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Spatial variability of suspended sediments in San Francisco Bay, California / Niky C. Taylor in Remote sensing, vol 13 n° 22 (November-2 2021)  

Public [article]  inRemote sensing > vol 13 n° 22 (November-2 2021) . - n° 4625 Titre : Spatial variability of suspended sediments in San Francisco Bay, California Type de document : Article/Communication Auteurs : Niky C. Taylor, Auteur ; Raphael M. Kudela, Auteur Année de publication : 2021 Article en page(s) : n° 4625 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] baie [Termes IGN] échantillonnage [Termes IGN] estuaire [Termes IGN] image Sentinel-MSI [Termes IGN] pas d'échantillonnage au sol [Termes IGN] qualité des eaux [Termes IGN] réflectance [Termes IGN] San Francisco [Termes IGN] sédiment [Termes IGN] spectroradiométrie [Termes IGN] surface de l'eau [Termes IGN] surveillance du littoral [Termes IGN] turbidité des eaux [Termes IGN] variabilité Résumé : (auteur) Understanding spatial variability of water quality in estuary systems is important for making monitoring decisions and designing sampling strategies. In San Francisco Bay, the largest estuary system on the west coast of North America, tracking the concentration of suspended materials in water is largely limited to point measurements with the assumption that each point is representative of its surrounding area. Strategies using remote sensing can expand monitoring efforts and provide a more complete view of spatial patterns and variability. In this study, we (1) quantify spatial variability in suspended particulate matter (SPM) concentrations at different spatial scales to contextualize current in-water point sampling and (2) demonstrate the potential of satellite and shipboard remote sensing to supplement current monitoring methods in San Francisco Bay. We collected radiometric data from the bow of a research vessel on three dates in 2019 corresponding to satellite overpasses by Sentinel-2, and used established algorithms to retrieve SPM concentrations. These more spatially comprehensive data identified features that are not picked up by current point sampling. This prompted us to examine how much variability exists at spatial scales between 20 m and 10 km in San Francisco Bay using 10 m resolution Sentinel-2 imagery. We found 23–80% variability in SPM at the 5 km scale (the scale at which point sampling occurs), demonstrating the risk in assuming limited point sampling is representative of a 5 km area. In addition, current monitoring takes place along a transect within the Bay’s main shipping channel, which we show underestimates the spatial variance of the full bay. Our results suggest that spatial structure and spatial variability in the Bay change seasonally based on freshwater inflow to the Bay, tidal state, and wind speed. We recommend monitoring programs take this into account when designing sampling strategies, and that end-users account for the inherent spatial uncertainty associated with the resolution at which data are collected. This analysis also highlights the applicability of remotely sensed data to augment traditional sampling strategies. In sum, this study presents ways to supplement water quality monitoring using remote sensing, and uses satellite imagery to make recommendations for future sampling strategies. Numéro de notice : A2021-839 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs13224625 Date de publication en ligne : 17/11/2021 En ligne : https://doi.org/10.3390/rs13224625 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99022 [article]

Protection naturelle contre la submersion, apport de l'intelligence artificielle / Antoine Mury in Cartes & Géomatique, n° 245-246 (septembre - décembre 2021)

Public [article]  inCartes & Géomatique > n° 245-246 (septembre - décembre 2021) . - pp 127 - 137 Titre : Protection naturelle contre la submersion, apport de l'intelligence artificielle Type de document : Article/Communication Auteurs : Antoine Mury, Auteur ; Antoine Collin, Auteur ; Dorothée James, Auteur Année de publication : 2021 Article en page(s) : pp 127 - 137 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] baie [Termes IGN] cartographie des risques [Termes IGN] classification par réseau neuronal [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] enjeu [Termes IGN] image Worldview [Termes IGN] littoral [Termes IGN] modèle de simulation [Termes IGN] Mont-Saint-Michel [Termes IGN] submersion marine [Termes IGN] vague [Termes IGN] vulnérabilité Résumé : (Auteur) Cette étude a pour objectif de proposer une méthodologie expérimentale de cartographie du risque de submersion marine, intégrant la protection littorale naturelle offerte par les systèmes écogéomorphologiques du domaine intertidal, par le biais d'une modélisation de l'atténuation des hauteurs significatives des vagues. Ce travail s'appuie sur des données à très haute résolution spatiale : des mesures de vague in situ, les imageries satellite WorldView-3 et aérienne LiDAR (Light Detection And Ranging), ainsi que sur l'intelligence artificielle par réseau de neurones artificiels. Numéro de notice : A2021-929 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99349 [article]

