that produced suboptimal outcomes (cf. Burton et al., 1978).

Several recent major global research initiatives have grown out of the Chicago School’s concern with the risk–hazards relationship, including sustainability science (e.g., Kates et al., 2001), socioecological resilience studies (e.g., Berkes and Folke, 1998), adaptation science (e.g., Smit et al., 1999), and coupled human–environment system vulnerability studies (e.g., McCarthy et al., 2001; Turner et al., 2003b). These four intersecting agendas define the core vulnerability-related research domains to which the geographical sciences are currently contributing. The contributions of the geographical sciences have focused particularly on understanding how people (and ecosystems) produce, and respond to, changing environmental conditions (e.g., Dow, 1992), and the social and political processes that produce differential exposures, sensitivities, and adaptive capacities, even in the absence of changing environmental conditions (e.g., Wisner et al., 2004).

A geographical perspective on vulnerability exhibits five basic features (Schröter et al., 2005). First, geographical studies of vulnerability situate the unit of analysis within the coupled human–environment system, rather than solely within the human or the environmental system. Accordingly, the methodological basis for these studies tends to be interdisciplinary, involving not only researchers from different academic backgrounds, but also stakeholders (i.e., those involved in making decisions about the processes under consideration). Second, the scale at which the coupled human–environment system is studied is generally “place-based,” meaning that local-scale human–environment processes and outcomes are emphasized—although not to the exclusion of processes and outcomes at other scales. Third, because the general unit of analysis is the coupled human–environment system, the drivers of system change are understood to be multiple and possibly interacting. Fourth, the analytical concern with exposures and sensitivities of multiple systems to multiple stressors at multiple scales means that central attention is given to the differential abilities of places to adapt to stresses. Finally, recognition of the dynamic nature of the interactions that shape coupled human–environment systems translates into a concern with shifting vulnerabilities across time (how vulnerabilities have changed in the past and what they might look like in the future). What unites these five characteristics of geographical vulnerability studies is that the particular interconnections among processes found in different places are privileged rather than assumed away.

Two recent studies illustrate what the geographical sciences bring to the study of vulnerability. In one study, Cutter and Finch (2008) analyze temporal and spatial changes in social vulnerability via the Social Vulnerability Index (SoVI), which measures the social vulnerability of U.S. counties to environmental hazards (originally introduced in Cutter et al., 2003). The SoVI is a score assigned to each unit of analysis (in this case, U.S. counties) derived from a principal components analysis of variables hypothesized to reflect various social vulnerabilities to natural hazards. Cutter and Finch draw on decennial U.S. Census data for the period 1960-2000, but their study is also forward looking. They examine trends in the historic data to project SoVI values for the year 2010, and they compare maps of SoVI scores for each past census year with the projected year (Figure 3.2). Future vulnerability studies of this sort could benefit from data at a finer spatial resolution (in some parts of the country, the county represents areas that are so large and populous as to mask important local variations), and from data reflecting the effects of multiple hazards in a given location. These types of data could be correlated with the SoVI; stakeholders could also be polled to comment on the utility and accuracy of the model results.

A second study by O’Brien et al. (2004) illustrates an approach to studying vulnerability that treats it as the product of multiple interacting stressors. Their case study looks at the interrelated vulnerability impacts of globalization and climate change in India (see also the discussion of this line of research as it relates to inequality, in Chapter 8). They collected secondary data reflecting multiple biophysical, social, economic-trade, and technological features of individual Indian districts, and analyzed the data using geographic information system (GIS) map algebra. This approach allowed them to produce a set of district-level maps of exposures, sensitivities, adaptive capacities, and vulnerabilities that highlighted districts that are doubly exposed to the negative impacts of globalization and climate change (see Figure 8.4). The authors further sampled three of these doubly exposed districts for further in-depth



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