Tracking Urban Sprawl: Applying Moran’s I technique in developing sprawl detection models

Hossein EstiriPhD CandidateInterdisciplinary PhD program Urban Design and PlanningUniversity of Washington MAy 30-JUNE 2, 2012

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…

Goaldeveloping and evaluating a methodology to measure and quantitatively identify urban sprawl, but not to quantify urban sprawl at this step.

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 CenterSelected Characteristics

ArcGIS 10 -- Spatial Autocorrelation (Morans I) (Spatial Statistics)

Source: ESRI (http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#//005p0000000n000000)

The index may vary between values +1.0 and −1.0, representing clustering and dispersion patterns.

Land covers data from 1992 and 2006 from NOAA Coastal Services Center.

30m*30m cells

Global Measures

Global Measures

Cluster and Outlier Analysis (Anselin Local Moran’s I) from Spatial Statistics Tools in ArcGIS 10. Local Moran’s I is a localized index for spatial autocorrelation statistic based on the Moran’s I statistic (Withers 2011).

a fixed distance band with 0.5 mile threshold distance was selected to calculate local Moran’s I for each cell. a fixed distance band with 0.5 mile threshold distance was selected to calculate local Moran’s I for each cell.

Local Measure (Local Moran’s Index)

From significant calculated Moran’s indices, values below 2472.8501 were chosen to illustrate the most dispersed areas. These values of Moran’s I also correspond to values below -1.5 standard deviation.

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 Moran’s I was also calculated.

(1) locan moran’s I z-score (Moran’s 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

• It seems that we can use spatial autocorrelation techniques (e.g. Moran’s I) and GIS to detect urban sprawl. However, recommending a sprawl detection threshold should be determined on case-by-case basis.

• While there is a significant correlation between the distance

index and the Moran’s 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

BibliographyBruegmann, Robert. Sprawl: a compact history. Chicago; London: The University of Chicago Press, 2005.Burchell, Robert W., Anthony Downs, Barbara McCann, and Sahan Mukherji. Sprawl Costs: Economic Impacts of Unchecked Development. Washington; Covelo; London: Island Press, 2005.ESRI Help. Cluster and Outlier Analysis: Anselin Local Moran's I (Spatial Statistics). n.d. http://resources.esri.com/help/9.3/arcgisdesktop/com/gp_toolref/spatial_statistics_tools/cluster_and_outlier_analysis_colon_anselin_local_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: 243-251.Nechyba, Thomas J., and Randall P. Walsh. "Urban Sprawl." The Journal of Economic Perspectives 18, no. 4 (2004): 177-200.NOAA Coastal Services Center. Coastal Change Analysis Program High-Resolution Land Cover. n.d. http://www.csc.noaa.gov/digitalcoast/data/ccaphighres/index.html.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: 284-294 .Withers, Suzanne D. "Part 10: Spatial statistics – Local Moran’s I and Getis Gi and Gi*." Advanced Quantitative Methods in Geography Course. 2011. http://depts.washington.edu/geograph/geog426/session10.ppt (accessed 6 2011).Wu, JunJie. "Environmental amenities, urban sprawl, and community characteristics." Journal of Environmental Economics and Management, 2006: 527–547.

AcknowledgementThe author would like to thank Dr. Suzanne Davies Withers for her constructive suggestions and guidance.