Simulations of the low-carbon land use scenarios of Beijing based on the improved FLUS model
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摘要: 合理的土地利用计划对避免高碳排放有着重要意义,进行低碳经济视角下的土地利用优化模拟有利于绿色发展和土地资源科学配置。以北京市为例,将兴趣点(point of interest,POI)数据纳入FLUS模型的BP-ANN算法模块中对其进行改进,利用2010年和2020年2期土地利用数据对改进模型的模拟精度进行对比验证。在此基础上,耦合Markov法及理想点法,对研究区2030年自然演变情景及低碳经济情景下的土地数量结构和空间布局进行模拟分析。研究结果表明: ①引入POI数据的FLUS模型在模拟2020年土地利用时,Kappa系数提高4.85%、总体精度提高3.42%,改进模型有利于提高模拟精度; ②经模拟验证,在自然演变情景中,碳排放量增加7.70%,建设用地面积增长7.68%,耕地、草地面积持续减退; ③在低碳经济情景中,与自然演变情景相比,碳排放量减少198.49万t,建设用地持续扩张的趋势得到遏制,浅山区草地被占用的现象得到缓解,北部林地面积增长明显。研究说明了土地利用模型的模拟精度随城市发展元素的变化而变化,纳入POI数据可以为土地规划提供更好的决策支持,低碳经济导向的土地结构调整及空间布局优化,可以为区域土地合理利用和规划布局提供参考。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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Key words:
- POI data /
- FLUS model /
- scenario simulation /
- low-carbon economy
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