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Titre : Atlas of remote sensing of the Wenchuan earthquake : Cas- Project Team of Remote Sensing for Wenchuan Earthquake Type de document : Monographie Auteurs : Huadong Guo, Auteur Editeur : Boca Raton, New York, ... : CRC Press Année de publication : 2019 Importance : 259 p. Format : 26 x 28 cm ISBN/ISSN/EAN : 978-1-4398-1674-5 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse du paysage
[Termes IGN] carte géologique
[Termes IGN] détection de changement
[Termes IGN] dommage matériel
[Termes IGN] image optique
[Termes IGN] image radar
[Termes IGN] image Radarsat
[Termes IGN] image satellite
[Termes IGN] impact sur l'environnement
[Termes IGN] réseau routier
[Termes IGN] séisme
[Termes IGN] Setchouan (Chine)
[Termes IGN] zone urbaineRésumé : (éditeur) In May 12, 2008, the Wenchuan County earthquake caused devastating loss of human life and property. Applying all the remote sensing technology available, the Chinese Academy of Sciences immediately launched into action, making full use of its state-of-the-art facilities, remote sensing planes, and satellites to amass invaluable optical and radar data. This unprecedented use of comprehensive remote sensing techniques provided accurate, up to the minute information for disaster management and has left us with a visually stunning and beautiful record that is as much a scientific achievement as it is an artistic one. Based on the accumulated data and images collected by the Project Team of Remote Sensing Monitoring and Assessment of the Wenchuan Earthquake, Atlas of Remote Sensing of the Wenchuan Earthquake documents the events as they happened in real time. The book covers the disaster from six aspects: geological, barrier lakes, collapsed buildings, damaged roads, destroyed farmland and forests, and demolished infrastructure. It also demonstrates that the Dujiangyan Irrigation Project, which has been standing for 2000 years, remains fully functioning, and keeps the Chengdu Plain operating optimally even after the earthquake. Translated into English for the first time, the Atlas presents a pictorial summation of this unique project. It chronicles the event with over 280 before and after color images from a range of perspectives. This volume dramatically demonstrates the value of remote sensing for understanding how an earthquake unfolds and the potential of remote sensing in helping coordinate emergency relief. A pictorial record of events as they unfolded, this book provides a systematic documentation of earthquake damage that can be used to prepare for future seismic events. Note de contenu : 1- Remote sensing data
2- Geological disaster
3- Barrier lakes
4- Collapsed buildings
5- Damaged roads
6- Destroyed farmlands and forests
7- Demolished infrastructure
8- Civilization perseveresNuméro de notice : 25917 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Monographie En ligne : https://library.oapen.org/handle/20.500.12657/40124 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96100
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 : Geospatial analyses of Earth observation (EO) data Type de document : Monographie Auteurs : Antonio Pepe, Éditeur scientifique ; Qing Zhao, Éditeur scientifique Editeur : London [UK] : IntechOpen Année de publication : 2019 Importance : 136 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-1-78984-584-6 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] aérosol
[Termes IGN] analyse spatiale
[Termes IGN] bassin hydrographique
[Termes IGN] bruit (théorie du signal)
[Termes IGN] cartographie géologique
[Termes IGN] changement climatique
[Termes IGN] couleur (variable spectrale)
[Termes IGN] détection de changement
[Termes IGN] données environnementales
[Termes IGN] image hyperspectrale
[Termes IGN] image optique
[Termes IGN] image Sentinel-MSI
[Termes IGN] Italie
[Termes IGN] lac
[Termes IGN] Malawi
[Termes IGN] minéral
[Termes IGN] observation de la Terre
[Termes IGN] risque naturel
[Termes IGN] télédétection spatiale
[Termes IGN] transformation de coordonnées
[Termes IGN] utilisation du solRésumé : (Editeur) Earth Observation and Geospatial Analysis presents current research related to the observation of Earth with sensors operating at various wavelengths. The book describes the use of remote sensing technologies for detecting and monitoring Earth's environmental changes (including surface and atmosphere) and its modifications over time. Chapters cover different research aspects in the framework of remote sensing with a particular emphasis on the use of hyperspectral and optical imageries. The presented experiments concern the study of soil properties, the analysis of land use/land changes, the analysis of bio-aerosols as well as the color of water, the investigation of the scar and samples of a cosmic meteoritic impact, and the theoretical treatment of the operation of spatial coordinate transformation in noisy environments. Overall, this book provides an overview of the adopted methodologies for the accomplishment of geospatial analyses to identify environmental changes due to climate change and natural phenomena. Note de contenu : 1. Application of Topographic Analyses for Mapping Spatial Patterns of Soil Properties
