Descripteur
Documents disponibles dans cette catégorie (4899)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Construction of bulk temperature/salinity from surface temperature and atlas profiles for monitoring water volume variations in the Caspian Sea / Ayoub Moradi (2019)
Titre : Construction of bulk temperature/salinity from surface temperature and atlas profiles for monitoring water volume variations in the Caspian Sea Type de document : Article/Communication Auteurs : Ayoub Moradi, Auteur ; Olivier de Viron, Auteur ; Laurent Métivier , Auteur ; Saeid Homayouni, Auteur Editeur : Téhéran : Kharazmi University Année de publication : 2019 Conférence : CICIS 2019, 4th Conference on Contemporary Issues in Computer Information and Sciences 23/01/2019 25/01/2019 Teheran Iran Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse de sensibilité
[Termes IGN] Caspienne, mer
[Termes IGN] image NOAA
[Termes IGN] montée du niveau de la mer
[Termes IGN] salinité
[Termes IGN] température de surface de la merRésumé : (auteur) Unlike the other lakes, the Caspian Sea has regular water level fluctuations caused by variation in temperature and salinity, which is known as thermohaline fluctuations. Vertically variable temperature and salinity data are needed in order to monitor thermohaline fluctuations. These data are regularly recorded for the open seas by remote sensing and in-situ approaches. However, there is no such information for inland water bodies, such as the Caspian Sea. In this research, daily Sea Surface Temperature (SST) from the NOAA satellite, plus long-term mean temperature, and salinity datasets from Atlas 2009 were utilized to construct bulk temperature and salinity in the Caspian Sea. The Atlas vertical profiles are not deep enough in the Caspian Sea; we expanded these data down to a thermocline depth, using a linear fitting. Constructed bulk temperature and salinity data utilized in water density calculations. The results show that thermohaline level fluctuation estimated by constructed bulk data is consisted of what a combination of altimetry and gravimetry system observed in the Caspian Sea. In the absence of necessary data, this method is helpful for bulk temperature and salinity estimations in the Caspian Sea with a satisfactory level of accuracy. The estimated thermohaline has an accuracy of about 93%, under the situation that there was 15% error in the estimation of both bulk temperature and salinity. Numéro de notice : C2019-080 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : IMAGERIE Nature : Communication DOI : sans En ligne : https://www.researchgate.net/publication/368243402_Construction_of_Bulk_Temperat [...] Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102859
Titre : Contributions to SAR image time series analysis Type de document : Thèse/HDR Auteurs : Ammar Mian, Auteur ; Jean-Philippe Ovarlez, Directeur de thèse ; Guillaume Ginolhac, Directeur de thèse Editeur : Bures-sur-Yvette : Université Paris-Saclay Année de publication : 2019 Importance : 219 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse de Doctorat de l’Université Paris-Saclay préparée à Centrale-Supélec : Sciences et Technologies de l’Information et de la CommunicationLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] covariance
[Termes IGN] détection de changement
[Termes IGN] géométrie de Riemann
[Termes IGN] image à très haute résolution
[Termes IGN] image radar moirée
[Termes IGN] ondelette de Shannon
[Termes IGN] processus gaussien
[Termes IGN] radar à antenne synthétique
[Termes IGN] série temporelle
[Termes IGN] transformation en ondelettesIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Remote sensing data from Synthetic Aperture Radar (SAR) sensors offer a unique opportunity to record, to analyze, and to predict the evolution of the Earth. In the last decade, numerous satellite remote sensing missions have been launched (Sentinel-1, UAVSAR, TerraSAR X, etc.). This resulted in a dramatic improvement in the Earth image acquisition capability and accessibility. The growing number of observation systems allows now to build high temporal/spatial-resolution Earth surface images data-sets. This new scenario significantly raises the interest in time-series processing to monitor changes occurring over large areas. However, developing new algorithms to process such a huge volume of data represents a current challenge. In this context, the present thesis aims at developing methodologies for change detection in high-resolution SAR image time series.These series raise two notable challenges that have to be overcome:On the one hand, standard statistical methods rely on multivariate data to infer a result which is often superior to a monovariate approach. Such multivariate data is however not always available when it concerns SAR images. To tackle this issue, new methodologies based on wavelet decomposition theory have been developed to fetch information based on the physical behavior of the scatterers present in the scene.On the other hand, the improvement in resolution obtained from the latest generation of sensors comes with an increased heterogeneity of the data obtained. For this setup, the standard Gaussian assumption used to develop classic change detection methodologies is no longer valid. As a consequence, new robust methodologies have been developed considering the family of elliptical distributions which have been shown to better fit the observed data.The association of both aspects has shown promising results in change detection applications. Note de contenu : Introduction
