Climate Change in the Midwest: Impacts, Risks, Vulnerability, and Adaptation

By S. C. Pryor | Go to book overview

10.
Intra-Urban Variations in Vulnerability
Associated with Extreme Heat Events in
Relationship to a Changing Climate

D. P. JOHNSON, V. LULLA, AND A. C. STANFORTH


introduction

In the developing literature on the nature of climate change and its potential impact on society, vulnerability is an emerging pervasive theme. As can be seen in chapter 1 of this volume, vulnerability, by its very nature, is a multidisciplinary and multidimensional concept and thus requires multiple levels of definition and examination (Bankoff 2001, Bankoff 2003). Vulnerability is also a term that has been recently utilized as a “catch-all” phrase and thus is in danger of losing some of its descriptive effectiveness (Cutter et al. 2008). Vulnerability is so encompassing because it stems from multiple conditions that could represent the social, health, intelligence, or economic status of an individual or location (Wisner 2004). For the present discussion, we are concerned with the vulnerability of populations to a changing climate; our definitions will focus on health and social vulnerability to extreme events, such as those that will likely punctuate climate change globally, particularly heat waves. This chapter intends to introduce vulnerability in the context of extreme heat and to present a case study where such an analysis of vulnerability has taken place.

Clearly, vulnerability to extreme heat, in such a complex system as an urban space, is not of the same magnitude through out the city. Depending on where people live, their environment and socioeconomic conditions (i.e., poverty) can impact their unique vulnerability, and each area of the city may be markedly different from another. Intra-urban vulnerability (Harpham 2009, Minuci and de Almeida 2009) is increasingly being studied with remote sensing because spatial information is vital to disaster planning and mitigation (Harlan et al. 2006, Cutter et al. 2008, Johnson et al. 2009, Johnson and Wilson 2009). This type of information leads to “intelligence-led decision making” and is becoming increasingly recognized as a robust modeling framework. The examination presented in this chapter will involve the discussion of a vulnerability case study for Indianapolis, Indiana, using both demographic and environmental

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