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Evaluating the capability of the Sentinel 2 data for soil organic carbon prediction in croplands / Fabio Castaldi in ISPRS Journal of photogrammetry and remote sensing, vol 147 (January 2019)
[article]
Titre : Evaluating the capability of the Sentinel 2 data for soil organic carbon prediction in croplands Type de document : Article/Communication Auteurs : Fabio Castaldi, Auteur ; Andreas Hueni, Auteur ; Sabine Chabrillat, Auteur ; Kathrin Ward, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 267 - 282 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Allemagne
[Termes IGN] analyse comparative
[Termes IGN] analyse multivariée
[Termes IGN] Belgique
[Termes IGN] bilan du carbone
[Termes IGN] capacité de stockage
[Termes IGN] image APEX
[Termes IGN] image hyperspectrale
[Termes IGN] image multibande
[Termes IGN] image Sentinel-MSI
[Termes IGN] Luxembourg
[Termes IGN] puits de carbone
[Termes IGN] rapport signal sur bruit
[Termes IGN] sol
[Termes IGN] surface cultivéeRésumé : (auteur) The short revisit time of the Sentinel-2 (S2) constellation entails a large availability of remote sensing data, but S2 data have been rarely used to predict soil organic carbon (SOC) content. Thus, this study aims at comparing the capability of multispectral S2 and airborne hyperspectral remote sensing data for SOC prediction, and at the same time, we investigated the importance of spectral and spatial resolution through the signal-to-noise ratio (SNR), the variable importance in the prediction (VIP) models and the spatial variability of the SOC maps at field and regional scales. We tested the capability of the S2 data to predict SOC in croplands with quite different soil types and parent materials in Germany, Luxembourg and Belgium, using multivariate statistics and local ground calibration with soil samples. We split the calibration dataset into sub-regions according to soil maps and built a multivariate regression model within each sub-region. The prediction accuracy obtained by S2 data is generally slightly lower than that retrieved by airborne hyperspectral data. The ratio of performance to deviation (RPD) is higher than 2 in Luxembourg (2.6) and German (2.2) site, while it is 1.1 in the Belgian area. After the spectral resampling of the airborne data according to S2 band, the prediction accuracy did not change for four out of five of the sub-regions. The variable importance values obtained by S2 data showed the same trend as the airborne VIP values, while the importance of SWIR bands decreased using airborne data resampled according the S2 bands. These differences of VIP values can be explained by the loss of spectral resolution as compared to APEX data and the strong difference in terms of SNR between the SWIR region and other spectral regions. The investigation on the spatial variability of the SOC maps derived by S2 data has shown that the spatial resolution of S2 is adequate to describe SOC variability both within field and at regional scale. Numéro de notice : A2019-037 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.11.026 Date de publication en ligne : 06/12/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.11.026 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91974
in ISPRS Journal of photogrammetry and remote sensing > vol 147 (January 2019) . - pp 267 - 282[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2019011 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019013 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2019012 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt 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
Titre : Fast Image and LiDAR alignment based on 3D rendering in sensor topology Type de document : Article/Communication Auteurs : Pierre Biasutti , Auteur ; Jean-François Aujol, Auteur ; Mathieu Brédif , Auteur ; Aurélie Bugeau, Auteur Editeur : Saint-Mandé : Institut national de l'information géographique et forestière - IGN (2012-) Année de publication : 2019 Projets : 1-Pas de projet / Importance : 9 p. Format : 21 x 30 cm Note générale : Bibliographie
This project has also received funding from the European Union’s Horizon 2020 research and innovation programme underthe Marie Skłodowska-Curie grant agreement No 777826.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image optique
