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Redlining occurs when institutions decline to make mortgage loans in specific areas. The practice originated in the 1930s, when federal agencies encouraged lenders to rate neighbourhoods for mortgage risk. Since the 1960s, especially in the US, it has been associated with disinvestment, racial discrimination and neighbourhood decline. It has always been viewed as a feature of the inner city. Historical evidence indicates that across Canada the first areas to be redlined were the less-desirable suburbs. Land registry and property assessment data establish the emergent patterns in Hamilton, Ontario. Between 1931 and 1951, institutional lending became a social norm first on new dwellings in suburbs. Individual lenders, previously dominant, were relegated to older inner-city properties or cheaper dwellings in less-desirable suburbs. In 1931, there were only minor geographical variations in the incidence of mortgage finance, and specifically of institutional financing, across the urban area. By 1951, lending institutions, led by insurance companies, were discriminating sharply in favour of the West End, the Mountain and Bartonville, and against those parts of the East End that were unserviced or close to lakefront industry. The evidence for Hamilton confirms that in Canada redlining originated in the suburbs. The same may also be true for US metropolitan areas, although the institutional context was different and relevant data are lacking.

As Hurricane Katrina revealed, coastal communities have become far more vulnerable to tropical storms and the long-term displacement of residents. Yet, because the emergency management model presumes that recovery quickly follows response, governments focus only on short-term, localized displacement. However, long-term and long-distance displacement exposes a gray area between immediate shelter and permanent housing, along with concerns about vulnerability, housing availability, and land development. We begin this article by discussing the transition between response and recovery. We then review literature regarding social vulnerability, displacement, provision of temporary housing, households' return decisions, and disaster-driven land development and housing construction processes. We close with thoughts on future research to increase planners' understanding of the issues involved and to help them craft effective policies.

Abstract. Natural hazards can be seen as a function of a specific natural process and human (economic) activity. Whereby the bulk of literature on natural hazard management has its focus on the natural process, an increasing number of scholars is emphasizing the importance of human activity in this context. Existing literature has identified certain socio-economic factors that determine the impact of natural disasters on society. The purpose of this paper is to highlight the effects of the institutional framework that influences human behavior by setting incentives and to point out the importance of institutional vulnerability. Results from an empirical investigation of large scale natural disasters between 1984 and 2004 show that countries with better institutions experience less victims and lower economic losses from natural disasters. In addition, the results suggest a non-linear relationship between economic development and economic disaster losses. The suggestions in this paper have implications for the discussion on how to deal with the adverse effects of natural hazards and how to develop efficient adaption strategies.

In this article a preliminary analysis of the loss of life caused by Hurricane Katrina in the New Orleans metropolitan area is presented. The hurricane caused more than 1,100 fatalities in the state of Louisiana. A preliminary data set that gives information on the recovery locations and individual characteristics for 771 fatalities has been analyzed. One-third of the analyzed fatalities occurred outside the flooded areas or in hospitals and shelters in the flooded area. These fatalities were due to the adverse public health situation that developed after the floods. Two-thirds of the analyzed fatalities were most likely associated with the direct physical impacts of the flood and mostly caused by drowning. The majority of victims were elderly: nearly 60% of fatalities were over 65 years old. Similar to historical flood events, mortality rates were highest in areas near severe breaches and in areas with large water depths. An empirical relationship has been derived between the water depth and mortality and this has been compared with similar mortality functions proposed based on data for other flood events. The overall mortality among the exposed population for this event was approximately 1%, which is similar to findings for historical flood events. Despite the fact that the presented results are preliminary they give important insights into the determinants of loss of life and the relationship between mortality and flood characteristics.

