| 长沙市基础教育资源空间可达性和供需匹配度评价 |
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| 引用本文： | 马宇,李德平,周亮,张栋,王嘉丞.长沙市基础教育资源空间可达性和供需匹配度评价[J].热带地理,2021,41(5):1060-1072. |
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| 作者姓名： | 马宇 李德平 周亮 张栋 王嘉丞 |
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| 作者单位： | 湖南师范大学，地理科学学院，长沙 410081;湖南师范大学，地理空间大数据挖掘与应用湖南省重点实验室，长沙 410081 |
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| 基金项目： | 湖南省教育厅科学研究重点项目(18A014) |
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| 摘 要： | 以长沙市为例，基于POI、夜间灯光、土地利用、路网、DEM等影响人口空间分布的变量因子，构建随机森林模型将2018年乡镇人口分解到100 m格网中，然后利用成本加权距离法分析基础教育资源的空间可达性，最后利用改进潜能模型计算基础教育资源的供需匹配度。结果表明：1）在村级（社区）尺度，人口空间化结果与统计数据的线性拟合R2达到0.73，优于WorldPop数据集；长沙市人口分布整体呈现“一主两副多点”的空间格局，能细致地刻画分布特征。2）长沙市基础教育资源空间可达性整体较好，分别有97.72%、96.20%和89.46%的居民能在30 min内到达最近的小学、初中和高中；城乡差异明显，设施密集、交通发达区域的基础教育资源可达性较好；可达性较差的村（社区）集中分布在辖区面积大、多林地山区的县（市）。3）长沙市主城区和浏阳、宁乡城区基础教育资源多处于供需均衡状态，但仍有部分区域的资源配置有待加强；镇区基础教育资源供需匹配度处于偏高状态，乡村地区基础教育资源在其服务半径内多处于匹配度高值状态，强度以设施点为中心向外逐渐降低，需要加强校车配置和接收寄宿学生的能力，以扩大生源范围。
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| 关 键 词： | 人口空间化 随机森林模型 POI数据 基础教育资源 可达性 匹配度 潜能模型 长沙市 |
| 收稿时间： | 2020-10-13 |
The Spatial Accessibility and Matching Degree between the Supply and Demand of Basic Educational Resources in Changsha City |
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| Yu Ma,Deping Li,Liang Zhou,Dong Zhang,Jiacheng Wang.The Spatial Accessibility and Matching Degree between the Supply and Demand of Basic Educational Resources in Changsha City[J].Tropical Geography,2021,41(5):1060-1072. |
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| Authors: | Yu Ma Deping Li Liang Zhou Dong Zhang Jiacheng Wang |
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| Institution: | College of Geographic Science, Hunan Normal University, Changsha 410081, China;Hunan Key Laboratory of Geospatial Big Data Mining and Application, Hunan Normal University, Changsha 410081, China |
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| Abstract: | With the advancement of urbanization, reasonable allocation of public service resources is crucial for the sustainable development of cities and other regions. Education is the cornerstone of national revitalization and social progress; thus, the spatial distribution of educational resources should be in line with the overall trend of population distribution. This study attempts to evaluate the status of basic educational resource allocation on a finer scale based on population spatialization and POI (Point of Interest) data. We studied Changsha City in Hunan Province, where the 2018 census data were distributed into 100-m grids using POI, nighttime light, land use, road network, DEM (Digital Elevation Model), and other data as control variables based on the Random Forest model. We analyzed the spatial accessibility of basic education resources using cost weighted raster analysis and calculated the matching degree between the supply and demand of the resources using the improved potential model. The findings indicate that: 1) At the village (community) scale, the linear correlation coefficient (R2) of the population density between the result of population spatialization and the census data reached 0.73, which is better than WorldPop (World Population Dataset). Overall, the population distribution was displayed as a spatial distribution pattern of "one main-two sub-multi points", which could reflect the spatial characteristics of the population distribution in detail. 2) The spatial accessibility of the basic educational resources in Changsha was generally good: 97.72%, 96.20%, and 89.46% of the residents can reach the nearest primary schools, middle schools, and high schools, respectively, within 30 minutes. The difference in accessibility between the urban and rural areas was significant: the accessibility of the basic educational resources in facilities-intensive and traffic-developed areas was good and the villages (communities) with bad accessibility to basic education resources were concentrated in large counties with a large population of woodland and mountainous areas, especially in the surrounding mountainous areas of Liuyang County. 3) Generally, the basic educational resources in the urban areas of Changsha City and Liuyang and Ningxiang counties were in a balanced state of supply and demand; however, there were some areas where improvements were required. The matching degree between the supply and demand of basic education resources in towns was slightly higher, whereas in rural areas, it was mostly in a high-value state within the service radius and the intensity gradually decreased with facilities as the center. Therefore, it is necessary to strengthen the allocation of school buses and the ability of schools to receive boarding students to expand the scope of student sources. Previous studies mostly used large-scale census data, which ignored the spatial differences within each administrative unit. While some studies used small-scale census data such as those on residential quarters and buildings, however, these data are often difficult to obtain. This study provides research ideas for the precise assessment of the status of urban public service resource allocation and support for the diagnosis and improvement of the shortcomings of the basic educational resource allocation in Changsha City. |
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| Keywords: | population spatialization Random Forest model POI data basic educational resource accessibility matching degree potential model Changsha City |
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