Next Article in Journal
Towards Self-Service GIS—Combining the Best of the Semantic Web and Web GIS
Next Article in Special Issue
A Refined Lines/Regions and Lines/Lines Topological Relations Model Based on Whole-Whole Objects Intersection Components
Previous Article in Journal
A Virtual Reality Simulation Method for Crowd Evacuation in a Multiexit Indoor Fire Environment
Previous Article in Special Issue
A Study of User Activity Patterns and the Effect of Venue Types on City Dynamics Using Location-Based Social Network Data
Article

Opportunities and Challenges of Geospatial Analysis for Promoting Urban Livability in the Era of Big Data and Machine Learning

1
IDA Lab, University of Salzburg, 5020 Salzburg, Austria
2
Boston Area Research Initiative, School of Public Policy and Urban Affairs, Northeastern University, Boston, MA 02115, USA
3
Department of Geoinformatics—Z_GIS, University of Salzburg, 5020 Salzburg, Austria
4
Centre for the Future of Places, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden
5
Fort Lauderdale Research and Education Center, University of Florida, Davie, FL 33314, USA
6
Center for Geographic Analysis, Harvard University, Cambridge, MA 02138, USA
7
GIS Center, Florida International University, Miami, FL 33199, USA
8
Department of Urban & Regional Planning, San José State University, San Jose, CA 95192-0185, USA
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(12), 752; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9120752
Received: 30 October 2020 / Revised: 3 December 2020 / Accepted: 10 December 2020 / Published: 15 December 2020
(This article belongs to the Special Issue Geodata Science and Spatial Analysis in Urban Studies)
Urban systems involve a multitude of closely intertwined components, which are more measurable than before due to new sensors, data collection, and spatio-temporal analysis methods. Turning these data into knowledge to facilitate planning efforts in addressing current challenges of urban complex systems requires advanced interdisciplinary analysis methods, such as urban informatics or urban data science. Yet, by applying a purely data-driven approach, it is too easy to get lost in the ‘forest’ of data, and to miss the ‘trees’ of successful, livable cities that are the ultimate aim of urban planning. This paper assesses how geospatial data, and urban analysis, using a mixed methods approach, can help to better understand urban dynamics and human behavior, and how it can assist planning efforts to improve livability. Based on reviewing state-of-the-art research the paper goes one step further and also addresses the potential as well as limitations of new data sources in urban analytics to get a better overview of the whole ‘forest’ of these new data sources and analysis methods. The main discussion revolves around the reliability of using big data from social media platforms or sensors, and how information can be extracted from massive amounts of data through novel analysis methods, such as machine learning, for better-informed decision making aiming at urban livability improvement. View Full-Text
Keywords: spatial data science; livability; urban planning; big data; urban assessment; spatio-temporal analysis spatial data science; livability; urban planning; big data; urban assessment; spatio-temporal analysis
Show Figures

Figure 1

MDPI and ACS Style

Kovacs-Györi, A.; Ristea, A.; Havas, C.; Mehaffy, M.; Hochmair, H.H.; Resch, B.; Juhasz, L.; Lehner, A.; Ramasubramanian, L.; Blaschke, T. Opportunities and Challenges of Geospatial Analysis for Promoting Urban Livability in the Era of Big Data and Machine Learning. ISPRS Int. J. Geo-Inf. 2020, 9, 752. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9120752

AMA Style

Kovacs-Györi A, Ristea A, Havas C, Mehaffy M, Hochmair HH, Resch B, Juhasz L, Lehner A, Ramasubramanian L, Blaschke T. Opportunities and Challenges of Geospatial Analysis for Promoting Urban Livability in the Era of Big Data and Machine Learning. ISPRS International Journal of Geo-Information. 2020; 9(12):752. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9120752

Chicago/Turabian Style

Kovacs-Györi, Anna, Alina Ristea, Clemens Havas, Michael Mehaffy, Hartwig H. Hochmair, Bernd Resch, Levente Juhasz, Arthur Lehner, Laxmi Ramasubramanian, and Thomas Blaschke. 2020. "Opportunities and Challenges of Geospatial Analysis for Promoting Urban Livability in the Era of Big Data and Machine Learning" ISPRS International Journal of Geo-Information 9, no. 12: 752. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9120752

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop