Parameterisation of Urban Sprawl Amon Boontore. S p r a w l P l a n i m e t e r Slpanimeter +...

Parameterisation of Urban SprawlAmon Boontore

S p r a w l P l a n i m e t e r

Slpanimeter

+

Optional Title

Outline

1)Main Objective

2) Operational Indicators of Urban Sprawl

3) Pilot Study

4) Future Works

Main Objective

Geographical Distribution of Land-uses

Geographical Separation

Travel

Urban Sprawl

Distance Travelle

d

Measurement is a key initial step in scientific understanding (De Cola & Lam 1993).

Definitions

Characteristics

Indicators

Earle Draper

Perhaps diffusion is too kind of word...in

bursting its bounds, the city actually sprawled

and made the countryside

ugly...uneconomic [in terms] of services and doubtful social value.

First Used

Sprawl is a pattern of land use in an urbanised area that exhibits low levels of some combination of eight distinct dimensions: density, continuity, concentration, clustering, centrality, nuclearity, mixed uses, and proximity (Galster et al 2001).The term is used variously to mean the gluttonous use of land, uninterrupted monotonous development and inefficient use of land (Peiser 2001).

Sprawl is the spread-out, skipped over development that characterises the non-central city metropolitan areas and non-metropolitan areas … (Ewing 1997).

…low-density development beyond the edge of service and development, which separates where people live from where they shop, work, recreate, and educate-thus requiring cars to move between zones (Seirra Club 1998).1. Low residential density

2. Unlimited outward extension of new development

3. Spatial segregation of different types of land uses through zoning regulations

4. Leapfrog development

5. No centralised ownership of land or planning of development

6. All transportation dominated by privately owned motor vehicles

7. Fragmentation of governance authority over land uses between many local governments

8. Great variances in the fiscal capacity of local governments

9. Widespread commercial strip development along major roadways

10. Major reliance upon the filtering or “trickle-down” process to provide housing for low-income households

(Transportation Research Board 1998).

Definitions of Urban Sprawl

Characteristics of Urban Sprawl

Subjective

Research Approach

Time & Data Limitation

Subjective

Prejudgement

Prejudgement

Subjective

1) Form

2) Density

3) Land-use Pattern

4) Urban Process

5) Impacts

6) Dependent Variable

7) Aesthetic

8) Example

1) Low Density

2) Spatial Seclusion

3) Single Functional Use

1) Low Density



2.1) Evenness 2.4)

Centralisation

2.2) Complexity

2.3) Clustering

Index of Dissimilar

ity

Gini

Entropy

Atkinson

Thiel’s

Index Fractal Dimensi

on

PARGeary’s Coefficie

ntMoran’s

I

Centralisation Index

ACI

3.1) Concentration

3.2) ExposureDuncan’s

Delta

ICO

Relative Concentration Index

ISO

Interaction Index

CTGETA

IJI

Residential

Density

Urban

Density

Residential Land-

use Density

Density Gradien

ts

1.1) Density

Sprawl Conceptual Variables & Indicators


i, j, k = number of tract

= Total developable land area

= Area of developable land in tract i

= Total residential land area

= Area of residential land in tract i

= Total non-residential land area

= Area of non-residential land in tract I

= Total developed land area

= Area of developed land in tract i

= Total residential proportion

= Residential Proportion in tract i

i

i

i

i

i

City A

City tract A1 = 100

City tract A2 = 100

1 5

2 15

1 10

2 5

1 30

2 50

1

1

2

2

Index of Dissimilarity:

2.1) Evenness


1 2 1

IOD = n

i i

i

3.1) Concentration Relative Concentration

Index:


1

1

1

21

1

1

/

/

RCO =

/

/

n

i iin

i ii

n

i i iin

i ii

3.2) Exposure

Interaction Index:


1

INT= n

i i

ii

Pilot Study: Data & MethodologyLand cover

maps

250 metres resolution

Year 2000

CORINE (Coordination of Information on the Environment) European Environment Agency

Maps

Distance

Travelled Data

Transportation DataInternational

Association of Public Transport (UITP)

