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| Lafon, Virginie; Marieu, Vincent; Butel, Rémi; Dehouck, Aurélie; Froidefond, Jean-marie; Trut, Gilles. |
| This study presents the first results of an ongoing research program that aims to derive thematic maps of the intertidal lagoon of Arcachon (SW Atlantic coast of France) from space imagery. At this stage, we present the results of the tests performed on Formosat-2 imagery. Several classification strategies have been tried with the aim to discriminate the sedimentary facies and the main species of the lagoon. The classes calculated by an optimized unsupervised clustering method, based on simulated annealing global minimization technique, were used to train a supervised classification algorithm. This approach allowed us to derive a bio-sedimentary map which overall accuracy is about 84%. Also, this method has the advantage of describing the fraction of... |
| Tipo: Text |
Palavras-chave: Télédétection; Cartographie; Littoral; Classification optimisée; Recuit simulé. |
| Ano: 2008 |
URL: http://archimer.ifremer.fr/doc/00254/36572/35110.pdf |
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| Dehouck, Aurélie; Baghdadi, Nicolas; Garcia, Aurelie; Curti, Cecile; Trut, Gilles; Lafon, Virginie. |
| L’imagerie satellitaire optique dispose d’un bon potentiel de cartographie des espaces naturels littoraux de par l’emprise spatiale, la haute résolution et le recul temporel qu’offrent les 25 ans d’archives image SPOT. Cette communication explore le potentiel des images SAR (Synthetic Aperture Radar) Haute Résolution (HR) pour la cartographie des habitats intertidaux en complément de l’imagerie optique traditionnelle. Dans un premier temps, le potentiel de discrimination des habitats du Bassin d’Arcachon est brièvement évalué à partir d’une série temporelle constituée de 15 images TerraSAR-X et de 2 images ALOS-PALSAR acquises entre 2007 et 2011. L’étude a permis de caractériser les signatures radar de la couverture sédimentaire intertidale, des herbiers... |
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| Ano: 2013 |
URL: http://archimer.ifremer.fr/doc/00254/36573/35111.pdf |
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| Gernez, Pierre; Lafon, Virginie; Lerouxel, Astrid; Curti, Cecile; Lubac, Bertrand; Cerisier, Sylvain; Barille, Laurent. |
| At the end of the SPOT4 mission, a four-month experiment was conducted in 2013 to acquire high spatial (20 m) and high temporal (5 days) resolution satellite data. In addition to the SPOT4 (Take5) dataset, we used several Landsat5, 7, 8 images to document the variations in suspended particulate matter (SPM) concentration in the turbid Gironde and Loire estuaries (France). Satellite-derived SPM concentration was validated using automated in situ turbidity measurements from two monitoring networks. The combination of a multi-temporal atmospheric correction method with a near-infrared to visible reflectance band ratio made it possible to quantify SPM surface concentration in moderately to extremely turbid waters (38-4320 g center dot m(-3)), at an accuracy... |
| Tipo: Text |
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| Ano: 2015 |
URL: https://archimer.ifremer.fr/doc/00590/70198/68221.pdf |
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| Novoa, Stefani; Doxaran, David; Ody, Anouck; Vanhellemont, Quinten; Lafon, Virginie; Lubac, Bertrand; Gernez, Pierre. |
| The accurate measurement of suspended particulate matter (SPM) concentrations in coastal waters is of crucial importance for ecosystem studies, sediment transport monitoring, and assessment of anthropogenic impacts in the coastal ocean. Ocean color remote sensing is an efficient tool to monitor SPM spatio-temporal variability in coastal waters. However, near-shore satellite images are complex to correct for atmospheric effects due to the proximity of land and to the high level of reflectance caused by high SPM concentrations in the visible and near-infrared spectral regions. The water reflectance signal ((w)) tends to saturate at short visible wavelengths when the SPM concentration increases. Using a comprehensive dataset of high-resolution satellite... |
| Tipo: Text |
Palavras-chave: Remote sensing; Suspended particulate matter; Coastal waters; River plumes; Multi-conditional algorithm. |
| Ano: 2017 |
URL: https://archimer.ifremer.fr/doc/00590/70197/68222.pdf |
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