1- SAR Image Time Series issues
2- Wavelet packets for SAR analysis
3- Robust Change Detection
4- Change-point detection and estimation
5- Riemannian geometry
ConclusionNuméro de notice : 25872 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Sciences et Technologies de l’Information et de la Communication : Paris-Saclay : 2019 Organisme de stage : Laboratoire SONDRA nature-HAL : Thèse DOI : sans En ligne : https://tel.archives-ouvertes.fr/tel-02464840/document Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95547
Titre : Coverage of the Taiwan island by InSAR with Sentinel-1 and ALOS images Type de document : Article/Communication Auteurs : Bénédicte Fruneau , Auteur ; Erwan Pathier, Auteur ; Marie-Pierre Doin, Auteur ; Jyr-Ching Hu, Auteur ; Hsin Tung, Auteur Editeur : Champs/Marne : Université Paris-Est Marne-la-Vallée UPEM Année de publication : 2019 Conférence : LPS 2019, ESA Living Planet Symposium 13/05/2019 17/05/2019 Milan Italie programme sans actes Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image Sentinel-SAR
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] surveillance géologique
[Termes IGN] TaïwanRésumé : (auteur) Taiwan Island, resulting from oblique collision between Philippine sea plate and Eurasian plate converging at a rate of about 8 cm per year, is one of the most active tectonic region in the world. With a subtropical environment, it is faced to different hazards, including earthquakes, debris flow, landslides, and flooding. The precise measurement of the present-day ground displacements at the scale of the whole Taiwan Island is thus essential in several domains of Earth Sciences, in particular for earthquake cycle study and earthquake hazard assessment, for subsidence and landslide monitoring, and also to better understand the kinematics and mechanics of mountain building. Taiwan benefits from a remarkable GNSS network. However, due to a complex geodynamical context and high strain rate, the pattern of deformation is not well solved by GNSS. In complement, INSAR shows its contribution with respect to GNSS, as it allows to dramatically increase the spatial information. Combining SAR dataset provided by ALOS-1, ALOS-2 and Sentinel-1 enables to generate consistent time series and dense maps of ground displacements by InSAR on the whole island over different periods. This possibility of long time series of observations is particularly interesting for earthquake cycle study.
Our processing uses NSBAS interferometric chain (Doin et al., 2015), based on a SBAS approach, that includes several corrections applied before unwrapping, in particular correction of atmospheric delays predicted from the global atmospheric re-analysis ERA-Interim model, and local DEM error correction. These corrections are of particular importance as they reduce the variance of the phase across regions with high topographic gradients, like the Central Range in Taiwan, hence facilitating unwrapping step. Using the full archive of ALOS-1 PALSAR images, a first complete deformation map of Taiwan has been derived over the period 2007-2011. Our InSAR results offer an unprecedented continuous view of deformation field of the entire Island. For instance, in the Central Range, the LOS velocity map shows a clear pattern of deformation, consistent with a rapid uplift (cm/y) of the Central Range South of the island. This uplift, already partially documented by GPS and leveling, is clearly mapped here and seems to show an overall continuity. In southwestern Taiwan, the InSAR LOS velocity map provides a good coverage in the foothills area, revealing several localized areas of interseismic deformation that were overlooked in GNSS, and that can be correlated with tectonic structures. Among them, is the 15 km-long Lungchuan anticline, showing relative surface displacement toward satellite by several cm/year. Those observations, combined with a geological study and field survey (Le Beon et al., 2017), suggest the existence of a back-thrust fault that reaches the surface on western side of Lungchuan ridge and roots on the ~4 km deep Tainan detachment. This structure has also been activated during 2010 Mw 6.3 Jia-Shian Earthquake and the Meinong earthquake (02/05/2016, Mw6.4). A time series analysis can also be conducted on 2014-2018 period with Sentinel-1 data. Since end of 2014, we benefit from S1 SAR images, acquired in C-band, thus less favorable than PALSAR L-band on Taiwan Island. However, this drawback is balanced thanks to the high frequency of image acquisitions (12 days on Taiwan with S1-A and S1-B). We can also take advantage of the 2 different geometries of acquisition (both ascending and descending) to derive horizontal and vertical components of the deformation. The combination of ALOS and Sentinel-1 InSAR results, in