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Titre de série : Learning to understand remote sensing images, 2 Titre : Volume 2 Type de document : Monographie Auteurs : Qi Wang, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2019 Importance : 376 p. ISBN/ISSN/EAN : 978-3-03897-699-8 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] analyse texturale
[Termes IGN] apprentissage profond
[Termes IGN] apprentissage semi-dirigé
[Termes IGN] fusion d'images
[Termes IGN] image hyperspectrale
[Termes IGN] image Landsat
[Termes IGN] image radar moirée
[Termes IGN] réseau neuronal convolutifRésumé : (Editeur) With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field. Numéro de notice : 26301B Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Monographie DOI : 10.3390/books978-3-03897-699-8 Date de publication en ligne : 09/12/2019 En ligne : https://doi.org/10.3390/books978-3-03897-699-8 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95034 Microwave indices from active and passive sensors for remote sensing applications / Emanuele Santi (2019)
Titre : Microwave indices from active and passive sensors for remote sensing applications Type de document : Monographie Auteurs : Emanuele Santi, Éditeur scientifique ; Simonetta Paloscia, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2019 Importance : 224 p. Format : 18 x 26 cm ISBN/ISSN/EAN : 978-3-03897-820-6 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bande C
[Termes IGN] bande Ku
[Termes IGN] bande X
[Termes IGN] diffusométrie
[Termes IGN] filtrage spatiotemporel
[Termes IGN] glace de mer
[Termes IGN] humidité du sol
[Termes IGN] image radar moirée
[Termes IGN] phénologie
[Termes IGN] prairie
[Termes IGN] série temporelleRésumé : (éditeur) Past research has comprehensively assessed the capabilities of satellite sensors operating at microwave frequencies, both active (SAR, scatterometers) and passive (radiometers), for the remote sensing of Earth’s surface. Besides brightness temperature and backscattering coefficient, microwave indices, defined as a combination of data collected at different frequencies and polarizations, revealed a good sensitivity to hydrological cycle parameters such as surface soil moisture, vegetation water content, and snow depth and its water equivalent. The differences between microwave backscattering and emission at more frequencies and polarizations have been well established in relation to these parameters, enabling operational retrieval algorithms based on microwave indices to be developed. This Special Issue aims at providing an overview of microwave signal capabilities in estimating the main land parameters of the hydrological cycle, e.g., soil moisture, vegetation water content, and snow water equivalent, on both local and global scales, with a particular focus on the applications of microwave indices. Note de contenu : Editorial
1- Ku-, X- and C-Band microwave backscatter indices from saline snow covers on Arctic first-year sea ice
2- Retrieval of effective correlation length and snow water equivalent from radar and passive microwave measurements
3- Soil moisture from fusion of scatterometer and SAR: closing the scale gap with temporal filtering
4- Using SAR-derived vegetation descriptors in a water cloud model to improve soil
moisture retrieval
5- Sensitivity of Sentinel-1 backscatter to vegetation dynamics: An Austrian case study
6- AMSR2 soil moisture downscaling using temperature and vegetation data
7- Analysis of the Radar Vegetation Index and potential improvements
8- Radiometric microwave indices for remote sensing of land surfaces
9- Soil moisture in the Biebrza wetlands retrieved from Sentinel-1 imagery
10- Exploiting time series of Sentinel-1 and Sentinel-2 imagery to detect meadow phenology in mountain regionsNuméro de notice : 25941 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Monographie DOI : 10.3390/books978-3-03897-821-3 En ligne : https://doi.org/10.3390/books978-3-03897-821-3 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96313 Monitoring crops water needs at high spatio-temporal resolution by synergy of optical / thermal and radar observations / Abdelhakim Amazirh (2019)
Titre : Monitoring crops water needs at high spatio-temporal resolution by synergy of optical / thermal and radar observations Type de document : Thèse/HDR Auteurs : Abdelhakim Amazirh, Auteur ; Abdelghani Chehbouni, Directeur de thèse ; Salah Er-Raki, Auteur Editeur : Toulouse : Université de Toulouse 3 Paul Sabatier Année de publication : 2019 Importance : 240 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse en vue de l’obtention du Doctorat de l'Université de Toulouse, Spécialité : Surfaces et Interfaces Continentales, HydrologieLangues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] évapotranspiration
[Termes IGN] gestion de l'eau
[Termes IGN] humidité du sol
[Termes IGN] image Landsat
[Termes IGN] image Landsat-8
[Termes IGN] image multibande
[Termes IGN] image optique
[Termes IGN] image radar