2. Clay Minerals Mapping from Imaging Spectroscopy
3. The Impact of Land Use and Land Cover Changes on the Nkula Dam in the Middle Shire River Catchment, Malawi
4. Advanced Methods for Spatial Analysis of Bioaerosol Long-Range Transport Processes
5. The Color of Water from Space: A Case Study for Italian Lakes from Sentinel-2
6. Bacubirito: An Outstanding Cosmic Sample on Earth
7. Spatial Coordinate Transformations with Noisy DataNuméro de notice : 26673 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Recueil / ouvrage collectif DOI : 10.5772/intechopen.74888 Date de publication en ligne : 27/11/2019 En ligne : https://www.intechopen.com/books/7304 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98967 Joint analysis of SAR and optical satellite images time series for grassland event detection / Anatol Garioud (2019)
Titre : Joint analysis of SAR and optical satellite images time series for grassland event detection Type de document : Article/Communication Auteurs : Anatol Garioud , Auteur ; Silvia Valero, Auteur ; Sébastien Giordano , Auteur ; Clément Mallet , Auteur Editeur : Leibniz : Leibniz Institute of Ecological Urban and Regional Development Année de publication : 2019 Conférence : ILUS 2019, 3rd International land use symposium, Land use changes: Trends and projections 04/12/2019 06/12/2019 Paris France programme sans actes Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] analyse d'image orientée objet
[Termes IGN] classification par réseau neuronal
[Termes IGN] cohérence des données
[Termes IGN] détection d'événement
[Termes IGN] détection de changement
[Termes IGN] image optique
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] Mâcon
[Termes IGN] prairie
[Termes IGN] puits de carboneRésumé : (auteur) Throughout Europe, grasslands are a major component of the landscape comprising 40% of agricultural land. Permanent Grassland (PM) means land used to grow herbaceous forage crops naturally (self-seeded) or through cultivation (sown) and that has not been included in the crop rotation of the holding for five years or more. PM are major ecosystems associated with high biodiversity which provide a wide range of ecosystem services (e.g. carbon sequestration, water quality, flood and erosion control). Grasslands have an important carbon storage capacity which is valuable for climate protection. Different studies have demonstrated that grassland managements such as grazing or mowing can cause significant effects on carbon storage in soils. Identifying and mapping grassland management practices over time can thus have important impact on climate studies. Remote sensing allows a synoptic and regular monitoring through systematic acquisitions of Earth Observation imagery. The emergence of free and easily Sentinel's satellite data provided by the European Copernicus program, offers new possibilities for grassland monitoring. Sentinel-1 (51) and Sentinel-2 (52) missions acquire radar and optical satellite image time series at high temporal resolution and fine spatial resolution. They fully match the requirements both for yearly and real-time monitoring. In this work, we target to jointly exploit both data sources to dynamically detect mowing events (MowEve) on permanent grasslands. Thematic related analysis of the datasets will highlight strengths and weaknesses of both optical and radar imagery. (i) 52 appears efficient for MowEve detection, with significant variations in the vegetation status that can be easily detected in the spectral signal extracted from the time series of images. But the temporal revisit of 52 although nominally 5 days is often reduced even by half due to the frequent cloud cover (ii) SAR images acquisitions being independent of illumination conditions or cloud cover allows for systematic acquisitions and revisit rate of 6 days. Data consistency makes S1 data essential during fast phenomena such as MowEve. Yet, radar data appears very sensitive to soil moisture, precipitations and geometrical properties making interpretation of their time series more challenging. MowEve detection being weakly supervised, the proposed methodology relies on applying traditional change detection strategies on a low-level fused 51 and S2 data representation. Recurrent Neural Networks will be trained to derive yearly or real-time synthetic 52 vegetation indices from both 52 and S1 observations. Furthermore, through attention mechanisms, our proposed RNN architecture will be able to take into account external data (climate, clouds, topography, etc.) so as to dynamically weight at parcel-level the contribution of optical and radar images. Such method will contribute to obtain dense temporal optical profiles without missing data and compatible with MowEve detection. An experimental evaluation will be carried out on a test site covering an area of 110x110 Km in France (Macon region). Object-oriented analysis will be presented based on permanent grasslands derived from the Land Parcel Identification System. The proposed approach will be compared with traditional MowEve methods essentially based on thresholding independently the different modalities. Numéro de notice : C2019-067 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComSansActesPubliés-Unpublished DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97022 Multitemporal SAR images denoising and change detection : applications to Sentinel-1 data / Weiying Zhao (2019)
