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Coastal water remote sensing from sentinel-2 satellite data using physical, statistical, and neural network retrieval approach / Frank S. Marzano in IEEE Transactions on geoscience and remote sensing, vol 59 n° 2 (February 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 59 n° 2 (February 2021) . - pp 915 - 928 Titre : Coastal water remote sensing from sentinel-2 satellite data using physical, statistical, and neural network retrieval approach Type de document : Article/Communication Auteurs : Frank S. Marzano, Auteur ; Michele Iacobelli, Auteur ; Massimo Orlandi, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 915 - 928 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] Adriatique, mer [Termes descripteurs IGN] bathymétrie [Termes descripteurs IGN] chlorophylle [Termes descripteurs IGN] correction atmosphérique [Termes descripteurs IGN] couleur de l'océan [Termes descripteurs IGN] eaux côtières [Termes descripteurs IGN] image Sentinel-MSI [Termes descripteurs IGN] incertitude spectrale [Termes descripteurs IGN] matière organique [Termes descripteurs IGN] Méditerranée, mer [Termes descripteurs IGN] réseau neuronal artificiel Résumé : (auteur) Recent optical remote sensing satellite missions, such as Sentinel-2 with the MultiSpectral Imager (MSI) onboard, allow the estimation of coastal water key parameters with very high spatial resolutions (down to 10 m). In this article, multiple approaches are proposed for retrieving chlorophyll-a (Chl-a) and total suspended matter (TSM) along the Adriatic and Tyrrhenian coasts in Italy, using both empirical and model-based frameworks to design regressive and neural network (NN) estimation methods. The latter proves to be more accurate on a regional scale, where standard ocean color physical models exhibit high uncertainty in their local parameterization due to the complex spectral characteristics of the observed scene. Retrieval results are encouraging for Chl-a with a coefficient of determination R2 up to 0.72 with a root-mean-square error (RMSE) of 0.33 mg m−3 , using an empirical NN. The TSM algorithms exhibit higher uncertainty, mainly due to scarcity of in situ measurements and model parameterizations, with R2=0.52 and RMSE = 1.95 g/m 3 using NNs. The bio-optical model, used for the development of model-based algorithms, shows some inadequacies in representing the inherent and apparent optical properties for the case study areas, especially considering the different spectral features between the oligotrophic Tyrrhenian Sea and the eutrophic Adriatic Sea. This study confirms the potential of Sentinel-2 MSI products for coastal water monitoring, but it also highlights key issues to be further tackled such as the atmospheric correction impact, the need of reliable in situ measurements, and possible bathymetry effects near the shores. Numéro de notice : A2021-110 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2980941 date de publication en ligne : 09/12/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2980941 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96912 [article]

Using sentinel-2 images to estimate topography, tidal-stage lags and exposure periods over large intertidal areas / José P. Granadeiro in Remote sensing, Vol 13 n° 2 (January 2021)  

Public [article]  inRemote sensing > Vol 13 n° 2 (January 2021) . - n° 320 Titre : Using sentinel-2 images to estimate topography, tidal-stage lags and exposure periods over large intertidal areas Type de document : Article/Communication Auteurs : José P. Granadeiro, Auteur ; João Belo, Auteur ; Mohamed Henriques, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 320 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] bathymétrie [Termes descripteurs IGN] carte bathymétrique [Termes descripteurs IGN] écosystème [Termes descripteurs IGN] estran [Termes descripteurs IGN] Guinée-Bissao [Termes descripteurs IGN] habitat (nature) [Termes descripteurs IGN] image Sentinel-MSI [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] régression logistique [Termes descripteurs IGN] topographie locale Résumé : (auteur) Intertidal areas provide key ecosystem services but are declining worldwide. Digital elevation models (DEMs) are important tools to monitor the evolution of such areas. In this study, we aim at (i) estimating the intertidal topography based on an established pixel-wise algorithm, from Sentinel-2 MultiSpectral Instrument scenes, (ii) implementing a set of procedures to improve the quality of such estimation, and (iii) estimating the exposure period of the intertidal area of the Bijagós Archipelago, Guinea-Bissau. We first propose a four-parameter logistic regression to estimate intertidal topography. Afterwards, we develop a novel method to estimate tide-stage lags in the area covered by a Sentinel-2 scene to correct for geographical bias in topographic estimation resulting from differences in water height within each image. Our method searches for the minimum differences in height estimates obtained from rising and ebbing tides separately, enabling the estimation of cotidal lines. Tidal-stage differences estimated closely matched those published by official authorities. We re-estimated pixel heights from which we produced a model of intertidal exposure period. We obtained a high correlation between predicted and in-situ measurements of exposure period. We highlight the importance of remote sensing to deliver large-scale intertidal DEM and tide-stage data, with relevance for coastal safety, ecology and biodiversity conservation. Numéro de notice : A2021-197 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/IMAGERIE Nature : Article DOI : 10.3390/rs13020320 date de publication en ligne : 19/01/2021 En ligne : https://doi.org/10.3390/rs13020320 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97148 [article]

