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scientifique

Automatic detection of suspected sewage discharge from coastal outfalls based on Sentinel-2 imagery / Yuxin Wang in Science of the total environment, vol 853 (December 2022)  

Public [article]  inScience of the total environment > vol 853 (December 2022) . - n° 158374 Titre : Automatic detection of suspected sewage discharge from coastal outfalls based on Sentinel-2 imagery Type de document : Article/Communication Auteurs : Yuxin Wang, Auteur ; Xianqiang He, Auteur ; Yan Bai, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 158374 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse de groupement [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] classification par nuées dynamiques [Termes IGN] couleur de l'océan [Termes IGN] détection automatique [Termes IGN] eau usée [Termes IGN] image Sentinel-MSI [Termes IGN] littoral [Termes IGN] perturbation écologique [Termes IGN] qualité des eaux Résumé : (auteur) Terrestrial pollution has a great impact on the coastal ecological environment, and widely distributed coastal outfalls act as the final gate through which pollutants flow into rivers and oceans. Thus, effectively monitoring the water quality of coastal outfalls is the key to protecting the ecological environment. Satellite remote sensing provides an attractive way to monitor sewage discharge. Selecting the coastal areas of Zhejiang Province, China, as an example, this study proposes an innovative method for automatically detecting suspected sewage discharge from coastal outfalls based on high spatial resolution satellite imageries from Sentinel-2. According to the accumulated in situ observations, we established a training dataset of water spectra covering various optical water types from satellite-retrieved remote sensing reflectance (Rrs). Based on the clustering results from unsupervised classification and different spectral indices, a random forest (RF) classification model was established for the optical water type classification and detection of suspected sewage. The final classification covers 14 optical water types, with type 12 and type 14 corresponding to the high eutrophication water type and suspected sewage water type, respectively. The classification result of model training datasets exhibited high accuracy with only one misclassified sample. This model was evaluated by historical sewage discharge events that were verified by on-site observations and demonstrated that it could successfully recognize sewage discharge from coastal outfalls. In addition, this model has been operationally applied to automatically detect suspected sewage discharge in the coastal area of Zhejiang Province, China, and shows broad application value for coastal pollution supervision, management, and source analysis. Numéro de notice : A2022-859 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.scitotenv.2022.158374 Date de publication en ligne : 28/08/2022 En ligne : https://doi.org/10.1016/j.scitotenv.2022.158374 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102135 [article]

Integrating Bayesian networks to forecast sea-level rise impacts on barrier island characteristics and habitat availability / Benjamin T. Gutierrez in Earth and space science, vol 9 n° 11 (November 2022)  

Public [article]  inEarth and space science > vol 9 n° 11 (November 2022) . - 24 p. Titre : Integrating Bayesian networks to forecast sea-level rise impacts on barrier island characteristics and habitat availability Type de document : Article/Communication Auteurs : Benjamin T. Gutierrez, Auteur ; Sarah Zeigler, Auteur ; Erika Lentz, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : 24 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de sensibilité [Termes IGN] changement climatique [Termes IGN] géomorphologie [Termes IGN] habitat animal [Termes IGN] île [Termes IGN] modèle de simulation [Termes IGN] montée du niveau de la mer [Termes IGN] New York (Etats-Unis ; ville) [Termes IGN] planification côtière [Termes IGN] réseau bayesien [Termes IGN] submersion marine [Termes IGN] surveillance du littoral [Termes IGN] trait de côte Résumé : (auteur) Evaluation of sea-level rise (SLR) impacts on coastal landforms and habitats is a persistent need for informing coastal planning and management, including policy decisions, particularly those that balance human interests and habitat protection throughout the coastal zone. Bayesian networks (BNs) are used to model barrier island change under different SLR scenarios that are relevant to management and policy decisions. BNs utilized here include a shoreline change model and two models of barrier island biogeomorphological evolution at different scales (50 and 5 m). These BNs were then linked to another BN to predict habitat availability for piping plovers (Charadrius melodus), a threatened shorebird reliant on beach habitats. We evaluated the performance of the two linked geomorphology BNs and further examined error rates by generating hindcasts of barrier island geomorphology and habitat availability for 2014 conditions. Geomorphology hindcasts revealed that model error declined with a greater number of known inputs, with error rates reaching 55% when multiple outputs were hindcast simultaneously. We also found that, although error in predictions of piping plover nest presence/absence increased when outputs from the geomorphology BNs were used as inputs in the piping plover habitat BN, the maximum error rate for piping plover habitat suitability in the fully-linked BNs was only 30%. Our findings suggest this approach may be useful for guiding scenario-based evaluations where known inputs can be used to constrain variables that produce higher uncertainty for morphological predictions. Overall, the approach demonstrates a way to assimilate data and model structures with uncertainty to produce forecasts to inform coastal planning and management. Numéro de notice : A2022-883 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1029/2022EA002286 Date de publication en ligne : 14/10/2022 En ligne : https://doi.org/10.1029/2022EA002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102024 [article]

