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Understanding the synergies of deep learning and data fusion of multispectral and panchromatic high resolution commercial satellite imagery for automated ice-wedge polygon detection / Chandi Witharana in ISPRS Journal of photogrammetry and remote sensing, vol 170 (December 2020)
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[article]
Titre : Understanding the synergies of deep learning and data fusion of multispectral and panchromatic high resolution commercial satellite imagery for automated ice-wedge polygon detection Type de document : Article/Communication Auteurs : Chandi Witharana, Auteur ; Md Abul Ehsan Bhuiyan, Auteur ; Anna K. Liljedahl, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 174-191 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme de fusion
[Termes IGN] apprentissage profond
[Termes IGN] Arctique
[Termes IGN] artefact
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection automatique
[Termes IGN] fusion d'images
[Termes IGN] glace
[Termes IGN] image à haute résolution
[Termes IGN] pergélisol
[Termes IGN] texture d'imageRésumé : (Auteur) The utility of sheer volumes of very high spatial resolution (VHSR) commercial imagery in mapping the Arctic region is new and actively evolving. Commercial satellite sensors typically record image data in low-resolution multispectral (MS) and high-resolution panchromatic (PAN) mode. Spatial resolution is needed to accurately describe feature shapes and textural patterns, such as ice-wedge polygons (IWPs) that are rapidly transforming surface features due to degrading permafrost, while spectral resolution allows capturing of land-use and land-cover types. Data fusion, the process of combining PAN and MS images with complementary characteristics often serves as an integral component of remote sensing mapping workflows. The fusion process generates spectral and spatial artifacts that may affect the classification accuracies of subsequent automated image analysis algorithms, such as deep learning (DL) convolutional neural nets (CNN). We employed a detailed multidimensional assessment to understand the performances of an array of eight application-oriented data fusion algorithms when applied to VHSR image scenes for DLCNN-based mapping of ice-wedge polygons. Our findings revealed the scene dependency of data fusion algorithms and emphasized the need for careful selection of the proper algorithm. Results suggested that the fusion algorithms that preserve spatial character of original PAN imagery favor the DLCNN model performances. The choice of fusion approach needs to be considered of equal importance to the required training dataset for successful applications using DLCNN on VHRS imagery in order to enable an accurate mapping effort of permafrost thaw across the Arctic region. Numéro de notice : A2020-705 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.10.010 Date de publication en ligne : 01/11/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.10.010 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96232
in ISPRS Journal of photogrammetry and remote sensing > vol 170 (December 2020) . - pp 174-191[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2020121 RAB Revue Centre de documentation En réserve L003 Disponible River ice segmentation with deep learning / Abhineet Singh in IEEE Transactions on geoscience and remote sensing, vol 58 n° 11 (November 2020)
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Titre : River ice segmentation with deep learning Type de document : Article/Communication Auteurs : Abhineet Singh, Auteur ; Hayden Kalke, Auteur ; Mark Loewen, Auteur Année de publication : 2020 Article en page(s) : pp 7570 - 7579 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage non-dirigé
[Termes IGN] apprentissage profond
[Termes IGN] Canada
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] glace
[Termes IGN] image captée par drone
[Termes IGN] rivière
[Termes IGN] segmentation d'image
[Termes IGN] segmentation sémantiqueRésumé : (auteur) This article deals with the problem of computing surface concentrations for two types of river ice from digital images acquired during freeze-up. It presents the results of attempting to solve this problem using several state-of-the-art semantic segmentation methods based on deep convolutional neural networks (CNNs). This task presents two main challenges—very limited availability of labeled training data and presence of noisy labels due to the great difficulty of visually distinguishing between the two types of ice, even for human experts. The results are used to analyze the extent to which some of the best deep learning methods currently in existence can handle these challenges. The code and data used in the experiments are made publicly available to facilitate further work in this domain. Numéro de notice : A2020-674 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2981082 Date de publication en ligne : 13/04/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2981082 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96165
