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Are there detectable common aperiodic displacements at ITRF co-location sites? / Maylis Teyssendier de la Serve (2021)
Titre : Are there detectable common aperiodic displacements at ITRF co-location sites? Type de document : Article/Communication Auteurs : Maylis Teyssendier de la Serve , Auteur ; Paul Rebischung , Auteur ; Xavier Collilieux , Auteur ; Zuheir Altamimi , Auteur ; Laurent Métivier , Auteur Editeur : Washington DC [Etats-Unis] : Earth and Space Science Open Archive ESSOAr Année de publication : 2021 Projets : 1-Pas de projet / Conférence : AGU 2021 Fall Meeting 13/12/2021 17/12/2021 New Orleans and virtual Louisiane - Etats-Unis Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux
[Termes IGN] co-positionnement
[Termes IGN] déformation de la croute terrestre
[Termes IGN] International Terrestrial Reference Frame
[Termes IGN] résidu
[Termes IGN] série temporelleRésumé : (auteur) Nowadays, the time evolution of ITRF station positions is described by piece-wise linear models extended with exponential and logarithmic functions to account for post-seismic displacements. The ITRF2020 will also account for seasonal deformation by means of annual and semi-annual sine waves. However, part of the Earth’s surface deformation is not captured by those deterministic functions, such as inter-annual hydrological loading deformation, or high-frequency atmospheric loading deformation. To account for such aperiodic displacements, a reference frame in the form of a time series could be considered. This would require aperiodic motions of the different space geodetic stations to be tied in a common frame by means of co-motion constraints. The relevance of such constraints is however debatable. Indeed, common aperiodic movements between co-located space geodetic stations have thus far not been evidenced. This presentation describes the comparison of station position time series from the different space geodetic techniques in order to highlight whether or not common aperiodic movements can be detected at co-location sites. Those time series are extracted from the solutions provided by the techniques international services for the ITRF2014. They are first carefully aligned to a common reference frame in order to minimize differential network effect. Then, they are cleaned from linear, post-seismic and periodic signals (including seasonal deformation and technique systematic errors). Residual time series from co-located stations are finally confronted with each other. Numéro de notice : C2021-069 Affiliation des auteurs : UMR IPGP-Géod (2020- ) Thématique : POSITIONNEMENT Nature : Poster nature-HAL : Poster-avec-CL DOI : 10.1002/essoar.10509118.1 Date de publication en ligne : 06/12/2021 En ligne : https://doi.org/10.1002/essoar.10509118.1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99604
Titre : Artificial intelligence methods applied to urban remote sensing and GIS Type de document : Monographie Auteurs : Chang-Wook Lee, Éditeur scientifique ; Hyangsun Han, Éditeur scientifique ; Hoonyol Lee, Éditeur scientifique ; Yu-Chul Park, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2021 Importance : 166 p. Format : 16 x 23 cm ISBN/ISSN/EAN : 978-3-0365-1603-5 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage profond
[Termes IGN] carte thématique
[Termes IGN] classification dirigée
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] Corée du sud
[Termes IGN] effondrement de terrain
[Termes IGN] espace vert
[Termes IGN] image à très haute résolution
[Termes IGN] image radar moirée
[Termes IGN] indice de végétation
[Termes IGN] intelligence artificielle
[Termes IGN] Jakarta (Indonésie)
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] Mexique
[Termes IGN] milieu urbain
[Termes IGN] pollution des eaux
[Termes IGN] réseau local sans fil
[Termes IGN] segmentation sémantique
[Termes IGN] séisme
[Termes IGN] système d'information géographiqueRésumé : (éditeur) This book is based on Special Issue "Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS" from early 2020 to 2021. This book includes seven papers related to the application of artificial intelligence, machine learning and deep learning algorithms using remote sensing and GIS techniques in urban areas. Note de contenu : 1- Improvement of earthquake risk awareness and seismic literacy of Korean citizens through earthquake vulnerability map from the 2017 Pohang earthquake, South Korea
