基于吉林一号夜光影像的高精度住房空置率测度与 影响因子研究
Research on High-precision Housing Vacancy Rate Measurement and Influencing Factors Based on Jilin-01 Nightlight Data
黄 浩
华南理工大学建筑学院
赵慧敏
清华大学建筑学院 博士研究生
摘要: 住房空置率是衡量城市兴衰与住房市场健康的重要指标，其影响着居民的生活水平和生活质量。现有研究多利用夜光数据或政府统计数据等进行测度，存在尺度较大、精度较低等问题，居住小区尺度的住房空置测度研究较为缺乏。基于此，采用分辨率为0.92—1.10 m的吉林一号高分夜光数据、居住小区矢量边界等多源数据，从居住小区尺度对住房空置率进行高精度估算，并采用市场新房、二手房待售待租数据和高精度人口数据进行二次精度检验。采用空间自相关等方法进一步分析住房空置率的分布差异和空间聚类，通过顾及样本自相关特征的随机森林模型深入解析住房空置率的潜在空间影响因子，并以长春市主城区1 869个住宅小区为样本进行研究，研究表明：长春市主城区高空置率居住小区的空间聚集性显著，中心城区西部及东北部为热点区域；长春市主城区高空置率居住小区主要为铁路旁住区、老旧住区、新建楼盘3大类型；影响长春市住房空置率前三的因子分别是房价、公共空间类设施密度、商业服务类设施密度。以期为空置住房的规划应对与精细化治理提供决策依据。
Abstract: Vacant housing correlates deeply with the well-being of residents. It is an important indicator to assess the health of the real estate market. Existing research mostly uses night light data or government statistics to estimate the housing vacancy rate (HVR), but still with the problems
of low accuracy and high cost of data acquisition. There is a lack of research on housing vacancy estimation on the residential block level. In this regard, 1 869 residential blocks in the main urban area of Changchun are taken as examples for empirical research. Firstly, multi-source data with high resolution such as Jilin-01 high-resolution night light data and land cover information are utilized to extract light intensity values and estimate HVR at the block level. A plausibility check is conducted using real estate and population statistics, which reveals high accuracy. Then, spatial autocorrelation is adopted to analyze the spatial distribution differences and clustering of HVR. Finally, the random forest model integrated with spatial autocorrelation features is utilized to measure the contribution rate of potential factors of HVR. The results show that: 1) residential areas with high HVR in Changchun have significant spatial aggregation, and the hotspot areas are located in the west and northeast; 2) residential areas with high HVR can be divided into three types: railway-side ones, old ones, and new-built ones; 3) housing price, density of public space facilities, and density of commercial service facilities contribute most to the HVR in Changchun. This study contributes to making planning strategies and refining the governance of vacant housing.
关键词：住房空置率；吉林一号夜间灯光数据；居住小区；空间自相关；影响因子
Keyword: housing vacancy rate; Jilin-01 night light data; residential areas; spatial autocorrelation; influencing factors
中图分类号：TU984
文献标识码: A
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