predicting urban growth on the atlantic coast using an integrative spatial modeling approach
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Predicting Urban Growth on the Atlantic Coast Using an Integrative Spatial Modeling Approach. Jeffery S. Allen and Kang Shou Lu Clemson University. Strom Thurmond Institute. Coastal Community Workshop, February 7, 2006, Charleston, SC. - PowerPoint PPT PresentationTRANSCRIPT
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!!!