Estimating Housing Vacancy Rate Using Nightlight and POI: A Case Study of Main Urban Area of Xi’an City, China

Abstract

Estimating the housing vacancy rate (HVR) has always been a hard-to-break point in the study of housing vacancy. This paper used nighttime light and POI (point of interest) data to estimate the HVR in the main urban area of Xi’an city based on extracting built-up areas. The built-up area was extracted using the threshold method, and the spatial resolution of the results was 130 m (same as Luojia-1). Meanwhile, after removing the non-residential areas from the images, the HVRs for the period 2018–2019 from four nighttime light images were calculated, and the HVR of the main urban area of Xi’an city was estimated using the average method and its spatial patterns were analyzed. The results show that: (1) Luojia-1 has great advantages in estimating urban HVRs. The HVRs calculated by Luojia-1 were characterized by a high resolution and a short calculation time. (2) After estimating the results of the four scenes’ remote sensing images, it was found that the results obtained using the average were closest to the actual vacancy situation, and the spatial distribution of the vacancy could be seen using the minimum values. (3) The overall housing occupancy in Xi’an city was good, and the HVRs were low, but the overall vacancy rate for the edge of the built-up area was high. The government should devote more attention to places with high HVRs.