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Abstract A rational land use plan is of great significance for avoiding high carbon emissions. The simulations of land use optimization from the perspective of low-carbon economy are conducive to the development of green economy and the scientific allocation of land resources. Taking Beijing as an example, this study incorporated the points of interest (POI) into the BP-ANN algorithm module of the FLUS model and verified the simulation accuracy of the improved model through comparison using the land use data of 2010 and 2020. On this basis, by coupling the Markov method and the order preference by similarity ideal solution (TOPSIS) method, this study simulated and analyzed the structure and spatial layout of land quantity in the study area in 2030 under the natural evolution scenario and the low-carbon economy scenario. The results show that: ① Compared with those of the original FLUS model, the Kappa coefficient and the overall accuracy of the improved model by incorporating POI data increased by 4.85% and 3.42%, respectively. These results indicate that the improved model had higher simulation accuracy. ② The simulation results verified that, under the natural evolution scenario, the carbon emission and the land for construction would increase by 7.70% and 7.68%, respectively, and the areas of farmland and grassland would continue to decline. ③ Under the low-carbon economy scenario, the carbon emissions would be reduced by 198.49×104 t, the continuous expansion trend of construction land would be curbed, the occupation of grassland in low mountainous areas would be mitigated, and the area of forest land in the north would increase significantly. The results show that the simulation accuracy of the land use model would change with urban development elements and that the incorporation of POI data helped to provide more effective decision support for land planning. The low-carbon economy-oriented land structure adjustment and spatial layout optimization can be used as a reference for the rational use, planning, and layout of regional lands.
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| Keywords
POI data
FLUS model
scenario simulation
low-carbon economy
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Issue Date: 20 March 2023
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2023,
Vol. 35
), HU Ruike(
