Mapping fine-scale urban housing prices by fusing remotely sensed imagery and social media data

Author:

Yao Yao1ORCID,Zhang Jinbao2ORCID,Hong Ye2ORCID,Liang Haolin2ORCID,He Jialv2ORCID

Affiliation:

1. School of Information Engineering, China University of Geosciences, Wuhan, China

2. School of Geography and Planning, Sun Yat-sen University; Guangzhou China

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Natural Science Foundation of Hubei Province

Publisher

Wiley

Subject

General Earth and Planetary Sciences

Reference62 articles.

1. Abadi , M. Agarwal , A. Barham , P. Brevdo , E. Chen , Z. Citro , C. Zheng , X. 2016 https://arxiv.org/abs/1603.04467

2. Interpolation of air quality measures in hedonic house price models: Spatial aspects;Anselin;Spatial Economic Analysis,2006

3. Analysis of spatial autocorrelation in house prices;Basu;Journal of Real Estate Finance and Economics,1998

4. Analysis of a random forests model;Biau;Journal of Machine Learning Research,2012

5. Incorporating spatial variation in housing attribute prices: A comparison of geographically weighted regression and the spatial expansion method;Bitter;Journal of Geographical Systems,2007

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