Bulletin of Surveying and Mapping ›› 2022, Vol. 0 ›› Issue (2): 100-105.doi: 10.13474/j.cnki.11-2246.2022.0051

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Quantitative study on geospacial factors affecting high-precision housing vacancy rate

ZHANG Dong1,2, LI Deping1,2, ZHOU Liang1,2, WANG Jiacheng1,2, MA Yu1,2, YI Min3   

  1. 1. College of Resources and Environmental Science, Hunan Normal University, Changsha 410081, China;
    2. Key Laboratory of Geospatial Big Data Mining and Application, Changsha 410081, China;
    3. Hunan Environmental Monitoring Center Station, Changsha 410004, China
  • Received:2021-02-22 Published:2022-03-11

Abstract: To reveal the dependence of housing vacancy rate on geospatial factors，this paper uses a 50 m×50 m grid as the basic unit, and calculates the grid-scale housing vacancy rate, natural factors and social factors through modeling and other methods, and divides the study area into different levels and analyzes the correlation.Further research on the influence mechanism of natural factors using the geo-detector method. The results show that: ① The housing vacancy rate in the study area is significantly correlated with the selected geospacial factors, and the impact of other natural factors is generally low, except for the proportion of vegetation on the house vacancy rate. ② Since the non-built-up areas are still in the stage of rapid development and have great development potential, the non-built-up areas are more dependent on social and natural factors than built-up areas. ③ The housing vacancy rate of each street is generally less affected by the slope than other natural factors.The interaction of each factor significantly enhances the explanatory power of the housing vacancy rate.This study provides a reference for the analysis of the influencing factors of the housing vacancy rate in small areas.

Key words: housing vacancy rate, grid, natural factors, the built-up area and non-built-up area, geographical detector

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