1. Simulating Future Suburban Development in Connecticut Jason Parent, Daniel Civco, and James Hurd jason.parent@uconn.edu Center for Land Use Education and Research Dept. of Natural Resources Management and Engineering University of Connecticut

2. 2 Study Objectives ► ► Simulate suburban development over the next 30 years ► ► Analyze impact of simulated development on forest fragmentation

3. 3 The Study Area Salmon River Watershed

4. 4 Study Area Properties ► 150 sq. miles in area ► Heavily forested (approx. 72% in 2002) ► Population is growing  18.6% increase between 1990 and 2000 ► Urban and associated land cover is increasing  Urban land increase of 16.6% between 1985 and 2002  Turf / grass increase of 18.6% between 1985 and 2002

5. 5 General Approach ► Multi-Criteria Evaluation  create suitability maps ► Buildout Analysis  identify potential building sites ► TimeScope Analysis  assign build dates to potential building sites

6. 6 General Approach ► Buffer potential buildings  account for land cover change associated with building ► Update land cover map ► Forest Fragmentation Model (Riitters et al. 2000)  identify types of forest present with respect to fragmentation

7. 7 Multi-Criteria Evaluation ► Two categories (suitable, unsuitable) ► Grid cells have values of 0 or 1 ► 0 = feature present (unsuitable) ► 1 = feature absent (suitable) ► i.e. water ► More than two categories ► Grid cells have a range of values (criterion scores): 0 to 100 ► 100 = most suitable categories ► 0 = least suitable categories ► i.e. soil types Constraints Factors ► Based on grids depicting relevant criteria ► Two kinds of criteria: constraints and factors

8. 8 Multi-Criteria Evaluation Constraint Grids Wetlands (50’ buffer) Hydrography (50’ buffer) Floodzones (50’ buffer)

9. 9 Multi-Criteria Evaluation Constraint Grids Municipal Open space DEP land Slope > 20%

10. 10 Criterion scores systematically assigned to each soil type Initially assigned maximum scores (100) to each soil type Reduced score for negative properties of soil types hydric septic potentialmin. sloperockinessscore reduction nohigh < 8not rocky medium8 to 15 stony or rocky no low or very lowNA very stony or very rocky noextremely low > 15 extremely stony yesNA rock outcrop 0 10 20 30 100 Multi-Criteria Evaluation: Factors: Soil Types

11. 11 Shapefile depicting criterion scores for soil types Multi-Criteria Evaluation: Soil Factor

12. 12 Multi-Criteria Evaluation: Roads Factor Structures tend to be located within a certain range of distances from a road  Satisfy home owner preference  Reduce development costs  Mandatory setback Maximum development approximately 100 feet from the nearest road

13. 13 Multi-Criteria Evaluation: Roads Factor major roads Grid depicting criterion scores low high calculate % land developed in each class scale from 0 to 100 Map distances from roads Group into classes with 20’ intervals

14. 14 Multi-Criteria Evaluation: Calculation of Suitability Values Constraint 1 Constraint 2 Constraint 3 multiply binary raster format (unsuitable = 0) all constraints (unsuitable = 0) Factor 1 Factor 2 x weight 1 x weight 2 add weighted factor combination raster format; values range from 0 to 100 multiply suitability raster Sum of weights = 1

15. 15 Roads factor Soils factor Constraints (water, wetland) Suitability Map

16. 16 Multi-Criteria Evaluation: Suitability Map (Bolton) highly suitable unsuitable

17. 17 Buildout Analysis ► Community Viz’s Scenario 360 Buildout tool ► Places points at all potential future building locations  uses zoning information to determine lot size, building separation distance, etc.  excludes constraint areas from analysis  works with parcel data

18. 18 Buildout Analysis Constraints ► Unsuitable land  suitability value = 0 ► Fully developed parcels  Parcels containing a structure and less than 240,000 sq ft (6 builders’ acres) ► 50 ft buffer around existing structures

