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Auteur Hosni Gherida |
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Improved atmospheric correction and chlorophyll-a remote sensing models for turbid waters in a dusty environment / Maryam R. Al Shehhi in ISPRS Journal of photogrammetry and remote sensing, vol 133 (November 2017)
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Titre : Improved atmospheric correction and chlorophyll-a remote sensing models for turbid waters in a dusty environment Type de document : Article/Communication Auteurs : Maryam R. Al Shehhi, Auteur ; Imen Gherboidj, Auteur ; Hosni Gherida, Auteur Année de publication : 2017 Article en page(s) : pp 46 - 60 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] Arabie
[Termes IGN] chlorophylle
[Termes IGN] correction atmosphérique
[Termes IGN] couleur de l'océan
[Termes IGN] eau de mer
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Terra-MODIS
[Termes IGN] test de performance
[Termes IGN] turbidité océaniqueRésumé : (Auteur) This study presents a comprehensive assessment of the performance of the commonly used atmospheric correction models (NIR, SWIR, NIR-SWIR and FM) and ocean color products (OC3 and OC2) derived from MODIS images over the Arabian Gulf, Sea of Oman, and Arabian Sea. The considered atmospheric correction models have been used to derive MODIS normalized water-leaving radiances (nLw), which are compared to in situ water nLw(λ) data collected at different locations by Masdar Institute, United Arab of Emirates, and from AERONET-OC (the ocean color component of the Aerosol Robotic Network) database. From this comparison, the NIR model has been found to be the best performing model among the considered atmospheric correction models, which in turn shows disparity, especially at short wavelengths (400–500 nm) under high aerosol optical depth conditions (AOT (869) > 0.3) and over turbid waters. To reduce the error induced by these factors, a modified model taking into consideration the atmospheric and water turbidity conditions has been proposed. A turbidity index was used to identify the turbid water and a threshold of AOT (869) = 0.3 was used to identify the dusty atmosphere. Despite improved results in the MODIS nLw(λ) using the proposed approach, Chl-a models (OC3 and OC2) show low performance when compared to the in situ Chl-a measurements collected during several field campaigns organized by local, regional and international organizations. This discrepancy might be caused by the improper parametrization of these models or/and the improper selection of bands. Thus, an adaptive power fit algorithm (R2 = 0.95) has been proposed to improve the estimation of Chl-a concentration from 0.07 to 10 mg/m3 by using a new blue/red MODIS band ratio of (443,488)/645 instead of the default band ratio used for OC3(443,488)/547. The selection of this new band ratio (443,488)/645 has been based on using band 645 nm which has been found to represent both water turbidity and algal absorption. Numéro de notice : A2017-721 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.09.011 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.09.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88406
in ISPRS Journal of photogrammetry and remote sensing > vol 133 (November 2017) . - pp 46 - 60[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2017111 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017112 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt 081-2017113 DEP-EXM Revue Saint-Mandé Dépôt en unité Exclu du prêt