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Delimiting the urban growth boundary (UGB) is important for limiting urban sprawl and improving urban sustainability. However, the future UGB delimitation for the entire China is still lacking. Here, we delimited China's UGBs before 2100 under localized shared socioeconomic pathways and 11 urban expansion modes (i.e., spontaneous growth, organic growth, and nine modes integrating both) and evaluated the urban shrinkage pressure and the effects on other land use/cover types and ecosystem services. The results revealed that China's urban land demand was projected to increase first and then decrease under five scenarios before 2100. The extent of UGBs was projected to be 121,199–142,982 km2, 34.14–58.25% higher than the urban area in 2020. As a result of urban population decline, China's urban land demand in 2100 was projected to be 20.83–53.41% lower than the extent of UGBs, implying that China, especially the three provinces of Heilongjiang, Jilin, and Liaoning, will face remarkable urban shrinkage pressure. Future urban expansion in China will mainly occupy cropland, and lead to a simultaneous decline in habitat quality, food production and carbon sequestration. Spontaneous growth will cause greater losses of ecosystem services than organic growth at the national scale, while in some provinces, such a difference will be reversed. To address the urban shrinkage pressure, China needs to control urban area and optimize urban spatial patterns based on UGBs. In addition, the place‐based optimal urban expansion mode is also required to reduce the negative impacts of future urban expansion on ecosystem services and promote sustainable development. Plain Language Summary: Urban expansion has caused a series of ecological and social problems. Therefore, setting urban growth boundaries around cities to limit urban sprawl within such boundaries and reduce its negative impacts has been a critical way for sustainable development. This study delimited China's urban growth boundaries before 2100 under five scenarios of localized shared socioeconomic pathways and 11 urban expansion modes (i.e., spontaneous growth, organic growth, and nine modes integrating both) and evaluated the potential effects of future urban expansion on urban shrinkage pressure, other land use/cover types and ecosystem services. The results showed that China's urban land demand was projected to show an increasing trend followed by a decrease under five scenarios from 2021 to 2100, leading to a nationwide urban shrinkage pressure, and the effects of future urban expansion on ecosystem services varied with urban expansion modes. This study suggests that China, especially the three provinces of Heilongjiang, Jilin, and Liaoning, should take measures to optimize urban spatial patterns and address urban shrinkage pressure, and each province needs to take the place‐based optimal urban expansion mode based on the environmental, social, and economic characteristics to improve urban sustainability. Key Points: The extent of China's urban growth boundary was projected to be 34.14–58.25% higher than the urban area in 2020China's urban land demand in 2100 would be lower than the extent of UGBs, implying China will face remarkable urban shrinkage pressureChina should take effective measures to address the urban shrinkage pressure and reduce the negative impacts from urban expansion [ABSTRACT FROM AUTHOR]

Urban evolution, a primary question of Urban Geography, has always been limited by the lack of continuous spatial-temporal data. Recently, this limitation has been overcome by the processing in Geographic Information System of sequential snapshots acquired by Remote Sensing. Therefore, we use the Landsat archive to reveal the (dis)similarities of the urbanization process (rhythm and modes) experienced by the municipalities of Braga and Guimarães between 1984 and 2016. The results show that, more than temporal (When?) or quantitatively (How much?), the urbanization process in the two municipalities presents spatial disparities (Where? and How?). The Landscape Expansion Index (LEI) highlights that more than 50% of urban growth occurs in contiguity with the pre-existing fabric. Infilling constitutes the second most important mode in Braga, but not in Guimarães, where this position is occupied by outlying growth. Consequently, in Braga the urban perimeter captures better the urbanization process than in Guimarães. Thus, LEI can make an important contribution to the understanding of diffuse urbanization, a territorial model constantly called banal, and that - due to such an assertion - has been ignored in relation to other problem-areas. [ABSTRACT FROM AUTHOR]

Context: Urbanization is the most important form of landscape change and is increasingly affecting biodiversity and ecosystem functions. Understanding how landscape patterns change in space and time is central to the evaluation of the environmental impacts of urbanization. Objectives: This research explores the spatiotemporal patterns of land use change in the Swiss urban agglomerations of Bern, Lausanne and Zurich at two characteristic spatial extents, and compares them to prominent hypotheses of urbanization patterns. Methods: For each urban agglomeration, four temporal snapshots from 1980 to 2016 have been derived from the land use inventory of the Swiss Federal Statistical Office. Fractal analysis of the area–radius relationship of urban land is used to separate each agglomeration into two characteristic spatial extents according to the distance of the city center, namely the inner and outer zones. The landscape metrics and growth modes are then computed at such extents. Results: The time series of landscape metrics and growth modes reveal fairly different patterns when computed in the inner and outer zones respectively. Bern and Lausanne exhibit mostly traits of coalescence stages at the inner zone while displaying many characteristics of diffusion in the outer zone. In contrast, the trends of observed in the inner and outer zones of Zurich are both reminiscent of a coalescence stages. Conclusions: Fractal analysis can be a useful approach to detect characteristic extents of urban agglomerations at which distinct spatiotemporal patterns might be observed. Current models of urbanization patterns should incorporate the notion of characteristic extents more explicitly. [ABSTRACT FROM AUTHOR]

