Omnipresent Sprawl? A Review of Urban Simulation Models with Respect to Urban Shrinkage

Decoupling Relationship between Industrial Land Expansion and Economic Development in China

Economic expansion has caused increasingly serious land resource problems, and the decoupling of urban industrial land expansion from economic development has become a big topic for intensive development. The current research has mainly concerned industrial land efficiency, a single, static indicator, compared to a decoupling model, which takes into account two variables and gives a full expression of the spatio-temporal dynamic characteristics. However, little attention has been paid to the relationship between industrial land expansion and economic development in China from the perspective of decoupling. Based on a combination of Tapio‘s decoupling model and spatial analysis methods, this paper investigates the decoupling relationship between industrial land expansion and economic development in Chinese cities from 2010 to 2019. On that basis, we divided the study area into three policy zones and made differentiated policy recommendations. In addition, based on the decoupling model, we obtained the decoupling indices of the cities and grouped the cities into eight decoupling types. After the spatial autocorrelation analysis, we further verified the spillover effect of decoupling with the results of urban spatial differentiation. This paper draws the following conclusions: (1) Urban industrial land expansion and economic development exhibit marked and increasingly significant spatial heterogeneity and agglomeration. (2) Industry and economy are in weak decoupling in most cities, but there are a growing number of cities in negative decoupling. (3) Decoupled cities are shifting from the southeast coast to the middle and lower reaches of the Yellow River and Yangtze River, while negatively decoupled cities keep spreading from northeast and south China to their periphery, with clear signs of re-coupling. (4) It is necessary to develop urban industrial land supply and supervision policies according to local actuality and to implement differentiated control of industrial land for cities and industrial sectors with different decoupling types. To some extent, this paper reveals the evolution dynamics, performances, and strategies of industrial land, providing a decision basis for industrial land management policies and industrial planning in China and other countries at similar stages.

Combining Remote-Sensing-Derived Data and Historical Maps for Long-Term Back-Casting of Urban Extents

Spatially explicit, fine-grained datasets describing historical urban extents are rarely available prior to the era of operational remote sensing. However, such data are necessary to better understand long-term urbanization and land development processes and for the assessment of coupled nature-human systems (e.g., the dynamics of the wildland-urban interface). Herein, we propose a framework that jointly uses remote-sensing-derived human settlement data (i.e., the Global Human Settlement Layer, GHSL) and scanned, georeferenced historical maps to automatically generate historical urban extents for the early 20th century. By applying unsupervised color space segmentation to the historical maps, spatially constrained to the urban extents derived from the GHSL, our approach generates historical settlement extents for seamless integration with the multitemporal GHSL. We apply our method to study areas in countries across four continents, and evaluate our approach against historical building density estimates from the Historical Settlement Data Compilation for the US (HISDAC-US), and against urban area estimates from the History Database of the Global Environment (HYDE). Our results achieve Area-under-the-Curve values > 0.9 when comparing to HISDAC-US and are largely in agreement with model-based urban areas from the HYDE database, demonstrating that the integration of remote-sensing-derived observations and historical cartographic data sources opens up new, promising avenues for assessing urbanization and long-term land cover change in countries where historical maps are available.

Simulating Urban Shrinkage in Detroit via Agent-Based Modeling

While the world’s total urban population continues to grow, not all cities are witnessing such growth—some are actually shrinking. This shrinkage has caused several problems to emerge, including population loss, economic depression, vacant properties and the contraction of housing markets. Such issues challenge efforts to make cities sustainable. While there is a growing body of work on studying shrinking cities, few explore such a phenomenon from the bottom-up using dynamic computational models. To fill this gap, this paper presents a spatially explicit agent-based model stylized on the Detroit Tri-County area, an area witnessing shrinkage. Specifically, the model demonstrates how the buying and selling of houses can lead to urban shrinkage through a bottom-up approach. The results of the model indicate that, along with the lower level housing transactions being captured, the aggregated level market conditions relating to urban shrinkage are also denoted (i.e., the contraction of housing markets). As such, the paper demonstrates the potential of simulation for exploring urban shrinkage and potentially offers a means to test policies to achieve urban sustainability.

