Abstract Lack of agreement on how to define and measure sprawl has hampered development of policy related to its causes and consequences. We question previous work for two reasons: the use of study areas that overbound or underbound sprawl landscapes, and the failure to account for land unavailable for development. We formulate “extended urban areas,” based on housing density and commuting patterns and argue that they represent a preferable geographic basis for measuring sprawl. We operationalize with satellite imagery a way for measuring land unavailable for development in these areas. We then compute five measures of urban development using the National Land Cover Data Base and decennial census data to assess the extent of sprawl in the extended urban areas of Atlanta, Baltimore, Boston, Los Angeles, and Washington. Our sensitivity analyses reveal that the measurement of sprawl critically depends on which land area forms the basis of the analysis, and, to a lesser degree, how one accounts for land unavailable for development.

New forms of urbanization are unfolding around the world that challenge inherited conceptions of the urban as a fixed, bounded and universally generalizable settlement type. Meanwhile, debates on the urban question continue to proliferate and intensify within the social sciences, the planning and design disciplines, and in everyday political struggles. Against this background, this paper revisits the question of the epistemology of the urban: through what categories, methods and cartographies should urban life be understood? After surveying some of the major contemporary mainstream and critical responses to this question, we argue for a radical rethinking of inherited epistemological assumptions regarding the urban and urbanization. Building upon reflexive approaches to critical social theory and our own ongoing research on planetary urbanization, we present a new epistemology of the urban in a series of seven theses. This epistemological framework is intended to clarify the intellectual and political stakes of contemporary debates on the urban question and to offer an analytical basis for deciphering the rapidly changing geographies of urbanization and urban struggle under early 21st-century capitalism. Our arguments are intended to ignite and advance further debate on the epistemological foundations for critical urban theory and practice today.

Urban sprawl refers to the extent of urbanisation, which is a global phenomenon mainly driven by population growth and large scale migration. In developing countries like India, where the population is over one billion, one-sixth of the world population, urban sprawl is taking its toll on the natural resources at an alarming pace. Urban planners require information related to the rate of growth, pattern and extent of sprawl to provide basic amenities such as water, sanitation, electricity, etc. In the absence of such information, most of the sprawl areas lack basic infrastructure facilities. Pattern and extent of sprawl could be modelled with the help of spatial and temporal data. GIS and remote sensing data along with collateral data help in analysing the growth, pattern and extent of sprawl. With the spatial and temporal analyses along with modelling it was possible to identify the pattern of sprawl and subsequently predict the nature of future sprawl. This paper brings out the extent of sprawl taking place over a period of nearly three decades using GIS and Remote Sensing. The study also attempts to describe some of the landscape metrics required for quantifying sprawl. For understanding and modelling this dynamic phenomenon, prominent causative factors are considered.

The literature on urban sprawl confuses causes, consequences, and conditions. This article presents a conceptual definition of sprawl based on eight distinct dimensions of land use patterns: density, continuity, concentration, clustering, centrality, nuclearity mixed uses, and proximity. Sprawl is defined as a condition of land use that is represented by low values on one or more of these dimensions. Each dimension is operationally defined and tested in 13 urbanized areas. Results for six dimensions are reported for each area, and an initial comparison of the extent of sprawl in the 13 areas is provided. The test confirms the utility of the approach and suggests that a clearer conceptual and operational definition can facilitate research on the causes and consequences of sprawl.

