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Detecting preseismic signals in GRACE gravity solutions: Application to the 2011 Tohoku Mw 9.0 earthquake / Isabelle Panet in Journal of geophysical research : Solid Earth, vol 127 n° 8 (August 2022)
[article]
Titre : Detecting preseismic signals in GRACE gravity solutions: Application to the 2011 Tohoku Mw 9.0 earthquake Type de document : Article/Communication Auteurs : Isabelle Panet , Auteur ; Clément Narteau, Auteur ; Jean-Michel Lemoine, Auteur ; Sylvain Bonvalot, Auteur ; Dominique Remy, Auteur Année de publication : 2022 Projets : 2-Pas d'info accessible - article non ouvert / Article en page(s) : n° e2022JB024542 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] déformation de la croute terrestre
[Termes IGN] données GRACE
[Termes IGN] gradient de gravitation
[Termes IGN] Pacifique (océan)
[Termes IGN] séisme
[Termes IGN] sismicité
[Termes IGN] subduction
[Termes IGN] tectonique des plaques
[Termes IGN] Tohoku (Japon)Résumé : (auteur) We conduct a global analysis of GRACE-reconstructed gravity gradients from July 2004 to February 2011, to test whether the deep signals preceding the March 2011 Tohoku earthquake can be detected before the event as a specific feature originating from solid Earth. First, we improve the angular resolution of the gravity gradients using two overlapping ranges of azimuthal sensitivity to investigate short-term signals of large amplitude aligned with the orientation of the Northwestern Pacific subduction. Then, we set-up a method to identify consistent solid Earth signals shared by different GRACE gravity models. Robust signals in a model are selected based on their spatial overlap and relative intensity with the signals of another model, so that their sensitivity to the GRACE data processing and ocean dealiasing product can be tested. We show that the dipolar gravity gradient anomaly before the Tohoku earthquake is nearly unique in space and time in the GRACE GRGS03 solutions. A well-resolved dipolar spatial pattern, typical of dislocations within the solid Earth and poorly sensitive to the ocean dealiasing model, is detected. In addition, the preseismic gravity gradient increase is highly consistent between the GRGS03 and CSR06 solutions, independently from their respective oceanic corrections, and can be clearly distinguished from rare anomalies of similar amplitudes all associated with the water cycle over continental areas. Our approach offers solutions for the continuous monitoring of the Pacific subduction belt to document transient slabs motions in real time from global satellite gravity fields, and their relation with shallower deformations and seismic events. Numéro de notice : A2022-605 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Autre URL associée : vers HAL Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1029/2022JB024542 Date de publication en ligne : 06/08/2022 En ligne : https://doi.org/10.1029/2022JB024542 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101384
in Journal of geophysical research : Solid Earth > vol 127 n° 8 (August 2022) . - n° e2022JB024542[article]Generating impact maps from bomb craters automatically detected in aerial wartime images using marked point processes / Christian Kruse in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 5 (August 2022)
[article]
Titre : Generating impact maps from bomb craters automatically detected in aerial wartime images using marked point processes Type de document : Article/Communication Auteurs : Christian Kruse, Auteur ; Dennis Wittich, Auteur ; Franz Rottensteiner, Auteur ; et al., Auteur Année de publication : 2022 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme du recuit simulé
[Termes IGN] chevauchement
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection automatique
[Termes IGN] échantillonnage de données
[Termes IGN] Europe centrale
[Termes IGN] guerre
[Termes IGN] image aérienne
[Termes IGN] méthode de Monte-Carlo par chaînes de Markov
[Termes IGN] méthode fondée sur le noyau
[Termes IGN] processus ponctuel marqué
[Termes IGN] processus stochastiqueRésumé : (auteur) Even more than 75 years after the Second World War, numerous unexploded bombs (duds) linger in the ground and pose a considerable hazard to society. The areas containing these duds are documented in so-called impact maps, which are based on locations of exploded bombs; these locations can be found in aerial images taken shortly after bombing. To generate impact maps, in this paper we present a novel approach based on marked point processes (MPPs) for the automatic detection of bomb craters in such images, some of which are overlapping. The object model for the craters is represented by circles and is embedded in the MPP-framework. By means of stochastic sampling, the most likely configuration of objects within the scene is determined. Each configuration is evaluated using an energy function that describes the consistency with a predefined object model. High gradient magnitudes along the object borders and homogeneous grey values inside the objects are favoured, while overlaps between objects are penalized. Reversible Jump Markov Chain Monte Carlo sampling, in combination with simulated annealing, provides the global optimum of the energy function. Our procedure allows the combination of individual detection results covering the same location. Afterwards, a probability map for duds is generated from the detections via kernel density estimation and areas around the detections are classified as contaminated, resulting in an impact map. Our results, based on 74 aerial wartime images taken over different areas in Central Europe, show the potential of the method; among other findings, a clear improvement is achieved by using redundant image information. We also compared the MPP method for bomb crater detection with a state-of-of-the-art convolutional neural network (CNN) for generating region proposals; it turned out that the CNN outperforms the MPPs if a sufficient amount of representative training data is available and a threshold for a region to be considered as crater is properly tuned prior to running the experiments. If this is not the case, the MPP approach achieves better results. Numéro de notice : A2022-515 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.ophoto.2022.100017 Date de publication en ligne : 02/06/2022 En ligne : https://doi.org/10.1016/j.ophoto.2022.100017 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101057