2- Land subsidence susceptibility mapping in Jakarta using functional and meta-ensemble machine learning algorithm based on time-series InSAR data
3- Integration of InSAR time-series data and GIS to assess Llnd subsidence along subway lines in the Seoul metropolitan area, South Korea
4- Mapping urban green spaces at the metropolitan level using very high resolution satellite imagery and deep learning techniques for semantic segmentation
5- Susceptibility analysis of the Mt. Umyeon landslide area using a physical slope model and probabilistic method
6- Intelligent WSN system for water quality analysis using machine learning algorithms: A case study (Tahuando River from Ecuador)
7- Groundwater potential mapping using remote sensing and GIS-based machine learning techniquesNuméro de notice : 28667 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Recueil / ouvrage collectif DOI : 10.3390/books978-3-0365-1603-5 En ligne : https://doi.org/10.3390/books978-3-0365-1603-5 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99870 Automated detection of lineaments express geological linear features of a tropical region using topographic fabric grain algorithm and the SRTM DEM / Samy Ismail Elmahdy in Geocarto international, vol 36 n° 1 ([01/01/2021])
[article]
Titre : Automated detection of lineaments express geological linear features of a tropical region using topographic fabric grain algorithm and the SRTM DEM Type de document : Article/Communication Auteurs : Samy Ismail Elmahdy, Auteur ; Mohamed Mostafa Mohamed, Auteur ; Tarig A Ali, Auteur Année de publication : 2021 Article en page(s) : pp 76 - 95 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte géologique
[Termes IGN] linéament
[Termes IGN] Malaisie
[Termes IGN] milieu tropical
[Termes IGN] MNS SRTM
[Termes IGN] modèle numérique de surface
[Termes IGN] structure géologiqueRésumé : (Auteur) The availability of the large volume of remote sensing data has allowed for the developing of several automated algorithms for detecting linear geological features and more reliable analysis. However, most of the algorithms focus on edge detection and tone change on a satellite image, which represents all geological and non-geological features. In this study, a topographic fabric algorithm, which calculates the slope and aspect at each point in a DEM, is applied for automatically geological linear features mapping in Bau Goldfield, Malaysia using the new version of the Shuttle Radar Topographic Mission (SRTM) DEM. A series of topographic fabric input parameters was tested using different combinations of input values in order to decide the optimal parameters that provided the suitable detection parameters, best fit and the highest accuracy. Comparison with the geological map demonstrated that the tested parameters made the algorithm able to automatically detect geological structures. Numéro de notice : A2021-052 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1594393 Date de publication en ligne : 29/05/2019 En ligne : https://doi.org/10.1080/10106049.2019.1594393 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96776
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Code-barres Cote Support Localisation Section Disponibilité 059-2021011 RAB Revue Centre de documentation En réserve L003 Disponible Beach morphology and its dynamism from remote sensing for coastal management support / Carlos Cabezas Rabadán (2021)
Titre : Beach morphology and its dynamism from remote sensing for coastal management support Type de document : Thèse/HDR Auteurs : Carlos Cabezas Rabadán, Auteur ; Josep E. Pardo Pascual, Directeur de thèse ; Miguel Rodilla Alamá, Directeur de thèse Editeur : Valencia : Universitat politécnica de Valencia Année de publication : 2021 Importance : 188 p. Format : 21 x 30 cm Note générale : bibliographie
Thesis dissertation submitted in fulfillment of the requirements for the Degree of Doctor of Philosophy at Universitat Politècnica de ValènciaLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] changement climatique
