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Automatic detection of inland water bodies along altimetry tracks for estimating surface water storage variations in the Congo basin / Frédéric Frappart in Remote sensing, vol 13 n° 19 (October-1 2021)  

Public [article]  inRemote sensing > vol 13 n° 19 (October-1 2021) . - n° 3804 Titre : Automatic detection of inland water bodies along altimetry tracks for estimating surface water storage variations in the Congo basin Type de document : Article/Communication Auteurs : Frédéric Frappart, Auteur ; Pierre Zeiger, Auteur ; Julie Betbeder, Auteur ; Valéry Gond, Auteur ; Régis Bellot , Auteur ; Nicolas Baghdadi, Auteur ; Fabien Blarel, Auteur ; José Darrozes, Auteur ; Luc Bourrel, Auteur ; Frédérique Seyler, Auteur Année de publication : 2021 Projets : TOSCA / Article en page(s) : n° 3804 Note générale : bibliographie This research was funded by CNES TOSCA grants number CASCHMIR and SWHYM. Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] classification par nuées dynamiques [Termes IGN] Congo (bassin) [Termes IGN] détection automatique [Termes IGN] données altimétriques [Termes IGN] eau de surface [Termes IGN] estimation statistique [Termes IGN] image Envisat-ASAR [Termes IGN] image Jason-AMR [Termes IGN] niveau de l'eau [Termes IGN] série temporelle [Termes IGN] stockage [Termes IGN] volume d'eau [Termes IGN] zone humide Résumé : (auteur) Surface water storage in floodplains and wetlands is poorly known from regional to global scales, in spite of its importance in the hydrological and the carbon balances, as the wet areas are an important water compartment which delays water transfer, modifies the sediment transport through sedimentation and erosion processes, and are a source for greenhouse gases. Remote sensing is a powerful tool for monitoring temporal variations in both the extent, level, and volume, of water using the synergy between satellite images and radar altimetry. Estimating water levels over flooded area using radar altimetry observation is difficult. In this study, an unsupervised classification approach is applied on the radar altimetry backscattering coefficients to discriminate between flooded and non-flooded areas in the Cuvette Centrale of Congo. Good detection of water (open water, permanent and seasonal inundation) is above 0.9 using radar altimetry backscattering from ENVISAT and Jason-2. Based on these results, the time series of water levels were automatically produced. They exhibit temporal variations in good agreement with the hydrological regime of the Cuvette Centrale. Comparisons against a manually generated time series of water levels from the same missions at the same locations show a very good agreement between the two processes (i.e., RMSE ≤ 0.25 m in more than 80%/90% of the cases and R ≥ 0.95 in more than 95%/75% of the cases for ENVISAT and Jason-2, respectively). The use of the time series of water levels over rivers and wetlands improves the spatial pattern of the annual amplitude of water storage in the Cuvette Centrale. It also leads to a decrease by a factor of four for the surface water estimates in this area, compared with a case where only time series over rivers are considered. Numéro de notice : A2021-935 Affiliation des auteurs : IGN+Ext (2020- ) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13193804 Date de publication en ligne : 23/09/2021 En ligne : https://doi.org/10.3390/rs13193804 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99542 [article]

TerraSAR-X dual-pol time-series for mapping of wetland vegetation / Julie Betbeder in ISPRS Journal of photogrammetry and remote sensing, vol 107 (September 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 107 (September 2015) . - pp 90 - 98 Titre : TerraSAR-X dual-pol time-series for mapping of wetland vegetation Type de document : Article/Communication Auteurs : Julie Betbeder, Auteur ; Sébastien Rapinel, Auteur ; Samuel Corgne, Auteur ; Eric Pottier, Auteur ; Laurence Hubert-Moy, Auteur Année de publication : 2015 Article en page(s) : pp 90 - 98 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] 1:10.000 [Termes IGN] caractérisation [Termes IGN] carte de la végétation [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] données multitemporelles [Termes IGN] données polarimétriques [Termes IGN] image radar moirée [Termes IGN] image TerraSAR-X [Termes IGN] série temporelle [Termes IGN] zone humide Résumé : (auteur) Mapping vegetation formations at a fine scale is crucial for assessing wetland functions and for better landscape management. Identification and characterization of vegetation formations is generally conducted at a fine scale using ecological ground surveys, which are limited to small areas. While optical remotely sensed imagery is limited to cloud-free periods, SAR time-series are used more extensively for wetland mapping and characterization using the relationship between distribution of vegetation formations and flood duration. The aim of this study was to determine the optimal number and key dates of SAR images to be classified to map wetland vegetation formations at a 1:10,000 scale. A series of eight dual-polarization TerraSAR-X images (HH/VV) was acquired in 2013 during dry and wet seasons in temperate climate conditions. One polarimetric parameter was extracted first, the Shannon entropy, which varies with wetland flooding status and vegetation roughness. Classification runs of all the possible combinations of SAR images using different k (number of images) subsets were performed to determine the best combinations of the Shannon entropy images to identify wetland vegetation formations. The classification runs were performed using Support Vector Machine techniques and were then analyzed using the McNemar test to investigate significant differences in the accuracy of all classification runs based on the different image subsets. The results highlight the relevant periods (i.e. late winter, spring and beginning of summer) for mapping vegetation formations, in accordance with ecological studies. They also indicate that a relationship can be established between vegetation formations and hydrodynamic processes with a short time-series of satellite images (i.e. 5 dates). This study introduces a new approach for herbaceous wetland monitoring using SAR polarimetric imagery. This approach estimates the number and key dates required for wetland management (e.g. restoration) and biodiversity studies using remote sensing data. Numéro de notice : A2015-727 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.05.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.05.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78377 [article]