[Termes IGN] semis de pointsRésumé : (Auteur) Mobile Mapping Systems are now commonly used in large urban acquisition campaigns. They are often equiped with LiDAR sensors and optical cameras, providing very large multimodal datasets. The fusion of both modalities serves different purposes such as point cloud colorization, geometry enhancement or object detection. However, this fusion task cannot be done directly as both modalities are only coarsely registered. This paper presents a fully automatic approach for LiDAR projection and optical image registration refinement based on LiDAR point cloud 3D renderings. First, a coarse 3D mesh is generated from the LiDAR point cloud using the sensor topology. Then, the mesh is rendered in the image domain. After that, a variational approach is used to align the rendering with the optical image. This method achieves high quality results while performing in very low computational time. Results on real data demonstrate the efficiency of the model for aligning LiDAR projections and optical images. Numéro de notice : P2019-002 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : Préprint DOI : sans En ligne : https://hal.science/hal-02100715v1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93283 Documents numériques
en open access
Fast Image and LiDAR alignment based on... - pdf preprintAdobe Acrobat PDF Geographic Information Systems in Geospatial Intelligence, ch. 5. Spectral optimization of airborne multispectral camera for land cover classification: automatic feature selection and spectral band clustering / Arnaud Le Bris (2019)
Titre de série : Geographic Information Systems in Geospatial Intelligence, ch. 5 Titre : Spectral optimization of airborne multispectral camera for land cover classification: automatic feature selection and spectral band clustering Type de document : Chapitre/Contribution Auteurs : Arnaud Le Bris , Auteur ; Nesrine Chehata , Auteur ; Xavier Briottet , Auteur ; Nicolas Paparoditis , Auteur Editeur : London [UK] : IntechOpen Année de publication : 2019 Projets : 1-Pas de projet / Importance : 4 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] bande spectrale
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification multibande
[Termes IGN] image hyperspectrale
[Termes IGN] optimisation (mathématiques)Résumé : (auteur) Hyperspectral imagery consists of hundreds of contiguous spectral bands. However, most of them are redundant. Thus a subset of well-chosen bands is generally sufficient for a specific problem, enabling to design adapted superspectral sensors dedicated to specific land cover classification. Related both to feature selection and extraction, spectral optimization identifies the most relevant band subset for specific applications, involving a band subset relevance score as well as a method to optimize it. This study first focuses on the choice of such relevance score. Several criteria are compared through both quantitative and qualitative analyses. To have a fair comparison, all tested criteria are compared to classic hyperspectral data sets using the same optimization heuristics: an incremental one to assess the impact of the number of selected bands and a stochastic one to obtain several possible good band subsets and to derive band importance measures out of intermediate good band subsets. Last, a specific approach is proposed to cope with the optimization of bandwidth. It consists in building a hierarchy of groups of adjacent bands, according to a score to decide which adjacent bands must be merged, before band selection is performed at the different levels of this hierarchy. Numéro de notice : H2019-008 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Chapître / contribution nature-HAL : ChOuvrScient DOI : 10.5772/intechopen.88507 Date de publication en ligne : 20/12/2019 En ligne : http://dx.doi.org/10.5772/intechopen.88507 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95734
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 Individual tree detection and crown delineation with 3D information from multi-view satellite Images / Changlin Xiao in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 1 (January 2019)PermalinkIntegration of lidar data and GIS data for point cloud semantic enrichment at the point level / Harith Aljumaily in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 1 (January 2019)PermalinkJoint analysis of SAR and optical satellite images time series for grassland event detection / Anatol Garioud (2019)PermalinkPermalinkPermalinkMacroalgues intertidales : Apport de la télédétection hyperspectrale pour le suivi sectoriel dans le cadre de la DCE/DCSMM / Arnaud Le Bris (2019)PermalinkMonitoring crops water needs at high spatio-temporal resolution by synergy of optical / thermal and radar observations / Abdelhakim Amazirh (2019)PermalinkSensitivity of urban material classification to spatial and spectral configurations from visible to short-wave infrared / Arnaud Le Bris (2019)PermalinkSimultaneous characterization of objects temperature and radiative properties through multispectral infrared thermography / Thibaud Toullier (2019)PermalinkSpectral unmixing with perturbed endmembers / Reza Arablouei in IEEE Transactions on geoscience and remote sensing, vol 57 n° 1 (January 2019)Permalink