秦巴-武陵山区重庆段乡镇域多维贫困测度及类型划分

深度揭示秦巴、武陵等连片特困山区的贫困特征对于当前脱贫攻坚效应分析、返贫预警机制构建以及2020年后乡村振兴工作开展具有重要的科学意义。该研究以秦巴-武陵山区重庆段境内392个乡镇为评价单元,通过构建多维贫困评价指标体系,运用熵权法、热点分析等方法,综合测度多维贫困指数,并进行贫困地理识别。结果显示：1）乡镇贫困程度多以比较、高度贫困为主,各维度贫困空间分布差异明显,多维贫困空间呈现"北深南中浅"分布且高值区集聚明显,北部秦巴山区贫困程度最深;2）基于各维度下贫困测度值识别评价单元致贫因素,划分出弱综合约束型、单因素约束型、双因素约束型、三因素约束型和强综合约束型,秦巴山区更多表现为三因素和强综合约束型为主,武陵山区更多表现为单因素和双因素约束型为主,而连接秦巴山区和武陵山区之间的万州区则以弱综合约束型为主,表明区域贫困是综合性因素导致的结果。该研究能为乡镇尺度开展脱贫效应评价及乡村振兴基础工作提供前提科学基础。

Multidimensional poverty measurement and type classification of township areas in Chongqing Section from Qinling-Bashan to Wuling Mountain Areas

Spatial poverty level can be an indicator to identify the special poverty in the contiguous mountainous areas of China. The in-depth identification can greatly contribute to constructing the early warning for the returning of poverty in the revitalization of rural areas, even to the integration of urban and rural areas after 2020. Among them, a large number of the population are living in absolute poverty in the Qinling-Bashan and Wuling Mountainous Areas, Chongqing, South China. Since the poverty alleviation strategy has been launched for the high level of poverty, it is very necessary to better consolidate the attack in the later stage during this time. Therefore, this study aims to clarify the spatial characteristics of multidimensional poverty in this region in the early and middle stages of poverty alleviation. An explanation was also given to delineate the causes and distribution of poverty in the township in the concentrated contiguous special poverty areas. The indicators were selected to characterize the physical and geographical features, social security, economic development, and location transportation in 2015. An evaluation index system of multidimensional poverty was constructed to implement the poverty geographical identification using the entropy rights method and hotspot analysis. The results showed that: 1) The poverty level of the township was mainly relatively high and above. There was a significantly different spatial distribution of poverty in various dimensions. The multidimensional poverty space presented a distribution of "north deep, south, middle and shallow", the outstanding concentration of high-value areas, and the highest poverty level in the northern study areas. It infers that the fragile natural environment was attributed to the fewer economic resources in the study areas. The undeveloped traffic system was coupled with the location far away from the metropolis, Chongqing City. The less circulation of local elements and external resources obstructed the local economic and social development. The degree of poverty was also deepened, as most local residents (labor and talents) migrated to Chongqing City. 2) The poverty degrees were measured under each dimension to identify the poverty factors of the evaluation unit. Five large types and 16 small types of weak comprehensive constraint type, one-factor constraint type, two-factor constraint type, three-factor constraint type, and strong comprehensive constraint type were divided, accounting for 27.29%, 33.42%, 21.43%, 16.33%, 1.53% of the Qinling-Bashan Mountains, indicating the three-factor and strong comprehensive constraints. By contrast, the Wuling Mountains were more manifested as the two-factor and one-dimensional constraints. The weak comprehensive constraints were dominated in the Wanzhou District that connected the Qinling-Bashan Mountains and the Wuling Mountains, indicating the regional poverty from the comprehensive factors. Therefore, the different types of poverty-causing factors can greatly contribute to the decision-making on infrastructure investment and the introduction of leading enterprises in each region. The finding can provide a prerequisite scientific basis to evaluate poverty alleviation and rural revitalization at the township scale.