Characterization of the Spatial Urban Growth of the city of Lubumbashi (Haut-Katanga, D.R. Congo) between 1989 and 2014. A quantification of the spatio-temporal dynamics of urbanization is crucial to apprehend urban morphology and its ecological effects, in order to support sustainable urban planning. This study aimed at understanding the spatial urban growth of Lubumbashi city based on the analysis of six SPOT satellites images. With the exception of the 1996-2002 period, Lubumbashi city underwent a high average annual growth rate exceeding that observed for other cities in sub-Saharan Africa. Between 1989 and 2014, the built-up percentage increased from 6 % to 20 %. Our results suggest that the urbanization of Lubumbashi city followed a complex diffusion-coalescence model. The main reason of this perturbation is the combination of the rapid demographic growth with an inappropriate urban growth management.

The newly implemented national policy “To build a world-class agglomeration of cities with the capital as the core” made the Jing-Jin-Ji Urban Agglomeration attract attention from both the scientific community and society. Here we quantified and compared the magnitude, rates, forms, and dynamics of urban expansion for 13 cities across the Jing-Jin-Ji Urban Agglomeration, and examined the relationship of urban patch structure and hierarchical structure of urban growth over the past four decades. We found that the rates and composition of urban expansion forms (i.e., infilling, edge-expansion and leapfrogging) varied considerably across cities and over time, due to national and regional policies, physical features and the urban administrative hierarchy. The overall annual urban expansion rate for the 13 cities was 5.5 ± 2.0% (mean ± standard deviation) between 1978 and 2015. Leapfrogging was the dominant urban expansion form in early period, edge-expansion took the leading role since 1990, and the contribution of infilling was generally less than 40%. Our results revealed that although three major cities (i.e., Tianjin, Beijing and Shijiazhuang) of the Jing-Jin-Ji Urban Agglomeration contributed 36.6% of the urban land area increase of this region, larger cities might not be better positioned for urban expansion. The urban expansion rates of cities were inversely related to city size in general from 1978 to 2015 with exception only from 2005 to 2010. Patch analysis showed that relationship between patch number and patch size derived previously at the national level can be applied to the Jing-Jin-Ji Urban Agglomeration despite the discrepancies in temporal scale and urban administrative hierarchy. This invariant self-organization of urban land patches during the urbanization process might provide insightful information guiding the design, planning, and management of sustainable cities in the capital urban agglomeration of China. [ABSTRACT FROM AUTHOR]

Urban growth has been recognized to involve three main modes: infilling, edge expansion, and outlying growth. However, the relationship between three urban growth modes and their driving factors remains little investigated. To better address these problems and understand the general spatiotemporal dynamics of the urban landscape, the authors quantitatively analyzed the patterns of three urban growth modes in four metropolitan cities in China (i.e., Beijing, Shanghai, Tianjin, and Guangzhou) during a 20-year period through an integrated approach of remote sensing and landscape expansion index (LEI). The relationship between urban growth modes and three driving factors (i.e., city center, existing urban areas, and main roads) in each city was also investigated using buffering analysis and the area-weighted mean distance index (AWMDI). Results showed that these four cities had a significant increase of urban areas and developed different urban growth patterns. Despite different natural environments and social economy, the urban growth modes of four cities exhibit a common feature that edge expansion nearly dominated the growth mode during the study periods, indicating the urban growth across these cities tends to be the phase of coalescence. Besides, from the variations in the growth density (GD)--distance curves, each growth mode of the four cities generally showed exponential attenuation with the distance to existing urban areas and roads in each period, except for the outlying growth, which showed a stochastic and scattered pattern away from the city center and existing urban areas. Results from the AWMDI in each city also suggested that existing urban areas have a generally stronger effect on infilling growth than roads, whereas roads were a stronger attractor of outlying growth than existing urban areas. The findings of this study show an improved understanding of urban growth modes and help to provide an effective way for urban planning management. [ABSTRACT FROM AUTHOR]

