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Improving 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)
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Titre : Improving the spatial bias correction algorithm in SMOS image reconstruction processor : validation of soil moisture retrievals with in situ data Type de document : Article/Communication Auteurs : Ali Khazaal, Auteur ; Philippe Richaume, Auteur ; François Cabot, Auteur ; Eric Anterrieu, Auteur ; Arnaud Mialon, Auteur ; Yann H. Kerr, Auteur Année de publication : 2019 Article en page(s) : pp 277 - 290 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] correction d'image
[Termes IGN] erreur systématique
[Termes IGN] humidité du sol
[Termes IGN] image SMOS
[Termes IGN] résidu
[Termes IGN] télédétection en hyperfréquence
[Termes IGN] température de luminanceRésumé : (Auteur) SMOS is a space mission led by the European Space Agency and designed to provide global maps of Soil Moisture and Ocean salinity, two important geophysical parameters for understanding the water cycle variations and climate change. The SMOS payload is a 2-D interferometer operating at L-band that consists of 69 elementary antennas located along a Y-shaped structure. Important spatial biases persist in the retrieved brightness temperature (BT) images mainly due to the phenomenon of aliasing inside the field of view of SMOS but also due to the Gibbs oscillations near land/ocean transitions. To minimize these biases, a differential image reconstruction algorithm is used in the operational processor that reduces the contrast of the image to be retrieved. To do that, the contribution of a constant artificial temperature map is removed from the measurements prior to reconstruction and then added back after the reconstruction. In this paper, we show that strong residual biases are still present in the retrieved images. To reduce them, we propose to improve the bias correction algorithm by using a more realistic artificial temperature scene based on separating the land and ocean regions and assigning a constant temperature over land and a Fresnel BT model over the ocean. The artificial scene is also improved by means of representing each pixel by its water fraction percentage to smooth the land/ocean transitions. The improved algorithm is validated over the ocean by comparing the retrieved temperatures to a forward geophysical model but also over land by comparing the retrieved soil moisture to in situ measurements. Numéro de notice : A2019-106 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2853619 Date de publication en ligne : 09/08/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2853619 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92412
in IEEE Transactions on geoscience and remote sensing > vol 57 n° 1 (January 2019) . - pp 277 - 290[article]Investigating the accuracy of a bathymetric refraction correction on Structure from Motion photogrammetric datasets / Aelaïg Cournez (2019)
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Titre : Investigating the accuracy of a bathymetric refraction correction on Structure from Motion photogrammetric datasets : River Feshie, Scotland Type de document : Mémoire Auteurs : Aelaïg Cournez, Auteur Editeur : Champs-sur-Marne : Ecole nationale des sciences géographiques ENSG Année de publication : 2019 Importance : 79 p. Format : 21 x 30 cm Note générale : Bibliographie
Rapport de projet pluridisciplinaire, cycle ING2Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] acquisition de données
[Termes IGN] correction automatique
[Termes IGN] correction des altitudes
[Termes IGN] données bathymétriques
[Termes IGN] drone
[Termes IGN] Ecosse
[Termes IGN] géomorphologie locale
[Termes IGN] réfraction de l'eau
[Termes IGN] rivière
[Termes IGN] semis de pointsIndex. décimale : PROJET Mémoires : Rapports de projet - stage des ingénieurs de 2e année Résumé : (Auteur) L’étude géomorphologique des rivières est essentielle dans la préservation des milieux naturels et de la biodiversité fluviale. Dans ce contexte, de nombreuses technologies sont développées afin de surveiller ces espaces aux cours des années et d’étudier leurs dynamiques hydrauliques et sédimentaires. L’essor des innovations en photogrammétrie permettent aujourd’hui de modéliser aisément un environnement à l’échelle d’une rivière sous forme d’un nuage de points 3D géo-référencés à partir d’acquisitions par drone. Or les données bathymétriques issues de ces acquisitions restent entachées d’une forte erreur en élévation due au phénomène de réfraction optique ayant lieu à l’interface entre l’air et l’eau. Ces dernières années, plusieurs algorithmes permettant de corriger cette erreur virent le jour tel que celui proposé par J.T. Dietrich. Or, à ce jour, cet algorithme ne fut testé que sur des portions de rivières limitées (200 mètres). Le but de ce projet de stage fut donc d’évaluer les performances de cet algorithme en termes de correction de l’élévation sur une portion d’environ deux kilomètres de rivière à chenaux en tresse et d’évaluer notamment les erreurs dues à la végétation et aux bassins profonds. Note de contenu : Introduction
