农村建设用地整治潜力规模与空间格局协同模拟研究 ——以湖北省宜城市为例

研究目的:提出一种农村建设用地整治潜力规模与空间格局协同预测模拟模型,为国土空间规划和全域土地综合整治提供更加准确的决策依据。研究方法:首先对社会经济宏观因素影响下的区域农村建设用地整治潜力规模进行分析,进而利用土地利用时空建模方法对农村建设用地图斑的整治概率进行预测,实现潜力规模约束下的整治潜力空间格局模拟,并以湖北省宜城市为案例区对模型的性能进行验证。研究结果:(1)宜城市2021—2035年农村建设用地整治的理论和现实潜力规模分别为4912.46 hm²和2201.94 hm²;(2)模型对宜城市农村建设用地图斑的整治潜力格局模拟准确率为81.58%,召回率为0.9879。研究结论:模型实现了对农村建设用地整治潜力规模与空间格局的协同预测与模拟,能为国土空间规划和全域土地综合整治等专项规划提供更加精细的决策依据。

A Potential Estimation and Geospatial Simulation Model for the Rural Construction Land Consolidation: A Case Study of Yicheng County, Hubei Province

The purpose of this paper is to develop a potential estimation and geospatial simulation model for rural construction land consolidation to better provide decision-support for spatial planning and land use policy formulation. The research methods are as follows. Firstly, a multi-factor comprehensive evaluation method is used to measure the impact of social and economic macro factors on rural construction land consolidation. Then, the realistic consolidation potential of rural construction land was predicted based on the analysis of regional demographic, economic and social factors and their influence on rural construction land consolidation. Second, the spatial-temporal data of land use and machine learning approach were employed to simulate the consolidation probability of rural construction land at the micro level under the area constraint of the realistic consolidation potential. Third, Yicheng County in Hubei Province was chosen as the study area to evaluate the performance of the model developed in this study. The results show: 1) the theoretical and realistic consolidation potential of rural construction land in Yicheng during 2021 and 2035 are 4 912.46 hm2 and 2 201.94 hm2, respectively. 2) The spatial simulation accuracy of the model is 81.58% and the recall rate is 0.987 9, which indicates the performance of the model is satisfactory. In conclusion, according to the consolidation probability and the area of the patches obtained, the results simulated by the model developed in this study can provide more reliable decision-making basis for spatial planning and regional comprehensive land consolidation.