addition to their high density of measure, covers different time periods and gives the opportunity to investigate temporal evolution of the deformation. Some areas, in particular in SW Taiwan, show changes in the tectonic deformation pattern, thus revealing transient behavior of some structures. Those observations can also be completed on several areas with previous ERS and Envisat INSAR results, offering an unique monitoring of more than 20 years.Numéro de notice : C2019-055 Affiliation des auteurs : LASTIG+Ext (2016-2019) Thématique : IMAGERIE Nature : Poster nature-HAL : ComSansActesPubliés-Unpublished DOI : sans En ligne : https://lps19.esa.int/NikalWebsitePortal/living-planet-symposium-2019/lps19/Agen [...] Format de la ressource électronique : vers le résumé Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96644 Discriminating ship from radio frequency interference based on noncircularity and non-gaussianity in sentinel-1 SAR imagery / Xiangguang Leng in IEEE Transactions on geoscience and remote sensing, vol 57 n° 1 (January 2019)
[article]
Titre : Discriminating ship from radio frequency interference based on noncircularity and non-gaussianity in sentinel-1 SAR imagery Type de document : Article/Communication Auteurs : Xiangguang Leng, Auteur ; Kefeng Ji, Auteur ; Shilin Zhou, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 352 - 363 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] interférence
[Termes IGN] navire
[Termes IGN] radiofréquenceRésumé : (Auteur) Complex information in single-channel synthetic aperture radar (SAR) imagery is seldom used. This is a common practice based on the conventional resolution theory. However, with the advent of high-resolution SAR sensors, information in the complex data has been found to be of significance for ocean applications. In particular, we note that there is a special type of instrumental artifact in Sentinel-1 images. It is rarely researched and may be attributed to radio frequency interference (RFI). It has similar intensity with ships and can degrade ocean interpretation performance severely. This paper proposes an innovative method to discriminate ships from RFIs based on noncircularity and non-Gaussianity. Among them, noncircularity is calculated based on the measure called normalized noncircularity, and non-Gaussianity is estimated based on the complex generalized Gaussian distribution. The discrimination rationale is analyzed in detail. The experimental procedure is based on Sentinel-1 interferometric wide swath products. Only cross-polarization data are tested since RFIs are quite weak in co-polarization data. It is found that noncircularity and non-Gaussianity can characterize and identify the difference between ships and RFIs. Ships present larger noncircularity and sup-Gaussianity while RFIs are found to exhibit quite low noncircularity and mainly show sub-Gaussianity. The proposed method achieves quite good performance. These results show that noncircularity and non-Gaussianity are extremely helpful complements for single-channel SAR imagery interpretation. Numéro de notice : A2019-107 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2854661 Date de publication en ligne : 14/08/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2854661 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92414
in IEEE Transactions on geoscience and remote sensing > vol 57 n° 1 (January 2019) . - pp 352 - 363[article]Earth observation, remote sensing and geoscientific ground investigations for archaeological and heritage research / Deodato Tapete (2019)
Titre : Earth observation, remote sensing and geoscientific ground investigations for archaeological and heritage research Type de document : Monographie Auteurs : Deodato Tapete, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2019 Importance : 304 p. ISBN/ISSN/EAN : 978-3-03921-194-4 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Active Microwave Instrumentation Synthetic Aperture Radar
[Termes IGN] analyse d'image orientée objet
[Termes IGN] bande C
[Termes IGN] bande X
[Termes IGN] détection automatique
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image captée par drone
[Termes IGN] image Sentinel-MSI
[Termes IGN] modèle numérique de terrain
[Termes IGN] patrimoine archéologique
[Termes IGN] site archéologiqueRésumé : (Auteur) This book collects 15 papers written by renowned scholars from across the globe that showcase the forefront research in Earth observation (EO), remote sensing (RS), and geoscientific ground investigations to study archaeological records and cultural heritage. Archaeologists, anthropologists, geographers, remote sensing, and archaeometry experts share their methodologies relying on a wealth of techniques and data including, but not limited to: very high resolution satellite images from optical and radar space-borne sensors, air-borne surveys, geographic information systems (GIS), archaeological fieldwork, and historical maps.A couple of the contributions highlight the value of noninvasive and nondestructive laboratory analyses (e.g., neutron diffraction) to reconstruct ancient manufacturing technologies, and of geological ground investigations to