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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)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 147 (January 2019) . - pp 267 - 282 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 cultivée Résumé : (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 [article]

Exemplaires(3)

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

Assessing the performance of two unsupervised dimensionality reduction techniques on hyperspectral APEX data for high resolution urban land-cover mapping / Luca Demarchi in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 166 - 179 Titre : Assessing the performance of two unsupervised dimensionality reduction techniques on hyperspectral APEX data for high resolution urban land-cover mapping Type de document : Article/Communication Auteurs : Luca Demarchi, Auteur ; Frank Canters, Auteur ; Claude Cariou, Auteur ; Giorgio Licciardi, Auteur ; Jonathan Cheung-Wai Chan, Auteur Année de publication : 2014 Article en page(s) : pp 166 - 179 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] Airborne Prism Experiment [Termes IGN] carte d'occupation du sol [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] classification par réseau neuronal [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] image APEX [Termes IGN] image hyperspectrale [Termes IGN] Perceptron multicouche Résumé : (Auteur) Despite the high richness of information content provided by airborne hyperspectral data, detailed urban land-cover mapping is still a challenging task. An important topic in hyperspectral remote sensing is the issue of high dimensionality, which is commonly addressed by dimensionality reduction techniques. While many studies focus on methodological developments in data reduction, less attention is paid to the assessment of the proposed methods in detailed urban hyperspectral land-cover mapping, using state-of-the-art image classification approaches. In this study we evaluate the potential of two unsupervised data reduction techniques, the Autoassociative Neural Network (AANN) and the BandClust method – the first a transformation based approach, the second a feature-selection based approach – for mapping of urban land cover at a high level of thematic detail, using an APEX 288-band hyperspectral dataset. Both methods were tested in combination with four state-of-the-art machine learning classifiers: Random Forest (RF), AdaBoost (ADB), the multiple layer perceptron (MLP), and support vector machines (SVM). When used in combination with a strong learner (MLP, SVM) BandClust produces classification accuracies similar to or higher than obtained with the full dataset, demonstrating the method’s capability of preserving critical spectral information, required for the classifier to successfully distinguish between the 22 urban land-cover classes defined in this study. In the AANN data reduction process, on the other hand, important spectral information seems to be compromised or lost, resulting in lower accuracies for three of the four classifiers tested. Detailed analysis of accuracies at class level confirms the superiority of the SVM/Bandclust combination for accurate urban land-cover mapping using a reduced hyperspectral dataset. This study also demonstrates the potential of the new APEX sensor data for detailed mapping of land cover in spatially and spectrally complex urban areas. Numéro de notice : A2014-018 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.10.012 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.10.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32923 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2014011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Airborne prism experiment calibration information system / Andreas Hueni in IEEE Transactions on geoscience and remote sensing, vol 51 n° 11 (November 2013)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 51 n° 11 (November 2013) . - pp 5169 - 5180 Titre : Airborne prism experiment calibration information system Type de document : Article/Communication Auteurs : Andreas Hueni, Auteur ; Karim Lenhard, Auteur ; Andreas Baumgartner, Auteur ; Michael E. Schaepman, Auteur Année de publication : 2013 Article en page(s) : pp 5169 - 5180 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] Airborne Prism Experiment [Termes IGN] base de données relationnelles [Termes IGN] capteur en peigne [Termes IGN] étalonnage de capteur (imagerie) [Termes IGN] image APEX [Termes IGN] Java (langage de programmation) [Termes IGN] Matlab [Termes IGN] spectromètre imageur [Termes IGN] spectroscopie [Termes IGN] traçabilité Résumé : (Auteur) The calibration of remote sensing instruments is a crucial step in the generation of products tied to international reference standards. Calibrating imaging spectrometers is particularly demanding due to the high number of spatiospectral pixels and, consequently, the large amount of data acquired during calibration sequences. Storage of these data and associated metadata in an organized manner, as well as the provision of efficient tools for the data analysis and fast and repeatable calibration coefficient generation with provenance information, is key to the provision of traceable measurements. The airborne prism experiment (APEX) calibration information system is a multilayered information technology solution comprising a database based on the entity-attribute-value (EAV) paradigm and software written in Java and Matlab, providing data access, visualization and processing, and handling the data volumes over the expected lifetime of the system. Although developed in the context of APEX, the system is rather generic and may be adapted to other pushbroom-based imagers with little effort. Numéro de notice : A2013-615 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2246575 En ligne : https://doi.org/10.1109/TGRS.2013.2246575 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32751 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-2013111	RAB	Revue	Centre de documentation	En réserve L003	Disponible