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Effects of offsets and outliers on the sea level trend at Antalya 2 tide gauge within the Eastern Mediterranean Sea / Mehmet Emin Ayhan in Marine geodesy, vol 45 n° 4 (July 2022)  

Public [article]  inMarine geodesy > vol 45 n° 4 (July 2022) . - pp 329 - 359 Titre : Effects of offsets and outliers on the sea level trend at Antalya 2 tide gauge within the Eastern Mediterranean Sea Type de document : Article/Communication Auteurs : Mehmet Emin Ayhan, Auteur Année de publication : 2022 Article en page(s) : pp 329 - 359 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Nivellement [Termes IGN] autocorrélation [Termes IGN] correction [Termes IGN] marégraphe [Termes IGN] Méditerranée, mer [Termes IGN] modèle statistique [Termes IGN] niveau de la mer [Termes IGN] niveau moyen des mers [Termes IGN] Turquie [Termes IGN] valeur aberrante [Termes IGN] variation saisonnière Résumé : (auteur) Antalya 2 tide gauge (TG) station is located on the coast of Turkey within the Eastern Mediterranean Sea. Relative sea level trends 6.0 ± 1.5 and 6.44 ± 0.45 mm/year over 1985–2009 at Antalya 2 TG are different from the trend (1.6 ± 1.5 mm/year over 1935–1977) at Antalya TG within 10 km. In order to investigate this trend discrepancy, the monthly mean series at Antalya 2 TG is re-analyzed for offsets, outliers and trend estimation. The Zivot-Andrews method and the Qp outlier test result in one offset at 1994.0417 year with magnitude of 71.24 ± 13.48 mm and nine outliers. The series, corrected for the offset and outliers, de-seasonalized and filled for missed points, is identified as trend-stationary process and analyzed for trend estimation by various models. The optimal model providing the lowest Akaike Information Criteria is polynomial linear trend with multiplicative seasonal Autoregressive Moving Average (ARMA(2,0)x(1,0)12). The estimated relative sea level trend by the optimal model is 1.77 ± 0.65 mm/year. The large trend discrepancy at Antalya 2 TG is accounted for by one offset primarily (∼71%) and nine outliers (∼3%). Numéro de notice : A2022-516 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1080/01490419.2022.2047843 Date de publication en ligne : 11/03/2022 En ligne : https://doi.org/10.1080/01490419.2022.2047843 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101064 [article]

On the consistency of coastal sea-level measurements in the Mediterranean Sea from tide gauges and satellite radar altimetry / Sara Bruni in Journal of geodesy, vol 96 n° 6 (June 2022)  

Public [article]  inJournal of geodesy > vol 96 n° 6 (June 2022) . - n° 41 Titre : On the consistency of coastal sea-level measurements in the Mediterranean Sea from tide gauges and satellite radar altimetry Type de document : Article/Communication Auteurs : Sara Bruni, Auteur ; Luciana Fenoglio, Auteur ; Fabio Raicich, Auteur ; Susanna Zerbini, Auteur Année de publication : 2022 Article en page(s) : n° 41 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes IGN] analyse comparative [Termes IGN] cohérence des données [Termes IGN] déformation verticale de la croute terrestre [Termes IGN] données altimétriques [Termes IGN] données marégraphiques [Termes IGN] Méditerranée, mer [Termes IGN] niveau de la mer Résumé : (auteur) We assess the consistency of sea-level variability derived from tide-gauge (TG) and satellite radar altimeter (ALT) data acquired along the coasts of the Mediterranean Sea. For a coherent comparison between these techniques, we use GNSS observations to characterize the local vertical land movement embedded in TG records, but not affecting ALT data. We first investigate the performance of CMEMS, a gridded altimeter product covering the period 1993–2019. TG and GNSS series are not required to cover the whole altimeter period. The inter-technique comparison reveals good agreement at annual and semi-annual scales, but also the occasional occurrence of nonlinear discrepancies impacting trend estimation. Large-scale patterns of variability are observed in the Ionian region and along the continental shores from the Alboran to the Adriatic Sea. The estimates of linear trends based on TG + GNSS or CMEMS observations are found consistent within 1σ at 27/45 sites, with the best agreement in the Western Mediterranean and Adriatic Seas. We also consider the X-TRACK/ALES altimeter dataset, provided along the tracks of the Jason missions (2002–2018) and optimized for coastal applications. In this case, we identify only 12 sites suitable for the comparison. The results show that inter-technique consistency is impacted by the length of the series used in the comparison. Optimum agreement between X-TRACK/ALES and TG + GNSS trends is reached at the two sites closer to a satellite track. However, we find sites where X-TRACK/ALES-derived sea-level trends present suspicious along-track variations at  Numéro de notice : A2022-452 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s00190-022-01626-9 En ligne : http://dx.doi.org/10.1007/s00190-022-01626-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100976 [article]