[Termes IGN] détection de changement
[Termes IGN] érosion côtière
[Termes IGN] géomorphologie
[Termes IGN] image Landsat
[Termes IGN] image Sentinel-MSI
[Termes IGN] modélisation spatio-temporelle
[Termes IGN] plage
[Termes IGN] sédiment
[Termes IGN] surveillance du littoral
[Termes IGN] trait de côteRésumé : (auteur) Beaches are coastal spaces that perform numerous environmental functions. They provide important benefits to society and coastal communities, including the ecological function, the provision of protection for coastal territories, and constitute a basic resource for the tourism industry. Due to climate change and human actions that alter the natural dynamism of the coast, beaches are experiencing increasingly harmful erosive processes that affect their physical integrity and the maintenance of their ecological functions. Beach management is often not adapted to the particularities of the different coastal segments. Decision-making is not based on sufficient information about characteristics, dynamism, and current state of beaches, resulting in short or ineffective solutions. Geomorphological characteristics are essential in the development of beach functions as they condition their physical dimensions and their behavior in response to the action of the sea. Therefore, their detailed and updated characterization is necessary to carry out efficient actions, allowing a more ecosystemic and sustainable coastal management. Remote sensing techniques have a great capacity for acquiring data from the land surface. In particular, Sentinel-2 and Landsat (5, 7, and 8) satellites freely provide medium resolution images with global coverage and high-revisit frequency. The algorithms for extracting the water/land interface recently developed by the Geo-Environmental Cartography and Remote Sensing Group (CGAT – UPV) allow defining the position of the shoreline on these images, constituting potentially useful data to describe beach morphology and dynamics. Universalizing their application requires testing and validation at different coastal types. For this purpose, the extraction process has been adapted for exploitation in tidal environments, and the resulting shorelines have been assessed under different oceanographic conditions offering an accuracy close to 5 m RMSE (Root-Mean-Square Error). From these shorelines, and taking into account the existing information needs for management, it is proposed to derive indicators to characterize the geomorphology of the beaches and to monitor their changes. To this end, the proposed methodologies ensure the efficient management of large volumes of shorelines, being able to characterize the beaches along broad coastal segments and periods. Thus, beach width and sediment grain size are derived as objective and easily understandable indicators of the beach geomorphology. Spatial-temporal modeling of the state and changes of shoreline position and beach width makes it possible to monitor the response to storms and anthropogenic actions, allowing to analyze changes that occur every few days or over decades. The large spatial coverage together with the integration with other cartographic databases allows characterizing the influence of beach geomorphology in the performance of its functions, offering a holistic view of the coast from a regional scale. The methodologies developed in this thesis and the indicators derived from remote sensing provide support and criteria for prioritizing the actions of managers. This contributes to fill the gap between the availability of techniques to obtain remote information and its application in the coastal decision-making process. Note de contenu : 1- General introduction
2- Assessing user’s expectations and perceptions on different beach types and the need for diverse management frameworks
3- Satellite-derived shorelines at an exposed mesotidal beach
4- Characterizing beach changes using satellite-derived shorelines
5- Detecting problematic beach widths for the recreational function from subpixel shoreline
6- Shoreline variability from Sentinel-2: an approach for estimating beach sediment size?
