城乡空置住房的识别、特征与成因——基于华北平原X县用电量等多源数据

对空置住房进行精准感知在国土空间规划中具有重要意义。基于华北X县2019年全县居民用电大数据构建了一种精准的空置识别和空置率计算模型。结果显示：该县出现过空置的住房占比高达33.81%,年空置率为21.64%;月空置率在一年中随月份小幅规律波动,波谷出现在2月和8月,波峰出现在5月和11月;村空置率具有空间自相关属性,县城为空置率高值集聚区;全年性空置为1931种空置节律模式中最主要的一种。将空置成因归纳为举家迁移和入城团聚等新流动模式促使全年空置和春节空置增多;扩展家庭内部住房过滤引发老旧住房空置;县城住房城镇化导致中心城区出现空置。应重视空置识别在国土空间规划中的基础作用,客观看待乡村住房空置现象,高度警惕县城的高空置率问题。

Identification,characters and causes of housing vacancy:A perspective from multi-source data

To figure out the number and pattern of the vacant houses is essential for spatial planning and city examination & evaluation. However, the limitation of fine data and methods has been a big barrier to accurately identifying and revealing the dynamic pattern of vacant houses. This paper developed a computational model to identify the vacant houses and to calculate the residential housing vacancy rate (HVR) based on the monthly electricity consumption data from all the households in X county in 2019. The results showed that: (1) The HVR of X county was 21.64%, and 33.81% of households had been vacant in 2019. Meanwhile, the rate of the households that were vacant in Chinese New Year's Eve and had been vacant all the year was 19.97% and 11.45%, respectively. (2) The monthly HVR fluctuated regularly, with February, August at the bottom, and May and November at the peak. However, the HVR of February when China's traditional Spring Festival fell did not decline as much as we expected. (3) The village HVR had spatial autocorrelation attribute and the urban built-up areas were the hotspots which deserve more attention. (4) Being vacant all the year is the top one model among 1931 vacant types. The paper held the view that the mechanism of the vacant in X county is (1) the change of the form of population migration and mobility; (2) housing filtering which occurred in rural families, and (3) over "housing urbanization" in the urban built-up areas. We argue that identifying and sensing vacant houses are fundamental works in spatial planning. Meanwhile, spatial planning should react properly to the rural vacant houses and transform the goal from the expansion of land to rising the wellbeing of people. We need to pay much attention to the vacant houses in the city because it is a signal of the mistake in planning. The vacant identifying computational model and the research result are helpful to advance housing vacancy study, which is significant for spatial planning.