Determination of the under water position of objects by reflectorless total stations / Štefan Rákay in Survey review, vol 53 n°376 (January 2021)  

Public [article]  inSurvey review > vol 53 n°376 (January 2021) . - pp 35 - 43 Titre : Determination of the under water position of objects by reflectorless total stations Type de document : Article/Communication Auteurs : Štefan Rákay, Auteur ; Slavomír Labant, Auteur ; Karol Bartoš, Auteur Année de publication : 2021 Article en page(s) : pp 35 - 43 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bathymétrie [Termes descripteurs IGN] bathymétrie laser [Termes descripteurs IGN] erreur géométrique [Termes descripteurs IGN] lever bathymétrique [Termes descripteurs IGN] mesurage électronique de distances [Termes descripteurs IGN] objet [Termes descripteurs IGN] onde électromagnétique [Termes descripteurs IGN] réfraction de l'eau [Termes descripteurs IGN] scène sous-marine [Termes descripteurs IGN] tachéomètre électronique [Termes descripteurs IGN] vitesse Résumé : (auteur) When surveying through a water surface, a distortion of several centimetres caused by the refraction and the change in the velocity of the electromagnetic waves can be observed. Therefore, neither the position nor the height of an underwater point (object), which can be seen from above the water surface, is correctly measured. The authors want to point out the magnitude of geometric errors when measuring to points under water as well as the computation of correct under water positions of points from measurement through a water layer. A practical experiment was performed for a water depth of 0.16 m. Numéro de notice : A2021-048 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2019.1683488 date de publication en ligne : 03/11/2019 En ligne : https://doi.org/10.1080/00396265.2019.1683488 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96783 [article]

The Influence of camera calibration on nearshore bathymetry estimation from UAV Vvdeos / Gonzalo Simarro in Remote sensing, vol 13 n° 1 (January 2021)  

Public [article]  inRemote sensing > vol 13 n° 1 (January 2021) . - n° 150 Titre : The Influence of camera calibration on nearshore bathymetry estimation from UAV Vvdeos Type de document : Article/Communication Auteurs : Gonzalo Simarro, Auteur ; Daniel Calvete, Auteur ; Theocharis A. Plomaritis, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 150 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes descripteurs IGN] aberration instrumentale [Termes descripteurs IGN] bathymétrie [Termes descripteurs IGN] distorsion d'image [Termes descripteurs IGN] eaux côtières [Termes descripteurs IGN] étalonnage de chambre métrique [Termes descripteurs IGN] étalonnage en vol [Termes descripteurs IGN] image captée par drone [Termes descripteurs IGN] lentille [Termes descripteurs IGN] réalité de terrain [Termes descripteurs IGN] sondeur monofaisceau Résumé : (auteur) Measuring the nearshore bathymetry is critical in coastal management and morphodynamic studies. The recent advent of Unmanned Aerial Vehicles (UAVs), in combination with coastal video monitoring techniques, allows for an alternative and low cost evaluation of the nearshore bathymetry. Camera calibration and stabilization is a critical issue in bathymetry estimation from video systems. This work introduces a new methodology in order to obtain such bathymetries, and it compares the results to echo-sounder ground truth data. The goal is to gain a better understanding on the influence of the camera calibration and stabilization on the inferred bathymetry. The results show how the proposed methodology allows for accurate evaluations of the bathymetry, with overall root mean square errors in the order of 40 cm. It is shown that the intrinsic calibration of the camera, related to the lens distortion, is the most critical aspect. Here, the intrinsic calibration that was obtained directly during the flight yields the best results. Numéro de notice : A2021-076 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13010150 date de publication en ligne : 05/01/2021 En ligne : https://doi.org/10.3390/rs13010150 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96814 [article]

