Demand for Open Space and Urban Sprawl: The Case of Knox County, Tennessee

  • Seong-Hoon ChoEmail author
  • Dayton M. Lambert
  • Roland K. Roberts
  • Seung Gyu Kim
Part of the Advances in Spatial Science book series (ADVSPATIAL)


Urban sprawl is often blamed for causing negative environmental effects from unsustainable land consumption and increased traffic congestion. While there is no generally accepted definition of urban sprawl, the process is well-described as the expansion of urban development into rural areas surrounding major cities, and the leapfrogging of development beyond the city’s outer boundary into smaller rural settlements (Hanham and Spiker 2005). Many studies have pointed toward the lifestyle choices of the economically affluent society for the rapid growth of urban sprawl (Brueckner 2000; Carruthers and Ulfarsson 2002; Frumkin 2002; Gordon and Richardson 1998, 2000, 2001a,b; Krieger 2005; Nechyba and Walsh 2004; Skaburskis 2000; Stone and Gibbins 2002). These lifestyle choices include preferences for larger homes and lot sizes, low density housing, mobility afforded by private vehicles, and the demand for open space. This kind of growth has raised concern about the potential negative impacts, especially the loss of benefits provided by farmland and open space, and higher costs of infrastructure and community services. Concerns about the negative consequences of urban sprawl have led local policymakers and nongovernmental activists to turn to urban and suburban open space conservation as potential mechanisms to counter urban sprawl. One example of these mechanisms includes “smart growth” policies. Smart growth policies are development initiatives that protect open space and farmland, revitalize communities, keep housing affordable, and provide more transportation choices (International City/County Management Association 2008). Local governments have incorporated “smart growth” principles designed to encourage compact development and preserve open space to curtail urban sprawl (Tracy 2003). Compact development is a key component of most smart growth policies. A large body of planning literature has addressed a variety of local strategies that are grouped under the rubric of “smart growth” (e.g., Blakely 1994; Daniels 2001; Handy 2005; Weitz 1999).


Open Space Geographically Weighted Regression Urban Sprawl Geographically Weighted Regression Model National Land Cover Database 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Acharya G, Bennett LL (2001) Valuing open space and land-use patterns in urban watersheds. J R Estate Finance Econ 22:221–237CrossRefGoogle Scholar
  2. Anselin L (1988) Spatial econometrics: methods and models. Kluwer, DordrechtGoogle Scholar
  3. Bates, LJ, Santerre RE (2001) The public demand for open space: The case of Connecticut communities. J Urban Econ 50:97–111CrossRefGoogle Scholar
  4. Bin O, Polasky S (2004) Effects of flood hazards on property values: evidence before and after Hurricane Floyd. Land Econ 80:490–500CrossRefGoogle Scholar
  5. Blaine TW, Lichtkoppler FR, Stanbro R (2003) An assessment of residents’ willingness to pay for green space and farmland preservation conservation easements using the contingent valuation method (CVM). J Ext 41 Available online:, 1 Oct. 2009
  6. Blakely EJ (1994) Planning local economic development: Theory and practice, 2nd edn. SAGE, LondonGoogle Scholar
  7. Breffle W, Morey E, Lodder T (1998) Using contingent valuation to estimate a neighborhood’s willingness to pay to preserve undeveloped urban land. Urban Stud 35:715–727CrossRefGoogle Scholar
  8. Brueckner JK (2000) Urban sprawl: diagnosis and remedies. Int Region Sci Rev 23:160–171CrossRefGoogle Scholar
  9. Brunsdon C, Fotheringham A, Charlton M (1996) Geographically weighted regression: a method for exploring spatial nonstationarity. Geogr Anal 28:281–298CrossRefGoogle Scholar
  10. Carruthers JI, Ulfarsson GF (2002) Fragmentation and sprawl: evidence from interregional analysis. Growth Change 33:312–340CrossRefGoogle Scholar
  11. Cho S, Clark CD, Park WM (2006) Two dimensions of the spatial distribution of housing: dependency and heterogeneity across Tennessee’s six metropolitan statistical areas. J Agr Appl Econ 38:299–316Google Scholar
  12. Cho S, Roberts RK (2007) Cure for urban sprawl: measuring the ratio of marginal implicit prices of density-to-lot-size. Rev Agr Econ 29:572–579CrossRefGoogle Scholar
  13. Cummings RO, Taylor LO (1999) Unbiased value estimates for environmental goods: a cheap talk design for the contingent valuation method. Am Econ Rev 89:649–665CrossRefGoogle Scholar
  14. Daniels T (2001) Smart growth: a new American approach to regional planning. Plann Pract Res 16:271–279CrossRefGoogle Scholar
  15. Dusansky R, Koc C, Onur I (2004) Is the demand curve for housing upward sloping? Working paper. Department of Economics/University of Texas at AustinGoogle Scholar
