基于乡村自组织演化规律的村庄分类振兴体系完善与类型识别

Refinement and Identification of Rural Revitalization Classification System Based on Self-organizing Development Patterns of Villages

摘要:

以乡村自组织演化理论为指导，形成对国家乡村振兴分类体系（包括城郊融合、特色保护、集聚提升村和搬迁撤并村）内生与外生分类差异的系统认识、四分类到五分类的分类完善以及兼顾村庄演化数量、质量与空间特征的识别方法改进，形成了一套顺应乡村演化规律的村庄分类管理方法。研究结果表明：乡村振兴分类体系中外生影响因素为主导划分的城郊融合、特色保护和外源型搬迁撤并村，宜采用流程图法识别；内生发展差异为主导划分的集聚提升村与内生型搬迁撤并村，需顺应乡村自组织演化规律识别。经自组织演化，村庄呈现“衰败-守成-繁荣”的正态有序分异规律，并具有数量、质量与空间特征，对应形成“搬迁-存续-集聚”的内生型分类体系，在村庄质量评价基础上采用改进的引力模型和县域-镇域尺度叠加模型识别村庄分类为同时考虑村庄自组织分异特征的可行方案。以L县为例，在对本文理论假说检验基础上，识别乡村振兴分类体系，最终识别结果符合乡村自组织演化的数量、质量与空间规律。

Abstract:

Guided by the theory of rural self-organization evolution, the endogenous and exogenous classification differences within the national rural revitalization classification system were systematically explored, which encompassed characteristic protection villages, suburban integrated villages, agglomeration villages, and relocation villages. The classification framework was refined from four to five categories and enhanced recognition methodologies that accounted for the quantity, quality, and spatial characteristics of village evolution. The results showed that for exogenously driven classifications, such as suburban integrated villages, characteristic preservation villages, and exogenous relocated villages, flowchart methods should be applied for identification. For classifications driven by endogenous development differences, such as agglomeration villages and endogenous relocated villages, the identification should follow the self-organizing evolution patterns of villages. Through self-organizing evolution, villages exhibited an ordered differentiation pattern of “decay-normal-prosperity” with distinct quantity, quality, and spatial characteristics. This led to the improvement of endogenous classifications of “relocation-existence-agglomeration”. Accordingly, employing an improved gravity model alongside a county-town scale overlay model for village evaluations offered a viable solution that aligned with the self-organizing evolutionary patterns of rural areas. Taking county L as an example, the theoretical hypotheses were tested, and the rural revitalization classification system was identified. The final classification results aligned with the quantity, quality, and spatial laws of rural self-organizing evolution.