Purpose To determine the relationship between urban sprawl, health, and health-related behaviors. Design Cross-sectional analysis using hierarchical modeling to relate characteristics of individuals and places to levels of physical activity, obesity, body mass index (BMI), hypertension, diabetes, and coronary heart disease. Setting U.S. counties (448) and metropolitan areas (83). Subjects Adults (n = 206,992) from pooled 1998, 1999, and 2000 Behavioral Risk Factor Surveillance System (BRFSS). Measures Sprawl indices, derived with principal components analysis from census and other data, served as independent variables. Self-reported behavior and health status from BRFSS served as dependent variables. Results After controlling for demographic and behavioral covariates, the county sprawl index had small but significant associations with minutes walked (p = .004), obesity (p < .001), BMI (p = .005), and hypertension (p = .018). Residents of sprawling counties were likely to walk less during leisure time, weigh more, and have greater prevalence of hypertension than residents of compact counties. At the metropolitan level, sprawl was similarly associated with minutes walked (p = .04) but not with the other variables. Conclusion This ecologic study reveals that urban form could be significantly associated with some forms of physical activity and some health outcomes. More research is needed to refine measures of urban form, improve measures of physical activity, and control for other individual and environmental influences on physical activity, obesity, and related health outcomes.

This study intends to explore the spatial analytical methods to identify both general trends and more subtle patterns of urban land changes. Landsat imagery of metropolitan Kansas City, USA was used to generate time series of land cover data over the past three decades. Based on remotely sensed land cover data, landscape metrics were calculated. Both the remotely sensed data and landscape metrics were used to characterize long-term trends and patterns of urban sprawl. Land cover change analyses at the metropolitan, county, and city levels reveal that over the past three decades the significant increase of built-up land in the study area was mainly at the expense of non-forest vegetation cover. The spatial and temporal heterogeneity of the land cover changes allowed the identification of fast and slow sprawling areas. The landscape metrics were analyzed across jurisdictional levels to understand the effects of the built-up expansion on the forestland and non-forest vegetation cover. The results of the analysis suggest that at the metropolitan level both the areas of non-forest vegetation and the forestland became more fragmented due to development while large forest patches were less affected. Metrics statistics show that this landscape effect occurred moderately at the county level, while it could be only weakly identified at the city level, suggesting a scale effect that the landscape response of urbanization can be better revealed within larger spatial units (e.g., a metropolitan area or a county as compared to a city). The interpretation of the built-up patch density metrics helped identify different stages of urbanization in two major urban sprawl directions of the metropolitan area. Land consumption indices (LCI) were devised to relate the remotely sensed built-up growth to changes in housing and commercial constructions as major driving factors, providing an effective measure to compare and characterize urban sprawl across jurisdictional boundaries and time periods.

Although many have written about urban sprawl, few have sought to measure it. In this article, we present several quantitative measures of urban form and compute these for neighborhoods of varying age in Washington County, the western portion of the Portland, Oregon, metropolitan area. Our results suggest (1) neighborhoods in Washington County have increased in single-family dwelling unit density since the 1960s; (2) internal street connectivity and pedestrian access to commercial areas and bus stops have improved since the early 1990s; (3) external connectivity continues to decline; and (4) the mixing of land uses remains limited. We conclude that while several measures appear to be improving, Portland's war on sprawl is not yet won.

Rapid urban development and dramatic change of landscape have been recently witnessed in some developing countries as a result of rapid economic development. The measurement and monitoring of land-use changes in these areas are crucial to government officials and planners who urgently need updated information for planning and management purposes. This paper examines the use of entropy in the measurement and monitoring of urban sprawl by the integration of remote sensing and GIS. The advantages of the entropy method are its simplicity and easy integration with GIS. Thee measurement of entropy is devised based on two locational factors-distances from town centers and roads-to capture and reveal spatial patterns of urban sprawl. The entropy space can be conveniently used to differentiate various kinds of urban growth patterns. The application of the method in the Pearl River Delta, one of the fastest growing regions in China, has demonstrated that it is very useful and effective for the monitoring of urban sprawl. It provides a useful tool for the quantitative measurement that is much needed for rapidly growing regions in identifying the spatial variations and temporal changes of urban sprawl patterns.

Conceptual ambiguity of sprawl and lack of consensus among researchers have made the measurement of urban sprawl very difficult, especially from remote sensing data. There are many scales and parameters that are in use to quantify the sprawl; however, many of them are suffered from several limitations. The objective of this article is to document and discuss these sprawl measurement techniques along with their merits and demerits towards the absolute acceptance or rejection. The paper also highlights the scope and direction of future research for the measurement of urban sprawl.

