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Brief communication: Glacier mapping and change estimation using very high-resolution declassified Hexagon KH-9 panoramic stereo imagery (1971-1984) / Sajid Ghuffar in The Cryosphere, vol 17 n° 3 (March 2023)  

Public [article]  inThe Cryosphere > vol 17 n° 3 (March 2023) . - pp 1299 - 1306 Titre : Brief communication: Glacier mapping and change estimation using very high-resolution declassified Hexagon KH-9 panoramic stereo imagery (1971-1984) Type de document : Article/Communication Auteurs : Sajid Ghuffar, Auteur ; Owen King, Auteur ; Grégoire Guillet, Auteur ; Ewelina Rupnik , Auteur ; Tobias Bolch, Auteur Année de publication : 2023 Article en page(s) : pp 1299 - 1306 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse diachronique [Termes IGN] glacier [Termes IGN] image Corona [Termes IGN] image panoramique [Termes IGN] image Pléiades-HR [Termes IGN] image SPOT Résumé : (auteur) The panoramic cameras (PCs) on board Hexagon KH-9 (KH-9PC) satellite missions from 1971–1984 captured very high-resolution stereo imagery with up to 60 cm spatial resolution. This study explores the potential of this imagery for glacier mapping and change estimation. We assess KH-9PC imagery using data from the KH-9 mapping camera (KH-9MC), KH-4PC, and SPOT and Pléiades satellite imagery. The high resolution of KH-9PC leads to higher-quality DEMs, which better resolve the accumulation region of the glaciers in comparison to the KH-9MC. On stable terrain, KH-9PC DEMs achieve an elevation accuracy of Numéro de notice : A2023-177 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/tc-17-1299-2023 Date de publication en ligne : 21/03/2023 En ligne : https://doi.org/10.5194/tc-17-1299-2023 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103285 [article]

Artificial intelligence oceanography / Xiaofeng Li (2023)  

Public Titre : Artificial intelligence oceanography Type de document : Monographie Auteurs : Xiaofeng Li, Éditeur scientifique ; Fan Wang, Éditeur scientifique Editeur : Springer Nature Année de publication : 2023 Importance : 346 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-981-19637-5-9 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] algue [Termes IGN] apprentissage profond [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] cyclone [Termes IGN] détection d'objet [Termes IGN] iceberg [Termes IGN] intelligence artificielle [Termes IGN] océanographie [Termes IGN] température de surface de la mer Résumé : (éditeur) This open access book invites readers to learn how to develop artificial intelligence (AI)-based algorithms to perform their research in oceanography. Various examples are exhibited to guide details of how to feed the big ocean data into the AI models to analyze and achieve optimized results. The number of scholars engaged in AI oceanography research will increase exponentially in the next decade. Therefore, this book will serve as a benchmark providing insights for scholars and graduate students interested in oceanography, computer science, and remote sensing. Note de contenu : 1- Artificial Intelligence Foundation of smart ocean 2- Forecasting tropical instability waves based on artificial intelligence 3- Sea surface height anomaly prediction based on artificial intelligence 4- Satellite data-driven internal solitary wave forecast based on machine learning techniques 5- AI-based subsurface thermohaline structure retrieval from remote sensing observations 6- Ocean heat content retrieval from remote sensing data based on machine learning 7- Detecting tropical cyclogenesis using broad learning system from satellite passive microwave observations 8- Tropical cyclone monitoring based on geostationary satellite imagery 9- Reconstruction of pCO2 data in the Southern ocean based on feedforward neural network 10- Detection and analysis of mesoscale eddies based on deep learning 11- Deep convolutional neural networks-based coastal inundation mapping from SAR imagery: with one application case for Bangladesh, a UN-defined least developed country 12- Sea ice detection from SAR images based on deep fully convolutional networks 13- Detection and analysis of marine green algae based on artificial intelligence 14- Automatic waterline extraction of large-scale tidal flats from SAR images based on deep convolutional neural networks 15- Extracting ship’s size from SAR images by deep learning 16- Benthic organism detection, quantification and seamount biology detection based on deep learning Numéro de notice : 24105 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Monographie DOI : 10.1007/978-981-19-6375-9 En ligne : https://link.springer.com/book/10.1007/978-981-19-6375-9 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103058

Decadal surface changes and displacements in Switzerland / Valentin Tertius Bickel in Journal of Geovisualization and Spatial Analysis, vol 6 n° 2 (December 2022)  

