Examining the Impact of Environmental Factors on Quality of Life Across Massachusetts

Professional Geographer

Volumn 65, Issue 2, 2013, Pages 187-204

  Ogneva Himmelberger, Yelena ^a   Rakshit, Rahul ^a   Pearsall, Hamil ^a  

^a CLARK UNIVERSITY   (United States)

Author keywords

data envelopment analysis; geographically weighted regression; Massachusetts; quality of life; socioeconomic conditions

Indexed keywords

DATA ENVELOPMENT ANALYSIS; ENVIRONMENTAL FACTOR; ENVIRONMENTAL IMPACT; PRINCIPAL COMPONENT ANALYSIS; QUALITY OF LIFE; SOCIOECONOMIC CONDITIONS; SPATIAL VARIATION; URBAN AREA; VEGETATION;

MASSACHUSETTS; UNITED STATES;

EID: 84875337596     PISSN: 00330124     EISSN: 14679272     Source Type: Journal    
DOI: 10.1080/00330124.2011.639631     Document Type: Article

References (60)

1. Anselin, L. 1995. Local indicators of spatial association-LISA. Geographical Analysis, 27(2): 93-115.
2. Bark-Hodgins, R. H., Osgood, D. E. and Colby, B. G. 2006. "Remotely sensed proxies for environmental amenities in hedonic analysis: What does green mean?". In Environmental valuation: Intraregional and interregional perspective, Edited by: Carruthers, J. I. and Mundy, B. 191-210. Farnham, UK: Ashgate.
3. Berry, B. and Horton, F. 1970. Geographic perspectives on urban systems., Englewood Cliffs, NJ: Prentice-Hall.
4. Berry, B. and Kasarda, J. D. 1977. Contemporary urban ecology, New York: Macmillan.
5. Bickford, S. A. and Laffan, S. W. 2006. Multi-extent analysis of the relationship between pteridophyte species richness and climate. Global Ecology and Biogeography, 15(6): 588-601.
6. Booysen, F. 2002. An overview and evaluation of composite indices of development. Social Indicators Research, 59: 115-51.
7. Brunsdon, C., McClatchey, J. and Unwin, D. J. 2001. Spatial variations in the average rainfall-altitude relationship in Great Britain: An approach using geographically weighted regression. International Journal of Climatology, 21(4): 455-66.
8. Carruthers, J. I. and Mulligan, G. F. 2009. The "plane of living" and the recent evolution of housing values in the United States. HUD Economic Development and Public Finance Working Paper No. REP 09-01, Washington, DC: Department of Housing and Urban Development. http://www.huduser.org/portal/publications/pdf/jic_gfm_rep_0901.pdf (last accessed 5 August 2011)
9. Cutter, S. 1986. Changes in interstate rankings 1931-1980. Geographical Review, 76: 276-87.
10. Diamond, D. B. and Tolley, G. S. 1982. "The economic roles of urban amenities". In The economics of urban amenities, Edited by: Diamond, D. B. and Tolley, G. S. 3-54. New York: Academic Press.
11. Diener, E. and Suh, E. 1997. Measuring quality of life: Economic, social, and subjective indicators. Social Indicators Research, 40(1): 189-216.
12. Dutch National Institute for Public Health and the Environment (RIVM). 2000. Nationale Milieu Verkenningen [National Outlook], Amsterdam, The Netherlands: RIVM.
13. ESRI. 2009. ArcMap 9.3, Redlands, CA: Environmental Systems Research Institute.
14. Executive Office of Transportation. 2009. Road inventory downloads. http://www.eot.state.ma.us/default.asp?pgid=content/plan02&sid=about (last accessed 5 January 2011)
15. Foody, G. M. 2003. Geographical weighting as a further refinement to regression modelling: An example focused on the NDVI-rainfall relationship. Remote Sensing of Environment, 88(3): 283-93.
16. Foody, G. M. 2004. Spatial nonstationarity and scale-dependency in the relationship between species richness and environmental determinants for the sub-Saharan endemic avifauna. Global Ecology & Biogeography, 13(4): 315-20.
17. Fotheringham, A. S., Brunsdon, C. and Charlton, M. 2002. Geographically weighted regression: The analysis of spatially varying relationships., New York: Wiley.