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Establishing vertical separation models for vulnerable coastlines in developing territories / Cassandra Nanlal in Marine geodesy, vol 44 n° 5 (September 2021)  

Public [article]  inMarine geodesy > vol 44 n° 5 (September 2021) . - pp 387 - 407 Titre : Establishing vertical separation models for vulnerable coastlines in developing territories Type de document : Article/Communication Auteurs : Cassandra Nanlal, Auteur ; Keith Miller, Auteur ; Dexter Davis, Auteur ; Michael Sutherland, Auteur Année de publication : 2021 Article en page(s) : pp 387 - 407 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux [Termes IGN] aménagement du littoral [Termes IGN] Amérique du sud [Termes IGN] changement climatique [Termes IGN] données altimétriques [Termes IGN] géodésie physique [Termes IGN] golfe [Termes IGN] hauteurs de mer [Termes IGN] niveau de la mer [Termes IGN] simulation hydrodynamique [Termes IGN] système de référence altimétrique [Termes IGN] système de référence local [Termes IGN] trait de côte [Termes IGN] vulnérabilité Résumé : (Auteur) Vertical separation models are valuable for coastal zone management and protection against the effects of climate change. To date, the development of such models has been undertaken in areas where long-term sea level measurements exist and there are resources for extensive offshore bathymetric and Global Navigation Satellite Systems surveys. Many small island developing states and other resource constrained territories host vulnerable coastal zones and would benefit from such models, however, financial constraints and data sparsity make it difficult. This article describes the establishment of a vertical separation model using an amalgamation of long- and short-term sea level measurements with hydrodynamic modeling. With existing vertical separations at only two coastal points for comparison, the model was designed to include a tidal prediction element which allowed for validation against sparse independently observed sea levels. Considering that unmodeled influences on sea levels in the study area can exceed 0.2 m at times, the method was tested against independently observed sea levels and can be considered successful with variances in the range of 1.3–4.5% of the average tidal range for the study area. This research provides the means of addressing a significant need in developing territories where long-term sea level records are unavailable and resource deficiencies exist. Numéro de notice : A2021-576 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01490419.2020.1844825 Date de publication en ligne : 02/12/2020 En ligne : https://doi.org/10.1080/01490419.2020.1844825 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98227 [article]

