University of the Littoral Opal Coast

About: University of the Littoral Opal Coast is a education organization based out in Dunkirk, France. It is known for research contribution in the topics: Catalysis & Dielectric. The organization has 1242 authors who have published 2383 publications receiving 46230 citations. The organization is also known as: ULCO.

Second-home owners and sea-level rise: the case of the Languedoc- Roussillon region (France)

Abstract: Municipalities of the Languedoc-Roussillon region (South-eastern France) are highly vulnerable to climate-change-induced sea-level rise (SLR) due to their low altitude and the great attractiveness of the region for tourism. This attractiveness has resulted in a very significant development of second homes, which represent half of the housing stock and three quarters of the total capacity for tourism hospitality. In the context of climate change adaptation measures related to SLR, it is imperative to consider the perceptions of second-home owners and their place in local governance arrangements. Scientists advocate the implementation of managed retreat policies to reduce vulnerability by reducing the exposure of buildings, but both the social acceptability and the economic feasibility of these policies are very low. We assume that second-home owners have different perceptions of the risk of inundation and are less involved in the governance mechanisms. It is very difficult to mobilise a large number of owners of small flats who are less concerned with, and less likely to contribute to, policy development, due to their less frequent presence. We studied these issues through a survey in three municipalities, based on a sample of 318 residents and 163 second-home owners faced with inundation risk. We observed a lower sensitivity to risk and a stronger attachment to homes on the part of secondhome owners (compared to residents). We also discuss, in terms of equity and efficiency, the impact of their low level of engagement in governance mechanisms.

Feature Extraction in Scanning Laser Range Data Using Invariant Parameters: Application to Vehicle Detection

Abstract: This paper presents a feature extraction method in scanning laser range data Many authors have studied this problem by proposing solutions that rely on a modeling of the scene in Cartesian coordinates These methods are based on the computation of the interscan distance between two consecutive measurements, which, in practice, is not very easy to estimate Our proposed method, ie, segmentation using invariant parameters (SIP), deals with laser measurements in natural coordinates, which avoids any preprocessing stage that could modify the measurement noise statistics This approach is founded on the use of an invariant description of the feature and leads to the definition of a criterion of line-segment detection that only depends on the sensor intrinsic parameters