Public [article]  inJournal of Geovisualization and Spatial Analysis > vol 6 n° 2 (December 2022) . - n° 24 Titre : Decadal surface changes and displacements in Switzerland Type de document : Article/Communication Auteurs : Valentin Tertius Bickel, Auteur ; Andrea Manconi, Auteur Année de publication : 2022 Article en page(s) : n° 24 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] corrélation d'images [Termes IGN] détection de changement [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] données multitemporelles [Termes IGN] effondrement de terrain [Termes IGN] géomorphologie locale [Termes IGN] glacier [Termes IGN] Liechtenstein [Termes IGN] modèle numérique de terrain [Termes IGN] stéréophotogrammétrie [Termes IGN] Suisse Résumé : (auteur) Multi-temporal, high-resolution, and homogeneous geospatial datasets acquired by space- and/or airborne sensors provide unprecedented opportunities for the characterization and monitoring of surface changes on very large spatial scales. Here, we demonstrate how an off-the-shelf, open-source image correlation algorithm can be combined with SwissALTI3D LiDAR-derived elevation data from different tracking periods to create country-scale surface displacement and vertical change maps of Switzerland, including Liechtenstein, with minimal computational effort. The results show that glacier displacement and ablation make up the most significant fraction of the detected surface changes in the last two decades. In addition, we identify numerous landslides and other geomorphic features, as well as manmade changes such as construction sites and landfills. All produced maps and data products are available online, free of charge. Numéro de notice : A2022-832 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s41651-022-00119-9 Date de publication en ligne : 01/08/2022 En ligne : https://doi.org/10.1007/s41651-022-00119-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102019 [article]

Large-area high spatial resolution albedo retrievals from remote sensing for use in assessing the impact of wildfire soot deposition on high mountain snow and ice melt / André Bertoncini in Remote sensing of environment, vol 278 (September 2022)  

Public [article]  inRemote sensing of environment > vol 278 (September 2022) . - n° 113101 Titre : Large-area high spatial resolution albedo retrievals from remote sensing for use in assessing the impact of wildfire soot deposition on high mountain snow and ice melt Type de document : Article/Communication Auteurs : André Bertoncini, Auteur ; Caroline Aubry-Wake, Auteur ; John W. Pomeroy, Auteur Année de publication : 2022 Article en page(s) : n° 113101 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] albedo [Termes IGN] Colombie-Britannique (Canada) [Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF [Termes IGN] fonte des glaces [Termes IGN] glacier [Termes IGN] Google Earth Engine [Termes IGN] image Sentinel-MSI [Termes IGN] image SRTM [Termes IGN] image Terra-MODIS [Termes IGN] incendie de forêt [Termes IGN] montagne [Termes IGN] neige [Termes IGN] pouvoir de résolution radiométrique Résumé : (auteur) Soot deposition from wildfires decreases snow and ice albedo and increases the absorption of shortwave radiation, which advances and accelerates melt. Soot deposition also induces algal growth, which further decreases snow and ice albedo. In recent years, increasingly severe and widespread wildfire activity has occurred in western Canada in association with climate change. In the summers of 2017 and 2018, westerly winds transported smoke from extensive record-breaking wildfires in British Columbia eastward to the Canadian Rockies, where substantial amounts of soot were deposited on high mountain glaciers, snowfields, and icefields. Several studies have addressed the problem of soot deposition on snow and ice, but the spatiotemporal resolution applied has not been compatible with studying mountain icefields that are extensive but contain substantial internal variability and have dynamical albedos. This study evaluates spatial patterns in the albedo decrease and net shortwave radiation (K*) increase caused by soot from intense wildfires in Western Canada deposited on the Columbia Icefield (151 km2), Canadian Rockies, during 2017 and 2018. Twelve Sentinel-2 images were used to generate high spatial resolution albedo retrievals during four summers (2017 to 2020) using a MODIS bidirectional reflectance distribution function (BRDF) model, which was employed to model the snow and ice reflectance anisotropy. Remote sensing estimates were evaluated using site-measured albedo on the icefield's Athabasca Glacier tongue, resulting in a R2, mean bias, and root mean square error (RMSE) of 0.68, 0.019, and 0.026, respectively. The biggest inter-annual spatially averaged soot-induced albedo declines were of 0.148 and 0.050 (2018 to 2020) for southeast-facing glaciers and the snow plateau, respectively. The highest inter-annual spatially-averaged soot-induced shortwave radiative forcing was 203 W/m2 for southeast-facing glaciers (2018 to 2020) and 106 W/m2 for the snow plateau (2017 to 2020). These findings indicate that snow albedo responded rapidly to and recovered rapidly from soot deposition. However, ice albedo remained low the year after fire, and this was likely related to a bio-albedo feedback involving microorganisms. Snow and ice K* were highest during low albedo years, especially for south-facing glaciers. These large-scale effects accelerated melt of the Columbia Icefield. The findings highlight the importance of using large-area high spatial resolution albedo estimates to analyze the effect of wildfire soot deposition on snow and ice albedo and K* on icefields, which is not possible using other approaches. Numéro de notice : A2022-466 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rse.2022.113101 Date de publication en ligne : 30/05/2022 En ligne : https://doi.org/10.1016/j.rse.2022.113101 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100800 [article]