The processes of urban growth vary in space and time. There is a lack of model transferability, which means that models estimated for a particular study area and period are not necessarily applicable for other periods and areas. This problem is often addressed through scenario analysis, where scenarios reflect different plausible model realisations based typically on expert consultation. This study proposes a novel framework for data-driven scenario development which, consists of three components - (i) multi-area, multi-period calibration, (ii) growth mode clustering, and (iii) cross-application. The framework finds clusters of parameters, referred to as growth modes: within the clusters, parameters represent similar spatial development trajectories; between the clusters, parameters represent substantially different spatial development trajectories. The framework is tested with a stochastic dynamic urban growth model across European functional urban areas over multiple time periods, estimated using a Bayesian method on an open global urban settlement dataset covering the period 1975–2014. The results confirm a lack of transferability, with reduced confidence in the model over the validation period, compared to the calibration period. Over the calibration period the probability that parameters estimated specifically for an area outperforms those for other areas is 96%. However, over an independent validation period, this probability drops to 72%. Four growth modes are identified along a gradient from compact to dispersed spatial developments. For most training areas, spatial development in the later period is better characterized by one of the four modes than their own historical parameters. The results provide strong support for using identified parameter clusters as a tool for data-driven and quantitative scenario development, to reflect part of the uncertainty of future spatial development trajectories. A promising further application is to use the growth modes to characterize past spatial development patterns. A trend of increasingly dispersed patterns could be identified over the studied functional urban areas which calls for more detailed explorations. [Display omitted] • Extrapolate urban spatial development processes from multi-area, multiperiod historical data. • Establish data-driven urban spatial development scenarios. • Confirm low transferability from the calibration period to the projection period. • Manage uncertainty as most areas are better represented by different established scenarios than their historic trajectory. • Detect a dispersed spatial development trend across studied urban areas in Europe. [ABSTRACT FROM AUTHOR]

In this article, we make the case for the existence of global macro-patterns of urban change and urban growth, in particular, which may be recognized across metropolitan systems located around the globe. In order to achieve these goals, we examine the pace and types of built-up land expansion inside metropolitan regions of the 43 major megacities in the globe between 1985 and 2015. We show that the advancement of the urbanization-metropolisation process involves the sequential co-occurrence of three urban growth modes (outlying, edge expansion, and infilling). It refutes earlier claims that the three expansion modes occur simultaneously (concurrent co-occurrence) and supports the diffusion-coalescence hypothesis of urbanization. Additionally, we suggest a straightforward model based on the urban scaling laws that can be used to predict the growth of new built-up land in metropolitan areas based on the current urban mass (agglomeration effect), the availability of undeveloped land (hinterland effect), and fundamental structural elements of wider settlement systems (national-level urbanization rate and fertility). We find that the agglomeration effect is crucial for urban infilling while the hinterland effect has a greater impact on edge expansion and outlying growth. We also predict that built-up land inside the administrative regions of the studied megacities will expand by 15% (11,000 sq. km.) between 2015 and 2030. Our research thereby advances knowledge of the physical development of urban systems. [Display omitted] • Examines macro-patterns of urban expansion of 43 worlds' largest megacities. • Evinces sequential co-occurrence of growth modes along urbanisation-metropolisation. • Urban expansion within metropolitan areas modelled by: • Urban mass, undeveloped land, and national-level urbanization and fertility rates. • Calls for integrating social and environmental aspects to advance urban theory. [ABSTRACT FROM AUTHOR]

Urbanization is the most dramatic form of land use change that has profoundly influenced environmental and socioeconomic conditions around the world. To assess these impacts and promote urban sustainability, a better understanding of urbanization patterns is needed. Recent studies have suggested several spatiotemporal patterns of urbanization, but their generality is yet to be adequately tested with long-term data. Thus, the main goal of our study was two-fold: (1) to examine the spatiotemporal patterns of urbanization of 16 world cities over a period of 200 years (1800-2000); and (2) to test four prominent hypotheses of urbanization patterns. Using a set of landscape metrics, we quantified temporal changes in the urban landscape pattern of the 16 cities and examined the four hypotheses individually. Our results show that these cities exhibit several common urbanization patterns: the urban landscape becomes compositionally more diverse, structurally more fragmented and geometrically more complex as urbanization progresses. Our study also suggests that urbanization is a process of shifting dominance among three urban growth modes: infilling, edge expanding and leapfrogging. However, idiosyncrasies do exist for individual cities, as detailed attributes of urbanization patterns often depend on the environmental and socioeconomic settings of cities. In addition, the choice of specific landscape metrics and the scales of analysis both influence the urbanization patterns revealed. Our study examined the urbanization patterns, for the first time, on long-term and global scales. The findings shed new light on the patterns and processes of urbanization, with implications for future studies of the ecology, planning and sustainability of cities. [ABSTRACT FROM AUTHOR]

