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Hervé Trebossen Benoît Deffontaines Nicolas Classeau Jacob Kouame Jean-Paul Rudant 《Comptes Rendus Geoscience》2005,337(13):1140-1153
This paper aims at illustrating different case examples of monitoring active coastal evolutions using remote sensing synthetic aperture radar images (ERS 1–2 and Envisat) in humid tropical areas. Effectively, the radar satellite images may be acquired under most climate conditions, especially in cloudy tropical areas. As case examples, we studied herein French Guiana shoreline and its fast evolution under the combined influences of sea currents, sediments and swells. We focused on two aspects of French Guiana littoral evolution: (1) sedimentation and erosion processes linked to mud banks displacements around Kourou City, and (2) around Iracoubo village. Lastly, we compared this short-term sedimentation balance with long-term data showing the discrepancies of short- and long-term littoral evolutions on whole French Guiana. To conclude, this work demonstrates the importance of SAR imagery to provide high-quality and high-frequency update geographic information for coastal management and littoral hazards especially in such tropical humid and cloudy areas. To cite this article: H. Trebossen et al., C. R. Geoscience 337 (2005). 相似文献
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In the present context of climate change and preservation of biodiversity, the appreciation of the vulnerability of the natural ecosystems and their capacity of adaptation appears among the main preoccupations to the world level (GIEC, 2007). This assessment of the ecosystems requires the availability of climatic data, what is often made difficult by the weak density or even the absence of meteorological stations notably, to the level of the mountains zones. In order to study the climate–vegetation relationship in North Algeria, we use an automatic interpolation method, the neural network method, for the reconstitution of climatic data of the sampled sites, (1035 phytoecological samples), from the existing meteorological network (269 stations). This method is characterized by a great suppleness of non-linearity and by its capacity for reconstituting information from partial and not well-defined indications such as the case of data provided from meteorological networks. In order to reconstitution of climatic data, we use the explicate variables, longitude, latitude and altitude, the variables to explain being the rainfall and temperatures. To define the best approach, the network calibration has been activated on climatic parameters taken globally or solely, for the whole of study zone, and by geographical sector. The results of the interpolation are expressed through a climatic parameter cartography, released automatically by the MapInfo software. The reliability results obtained by this method can be appreciated by elaboration of errors maps comparing to reference data. 相似文献
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