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中国县域全域土地综合整治适宜性评价及分类治理

Suitability evaluation and classified governance of county-level comprehensive land consolidation in China

  • 摘要: 全域土地综合整治是推动国土空间治理现代化和高质量发展的重要抓手。全国范围内资源禀赋与制度基础差异显著,现有全域土地综合整治模式存在较强的地域依赖性。为破解全域土地综合整治全国推广中面临的区域异质性难题,识别不同县域的整治适宜性与推进路径,本研究基于整治迫切性与可行性的双重内涵,构建以整治需求与整治能力为核心维度的“需求—能力协同”适宜性评价框架。在此框架下,本研究识别出了中国2843个县域的整治适宜性类型。研究结果表明:1)县域整治需求总体呈“北高南低”格局,整治能力呈“东南高、西北低”格局,二者仅呈弱正相关,表明县域整治需求与能力的同步性有限;2)识别出4类整治适宜性核心类型,包括优先推进型(A)、经济支撑受限型(C1)、社会响应受限型(C2)、双约束攻坚型(F),合计 2132 个县;3)双束攻坚型636个县(占 22.37%)呈现“需求紧迫但经济、社会能力双低”特征,连片分布于胡焕庸线西北侧(占该侧 33.57%),是被传统单维评价所遮蔽的政策瓶颈类型;4)针对四类政策核心对象,本研究提出“分类适配、精准施策”的差异化提升路径,为全国全域土地综合整治的因地制宜推进提供县域尺度依据。

     

    Abstract: Comprehensive land consolidation (CLC) is an important instrument for modernizing territorial spatial governance and supporting high-quality development in China. Yet pronounced county-level differences in land-use problems and implementation conditions make existing models strongly place-dependent. Single-score suitability assessments may assign similar values to counties with different demand-capacity combinations, limiting their usefulness for determining priorities and support measures. This study therefore developed a Demand-Capacity Synergy framework, defining suitability as the matching state between the urgency of consolidation demand and the capacity to undertake consolidation tasks rather than as a binary judgment of whether consolidation should be implemented. A total of 2,843 county-level units were evaluated using multi-source land-cover, ecological, demographic, socioeconomic, and point-of-interest data, mainly for 2023. The Consolidation Demand Index (N) incorporated ecological environmental quality, cultivated land fragmentation, per capita construction land, and production-living-ecological spatial conflict. Capacity was decomposed into the Economic Support Capacity Index (E), representing fiscal and economic conditions, and the Social Response Capacity Index (S), representing demographic change, education, public facilities, and grassroots administrative coverage. Entropy weighting was applied within each dimension, and E and S were aggregated by geometric mean to obtain the Consolidation Capacity Index (Cap), preserving sensitivity to weakness in either component. Correlation analysis and principal component analysis were used to inspect the data structure. Types were identified using the 25th percentile of N and the medians of E and S as relative thresholds, with threshold sensitivity tests. The results showed that N and Cap followed different spatial patterns. N was generally higher in northern China and lower in southern China, with high values mainly in the Northeast Plain, eastern Inner Mongolia, the North China Plain, and some arid agro-pastoral areas in northwestern China. Cap was higher in southeastern China and lower in northwestern China, with high values concentrated in eastern coastal areas and major urban agglomerations. N and Cap were only weakly positively correlated (Pearson r = 0.1780; Spearman rho = 0.2576; p < 0.001), indicating limited synchronization between consolidation urgency and implementation capacity. Classifications based on alternative N thresholds were approximately 95.01% consistent with the baseline classification. Six suitability types were identified. Four core policy types covered 2,132 counties: Priority Consolidation (A; 841 counties, 29.58%), Economically Constrained (C1; 301, 10.59%), Socially Constrained (C2; 354, 12.45%), and Dual-Constraint Critical (F; 636, 22.37%). Type F combined relatively high demand with low economic and social capacity and accounted for 33.57% of counties northwest of the Hu Line. These counties could be difficult to distinguish from low-demand counties through a single composite score. The non-core high-capacity and low-capacity types, B and D, contained 152 and 559 counties, respectively. The identified combinations imply different implementation priorities. Type A can be prioritized for integrated and systematic tasks. Type C1 requires stronger economic support and project scales suited to local capacity, whereas Type C2 requires greater attention to public participation, benefit coordination, public services, and grassroots organization. Type F requires external fiscal, financial, technical, and organizational support, and phased implementation. Types B and D indicate a lower relative priority for large-scale comprehensive projects rather than an absence of consolidation needs. The framework thus shifts suitability assessment from a single ranking toward matching consolidation priorities, task scales, implementation timing, and support measures, providing county-level evidence for locally adapted implementation of comprehensive land consolidation in China.

     

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