Spatial Identification of Housing Vacancy in China

The housing vacancy rate(HVR)is an important index in assessing the healthiness of residential real estate market.In China,it is hardly to take advantage of the basic data of real estate information due to the opaque of those data.In this paper,the HVR is estimated to two scales.At the grid level,urban area ratio was calculated by nighttime images after eliminating outliers of nighttime images and night light intensity of non-residential pixels in mixed pixels by a proposed modified optimal threshold method,and built-up areas in each pixel were extracted from the land-cover data.Then,the HVR is calculated by comparing the light intensity of specific grid with the light intensity of full occupancy rate regions.At the administrative scale,the GCI(‘ghost city’index)is constructed by calculating the ratio of the total light radiation intensity of a city to the total construction land area of the city.The overall spatial differentiation pattern of the vacant houses in the national prefecture level administrative regions is analyzed.The following conclusions were drawn:vacant housing is rare in certain eastern coastal cities and regions in China with relatively fast economic development.Cities based on exhausted resources,some mountainous cities,and cities with relatively backward economic development more typically showed high levels of housing vacancy.The GCI of prefecture-level administrative units gradually declined from north to south,whereas the east-west distribution showed a parabolic shape.As city level decreased,the GCI registered a gradual upward trend.China’s urban housing vacancy can be divided into five categories:industry or resources driven,government planned,epitaxy expansionary,environmental constraint and speculative activate by combining the spatial distribution of housing vacancy with the factors of natural environment,social economic development level,and population density into consideration.

Housing vacancy identification in shrinking cities based on multi-source data:A case study of Fushun city in Northeast China

Urban shrinkage has attracted the attention of many geographers and urban planners in recent years.However,there are fewer studies on vacant housing in shrinking cities.Therefore,this study combines multi-source remote sensing images and urban building data to assess the spatiotemporal variation patterns of housing vacancy in a typical shrinking city in China.The following points were obtained:(1)We developed an evaluation model to identify vacant residential buildings in shrinking cities by removing the contribution of nighttime lights from roads and non-residential buildings;(2)The residential building vacancy rate in Fushun city significantly increased from 2013 to 2020,resulting in a significant high-value clustering effect.The impact of urban shrinkage on vacant residential buildings was higher than that on vacant non-residential buildings;(3)The World Pop population data demonstrated consistent spatial distribution and trend of population change in Fushun with the residential building vacancy rate results,suggesting good reliability of the constructed evaluation model in this study.Identifying housing vacancies can help the local government to raise awareness of the housing vacancy problem in shrinking cities and to propose reasonable renewal strategies.

Influencing Factors of Housing Sales Vacancy in the Guangzhou Metropolitan Area,China

In this paper,nine indicators selected from three perspectives(convenience,environmental and location characteristics)and three regression models(OLS,SLM and SEM)are used to explore the influencing factors of housing sales vacancy in the Guangzhou Metropolitan Area,China.The results show that subway accessibility,peripheral aversion municipal facilities and distance from the CBD(Central Business District)are consistent with theoretical expectations.Subway accessibility is negatively correlated with the housing sales vacancy rates,while peripheral aversion municipal facilities and distance from the CBD are positively correlated with housing vacancy rates.

Spatial Pattern of Housing Sales Vacancy in Guangzhou’s Urban District, China

Housing vacancy can reflect the destocking degree of the real estate market.Based on the data of 57 opened residential quarters(46,622 units)from 2015 to 2018,this paper constructs a calculation formula of the sales vacancy rate and then analyzes the spatial pattern in Guangzhou’s urban district.The results show that there is obvious differentiation in the spatial pattern of housing sales vacancy in Guangzhou’s urban district,showing a higher spatial pattern in the old area and urban district and a lower spatial pattern in the core area.Subdistricts with high vacancy rates are mainly located in the east of the old area,the south and east of the urban district and near Baiyun Mountain in the north.