This article aims to shed light on the policies designed to remove assets highly exposed to climate-change-related sea level rises. This kind of adaptation policy, which involves reducing the risk of exposure, supposes a paradigm shift from the logic of protection by means of seawalls, i.e., from fighting against sea level rise, to trying to adapt and live with it. From a methodological point of view, we use a sequence of tools (econometric modeling, then spatial modeling using a GIS). We test the spatialization of willingness-to-pay (WTP) to protect the homes. The input variables are part of a phenomenological (perceptions) and neo-positivist (Euclidean distance, altitude) approach. Depending on their significance, some are not kept during the modeling. The econometric and spatial analysis continues with a cartographic analysis based on a spatialized observation of the results. The objective is to assess the attachment to property and place. Thus it aims to evaluate the resistances of the inhabitants with respect to the acceptability of these policies, and to study whether the magnitude of WTP is explained by geographical factors coming from laws based on measurement (Taylor, 1983), such as the proximity to the risk (Euclidean distance to the risk), or if it relates to more subjective elements linked to the sensitivity of the inhabitants across time, such as the attachment to the landscape or the living space (Hellequin et al., 2013; Rey-Valette et al., 2012).The analysis draws on perception surveys conducted on main and second-home residents of the communes of Palavas-les-Flots, Mauguio-Carnon, and Pérols (department of Herault, France). These spatial treatments show the existence of a relatively objective risk perception by homeowners in Palavas- les-Flots and Mauguio-Carnon. These inhabitants are aware of the potential dangers related to their locations and their distances from the sea. On the other hand, in Pérols, a backcountry residential municipality only indirectly affected by submersion owing to the ponds, risk perception is affected by the landscape features of the site.© 2016 Lavoisier, Paris. All rights reserved.
Abstract
English
Authors
Guillaume
Bailly
Bénédicte
Rulleau
Hélène
Rey-Valette
Cite
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