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Hossein Estiri PhD Candidate Interdisciplinary PhD program Urban Design and Planning University of Washington MAy 30-JUNE 2, 2012.

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Presentation on theme: "Hossein Estiri PhD Candidate Interdisciplinary PhD program Urban Design and Planning University of Washington MAy 30-JUNE 2, 2012."— Presentation transcript:

1 Hossein Estiri PhD Candidate Interdisciplinary PhD program Urban Design and Planning University of Washington MAy 30-JUNE 2, 2012

2 Urban Sprawl is widely discussed among scholars; however, the understanding about it is still inadequately implicit… There are many definitions for sprawl that imply a multitude of quantitative & qualitative methods to explaining its extents. Some General Definitions the tendency toward a decreasing density as the urban area expands (Nechyba and Walsh 2004)…low-density, scattered & dispersed along highways developments (Bruegmann 2005; Morris 2005), excessive suburbanization, disjointed pattern of land development (Wu 2006), leapfrog development (Burchell, et al. 2005), lack of multi-use development patterns, automobile dependence, gridlock, and inadequate public transit (Morris 2005). Problem: Defining Urban Sprawl! since the dimensions of urban sprawl differ from place to place, it is difficult to define generalizable criteria to measure the extent of urban sprawl… Goal developing and evaluating a methodology to measure and quantitatively identify urban sprawl, but not to quantify urban sprawl at this step.

3 I used a geospatial analysis tool in ArcGIS 10 to develop a measurement technique and assess its feasibility to quantitatively identify urban sprawl. Moran's I (Moran 1950) a measure of spatial autocorrelation … measures the observed similarity based on a simultaneous measurement of both observed locations and observed values (Winter-Livneha, Svorayb and Gileada 2010). The ArcGIS tool is developed to study spatial clustering or dispersion. Methodology the tendency toward a decreasing density as the urban area expands (Nechyba and Walsh 2004)…low-density, scattered & dispersed along highways developments (Bruegmann 2005; Morris 2005), excessive suburbanization, disjointed pattern of land development (Wu 2006), leapfrog development (Burchell, et al. 2005), lack of multi-use development patterns, automobile dependence, gridlock, and inadequate public transit (Morris 2005). Dispersion ………………. Distance from City Center Selected Characteristics

4 ArcGIS Spatial Autocorrelation (Morans I) (Spatial Statistics) Source: ESRI (http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#//005p n000000)http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#//005p n The index may vary between values +1.0 and 1.0, representing clustering and dispersion patterns.

5 Land covers data from 1992 and 2006 from NOAA Coastal Services Center. 30m*30m cells

6 Global Measures

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8 Cluster and Outlier Analysis (Anselin Local Morans I) from Spatial Statistics Tools in ArcGIS 10. Local Morans I is a localized index for spatial autocorrelation statistic based on the Morans I statistic (Withers 2011). a fixed distance band with 0.5 mile threshold distance was selected to calculate local Morans I for each cell. Local Measure (Local Morans Index)

9 From significant calculated Morans indices, values below were chosen to illustrate the most dispersed areas. These values of Morans I also correspond to values below -1.5 standard deviation.

10 Adding 2 urbanization indices 1sq.mile grids -- The closet Euclidean distance to Downtowns Seattle and Bellevue for each of the land cover cells with significant local Morans I was also calculated.

11 (1)locan morans I z-score (Morans I index); (2)percent developed land in the 1-Mile grid (%Urban); (3)percent land cover change from Natural to Urban in the 1-Mile grid (%Urbanized); (4)distance from downtowns (Distance); and (5)percent dispersed area in 1_mile grid (%Dispersed). 5 calculated indices

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13 It seems that we can use spatial autocorrelation techniques (e.g. Morans I) and GIS to detect urban sprawl. However, recommending a sprawl detection threshold should be determined on case-by-case basis.sprawl detection threshold While there is a significant correlation between the distance index and the Morans I index, Non-linearity is evident. This might be due to either limitations of measurement in this study or nature the phenomenon of sprawl. Limitations Euclidean distance vs. Network Distance Impacts of water bodies on local measures

14 Bibliography Bruegmann, Robert. Sprawl: a compact history. Chicago; London: The University of Chicago Press, Burchell, Robert W., Anthony Downs, Barbara McCann, and Sahan Mukherji. Sprawl Costs: Economic Impacts of Unchecked Development. Washington; Covelo; London: Island Press, ESRI Help. Cluster and Outlier Analysis: Anselin Local Moran's I (Spatial Statistics). n.d. _moran_s_i_spatial_statistics_.htm. Kahn, Matthew E. "The environmental impact of suburbanization." Journal of Policy Analysis and Management 19, no. 4 (2000): 569–586. Moran, P. "The interpretation of statistical maps." Journal of the Royal Statistical Society, 1948: Nechyba, Thomas J., and Randall P. Walsh. "Urban Sprawl." The Journal of Economic Perspectives 18, no. 4 (2004): NOAA Coastal Services Center. Coastal Change Analysis Program High-Resolution Land Cover. n.d. Winter-Livneha, Rona, Tal Svorayb, and Isaac Gileada. "Settlement patterns, social complexity and agricultural strategies during the Chalcolithic period in the Northern Negev, Israel." Journal of Archaeological Science, 2010: Withers, Suzanne D. "Part 10: Spatial statistics – Local Morans I and Getis Gi and Gi*." Advanced Quantitative Methods in Geography Course (accessed ). Wu, JunJie. "Environmental amenities, urban sprawl, and community characteristics." Journal of Environmental Economics and Management, 2006: 527–547. Acknowledgement The author would like to thank Dr. Suzanne Davies Withers for her constructive suggestions and guidance.


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