Year 1995

Case Studies

30

Austria: Graz, Vienna; Belgium: Brussels; Denmark: Copenhagen; Finland: Helsinki; Paris: Lyon, Marseille, Nantes, Paris; Germany: Berlin, Frankfurt, Hamburg, Dusseldorf, Munich, Stuttgart; Greece: Athens; Italy: Milan, Bologna, Rome; Netherlands: Amsterdam; Spain: Barcelona, Madrid; Sweden: Stockholm; UK:Glasgow, London, Manchester, Newcastle

Overall average trip distance (km/trip)

Car

Public modes

Mechanised modes

Private modes Motorise

d modes

Motorised modes

Overall Mobility (daily trips/cap)

– Foot

Mechanised modes

Public modes

Private modes

Pilot Study: Data & Methodology

Daily Km/capMechanis

ed

Private

Public

Motorised

All

Mineral extraction sites

Undevelopable land

Inland marchesBeaches, dunes, sands

Bare rocks

Burnt Areas

Glaciers and perpetual snow

Peat bogs

Dump sites

Salt marshesSalines

Intertidal flats

Water courses

Water bodies

Coastal lagoons

Estuaries

Sea and ocean

Road and rail networks and associated land

RN Construction

sites

Non-irrigated arable land

Permanently irrigated land

Rice fieldsVineyards

Fruit trees and berry plantations

Olive groves

Pastures

Annual crops

Complex cultivation patterns

Natural vegetation

Agro-forestry areas

Broad-leaved forest

Coniferous forest

Mixed forest

Natural grasslands

Moors and heathland

Sclerophyllous vegetation

Woodland-schrub

Sparsely vegetated areas

Developable land

Continuous urban fabricDiscontinuous urban fabric

Residential land

Industrial and commercial units Port

areasAirports Green urban

areasSport and leisure facilities

Non-residential land


1

9

876

543

2

...n

12...10 11


Data Sourcing Evenness:

IODConcentration: RCO

Exposure: INT


Pilot Study: Results

R2 = .176

Sig. = .003


Grouping of Case StudiesRange (million

m2)n

XS

XL

L

M

SM

S

158-716

1182-36664796

4997-7834

10533-125214476

1Total

5

1

104

1

30

9


R2 = .883

Sig. = .002

SM-M


R2 = .549

Sig. = .006

XS-S


R2 = .415

Sig. = .033

XS-S-SM

Pilot Study: ResultsXS XLLMSMS

RCO-Private (12, .549, .006)IOD-Public (13, .342, .036)

RCO-Private (13, .414, .018)IOD-Public (15, .305, .033)INT-Public (11, .415, .033)

IOD-Mechanised (9, .714, .004)IOD-Mechanised (8, .683, .011)

IOD-Mechanised (10, .733, .002)IOD-Mechanised (9, .705, .005)IOD-Mechanised (8, .833, .002)

RCO-Motorised (20, .237, .03)

RCO-Private (14, .374, .02)RCO-Motorised (15, .294, .037)

RCO-Motorised (27, .176, .03)

(5) (9) (1) (10)

(4) (1)

Future Works

5x5 Km grid sq

1

9

876

543

2

...n

12...10 11

Workable Grid Size

Reduction of Indicators

?

Future Works: Sensitivity Plot

IOD

RCOFuture Works: Sensitivity Plot

INTFuture Works: Sensitivity Plot

1) Low Density



2.1) Evenness 2.4)

Centralisation

2.2) Complexity

2.3) Clustering

Index of Dissimilar

ity

Gini

Entropy

Atkinson

Thiel’s

Index Fractal Dimensi

on

PARGeary’s Coefficie

ntMoran’s

I

Centralisation Index

ACI

3.1) Concentration

3.2) ExposureDuncan’s

Delta

ICO

Relative Concentration Index

ISO

Interaction Index

CTGETA

IJI

Residential

Density

Urban

Density

Residential Land-

use Density

Density Gradien

ts

1.1) Density

Future Works: Correlations

Thank you

Parameterisation of Urban Sprawl Amon Boontore. S p r a w l P l a n i m e t e r Slpanimeter +...

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