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Identification of alpine glaciers in the central Himalayas using fully polarimetric L-Band SAR data / Guo-Hui Yao in IEEE Transactions on geoscience and remote sensing, vol 58 n° 1 (January 2020)
[article]
Titre : Identification of alpine glaciers in the central Himalayas using fully polarimetric L-Band SAR data Type de document : Article/Communication Auteurs : Guo-Hui Yao, Auteur ; Chang-qing Ke, Auteur ; Xiaobing Zhou, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 691 - 703 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse multiéchelle
[Termes IGN] bande L
[Termes IGN] classification orientée objet
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] données polarimétriques
[Termes IGN] échantillonnage
[Termes IGN] glacier
[Termes IGN] Himalaya
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image Landsat-OLI
[Termes IGN] image radar moirée
[Termes IGN] interferométrie différentielle
[Termes IGN] matrice de covariance
[Termes IGN] précision de la classification
[Termes IGN] segmentationRésumé : (auteur) To study the applicability of full polarimetric synthetic aperture radar (SAR) data to identify alpine glaciers in the central Himalayas, six polarimetric decomposition methods were used to obtain 20 polarimetric characteristic parameters based on the Advanced Land Observing Satellite 2 (ALOS-2) Phased Array type L-band SAR (PALSAR) data. Object-oriented multiscale segmentation was performed on a Landsat 8 Operational Land Imager (OLI) image prior to classification, and the vector boundaries of different types of training samples were selected from the segmented results. We performed a support vector machine (SVM)-based classification on the characteristic parameters from each polarimetric decomposition. All 20 parameters were then screened and combined according to different requirements: the degree of separability of different types of training samples and the type of scattering mechanisms. The results show that the classification accuracy of the incoherent decomposition characteristics based on the covariance matrix is the best, reaching 87%, and it can exceed 91% after adding the local incidence angle to the suite of classifiers. Eventually, more than 93% accuracy was achieved using a combination of multiple polarimetric parameters, which reduced the misclassification between bare ice and rock. We also analyzed the use of controlling factors on the accuracy of alpine glacier identification and found that the polarimetric information and aspect of the glacier surface are the most important factors. The former is the main basis for identification but the latter will confuse the feature distributions of different categories and cause misclassification. Numéro de notice : A2020-077 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2939430 Date de publication en ligne : 25/09/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2939430 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94613
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 1 (January 2020) . - pp 691 - 703[article]Impact of GPS processing on the estimation of snow water equivalent using refracted GPS signals / Ladina Steiner in IEEE Transactions on geoscience and remote sensing, vol 58 n° 1 (January 2020)
[article]
Titre : Impact of GPS processing on the estimation of snow water equivalent using refracted GPS signals Type de document : Article/Communication Auteurs : Ladina Steiner, Auteur ; Michael Meindl, Auteur ; Christoph Marty, Auteur ; Alain Geiger, Auteur Année de publication : 2020 Article en page(s) : pp 123 - 135 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] Alpes
[Termes IGN] altitude
[Termes IGN] antenne GPS
[Termes IGN] eau de fonte
[Termes IGN] étalonnage des données
[Termes IGN] manteau neigeux
[Termes IGN] modèle hydrographique
[Termes IGN] neige
[Termes IGN] phase GPS
[Termes IGN] pondération
[Termes IGN] réfraction
[Termes IGN] signal GPS
[Termes IGN] SuisseRésumé : (auteur) Global navigation satellite system (GNSS) antennas buried underneath a snowpack have a high potential for in situ snow water equivalent (SWE) estimation. Automated and continuous SWE quantification independent of weather conditions could enhance snow hydrological monitoring and modeling. Accurate and reliable in situ data are needed for the calibration and validation of remote sensing data and snowpack modeling. A relative bias of less than 5% is achieved using sub-snow global positioning system (GPS) antennas (GPS refractometry) during a three full seasons time period in the Swiss Alps. A systematic overview regarding the temporal reliability of the sub-snow GPS derived results is, however, missing for this emerging technique. Moreover, GPS processing impacts the results significantly. Different GPS processing parameters are therefore selected and their influence on the SWE estimation is investigated. The impact of elevation-dependent weighting, the elevation cutoff angles, and the time intervals for SWE estimation are systematically assessed. The best results are achieved using all observations with an elevation-dependent weighting scheme. Moreover, the SWE estimation performance is equally accurate for hourly SWE estimation as for lower temporal resolutions up to daily estimates. The impact of snow on the coordinate solution is furthermore evaluated. While the east and north components are not systematically influenced by the overlying snowpack, the vertical component exhibits a significant variation and strongly depends on the SWE. The biased vertical component therefore provides an additional possibility to estimate SWE. Numéro de notice : A2020-074 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2934016 Date de publication en ligne : 06/09/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2934016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94605
