Abstract
As urban areas continue to disperse and decentralize, new urban growth is increasingly occurring in peri-urban or rural areas beyond the suburban fringe, but within commuting distance of metropolitan areas. This trend is referred to in a variety of ways, including urban expansion, urban dispersion, or peri-urbanization. Many communities are concerned with seemingly uncontrolled urban sprawl and expansion into peri-urban areas for a variety of reasons, including the fiscal, environmental and social impacts associated with urban land-use change. Urbanization can alter major biogeochemical cycles, add or remove species, and have drastic effects on habitat (Vitousek et al. 1997), particularly when such development is low-density and scattered (Theobald 2004). Urban decentralization can also decimate the inner-city tax base (Downs 1999). Growth at the urban fringe, or in the rural portions of metropolitan counties, has greatly increased, and is of significantly lower density than the surrounding urbanized areas and clusters (Heimlich and Anderson, 2001). In Ohio, low-density development outside urbanized areas has increased from 58 to 72% of total land area between 1970 and 2000 (Partridge and Clark 2008).
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- 1.
There are two possible measurement errors that could be induced by this method: (1) multiple agricultural parcels were simultaneously converted within one subdivision; and (2) one agricultural parcel was subdivided to create more than one of the developed parcels not part of a subdivision. To the degree that the optimal development timing process considered the full spatial extent of the eventual subdivisions, problem (1) should not cause bias in the model coefficients. Problem (2) could potentially cause bias, but of unknown direction; because estimation was run on a spatially stratified sample, this potential bias was likely minimized.
- 2.
Fitting a model using only a sample of the data increases the risk that the estimated parameters are specific to the observations selected. Three distinct samples were initially drawn, and neither coefficients nor standard errors varied significantly. In addition, tests of leverage, i.e., for multivariate outliers, were also not significant.
- 3.
However, road improvements are unlikely to be independent of development risk: roads are more likely to be widened where prior growth has occurred.
References
Abbott RD (1985) Logistic regression in survival analysis. Am J Epidemiol 121:465–471
Allison PD (1982) Discrete-time methods for the analysis of event histories. In: Leinhardt S (ed) Sociological methods and research. Jossey-Bass, San Francisco, pp 61–98
Anas A, Arnott, R Small KA (1998) Urban spatial structure. J Econ Lit 36:1426–1464
An L, Brown DG (2008) Survival analysis in land change science: integrating with GIScience to address temporal complexities. Ann Assoc Am Geogr 98:323–344
Byun P, Esparza AX (2005) A revisionist model of suburbanization and sprawl: the role of political fragmentation, growth control, and spillovers. J Plann Educ Res 24:252–264
Campbell Jr, HS, Munroe DK (2007) Greenways and greenbacks: the impact of the Catawba regional trail on property values in Charlotte, North Carolina. SE Geogr 47:118–137
Capozza DR, Helsley RW (1989) The fundamentals of land prices and urban growth. J of Urban Econ 26(3):295–306
Carruthers J, Ulfarsson, G (2002) Fragmentation and sprawl: evidence from interregional analysis. Growth Change 33:312–340
Cavailhès J, Brossard T, Foltête J-C, Hilal M, Joly D, Torneux F-P, Tritz C, Wavresky P (2006) Seeing and being seen: a GIS-based hedonic price valuation of landscape. Presented at the 1ère Recontre du Longement, Marseille, Octobre 2006
Clark JK, McChesney R, Munroe DK, Irwin EG (2005) Spatial characteristics of exurban settlement pattern in the US. Paper prepared for the 52nd Annual North American Meetings of the Regional Science Association Las Vegas, NV, November 2005
Cox D (1972) Regression models and life tables. J Roy Stat Soc B 34:187–220
Cressie N (1993) Statistics for spatial data. Wiley, New York, NY
Downs A (1999) Some realities about sprawl and urban decline. Housing Policy Debate 10:955–974
Esparza AX, Carruthers JI (2000) Land use planning and exurbanization in the rural mountain West. J Plann Educ Res 20:23–36
Fleming M (2000) Spatial statistics and econometrics for models in fisheries economics: discussion. Am J Agr Econ 82:1207–1209
