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Model-Based Clustering of Social Vulnerability to Urban Extreme Heat Events

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Geographic Information Science (GIScience 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9927))

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Abstract

Geodemographic classification methods are applied to Denver Colorado to develop a typology of social vulnerability to heat exposure. Environmental hazards are known to exhibit biophysical variations (e.g., land cover and housing characteristics) and social variations (e.g., demographic and economic adaptations to heat mitigation). Geodemographic model-based classification permits a more extensive set of input variables, with richer attributions; and it can account for spatial context on variable interactions. Additionally, it generates comparative assessments of environmental stress on multiple demographic groups. The paper emphasizes performance of model-based clustering in geodemographic analysis, describing two stages of classification analysis. In so doing, this research examines ways in which high heat exposure intersects with socioecological variation to drive social vulnerability during extreme heat events. The first stage classifies tract-level variables for social and biophysical stressors. Membership probabilities from the initial (baseline) classification are then input to a second classification that integrates the biophysical and social domains within a membership probability space to form a final place typology. Final place categories are compared to three broad land surface temperature (LST) regimes derived from simple clustering of mean daytime and nighttime land surface temperatures. The results point to several broad considerations for heat mitigation planning that are aligned with extant research on urban heat vulnerability. However, the relative coarseness of the classification structure also reveals a need for further investigation of the internal structure of each class, as well as aggregation effects, in future studies.

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References

  1. Adger, W.N.: Vulnerability. Glob. Environ. Change 16(3), 268–281 (2006)

    Article  Google Scholar 

  2. Andrews, J.L., McNicholas, P.D.: tEIGEN: model-based clustering and classification with the multivariate t-distribution, 2015, r package version 2

    Google Scholar 

  3. Brown, M.C.: Using Gini-style indices to evaluate the spatial patterns of health practitioners: theoretical considerations and an application based on alberta data. Soc. Sci. Med. 38(9), 1243–1256 (1994)

    Article  Google Scholar 

  4. Buyantuyev, A., Wu, J.: Urban heat islands and landscape heterogeneity: linking spatiotemporal variations in surface temperatures to land-cover and socioeconomic patterns. Landscape Ecol. 25(1), 17–33 (2010)

    Article  Google Scholar 

  5. Cutter, S.L., Boruff, B.J., Shirley, W.L.: Social vulnerability to environmental hazards*. Soc. Sci. Q. 84(2), 242–261 (2003)

    Article  Google Scholar 

  6. Declet-Barreto, J., Brazel, A.J., Martin, C.A., Chow, W.T., Harlan, S.L.: Creating the park cool Island in an inner-city neighborhood: heat mitigation strategy for Phoenix, AZ. Urban Ecosyst. 16(3), 617–635 (2013)

    Article  Google Scholar 

  7. Fraley, C., Raftery, A.E.: Model-based clustering, discriminant analysis, and density estimation. J. Am. Stat. Assoc. 97(458), 611–631 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  8. Gallopín, G.C.: Linkages between vulnerability, resilience, and adaptive capacity. Glob. Environ. Change 16(3), 293–303 (2006)

    Article  Google Scholar 

  9. Guhathakurta, S., Gober, P.: The impact of the Phoenix urban heat Island on residential water use. J. Am. Plan. Assoc. 73(3), 317–329 (2007)

    Article  Google Scholar 

  10. Harlan, S.L., Brazel, A.J., Prashad, L., Stefanov, W.L., Larsen, L.: Neighborhood microclimates and vulnerability to heat stress. Soc. Sci. Med. 63(11), 2847–2863 (2006)

    Article  Google Scholar 

  11. Harlan, S.L., Declet-Barreto, J.H., Stefanov, W.L., Petitti, D.B.: Neighborhood effects on heat deaths: social and environmental predictors of vulnerability in Maricopa County, Arizona. Environ. Health Perspect. (Online) 121(2), 197 (2013)

    Google Scholar 

  12. Jenerette, G.D., Harlan, S.L., Brazel, A., Jones, N., Larsen, L., Stefanov, W.L.: Regional relationships between surface temperature, vegetation, and human settlement in a rapidly urbanizing ecosystem. Landscape Ecol. 22(3), 353–365 (2007)

    Article  Google Scholar 

  13. Jenerette, G.D., Harlan, S.L., Stefanov, W.L., Martin, C.A.: Ecosystem services and urban heat riskscape moderation: water, green spaces, and social inequality in Phoenix, USA. Ecol. Appl. 21(7), 2637–2651 (2011)

    Article  Google Scholar 

  14. Jesdale, B.M., Morello-Frosch, R., Cushing, L.: The racial/ethnic distribution of heat risk-related land cover in relation to residential segregation. Environ. Health Perspect. (Online) 121(7), 811 (2013)

    Article  Google Scholar 

  15. Johnson, D.P., Stanforth, A., Lulla, V., Luber, G.: Developing an applied extreme heat vulnerability index utilizing socioeconomic and environmental data. Appl. Geogr. 35(1), 23–31 (2012)

    Article  Google Scholar 

  16. Lam, N.S., Reams, M., Li, K., Li, C., Mata, L.P.: Measuring community resilience to coastal hazards along the Northern Gulf of Mexico. Nat. Hazards Rev. 17(1), 1–12 (2015). Article ID 04015013

    Google Scholar 

  17. Maier, G., Grundstein, A., Jang, W., Li, C., Naeher, L.P., Shepherd, M.: Assessing the performance of a vulnerability index during oppressive heat across Georgia, United States. Weather, Clim. Soc. 6(2), 253–263 (2014)