  16. ESRI (2004) ESRI Data & Maps 2004., 1 Oct. 2009.
  17. Ewing R, Pendall K, Chen D (2002) Measuring sprawl and its impact. Smart Growth America, Washington, DCGoogle Scholar
  18. Flores NE, Carson RT (1997) The relationship between the income elasticities of demand and willingness to pay. J Environ Econ Manage 33:287–295CrossRefGoogle Scholar
  19. Fotheringham AS, Brunsdon C, Charlton M (2002) Geographically weighted regression: the analysis of spatially varying relationships. Wiley, New JerseyGoogle Scholar
  20. Frumkin H (2002) Urban sprawl and public health. Publ Health Re 117:201–217Google Scholar
  21. Geoghegan J, Lynch L, Bucholtz S (2003) Capitalization of open spaces into housing values and the residential property tax revenue impacts of agricultural easement programs. Agr Res Econ Rev 32:33–45Google Scholar
  22. Gordon P, Richardson HW (1998) Prove it. Brookings Rev 16:23–26CrossRefGoogle Scholar
  23. Gordon P, Richardson HW (2000) Critiquing sprawl’s critics. Policy Analysis No. 365, January 24Google Scholar
  24. Gordon P, Richardson HW (2001a) Transportation and land use. Chapter 3 In: Holcombe R, Staley S (eds) Smarter growth: market-based strategies for land use planning in the 21st century. Greenwood Press, Westport, CTGoogle Scholar
  25. Gordon P, Richardson HW (2001b) The sprawl debate: let markets plan. Publius J Federalism 31:131–149CrossRefGoogle Scholar
  26. Gujarati D (1995) Basic Econometrics, 3rd edn. McGraw-Hill, New YorkGoogle Scholar
  27. Handy S (2005) Smart growth and the transportation-land use connection: what does the research tell us? Int Region Sci Rev 28:146–167CrossRefGoogle Scholar
  28. Hanham R, Spiker JS (2005) Urban sprawl detection using satellite imagery and geographically weighted regression. In: Geospatial technologies in urban economics. Springer, Berlinthebe, pp 137–151Google Scholar
  29. International City /County Management Association (2008), 1 Oct. 2009
  30. Irwin EG (2002) The effects of open space on residential property values. Land Econ 78:465–80CrossRefGoogle Scholar
  31. Irwin EG, Bockstael NE (2001) The problem of identifying land use spillovers: Measuring the effects of open space on residential property values. Am J Agr Econ 83:698–704CrossRefGoogle Scholar
  32. Iwata S, Murao H, Wang Q (2000) Nonparametric assessment of the effect of neighborhood land uses on residential house values. In: Thomas F, Hill RC (eds) Advances in econometrics: applying kernel and nonparametric estimation to economic topics. JAI Press, Stamford, CT, pp 229–257Google Scholar
  33. Kelejian HH, Prucha IR (1998) A generalized spatial two-stage least squares procedure for estimating a spatial autoregressive model with autoregressive disturbances. J R Estate Finance Econ 17:99–121CrossRefGoogle Scholar
  34. KGIS (2009) Knox net where. Knoxville, Knox County, Knoxville Utilities Board Geographic Information System., 1 Oct. 2009
  35. Krieger A (2005) The costs – And benefits? – of sprawl. In Saunders WS (ed) Sprawl and suburbia. University of Minnesota Press, Minneapolis, pp 44–56Google Scholar
  36. Lichtenberg E, Tra C, Hardie I (2007) Land use regulation and the provision of open space in suburban residential subdivisions. J Environ Econ Manage 54:199–213CrossRefGoogle Scholar
  37. Maddala GS (1983) Limited dependent and qualitative variables in econometrics. Cambridge University Press, New YorkCrossRefGoogle Scholar
  38. Maddala GS (1992) Introduction to econometrics. Prentice Hall, Upper Saddle River, NJGoogle Scholar
  39. Mahan BL, Polasky S, Adams RM (2000) Valuing urban wetlands: A property price approach. Land Econ 76:100–113CrossRefGoogle Scholar
  40. McConnell V, Walls M (2005) The value of open space: Evidence from studies of non-market benefits. Working Paper, Resources for the Future, Washington DCGoogle Scholar
  41. MPC (2001) Metropolitan Planning Commission. Tennessee public chapter 1101: growth plan for knoxville, Knox County, and Farragut, Tennessee.