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 1 (January 2020) . - pp 123 - 135[article]Past and future evolution of French Alpine glaciers in a changing climate: a deep learning glacio-hydrological modelling approach / Jordi Bolibar Navarro (2020)
Titre : Past and future evolution of French Alpine glaciers in a changing climate: a deep learning glacio-hydrological modelling approach Type de document : Thèse/HDR Auteurs : Jordi Bolibar Navarro, Auteur ; Antoine Rabatel, Auteur ; Isabelle Gouttevin, Auteur ; Eric Sauquet, Auteur Editeur : Grenoble [France] : Université Grenoble Alpes Année de publication : 2020 Importance : 143 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse pour obtenir le grade de Docteur de l'Université Grenoble Alpes, Spécialité : Sciences de la Terre et de l’Univers et de l’EnvironnementLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] Alpes (France)
[Termes IGN] analyse diachronique
[Termes IGN] apprentissage automatique
[Termes IGN] bilan de masse
[Termes IGN] changement climatique
[Termes IGN] glacier
[Termes IGN] modèle de simulation
[Termes IGN] modèle hydrographique
[Termes IGN] modèle numérique de surface
[Termes IGN] réseau neuronal artificielIndex. décimale : THESE Thèses et HDR Résumé : (auteur) The European Alps are among the most affected regions in the world by climate change, displaying some of the strongest glacier retreat rates. Long-term interactions between society, mountain ecosystems and glaciers in the region raise important questions on the future evolution of glaciers and their derived environmental and socioeconomical impacts. In order to correctly assess the regional response of glaciers in the French Alps to climate change, there is a need for adequate modelling tools. In this work, we explore new ways to tackle both glacier evolution and glacio-hydrological modelling at a regional scale. Glacier evolution modelling has traditionally been performed using empirical or physical approaches, which are becoming increasingly challenging to optimize with the ever growing amount of available data. Here, we present, to our knowledge, the first effort ever to apply deep learning (i.e. deep artificial neural networks) to simulate the evolution of glaciers. Since both the climate and glacier systems are highly nonlinear, traditional linear mass balance models offer a limited representation of climate-glacier interactions. We show how important nonlinearities in glacier mass balance are captured by deep learning, substantially improving model performance over linear methods.This novel method was first applied in a study to reconstruct annual mass balance changes for all glaciers in the French Alps for the 1967-2015 period. Using climate reanalyses, topographical data and glacier inventories, we demonstrate how such an approach can be successfully used to reconstruct large-scale mass balance changes from observations. This study also offered new insights on how glaciers evolved in the French Alps during the last half century, confirming the rather neutral observed mass balance rates in the 1980s and displaying a well-marked acceleration in mass loss from the 2000s onwards. Important differences between regions are found, with the Mont-Blanc massif presenting the lowest mass loss and the Chablais being the most affected one. Secondly, we applied this modelling framework to simulate the future evolution of all glaciers in the region under multiple (N=29) climate change scenarios. Our estimates indicate that most ice volume in the region will be lost by the end of the 21st century independently from future climate scenarios. We predict average glacier volume losses of 74%, 80% and 88% under RCP 2.6 (n=3), RCP 4.5 (n=13) and RCP 8.5 (n=13), respectively. By the end of the 21st century the French Alps will be largely ice-free, with glaciers only remaining in the Mont-Blanc and Pelvoux massifs. Note de contenu : Introduction
1- Glaciers
2- Glacierized mountain catchments
3- OutlookNuméro de notice : 28311 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Thèse française Note de thèse : Thèse de Doctorat : Sciences de la Terre et de l’Univers et de l’Environnement : Grenoble : 2020 Organisme de stage : Institut des Géosciences de l’Environnement (Grenoble) DOI : sans En ligne : https://tel.archives-ouvertes.fr/tel-03052063v2/document Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98202 Inside the ice shelf: using augmented reality to visualise 3D lidar and radar data of Antarctica / Alexandra L. Boghosian in Photogrammetric record, vol 34 n° 168 (December 2019)
[article]
Titre : Inside the ice shelf: using augmented reality to visualise 3D lidar and radar data of Antarctica Type de document : Article/Communication Auteurs : Alexandra L. Boghosian, Auteur ; Martin J. Pratt, Auteur ; Maya A. Becker, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 346 - 364 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Antarctique