This paper examines the challenges facing English flood risk management (FRM) policy and practice when considering fair decision-making processes and outcomes at a range of spatial scales. It is recognised that flooding is not fair per se : the inherent natural spatial inequality of flood frequency and extent, plus the legacy of differential system interventions, being the cause. But, drawing on the three social justice models – procedural equality, Rawls’ maximin rule and maximum utility – the authors examine the fairness principles currently employed in FRM decision-making. This is achieved, firstly, in relation to the distribution of taxpayer’s money for FRM at the national, regional and local levels and, secondly, for non-structural strategies – most notably those of insurance, flood warnings and awareness raising, land use control, home owner adaptation and emergency management. A case study of the Lower Thames catchment illustrates the challenges facing decision-makers in ‘real life’: how those strategies which appear to be most technically and economically effective fall far short of being fair from either a vulnerability or equality perspective. The paper concludes that if we are to manage flood risk somewhat more fairly then a move in the direction of government funding of nationally consistent non-structural strategies, in conjunction with lower investment decision thresholds for other local-level FRM options, appears to offer a greater contribution to equality and vulnerability-based social justice principles than the status quo.

Rivers are sensitive to natural climate change as well as to human impacts such as flow modification and land-use change. Climate change could cause changes to precipitation amounts, the intensity of cyclonic storms, the proportion of precipitation falling as rain, glacier mass balance, and the extent of permafrost; all of which affect the hydrology and morphology of river systems. Changes to the frequency and magnitude of flood flows present the greatest threat. Historically, wetter periods are associated with significantly higher flood frequency and magnitude. These effects are reduced in drainage basins with large lakes or glacier storage. Alluvial rivers with fine-grained sediments are most sensitive, but all rivers will respond, except those flowing through resistant bedrock. The consequences of changes in flow include changes in channel dimensions, gradient, channel pattern, sedimentation, bank erosion rates, and channel migration rates. The most sensitive and vulnerable regions are in southern Canada, particularly those regions at risk of substantial increases in rainfall intensity and duration. In northern rivers, thawing of permafrost and changes to river-ice conditions are important concerns. The type and magnitude of effects will be different between regions, as well as between small and large river basins. Time scales of change will range from years to centuries. These changes will affect the use that we make of rivers and their floodplains, and may require mitigative measures. Radical change is also possible. Climatic impacts will be ubiquitous and will be in addition to existing and future direct human impact on streamflow and rivers.

Global environmental change and sustainability science increasingly recognize the need to address the consequences of changes taking place in the structure and function of the biosphere. These changes raise questions such as: Who and what are vulnerable to the multiple environmental changes underway, and where? Research demonstrates that vulnerability is registered not by exposure to hazards (perturbations and stresses) alone but also resides in the sensitivity and resilience of the system experiencing such hazards. This recognition requires revisions and enlargements in the basic design of vulnerability assessments, including the capacity to treat coupled human–environment systems and those linkages within and without the systems that affect their vulnerability. A vulnerability framework for the assessment of coupled human–environment systems is presented.

Abstract This paper demonstrates the importance of disaggregating population data aggregated by census tracts or other units, for more realistic population distribution/location. A newly developed mapping method, the Cadastral-based Expert Dasymetric System (CEDS), calculates population in hyper-heterogeneous urban areas better than traditional mapping techniques. A case study estimating population potentially impacted by flood hazard in New York City compares the impacted population determined by CEDS with that derived by centroid-containment method and filtered areal-weighting interpolation. Compared to CEDS, 37% and 72% fewer people are estimated to be at risk from floods city-wide, using conventional areal weighting of census data, and centroid-containment selection, respectively. Undercounting of impacted population could have serious implications for emergency management and disaster planning. Ethnic/racial populations are also spatially disaggregated to determine any environmental justice impacts with flood risk. Minorities are disproportionately undercounted using traditional methods. Underestimating more vulnerable sub-populations impairs preparedness and relief efforts.

County-level socioeconomic and demographic data were used to construct an index of social vulnerability to environmental hazards, called the Social Vulnerability Index (SoVI) for the United States based on 1990 data. Copyright (c) 2003 by the Southwestern Social Science Association.