Li, Yijing;
Zhao, Qunshan;
Zhong, Chen;
(2022)
GIS and urban data science.
Annals of GIS
10.1080/19475683.2022.2070969.
(In press).
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Abstract
With the emergence of new forms of geospatial/urban big data and advanced spatial analytics and machine learning methods, new patterns and phenomena can be explored and discovered in our cities and societies. In this special issue, we presented an overview of nine studies to understand how to use urban data science and GIS in healthcare services, hospitality and safety, transportation and mobility, economy, urban planning, higher education, and natural disasters, spreading across developed countries in North America and Europe, as well as Global South areas in Asia and the Middle East. The embrace of diverse geo-computational methods in this special issue brings forward an outlook to future GIS and Urban Data Science towards more advanced computational capability, global vision and urban-focused research.
| Type: | Article |
|---|---|
| Title: | GIS and urban data science |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1080/19475683.2022.2070969 |
| Publisher version: | https://doi.org/10.1080/19475683.2022.2070969 |
| Language: | English |
| Additional information: | © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group, on behalf of Nanjing Normal University. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/). |
| Keywords: | GIS, urban data science, urban analytics, informatics |
| UCL classification: | UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Centre for Advanced Spatial Analysis UCL > Provost and Vice Provost Offices > UCL BEAMS UCL |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10148603 |
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