in ISPRS Open Journal of Photogrammetry and Remote Sensing > vol 5 (August 2022)[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)
[article]
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.pdfLangues : 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'appuiRésumé : (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
in IEEE Transactions on geoscience and remote sensing > vol 60 n° 8 (August 2022) . - pp[article]Multiscale assimilation of Sentinel and Landsat data for soil moisture and Leaf Area Index predictions using an ensemble-Kalman-filter-based assimilation approach in a heterogeneous ecosystem / Nicola Montaldo in Remote sensing, vol 14 n° 14 (July-2 2022)
[article]
Titre : Multiscale assimilation of Sentinel and Landsat data for soil moisture and Leaf Area Index predictions using an ensemble-Kalman-filter-based assimilation approach in a heterogeneous ecosystem Type de document : Article/Communication Auteurs : Nicola Montaldo, Auteur ; Andrea Gaspa, Auteur ; Roberto Corona, Auteur Année de publication : 2022 Article en page(s) : n° 3458 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] assimilation des données
[Termes IGN] bassin méditerranéen
[Termes IGN] écosystème
[Termes IGN] filtre de Kalman
[Termes IGN] humidité du sol
[Termes IGN] image Landsat-8
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] Leaf Area Index
[Termes IGN] modèle dynamique
[Termes IGN] modèle hydrographique
[Termes IGN] Sardaigne
[Termes IGN] zone semi-arideRésumé : (auteur) Data assimilation techniques allow researchers to optimally merge remote sensing observations in ecohydrological models, guiding them for improving land surface fluxes predictions. Presently, freely available remote sensing products, such as those of Sentinel 1 radar, Landsat 8 sensors, and Sentinel 2 sensors, allow the monitoring of land surface variables (e.g., radar backscatter for soil moisture and the normalized difference vegetation index (NDVI) and for leaf area index (LAI)) at unprecedentedly high spatial and time resolutions, appropriate for heterogeneous ecosystems, typical of semiarid ecosystems characterized by contrasting vegetation components (grass and trees) competing for water use. A multiscale assimilation approach that assimilates radar backscatter and grass and tree NDVI in a coupled vegetation dynamic–land surface model is proposed. It is based on the ensemble Kalman filter (EnKF), and it is not limited to assimilating remote sensing data for model predictions, but it uses assimilated data for dynamically updating key model parameters (the ENKFdc approach), including saturated hydraulic conductivity and grass and tree maintenance respiration coefficients, which are highly sensitive parameters of soil–water balance and biomass budget models, respectively. The proposed EnKFdc assimilation approach facilitated good predictions of soil moisture, grass, and tree LAI in a heterogeneous ecosystem in Sardinia for a 3-year period with contrasting hydrometeorological (dry vs. wet) conditions. Contrary to the EnKF-based approach, the proposed EnKFdc approach performed well for the full range of hydrometeorological conditions and parameters, even assuming extremely biased model conditions with very high or low parameter values compared with the calibrated (“true”) values. The EnKFdc approach is crucial for soil moisture and LAI predictions in winter and spring, key seasons for water resources management in Mediterranean water-limited ecosystems. The use of ENKFdc also enabled us to predict evapotranspiration and carbon flux well, with errors of less than 4% and 15%, respectively; such results were obtained even with extremely biased initial model conditions. Numéro de notice : A2022-574 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs14143458 En ligne : https://doi.org/10.3390/rs14143458 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101293
in Remote sensing > vol 14 n° 14 (July-2 2022) . - n° 3458[article]Effects of offsets and outliers on the sea level trend at Antalya 2 tide gauge within the Eastern Mediterranean Sea / Mehmet Emin Ayhan in Marine geodesy, vol 45 n° 4 (July 2022)
[article]
Titre : Effects of offsets and outliers on the sea level trend at Antalya 2 tide gauge within the Eastern Mediterranean Sea Type de document : Article/Communication Auteurs : Mehmet Emin Ayhan, Auteur Année de publication : 2022 Article en page(s) : pp 329 - 359 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] autocorrélation
[Termes IGN] compensation
[Termes IGN] données marégraphiques
[Termes IGN] Méditerranée, mer
[Termes IGN] modèle statistique
[Termes IGN] niveau de la mer
[Termes IGN] niveau moyen des mers
[Termes IGN] Turquie
[Termes IGN] valeur aberrante
[Termes IGN] variation saisonnière
[Vedettes matières IGN] AltimétrieRésumé : (auteur) Antalya 2 tide gauge (TG) station is located on the coast of Turkey within the Eastern Mediterranean Sea. Relative sea level trends 6.0 ± 1.5 and 6.44 ± 0.45 mm/year over 1985–2009 at Antalya 2 TG are different from the trend (1.6 ± 1.5 mm/year over 1935–1977) at Antalya TG within 10 km. In order to investigate this trend discrepancy, the monthly mean series at Antalya 2 TG is re-analyzed for offsets, outliers and trend estimation. The Zivot-Andrews method and the Qp outlier test result in one offset at 1994.0417 year with magnitude of 71.24 ± 13.48 mm and nine outliers. The series, corrected for the offset and outliers, de-seasonalized and filled for missed points, is identified as trend-stationary process and analyzed for trend estimation by various models. The optimal model providing the lowest Akaike Information Criteria is polynomial linear trend with multiplicative seasonal Autoregressive Moving Average (ARMA(2,0)x(1,0)12). The estimated relative sea level trend by the optimal model is 1.77 ± 0.65 mm/year. The large trend discrepancy at Antalya 2 TG is accounted for by one offset primarily (∼71%) and nine outliers (∼3%). Numéro de notice : A2022-516 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1080/01490419.2022.2047843 Date de publication en ligne : 11/03/2022 En ligne : https://doi.org/10.1080/01490419.2022.2047843 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101064
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