Urban land price assessment based on GIS and deep learning

IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss.2019.8900516 ◽

2019 ◽

Author(s):

Hongga Li ◽

Xiaoxia Huang ◽

Xia Li

Keyword(s):

Deep Learning ◽

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Theoretical analysis and determining methods for modification coefficients between floor-area rate and urban land price

2011 International Conference on Multimedia Technology ◽

10.1109/icmt.2011.6003205 ◽

2011 ◽

Author(s):

Jinting Zhang ◽

Xuejia Sun ◽

Fei Fang

Keyword(s):

Theoretical Analysis ◽

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Redevelopment and the Urban Land Price Gradient

Journal of Urban Economics ◽

10.1006/juec.1994.1012 ◽

1994 ◽

Vol 35 (2) ◽

pp. 182-200 ◽

Author(s):

Stuart S. Rosenthal ◽

Robert W. Helsley

Keyword(s):

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Prediction of the land price based on deep learning and residual kriging

Journal of the Korean Data and Information Science Society ◽

10.7465/jkdi.2021.32.3.475 ◽

2021 ◽

Vol 32 (3) ◽

pp. 475-485

Author(s):

Jinho Choi ◽

Yongku Kim

Keyword(s):

Deep Learning ◽

Residual Kriging

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Study on function of urban land price on land spatial expansion based on the gravity model

2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery ◽

10.1109/fskd.2010.5569553 ◽

2010 ◽

Author(s):

Wang Li ◽

Feng Zhongjiang ◽

Liang Yanqing ◽

Ge Jingfeng ◽

Liu Yunliang ◽

...

Keyword(s):

Gravity Model ◽

Spatial Expansion ◽

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The benchmark land price system and urban land use efficiency in China

Chinese Geographical Science ◽

10.1007/s11769-001-0045-x ◽

2001 ◽

Vol 11 (4) ◽

pp. 306-314 ◽

Author(s):

Cheng-ri Ding

Keyword(s):

Land Use ◽

Price System ◽

Urban Land Use ◽

Land Use Efficiency ◽

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Urban Land: Price Indices, Performance, and Leading Indicators

The Journal of Real Estate Finance and Economics ◽

10.1007/s11146-019-09696-x ◽

2019 ◽

Vol 60 (3) ◽

pp. 396-419 ◽

Author(s):

Mark Fitzgerald ◽

David J. Hansen ◽

Will McIntosh ◽

Barrett A. Slade

Keyword(s):

Leading Indicators ◽

Price Indices ◽

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Study on the Spatial Differentiation and Temporal Evolution of Urban Land Price: Evidence from Beijing

Proceedings of the 19th International Symposium on Advancement of Construction Management and Real Estate ◽

10.1007/978-3-662-46994-1_57 ◽

2015 ◽

pp. 693-706

Author(s):

Lin Gan ◽

Chang-chun Feng

Keyword(s):

Temporal Evolution ◽

Spatial Differentiation ◽

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Study on spatial autocorrelation of urban land price distribution in Changzhou city of Jiangsu Province

Chinese Geographical Science ◽

10.1007/s11769-006-0011-8 ◽

2006 ◽

Vol 16 (2) ◽

pp. 160-164 ◽

Author(s):

Zhong-gang Liu ◽

Man-chun Li ◽

Yan Sun ◽

Wen-bo Ma

Keyword(s):

Spatial Autocorrelation ◽

Jiangsu Province ◽

Price Distribution

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Urban Land Price: The Extraordinary Case of Honolulu, Hawaii

Urban Studies ◽

10.1080/00420988920080311 ◽

1989 ◽

Vol 26 (3) ◽

pp. 301-314 ◽

Author(s):

Louis A. Rose ◽

Sumner J. La Croix

Keyword(s):

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Deep learning method for evaluating photovoltaic potential of urban land-use: A case study of Wuhan, China

Applied Energy ◽

10.1016/j.apenergy.2020.116329 ◽

2020 ◽

pp. 116329

Author(s):

Chen Zhang ◽

Zhixin Li ◽

Haihua Jiang ◽

Yongqiang Luo ◽

Shen Xu

Keyword(s):

Land Use ◽

Deep Learning ◽

Urban Land Use ◽

Learning Method

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