A century of decoupling size and structure of urban spaces in the United States

Most cities in the United States of America are thought to have followed similar development trajectories to evolve into their present form. However, data on spatial development of cities are limited prior to 1970. Here we leverage a compilation of high-resolution spatial land use and building data to examine the evolving size and form (shape and structure) of US metropolitan areas since the early twentieth century. Our analysis of building patterns over 100 years reveals strong regularities in the development of the size and density of cities and their surroundings, regardless of timing or location of development. At the same time, we find that trajectories regarding shape and structure are harder to codify and more complex. We conclude that these discrepant developments of urban size- and form-related characteristics are driven, in part, by the long-term decoupling of these two sets of attributes over time.

Assessing the Impacts of Urban Land Use Changes on Regional Ecosystem Services According to Urban Green Space Policies Via the Patch-Based Cellular Automata Model

As urbanization affects the quality of regional ecosystems, which are needed to ensure the well-being of residents, urban land management plans should consider ecosystem services. While several studies have assessed urbanization impacts on regional ecosystem services in developing urban areas, they used limited approaches that only considered options pertaining to urban green space management. A modeling approach that simulates changes in urban land use and associated ecosystem services can better support urban land management decisions by comparing the effects of different scenarios. We simulated urban land use change impacts on regional ecosystem services using a patch-based cellular automata model and assessment tools for seven ecosystem service indicators in different urban management scenarios regarding green space policies in Ansan, South Korea. The simulation results showed spatial patterns of land use changes and impacts on associated ecosystem services although their impacts varied according to different service types. While urbanization affected regional ecosystem services to a lesser extent than land use changes, urban green space policies contributed to increasing ecosystem services. Our approach provides useful information for improved policy decisions with regard to coupling urban management with ecosystem services, as urban green spaces are necessary for residents' well-being.

Dynamic Models for Exploring the Resilience in Territorial Scenarios

The present paper focuses on the role covered by dynamic models as support for the decision-making process in the evaluation of policies and actions for increasing the resilience of cities and territories. In recent decades, urban resilience has been recognized as a dynamic and multidimensional phenomenon that characterizes urban and metropolitan area dynamics. Therefore, it may be considered a fundamental aspect of urban and territorial planning. The employment of quantitative methods, such as dynamic models, is useful for the prediction of the dynamic behavior of territories and of their resilience. The present work discusses the system dynamics model and the Lotka–Volterra cooperative systems and shows how these models can aid technicians in resilience assessment and also decision makers in the definition of policies and actions, especially if integrated in wide evaluation frameworks for urban resilience achievements. This paper aims to provide an epistemological perspective of the application of dynamic models in resilience assessment, underlying the possible contribution to this issue through the analysis of a real case study and methodological framework. The main objective of this work is to lay the basis for future compared applications of these two models to the same case study.

Spatiotemporal Differences in Determinants of City Shrinkage Based on Semiparametric Geographically Weighted Regression

City shrinkage, as an ongoing worldwide phenomenon, is an issue for urban planning and regional development. City shrinkage is remarkable in Japan, with over 85% of municipalities experiencing population loss from 2005 to 2015. As Japan’s society ages and with its low fertility rate, city shrinkage has had a tremendous negative effect on economic development and urban planning. Understanding the spatial dependence and spatial heterogeneity of city shrinkage and its determinants is essential for ensuring the sustainable development of a city or region. In this study, a semiparametric geographically weighted regression (SGWR) model was adopted to explore the spatiotemporal differences in determinants of city shrinkage. The results reveal that the SGWR model incorporating the global and local variables is more interpretive compared to ordinary least squares and geographically weighted regression models in exploring the correlates of city shrinkage. We found the spatial dependence and heterogeneity of shrinking cities resulted from demographic, economy, and social factors, and revealed low fertility, the ageing population, and enterprise change ratio influenced city shrinkage in different regions at different times in Japan, whereas foreign population ratio, industry structure, and social welfare had global impacts. The findings provide useful information for understanding city shrinkage at global and local scales.

