City as Flux: Interrogating the Changing Nature of Urban Change

What do we mean by the changing nature of urban change? First of all, in the 20th and 21st centuries, cities have been changing in different and dramatic ways, whether through grassroots mobilizations, through technological leaps, or through profit-driven speculations. Second, our understanding of how cities change has also been evolving, in particularly through empirical work that challenges the broad-brush universalizations of conventional thinking. The authors of the six selected articles take us through an around-the-world tour of cities and regions that range from Mulhouse in France to Dakar in Senegal to Las Vegas in the United States to Bogota in Colombia and beyond. Each author carefully examines the nature of urban change and how planners, developers, and citizens are either dealing with that change or even shaping it. Together, what the articles suggest is that we need a more fine-grained understanding of the city as flux in order to obtain better theoretical insights as well as urban practices that can better manage and ultimately shape urban change to benefit citizens, especially those who are marginalized.

Fits-and-Starts: The Changing Nature of the Material City

How and why does the material city in the late 20th and early 21st century change? This article examines one type of prominent urban change, which is “fits-and-starts” and represents change that is concentrated in space and time and that nonetheless has longer term repercussions with high economic and environmental costs. Through a review of the literature and an illuminating case study in Las Vegas, this article reveals how human perception and decision-making via two interrelated phenomena, future speculation and manufactured obsolescence, drive such change. The case study in Las Vegas is particularly fascinating because as a city of apparent extremes, it not only reveals in clear relief phenomena that are present in the capitalist city but it also offers insights into basic patterns of decision-making that actually shape—or design—the contemporary city. The article concludes with more general insights into the nature of this type of urban change and implications for alternative types of urban practices.

HEDONIC MODELING OF HOUSING PURCHASE/SALE DENSITY WITH URBAN CHANGE FACTORS

Due to the industrialization in the cities, land needs have appeared in the increasing urban population. These needs have created houses with the accumulate of collective living spaces in the city. It is necessary to determine the supply-demand relationship and value of these real estates with economic importance for smart urban management systems and decision support systems in the market. The value of real estate varies according to the country in which it is located, but in general, it is affected by many factors such as spatial attributes, demographic factors, building factors, economic conditions. Depending on these factors, values and purchase-sale densities of housing also change.In this study, for prediction of housing purchase-sale density, hedonic modeling was realized with 15 features from urban change factors. Urban change factors that affect the purchase/sale of housing such as land use, demographic factors, population density and structural factors have been examined through Geographic Information System (GIS). The hedonic regression method was used for predicting the density of housing purchase/sale. As a result of the modeling, it was found as R2 = 0,85.

Urban space change and future prediction of Kangpur Nagar, Uttar Pradesh using EO data

Urban Land use changes, measurements, and the analysis of rate trends of growth would help in resources management and planning, etc. In this study, we analyze the urban change dynamics using a support vector machine model. This method derives the urban and rural land-use change and various components, such as population growth, built-up areas, and other utilities. Urban growth increases rapidly due to exponential growth of population, industrial growth, etc. The population growth also affects the availability of various purposes in its spatial distribution. In this present study, we carried out using multi-temporal satellite remote sensing data Landsat MSS (Multispectral scanner), ETM+ (Enhanced thematic mapper), OLI (Operational land imager) for the analysis of urban change dynamics between years 1980-1990, 1990-2003, 2012-2020 in Kanpur Nagar city in the state of Uttar Pradesh in India. In our study, we used SVM (Support Vector Machine) Model to analyze the urban change dynamics. A support vector machine classification technique was applied to generate the LULC maps using Landsat images of the years 1980, 1990, 2003, and 2020. Envi and ArcGIS software had used to identify the land cover changes and the applying urban simulation model (CA- Markov model) in Idrisi selva edition 17.0 software. The LULC maps of 2003 and 2020 were used to simulate the LULC projected map for 2050 using (Cellular automata) CA- Markov based simulation model.

Artistic research in processes of urban change

Can the figure of the city of knowledge be an inspiration to commissioning of artistic research in contexts of urban change? This article argues that it represents a way beyond the seemingly dead ends that have been forged by the temporary and creative city. This article presents some initial reflections on this subject and reflects upon how artistic research expands the roles ascribed to public art. The conceptual approach to understand the relations between knowledge and the development of cities applied in this article, draws on the idea that cities are learned developed by urban geographer Colin MacFarlane (MacFarlane, 2011). The article applies MacFarlane’s concept to artistic research in public space and argues that artistic research as public art can move divisions between what is extra-public and public, known and unknown. Drawing on public art projects that have relations to the urban development of Bjørvika, the article argues that artistic research of the city produces new ways to “learn the city” and conceive change.

Impact of AI-Based Tools and Urban Big Data Analytics on the Design and Planning of Cities

Wide access to large volumes of urban big data and artificial intelligence (AI)-based tools allow performing new analyses that were previously impossible due to the lack of data or their high aggregation. This paper aims to assess the possibilities of the use of urban big data analytics based on AI-related tools to support the design and planning of cities. To this end, the author introduces a conceptual framework to assess the influence of the emergence of these tools on the design and planning of the cities in the context of urban change. In this paper, the implications of the application of artificial-intelligence-based tools and geo-localised big data, both in solving specific research problems in the field of urban planning and design as well as on planning practice, are discussed. The paper is concluded with both cognitive conclusions and recommendations for planning practice. It is directed towards urban planners interested in the emerging urban big data analytics based on AI-related tools and towards urban theorists working on new methods of describing urban change.