生态与农村环境学报 ›› 2022, Vol. 38 ›› Issue (8): 1030-1040.doi: 10.19741/j.issn.1673-4831.2022.0243

• 区域环境与发展 • 上一篇    下一篇

甘肃省乡村人居环境质量测度与关键驱动因子分析

王小鹏, 何启明   

  1. 甘肃中医药大学理科教学部, 甘肃 定西 743000
  • 收稿日期:2022-03-23 出版日期:2022-08-25 发布日期:2022-08-23
  • 通讯作者: 何启明,E-mail:907655065@qq.com E-mail:907655065@qq.com
  • 作者简介:王小鹏(1984-),男,甘肃临洮人,讲师,研究方向为生态经济学。E-mail:wxpgzy@163.com
  • 基金资助:
    甘肃省高等学校创新能力提升项目(2019A-196);甘肃省技术创新引导计划-软科学专项(21CX1ZA277)

Evaluation of Rural Human Settlement Quality and its Key Driving Factors in Gansu Province

WANG Xiao-peng, HE Qi-ming   

  1. Department of Science Teaching, Gansu University of Chinese Medicine, Dingxi 743000, China
  • Received:2022-03-23 Online:2022-08-25 Published:2022-08-23

摘要: 乡村人居环境建设已成为乡村振兴战略实施的重要任务,其内在作用机理与关键驱动研究能够为乡村人居环境治理与建设的精准施策提供科学依据。采用乡村人居环境质量测度模型、典型相关分析、岭回归等方法进行甘肃省乡村人居环境质量测度、影响因素的作用机理分析,并识别人居环境质量的关键驱动。结果表明:(1)甘肃乡村人居环境质量综合指数均值为0.238,高于均值水平的县域占比达45.98%;综合指数、居住条件、产业经济发展以及生态环境与治理指数基本呈现由西北向东南降低态势;公共服务设施维度却表现为中部高,两端低的空间格局;基础设施维度中低水平与较低水平的评价单元相对零散分布且范围较广。(2)自然地理变量组中可灌溉耕地占比的典型载荷为-0.798,正向作用于基础设施、居住条件、产业经济(载荷系数均<0)等目标变量;区域经济发展组中所有解释指标均与典型变量呈正相关,解释指标正向促进着人居环境质量;社会文化控制变量组中小学文化程度以下的居民占比、少数民族聚落村占比2个解释变量的典型载荷分别为-0.976、-0.494,负面影响着乡村基础设施建设与产业经济发展(目标变量载荷系数>0)。(3)可灌溉耕地占比岭回归系数为0.143(P<0.05),成为乡村人居环境质量提升的关键驱动因子,山区与丘陵村落占比指标则成为关键约束(r=-0.134,P<0.05);区域经济发展组指标岭回归系数均为正值,有火车站、高速公路入口的乡镇占比(P<0.01)、非农行业劳动力占比(P<0.05)发挥正向驱动作用;社会文化环境中,小学文化以下居民占比系数为负值(P<0.01),居民文化程度低下成为乡村人居环境质量提升的关键障碍。

关键词: 乡村人居环境, 关键驱动, 典型相关分析, 岭回归, 甘肃省

Abstract: The construction of rural human settlements has become an important task in the implementation of rural revitalization strategy. The research on the internal mechanism and key driving forces can provide scientific basis for the governance and construction of rural human settlements. The measurement model of rural human settlements quality, canonical correlation analysis, and ridge regression model were used to realize the measurement of rural human settlements quality in Gansu Province. and the key driving factors were identified. The results show that:(1) The average value of rural human settlements quality in Gansu Province was 0.238, and the proportion of counties above the mean level was 45.98%. The living conditions, the industrial and economic development, and the governance of ecological environment in Gansu Province show a decreasing trend from northwest to southeast. The dimension of public service facilities is high in the middle and low at both ends. The low-level and lower-level evaluation units in infrastructure dimension are relatively scattered and widely distributed. (2) In the group of natural geographic variables, typical load of irrigated arable land was -0.798, and it has positive effect on the target variables such as infrastructure, living conditions and industrial economy. All the explanatory indicators in the regional economic development group showed positive correlation with the typical variables, and positively promoted the quality of human settlements. In the social control variable group, the canonical loadings of two explanatory variables, i.e. the proportion of residents with primary school education level-lower, and the proportion of minority villages, were -0.976 and -0.494, respectively, which negatively affected rural infrastructure construction and industrial economic development. (3) The ridge regression coefficient of the proportion of irrigated arable land was 0.143 (P<0.05), which is the key driving factor to improve the quality of rural human settlements, while the proportion of villages in mountainous and hill areas was -0.134 (P < 0.05) is the key constraint factor. The proportion of villages and towns near railway stations or expressway intersections (P<0.01) and labor force in non-agricultural industries (P<0.05) played positive driving role. In the social and cultural environment, the regression coefficient of the proportion index of residents below primary school education level was negative (P<0.01). The low education level of residents has become the key obstacle to the improvement of rural living environment quality.

Key words: rural human settlements, key driving factors, canonical correlation analysis, ridge regression model, Gansu Province

中图分类号: