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Measuring Spatial Patterns and Measuring Spatial Patterns and Trends in Urban DevelopmentTrends in Urban Development

Jason ParentJason Parentjason.parent@uconn.edujason.parent@uconn.edu

Academic Assistant – GIS AnalystAcademic Assistant – GIS Analyst

Daniel CivcoDaniel CivcoProfessor of GeomaticsProfessor of Geomatics

Center for Land Use Education And Research (CLEAR) Center for Land Use Education And Research (CLEAR) Natural Resources Management and Engineering Natural Resources Management and Engineering

University of Connecticut University of Connecticut

Shlomo AngelShlomo AngelAdjunct Professor of Urban PlanningAdjunct Professor of Urban Planning

Robert F. Wagner School of Public Service, New York Robert F. Wagner School of Public Service, New York University University

Woodrow Wilson School of Public and International Affairs, Woodrow Wilson School of Public and International Affairs, Princeton University Princeton University

Image courtesy of the Union of Concerned Scientists: www.ucsusa.org

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The Consequences The Consequences of Development Pattern and of Development Pattern and

DensityDensity► Development consumes and degrades Development consumes and degrades

nearby natural resources.nearby natural resources.► The pattern of development influences the The pattern of development influences the

impact on natural resources…impact on natural resources… ““Sprawling” patterns consumes more land than Sprawling” patterns consumes more land than

traditional urban development and causes traditional urban development and causes greater fragmentation of open lands.greater fragmentation of open lands.

► Population density determines how much Population density determines how much land is consumed for a given population.land is consumed for a given population. Low population densities result in more land Low population densities result in more land

being converted to urban land cover.being converted to urban land cover.

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Indicators of ‘sprawling’ Indicators of ‘sprawling’ development?development?

1.1. Declining spatial density of developed landDeclining spatial density of developed land

2.2. Declining population densityDeclining population density

3.3. Increasing amount of degradedIncreasing amount of degraded** land land relative to the developed arearelative to the developed area

4.4. Increasing interspersion of developed and Increasing interspersion of developed and undeveloped landundeveloped land

5.5. Declining compactness of the urban areaDeclining compactness of the urban area

6.6. Increasing numbers of unviable patches Increasing numbers of unviable patches isolated by urbanized landisolated by urbanized land

* We consider land “degraded” if within 100 meters of developed land

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ObjectivesObjectives►Develop metrics that can be used to Develop metrics that can be used to

quantify major indicators of urban quantify major indicators of urban sprawl.sprawl. Metrics comparable over time and for Metrics comparable over time and for

different citiesdifferent cities

►Apply metrics to a global sample of 120 Apply metrics to a global sample of 120 cities for two time periods: circa 1990 cities for two time periods: circa 1990 and 2000.and 2000. Correlate metrics with socio-economic Correlate metrics with socio-economic

factors including income levels, political factors including income levels, political region, and city population.region, and city population.

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Land Cover MapsLand Cover Maps

►Basis for all analysis.Basis for all analysis.►Derived from Landsat satellite imageryDerived from Landsat satellite imagery

pixel size 30 meterspixel size 30 meters

Color Infrared(4,5,3)

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Land Cover MapsLand Cover Maps

►Classified urban (developed) and water Classified urban (developed) and water for each city for the two time periods.for each city for the two time periods.

►““Other” is considered open Other” is considered open (undeveloped) land.(undeveloped) land.

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Population dataPopulation data

►Population data associated with Population data associated with administrative districts for each city.administrative districts for each city.

►Census data interpolated to estimate Census data interpolated to estimate population for land cover dates.population for land cover dates.

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Slope dataSlope data

►Slope derived from Shuttle Radar Slope derived from Shuttle Radar Topography Mission data.Topography Mission data. pixel resolution of 85 meterspixel resolution of 85 meters resampled to match land cover resolutionresampled to match land cover resolution

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Spatial density of developed Spatial density of developed landland

►Developed land cover approximates Developed land cover approximates impervious surface area.impervious surface area.

►Developed pixels classified based on Developed pixels classified based on percentage of land within 560 meters percentage of land within 560 meters that is developed.that is developed. A roving neighborhood centers on each A roving neighborhood centers on each

developed pixel and % developed land is developed pixel and % developed land is calculated.calculated.

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960 dev. pix

1200 total pix= 80%

Urban50-100%

Developed pixels are dark gray

560 m

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240 dev. pix

1200 total pix= 20%

Suburban10 – 50%

Developed pixels are dark gray

560 m

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40 dev. pix

1200 total pix= 3%

Rural0 – 10%

Developed pixels are dark gray

560 m

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Kauffman, G. and T. Brant. The Role of Impervious Cover as a Watershed-based Zoning Tool to Protect water Quality in the Christina River Basin of Delaware, Pennsylvania, and Maryland. University of Delaware, Institute for Public Administration, Water Resources Agency. Watershed Management 2000 Conference

Percent imperviousness vs. Percent imperviousness vs. development densitydevelopment density

suburban

urban

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Developed pixel classificationDeveloped pixel classification

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Open land degraded by proximity Open land degraded by proximity to developed landto developed land

► Close proximity of open land to developed Close proximity of open land to developed land reduces natural resource value:land reduces natural resource value: Lower quality as habitat.Lower quality as habitat. Increased susceptibility to invasive species.Increased susceptibility to invasive species. Less suitable as a timber resource (if forested).Less suitable as a timber resource (if forested).

► Over what distances do “edge-effects” occur?Over what distances do “edge-effects” occur? Depends on issue of interestDepends on issue of interest

► For habitat, ranges from 25 meters to several hundred For habitat, ranges from 25 meters to several hundred meters depending on species.meters depending on species.

We assume a 100 meter edge-width for general We assume a 100 meter edge-width for general purposes in this study.purposes in this study.

► Lands within 100 meters of developed land Lands within 100 meters of developed land are classified as are classified as edge open land.

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Open land degraded by isolation Open land degraded by isolation from other non-degraded open landsfrom other non-degraded open lands

► Open land may be degraded if Open land may be degraded if cut-off from other open lands.cut-off from other open lands. Many species require mixing Many species require mixing

between different between different populations.populations.

Isolated patches may be too Isolated patches may be too small to sustain viable small to sustain viable populations for certain populations for certain species.species.

► We consider the following We consider the following to be impassable to wildlife:to be impassable to wildlife: urbanurban suburbansuburban edge open landedge open land

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Patch size vs. habitat qualityPatch size vs. habitat quality

► We assume that We assume that patches are patches are viable if larger viable if larger than 200 ha.than 200 ha.

► Patches smaller Patches smaller than 200 ha are than 200 ha are classified as classified as isolated open isolated open patchespatches..

http://sof.eomf.on.ca/Biological_Diversity/Ecosystem/Fragmentation/Indicators/Size/i_wooded_patch_size_by_watershed_e.htm

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Baku, Azerbaijan T1 (July 1988)

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Baku, Azerbaijan T2 (Aug 1999)

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Baku, AzerbaijanBaku, Azerbaijan

CategoryCategory T1T1 T2T2 Annual % Annual % ChangeChange

Total dev. (kmTotal dev. (km22)) 114.8114.8 155.1155.1 3.2%3.2%

Urban (%)Urban (%)** 31%31% 42%42% 1.0%1.0%

Suburban (%)Suburban (%)** 57%57% 48%48% -0.8%-0.8%

Rural (%)Rural (%)** 12%12% 10%10% -0.2%-0.2%

Edge open (%)Edge open (%)** 145%145% 120%120% -2.3%-2.3%

Isolated open (%)Isolated open (%)** 6.4%6.4% 3.5%3.5% -0.3%-0.3%

* Areas represented as percent of the total developed area

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Population densityPopulation density

► Measured for the developed areaMeasured for the developed area► Population from city administrative districtsPopulation from city administrative districts

T1T1 T2T2 Annual % changeAnnual % change

275275 230230 -1.7%-1.7%

Population density (persons / ha) of developed area for Baku

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Interspersion of Interspersion of developed and open landdeveloped and open land

►Greater dispersion of developed land Greater dispersion of developed land within open land increases the amount within open land increases the amount of open land influenced per unit of of open land influenced per unit of developed land.developed land.

►Sprawling development patterns are Sprawling development patterns are expected to have greater percentage of expected to have greater percentage of developed land that is adjacent to open developed land that is adjacent to open land. land.

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Interspersion of developed and open Interspersion of developed and open land land

– the Edge Index– the Edge Index

► Edge Index:Edge Index: The fraction of developed The fraction of developed

pixels that are cardinally pixels that are cardinally adjacent to at least one adjacent to at least one undeveloped pixel.undeveloped pixel.

In other words, the In other words, the fraction of pixels that fraction of pixels that make up the edge of the make up the edge of the developed area.developed area.

Built-up pixels in grayOpen pixels in white

Roving window centers on each developed pixel

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Interspersion of developed and open Interspersion of developed and open land land

– the Openness Index– the Openness Index

The Openness Index:The Openness Index: ► The average The average opennessopenness of of

developed pixels.developed pixels.► Openness = the fraction Openness = the fraction

of land within a 560 of land within a 560 meter radius that is meter radius that is undeveloped.undeveloped. Roving neighborhood Roving neighborhood

centers on each centers on each developed pixel.developed pixel.

960 open pix

1200 total pix= 0.8

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MetricMetric T1T1 T2T2 Annual % Annual % ChangeChange

Edge indexEdge index 0.730.73 0.710.71 -0.3%-0.3%

Openness indexOpenness index 0.650.65 0.610.61 -0.6%-0.6%

Interspersion metrics for BakuInterspersion metrics for Baku

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The shape of the urban footprintThe shape of the urban footprint

► The urban footprint is the land directly The urban footprint is the land directly impacted by the presence of development.impacted by the presence of development.

► Irregular and non-compact footprints will Irregular and non-compact footprints will create more edge and isolated open land create more edge and isolated open land and encourage low density development.and encourage low density development.

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Compactness indicesCompactness indices

►We use several metrics for measuring We use several metrics for measuring compactness of a shape:compactness of a shape: Values are normalized and range between Values are normalized and range between

0 and 10 and 1►Normalized using a circle with area equal to Normalized using a circle with area equal to

the shape area – the the shape area – the equal area circleequal area circle

Most are highly correlated with each other Most are highly correlated with each other and with people’s perception of and with people’s perception of compactnesscompactness

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Metrics vs. intuitionMetrics vs. intuition

► Metrics are highly correlated with each other Metrics are highly correlated with each other as well as with people’s intuition.as well as with people’s intuition.

► Metrics are good proxies for each other – Metrics are good proxies for each other – some are easier to calculate.some are easier to calculate.

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Correlation Matrix

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Measuring Compactness: The Proximity Measuring Compactness: The Proximity IndexIndex

The Proximity IndexThe Proximity Index::► Based on average Based on average

distance, of all points in distance, of all points in the urban footprint, to the urban footprint, to the center of the the center of the footprint.footprint.

► Normalized by the Normalized by the average distance (d) to average distance (d) to center of the center of the equal area equal area circlecircle with radius (r) – a with radius (r) – a circle with an area equal circle with an area equal to that of the urban to that of the urban footprint.footprint. d = (2 / 3) * rd = (2 / 3) * r

Urban footprint in gray,center is black

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Measuring Compactness: The Cohesion Measuring Compactness: The Cohesion IndexIndex

The Cohesion Index:The Cohesion Index:► Based on the average Based on the average

distance between all distance between all possible pairs of points possible pairs of points in the urban footprintin the urban footprint

► Normalized by average Normalized by average distance (d) between distance (d) between all pairs of points within all pairs of points within the the equal area circle equal area circle with radius (r).with radius (r). d = 0.9054 * rd = 0.9054 * r

Urban footprint pixels in gray,sample points in black

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Measuring Compactness: Measuring Compactness: The Exchange and Net Exchange IndicesThe Exchange and Net Exchange Indices

The Exchange IndexThe Exchange Index► The fraction of the shape area The fraction of the shape area

that is within an that is within an equal area equal area circlecircle centered at the shape centered at the shape center.center.

