Estimating Land Development Time Lags in China Using DMSP/OLS Nighttime Light Image

Remote Sensing

Ge Qu¹  Wen Wang¹  Li Zhang¹ 

[1] Center for Spatial Information, School of Environment and Natural Resources,Renmin University of China, Beijing 100872, China;

关键词: DMSP/OLS nighttime light image;    real estate market;    time lags;    land development;   

DOI  :  10.3390/rs70100882

来源: DOAJ

【 摘 要 】

The Chinese real estate industry has experienced rapid growth since China’s economic reform. Along with a booming industry, a third of purchased lands were left undeveloped in the last decade. Knowledge of real estate development time lags between land being purchased and property being occupied can enable policymakers to produce more effective policies and regulations to guide the real estate industry and sustain economic development and social welfare. This paper presents an innovative method to estimate provincial land development time lags in China using DMSP/OLS NTL imagery and real estate statistical data. The results showed that real estate development time lag was common in China during 2000–2010. More than half of the study sites showed development time lags of three years or longer. An Increment of Developed Pixels (IDP) index was established to outline yearly land development completions in China between 2000 and 2010. A Comprehensive Real Estate Price Index (CREPI) was created to explore the causes of the time lags. A strong and positive correlation was found between the real estate development time lags and CREPI values (with r = 0.619, n = 31, p < 0.0005). The results indicated that the land development time lag during the study period was positively correlated to the activity of the local real estate market, the price trend of land and housing properties, and the local economic situation. The results also proved that with the support of statistical data the DMSP/OLS NTL image could offer an economically efficient and reliable solution to estimate the time lag of real estate development.

【 授权许可】

Unknown