18. Fotheringham, A. S., Charlton, M. and Brunsdon, C. 1996. The geography of parameter space: An investigation into spatial nonstationarity. International Journal of GIS, 10: 605-27.
19. Fotheringham, A. S., Charlton, M. and Brunsdon, C. 2001. Spatial variations in school performance: A local analysis using geographically weighted regression. Geographical and Environmental Modelling, 5(1): 43-66.
20. Glaeser, E. and Gottlieb, J. 2006. Urban resurgence and the consumer city. Urban Studies, 43(8): 1275-99.
21. Glaeser, E., Kolko, J. and Saiz, A. 2001. Consumer city. Journal of Economic Geography, 1(1): 27-50.
22. Glaeser, E. and Redlick, C. 2009. Social capital and urban growth. International Regional Science Review, 32(3): 264-99.
23. Griffith, D. 2008. Spatial-filtering-based contributions to a critique of geographically weighted regression (GWR). Environment and Planning A, 40: 2751-69.
24. Grove, J. M., Cadenasso, M. L., Burch, W. R. Jr., Pickett, S. T., Schwarz, K. and O'Neil-Dunne, J. 2006. Data and methods comparing social structure and vegetation structure of urban neighborhoods in Baltimore, Maryland. Society & Natural Resources, 19(2): 117-36.
25. Haining, R. 2003. Spatial data analysis: Theory and practice., New York: Cambridge University Press.
26. Jensen, R. R. and Binford, M. W. 2004. Measurement and comparison of Leaf Area Index estimators derived from satellite remote sensing techniques. International Journal of Remote Sensing, 25(20): 4251-65.
27. Kaiser, H. F. 1960. The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20: 141-51.
28. Kupfer, J. A. and Farris, C. A. 2007. Incorporating spatial non-stationarity of regression coefficients into predictive vegetation models. Landscape Ecology, 22(6): 837-52.
29. Lafary, E. W., Gatrell, J. D. and Jensen, R. R. 2008. People, pixels and weights in Vanderburgh County, Indiana: Toward a new urban geography of human-environment interactions. Geocarto International, 23(1): 53-66.
30. Li, G. and Weng, Q. 2007. Measuring the quality of life in city of Indianapolis by integration of remote sensing and census data. International Journal of Remote Sensing, 28(2): 249-67.
31. Lo, C. P. and Faber, B. J. 1997. Integration of Landsat thematic mapper and census data for quality of life assessment. Remote Sensing of the Environment, 62(2): 143-57.
32. MassGIS. 2011. Office of Geographic and Environmental Information (MassGIS). http://www.mass.gov/mgis/laylist.htm (last accessed 10 January 2011)
33. McGranahan, D. 1999. Natural amenities drive rural population change. Agricultural Economic Report No. AER781. Economic Research Service, U.S. Department of Agriculture. http://www.ers.usda.gov/Publications/AER781/ (last accessed 5 August 2011)
34. Morrill, R. L. and Wohlenberg, E. H. 1971. The geography of poverty in the United States, New York: McGraw-Hill.
35. Mulligan, G. and Burke, R. 2002. Quality of life in the US states: 1970 and 2000. Association of Pacific Geographers Yearbook, 64: 73-97.
36. Mulligan, G., Carruthers, J. and Cahill, M. 2004. "Urban quality of life and public policy: A survey". In Urban dynamics and growth: Advances in urban economics, Edited by: Capello, R. and Nijkamp, P. 729-802. Amsterdam: Elsevier.
37. Nichol, J. E. and Wong, M. S. 2006. "Assessing urban environmental quality with multiple parameters". In Urban remote sensing, Edited by: Weng, Q. and Quattrochi, D. 253-68. London and New York: CRC Press, Taylor & Francis Group.
38. Ogneva-Himmelberger, Y., Pearsall, H. and Rakshit, R. 2009. Concrete evidence & geographically weighted regression: A regional analysis of wealth and the land cover in Massachusetts. Applied Geography, 29: 478-87.
