Identification And Driving Force Analysis Of Housing Vacancy In Guangdong Province

Rapid urbanization has brought large-scale expansion and considerable economic benefits to the city.But at the same time,due to the rapid development in some areas,the problem of the disconnection of population resources and regional development has occurred,and a large number of houses have been vacant.A large number of vacant houses can easily lead to real estate bubbles and hinder the healthy and sustainable development of cities.Therefore,it is imperative to identify the vacant house and analyze its influencing factors.Guangdong Province is China's largest economic province,and its real estate market is of great significance for the steady,orderly and healthy development.In this study,Guangdong Province was used as the research area,and the NPP-VIIRS night light image data,land cover utilization data and population grid data were used to construct an index(HVI)for evaluating the vacancy of houses.This study takes districts and counties as the research unit,probes into the vacancy of houses in 123 administrative districts and counties in Guangdong Province in 2015 and analyzes their spatial distribution characteristics.The research results show that:(1)In 2015,the severity of the overall housing vacancy in each region of Guangdong Province was: Northern Guangdong> Western Guangdong> East Guangdong> Pearl River Delta.(2)Areas with high housing vacancy rates and severe housing vacancy can be divided into two categories: one is poor areas with poor economic development and severe population loss;the other is newly emerging urban areas and development zones.(3)The phenomenon of vacant houses in Guangdong has significant spatial autocorrelation characteristics.High-high clusters are clustered in Shenzhen and Guangzhou,and the vacancy index of neighboring districts and counties are all high,showing a positive correlation trend;low-low clusters show a continuous clustering state,mainly concentrated in the north of Guangdong province near Guangxi province,In the districts and counties of Hunan Province,the vacancy index of neighboringdistricts and counties is low,showing a positive correlation trend;the low-high category is clustered in Baiyun District,Guangzhou..In Nanyuan Yao Autonomous County of Qingyuan City,Huaiji County of Zhaoqing City,and Shenzhen are the four districts and counties of Bao'an District and Luohu District,the local spatial autocorrelation clusters are relatively significant.The cold spots are mainly concentrated in the interprovincial junctions in the mountainous areas of northern Guangdong and Xuwen County in Zhanjiang.Hot spots are mainly concentrated in Baiyun District,Yuexiu District,Tianhe District,Haizhu District,Liwan District of Guangzhou,and most of Shenzhen.(4)Use the GWR geographic weighted regression model to perform regression analysis on the four types of influencing factors of population migration,housing prices,medical allocation,and educational resources.Population mobility,medical allocation,and educational resources are all positively correlated with the housing vacancy index,and housing prices are negatively correlated with the housing vacancy index.The higher the house price,the easier it is to cause vacancy.At the end of the study,from the perspective of policy macro-control,financial institutions,population resources,etc.,the countermeasures to prevent the occurrence of housing vacancies and alleviate existing housing vacancies were discussed,helping to keep the housing vacancy rate within a reasonable range,and providing a healthy and high quality real estate market Provide a reference for sustainable development.