Predicting Urban Growth on the Atlantic Coast Using an Integrative Spatial

Modeling Approach

Jeffery S. Allen and Kang Shou LuClemson University

Strom Thurmond Institute

Coastal Community Workshop, February 7, 2006, Charleston, SC

Population Change in South Carolina Coastal Counties from 1970 - 2000.

County Population 1970 Population 1990 Population 2000Beaufort 51,136 86,425 120,937Berkeley 56,199 128,776 142,651Charleston 247,650 295,039 309,969Colleton 27,622 34,377 38,264Dorchester 32,276 83,060 96,413Georgetown 33,500 46,302 55,797Horry 69,992 144,053 196,629Jasper 11,885 15,487 20,678

South Carolina 2,590,713 3,486,703 4,012,012

Population density map for North Carolina, South Carolina, and Georgia

# of People Per Square Mile*

> 800

400 - 800

200 - 400

100 - 200

0 - 100

* 1999 population estimates by CACI International, Inc. based on 1990 US Census

5.3%

30.2%

0%5%

10%15%20%25%30%35%

South Carolina: Comparison of Population Growth to Increase in Developed Land 1992-97

Developed Land

Population

Source: (London and Hill, 2000) -- USDA, US Census Bureau and Jim Self Center on the Future, Clemson University.

1 1 3 4

29

1 1 6 1 4 3 4 1 1 4 3 5 10 7 211 7 8 6 5

15 13 17 1421 17 22 18

45

24

44

58 60

82

100

70

56

94

78

129

171176

333

224233

203

272

244

86

325

115

2

0

50

100

150

200

250

300

350

The total number of parcels is 4107 of which 618 parcels have no transaction date and were thus excluded from the above chart.

Calculated using only the data for years with at least one parcel transaction. 30 of 73 years during 1908-1981 have no transaction at all.

Number of Parcel Transactions

Year

Land (Parcel) Transaction in Murrells Inlet, 1908-1996

Charleston Area Urban Extent 1973

Charleston Area Urban Extent 1994

1. Components or structures of the land use systems:simple vs. complex2. Relationships between components, agents, factors, and processes:

deterministic vs. indeterministic.3. Changes over space (and time): ordered vs. random vs. chaotic4. Spatial distribution or patterns: regularity vs. irregularity (fractal)

Challenges Faced in Urban Land Use Modeling

Land

Land Use Systems

Uses

Economic SocialCultural

•Natural resources•Activity settings•Aesthetic sanities •Natural functions

•Functions•Structures•Activities•Ownership•Use status

GeologyGeomorphologyHydrologyClimateSoilVegetation

Human Systems

Physical Systems

•Availability•Suitability•Capacity•Sustainability

Model vs. Reality

Year

Population Growth (1973-1994)

Change in Per Capita Urban Area (1973-1994)

Urban Growth (1973-1994)

Year

Year

Po

pula

tion

(in T

hou

than

ds)

540520500480460440420400380360340320

Urb

an A

rea

(in

Squ

are

Mile

s)U

rban

Are

a (i

n S

qua

re F

eet

per

Pe

rson

)

Population : 339287 Persons in 1973 532688 Persons in 1994Net Growth: 192601 personsAverage Net Growth: 9000 Persons per YearAnnual Growth Rate: 2%Years Taken for Double: 34

Urban Area: 70.36 Square Miles in 1973 250.07 Square Miles in 1994Net Growth: 179.61 Square MilesAverage Annual Net Growth: 8.59 Square Miles Annual Growth Rate: 7%Years Taken for Double: 10

Urban Area: 5790 Square Feet in 1973 13087 Square Feet in 1994Net Change: 7297 Square FeetAverage Annual Net Change: 347 Square Feet Annual Change Rate: 4%Years Taken for Double: 18

8060

260

240

220

200

180

160

140

120

100

5000

6000

7000

8000

9000

10000

11000

12000

13000

14000

Urban Area Growth by 256%

Urban Area Growth vs. Population Growth in the Charleston Area, 1973-1994

Per Capita Urban Area Consumption (128%)

Growth Ratio (Sprawl Index) = --------- = 6.22 : 1

256%

41%

Population Growth by 41%

Parcel--smallest legal unit

Zone--area demarcated by the major roads

Grid or Cell--square-shaped area

Murrells Inlet

Mount Pleasant

Part of Mount Pleasant

Analysis Units

---200x200 m2 grids (cells) for calibrating models---30x30 m2 grids (cells) for prediction

Examples of Predictor Variables

Population Density

Protected Land

Wetland

Slope

Cost Dista

nce Previous Urban

Roads

Water Lines

0 1

Urban Transition Probability

Water

Urban-Land Transition Probabilities

Logistic Regression Prediction

Integrated GIS Prediction

Focus Group Prediction Rule-Based Prediction

Comparison ofPredicted Results of

Four Models

Urban 1973

Urban 1994Urban 2030Non-Urban 2030WaterInterstate HwySecondary Hwy

Region-Level (COG) Growth Simulation

BCD Region: Ratio 5:1

Growth Scenarios: Ratios 1:1 – 6:1

Resources at Risk by 2030

• Cultivated Agriculture - 57%

• Freshwater Wetlands - 35%

• Tidal Creeks - 41%

• Cultural/Historic Sites - 57%

• Archaeological Sites - 36%

Urban Growth Problems

Uncontrolled growth - urban sprawl results in many problems such as:

Increased cost of living Rising taxes and pressure on infrastructure and urban services Traffic congestion and increased (travel) time Environmental pollution/degradation Loss of farm/forest land, habitats and rural (natural) landscape Downtown declines and community segregation Increased dependence on the automobile Loss of sense of place - undifferentiated landscape

Benefits of Urban Growth

Increased standard of living Generation of wealth Increase in amenities Production of affordable housing Increase in tax base New business opportunities New job opportunities Increased “freedom” with the automobile It is what we desire - “Freedom of Choice”

What do we do now?

Growth is coming whether we want it or not Determine where we do not want to grow Increase communication among SPD’s, etc. Be inclusive in planning Provide incentives for growth in “growth areas” Provide “dis-incentives” for areas to protect Make users pay the freight for new growth It is always easier said than done!!!