基于改进熵权DEA-TOPSIS模型的乡村国土综合整治格局优化

针对国土综合整治时空格局优化的多目标量化问题,以空间脆弱性和时间迫切性为切入点,构建以目标功能为主线的乡村社会-生态系统脆弱性和迫切性评价指标体系,采用改进熵权DEA模型开展脆弱性效率评价和改进熵权多因素综合模型进行迫切性评价;在此基础上,采用层次目标分解法和主导问题归因法构建“业态兴旺、形态优化、生态宜居和综合复兴”4种国土综合整治多目标格局优化方案,采用改进熵权TOPSIS分析法开展多目标最优决策定量分析,以期从有限多目标系统优选和排序视角识别和划分国土综合整治多目标时空格局类型,实现对乡村国土综合整治多目标格局优化体系构建的目的。研究以上海市青浦区184个行政村为例进行实证,研究结果表明：改进熵权DEA模型能有效克服多行政村高度关联造成的结果偏大问题,提高了空间适宜性的应用精度;改进熵权TOPSIS模型能较为准确地划分国土综合整治的多目标格局优化方案,细化各最优方案间的异质性;2018年青浦区社会-生态系统脆弱性均值表现为社会子系统脆弱性（0.605）>经济子系统脆弱性（0.577）>生态子系统脆弱性（0.549）,社会子系统脆弱成为影响该区脆弱性的重要原因;行政村社会-生态系统脆弱性空间上呈现由中部向南北递增变化趋势;而村域国土综合整治迫切性空间团聚状分异显著,其值域范围为0.435, 0.785],农业产业整治迫切性最大;针对脆弱性-迫切性多目标构建的4种多目标方案决策评价结果,将该区国土综合整治时空格局优化类型划分为16种。该研究结果丰富了乡村地理学理论,可为乡村区域治理、乡村振兴和区域可持续发展提供决策依据。

Pattern Optimization for Integrated Rural Land Management with an Improved Entropy Weight DEA-TOPSIS Model

The essence of integrated territory consolidation is the process of readjusting the relationship between man and land. Under the background of rural revitalization strategy, integrated territory consolidation has been endowed with multiple functions and objectives. Pattern optimization, which contains the comprehensive process of timing arrangement, spatial organization, and goal coordination, is a way to achieve multi-objective integrated territory consolidation. This research analyzes the problem of multi-objective quantification for optimization of spatio-temporal patterns of multi-objective integrated territory consolidation. Using spatial vulnerability and timing urgency as the key points, the index system of social-ecosystem vulnerability and urgency evaluation in rural regions with target function as the main line was constructed. The EW-DEA model and improved multi-factor synthesis model of entropy weight were used to comprehensively evaluate vulnerability efficiency and urgency. Then, the hierarchical objective decomposition method and the attribution method of leading problems were used to construct four kinds of multi-objective pattern optimization of rural integrated territory consolidation. Four plans of prosperity of industrial plan, optimization of structure plan, ecological livability plan, and comprehensive rejuvenation plan, and quantitative analysis of multi-objective optimal decision were carried out using EW-TOPSIS analysis method. This research would achieve the goals of identifying and dividing the types of multi-objective pattern optimization of rural integrated territory consolidation from the perspective of limited multi-objective system selection and ranking, as well as to realize the purpose of constructing multi-objective pattern optimization system for rural integrated territory consolidation. This research took 184 administrative villages in Qingpu District of Shanghai City as examples and the following results were obtained. Firstly, EW-DEA model can effectively overcome the problem of high correlation between multiple administrative villages and improve the application accuracy of spatial suitability. EW-TOPSIS model can accurately divide the multi-objective pattern optimization scheme of rural integrated territory consolidation and refine the heterogeneity among the optimal schemes. Secondly, the mean value of social-ecosystem vulnerability of Qingpu District in the year of 2018 was shown as social subsystem vulnerability (0.605) > economic subsystem vulnerability (0.577)>ecosystem vulnerability (0.549). Vulnerability of social subsystems was an important reason for limiting vulnerability in the region. Thirdly, the vulnerability of social-ecosystem in administrative villages was increasing from central to north-south parts of the region, while the spatial agglomeration of the urgency of rural integrated territory consolidation was significant, with its threshold in 0.435, 0.785]. The urgency of agricultural industry was the maximum. Fourthly, according to the results of multi-objective decision-making evaluation of four multi-objective schemes based on vulnerability and urgency, pattern optimization types of rural integrated territory consolidation in Qingpu District can be divided into 16 types. The research results enrich the theory of rural geography and provide decision basis for rural regional governance, rural revitalization, and regional sustainable development.