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 11 (November 2020) . - pp 7570 - 7579[article]Classification 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)
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Titre : Classification du type et de la concentration de la banquise, à partir d’images Sentinel-1 SAR, grâce à des réseaux de neurones convolutifs Type de document : Mémoire Auteurs : Hugo Boulze , Auteur
Editeur : Champs-sur-Marne : Ecole nationale des sciences géographiques ENSG Année de publication : 2019 Importance : 72 p. Format : 21 x 30 cm Note générale : Bibliographie
Rapport de projet pluridisciplinaire, cycle ING2Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] banquise
[Termes IGN] carte thématique
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] glace
[Termes IGN] image Sentinel-SARIndex. décimale : PROJET Mémoires : Rapports de projet - stage des ingénieurs de 2e année Résumé : (Auteur) Note de contenu : Introduction
1. Données et traitements
1.1 Images Sentinel-1 SAR
1.2 Cartes de glaces
1.3 Création des données
1.4 Pré-traitements
2. Réseau de neurones convolutifs (CNN)
2.1 Définition
2.2 Notions complémentaires
2.3 Hyperparamètres et paramètres entraînables
3. Expérimentations
3.1 Critères d’évaluation
3.2 Choix des hyperparamètres
3.3 Combinaisons des hyperparamètres
3.4 Démarche des expérimentations
4. Résultats
4.1 Détermination des hyperparamètres liés au réseau de neurones
4.2 Détermination des hyperparamètres liés aux données
4.3 Entraînements du meilleur modèle
4.4 DiscussionsNuméro de notice : 26127 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Mémoire de projet pluridisciplinaire Organisme de stage : Nansen Environmental and Remote Sensing Center NERSC Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93913 Documents numériques
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Classification du type et de la concentration de la banquise... - pdf auteurAdobe Acrobat PDFRelevé de la grotte glacée de Cenote Abyss dans les Dolomites / Farouk Kadded in XYZ, n° 157 (décembre 2018 - février 2019)
[article]
Titre : Relevé de la grotte glacée de Cenote Abyss dans les Dolomites Type de document : Article/Communication Auteurs : Farouk Kadded, Auteur ; Tommasso Santagata, Auteur Année de publication : 2018 Article en page(s) : pp 57 - 60 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] 3DReshaper
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] glace
[Termes IGN] grotte
[Termes IGN] image captée par drone
[Termes IGN] instrumentation Leica
[Termes IGN] Italie
[Termes IGN] positionnement par GNSS
[Termes IGN] semis de points
[Termes IGN] spéléologie
[Termes IGN] traitement de semis de pointsRésumé : (auteur) The abyss of Conturines, alsoknown as Cenote Abyss, represents one of the deepest and lagest caves of the Dolomites.This 280 m deep cave is characterized by a huge ice deposit, which makes it of major interest for the study of paleoclimate and modern climate change in this region of the Alps.The cave was discovered in 1994 after the abrupt empying of a lake at 2940 m. In 2015, a research project began to monitor the long-term movements an d volume changes of this ice deposit and to understand the microclimate of the cave. With two expeditions organized in October 2015 and September 2016, a complete study of the cave was carried out using a 3D laser scanner HDS7000 in 2015 and a scanner ScanStation P40 in 2016. Installation of barometric datalodgers, temperature and humidity in different areas of the cave provide a one-year record of the microclimate. In addtion, pollen traps have been installed to study the current flow of pollen on and inside the cave while preliminary analyzes of pollen grains held in the ice are in progress. The Cenote Abyss Ice Caves Research Project aim to shed light on the changing climate of the Dolomites over the past several hundred years, perhaps thousands of years, as well as on environmental changes more recent events that led to the melting of the cave glacier. Numéro de notice : A2018-546 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91582
in XYZ > n° 157 (décembre 2018 - février 2019) . - pp 57 - 60[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 112-2018041 RAB Revue Centre de documentation En réserve L003 Disponible
Titre : Gravity forward modeling with a tesseroid-based rock-water-ice approach : Theory and applications in the context of the GOCE mission and height system unification Type de document : Thèse/HDR Auteurs : Thomas Grombein, Auteur Editeur : Munich : Bayerische Akademie der Wissenschaften Année de publication : 2017 Collection : DGK - C Sous-collection : Dissertationen num. 798 Importance : 222 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-3-7696-5210-9 Note générale : bibliographie
Inaugural dissertation for the fulfillment of the requirements for the academic degree of Doctor of Engineering (Dr.-Ing.) accepted by the Department of Civil Engineering, Geo and Environmental Sciences of the Karlsruhe Institute of Technology (KIT)