A pipeline for automated processing of Corona KH-4 (1962-1972) stereo imagery / Sajid Ghuffar in IEEE Transactions on geoscience and remote sensing, vol 60 n° 8 (August 2022)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 60 n° 8 (August 2022) . - pp Titre : A pipeline for automated processing of Corona KH-4 (1962-1972) stereo imagery Type de document : Article/Communication Auteurs : Sajid Ghuffar, Auteur ; Tobias Bolch, Auteur ; Ewelina Rupnik , Auteur ; Atanu Bhattacharya, Auteur Année de publication : 2022 Article en page(s) : pp Note générale : bibliographie voir aussi https://research-repository.st-andrews.ac.uk/bitstream/10023/26124/1/Ghuffar_2022_IEEE_TGRS_Pipeline_automated_processing_AAM.pdf Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] appariement d'images [Termes IGN] apprentissage profond [Termes IGN] chaîne de traitement [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] compensation par faisceaux [Termes IGN] géométrie de l'image [Termes IGN] géométrie épipolaire [Termes IGN] glacier [Termes IGN] Himalaya [Termes IGN] image Corona [Termes IGN] image panoramique [Termes IGN] MNS SRTM [Termes IGN] modèle numérique de surface [Termes IGN] modèle stéréoscopique [Termes IGN] point d'appui Résumé : (auteur) The Corona KH-4 reconnaissance satellite missions from 1962-1972 acquired panoramic stereo imagery with high spatial resolution of 1.8-7.5 m. The potential of 800,000+ declassified Corona images has not been leveraged due to the complexities arising from handling of panoramic imaging geometry, film distortions and limited availability of the metadata required for georeferencing of the Corona imagery. This paper presents Corona Stereo Pipeline (CoSP): A pipeline for processing of Corona KH-4 stereo panoramic imagery. CoSP utlizes a deep learning based feature matcher SuperGlue to automatically match features point between Corona KH-4 images and recent satellite imagery to generate Ground Control Points (GCPs). To model the imaging geometry and the scanning motion of the panoramic KH-4 cameras, a rigorous camera model consisting of modified collinearity equations with time dependent exterior orientation parameters is employed. The results show that using the entire frame of the Corona image, bundle adjustment using well-distributed GCPs results in an average standard deviation (SD) of less than 2 pixels. We evaluate fiducial marks on the Corona films and show that pre-processing the Corona images to compensate for film bending improves the accuracy. We further assess a polynomial epipolar resampling method for rectification of Corona stereo images. The distortion pattern of image residuals of GCPs and y-parallax in epipolar resampled images suggest that film distortions due to long term storage as likely cause of systematic deviations. Compared to the SRTM DEM, the Corona DEM computed using CoSP achieved a Normalized Median Absolute Deviation (NMAD) of elevation differences of ? 4m over an area of approx. 4000km2. We show that the proposed pipeline can be applied to sequence of complex scenes involving high relief and glacierized terrain and that the resulting DEMs can be used to compute long term glacier elevation changes over large areas. Numéro de notice : A2022-952 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : vers ArXiv Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2022.3200151 Date de publication en ligne : 19/08/2022 En ligne : https://doi.org/10.1109/TGRS.2022.3200151 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103286 [article]

Glacier mass loss in the Alaknanda basin, Garhwal Himalaya on a decadal scale / S.N. Remya in Geocarto international, vol 37 n° 10 ([01/06/2022])  

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Applications and challenges of GRACE and GRACE follow-on satellite gravimetry / Jianli Chen in Surveys in Geophysics, vol 43 n° 1 (February 2022)  

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Fast local adaptive multiscale image matching algorithm for remote sensing image correlation / Niccolò Dematteis in Computers & geosciences, vol 159 (February 2022)  

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Global and climate challenges, graph-based data analysis for multisource information extraction / Morgane Batelier (2022) 

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Global glacier mass change by spatiotemporal analysis of digital elevation models / Romain Hugonnet (2022)  

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Simulation of the meltwater under different climate change scenarios in a poorly gauged snow and glacier-fed Chitral River catchment (Hindukush region) / Huma Hayat in Geocarto international, vol 37 n° 1 ([01/01/2022])  

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Studying informativeness of satellite image texture for sea ice state retrieval using deep learning methods / Clément Fougerouse (2022) 

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Le Mont-Blanc mesuré au LiDAR héliporté / Mathieu Peyréga in XYZ, n° 169 (décembre 2021)

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Snow cover change assessment in the upper Bhagirathi basin using an enhanced cloud removal algorithm / Mritunjay Kumar Singh in Geocarto international, vol 36 n° 20 ([01/12/2021])  

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4 807,81 m, le sommet décline / Anonyme in Géomètre, n° 2195 (octobre 2021)

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