the kappa coefficient and OA values were higher for the simulation of FLUS model using dynamic multi-year data. The simulation results are closer to the actual situation, especially the simulation enhancement effect is more obvious for the long-term; (2) by comparing the land use types of four different future development scenarios, it is suggested that Huangguashan village should adopt the integrated development priority scenario as the direction of future policy formulation and planning development in the future. This research can provide more effective scientific decision support and significance for governments to formulate multi-scheme rural land use development policies.

Keywords: Dynamic multi-year data; FLUS model; Land use simulation; Simulation accuracy; Huangguashan village (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:475:y:2023:i:c:s0304380022003027

DOI: 10.1016/j.ecolmodel.2022.110204

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