1. Methods: Fieldwork
1.1 Study area
1.2 2019 surveys
1.3 Resulting datasets
1.4 Historic survey data
2. Methods: Processing
2.1 Topographic modelling
2.2 Water surface modelling
2.3 Pre-process steps before Dietrich algorithm execution
2.4 Description of Dietrich algorithm
3. Results
3.1 Elevation correction
3.2 Elevation errors and depth
3.3 Elevation errors associated with vegetation and complex bank heights
3.4 Elevation errors and geomorphic units
ConclusionNuméro de notice : 26122 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Mémoire de projet pluridisciplinaire Organisme de stage : Geographical and Earth Sciences School (University of Glasgow) Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93863 Documents numériques
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Titre : Machine learning for image segmentation Titre original : Apprentissage artificiel pour la segmentation d'image Type de document : Thèse/HDR Auteurs : Kaiwen Chang, Auteur ; Jesus Angulo lopez, Directeur de thèse ; Jesus Angulo lopez, Directeur de thèse ; Bruno Figliuzzi, Directeur de thèse Editeur : Paris : Université Paris Sciences et Lettres Année de publication : 2019 Importance : 155 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse de Doctorat de l'Université PSL, Spécialité : Morphologie MathématiqueLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage automatique
[Termes IGN] base de données d'images
[Termes IGN] graphe
[Termes IGN] morphologie mathématique
[Termes IGN] optique géométrique
[Termes IGN] rayonnement lumineux
[Termes IGN] segmentation d'image
[Termes IGN] segmentation par graphes d'adjacence de régions
[Termes IGN] superpixelIndex. décimale : THESE Thèses et HDR Résumé : (auteur) In this PhD thesis, our aim is to establish a general methodology for performing the segmentation of a dataset constituted of similar images with only a few annotated images as training examples. This methodology is directly intended to be applied to images gathered in Earth observation or materials science applications, for which there is not enough annotated examples to train state-of-the-art deep learning based segmentation algorithms. The proposed methodology starts from a superpixel partition of the image and gradually merges the initial regions until anactual segmentation is obtained. The two main contributions described in this PhD thesis are the development of a new superpixel algorithm which makes use of the Eikonal equation, and the development of a superpixel merging algorithm steaming from the adaption of the Eikonal equation to the setting of graphs. The superpixels merging approach makes use of a region adjacency graph computed from the superpixel partition. The edges are weighted by a dissimilarity measure learned by a machine learning algorithm from low-level cues computed on the superpixels. In terms of application, our approach to image segmentation is finally evaluated on the SWIMSEG dataset, a dataset which contains sky cloud images. On this dataset, using only a limited amount of images for training our algorithm, we were able to obtain segmentation results similar to the ones obtained with state-of-the-art algorithms. Note de contenu : 1- Introduction
2- Fast marching based superpixels
3- Hierarchical segmentation based on wavelet decomposition
4- Learning similarities between regions
5- Region merging
6- Application
Conclusion and perspectivesNuméro de notice : 25837 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Morphologie Mathématique : Paris Sciences et Lettres : 2019 Organisme de stage : Centre de Morphologie Mathématique (Mines ParisTech) nature-HAL : Thèse DOI : sans En ligne : https://hal.archives-ouvertes.fr/tel-02510662 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95191 Microwave indices from active and passive sensors for remote sensing applications / Emanuele Santi (2019)
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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)
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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 Real-time capturing of seismic waveforms using high-rate BDS, GPS and GLONASS observations: the 2017 Mw 6.5 Jiuzhaigou earthquake in China / Xingxing Li in GPS solutions, vol 23 n° 1 (January 2019)
PermalinkPermalinkPermalinkPermalinkPermalinkSensitivity of urban material classification to spatial and spectral configurations from visible to short-wave infrared / Arnaud Le Bris (2019)
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PermalinkPermalinkToward 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)
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