Diese Dissertation ist auf dem Server der Deutschen Geodätischen Kommission unter <http://dgk.badw.de/> sowie auf dem Server des Karlsruher Instituts für Technologie unter <http://dx.doi.org/10.5445/KSP/1000068500> elektronisch publiziertLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] champ de pesanteur terrestre
[Termes IGN] données GOCE
[Termes IGN] eau de surface
[Termes IGN] glace
[Termes IGN] gradient de gravitation
[Termes IGN] isostasie
[Termes IGN] levé gravimétrique
[Termes IGN] ondelette
[Termes IGN] problème des valeurs limites
[Termes IGN] tesseroidRésumé : (auteur) Due to the increasing availability of global high-resolution digital terrain models (DTMs), it has nowadays become possible to obtain a detailed image of the Earth’s topography. This enables to precisely determine the gravitational effect of the topographic masses on the Earth’s gravity field. The central technique for this aim is gravity forward modeling (GFM), which is based on Newton’s law of universal gravitation, and allows to convert topographic heights along with suitable density assumptions into corresponding values of the gravitational potential and its derivatives. This topographic gravity forward modeling attracts a growing interest in various areas of geodetic gravity field determination and geophysical studies of the Earth’s composition and structure (e.g., solid-earth sciences). However, previous GFM methods have proven unsuitable for the increasing accuracy requirements stemming from an improved precision of geodetic measurements. This is due to commonly used simplifications and approximations, such as (i) the use of condensed heights for water and ice masses (rock-equivalent heights), (ii) mass discretizations or arrangements based on planar and spherical approximations, and (iii) assumptions regarding the spectral consistency between band-limited topographic heights and induced gravity, as in residual terrain modeling (RTM) techniques. This thesis contributes to state-of-the-art GFM in the space domain by providing effective techniques and refinements that overcome these limitations. More concretely, the theory of the Rock-Water-Ice (RWI) approach is developed that encompasses a more realistic modeling of the Earth’s topographic and isostatic masses, i.e., the masses of the continents, oceans, lakes, ice sheets and shelves, as well as their deeper lying (isostatic) compensation masses in the Earth’s interior. The RWI method is characterized by a three-layer decomposition of the Earth’s topography that accounts for a rigorous separate modeling of the rock, water, and ice masses with variable density values. Furthermore, a modified Airy-Heiskanen isostatic concept is applied that is enhanced by additional geophysical information in terms of a seismologically derived depth model of the Mohorovicic discontinuity, i.e., the boundary surface between the Earth’s crust and mantle. To counteract the increased computational demand of the more complex modeling, an efficient numerical algorithm is needed for the forward modeling. For space domain GFM, it has become more and more customary to use a mass discretization based on tesseroids, which are mass bodies bounded by geocentric spherical coordinate lines, and hence are directly linked to the curvature of the Earth. Several studies have demonstrated their superiority over classical prism methods with respect to precision and computation time. However, for global applications based on high-resolution DTMs, any computational speed-up with respect to a single mass body leads to a massive improvement in the overall computation time. This thesis presents a considerable optimization of previously used tesseroid formulas, where the gravitational field of a tesseroid and its derivatives up to second-order are represented in a compact and computationally attractive form. This allows an efficient numerical evaluation that reduces the overall runtime by about 20 to 55%, depending on the evaluated gravity field functional. Additionally, to correctly locate topographic masses in space, tesseroids are arranged on an ellipsoidal reference surface. Within this thesis, the novel tesseroid-based RWI approach is applied to different topographic input data and is used for various gravity field functionals in two main applications. Both are connected to ESA’s satellite mission GOCE (Gravity field and steady-state Ocean Circulation Explorer) that measured the second-order derivatives of the gravitational potential, commonly known as gravity gradients. In the first application, RWI-based topographic-isostatic effects are calculated along the orbit of the GOCE satellite and are subtracted from the gravity gradient observations. In this way, the measurement signal is smoothed so that interpolation and prediction tasks, such as harmonic downward continuation of the gradients from satellite altitude to the Earth’s surface, can be executed with an improved numerical stability. While in previous studies such a concept was applied to simulated gravity