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télédétection
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Télédétection aérospatiale Télédétection par satellite Télédétection satellitaire Télédétection spatiale Appareils enregistreurs >> Agriculture de précision Capteurs (technologie) Photogrammétrie aérienne Photographie aérienne >>Terme(s) spécifique(s) : Télédétection en sciences de la Terre Cartographie radar Traitement d'images -- Techniques numériques Images de télédétection Radar à antenne synthétique Radar en sciences de la Terre Reconnaissance aérienne Satellites artificiels en télédétection Satellites de télédétection des ressources terrestres SPOT (satellites de télédétection) Surveillance électronique Télédétection hyperfréquence Télémesure spatiale Thermographie Equiv. LCSH : Remote sensing Domaine(s) : 500; 600 |
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Exploitation of hyperspectral data for assessing vegetation health under exposure to petroleum hydrocarbons / Guillaume Lassalle (2019)
Titre : Exploitation of hyperspectral data for assessing vegetation health under exposure to petroleum hydrocarbons Type de document : Thèse/HDR Auteurs : Guillaume Lassalle, Auteur ; Arnaud Elger, Directeur de thèse ; Sophie Fabre, Directeur de thèse Editeur : Toulouse : Université Fédérale Toulouse Midi-Pyrénées Année de publication : 2019 Autre Editeur : Toulouse : Institut Supérieur de l’Aéronautique et de l’Espace Importance : 277 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse en vue de l'obtention du Doctorat de l'Université de Toulouse délivré par l'Institut Supérieur de l’Aéronautique et de l’Espace, spécialité : Surfaces et interfaces continentales, Hydrologie Agrosystèmes, écosystèmes et environnementLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] canopée
[Termes IGN] contamination
[Termes IGN] feuille (végétation)
[Termes IGN] hydrocarbure
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] indice de végétation
[Termes IGN] modèle de transfert radiatif
[Termes IGN] pollution des sols
[Termes IGN] prospection pétrolière
[Termes IGN] réflectance spectrale
[Termes IGN] régression multiple
[Termes IGN] signature spectrale
[Termes IGN] surveillance de la végétationIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Oil exploration and contamination monitoring remain limited in regions covered by vegetation. Natural seepages and oil leakages due to facility failures are often masked by the foliage, making ineffective the current technologies used for detecting crude oil and petroleum products. However, the exposure of vegetation to oil affects its health and, consequently, its optical properties in the [400:2500] nm domain. This suggest being able to detect seepages and leakages indirectly, by analyzing vegetation health through its spectral reflectance. Based on this assumption, this thesis evaluates the potential of airborne hyperspectral imagery with high spatial resolution for detecting and quantifying oil contamination in vegetated regions. To achieve this, a three-step multiscale approach was adopted. The first step aimed at developing a method for detecting and characterizing the contamination under controlled conditions, by exploiting the optical properties of Rubus fruticosus L. The proposed method combines 14 vegetation indices in classification and allows detecting various oil contaminants accurately, from leaf to canopy scale. Its use under natural conditions was validated on a contaminated mud pit colonized by the same species. During the second step, a method for quantifying total petroleum hydrocarbons, based on inverting the PROSPECT model, was developed. The method exploits the pigment content of leaves, estimated from their spectral signature, for predicting the level of hydrocarbon contamination in soils accurately. The last step of the approach demonstrated the robustness of the two methods using airborne imagery. They proved performing for detecting and quantifying mud pit contamination. Another method of quantification, based on multiple regression, was proposed. At the end of this thesis, the three methods proposed were validated for use both on the field, at leaf and canopy scales, and on airborne hyperspectral images with high spatial resolution. Their performances depend however on the species, the season and the level of soil contamination. A similar approach was conducted under tropical conditions, allowing the development of a method for quantifying the contamination adapted to this context. In a perspective of operational use, an important effort is still required for extending the scope of the methods to other contexts and for anticipating their use on satellite- and drone-embedded hyperspectral sensors. Finally, the contribution of active remote sensing (radar and LiDAR) should be considered in further research, in order to overcome some of the limits specific to passive optical remote sensing. Note de contenu : General introduction
1- State-of-the-art of passive hyperspectral remote sensing for oil exploration and contamination monitoring in vegetated regions
2- Development of methods for detecting and quantifying oil contamination based on vegetation optical properties, under controlled conditions
3- Application and evaluation of the methods under natural conditions, from field scale to airborne hyperspectral imagery
General conclusionNuméro de notice : 25946 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Spécialité : Surfaces et interfaces continentales, Hydrologie Agrosystèmes, écosystèmes et environnement : Toulouse : 2019 nature-HAL : Thèse DOI : sans En ligne : http://www.theses.fr/2019ESAE0030 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96343 Exploitation de séries temporelles d'images multi-sources pour la cartographie des surfaces en eau / Filsa Bioresita (2019)