Titre : Multitemporal SAR images denoising and change detection : applications to Sentinel-1 data Type de document : Thèse/HDR Auteurs : Weiying Zhao, Auteur ; Florence Tupin, Directeur de thèse Editeur : Bures-sur-Yvette : Université Paris-Saclay Année de publication : 2019 Autre Editeur : Paris [France] : Télécom ParisTech Importance : 181 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse de doctorat de l'Université Paris-Saclay préparée à Telecom ParisTech, Specialité de doctorat : traitement du signal et des imagesLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse diachronique
[Termes IGN] apprentissage profond
[Termes IGN] détection de changement
[Termes IGN] filtrage du bruit
[Termes IGN] filtrage temporel
[Termes IGN] filtre adaptatif
[Termes IGN] filtre de déchatoiement
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] radar à antenne synthétiqueIndex. décimale : THESE Thèses et HDR Résumé : (auteur) The inherent speckle which is attached to any coherent imaging system affects the analysis and interpretation of synthetic aperture radar (SAR) images. To take advantage of well-registered multi-temporal SAR images, we improve the adaptive nonlocal temporal filter with state-of-the-art adaptive denoising methods and propose a patch based adaptive temporal filter. To address the bias problem of the denoising results, we propose a fast and efficient multitemporal despeckling method. The key idea of the proposed approach is the use of the ratio image, provided by the ratio between an image and the temporal mean of the stack. This ratio image is easier to denoise than a single image thanks to its improved stationarity. Besides, temporally stable thin structures are well-preserved thanks to the multi-temporal mean. Without reference image, we propose to use a patch-based auto-covariance residual evaluation method to examine the residual image and look for possible remaining structural contents. With speckle reduction images, we propose to use simplified generalized likelihood ratio method to detect the change area, change magnitude and change times in long series of well-registered images. Based on spectral clustering, we apply the simplified generalized likelihood ratio to detect the time series change types. Then, jet colormap and HSV colorization may be used to vividly visualize the detection results. These methods have been successfully applied to monitor farmland area, urban area, harbor region, and flooding area changes. Note de contenu : Introduction
I- Basics of SAR and used data
II- Multitemporal denoising
III- Multi-temporal images change detection
Conclusion and perspectiveNuméro de notice : 25845 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Traitement du signal et des images : Telecom ParisTech : 2019 Organisme de stage : Telecom ParisTech nature-HAL : Thèse DOI : sans En ligne : https://pastel.archives-ouvertes.fr/tel-02095817/document Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95253 A 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)PermalinkSeparating the influence of vegetation changes in polarimetric differential SAR interferometry / Virginia Brancato in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)PermalinkChange detection based on stacked generalization system with segmentation constraint / Kun Tan in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 11 (November 2018)PermalinkHow to calibrate historical aerial photographs : a change analysis of naturally dynamic boreal forest landscapes / Niko Kulha in Forests, vol 9 n° 10 (October 2018)PermalinkTowards a polyalgorithm for land use change detection / Rishu Saxena in ISPRS Journal of photogrammetry and remote sensing, vol 144 (October 2018)PermalinkAn experimental framework for integrating citizen and community science into land cover, land use, and land change detection processes in a national mapping agency / Ana-Maria Olteanu-Raimond in Land, vol 7 n° 3 (September 2018)PermalinkAn improved temporal mixture analysis unmixing method for estimating impervious surface area based on MODIS and DMSP-OLS data / Li Zhuo in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)PermalinkContextual classification using photometry and elevation data for damage detection after an earthquake event / Ewelina Rupnik in European journal of remote sensing, vol 51 n° 1 (2018)PermalinkSensitivity analysis of pansharpening in hyperspectral change detection / Seyd Teymoor Seydi in Applied geomatics, vol 10 n° 1 (March 2018)PermalinkDétection de changement par imagerie radar sur les zones naturelles et agricoles en milieu tropical / Jérôme Lebreton (2018)Permalink