Deep learning for detecting and classifying ocean objects: application of YoloV3 for iceberg–ship discrimination / Frederik Hass in ISPRS International journal of geo-information, vol 9 n° 12 (December 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 12 (December 2020) . - n° 758 Titre : Deep learning for detecting and classifying ocean objects: application of YoloV3 for iceberg–ship discrimination Type de document : Article/Communication Auteurs : Frederik Hass, Auteur ; Jamal Jokar Arsanjani, Auteur Année de publication : 2020 Article en page(s) : n° 758 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] apprentissage profond [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] Groenland [Termes IGN] hydrocarbure [Termes IGN] iceberg [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] navire [Termes IGN] océan [Termes IGN] seuillage d'image [Termes IGN] trafic maritime Résumé : (auteur) Synthetic aperture radar (SAR) plays a remarkable role in ocean surveillance, with capabilities of detecting oil spills, icebergs, and marine traffic both at daytime and at night, regardless of clouds and extreme weather conditions. The detection of ocean objects using SAR relies on well-established methods, mostly adaptive thresholding algorithms. In most waters, the dominant ocean objects are ships, whereas in arctic waters the vast majority of objects are icebergs drifting in the ocean and can be mistaken for ships in terms of navigation and ocean surveillance. Since these objects can look very much alike in SAR images, the determination of what objects actually are still relies on manual detection and human interpretation. With the increasing interest in the arctic regions for marine transportation, it is crucial to develop novel approaches for automatic monitoring of the traffic in these waters with satellite data. Hence, this study aims at proposing a deep learning model based on YoloV3 for discriminating icebergs and ships, which could be used for mapping ocean objects ahead of a journey. Using dual-polarization Sentinel-1 data, we pilot-tested our approach on a case study in Greenland. Our findings reveal that our approach is capable of training a deep learning model with reliable detection accuracy. Our methodical approach along with the choice of data and classifiers can be of great importance to climate change researchers, shipping industries and biodiversity analysts. The main difficulties were faced in the creation of training data in the Arctic waters and we concluded that future work must focus on issues regarding training data. Numéro de notice : A2020-808 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9120758 Date de publication en ligne : 19/12/2020 En ligne : https://doi.org/10.3390/ijgi9120758 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96953 [article]

Shoreline extraction from WorldView2 satellite data in the presence of foam pixels using multispectral classification method / Audrey Minghelli in Remote sensing, vol 12 n° 16 (August-2 2020)  

Public [article]  inRemote sensing > vol 12 n° 16 (August-2 2020) . - n° 2664 Titre : Shoreline extraction from WorldView2 satellite data in the presence of foam pixels using multispectral classification method Type de document : Article/Communication Auteurs : Audrey Minghelli, Auteur ; Jérôme Spagnoli, Auteur ; Manchun Lei , Auteur ; Malik Chami, Auteur ; Sabine Charmasson, Auteur Année de publication : 2020 Projets : AMORAD / Radakovitch, Olivier Article en page(s) : n° 2664 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] baie [Termes IGN] classification multibande [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] détection de contours [Termes IGN] écume [Termes IGN] image Worldview [Termes IGN] littoral [Termes IGN] Sendaï [Termes IGN] trait de côte Résumé : (auteur) Foam is often present in satellite images of coastal areas and can lead to serious errors in the detection of shorelines especially when processing high spatial resolution images ( Numéro de notice : A2020-570 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs12162664 Date de publication en ligne : 18/08/2020 En ligne : https://doi.org/10.3390/rs12162664 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95877 [article]

Global observations of ocean surface winds and waves using spaceborne synthetic aperture radar measurements / Huimin Li (2019)  

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De la navigation "à vue" au calcul des longitudes / Jean-Yves Sarazin in Carto, le monde en cartes, n° 28 (mars - avril 2015)

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Assimilation of GRACE-derived oceanic mass distributions with a global ocean circulation model / J. Saynisch in Journal of geodesy, vol 89 n° 2 (February 2015)  

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Empirical model of the gravitational field generated by the oceanic lithosphere / Robert Tenzer in Advances in space research, vol 55 n° 1 ([01/01/2015])  

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Domaine public à parcelliser / Pierre Clergeot in Géomètre, n° 2116 (juillet - août 2014)

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Mémo visuel de géologie / Yves Lagabrielle (2013)

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Evaluation of the spatial changes in seagrass cover in the lagoons of Lakshadweep islands, India, using IRS LISS III satellite images / E.P. Nobi in Geocarto international, vol 27 n° 8 (December 2012)  

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Advancing global marine biogeography research with open-source GIS software and cloud computing / E. Fujioka in Transactions in GIS, vol 16 n° 2 (April 2012)  

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Encyclopédie des tours du monde / C. Nau (2012)

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Magellan / C. Clot (2012)

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