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It is extremely difficult to define urban sprawl. The initial definition of sprawl was used for growth management in Florida in the early 90s (Ewing 1997). The definition which was eventually adopted by the State included four types of urban forms which are the following: (1) scattered or leapfrog development, (2) commercial strip development, (3) low-density development, and (4) single-use development

One common characteristic of all four types of development pattern is poor accessibility.

In scattered development, residents and service providers must pass vacant land on their way from one developed use to another.

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In classic strip development, the consumer must pass other uses on the way from one store to the next; it is the antithesis of multipurpose travel to an activity center.

Obviously, in low-density and single-use development, everything is far apart because of large land holdings and isolation of land uses. (Write something more)

In sprawl, poor accessibility generally leaves the residents with no choice other than using automobile for kilometers and kilometers of travel.


Measuring Sprawl

Beginning around 2000, there came a shift and researchers pursued to develop objective measures of sprawl which would be related to quantifiable outcomes with the purpose of changing the debate over sprawl from subjective to objective and quantitative. (shima hamidi)

Early attempts to quantify the amount of urban sprawl were quite rudimentary as most of the researchers created measures of urban sprawl that were only focused on population density (Pendall 1999; Fulton et al. 2001; Lang 2003; Pendall and Carruthers 2003). The probable reason for density to be the primary indicator of sprawl in the early studies were that it is anything but difficult to calculate and catches one critical dimension of sprawl. However, considering only density as a measure of sprawl undermines the complexity of sprawl and does not captures all the essential elements of sprawl. (Shima Hamidi)

The same mistakes were made in initial research related to quantitative studies of sprawl using satellite imagery and GIS as they neglected the land use interactions and street patterns. (Besussi and Chin 2003; Burchfield et al. 2006; Malpezzi and Guo 2001; Torrens and Alberti 2000).

Most of these studies used land maps taken from satellite imagery to calculate form factors such as edge density and fractal dimension (Huang, Lu, and Sellers 2007; Martellozzo and Clarke 2011; Poelmans and Van Rompaey 2009). Increase in availability and enhancement of quality of satellite imagery have made it relatively simpler in recent years to study land form maps (Batisani and Yarnal 2009; Thapa and Murayama 2010; Bhatta, Saraswati, and Bandyopadhyay 2010). As these methods did not take into account the land use and street connectivity patterns they are not good enough to differentiate between the development patterns leading to high accessibility and development patterns leading to low accessibility. (Shima Hamidi)

A notable thing about urban form measurement in these experiments was the various sprawl ratings offered to various metros by numerous analysts. With the exception of Atlanta, which often ranks as among the worst, the various variables utilized to operationalize sprawl lead to different outcomes. In a study, Portland was ranked among the very least sprawling along with Los Angeles which was ranked among the most sprawling (Glaeser, Kahn, and Chu 2001). Whereas in another different study, the rankings of two cities were reversed (Nasser and Overberg 2001). Another prominent deficiency was the failure to corroborate sprawl metrics against logical outcomes such as travel characteristics of the population. (Shima Hamidi)

Sprawl has a consistently recognized outcome with respect to automobile dependence, with increase in sprawl automobile dependence increases. Contemporary research as shown that after controlling for other relevant influences, sprawling cities have reasonably high auto ownership, low transit commute mode share, low walkability, as well as long drive times to do the work place. (Shima Hamidi)



Most researchers now agree that sprawl is a multidimensional phenomenon that is best measured by a combination of factors (Galster et al. 2001; Ewing, Pendall, and Chen 2002; Cutsinger et al. 2005; Frenkel and Ashkenazi 2008; Torrens 2008; Jaeger et al. 2010; Mubareka et al. 2011).

This multi-dimensionality of sprawl has led to a lot of questions such as: What are the various dimensions of sprawl? How to measure them? Should these dimensions be combined into a single sprawl index and, if so, how? (Shima Hamidi)

Galster et al. (2001) first developed the multidimensional measures of sprawl. He disaggregated land use patterns into eight dimensions: density, clustering, centrality, continuity, concentration, nuclearity, heterogeneity, and proximity. Sprawl then was defined as any pattern of land use development that had low levels in one or more of these dimensions. The researchers defined each dimension and quantified six of the eight measures for multiple urbanized areas.

Cutsinger et al. (2005) updated the index by using twelve conceptually distinct dimensions of land use patterns that were used to calculate sprawl for fifty large U.S. metropolitan areas. (Hamidi et al.)

Another important initial effort was that of Ewing, Pendall, and Chen (2002). They computed sprawl in two steps: first, using principal component analysis, they developed indices for four constituents of urban form—development density, land use mix, activity centering, and street accessibility. They then combined the 4 factors into a general compactness/ sprawl index. General index and both the single elements were then validated against transportation outcome measures.

Categories: Management


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