Urban Planning for Sustainable Development of Cities in the Geospatial (Big) Data ERA
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Urban and Rural Development".
Deadline for manuscript submissions: closed (31 January 2023) | Viewed by 43274
Special Issue Editors
Interests: urban planning; risk management; spatial decision support systems; spatial analysis; data analytics; GIS; geo crowdsourced data
Interests: GIS; data science; spatial decision support systems; spatial analysis
Interests: urban planning; spatial planning; risk management
Interests: data science in the management of ecological and digital transition process technical change; urban and territorial complexity diffusion of innovation and societal challenges
Special Issue Information
Dear Colleagues,
Urbanization poses great challenges for humans as it determines enormous impacts, such as environmental pollution, noise pollution, heat island effects, habitat fragmentation, loss of ecosystem services, and pressures on urban security, protected heritage sites and, generally, on the landscape changes.
Although cities occupy only three percent of the world’s surface, indeed, they are responsible for three quarters of global resource consumption and 76% of greenhouse gas emissions (Creutzig, 2015).
The 17 Sustainable Development Goals (SDGs) of the UN Agenda 2030 sanction unequivocally the link between environmental changes and social inequalities, innovating deeply the real concept of sustainable development as defined in its first definition in 1987.
In this context, the following questions need to be answered: How is it possible to manage efficiently a city with a view to sustainable development? How can be citizens become involved in reflecting on their future? What can be the main requirements for organizing smart cities? (Laurini, 2020).
A new science based on big data, urban models and network theory is emerging, providing a different and new perspective for planners and decision makers so that they can deepen the knowledge of current and future cities (Betty, 2021).
As a consequence, the responsibilities of urban planning must be investigated with reference to the challenges launched by the SDGs, starting from Goal 11, “Make cities and human settlements inclusive, safe, resilient and sustainable”, and the awareness of the role that geospatial big data can play in the achievement of this goal. In fact, the growing accessibility of such data from direct and indirect sources (i.e., remote sensing, sensors/Internet of Things, geo crowdsourced data) produces a set of multilevel and multi-sectorial information available to the urban planner. This favours the integration of different disciplines in the study of urban phenomena but, nevertheless, generates uncertainty due to the data complexity and redundancy. Therefore, there is a need to extract knowledge intelligently from these geospatial big data in order to understand, predict and manage how cities and urban areas work, change and grow.
In order to understand how urban and regional planning can benefit from geospatial big data with the main aim to reach the SDGS objectives, this Special Issue is dedicated to the exploration of:
- conceptual approaches and application experiences;
- theoretical and methodological development;
- techniques (i.e. machine-learning, data analytics, data visualization and data models for the representation of geospatial big data, Data-informed design and planning, urban modelling, E-participation;);
- integrated application of BIM and GIS;
- geographic knowledge bases;
- scientifically grounded indicators.
References:
- Batty M. Planning the 21st Century City – Four Snapshots for a New Science, International Review for Spatial Planning and Sustainable Development. 2021, 9, 1–9. doi:10.14246/irspsd.9.1_1.
- Batty, M.; Marshall, S. Thinking Organic, Acting Civic: The Paradox of Planning for Cities in Evolution. Urban Plan 2017, 166, 4–14. doi:10.1016/j.landurbplan.2016.06.002.
- Creutzig, F.; Baiocchi, G.; Bierkandt, R.; Pichler, P.P.; Seto, K.C. A global typology of urban energy use and potentials for an urbanization mitigation wedge. Natl. Acad. Sci. USA 2015, 112, 6283–6288.
- Kharrazi, A.; Qin, H.; Zhang, Y. Urban Big Data and Sustainable Development Goals: Challenges and Opportunities. Sustainability 2016, 8, 1293.
- Kitchin, R. The Real-Time City? Big Data and Smart Urbanism. GeoJournal 2014, 79, 1–14.
- Laurini, R.; Servigne, S.; Favetta, F. Sobre la inteligencia territorial y las bases del conocimiento geográfico. Cuadernos De Administración 2020, 33. doi:10.11144/Javeriana.cao33.atigk.
- Laurini, R. Geographicknowledge infrastructure: Applications for territorial intelligence and smart cities. Elsevier & ISTE: London, UK, 2017.
- Sassen, S. How the Powerless Can “Hack” Global Cities. The Architect’s Newspaper, August 10 2017. Available online: https://www.archpaper.com/2017/08/saskia-sassen-hack-global-cities/.
- Shaw, M.; Howell, S. Governing Safer Cities: Strategies for a Globalised World. A Framework to Guide Urban Policy-Makers and Practitioners; United Nations Office on Drugs and Crime-UNODC, 2016. Available online: https://www.unodc.org/documents/justice-and-prison-reform/SaferCities.pdf (accessed 14 December 2020).
- Tong H, Kang J. Relationship between urban development patterns and noise complaints in England. Plan B Urban Anal. City Sci. 2020. doi:10.1177/2399808320930247.
Prof. Dr. Michele Grimaldi
Prof. Dr. Monica Sebillo
Prof. Dr. Isidoro Fasolino
Prof. Dr. Carmelina Bevilacqua
Guest Editors
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Keywords
- urban planning
- spatial planning
- Sustainable Development Goals (SDGs)
- smart cities
- spatial decision support systems
- ICT
- Open Data
- Big Data
- IoT
- IoE
- BIM
- data analytics
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