    Article  Google Scholar 

  18. Morrow, B.H.: Identifying and mapping community vulnerability. Disasters 23(1), 1–18 (1999)

    Article  Google Scholar 

  19. Nguyen, J.L., Schwartz, J., Dockery, D.W.: The relationship between indoor and outdoor temperature, apparent temperature, relative humidity, and absolute humidity. Indoor Air 24(1), 103–112 (2014)

    Article  Google Scholar 

  20. Polsky, C., Neff, R., Yarnal, B.: Building comparable global change vulnerability assessments: the vulnerability scoping diagram. Glob. Environ. Change 17(3), 472–485 (2007)

    Article  Google Scholar 

  21. Quinn, A., Tamerius, J.D., Perzanowski, M., Jacobson, J.S., Goldstein, I., Acosta, L., Shaman, J.: Predicting indoor heat exposure risk during extreme heat events. Sci. Total Environ. 490, 686–693 (2014)

    Article  Google Scholar 

  22. Reid, C.E., Mann, J.K., Alfasso, R., English, P.B., King, G.C., Lincoln, R.A., Margolis, H.G., Rubado, D.J., Sabato, J.E., West, N.L., et al.: Evaluation of a heat vulnerability index on abnormally hot days: an environmental public health tracking study. Environ. Health Perspect. 120(5), 715 (2012)

    Article  Google Scholar 

  23. Reid, C.E., O’Neill, M.S., Gronlund, C.J., Brines, S.J., Brown, D.G., Diez-Roux, A.V., Schwartz, J.: Mapping community determinants of heat vulnerability. Environ. Health Perspect. 117(11), 1730 (2009)

    Google Scholar 

  24. Rosenthal, J.K., Kinney, P.L., Metzger, K.B.: Intra-urban vulnerability to heat-related mortality in New York City, 1997–2006. Health Place 30, 45–60 (2014)

    Article  Google Scholar 

  25. Rufat, S.: Spectroscopy of urban vulnerability. Ann. Assoc. Am. Geogr. 103(3), 505–525 (2013)

    Article  Google Scholar 

  26. Shiu-Thornton, S., Balabis, J., Senturia, K., Tamayo, A., Oberle, M.: Disaster preparedness for limited english proficient communities: medical interpreters as cultural brokers and gatekeepers. Publ. Health Rep. 122(4), 466–471 (2007)

    Google Scholar 

  27. Smit, B., Wandel, J.: Adaptation, adaptive capacity and vulnerability. Glob. Environ. Change 16(3), 282–292 (2006)

    Article  Google Scholar 

  28. Spielman, S.E., Singleton, A.: Studying neighborhoods using uncertain data from the American community survey: a contextual approach. Ann. Assoc. Am. Geogr. 105(5), 1003–1025 (2015)

    Article  Google Scholar 

  29. Stone, B., Hess, J.J., Frumkin, H., et al.: Urban form and extreme heat events: are sprawling cities more vulnerable to climate change than compact cities. Environ. Health Perspect. 118(10), 1425–1428 (2010)

    Article  Google Scholar 

  30. Turner, B.L., Kasperson, R.E., Matson, P.A., McCarthy, J.J., Corell, R.W., Christensen, L., Eckley, N., Kasperson, J.X., Luers, A., Martello, M.L., et al.: A framework for vulnerability analysis in sustainability science. Proc. Natl. Acad. Sci. 100(14), 8074–8079 (2003)

    Article  Google Scholar 

  31. Wisner, B., Blaikie, P., Cannon, T., Davis, I.: At Risk: Natural Hazards, People’s Vulnerability and Disasters. Routledge, Abingdon-on-Thames (2004)

    Google Scholar 

  32. Wolf, T., McGregor, G.: The development of a heat wave vulnerability index for London, United Kingdom. Weather Clim. Extremes 1, 59–68 (2013)

    Article  Google Scholar 

  33. Wood, N.J., Jones, J., Spielman, S., Schmidtlein, M.C.: Community clusters of Tsunami vulnerability in the US Pacific Northwest. Proc. Nat. Acad. Sci. 112(17), 5354–5359 (2015)

    Article  Google Scholar 

  34. Xu, Y., Dadvand, P., Barrera-Gómez, J., Sartini, C., Marí-Dell’Olmo, M., Borrell, C., Medina-Ramón, M., Sunyer, J., Basagaña, X.: Differences on the effect of heat waves on mortality by sociodemographic and urban landscape characteristics. J. Epidemiol. Commun. Health 67(6), 519–525 (2013)

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Geography, University of Colorado-Boulder, Boulder, USA

    Joseph V. Tuccillo & Barbara P. Buttenfield

Authors
  1. Joseph V. Tuccillo
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  2. Barbara P. Buttenfield
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Correspondence to Joseph V. Tuccillo .

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Editors and Affiliations

  1. University of Texas at Austin , Austin, Texas, USA

    Jennifer A. Miller

  2. University of California at Berkeley , Berkeley, California, USA

    David O'Sullivan

  3. University of Wisconsin-Madison , Madison, Wisconsin, USA

    Nancy Wiegand

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© 2016 Springer International Publishing Switzerland

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Tuccillo, J.V., Buttenfield, B.P. (2016). Model-Based Clustering of Social Vulnerability to Urban Extreme Heat Events. In: Miller, J., O'Sullivan, D., Wiegand, N. (eds) Geographic Information Science. GIScience 2016. Lecture Notes in Computer Science(), vol 9927. Springer, Cham. https://doi.org/10.1007/978-3-319-45738-3_8

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  • DOI: https://doi.org/10.1007/978-3-319-45738-3_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45737-6

  • Online ISBN: 978-3-319-45738-3

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