Visualising urban gentrification and displacement in Greater London
Author
Abstract
Suggested Citation
DOI: 10.1177/0308518X19880211
Download full text from publisher
References listed on IDEAS
- Jonathan Reades & Jordan De Souza & Phil Hubbard, 2019. "Understanding urban gentrification through machine learning," Urban Studies, Urban Studies Journal Limited, vol. 56(5), pages 922-942, April.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Mikio Yoshida & Haruka Kato, 2023. "Housing Affordability Risk and Tourism Gentrification in Kyoto City," Sustainability, MDPI, vol. 16(1), pages 1-14, December.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Jonathan Reades, 2020. "Teaching on Jupyter: Using notebooks to accelerate learning and curriculum development," REGION, European Regional Science Association, vol. 7, pages 21-34.
- Zhou, You & Zhang, Lingzhu & Chiaradia, Alain J F, 2021. "An adaptation of reference class forecasting for the assessment of large-scale urban planning vision, a SEM-ANN approach to the case of Hong Kong Lantau tomorrow," Land Use Policy, Elsevier, vol. 109(C).
- Spandagos, Constantine & Tovar Reaños, Miguel & Lynch, Muireann Á, 2023. "Energy poverty prediction and effective targeting for just transitions with machine learning," Papers WP762, Economic and Social Research Institute (ESRI).
- Karen Chapple & Ate Poorthuis & Matthew Zook & Eva Phillips, 2022. "Monitoring streets through tweets: Using user-generated geographic information to predict gentrification and displacement," Environment and Planning B, , vol. 49(2), pages 704-721, February.
- devin michelle bunten & Benjamin Preis & Shifrah Aron-Dine, 2024. "Re-measuring gentrification," Urban Studies, Urban Studies Journal Limited, vol. 61(1), pages 20-39, January.
- Javad Eshtiyagh & Baotong Zhang & Yujing Sun & Linhui Wu & Zhao Wang, 2023. "A graph-based multimodal framework to predict gentrification," Papers 2312.15646, arXiv.org, revised Dec 2023.
- Pengyuan Liu & Yan Zhang & Filip Biljecki, 2024. "Explainable spatially explicit geospatial artificial intelligence in urban analytics," Environment and Planning B, , vol. 51(5), pages 1104-1123, June.
- Spandagos, Constantine & Tovar Reaños, Miguel Angel & Lynch, Muireann Á., 2023. "Energy poverty prediction and effective targeting for just transitions with machine learning," Energy Economics, Elsevier, vol. 128(C).
- Jan Voltaire Vergara & Maria Y Rodriguez & Jonathan Phillips & Ehren Dohler & Melissa L Villodas & Amy Blank Wilson & Kenneth Joseph, 2024. "An evaluation framework for predictive models of neighbourhood change with applications to predicting residential sales in Buffalo, NY," Urban Studies, Urban Studies Journal Limited, vol. 61(5), pages 838-858, April.
- Seung-Chul Noh & Jung-Ho Park, 2021. "Café and Restaurant under My Home: Predicting Urban Commercialization through Machine Learning," Sustainability, MDPI, vol. 13(10), pages 1-22, May.
More about this item
Keywords
Gentrification; displacement; socio-spatial inequality; London;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:envira:v:52:y:2020:i:5:p:819-824. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.