corroborate hypotheses of historical events that shaped cultural landscapes.Case studies encompass famous UNESCO World Heritage Sites (e.g., the Nasca Lines in Peru), remote and yet-to-discover archaeological areas in tropical forests in central America, European countries, south Asian changing landscapes, and environments which are arid nowadays but were probably full of woody vegetation in the past.Finally, the reader can learn about the state-of-the-art of education initiatives to train site managers in the use of space technologies in support of their activities, and can understand the legal aspects involved in the application of EO and RS to address current challenges of African heritage preservation. Numéro de notice : 26501 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Recueil / ouvrage collectif DOI : 10.3390/books978-3-03921-194-4 En ligne : https://doi.org/10.3390/books978-3-03921-194-4 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97049 Evaluating SAR-optical sensor fusion for aboveground biomass estimation in a Brazilian tropical forest / Aline Bernarda Debastiani in Annals of forest research, vol 62 n° 1 (January - June 2019)PermalinkEvaluating the capability of the Sentinel 2 data for soil organic carbon prediction in croplands / Fabio Castaldi in ISPRS Journal of photogrammetry and remote sensing, vol 147 (January 2019)PermalinkÉvaluation de la dégradation des forêts primaires par télédétection dans un espace de front pionnier consolidé d’Amazonie orientale (Paragominas) / Ali Fadhil Hasan (2019)PermalinkEvaluation of time-series SAR and optical images for the study of winter land-use / Julien Denize (2019)PermalinkExploitation de séries temporelles d'images multi-sources pour la cartographie des surfaces en eau / Filsa Bioresita (2019)PermalinkPermalinkGéomatique webmapping en open source / David Collado (2019)PermalinkPermalinkGlobal observations of ocean surface winds and waves using spaceborne synthetic aperture radar measurements / Huimin Li (2019)PermalinkPermalinkImproving the spatial bias correction algorithm in SMOS image reconstruction processor : validation of soil moisture retrievals with in situ data / Ali Khazaal in IEEE Transactions on geoscience and remote sensing, vol 57 n° 1 (January 2019)PermalinkIndividual tree detection and crown delineation with 3D information from multi-view satellite Images / Changlin Xiao in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 1 (January 2019)PermalinkPermalinkJoint analysis of SAR and optical satellite images time series for grassland event detection / Anatol Garioud (2019)PermalinkPermalinkPermalinkMéthodes d'exploitation de données historiques pour la production de cartes d'occupation des sols à partir d'images de télédétection et en absence de données de référence de la période à cartographier / Benjamin Tardy (2019)PermalinkMonitoring crops water needs at high spatio-temporal resolution by synergy of optical / thermal and radar observations / Abdelhakim Amazirh (2019)PermalinkPermalinkA multi-faceted CNN architecture for automatic classification of mobile LiDAR data and an algorithm to reproduce point cloud samples for enhanced training / Bhavesh Kumar in ISPRS Journal of photogrammetry and remote sensing, vol 147 (January 2019)PermalinkMultimodal scene understanding: algorithms, applications and deep learning, ch. 11. Decision fusion of remote-sensing data for land cover classification / Arnaud Le Bris (2019)PermalinkMultitemporal SAR images denoising and change detection : applications to Sentinel-1 data / Weiying Zhao (2019)PermalinkPermalinkPermalinkPermalinkPermalinkPermalinkPermalinkRetrieving relevant land cover and land use data to study urban climate change / Bénédicte Bucher (2019)PermalinkPermalinkPermalinkPermalinkPermalinkPermalinkSemantic aware quality evaluation of 3D building models : Modeling and simulation / Oussama Ennafii (2019)PermalinkSensitivity of urban material classification to spatial and spectral configurations from visible to short-wave infrared / Arnaud Le Bris (2019)PermalinkPermalinkA spatiotemporal calculus for reasoning about land-use trajectories / Adeline Marinho Maciel in International journal of geographical information science IJGIS, Vol 33 n° 1-2 (January - February 2019)PermalinkPermalinkThe necessary yet complex evaluation of 3D city models: a semantic approach / Oussama Ennafii (2019)PermalinkTime-space tradeoff in deep learning models for crop classification on satellite multi-spectral image time series / Vivien Sainte Fare Garnot (2019)PermalinkToward global soil moisture monitoring with sentinel-1 : harnessing assets and overcoming obstacles / Bernhard Bauer-Marschallinger in IEEE Transactions on geoscience and remote sensing, vol 57 n° 1 (January 2019)PermalinkTraitement d'images multispectrales et spatialisation des données pour la caractérisation de la matière organique des phases solides naturelles / Kevin Jacq (2019)PermalinkUnderstanding of atmospheric systems with efficient numerical methods for observation and prediction / Lei-Ming Ma (2019)PermalinkUrban deformation monitoring using persistent scatterer Interferometry and SAR tomography / Michele Crosetto (2019)Permalink