Topographic descriptors on the early Dutch charts of the antipodes / Jan Tent in International journal of cartography, vol 8 n° 3 (November 2022)  

Public [article]  inInternational journal of cartography > vol 8 n° 3 (November 2022) . - pp 272 - 290 Titre : Topographic descriptors on the early Dutch charts of the antipodes Type de document : Article/Communication Auteurs : Jan Tent, Auteur Année de publication : 2022 Article en page(s) : pp 272 - 290 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Toponymie [Termes IGN] Australie [Termes IGN] carte ancienne [Termes IGN] descripteur [Termes IGN] explorateur [Termes IGN] littoral [Termes IGN] néerlandais (langue) [Termes IGN] nomenclature [Termes IGN] Nouvelle-Zélande [Termes IGN] Papouasie-Nouvelle-Guinée [Termes IGN] toponyme Résumé : (auteur) The early Dutch charts of coastal Australia, New Zealand and New Guinea are peppered not only with toponyms but also with topographic descriptors. The latter were intended as navigational aids and warnings for future navigators. Naming or describing a geographic feature is a method of distinguishing it from the surrounding topography. At times some topographic descriptors have been considered or interpreted as toponyms. This article explores whether there are any means of determining the difference between the two, and what may have been initially intended by the explorers who entered them on their manuscript charts. Reasons for the relevance of making such a distinction are also considered. Numéro de notice : A2022-746 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/TOPONYMIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2020.1859937 Date de publication en ligne : 11/02/2021 En ligne : https://doi.org/10.1080/23729333.2020.1859937 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101731 [article]

Analytical method for high-precision seabed surface modelling combining B-spline functions and Fourier series / Tyler Susa in Marine geodesy, vol 45 n° 5 (September 2022)  

Public [article]  inMarine geodesy > vol 45 n° 5 (September 2022) . - pp 435 - 461 Titre : Analytical method for high-precision seabed surface modelling combining B-spline functions and Fourier series Type de document : Article/Communication Auteurs : Tyler Susa, Auteur Année de publication : 2022 Article en page(s) : pp 435 - 461 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] bathymétrie [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] données d'entrainement (apprentissage automatique) [Termes IGN] Extreme Gradient Machine [Termes IGN] fond marin [Termes IGN] image Sentinel-MSI [Termes IGN] littoral [Termes IGN] modèle numérique de surface [Termes IGN] modélisation [Termes IGN] Porto Rico [Termes IGN] profondeur [Termes IGN] réflectance Résumé : (auteur) Accurate charting of nearshore bathymetry is critical to the safe and dependable use of coastal waterways frequented by the trading, fishing, tourism, and ocean energy industries. The accessibility of satellite imagery and the availability of various satellite-derived bathymetry (SDB) techniques have provided a cost-effective alternative to traditional in-situ bathymetric surveys. Furthermore, improved algorithms and the advancement of machine learning models have provided opportunity for higher quality bathymetric derivations. However, to date the relative accuracy and performance between traditional physics-based techniques, improved physics-based methods, and machine learning ensemble models have not been adequately quantified. In this study, nearshore bathymetry is derived from Sentinel-2 satellite imagery near La Parguera, Puerto Rico utilizing a traditional band-ratio algorithm, a band-ratio switching method, a random forest machine learning model, and the XGBoost machine learning model. The machine learning models returned comparable results and were markedly more accurate relative to other techniques; however, both machine learning models required an extensive training dataset. All models were constrained by environmental influences and image spatial resolution, which were assessed to be the limiting factors for routine use of satellite-derived bathymetry as a reliable method for hydrographic surveying. Numéro de notice : A2022-609 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01490419.2022.2064572 Date de publication en ligne : 04/05/2022 En ligne : https://doi.org/10.1080/01490419.2022.2064572 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101392 [article]

