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Geospatial analysis of September, 2019 floods in the lower gangetic plains of Bihar using multi-temporal satellites and river gauge data / C.M. Bhatt in Geomatics, Natural Hazards and Risk, vol 12 n° 1 (2021)
[article]
Titre : Geospatial analysis of September, 2019 floods in the lower gangetic plains of Bihar using multi-temporal satellites and river gauge data Type de document : Article/Communication Auteurs : C.M. Bhatt, Auteur ; Amitesh Gupta, Auteur ; Arijit Roy, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 84 - 102 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] cartographie des risques
[Termes IGN] crue
[Termes IGN] données spatiotemporelles
[Termes IGN] Gange (fleuve)
[Termes IGN] humidité du sol
[Termes IGN] image Aqua-AMSR
[Termes IGN] image Aqua-MODIS
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] image Terra-MODIS
[Termes IGN] Inde
[Termes IGN] inondation
[Termes IGN] précipitationRésumé : (auteur) During late September, 2019 Bihar was struggling with severe flooding problem, which otherwise is marked as a period of flood recession due to withdrawal of south-east monsoons. The present study assess the flood situation using Sentinel-1 SAR images and complements the understanding about the flood event using long term (2000-18) multi-temporal space based flood sensitive proxy indicators like precipitation (GPM), soil moisture (AMSR-2), vegetation condition (MODIS) together with ground based river gauge (CWC) data. The study reveals that in 2019 during the 39th week of the year (late September) the central and eastern parts of Bihar witnessed heavy precipitation (176 percent higher than average), leading to enhanced soil moisture build up (19 percent higher than average) and consequently triggering severe flooding. River Ganga was observed to be flowing above danger level for almost two weeks. Due to the prolonged submergence by floodwaters a significant drop was observed in the NDVI and EVI values of about 13.7 and 11.1 percent respectively from the normal. About 8.36 lakh ha area was observed to be inundated, impacting about 9.26 million population. Patna followed by Bhagalpur were the two worst affected districts with almost 30% and 36% of districts geographical area being flooded. Numéro de notice : A2021-107 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475705.2020.1861113 Date de publication en ligne : 24/12/2020 En ligne : https://doi.org/10.1080/19475705.2020.1861113 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96904
in Geomatics, Natural Hazards and Risk > vol 12 n° 1 (2021) . - pp 84 - 102[article]How do people perceive the disclosure risk of maps? Examining the perceived disclosure risk of maps and its implications for geoprivacy protection / Junghwan Kim in Cartography and Geographic Information Science, vol 48 n° 1 (January 2021)
[article]
Titre : How do people perceive the disclosure risk of maps? Examining the perceived disclosure risk of maps and its implications for geoprivacy protection Type de document : Article/Communication Auteurs : Junghwan Kim, Auteur ; Mei-Po Kwan, Auteur ; Margaret C. Levenstein, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2 - 20 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Information géographique
[Termes IGN] cartographie thématique
[Termes IGN] confidentialité
[Termes IGN] données personnelles
[Termes IGN] droit privé
[Termes IGN] entretien d'enquête
[Termes IGN] géomasquage
[Termes IGN] information cartographique
[Termes IGN] photo-identification
[Termes IGN] protection de la vie privée
[Termes IGN] vulnérabilitéRésumé : (auteur) This research examines how people subjectively perceive the disclosure risk of a map using original data collected in an online survey with 856 participants. The results indicate that perceived disclosure risk increases as the amount of locational information displayed on a map increases. Compared to point-based maps, perceived disclosure risk is significantly lower for kernel density maps, convex hull maps, and standard deviational ellipse maps. The results also revealed that perceived disclosure risk is affected by map scale and the presence of information of other people on a map. For geomasking methods, perceived disclosure risk decreases as aggregation level increases and as relocation distance increases. However, aggregation methods (point to polygon) are more effective in preventing the re-identification of individuals when compared to relocation methods (point to point). Lastly, the perceived disclosure risk of a map that displays socially-vulnerable people is significantly higher than that of a map that displays non-vulnerable groups. Specifically, a map displaying the private locations of elementary school students has the highest perceived disclosure risk. Based on the results, a set of geoprivacy protection guidelines for mapping people’s private locations to minimize people’s perceived disclosure risk is proposed. Implications for mapping infectious diseases like the COVID-19 are also discussed. Numéro de notice : A2021-016 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2020.1794976 Date de publication en ligne : 24/08/2020 En ligne : https://doi.org/10.1080/15230406.2020.1794976 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96451
in Cartography and Geographic Information Science > vol 48 n° 1 (January 2021) . - pp 2 - 20[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-2021011 RAB Revue Centre de documentation En réserve L003 Disponible A hybrid approach for recovering high-resolution temporal gravity fields from satellite laser ranging / Anno Löcher in Journal of geodesy, vol 95 n° 1 (January 2021)
