High precision space estimation of housing vacancy rate using high resolution image and Luojia-1

doi:10.13474/j.cnki.11-2246.2021.0008

Abstract

Abstract: To estimate the house vacancy rate, this paper proposes a method that divides the study area into three parts: high-rise area in the built-up area, low-rise area in the built-up area and non-built-up area. In this method,the accuracy of the estimated results is tested by “night field record”, and the local indicators of spatial association (LISA) is used to analyze its spatial aggregation.It can be found from the results that, ① The overall house vacancy rates in the study area are 17.88%.The root-mean-square error is 0.14. The house vacancy rates in non-built-up areas are higher than that in built-up areas, while the full occupancy rates are lower than that in built-up areas. ② The house vacancy rates in the study area present two spatial agglomeration characteristics: H-H agglomeration and L-L agglomeration. It provides a reference for further information about the vacancy rates of houses in rural areas and the spatial distribution regularity of house vacancy.

Key words: house vacancy rate, the built-up area and non-built-up area, Luojia-1 night light date, LISA

CLC Number:

P237

ZHANG Dong, LI Deping, ZHOU Liang, HUANG Jinxia, GAO Hang, WANG Jiacheng, MA Yu. High precision space estimation of housing vacancy rate using high resolution image and Luojia-1[J]. Bulletin of Surveying and Mapping, 2021, 0(1): 41-46,52.

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