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)  

Public [article]  inISPRS International journal of geo-information > vol 11 n° 3 (March 2022) . - n° 155 Titre : Monitoring coastal vulnerability by using DEMs based on UAV spatial data Type de document : Article/Communication Auteurs : Antonio Minervino Amodio, Auteur ; Gianluigi Di Paola, Auteur ; Carmen Maria Rosskopf, Auteur Année de publication : 2022 Article en page(s) : n° 155 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] Adriatique, mer [Termes IGN] détection de changement [Termes IGN] érosion côtière [Termes IGN] géoréférencement [Termes IGN] image captée par drone [Termes IGN] Italie [Termes IGN] littoral méditerranéen [Termes IGN] modèle numérique de surface [Termes IGN] orthophotographie [Termes IGN] point d'appui [Termes IGN] structure-from-motion [Termes IGN] surveillance du littoral [Termes IGN] trait de côte [Termes IGN] vulnérabilité Résumé : (auteur) The use of Unmanned Aerial Vehicles (UAVs) represents a rather innovative, quick, and low-cost methodological approach offering applications in several fields of investigation. The present study illustrates the developed method using Digital Elevation Models (DEMs) based on UAV-derived data for evaluating short-term morphological-topographic changes of the beach system and related implications for coastal vulnerability assessment. UAV surveys were performed during the summers of 2019 and 2020 along a beach stretch affected by erosion, located along the central Adriatic coast. Acquired high-resolution aerial photos were used to generate large-scale DEMs as well as orthophotos of the beach using the Structure from Motion (SfM) image processing tool. Comparison of the generated 2019 and 2020 DEMs highlighted significant morphological changes and a sediment volume loss of about 780 m3 within a surface area of about 4400 m2. Based on 20 m spaced beach profiles derived from the DEMs, a coastal vulnerability assessment was performed using the CVA approach that highlighted some significant variations in the CVA index between 2019 and 2020. Results evidence that UAV surveys provide high-resolution topographic data, suitable for specific beach monitoring activities and the updating of some parameters that enter in the CVA model contributing to its correct application. Numéro de notice : A2022-185 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi11030155 Date de publication en ligne : 22/02/2022 En ligne : https://doi.org/10.3390/ijgi11030155 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99895 [article]

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 IGN] Adriatique, mer [Termes IGN] bathymétrie [Termes IGN] chlorophylle [Termes IGN] correction atmosphérique [Termes IGN] couleur de l'océan [Termes IGN] eaux côtières [Termes IGN] image Sentinel-MSI [Termes IGN] incertitude spectrale [Termes IGN] matière organique [Termes IGN] Méditerranée, mer [Termes 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]

Assessment of chlorophyll-a concentration from Sentinel-3 satellite images at the Mediterranean Sea using CMEMS open source in situ data / Ioannis Moutzouris-Sidiris in Open geosciences, vol 13 n° 1 (January 2021)  