gradients, this thesis presents the application to real GOCE measurements. As the smoothing effect strongly depends on the variability of the topography crossed by the satellite, this procedure is particularly suitable for regional applications. For a time series when the satellite passed the Himalayan region, a comparison of the observed gradients to the reduced ones reveals significant smoothing effects that are quantified by analyses in the space and frequency domain. The second application contributes to the task of height system unification, which aims to connect the different locally defined reference levels, conventionally used for national height systems. This is achieved by a satellite-based method which employs global geopotential models derived from data of the GOCE mission, whose limited spectral resolution is extended by high-frequency topographic effects of the RWI approach. To extract these high-frequency signals, a novel (residual) gravity forward modeling method is proposed that allows to perform the required high pass filtering directly in the gravity domain, thus, avoiding the above-mentioned assumption (iii) of the RTM method. By using three representative study areas in Germany, Austria, and Brazil, the benefit and importance of high-frequency topography-implied gravity signals for an accurate estimation of height datum offsets is demonstrated. As a highlight of this thesis, the RWI approach is utilized to generate a series of topographic-isostatic gravity field models. These RWI models provide a high-resolution representation of the Earth’s topographic-isostatic gravitational potential in terms of spherical harmonics expanded up to degree and order 1800 (Release 2012), and 2190 (Release 2015). The spherical harmonic coefficients of these models are obtained from a spherical harmonic analysis of global gridded potential values, which have been calculated by massive parallel computing on high-performance computer systems. By using spherical harmonic synthesis, the RWI model can be used to efficiently calculate various functionals of the topographic-isostatic potential in different heights. For this purpose, the RWI models are publicly available via the database of the International Centre for Global Earth Models (ICGEM) and have already been used in a wide range of studies by other research groups. Note de contenu : 1. Introductory chapter
2. Optimized formulas for the gravitational field of a tesseroid
3. A wavelet-based assessment of topographic-isostatic reductions for GOCE gravity gradients
4. The Rock-Water-Ice topographic gravity field model RWI TOPO 2015 and its comparison to a conventional rock-equivalent version
5. On high-frequency topography-implied gravity signals for height system unification 6. Height system unification based on the fixed GBVP approachNuméro de notice : 17488 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Thèse étrangère Note de thèse : dissertation : : Karlsruhe Institute of Technology : 2017 DOI : 10.5445/KSP/1000068500 En ligne : http://doi.org/10.5445/KSP/1000068500 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89828 SMAP L-Band microwave radiometer: RFI mitigation prelaunch analysis and first year on-orbit observations / Priscilla N. Mohammed in IEEE Transactions on geoscience and remote sensing, vol 54 n° 10 (October 2016)
PermalinkTopographic gravitational potential up to second-order derivatives: an examination of approximation errors caused by rock-equivalent topography (RET) / Michael Kuhns in Journal of geodesy, vol 90 n° 9 (September 2016)
PermalinkNumerical and experimental evaluation of terrestrial LiDAR for parameterizing centimeter-scale sea ice surface roughness / Jack C. Landy in IEEE Transactions on geoscience and remote sensing, vol 53 n° 9 (September 2015)
PermalinkSea level and global ice volumes from the Last Glacial Maximum to the Holocene / Kurt Lambeck in Proceedings of the National Academy of Sciences of the United States of America PNAS, vol 111 n° 43 (2014)
PermalinkEvaluation of modified four-component scattering power decomposition method over highly rugged glaciated terrain / G. Singh in Geocarto international, vol 27 n° 2 (March 2012)
PermalinkReflecting on GPS: sensing land and ice from low Earth orbit / S.T. Gleason in GPS world, vol 18 n° 10 (October 2008)
PermalinkEstimating volume change of mountain glaciers using SRTM and map-based topographic data / A.B. Surazakov in IEEE Transactions on geoscience and remote sensing, vol 44 n° 10 Tome 2 (October 2006)
PermalinkPermalinkDerivation of a threshold function for the advanced very high resolution radiometer 3, 75um channel and its application in automatic cloud discrimination over snow/ice surfaces / X. Xiong in International Journal of Remote Sensing IJRS, vol 25 n° 15 (August 2004)
PermalinkNarrowband-to-broadband albedo conversion for glacier ice and snow: equations based on modeling and ranges of validity of the equations / W. Greuell in Remote sensing of environment, vol 89 n° 1 (15/01/2004)
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