7- Conclusions, management implications and future perspectivesNuméro de notice : 28599 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : PhD Thesis : Geomatics : Valencia, Spain : 2021 DOI : 10.4995/Thesis/10251/165076 En ligne : https://doi.org/10.4995/Thesis/10251/165076 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99405
Titre : Benefiting from local rigidity in 3D point cloud processing Type de document : Thèse/HDR Auteurs : Zan Gojcic, Auteur Editeur : Zurich : Eidgenossische Technische Hochschule ETH - Ecole Polytechnique Fédérale de Zurich EPFZ Année de publication : 2021 Importance : 141 p. Format : 21 x 30 cm Note générale : bibliographie
A thesis submitted to attain the degree of Doctor of Sciences of ETH ZurichLangues : Français (fre) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage profond
[Termes IGN] capteur actif
[Termes IGN] champ vectoriel
[Termes IGN] déformation d'image
[Termes IGN] données lidar
[Termes IGN] effondrement de terrain
[Termes IGN] enregistrement de données
[Termes IGN] filtrage du bruit
[Termes IGN] flux
[Termes IGN] image 3D
[Termes IGN] navigation autonome
[Termes IGN] orientation du capteur
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] téléphone intelligent
[Termes IGN] traitement de semis de points
[Termes IGN] voxelIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Incorporating 3D understanding and spatial reasoning into (intelligent) algorithms is crucial for solving several tasks in fields such as engineering geodesy, risk assessment, and autonomous driving. Humans are capable of reasoning about 3D spatial relations even from a single 2D image. However, making the priors that we rely on explicit and integrating them into computer programs is very challenging. Operating directly on 3D input data, such as 3D point clouds, alleviates the need to lift 2D data into a 3D representation within the task-specific algorithm and hence reduces the complexity of the problem. The 3D point clouds are not only a better-suited input data representation, but they are also becoming increasingly easier to acquire. Indeed, nowadays, LiDAR sensors are even integrated into consumer devices such as mobile phones. However, these sensors often have a limited field of view, and hence multiple acquisitions are required to cover the whole area of interest. Between these acquisitions, the sensor has to be moved and pointed in a different direction. Moreover, the world that surrounds us is also dynamic and might change as well. Reasoning about the motion of both the sensor and the environment, based on point clouds acquired in two-time steps, is therfore an integral part of point cloud processing. This thesis focuses on incorporating rigidity priors into novel deep learning based approaches for dynamic 3D perception from point cloud data. Specifically, the tasks of point cloud registration, deformation analysis, and scene flow estimation are studied. At first, these tasks are incorporated into a common framework where the main difference is in the level of rigidity assumptions that are imposed on the motion of the scene or
the acquisition sensor. Then, the tasks specific priors are proposed and incorporated into novel deep learning architectures. While the global rigidity can be assumed in point cloud registration, the motion patterns in deformation analysis and scene flow estimation are more complex. Therefore, the global rigidity prior has to be relaxed to local or instancelevel rigidity, respectively. Rigidity priors not only add structure to the aforementioned tasks, which prevents physically implausible estimates and improves the generalization of the algorithms, but in some cases also reduce the supervision requirements. The proposed approaches were quantitatively and qualitatively evaluated on several datasets, and they yield favorable performance compared to the state-of-the-art.Numéro de notice : 28660 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : PhD : Sciences : ETH Zurich : 2021 DOI : sans En ligne : https://www.research-collection.ethz.ch/handle/20.500.11850/523368 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99817 Cartographie de gîsements de matières colorantes utilisées pendant la Préhistoire et configuration de l’application Input de relevés de terrain / Mathilde Waymel (2021)PermalinkCharacteristics of seasonal variations and noises of the daily double-difference and PPP solutions / Kamil Maciuk in Journal of applied geodesy, vol 15 n° 1 (January 2021)PermalinkContribution des SIG et de la modélisation volumique à la caractérisation géomorphologique et géologique de la région des Doukkala « Meseta côtière, Maroc » / Youness Ahmed Laaziz (2021)PermalinkPermalinkDynamic committee machine with fuzzy-c-means clustering for total organic carbon content prediction from wireline logs / Yang Bai in Computers & geosciences, vol 146 (January 2021)PermalinkDynamic mechanism of blown sand hazard formation at the Jieqiong section of the Lhasa–Shigatse railway / Shengbo Xie in Geomatics, Natural Hazards and Risk, vol 12 n° 1 (2021)PermalinkFusion of ground penetrating radar and laser scanning for infrastructure mapping / Dominik Merkle in Journal of applied geodesy, vol 15 n° 1 (January 2021)PermalinkPermalinkGeomorphic analysis of Xiadian buried fault zone in Eastern Beijing plain based on SPOT image and unmanned aerial vehicle (UAV) data / Yanping Wang in Geomatics, Natural Hazards and Risk, vol 12 n° 1 (2021)PermalinkHeight system unification and estimation of the lithospheric structure beneath Vietnam through high-resolution gravity field and quasigeoid modeling / Dinh Toan Vu (2021)Permalink