Context: Rates, patterns, and consequences of urban expansion are drawing increasing attention globally because of their profound impacts on socioeconomics, human life, and the environment. Horizontal comparative studies across multiple cities over large geographic regions are rare. Objectives: We quantified and compared the magnitude and forms of urban expansion for China's 32 major cities, and examined the spatiotemporal evolution of urban growth and trajectory of patch structure formation. Methods: Multi-temporal Landsat data of circa 1978, 1990, 1995, 2000, 2005, and 2010, patch-based analyses, and urban growth metrics were used. Results: These 32 major cities have experienced extensive expansion during the study period. Leapfrogging was the dominant urban expansion form, followed by edge-expansion and infilling in the early time periods. Interestingly, the fractions of infilling, edge-expansion, and leapfrogging has gradually reached a quasi-equilibrium condition with a ratio of 2:4:4 (the number) and 2:5:3 (the area) during recent years. Patch analysis suggested that these cities evolved under a nationally-consistent converged urban patch structure regardless of city size, location, and history. The dynamics of urban growth in China corresponded well with its socioeconomic and political geography and the phased implementation of various regional and national policies. Conclusions: Our results generally supported the continuum of diffusion-coalescence urbanization process and a spatial self-organization of urban land patches during urbanization. More studies are needed to test the generality of urban growth hypothesis and examine the universality of converged urban patch structure across regions and countries and to understand their implications to city organization, metabolism, and evolution. [ABSTRACT FROM AUTHOR]

Urbanization transforms landscape structure and profoundly affects biodiversity and ecological processes. To understand and solve these ecological problems, at least three aspects of spatiotemporal patterns of urbanization need to be quantified: the speed, urban growth modes, and resultant changes in landscape pattern. In this study, we quantified these spatiotemporal patterns of urbanization in the central Yangtze River Delta region, China from 1979 to 2008, based on a hierarchical patch dynamics framework that guided the research design and the analysis with landscape metrics. Our results show that the urbanized area in the study region increased exponentially during the 30 years at the county, prefectural, and regional levels, with increasing speed down the urban hierarchy. Three growth modes—infilling, edge-expanding, and leapfrogging—operated concurrently and their relative dominance shifted over time. As urbanization progressed, patch density and edge density generally increased, and the connectivity of urban patches in terms of the average nearest neighbor distance also increased. While landscape-level structural complexity also tended to increase, the shape of individual patches became increasingly regular. Our results suggest that whether urban landscapes are becoming more homogenous or heterogeneous may be dependent on scale in time and space as well as landscape metrics used. The speed, growth modes, and landscape pattern are related to each other in complicated fashions. This complex relationship can be better understood by conceptualizing urbanization not simply as a dichotomous diffusion-coalescence switching process, but as a spiraling process of shifting dominance among multiple growth modes: the wax and wane of infilling, edge-expansion, and leapfrog across the landscape. [ABSTRACT FROM AUTHOR]

Urban form is generally accepted to be the most significant aspect controlling LST. This study analyzes the spatio-temporal urban growth pattern in India's rapidly urbanizing National Capital Region (NCR) to discern its dominant urban form based on urban sprawl metrics (USM - a neighborhood based built-up density approach) and traces its spatio-temporal growth patterns. It then gauges the relations between the landscape composition and various development modes of this dominant urban form with the ascertained nighttime LST distribution. The results of the USM based analysis show that the NCR's dominant urban form is constituted by the urban core, which has expanded markedly during the study period of 2000-2018. Within the urban core, nighttime LST increased, particularly during the fall months. Linear regression models (both non-spatial and spatial) reveal a positive relation between the nighttime LST and the built-up area and infilling growth mode. Contrarily, nighttime LST is negatively correlated with the edge-expansion and the respective areas under urbanized green and non-green open spaces. New planning approaches are thus required to restrict infilling based densification and promote well-planned edge-expansion with the designation of new green spaces as well as the greening existing non-green open spaces, particularly in areas underprovided with greenery. [Display omitted] • Links LST rise with the diffusion-coalescence hypothesis of urban growth pattern. • Dense urban core is dominant urban form wherever LST has increased dramatically. • Green and non-green open spaces within the urban core act as cold islands. • Infill restricted well-planned edge expansion can be a way forward. • Strategic conversion of non-green open space into green open space is recommended. [ABSTRACT FROM AUTHOR]