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Auteur Yunpeng Wang |
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Sea ice extent detection in the Bohai Sea using Sentinel-3 OLCI data / Hua Su in Remote sensing, Vol 11 n° 20 (October-2 2019)
[article]
Titre : Sea ice extent detection in the Bohai Sea using Sentinel-3 OLCI data Type de document : Article/Communication Auteurs : Hua Su, Auteur ; Bowen Ji, Auteur ; Yunpeng Wang, Auteur Année de publication : 2019 Article en page(s) : 17 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bande infrarouge
[Termes IGN] changement climatique
[Termes IGN] Chine, mer de
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] glace de mer
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-OLCI
[Termes IGN] Normalized Difference Snow Index
[Termes IGN] réflectanceRésumé : (auteur) Sea ice distribution is an important indicator of ice conditions and regional climate change in the Bohai Sea (China). In this study, we monitored the spatiotemporal distribution of the Bohai Sea ice in the winter of 2017–2018 by developing sea ice information indexes using 300 m resolution Sentinel-3 Ocean and Land Color Instrument (OLCI) images. We assessed and validated the index performance using Sentinel-2 MultiSpectral Instrument (MSI) images with higher spatial resolution. The results indicate that the proposed Normalized Difference Sea Ice Information Index (NDSIIIOLCI), which is based on OLCI Bands 20 and 21, can be used to rapidly and effectively detect sea ice but is somewhat affected by the turbidity of the seawater in the southern Bohai Sea. The novel Enhanced Normalized Difference Sea Ice Information Index (ENDSIIIOLCI), which builds on NDSIIIOLCI by also considering OLCI Bands 12 and 16, can monitor sea ice more accurately and effectively than NDSIIIOLCI and suffers less from interference from turbidity. The spatiotemporal evolution of the Bohai Sea ice in the winter of 2017–2018 was successfully monitored by ENDSIIIOLCI. The results show that this sea ice information index based on OLCI data can effectively extract sea ice extent for sediment-laden water and is well suited for monitoring the evolution of Bohai Sea ice in winter. Numéro de notice : A2019-557 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs11202436 Date de publication en ligne : 29/10/2019 En ligne : https://doi.org/10.3390/rs11202436 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94214
in Remote sensing > Vol 11 n° 20 (October-2 2019) . - 17 p.[article]A new scheme for urban impervious surface classification from SAR images / Hongsheng Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 139 (May 2018)
[article]
Titre : A new scheme for urban impervious surface classification from SAR images Type de document : Article/Communication Auteurs : Hongsheng Zhang, Auteur ; Hui Lin, Auteur ; Yunpeng Wang, Auteur Année de publication : 2018 Article en page(s) : pp 103 - 118 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] classification
[Termes IGN] Hong-Kong
[Termes IGN] image radar moirée
[Termes IGN] image Radarsat
[Termes IGN] Macao
[Termes IGN] polarimétrie radar
[Termes IGN] Shenzhen
[Termes IGN] surface imperméable
[Termes IGN] zone urbaineRésumé : (Auteur) Urban impervious surfaces have been recognized as a significant indicator for various environmental and socio-economic studies. There is an increasingly urgent demand for timely and accurate monitoring of the impervious surfaces with satellite technology from local to global scales. In the past decades, optical remote sensing has been widely employed for this task with various techniques. However, there are still a range of challenges, e.g. handling cloud contamination on optical data. Therefore, the Synthetic Aperture Radar (SAR) was introduced for the challenging task because it is uniquely all-time- and all-weather-capable. Nevertheless, with an increasing number of SAR data applied, the methodology used for impervious surfaces classification remains unchanged from the methods used for optical datasets. This shortcoming has prevented the community from fully exploring the potential of using SAR data for impervious surfaces classification. We proposed a new scheme that is comparable to the well-known and fundamental Vegetation-Impervious surface-Soil (V-I-S) model for mapping urban impervious surfaces. Three scenes of fully polarimetric Radsarsat-2 data for the cities of Shenzhen, Hong Kong and Macau were employed to test and validate the proposed methodology. Experimental results indicated that the overall accuracy and Kappa coefficient were 96.00% and 0.8808 in Shenzhen, 93.87% and 0.8307 in Hong Kong and 97.48% and 0.9354 in Macau, indicating the applicability and great potential of the new scheme for impervious surfaces classification using polarimetric SAR data. Comparison with the traditional scheme indicated that this new scheme was able to improve the overall accuracy by up to 4.6% and Kappa coefficient by up to 0.18. Numéro de notice : A2018-111 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.03.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.03.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89541
in ISPRS Journal of photogrammetry and remote sensing > vol 139 (May 2018) . - pp 103 - 118[article]Exemplaires(1)
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