City size distributions, defined on the basis of population, are often described by power laws. Zipf's Law states that the exponent of the power law for rank-size distributions of cities is near 1. Verification of power law scaling for city size distributions at continental and global scales is complicated by small sample sizes, inappropriate estimation techniques, inconsistent definitions of urban extent and variations in the accuracy and spatial resolution of census administrative units. We attempt to circumvent some of these complications by using a continuous spatial proxy for anthropogenic development and treat it as a spatial complement to population distribution. We quantify the linearity and exponent of the rank-size distribution of spatially contiguous patches of stable night light over a range of brightnesses corresponding to different intensities of development. Temporally stable night lights, as measured by the Defense Meteorological Satellite Program-Operational Line Scanner (DMSP-OLS), provide a unique proxy for anthropogenic development. Brightness and spatial extent of emitted light are correlated to population density (Sutton et al., 2001), built area density (Elvidge et al., 2007c) and economic activity ( Doll et al., 2006 and Henderson et al., 2009 ) at global scales and within specific countries. Using a variable brightness threshold to derive spatial extent of developed land area eliminates the complication of administrative definitions of urban extent and makes it possible to test Zipf's Law in the spatial dimension for a wide range of anthropogenic development. Higher brightness thresholds generally correspond to more intense development while lower thresholds extend the lighted area to include smaller settlements and less intensively developed peri-urban and agricultural areas. Using both Ordinary Least Squares (OLS) and Maximum Likelihood Estimation (MLE) to estimate power law linearity and exponent of the resulting rank-size distributions across a range of upper tail cutoffs, we consistently find statistically significant exponents in the range 0.95 to 1.11 with an abrupt transition to very large, extensively connected, spatial networks of development near the low light detection limit of the sensor. This range of exponents and transition are observed at both continental and global scales. The results suggest that Zipf's Law also holds for spatial extent of anthropogenic development across a range of intensities at both continental and global scales. The implication is that the dynamics of urban growth and development may be represented as spatial phase transitions when the spatial extent and intensity of development are treated as continuous variables rather than discrete entities.

This article reviews the literature on characteristics, causes, and costs of alternative development patterns. In doing so it debunks arguments by Gordon and Richardson in favor of Los Angeles-style sprawl. Sprawl is not suburbanization generally, but rather forms of suburban development that lack accessibility and open space. Sprawl is not a natural response to market forces, but a product of subsidies and other market imperfections. The costs of sprawl are borne by all of us, not just those creating it, and include inflated public spending, loss of resource lands, and a waning sense of community. The only realistic cure for sprawl is active planning of the sort practiced almost everywhere except the United States (and beginning to appear here out of necessity).

Because of its rapid economic development, China has been undergoing a dramatic urbanization process in recent decades. Such a process can be reflected by urban expansion, which can be represented by the change in urban built-up areas. In the literature, very little has been discussed on the extraction of built-up areas with a high frequency of acquisition for a large region. This article introduces a methodology to extract built-up areas using night-time stable light data. An improved calibration method is formulated to first eliminate the discrepancies across different satellites and years. A thresholding technique utilizing the sudden jump method is then employed to extract built-up areas for each prefectural city in each year. This method selects the best threshold by scrutinizing the sudden jump in the natural logarithms of the areas under different digital number (DN) thresholds. Moreover, the urbanization process of South China is examined using the extracted time series of built-up areas. The results show that such extracted time series represent changes in urban areas rather well when compared with the Thematic Mapper (TM) images, and a significant linear relationship between the extracted built-up areas and those of the land-use map and the China City Statistical Yearbook (CCSY) has also been established. Moreover, the empirical analyses also reveal that urban expansion took place in all cities from 1992 to 2010, especially in coastal cities, capital cities, and cities in the special economic zones.