Heimlich R, Anderson WD (2001) Development at the urban fringe and beyond: impacts on agriculture and rural land. Agricultural Economic Report No 803, United States Department of Agriculture, Washington, DC
Hite D, Sohngen B, Templeton J (2003) Zoning, development timing, and agricultural land use at the suburban fringe: a competing risks approach. Agr Res Econ Rev 32:145–157
Irwin EG (2002) The effects of open space on residential property values. Land Econ 78:465–480
Irwin EG, Bockstael NE (2002) Interacting agents, spatial externalities and the evolution of residential land use patterns. J Econ Geogr 2:31–54
Irwin EG, Bockstael NE (2004) Endogenous spatial externalities: empirical evidence and implications for the evolution of exurban residential land use patterns. In: Anselin L, Florax RJGM, Rey SJ (eds) Advances in spatial econometrics: methodology, tools and applications. Springer, Berlin Heidelberg New York pp 359–380
Irwin EG, Geoghegan J (2001) Theory, data, methods: development spatially explicit economic models of land use change. Agr Ecosyst Environ 85:7–24
Irwin EG, Bell KP, Geoghegan J (2003) Modeling and managing urban growth at the rural-urban fringe: a parcel-level model of residential land use change. Agr Res Econ Rev 32:83–102
Lake IR, Lovett AA, Bateman IJ, Day B (2000) Using GIS and large-scale digital data to implement hedonic pricing studies. Int J Geogr Inform Sci 14:521–541
Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159–174
McCullagh P (1980) Regression models for ordinal data. J Roy Stat Soc B 42:109–142
McGarigal K, Cushman SA, Neel MC, Ene E (2002) FRAGSTATS: spatial pattern analysis program for categorical maps. Computer software program produced by the authors at the University of Massachusetts, Amherst
Mieskowski P, Mills E (1993) The causes of metropolitan suburbanization. J Econ Perspect 7:135–147
Munroe DK (2007) Exploring the determinants of spatial pattern in residential land markets: amenities and disamenities in Charlotte, NC, USA. Environ Plann B 34:336–354
Munroe DK, Müller D (2007) Issues in spatially explicit statistical land-use/cover change (LUCC) models: examples from western Honduras and the Central Highlands of Vietnam. Land Use Pol 24:521–530
Munroe DK, York AM (2003) Jobs, houses, and trees: changing regional structure, local land-use patterns, and forest cover in southern Indiana. Growth and Change 34:299–320
Parker DC, Meretsky V (2004) Measuring pattern outcomes in an agent-based model of edge-effect externalities using spatial metrics. Agr Ecosyst Environ 101:233–250
Partridge MD, Clark JK (2008) Our joint future: rural-urban interdependence in 21st Century Ohio. White Paper Prepared for the Brookings Institution, Greater Ohio
Partridge MD, Sharp JS, Clark JK (2007) Growth and change: population change in Ohio and its rural-urban interface. The Exurban Change Project and Swank Program in Rural-Urban Policy, Summary Report May 2007
Pontius Jr. RG (2002) Statistical methods to partition effects of quantity and location during comparison of categorical maps at multiple resolutions. Photogramm Eng Rem Sens 68:1041–1049
Steel S (1992) Farm markets mix entertainment, produce to lure customers. Columbus Dispatch, pp 2D
Theobald DV (2004) Placing exurban land-use change in a human modification framework. Front Ecol Environ 2:139–144
Vance C, Geoghegan J (2002) Temporal and spatial modeling of tropical deforestation: a survival analysis linking satellite and household survey data. Agr Econ 27:317–332
Veldkamp A, Lambin EF (2001) Predicting land-use change. Agr Ecosyst Environ 85:1–6
Verburg PH, van Eck JRR, de Nijs TCM, Dijst MJ, Schot P (2004) Determinants of land-use change patterns in the Netherlands. Environ Plann B 31:125–150
Vitousek PM, Mooney HA, Lubchenco J, Melillo JM (1997) Human domination of earth’s ecosystems. Science 277:494–499
Zhang T (2001) Community features and urban sprawl: the case of the Chicago metropolitan region. Land Use Pol 18:221–232
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Munroe, D.K. (2010). Pattern-Based Evaluation of Peri-Urban Development in Delaware County, Ohio, USA: Roads, Zoning and Spatial Externalities. In: Páez, A., Gallo, J., Buliung, R., Dall'erba, S. (eds) Progress in Spatial Analysis. Advances in Spatial Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03326-1_8
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