Italy without Urban ‘Sprinkling’. A Uchronia for a Country that Needs a Retrofit of Its Urban and Landscape Planning

The research presented in the work is linked to important production of data over 10 years of activity that allowed us to trace the configuration of Italian urban settlements in the 1950s. Starting from this information, the paper puts forward a uchronian reconstruction of the physiognomy of the national territory asking if—instead of the weak urban development policies implemented for over half a century—a more purposeful method of planning and designing settlements had been chosen in the Sixties to favor their aggregation and protect the country’s huge landscape heritage. From the model used, important indications emerge for control and management of retrofit (de-sprinkling) policies of which the need has been felt in recent years, as suggested by repeated messages from European bodies, the scientific community, associations and some politicians. The uchronic scenario is constructed starting from the settlement configuration of the 1950s, developing a model of maximum aggregation for the urbanized parts that were intervened in between this period and 2000, simulating a geography that maintains the quantities of soil transformed over the last 50 years. It emerges from the processing of the data that the Italian territory would have retained its low settlement density areas almost intact at the same level as in the 50s, that is to say 73% of the entire peninsular territory. It would also have preserved a large part of its free peninsular and insular coastline at about 60–70%, against the present day 45%.

Urban Growth and Demographic Dynamics in Southern Europe: Toward a New Statistical Approach to Regional Science

Metropolitan growth in Europe has resulted in drastic changes of urban forms, socio-spatial structures and land-use patterns due to sequential processes of urbanization, suburbanization and re-urbanization. To assess latent shifts from mono-centric models towards more disarticulated and decentralized settlement configurations, the present study evaluates spatio-temporal patterns of growth between the 1920s and the 2010s in three Mediterranean cities with different structure and functions (Barcelona: compact and moderately polycentric; Rome: dispersed, medium-density; Athens: mono-centric, hyper-compact). To identify and characterize long-term urban transformations, an original approach was illustrated in this study, based on a multivariate analysis of 13 indicators resulting from descriptive statistics and linear regression modeling the relationship between population density and distance from inner cities. The empirical results of this study indicate that Barcelona, Rome and Athens have experienced different urbanization cycles, characterized by a (more or less) concentrated distribution of population along urban gradients. Despite similarities in demographic dynamics and planning practices, these processes have determined (i) a mostly centralized growth in Barcelona, (ii) a relatively dispersed and discontinuous spatial structure in Rome, and (iii) a steep decline of population density with the distance from downtown Athens. Compact urban expansion, population decline and urban de-concentration were finally assessed using the analytical approach proposed in this study.

Simulating Demography and Housing Demand in an Urban Region under Scenarios of Growth and Shrinkage

After the fall of the Berlin wall in 1989, demographic decline and urban shrinkage brought massive changes in the housing stock in East German cities. Urban planners and policy makers face complex problems caused by the resulting vacancies and demolitions and the handling of urban brownfields in the inner city. At the same time, cities are under ongoing pressure of suburbanisation. Because existing models focus mainly on demographic and urban growth and their impact on housing stocks, we present a simulation model that is able to compute both growth and shrinkage processes. We uncover nonlinear dynamics and feedbacks between demography, housing preference, and supply of housing space. The simulation results show that, despite population decline, the increasing number of single households leads to a growing total housing demand in the central parts of the study area. Beyond this area, residential vacancies in multistorey housing segments will remain regardless of population growth. At the same time, the simulations show that, despite population shrinkage and an overall oversupply of flats, there is a negative net demand for flats in affordable prefabricated housing estates as the percentage of low-income households increases. These findings will help planners modify or adapt their visions of the residential function in shrinking cities and to adjust current programmes of renewal and restructuring.