[article]
Titre : A hybrid approach for recovering high-resolution temporal gravity fields from satellite laser ranging Type de document : Article/Communication Auteurs : Anno Löcher, Auteur ; Jürgen Kusche, Auteur Année de publication : 2021 Article en page(s) : n° 6 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] champ de pesanteur terrestre
[Termes IGN] changement temporel
[Termes IGN] données GRACE
[Termes IGN] données TLS (télémétrie)
[Termes IGN] facteur d'échelle
[Termes IGN] fonction orthogonale
[Termes IGN] harmonique sphérique
[Termes IGN] modélisation
[Termes IGN] série temporelleRésumé : (auteur) A new approach to recover time-variable gravity fields from satellite laser ranging (SLR) is presented. It takes up the concept of lumped coefficients by representing the temporal changes of the Earth’s gravity field by spatial patterns via combinations of spherical harmonics. These patterns are derived from the GRACE mission by decomposing the series of monthly gravity field solutions into empirical orthogonal functions (EOFs). The basic idea of the approach is then to use the leading EOFs as base functions in the gravity field modelling and to adjust the respective scaling factors straightforward within the dynamic orbit computation; only for the lowest degrees, the spherical harmonic coefficients are estimated separately. As a result, the estimated gravity fields have formally the same spatial resolution as GRACE. It is shown that, within the GRACE time frame, both the secular and the seasonal signals in the GRACE time series are reproduced with high accuracy. In the period prior to GRACE, the SLR solutions are in good agreement with other techniques and models and confirm, for instance, that the Greenland ice sheet was stable until the late 1990s. Further validation is done with the first monthly fields from GRACE Follow-On, showing a similar agreement as with GRACE itself. Significant differences to the reference data only emerge occasionally when zooming into smaller river basins with strong interannual mass variations. In such cases, the approach reaches its limits which are set by the low spectral sensitivity of the SLR satellites and the strong constraints exerted by the EOFs. The benefit achieved by the enhanced spatial resolution has to be seen, therefore, primarily in the proper capturing of the mass signal in medium or large areas rather than in the opportunity to focus on isolated spatial details. Numéro de notice : A2021-026 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-020-01460-x Date de publication en ligne : 23/12/2020 En ligne : https://doi.org/10.1007/s00190-020-01460-x Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96710
in Journal of geodesy > vol 95 n° 1 (January 2021) . - n° 6[article]Image matching from handcrafted to deep features: A survey / Jiayi Ma in International journal of computer vision, vol 29 n° 1 (January 2021)
[article]
Titre : Image matching from handcrafted to deep features: A survey Type de document : Article/Communication Auteurs : Jiayi Ma, Auteur ; Xingyu Jiang, Auteur ; Aoxiang Fan, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 23 - 79 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement d'images
[Termes IGN] appariement de graphes
[Termes IGN] apprentissage profond
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] lissage de courbe
[Termes IGN] recalage d'imageRésumé : (auteur) As a fundamental and critical task in various visual applications, image matching can identify then correspond the same or similar structure/content from two or more images. Over the past decades, growing amount and diversity of methods have been proposed for image matching, particularly with the development of deep learning techniques over the recent years. However, it may leave several open questions about which method would be a suitable choice for specific applications with respect to different scenarios and task requirements and how to design better image matching methods with superior performance in accuracy, robustness and efficiency. This encourages us to conduct a comprehensive and systematic review and analysis for those classical and latest techniques. Following the feature-based image matching pipeline, we first introduce feature detection, description, and matching techniques from handcrafted methods to trainable ones and provide an analysis of the development of these methods in theory and practice. Secondly, we briefly introduce several typical image matching-based applications for a comprehensive understanding of the significance of image matching. In addition, we also provide a comprehensive and objective comparison of these classical and latest techniques through extensive experiments on representative datasets. Finally, we conclude with the current status of image matching technologies and deliver insightful discussions and prospects for future works. This survey can serve as a reference for (but not limited to) researchers and engineers in image matching and related fields. Numéro de notice : A2021-131 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s11263-020-01359-2 Date de publication en ligne : 04/08/2020 En ligne : https://doi.org/https://doi.org/10.1007/s11263-020-01359-2 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96967
in International journal of computer vision > vol 29 n° 1 (January 2021) . - pp 23 - 79[article]Initialization methods of convolutional neural networks for detection of image manipulations / Ivan Castillo Camacho (2021)
