Study on Average Housing Prices in the Inland Capital Cities of China by Night-time Light Remote Sensing and Official Statistics Data

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成果类型：

期刊论文

作者：

Li, Chang*;Zhu, Heli;Ye, Xinyue;Jiang, Chang;Dong, Jing;...

通讯作者：

Li, Chang

作者机构：

[Zhu, Heli; Wang, Di; Dong, Jing; Wu, Yijin; Li, Chang; Jiang, Chang] Cent China Normal Univ, Key Lab Geog Proc Analysing & Modelling, 152 Luoyu Rd, Wuhan 430079, Peoples R China.

[Zhu, Heli; Wang, Di; Dong, Jing; Wu, Yijin; Li, Chang; Jiang, Chang] Cent China Normal Univ, Coll Urban & Environm Sci, 152 Luoyu Rd, Wuhan 430079, Peoples R China.

[Ye, Xinyue] New Jersey Inst Technol, Dept Informat, Newark, NJ USA.

通讯机构：

[Li, Chang] C

Cent China Normal Univ, Key Lab Geog Proc Analysing & Modelling, 152 Luoyu Rd, Wuhan 430079, Peoples R China.

Cent China Normal Univ, Coll Urban & Environm Sci, 152 Luoyu Rd, Wuhan 430079, Peoples R China.

语种：

英文

期刊：

Scientific Reports

ISSN：

2045-2322

年：

2020

卷：

期：

DOI：

10.1038/s41598-020-64506-2

基金类别：

National Natural Science Foundation of China (NSFC)National Natural Science Foundation of China (NSFC) [41771493, 41101407]; USA National Science FoundationNational Science Foundation (NSF) [1739491, 1937908]; self-determined research funds of CCNU from the basic research and operation of MOE [CCNU19TS002]

机构署名：

本校为第一且通讯机构

院系归属：

城市与环境科学学院

摘要：

In this paper, the annually average Defense Meteorological Satellite Program-Operational Linescan System (DMSP/OLS) night-time light data is first proposed as a surrogate indicator to mine and forecast the average housing prices in the inland capital cities of China. First, based on the time-series analysis of individual cities, five regression models with gross error elimination are established between average night-time light intensity (ANLI) and average commercial residential housing price (ACRHP) adjusted by annual inflation rate or not from 2002 to 2013. Next, an optimal model is selected...

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Study on Average Housing Prices in the Inland Capital Cities of China by Night-time Light Remote Sensing and Official Statistics Data

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