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Spectral Interference of Heavy Metal Contamination on Spectral Signals of Moisture Content for Heavy Metal Contaminated Soils / Haein Shin in IEEE Transactions on geoscience and remote sensing, vol 58 n° 4 (April 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 4 (April 2020) . - pp 2266 - 2275 Titre : Spectral Interference of Heavy Metal Contamination on Spectral Signals of Moisture Content for Heavy Metal Contaminated Soils Type de document : Article/Communication Auteurs : Haein Shin, Auteur ; Jaehyung Yu, Auteur ; Lei Wang, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 2266 - 2275 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] arsenic [Termes IGN] bande spectrale [Termes IGN] bruit blanc [Termes IGN] contamination [Termes IGN] cuivre [Termes IGN] dégradation du signal [Termes IGN] échantillonnage [Termes IGN] humidité du sol [Termes IGN] interférence [Termes IGN] métal lourd [Termes IGN] modèle de régression [Termes IGN] plomb [Termes IGN] pollution des sols [Termes IGN] signature spectrale Résumé : (auteur) This article examined the spectral interference by heavy metal on the spectral signal of moisture content of heavy metal contaminated soils. Soil samples were collected from an abandoned mine area, and the chemical analysis revealed extremely high contamination amount of copper (Cu), zinc (Zn), arsenic (As), cadmium (Cd), and lead (Pb). The mineralogical analysis showed that the spectral signature of the heavy metal contaminated soils was manifested by secondary minerals. Water content suppressed the spectral reflectance of the soil samples but increased the absorption depths. Although a regression model can predict moisture content using the magnitude of the water absorption feature, the accuracy was much lower when the heavy metal concentration was extremely high. It indicates that geochemical reactions between the heavy metal cation and iron oxide/clay minerals may have affected the spectral responses of the contaminated soils at the water absorption bands. Our model also showed that there was a shift of the absorption features of moisture content if the heavy metal contamination level went up. Unlike normal soils, the absorption features of clay minerals and ferric iron were not able to accurately predict moisture in highly contaminated soils. Given the fact that the spectral bands selected in this article were associated with water absorption, the findings from this article may only be useful to a drone-based low-altitude remote sensing of soil moisture content. Numéro de notice : A2020-193 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2946297 Date de publication en ligne : 31/10/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2946297 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94860 [article]

Sea ice concentration estimation during melt from dual-pol SAR scenes using deep convolutional neural networks: a case study / Lei Wang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 8 (August 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 8 (August 2016) . - pp 4524 - 4533 Titre : Sea ice concentration estimation during melt from dual-pol SAR scenes using deep convolutional neural networks: a case study Type de document : Article/Communication Auteurs : Lei Wang, Auteur ; K. Andrea Scott, Auteur ; Linlin Xu, Auteur ; David A. Clausi, Auteur Année de publication : 2016 Article en page(s) : pp 4524 - 4533 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] classification par réseau neuronal [Termes IGN] eau de fonte [Termes IGN] glace de mer [Termes IGN] iceberg [Termes IGN] image Radarsat [Termes IGN] navigation maritime [Termes IGN] réseau neuronal convolutif Résumé : (Auteur) High-resolution ice concentration maps are of great interest for ship navigation and ice hazard forecasting. In this case study, a convolutional neural network (CNN) has been used to estimate ice concentration using synthetic aperture radar (SAR) scenes captured during the melt season. These dual-pol RADARSAT-2 satellite images are used as input, and the ice concentration is the direct output from the CNN. With no feature extraction or segmentation postprocessing, the absolute mean errors of the generated ice concentration maps are less than 10% on average when compared with manual interpretation of the ice state by ice experts. The CNN is demonstrated to produce ice concentration maps with more detail than produced operationally. Reasonable ice concentration estimations are made in melt regions and in regions of low ice concentration. Numéro de notice : A2016-886 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2543660 En ligne : https://doi.org/10.1109/TGRS.2016.2543660 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83066 [article]

Urban positioning on a smartphone: real-time shadow matching using GNSS and 3D city models / Lei Wang in Inside GNSS, vol 8 n° 6 (November - December 2013) 

Public [article]  inInside GNSS > vol 8 n° 6 (November - December 2013) . - 13 p. ; pp 44 - 56 Titre : Urban positioning on a smartphone: real-time shadow matching using GNSS and 3D city models Type de document : Article/Communication Auteurs : Lei Wang, Auteur ; Paul D. Groves, Auteur ; Marek Ziebart, Auteur Année de publication : 2013 Article en page(s) : 13 p. ; pp 44 - 56 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes IGN] canyon urbain [Termes IGN] correction du trajet multiple [Termes IGN] milieu urbain [Termes IGN] signal GNSS [Termes IGN] téléphone intelligent [Termes IGN] trajet multiple Résumé : (Editeur) This article presents a smartphone-based system that uses the GNSS signal 'shadows' cast by buildings - usually the satellite-signal blocking bane of navigating in narrow urban canyons - to improve the accuracy of street-level positioning. The authors present the results of field tests that reveal dramatic reduction of positioning errors and improved availability. Numéro de notice : A2013-728 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75694 [article]

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