Titre : Initialization methods of convolutional neural networks for detection of image manipulations Titre original : Méthodes d'initialisation des réseaux de neurones convolutifs pour la détection des manipulations d'images Type de document : Thèse/HDR Auteurs : Ivan Castillo Camacho, Auteur ; Kai Wang, Directeur de thèse Editeur : Grenoble [France] : Université Grenoble Alpes Année de publication : 2021 Importance : 145 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse pour obtenir le grade de Docteur de l'Université Grenoble, spécialité : signal, image, paroles, télécomsLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] altération
[Termes IGN] apprentissage profond
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] covariance
[Termes IGN] détection d'anomalie
[Termes IGN] estompage
[Termes IGN] filtre passe-haut
[Termes IGN] flux de données
[Termes IGN] infraction
[Termes IGN] manipulation de données
[Termes IGN] qualité des données
[Termes IGN] retouche
[Termes IGN] varianceIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Fake images and videos have engulfed mass communication media. This is not something recent, manipulations and forgeries have occurred since the advent of photography itself. These alterations can go from innocent retouches in an attempt to make an image visually attractive to the spread of misleading information or even the use of false media in legal instances. Accordingly, the creation of methods that can help us assure the authenticity of an image presented as non-modified is of paramount importance. In this thesis, we aim at detecting image manipulation operations using deep learning techniques. We present three methods showing the progression of our work under one common objective, i.e, the design and test of Convolutional Neural Network (CNN) initialization methods for image forensic problems with a variance stability focus for the output of a CNN layer.First, we carry out an extensive review of the state of the art in deep-learning-based methods for image forensics. From this review we can confirm that the first layer of a CNN has big impact on the final performance. Specifically, the initialization used on the first-layer filters plays an important role that should be in line with the image forensic task in hand.As our first attempt to address this research problem, we propose a low-complexity initialization method for CNNs. Taking advantage of previous methods designed for the computer vision field, we extend the popular Xavier method to design a filter that would provide variance stability after a convolution operation. This method generates a set of random high-pass filters for the initialization of a CNN's first layer. These filters allow us to better identify forensic traces which usually lie towards the high-frequency part of the image.This first approach constitutes a good staring point of our work. However, a wrong assumption, largely utilized in the research community, was made. This is corrected in our second method where we follow a different data-dependent approach and take into consideration the real statistical properties of natural images. Accordingly, we propose a scaling method for first-layer filters which can cope well with different CNN initialization algorithms. The objective remains in keeping the stability of the variance of data flow in a CNN. We also present theoretical and experimental studies on the output variance for convolutional filter, which are the basis of our proposed data-dependent scaling.Next we describe a revisited version of our first proposal now with a corrected assumption on the statistics of natural images. More precisely, we propose an improved random high-pass initialization method which does not explicitly compute the statistics of input data. We believe that such a ``data-independent'' approach has higher flexibility and broader application range than our second method in situations where the computation of input statistics is not possible.Our proposed methods are tested over several image forensic problems and different CNN architectures.Finally, during all this thesis work we took part in a challenge competition of image forgery detection organized by the French National Research Agency and the French Directorate General of Armaments. We explain in the Appendix the objectives of the challenge along with a brief description of our work conducted for the competition. Note de contenu : 1- Introduction
2- Background knowledge and state of the art
3- Random high-pass initialization
4- Data-dependent initialization
5- Revisiting the random high-pass initialization
6- Conclusions and perspectivesNuméro de notice : 28437 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : signal, image, paroles, télécoms : Grenoble : 2021 DOI : sans En ligne : https://hal.science/tel-03346063/ Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98833 Jahresbericht 2020 des Bundesamtes für Kartographie und Geodäsie / Bundesamt für Kartographie und Geodäsie (2021)PermalinkPermalinkPermalinkMéthodes et outils pour l’analyse spatiale exploratoire en géolinguistique : contributions aux humanités numériques spatialisées / Clément Chagnaud (2021)PermalinkPermalinkModélisation numérique des paysages sonores urbains / Jonathan Siliézar (2021)PermalinkOptimisations cartographiques pour la gestion des crises et des risques majeurs : le cas de la cartographie des dommages post-catastrophes / Thomas Candela (2021)PermalinkProposition d’un référentiel de description et de détection de la végétation dans une agglomération / Mathilde Segaud (2021)PermalinkPermalinkRadio base stations and electromagnetic fields: GIS applications and models for identifying possible risk factors and areas exposed. Some exemplifications in Rome / Cristiano Pesaresi in ISPRS International journal of geo-information, vol 10 n° 1 (January 2021)Permalink