39. Osborne, P., Foody, G. and Suarez-Seoane, S. 2007. Non-stationarity and local approaches to modelling the distributions of wildfire. Diversity and Distributions, 13: 313-23.
40. Pacione, M. 2003. Urban environmental quality and human wellbeing-A social geographical perspective. Landscape and Urban Planning, 65(1-2): 19-30.
41. Paragon Decision Technology. 2011. Advanced Interactive Multidimensional Modeling System (AIMMS), Bellevue, WA: Paragon Decision Technology.
42. Ratick, S., Morehouse, H. and Klimberg, R. 2009. Creating an index of vulnerability to severe coastal storms along the North Shore of Boston: Financial modeling applications and data envelopment applications. Applications of Management Science, 13: 143-78.
43. Smith, D. M. 1973. The geography of social well-being in the United States., New York: McGraw-Hill.
44. Smith, D. M. 1977. Human geography: A welfare approach., London: Edward Arnold.
45. Smith, D. M. 1994. Geography and social justice., Cambridge, MA: Blackwell.
46. SPSS. 2007. SPSS Base 16.0, Chicago, IL: SPSS, Inc.
47. Stathopoulou, M. and Cartalis, C. Mapping quality of life in metropolitan Athens using satellite and census data. Paper presented at 1st EARSeL Workshop of the SIG Urban Remote Sensing. Berlin.
48. Thorndike, E. L. 1939. Your city., New York: Harcourt, Brace.
49. Tu, J. and Xia, Z. G. 2008. Examining spatially varying relationships between land use and water quality using geographically weighted regression I: Model design and evaluation. Science of the Total Environment, 407(1): 358-78.
50. U.S. Census Bureau. 2010. "American FactFinder". http://factfinder.census.gov/home/saff/main.html?_lang=en (last accessed 10 January 2011)
51. van Kamp, I, Leidelmeijer, K., Marsman, G. and de Hollander, A. 2003. Urban environmental quality and human well-being: Towards a conceptual framework and demarcation of concepts; a literature study. Landscape and Urban Planning, 65(1-2): 5-18.
52. Vigdor, J. 2002. Does gentrification harm the poor?. Brookings-Wharton Papers on Urban Affairs, 2002: 133-82.
53. Waller, L., Zhu, L., Gotway, C., Gorman, D. and Gruenewald, P. 2007. Quantifying geographic variations in associations between alcohol distribution and violence: A comparison of geographically weighted regression and spatially varying coefficient models. Stochastic Environmental Research and Risk Assessment, 21(5): 573-88.
54. Wheeler, D. and Tiefelsdorf, M. 2005. Multicollinearity and correlation among local regression coefficients in geographically weighted regression. Journal of Geographical Systems, 7: 161-87.
55. Whisler, R. L., Waldorf, B. S., Mulligan, G. F. and Plane, D. 2008. Quality of life and the migration of the college-educated: A life-course approach. Growth and Change, 39(1): 58-94.
56. Withers, S. D. and Clark, W. 2006. Housing costs and the geography of family migration outcomes. Population, Space and Place, 12: 273-89.
57. Yu, D. L. 2006. Spatially varying development mechanisms in the greater Beijing area: A geographically weighted regression investigation. Annals of Regional Science, 40: 173-90.
58. Yu, D. L. and Wu, C. 2004. Understanding population segregation from Landsat ETM+ imagery: A geographically weighted regression approach. Geoscience and Remote Sensing, 41(3): 187-206.
59. Zhou, P., Ang, B. W. and Poh, K. L. 2006. Comparing aggregating methods for constructing the composite environmental index: An objective measure. Ecological Economics, 59: 305-11.
60. Zhou, P., Ang, B. W. and Zhou, D. Q. 2010. Weighting and aggregation in composite indicator construction: A multiplicative optimization approach. Social Indicators Research, 96(1): 169-81.