The Net Exchange IndexThe Net Exchange Index► The fraction of the shape area The fraction of the shape area

that is within the that is within the netnet equal area equal area circlecircle centered at the shape centered at the shape center.center.

► The The net equal area circlenet equal area circle has a has a buildable area (excluding water buildable area (excluding water and excessive slope) equal to and excessive slope) equal to the urbanized areathe urbanized area

Compactness = 0.75

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Urban footprints ofUrban footprints ofMinneapolis and BangkokMinneapolis and Bangkok

Bangkok (1994) Minneapolis (1992)

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Exchange Index for Bangkok (1994-2002) Exchange Index for Bangkok (1994-2002) and Minneapolis (1992-2001)and Minneapolis (1992-2001)

MetricT1 T2 Annual ΔT

Bangkok Minneapolis Bangkok Minneapolis Bangkok Minneapolis

Proximity 0.67 0.87 0.75 0.91 1.11% 0.46%

Cohesion 0.65 0.85 0.72 0.89 0.97% 0.46%

Compactness 0.62 0.75 0.66 0.80 0.56% 0.57%

Constrained compactness

0.62 0.77 0.67 0.82 0.62% 0.57%

Increasing compactness

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Preliminary resultsPreliminary results

►Sprawl tends to be inversely correlated Sprawl tends to be inversely correlated with income level:with income level: Developed countries have much lower Developed countries have much lower

population densities than developing population densities than developing countries.countries.

Population density in all regions tends to Population density in all regions tends to decline over time.decline over time.

►Spatial densities seem to increase over Spatial densities seem to increase over time as the result of infill of the urban time as the result of infill of the urban footprint.footprint. Possibly a cyclic phenomenaPossibly a cyclic phenomena

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ConclusionsConclusions

► Analysis of a global sample of 120 cities will Analysis of a global sample of 120 cities will be completed in the near future…be completed in the near future… Will determine significance of factors believed to Will determine significance of factors believed to

drive urban sprawl.drive urban sprawl. Will illuminate how urban development patterns Will illuminate how urban development patterns

and population densities change over time.and population densities change over time.

► Metrics have potential applications in other Metrics have potential applications in other landscape level analyses…landscape level analyses… i.e. measuring patch compactness, interspersion i.e. measuring patch compactness, interspersion

of land covers, etc.of land covers, etc.

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PublicationsPublications► Future publications and project information will be available

through the Center for Land Use Education and Research – http://clear.uconn.edu

► Angel, S, J. R. Parent, and D. L. Civco. May 2007. Urban Sprawl Metrics: An Analysis of Global Urban Expansion Using GIS. ASPRS May 2007 Annual Conference. Tampa, FL

► Angel, S, S. C. Sheppard, D. L. Civco, R. Buckley, A. Chabaeva, L. Gitlin, A. Kraley, J. Parent, M. Perlin. 2005. The Dynamics of Global Urban Expansion. Transport and Urban Development Department. The World Bank. Washington D.C., September.

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Urban Growth Analysis:Urban Growth Analysis:Calculating Metrics to Quantify Urban Calculating Metrics to Quantify Urban

SprawlSprawlJason ParentJason Parent

jason.parent@uconn.edujason.parent@uconn.eduAcademic Assistant – GIS AnalystAcademic Assistant – GIS Analyst

Daniel CivcoDaniel CivcoProfessor of GeomaticsProfessor of Geomatics

Center for Land Use Education And Research (CLEAR) Center for Land Use Education And Research (CLEAR) Natural Resources Management and Engineering Natural Resources Management and Engineering

University of Connecticut University of Connecticut

Shlomo AngelShlomo AngelAdjunct Professor of Urban PlanningAdjunct Professor of Urban Planning

Robert F. Wagner School of Public Service, New York Robert F. Wagner School of Public Service, New York University University

Woodrow Wilson School of Public and International Affairs, Woodrow Wilson School of Public and International Affairs, Princeton University Princeton University

Image courtesy of the Union of Concerned Scientists: www.ucsusa.org

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