Underwater object detection and reconstruction based on active single-pixel imaging and super-resolution convolutional neural network / Mengdi Li in Sensors, vol 21 n° 1 (January 2021)  

Public [article]  inSensors > vol 21 n° 1 (January 2021) . - n° 313 Titre : Underwater object detection and reconstruction based on active single-pixel imaging and super-resolution convolutional neural network Type de document : Article/Communication Auteurs : Mengdi Li, Auteur ; Anumoi Mathai, Auteur ; Stephen L. H. Lau, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 313 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] approche pixel [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] détection d'objet [Termes descripteurs IGN] fond marin [Termes descripteurs IGN] rapport signal sur bruit [Termes descripteurs IGN] reconstruction d'image [Termes descripteurs IGN] reconstruction d'objet Résumé : (auteur) Due to medium scattering, absorption, and complex light interactions, capturing objects from the underwater environment has always been a difficult task. Single-pixel imaging (SPI) is an efficient imaging approach that can obtain spatial object information under low-light conditions. In this paper, we propose a single-pixel object inspection system for the underwater environment based on compressive sensing super-resolution convolutional neural network (CS-SRCNN). With the CS-SRCNN algorithm, image reconstruction can be achieved with 30% of the total pixels in the image. We also investigate the impact of compression ratios on underwater object SPI reconstruction performance. In addition, we analyzed the effect of peak signal to noise ratio (PSNR) and structural similarity index (SSIM) to determine the image quality of the reconstructed image. Our work is compared to the SPI system and SRCNN method to demonstrate its efficiency in capturing object results from an underwater environment. The PSNR and SSIM of the proposed method have increased to 35.44% and 73.07%, respectively. This work provides new insight into SPI applications and creates a better alternative for underwater optical object imaging to achieve good quality. Numéro de notice : A2021-158 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/s21010313 date de publication en ligne : 05/01/2021 En ligne : https://doi.org/10.3390/s21010313 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97073 [article]

Shallow water bathymetry derived from green wavelength terrestrial laser scanner / Theodore Panagou in Marine geodesy, Vol 43 n° 5 (September 2020)  

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Can ensemble techniques improve coral reef habitat classification accuracy using multispectral data? / Mohammad Shawkat Hossain in Geocarto international, vol 35 n° 11 ([01/08/2020])  

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Long time-series remote sensing analysis of the periodic cycle evolution of the inlets and ebb-tidal delta of Xincun Lagoon, Hainan Island, China / Huaguo Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 165 (July 2020)  

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Improving GNSS-acoustic positioning by optimizing the ship’s track lines and observation combinations / Guanxu Chen in Journal of geodesy, vol 94 n° 6 (June 2020)  

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Filtering of airborne LiDAR bathymetry based on bidirectional cloth simulation / Anxiu Yang in ISPRS Journal of photogrammetry and remote sensing, vol 163 (May 2020)  

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Applying iterative method to solving high-order terms of seafloor topography / Diao Fan in Marine geodesy, Vol 43 n° 1 (January 2020)  

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Photogrammetric Bathymetry for the Canadian Arctic / Matus Hodul in Marine geodesy, Vol 43 n° 1 (January 2020)  

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Uso de QGIS en la teledetección, Vol. 4. QGIS y sus aplicaciones en agua y en gestion del riego / Nicolas Baghdadi (2020)

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sUAS-based remote rensing of river discharge using thermal particle image velocimetry and bathymetric lidar / Paul J. Kinzel in Remote sensing, vol 11 n° 19 (October 2019)  

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Evolution des techniques topographiques à EDF depuis les 40 dernières années / Rémy Boudon in XYZ, n° 160 (septembre 2019)

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