19. 19 Buildout Analysis Zoning Regulations Required zoning information:  Zone name  Minimum lot size (acres)  Building efficiency ► The percentage of available land that can be built upon  Efficiency less than 100% because of roads, open space requirements, etc.  Building separation distance ► Minimum distance between the center points of two buildings Zoning regulations for East Hampton

20. 20 Buildout Analysis Results

21. 21 TimeScope Analysis ► Community Viz’s Scenario 360 TimeScope tool ► Assigns a build date to each buildout “building”  Simulates the order in which building construction will occur over a specified period of time ► Based on parcel suitability  Building growth rate is specified by user ► For a given time step (i.e. year), the value of the current time step is assigned to:  A number of building locations, equal to the annual building growth rate  Building locations for which a build date has not already been assigned  Locations with the highest remaining suitability value

22. 22 TimeScope Analysis Building Growth Rates ► Building growth was assumed to parallel population growth ► Census data indicate that population growth has been linear over the past 40 years  Population extrapolated out to 2036 by linear regression of past census data

23. 23 TimeScope Analysis Building Growth Rates Gt =Gt =Gt =Gt = P t 2036 AtAtAtAt - H t 2004 2036 - 2004 G t = annual number of houses constructed P t 2036 = predicted population in 2036 A t = average number of people per house in 2000 H t 2004 = number of houses in 2004 Estimated Population and Building Growth

24. 24 TimeScope Analysis Results: Colchester

25. 25 TimeScope Analysis Results: Colchester

26. 26 Buildout Building Buffers

27. 27 Future Land Cover Maps ► Forecasted land cover for 2010, 2015, 2020, 2025, 2030, and 2036 ► 2002 land cover base map  Derived from Landsat satellite imagery ► Selected buffers, with the appropriate build dates, for each forecast year ► Land cover grid cells, within the selected buffers, were converted to urban land cover

28. 28 Future Land Cover Maps: Marlborough

29. 29 Forest Fragmentation Analysis ► Model developed by Riitters et al. (2000) ► Identifies forest grid cells as one of 5 types based on the percentage of forest grid cells and connectivity of forest grid cells in the surrounding area:  Interior: all surrounding grid cells are forest  Edge: grid cell is on the exterior edge of a forest tract  Perforated: the interior edge of forest tract  Transitional: about half of the surrounding grid cells are forest  Patch: less than 40% of surrounding grid cells are forest ► In this study, edge and perforated forest types were within 60 meters of the forest perimeter

30. 30 Forest Fragmentation Maps: East Haddam

31. 31 Changes Predicted to Occur, between 2002 and 2036, in Land Cover ► 3% of forest cover will be converted to non- forested land cover ► Urban land and associated turf will increase by approximately 18% ► Agricultural land will decline by approximately 5.6%

32. 32 Changes Predicted to Occur between 2002 and 2036 in Forest Fragmentation ► Interior forest will decline by 28% ► Perforated, transitional, and patch forest will increase by 67%, 10%, and 8% respectively ► Edge forest will decline by 15.5%

33. 33 Discussion ► ► Analysis does not account for road construction   Estimates of forest cover change are conservative   Perforated forest area is over-estimated while edge forest area is underestimated ► ► Building growth rates used in the TimeScope analysis are probably not applicable to non-residential zones   The effect in this study should be minimal since the towns had little non-residential area ► ► The analysis is applicable to regions in which the major forest fragmenting process is suburban development.

34. 34 Future Work ► Incorporate a model to predict road development ► Include socioeconomic data into the derivation of the suitability maps  Identify land availability ► Derive building growth rate estimates applicable to non-residential zones ► Compare of the effects of current zoning scenarios with low impact zoning scenarios

35. Simulating Future Suburban Development in Connecticut Jason Parent, Daniel Civco, and James Hurd jason.parent@uconn.edu Center for Land Use Education and Research Dept. of Natural Resources Management and Engineering University of Connecticut Questions?