Volume 5, Issue 2, June 2020, Page: 32-39
City as a System Supported by Artificial Intelligence
Anna Bazan-Krzywoszańska, Faculty of Civil Engineering Architecture and Environmental Engineering, University of Zielona Góra, Zielona Góra, Poland
Robert Lach, Spatial Data System Sp. z o.o., Gliwice, Poland
Maria Mrówczyńska, Faculty of Civil Engineering Architecture and Environmental Engineering, University of Zielona Góra, Zielona Góra, Poland
Received: Feb. 25, 2020;       Accepted: Apr. 7, 2020;       Published: Apr. 28, 2020
DOI: 10.11648/j.urp.20200502.11      View  390      Downloads  148
The primary objective of urban policy is to strengthen the capacity of cities to develop in such a way as to create an efficient, compact, sustainable and coherent structure, and thus to be strong and competitive. The potential associated with reducing urban flows, combined with effective management and use of natural resources, depends on sustainable development, but also on factors such as: compactness of form, morphology and urban structure of settlement units, among which cities become a space with great potential for saving natural resources, e.g. energy. The new approach towards thinking about city and planning its space entails consequences. The study of cities’ functionality is more and more involved with the process of integrating often dispersed, interdisciplinary databases. They provide information about the status and operation of a city system, based on qualitative and quantitative data. Earlier access to broad data sets was quite limited, but with the liberalization of access to satellite imagery data in Europe, and with more frequent operational functioning of several constellation of various image resolutions, practically each city on Earth can start to apply spatio-temporal monitoring of growth of urban organisms. It is already possible to monitor urban change with medium, high and very high resolution imagery at the entire Earth surface. These monitoring techniques procedures involve continuous observation and supervision. These types of activities allow to monitor the implementation of spatial policy processes, with regard to the set short- and long-term objectives. They can also help to initiate feedback processes related to possible adjustment of targets, thus – enriching decision makers with a broader, or better decision support, improving decision-making process with the use of big geospatial data. Space planning took on a new significance, since taking into consideration shaping the living conditions in the context of that process’s implications. Given the above, there is a need to develop tools to support conscious and effective implementation of spatial policy objectives. The complexity of processes occurring in space, as well as the willingness to understand and describe them, results in the development of new research techniques. The tools based on artificial intelligence are very helpful. The process of digital transformation of society and economy with the participation of algorithms is great developmental challenges of the XXI century. Public services in this system must be deeply rich with data. For this reason, in recent years, data has become one of the main or even the most important production factor. The acquisition, collection, analysis, processing and use of data and the continuous development of algorithms is becoming a fundamental competence of countries and cities.
City Space Management, GIS, SDI, 3D/4D City Models, CityGML, Big Data
To cite this article
Anna Bazan-Krzywoszańska, Robert Lach, Maria Mrówczyńska, City as a System Supported by Artificial Intelligence, Urban and Regional Planning. Special Issue: Management of the City - A Multi-Branch Task. Vol. 5, No. 2, 2020, pp. 32-39. doi: 10.11648/j.urp.20200502.11
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