Titre : Exploitation de séries temporelles d'images multi-sources pour la cartographie des surfaces en eau Type de document : Thèse/HDR Auteurs : Filsa Bioresita, Auteur ; Anne Puissant, Directeur de thèse Editeur : Strasbourg : Université de Strasbourg Année de publication : 2019 Importance : 214 p. Format : 21 x 30 cm Note générale : Bibliographie
PhD Thesis University of Strasbourg for obtaining the degree of Doctor of the University of Strasbourg, Speciality: Geography, GeomaticsLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] biodiversité
[Termes IGN] eau de surface
[Termes IGN] estimation bayesienne
[Termes IGN] fusion d'images
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] inondation
[Termes IGN] nutriment végétal
[Termes IGN] polarimétrie
[Termes IGN] série temporelle
[Termes IGN] service écosystémique
[Termes IGN] surveillance hydrologique
[Termes IGN] télédétection spatiale
[Termes IGN] traitement automatique de donnéesIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Les eaux de surface sont des ressources importantes pour la biosphère et l'anthroposphère. Elles favorisent la préservation des habitats, le développement de la biodiversité et le maintien des services écosystémiques en contrôlant le cycle des nutriments et le carbone à l’échelle mondiale. Elles sont essentielles à la vie quotidienne de l’homme, notamment pour l'irrigation, la consommation d’eau potable, la production hydro-électrique, etc. Par ailleurs, lors des inondations, elles peuvent présenter des dangers pour l'homme, les habitations et les infrastructures. La surveillance des changements dynamiques des eaux de surface a donc un rôle primordial pour guider les choix des gestionnaires dans le processus d’aide à la décision. L’imagerie satellitaire constitue une source de données adaptée permettant de fournir des informations sur les eaux de surface. De nos jours, la télédétection satellitaire a connu une révolution avec le lancement des satellites Sentinel-1 (Radar) et Sentinel-2 (Optique) qui disposent d’une haute fréquence de revisite et d’une résolution spatiale moyenne à élevée. Ces données peuvent fournir des séries temporelles essentielles pour apporter davantage d'informations afin d'améliorer la capacité d'observation des eaux de surface. L’exploitation de telles données massives et multi-sources pose des défis en termes d’extraction de connaissances et de processus de traitement d’images car les chaines de traitement doivent être le plus automatiques possibles. Dans ce contexte, l'objectif de ce travail de thèse est de proposer de nouvelles approches permettant de cartographier l’extension spatiales des eaux de surface et des inondations, en explorant l'utilisation unique et combinée des données Sentinel-1 et Sentinel-2. Note de contenu : 1- Introduction, research questions and objectives
2- The state of the art
3- Study area, data sets and pre-processing of Sentinel 1 & 2
4- Detection of surface water area using mono-date Sentinel 1 amplitude data
5- Detection of surface water area using time series of Sentinel 1 amplitude data and Sentinel 2 data
6- Another methods and validation on different thematic context
7- General conclusions and perspectivesNuméro de notice : 25726 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : PhD Thesis : Geography, Geomatics : Strasbourg : 2019 nature-HAL : Thèse DOI : sans En ligne : https://hal.science/hal-03618382/document Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94887
Titre : Feedbacks on VGI in-situ campaign for updating LULC data Type de document : Article/Communication Auteurs : Laurence Jolivet , Auteur ; Ana-Maria Olteanu-Raimond , Auteur ; Marie-Dominique Van Damme , Auteur ; Marie Gombert, Auteur ; Simon Fauret, Auteur ; Thierry Saffroy , Auteur Editeur : International Cartographic Association ICA - Association cartographique internationale ACI Année de publication : 2019 Projets : Landsense / Raimond, Ana-Maria Conférence : ICC 2019, 29th International Cartographic Conference ICA, Mapping everything for everyone 15/07/2019 20/07/2019 Tokyo Japon Open Access Abstracts of the ICA Importance : 2 p. Format : 21 x 30 cm Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] 1:5.000
[Termes IGN] application web
[Termes IGN] données localisées des bénévoles
[Termes IGN] Institut national de l'information géographique et forestière (France)
[Termes IGN] mise à jour de base de données
[Termes IGN] Occitanie (région 2016)
[Termes IGN] occupation du sol
[Termes IGN] production participative
[Termes IGN] utilisation du solRésumé : (auteur) The goal of this paper is to present the defined strategy for running an in-situ campaign about LULC authoritative data monitoring and to give an overview about the data collected during the campaign. The targeted database is OCS-GE containing LULC data which is produced by IGN France for a 1: 5.000 scale use. A mobile application named PAYSAGES was implemented for collecting in-situ information. Contributions have been recorded about edition of uses for buildings, quarries, construction areas, agricultural fields and about validation of automatically detected changes. Numéro de notice : C2019-045 Affiliation des auteurs : LASTIG COGIT (2012-2019) Autre URL associée : vers HAL Thématique : GEOMATIQUE Nature : Poster nature-HAL : Poster-avec-CL DOI : 10.5194/ica-abs-1-152-2019 Date de publication en ligne : 15/07/2019 En ligne : https://www.abstr-int-cartogr-assoc.net/1/152/2019/ Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95339
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 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)
[article]
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
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