[Termes IGN] banquise
[Termes IGN] couplage GNSS-INS
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] glace de mer
[Termes IGN] image radar
[Termes IGN] Matlab
[Termes IGN] modèle numérique de surface
[Termes IGN] pas d'échantillonnage au sol
[Termes IGN] réalité augmentée
[Termes IGN] semis de points
[Termes IGN] travail coopératif
[Termes IGN] VRMLRésumé : (auteur) From 2015 to 2017, the ROSETTA‐Ice project comprehensively mapped Antarctica's Ross Ice Shelf using IcePod, a newly developed aerogeophysical platform. The campaign imaged the ice‐shelf surface with lidar and its internal structure with ice‐penetrating radar. The ROSETTA‐Ice data was combined with pre‐existing ice surface and bed topography digital elevation models to create the first augmented reality (AR) visualisation of the Antarctic Ice Sheet, using the Microsoft HoloLens. The ROSETTA‐Ice datasets support cross‐disciplinary science that aims to understand 4D processes, namely the change of 3D ice‐shelf structures over time. The work presented here uses AR to visualise this dataset in 3D and highlights how AR can be simultaneously a useful research tool for interdisciplinary geoscience as well as an effective device for science communication education. Numéro de notice : A2019-575 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12298 Date de publication en ligne : 23/12/2019 En ligne : https://doi.org/10.1111/phor.12298 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94455
in Photogrammetric record > vol 34 n° 168 (December 2019) . - pp 346 - 364[article]Sea ice extent detection in the Bohai Sea using Sentinel-3 OLCI data / Hua Su in Remote sensing, Vol 11 n° 20 (October-2 2019)
[article]
Titre : Sea ice extent detection in the Bohai Sea using Sentinel-3 OLCI data Type de document : Article/Communication Auteurs : Hua Su, Auteur ; Bowen Ji, Auteur ; Yunpeng Wang, Auteur Année de publication : 2019 Article en page(s) : 17 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bande infrarouge
[Termes IGN] changement climatique
[Termes IGN] Chine, mer de
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] glace de mer
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-OLCI
[Termes IGN] Normalized Difference Snow Index
[Termes IGN] réflectanceRésumé : (auteur) Sea ice distribution is an important indicator of ice conditions and regional climate change in the Bohai Sea (China). In this study, we monitored the spatiotemporal distribution of the Bohai Sea ice in the winter of 2017–2018 by developing sea ice information indexes using 300 m resolution Sentinel-3 Ocean and Land Color Instrument (OLCI) images. We assessed and validated the index performance using Sentinel-2 MultiSpectral Instrument (MSI) images with higher spatial resolution. The results indicate that the proposed Normalized Difference Sea Ice Information Index (NDSIIIOLCI), which is based on OLCI Bands 20 and 21, can be used to rapidly and effectively detect sea ice but is somewhat affected by the turbidity of the seawater in the southern Bohai Sea. The novel Enhanced Normalized Difference Sea Ice Information Index (ENDSIIIOLCI), which builds on NDSIIIOLCI by also considering OLCI Bands 12 and 16, can monitor sea ice more accurately and effectively than NDSIIIOLCI and suffers less from interference from turbidity. The spatiotemporal evolution of the Bohai Sea ice in the winter of 2017–2018 was successfully monitored by ENDSIIIOLCI. The results show that this sea ice information index based on OLCI data can effectively extract sea ice extent for sediment-laden water and is well suited for monitoring the evolution of Bohai Sea ice in winter. Numéro de notice : A2019-557 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs11202436 Date de publication en ligne : 29/10/2019 En ligne : https://doi.org/10.3390/rs11202436 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94214
in Remote sensing > Vol 11 n° 20 (October-2 2019) . - 17 p.[article]Time-lapse photogrammetry of distributed snow depth during snowmelt / Simon Filhol in Water resources research, vol 55 n° 9 (September 2019)PermalinkIntegration of corner reflectors for the monitoring of mountain glacier areas with Sentinel-1 time series / Matthias Jauvin in Remote sensing, vol 11 n° 8 (August 2019)PermalinkClassification of glacial lakes using integrated approach of DFPS technique and gradient analysis using Sentinel 2A data / Prateek Verma in Geocarto international, vol 34 n° 10 ([15/07/2019])PermalinkImproved algorithms for the measurement of total precipitable water and cloud liquid water from SARAL microwave radiometer observations / Rajput Neha Mangalsinh in Marine geodesy, vol 42 n° 4 (July 2019)PermalinkReal-time sea-level monitoring using Kalman filtering of GNSS-R data / Joakim Strandberg in GPS solutions, vol 23 n° 3 (July 2019)PermalinkClassification du type et de la concentration de la banquise, à partir d’images Sentinel-1 SAR, grâce à des réseaux de neurones convolutifs / Hugo Boulze (2019)PermalinkMicrowave indices from active and passive sensors for remote sensing applications / Emanuele Santi (2019)PermalinkPermalinkRelevé de la grotte glacée de Cenote Abyss dans les Dolomites / Farouk Kadded in XYZ, n° 157 (décembre 2018 - février 2019)PermalinkA data model for moving regions of fixed shape in databases / Florian Heinz in International journal of geographical information science IJGIS, vol 32 n° 9-10 (September - October 2018)Permalink