Public [article]  inOpen geosciences > vol 13 n° 1 (January 2021) . - pp 85 - 97 Titre : Assessment of chlorophyll-a concentration from Sentinel-3 satellite images at the Mediterranean Sea using CMEMS open source in situ data Type de document : Article/Communication Auteurs : Ioannis Moutzouris-Sidiris, Auteur ; Konstantinos Topouzelis, Auteur Année de publication : 2021 Article en page(s) : pp 85 - 97 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse comparative [Termes IGN] chlorophylle [Termes IGN] classification par réseau neuronal [Termes IGN] couleur de l'océan [Termes IGN] image Envisat-MERIS [Termes IGN] image Sentinel-3 [Termes IGN] image Sentinel-OLCI [Termes IGN] Méditerranée, mer Résumé : (auteur) The objective of this study is to evaluate the efficiency of two well-known algorithms (Ocean Colour 4 for MERIS [OC4Me] and neural net [NN]) used in the calculation of chlorophyll-a (Chl-a) from the Sentinel-3 Ocean and Land Colour Instrument (OLCI) compared to in situ measurements covering the Mediterranean Sea. In situ data set, obtained from the Copernicus Marine Environmental Monitoring Service (CMEMS) and more specifically from the data set with the title INSITU_MED_NRT_OBSERVATIONS_013_035, and Chl-a values at different depths were extracted. The concentration of Chl-a at a penetration depth was calculated. Then, water was classified into two categories, Case-1 and Case-2. For Case-2 waters, the OC4Me presents a moderate correlation with the in situ data for a time window of 0–2 h. In contrast with the NN algorithm, where very weak correlations were calculated, lower values of the statistical index of Bias for Case-1 waters were calculated for the OC4Me algorithm. Higher values of Pearson correlation were calculated (r > 0.5) for OC4Me algorithm than NN. OC4Me performed better than NN. Numéro de notice : A2021-487 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1515/geo-2020-0204 Date de publication en ligne : 29/01/2021 En ligne : https://doi.org/10.1515/geo-2020-0204 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97776 [article]

Modélisation de l’aire de réception d’une antenne AIS en fonction de données d’altitude et de cartes de prévision de propagation d’ondes VHF / Zackary Vanche (2021) 

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Développement de la photogrammétrie et d'analyses d'images pour l'étude et le suivi d'habitats marins / Guilhem Marre (2020)  

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The AROME-WMED reanalyses of the first special observation period of the Hydrological cycle in the Mediterranean experiment (HyMeX) / Nadia Fourrié in Geoscientific Model Development, vol 12 n° 7 (July 2019)  

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Sea surface salinity remote sensing / Emmanuel P. Dinnat (2019)  

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Multi‐scale observations of atmospheric moisture variability in relation to heavy precipitating systems in the northwestern Mediterranean during HyMeX IOP12 / Samiro Khodayar in Quarterly Journal of the Royal Meteorological Society, vol 144 n° 717 (October 2018 Part B)  

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Improving the analysis of biogeochemical patterns associated with internal waves in the strait of Gibraltar using remote sensing images / Gabriel Navarro in Estuarine, Coastal and Shelf Science, vol 204 (May 2018)  

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Mass evolution of Mediterranean, Black, Red, and Caspian Seas from GRACE and altimetry : accuracy assessment and solution calibration / B. D. Loomis in Journal of geodesy, vol 91 n° 2 (February 2017)  

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A high-quality reprocessed ground-based GPS dataset for atmospheric process studies, radiosonde and model evaluation, and reanalysis of HyMeX Special Observing Period / Olivier Bock in Quarterly Journal of the Royal Meteorological Society, vol 142 n° S1 (August 2016)  

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The Costa Concordia last cruise: The first application of high frequency monitoring based on COSMO-SkyMed constellation for wreck removal / Andrea Ciampalini in ISPRS Journal of photogrammetry and remote sensing, vol 112 (February 2016)  

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Water vapor measurements by mobile Raman lidar over the Mediterranean Sea in the framework of HyMeX: application to multi-platform validation of moisture profiles / Julien Totems in EPJ Web of Conferences, vol 119 (2016)  

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