[Termes IGN] image Sentinel-SAR
[Termes IGN] image Terra-MODIS
[Termes IGN] image thermique
[Termes IGN] indice de végétation
[Termes IGN] Marrakech
[Termes IGN] modèle de transfert radiatif
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] parcelle agricole
[Termes IGN] ressources en eau
[Termes IGN] stress hydrique
[Termes IGN] température de surface
[Termes IGN] zone semi-arideIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Optimizing water management in agriculture is essential over semi-arid areas in order to preserve water resources which are already low and erratic due to human actions and climate change. This thesis aims to use the synergy of multispectral remote sensing observations (radar, optical and thermal data) for high spatio-temporal resolution monitoring of crops water needs. In this context, different approaches using various sensors (Landsat-7/8, Sentinel-1 and MODIS) have been developed to provide information on the crop Soil Moisture (SM) and water stress at a spatio-temporal scale relevant to irrigation management. This work fits well the REC "Root zone soil moisture Estimates at the daily and agricultural parcel scales for Crop irrigation management and water use impact: a multi-sensor remote sensing approach" (http://rec.isardsat.com/) project objectives, which aim to estimate the Root Zone Soil Moisture (RZSM) for optimizing the management of irrigation water. Innovative and promising approaches are set up to estimate evapotranspiration (ET), RZSM, land surface temperature (LST) and vegetation water stress through SM indices derived from multispectral observations with high spatio-temporal resolution. The proposed methodologies rely on image-based methods, radiative transfer modelling and water and energy balance modelling and are applied in a semi-arid climate region (central Morocco). In the frame of my PhD thesis, three axes have been investigated. In the first axis, a Landsat LST-derived RZSM index is used to estimate the ET over wheat parcels and bare soil. The ET modelling estimation is explored using a modified Penman-Monteith equation obtained by introducing a simple empirical relationship between surface resistance (rc) and a RZSM index. The later is estimated from Landsat-derived land surface temperature (LST) combined with the LST endmembers (in wet and dry conditions) simulated by a surface energy balance model driven by meteorological forcing and Landsat-derived fractional vegetation cover. The investigated method is calibrated and validated over two wheat parcels located in the same area near Marrakech City in Morocco. In the next axis, a method to retrieve near surface (0-5 cm) SM at high spatial and temporal resolution is developed from a synergy between radar (Sentinel-1) and thermal (Landsat) data and by using a soil energy balance model. The developed approach is validated over bare soil agricultural fields and gives an accurate estimates of near surface SM with a root mean square difference compared to in situ SM equal to 0.03 m3 m-3. In the final axis a new method is developed to disaggregate the 1 km resolution MODIS LST at 100 m resolution by integrating the near surface SM derived from Sentinel-1 radar data and the optical-vegetation index derived from Landsat observations. The new algorithm including the S-1 backscatter as input to the disaggregation, produces more stable and robust results during the selected year. Where, 3.35 °C and 0.75 were the lowest RMSE and the highest correlation coefficient assessed using the new algorithm. Note de contenu : General Introduction
1- Bibliographic synthesis
2- Data & study sites description
3- Models & methods
4- Results & discussions
Conclusions and perspectivesNuméro de notice : 25694 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Surfaces et Interfaces Continentales, Hydrologie : Toulouse 3 : 2019 Organisme de stage : Centre d'Etudes Spatiales de la Biosphère CESBIO nature-HAL : Thèse DOI : sans En ligne : http://thesesups.ups-tlse.fr/4412/ Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94759 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
Titre : Remote sensing of environmental changes in cold regions Type de document : Monographie Auteurs : Jinyang Du, Éditeur scientifique ; Jennifer D. Watts, Éditeur scientifique ; Hui Lu, Éditeur scientifique ; Lingmei Jiang, Éditeur scientifique ; Paolo Tarolli, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2019 Importance : 210 p. ISBN/ISSN/EAN : 978-3-03921-571-3 Note générale : Bibliographie
This book is a printed edition of the Special Issue Remote sensing of environmental changes in cold regions that was published in Remote SensingLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Alaska (Etats-Unis)
[Termes IGN] Arctique
[Termes IGN] changement climatique
[Termes IGN] climat froid
[Termes IGN] cryosphère
[Termes IGN] eau de surface
[Termes IGN] extraction de la végétation
[Termes IGN] image Aqua-MODIS
[Termes IGN] image radar moirée