  42. Nechyba TJ, Walsh RP (2004) Urban sprawl. J Econ Perspect 18:177–200CrossRefGoogle Scholar
  43. Nelson N, Kramer E, Dorfman J, Bumback B (2004) Estimating the economic benefit of landscape pattern: an hedonic analysis of spatial landscape indices. Institute of Ecology, The University of Georgia, Athens, GA. Available online at, 1 Oct. 2009
  44. NLCD (2001) National Land Cover Database 2001., 1 Oct. 2009
  45. OFHEO (2006) Office of federal housing enterprise oversight., 1 Oct. 2009
  46. Open Space Inventory (1999) State of New York., 1 Oct. 2009
  47. Rosenberger RS, Walsh RG (1997) Nonmarket value of western valley. Ranchland using contingent valuation. J Agr Res Eco 22:296–309Google Scholar
  48. Skaburskis A (2000) Housing prices and housing density: Do higher prices make cities more compact? Can J Reg Sci 23:455–487Google Scholar
  49. Sorg CF, Loomis JB, Donnelly DM, Peterson GL, Nelson LJ (1985) Net economic value of cold and warm water fishing in Idaho. USDA Forest Service, Resource Bulletin RM–11, p 26Google Scholar
  50. Stevens T (1990) The economic value of bald eagles, wild turkeys, Atlantic salmon, and coyotes in New England. Resources and Environment: Management Choices. November report. Department of Resource Economics, University of Massachusetts, AmherstGoogle Scholar
  51. Stone L, Gibbins R. (2002) Tightening our beltways: urban sprawl in western Canada. A Western Cities Project Discussion Paper, the Canada West foundation, October 2002Google Scholar
  52. Thorsnes P (2002) The value of a suburban forest preserve: Estimates from sales of vacant residential building lots. Land Econ 78:426–441CrossRefGoogle Scholar
  53. Tracy S (2003) Smart Growth Zoning Codes: A Resource Guide. Local Government CommissionGoogle Scholar
  54. Tyrväinen L, Väänänen H (1998) The economic value of urban forest amenities: an application of the contingent valuation method. Landsc Urban Plann 43:105–118CrossRefGoogle Scholar
  55. US Census Bureau (2002) Census 2000 Summary File 1 (Sf 1) 100-percent data, Tables pctl2 and pctl2b., Oct 1, 2009.
  56. Walsh R (2007) Endogenous open space amenities in a locational equilibrium. J Urban Econ 61:319–344CrossRefGoogle Scholar
  57. Weitz J (1999) From quiet revolution to smart growth: atate growth management programs, 1960 to 1999. J Plann Lit 14:266–337CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Seong-Hoon Cho
    • 1
    Email author
  • Dayton M. Lambert
  • Roland K. Roberts
  • Seung Gyu Kim
  1. 1.Department of Agricultural EconomicsUniversity of TennesseeKnoxvilleUSA

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