Determinants of urban sprawl in European cities

Oueslati, Walid; Alvanides, Seraphim; Garrod, Guy

doi:10.1177/0042098015577773

Cited by 249 publications

(167 citation statements)

References 40 publications

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“…Sprawl measurement techniques quantify spatial patterns and structures of land use cover patches [11,31,50]. To measure spatial configuration of urban areas, several metrics have been studied and analysed.…”

Section: Discussionmentioning

confidence: 99%

“…This landscape metric is one of the most widely used metrics to calculate the distance between patches [11,31,[42][43][44]. Both analyses allow us to measure urban dynamics depending on the distance to urban areas.…”

Section: Proximity Index For Artificial Surfaces In 1995 2007 and 2010mentioning

confidence: 99%

“…There are different definitions of urban sprawl; however, as a common definition, urban sprawl occurs in the fringe of large cities, and is defined by its compactness and dispersion. Urban sprawl is also identified as the urban expansion into the suburban areas and is categorised by unplanned [10], uneven growth [11], contiguous suburban growth [12], mixed uses [13], scattered and leapfrog development [14], strip or linear development, poly-nucleated nodal development [15], and both as a state, and a process. [16].…”

Section: Introductionmentioning

confidence: 99%

“…On the one hand, it has undesirable impacts on public health and quality of life [17], loss of farmlands [9], increased urban pollution [18], greater dependence on cars [19], or social fragmentation [20]. On the other hand, however, it also has positive impacts on the sense of community between the inhabitants [21], more living space [9], decreasing crime rates [19]-and fragmented urban growth has been perceived as economic expansion [11].…”

Section: Introductionmentioning

confidence: 99%

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Assessing the Effect of Spatial Proximity on Urban Growth

et al. 2018

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Land-Use/Cover Change (LUCC) reacts to demographic pressures, economic trends, or improved transport networks. Urban growth with implications on LUCC patterns can be measured using a diversity of methods. Our study derives from Tobler's first law of geography: 'everything is related to everything else, but near things are more related than distant ones'. We identified and measured the influence of neighbouring distance on urban growth from the edge of existing urban areas. For that, we have developed a method, built using the NetLogo software tool, which we called Land-use chAnge and Neighbouring Distance (LAND). We selected Torres Vedras (Portugal) to conduct our case study due to its increasing urban development in the past few years. The periods of analysis were 1995-2010, 1995-2007, and 2007-2010. The results have shown the influence and the effect of strong spatial correlation between the proximity of existing artificial surfaces and the emergence of new ones. The understanding of the patterns of urban growth is helpful to plan forward land developments. This method can be used to write guidelines for decision makers to monitor urban expansion and define spatial planning priorities.

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Section: Discussionmentioning

confidence: 99%

Section: Proximity Index For Artificial Surfaces In 1995 2007 and 2010mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Assessing the Effect of Spatial Proximity on Urban Growth

et al. 2018

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“…Oueslati et al (2015) examine the relationship between urban sprawl and a set of controlling factors in several European cities. Their results show the significant role that socioeconomic, transportation, and environmental factors play in urban sprawl.…”

Section: Previous Work On Densificationmentioning

confidence: 99%

Addressing the determinants of built-up expansion and densification processes at the regional scale

et al. 2018

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Abstract:An in-depth understanding of the main factors behind built-up development is a key prerequisite for designing policies dedicated to a more efficient land use. Infill development policies are essential to curb sprawl and allow a progressive recycling of low-density areas inherited from the past. This paper examines the controlling factors of built-up expansion and densification processes in Wallonia (Belgium). Unlike the usual urban/built-up expansion studies, our approach considers various levels of built-up densities to distinguish between different types of developments, ranging from low-density extensions (or sprawl) to high-density infill development. Belgian cadastral data for 1990, 2000, and 2010 were used to generate four classes of built-up areas, namely, non-, low-, medium-and high-density areas. A number of socioeconomic, geographic, and political factors related to built-up development were operationalized following the literature. We then used a multinomial logistic regression model to analyze the effects of these factors on the transitions between different densities in the two decades between 1990 and 2010. The findings indicate that all the controlling factors show distinctive variations based on density. More specifically, the centrality of zoning policies in explaining expansion processes is highlighted. This is especially 2 the case for high-density expansions. In contrast, physical and neighborhood factors play a larger role in infill development, especially for dense infill development.

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Measuring heterogeneity in urban expansion via spatial entropy

Altieri

Roli

2018

Environmetrics

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The lack of efficiency in urban diffusion is a debated issue, important for biologists, urban specialists, planners and statisticians, both in developed and new developing countries. Many approaches have been considered to measure urban sprawl, roughly identified as chaotic urban expansion; such idea of chaos is here linked to the concept of entropy. Entropy, firstly introduced in information theory, has rapidly become a standard tool in ecology, biology, and geography to measure the degree of heterogeneity among observations; in such contexts, entropy measures should include spatial information. The aim of this paper is to employ a rigorous spatial entropy‐based approach to measure urban sprawl associated to the diffusion of metropolitan cities. In order to assess the performance of the considered measures, a comparative study is run over archetypical urban scenarios; afterwards, measures are used to quantify the degree of disorder in the urban expansion of three cities in Europe. Results are easily interpretable and can be used both as absolute measures of urban sprawl and for comparison over space and time.

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Determinants of urban sprawl in European cities

Cited by 249 publications

References 40 publications

Assessing the Effect of Spatial Proximity on Urban Growth

Assessing the Effect of Spatial Proximity on Urban Growth

Addressing the determinants of built-up expansion and densification processes at the regional scale

Measuring heterogeneity in urban expansion via spatial entropy

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