[Termes IGN] image Radarsat
[Termes IGN] image Terra-MODIS
[Termes IGN] impact sur l'environnement
[Termes IGN] incendie
[Termes IGN] nadir
[Termes IGN] neigeRésumé : (Editeur) This Special Issue gathers papers reporting recent advances in the remote sensing of cold regions. It includes contributions presenting improvements in modeling microwave emissions from snow, assessment of satellite-based sea ice concentration products, satellite monitoring of ice jam and glacier lake outburst floods, satellite mapping of snow depth and soil freeze/thaw states, near-nadir interferometric imaging of surface water bodies, and remote sensing-based assessment of high arctic lake environment and vegetation recovery from wildfire disturbances in Alaska. A comprehensive review is presented to summarize the achievements, challenges, and opportunities of cold land remote sensing. Note de contenu : - Modelling the L-Band Snow-Covered Surface Emission in a Winter Canadian Prairie Environment / Alexandre Roy, Marion Leduc-Leballeur, Ghislain Picard, Alain Royer, Peter Toose, Chris Derksen, Juha Lemmetyinen, Aaron Berg, Tracy Rowlandson and Mike Schwank
- Comparison of Passive Microwave Data with Shipborne Photographic Observation sof Summer Sea Ice Concentration along an Arctic Cruise Path / Qingkai Wang, Peng Lu, Yongheng Zu, Zhijun Li, Matti Leppa¨ranta and Guiyong Zhang
- Radar Scatter Decomposition to Differentiate between Running Ice Accumulations and Intact Ice Covers along Rivers / Karl–Erich Lindenschmidt and Zhaoqin Li
- Development of a Snow Depth Estimation Algorithm over China for the FY-3D/MWRI / Jianwei Yang, Lingmei Jiang, Shengli Wu, Gongxue Wang, Jian Wang and Xiaojing Liu
- Development of a Parameterized Model to Estimate Microwave Radiation Response Depth of Frozen Soil / Tao Zhang, Lingmei Jiang, Shaojie Zhao, Linna Chai, Yunqing Li and Yuhao Pan
- Mapping High Mountain Lakes Using Space-Borne Near-Nadir SAR Observations / Shengyang Li, Hong Tan, Zhiwen Liu, Zhuang Zhou, Yunfei Liu, Wanfeng Zhang, Kang Liu and Bangyong Qin
- Development of Supraglacial Ponds in the Everest Region, Nepal, between 1989 and 2018 / Mohan Bahadur Chand and Teiji Watanabe
- Impacts of Climate Change and Intensive Lesser Snow Goose (Chen caerulescens caerulescens) Activity on Surface Water in High Arctic Pond Complexes / T. Kiyo F. Campbell, Trevor C. Lantz and Robert H. Fraser
- Recovery Rates of Wetland Vegetation Greenness in Severely Burned Ecosystems of Alaska Derived from Satellite Image Analysis / Christopher PotterNuméro de notice : 26508 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Recueil / ouvrage collectif DOI : 10.3390/books978-3-03921-571-3 En ligne : https://doi.org/10.3390/books978-3-03921-571-3 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97134 PermalinkPermalinkPermalinkPermalinkToward 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)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)PermalinkVariational learning of mixture wishart model for PolSAR image classification / Qian Wu in IEEE Transactions on geoscience and remote sensing, vol 57 n° 1 (January 2019)PermalinkPolarization orientation angle and polarimetric SAR scattering characteristics of steep terrain / Jong-Sen Lee in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)PermalinkPotential of Sentinel-1 data for monitoring temperate mixed forest phenology / Pierre-Louis Frison in Remote sensing, vol 10 n° 12 (December 2018)PermalinkInvestigation of the success of monitoring slow motion landslides using Persistent Scatterer Interferometry and GNSS methods / K.O. Hastaoglu in Survey review, vol 50 n° 363 (September 2018)PermalinkA new scheme for urban impervious surface classification from SAR images / Hongsheng Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 139 (May 2018)PermalinkA statistical approach to preprocess and enhance C-band SAR images in order to detect automatically marine oil slicks / Zhour Najoui in IEEE Transactions on geoscience and remote sensing, vol 56 n° 5 (May 2018)PermalinkTowards automatic SAR-optical stereogrammetry over urban areas using very high resolution imagery / Chunping Qiu in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)PermalinkEstimated location of the seafloor sources of marine natural oil seeps from sea surface outbreaks : A new "source path procedure" applied to the northern Gulf of Mexico / Zhour Najoui in Marine and Petroleum Geology, Vol 91 (March 2018)PermalinkPermalinkCaractérisation et qualification de Modèles Numériques de Surfaces (MNS) - Analyse de la cohérence avec des masques d’eau / Guillaume Sutter (2018)PermalinkCartographie des déformations de surface sur l’île de Taiwan par interférométrie RADAR Sentinel-1 / Miloud Fekaouni (2018)PermalinkDétection de changement par imagerie radar sur les zones naturelles et agricoles en milieu tropical / Jérôme Lebreton (2018)PermalinkEtude préalable à l'installation d'un coin radar sur le site de co-localisation de Calern / Guillaume Schmidt (2018)Permalink