## 5 Discussion
### Highlights and Limitations  
Real estate plays an important role in social and economical development, especially in the industry of the national economy. The stable development of the real estate market can directly influence the life quality of residents. The study of housing vacancy has important practical implications. The highlights of this paper are reflected in the following two aspects based on the above background. Firstly, the method improves the accuracy of the calculation results. The used spatial resolution of Luojia-1 (130 m) used herein is much higher than the NPP-VIIRS (500 m) and the DMSP/OLS (1000 m), which has a high reference value for studying small-scale HVR. Secondly, the highlight of the calculation method. We compared the average results of the four phases of the images with the average results after calculating the HVR of the four-phased images separately, combined with the survey data. The result indicated that the average method was closer to the real housing vacancy conditions and provides new ideas and new methods for the calculation and research of the HVR.  
This paper proposed a new method to quantitatively evaluate the current situation of housing vacancies in the area using remote sensing data and the POI of night lights. Prior to the use of this methodology to evaluate the HVRs, various methods should be used to verify the accuracy of the data and to compare the data obtained in various ways to determine the applicability and accuracy of the method. Coupled with the complexity of the housing vacancy problem, the research results of this paper also have a certain degree of limitations, The main limitations are as follows:  
1. Although this paper used the highest resolution Luojia-1 nighttime light data (spatial resolution: 130 m) that can be obtained at present, such a spatial resolution was still lower and insufficient for conducting urban internal research. The accuracy is slightly unsatisfactory.
2. Nighttime light data are susceptible to the urban area light intensity, fire, exhaust gas combustion, and many other background noises. At present, researchers have proposed noise reduction, calibration, desaturation, and other processing methods, but there is no universally accepted method. Although the Luojia-1 data used in this paper greatly reduced the saturation spillover effect, the measurement error will still have an impact on the accuracy of the housing vacancy estimate.
3. In many cities, especially in megacities, the urban built-up area and the night lighting area do not necessarily coincide strictly, the separation of work and housing is widespread, and there is no strict proportional relationship between the strength of the light and the housing vacancy. The higher the degree of separation between work and housing, the greater the impact on the estimation of the HVRs.  
At present, the situation of vacant housing in cities and towns is grim, and in the future, we will explore housing vacancies in more depth and analyze the spatial and temporal changes of vacant housing by obtaining multiperiod vacancy data. A comprehensive influencing factor index system related to vacancy may be constructed and its relationship with the social environment, built environment, and other factors will be explored further. Future work could provide a better understanding of the types of vacancy problems for researchers that are unique to different cities and regions in China.