Littoraux sous double surveillance / Laurent Polidori in Géomètre, n° 2204 (juillet-août 2022)

Public [article]  inGéomètre > n° 2204 (juillet-août 2022) . - pp 23 - 23 Titre : Littoraux sous double surveillance Type de document : Article/Communication Auteurs : Laurent Polidori, Auteur Année de publication : 2022 Article en page(s) : pp 23 - 23 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Litto3D [Termes IGN] marée océanique [Termes IGN] montée du niveau de la mer [Termes IGN] satellite d'observation de la mer [Termes IGN] satellite d'observation de la Terre [Termes IGN] surveillance du littoral [Termes IGN] trait de côte Résumé : (Auteur) Concentré d’enjeux écologiques et sociaux, le littoral est sous la surveillance permanente des satellites. Mais cet objet complexe et changeant se dérobe parfois à l’observation. Numéro de notice : A2022-526 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtSansCL DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101295 [article]

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
063-2022071	SL	Revue	Centre de documentation	Revues en salle	En circulation Exclu du prêt

Plastic waste cleanup priorities to reduce marine pollution: A spatiotemporal analysis for Accra and Lagos with satellite data / Susmita Dasgupta in Science of the total environment, vol 839 (May 2022)  

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Aboveground biomass of salt-marsh vegetation in coastal wetlands: Sample expansion of in situ hyperspectral and Sentinel-2 data using a generative adversarial network / Chen Chen in Remote sensing of environment, vol 270 (March 2022)  

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Monitoring coastal vulnerability by using DEMs based on UAV spatial data / Antonio Minervino Amodio in ISPRS International journal of geo-information, vol 11 n° 3 (March 2022)  

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Apport des nouveaux systèmes GNSS de cartographie du niveau marin à l’exploitation des données altimétriques en zone côtière / Clémence Chupin (2022)  

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Évolution rétrospective et prospective d’un massif dunaire par imagerie multispectrale et LiDAR / Iris Jeuffrard (2022)   

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Historical shoreline analysis and field monitoring at Ennore coastal stretch along the Southeast coast of India / M. Dhananjayan in Marine geodesy, vol 45 n° 1 (January 2022)  

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Modalités et rythmes d'évolution des falaises des Vaches Noires (Normandie, France) : caractérisation et quantification des dynamiques hydrogravitaires par approches multi-scalaires / Thomas Roulland (2022)  

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GIS to identify exposed shoreline sectors to wave impacts: case of El Tarf coast / Abdeldjalil Goumrasa in Applied geomatics, vol 13 n° 4 (December 2021)  

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Diffuse attenuation coefficient (Kd) from ICESat-2 ATLAS spaceborne Lidar using random-forest regression / Forrest Corcoran in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 11 (November 2021)  

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Efficient measurement of large-scale decadal shoreline change with increased accuracy in tide-dominated coastal environments with Google Earth Engine / Yongjing Mao in ISPRS Journal of photogrammetry and remote sensing, Vol 181 (November 2021)  

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