To what extent can Ulva and Sargassum be detected and separated in satellite imagery?

Detection limit Discrimination limit East China Sea MSI OLCI Remote sensing Sargassum horneri Ulva prolifera Yellow sea

Journal

Harmful algae
ISSN: 1878-1470
Titre abrégé: Harmful Algae
Pays: Netherlands
ID NLM: 101128968

Informations de publication

Date de publication:
03 2021
Historique:
received: 16 08 2020
revised: 17 02 2021
accepted: 18 02 2021
entrez: 13 5 2021
pubmed: 14 5 2021
medline: 28 5 2021
Statut: ppublish

Résumé

Blooms of floating macroalgae have been reported around the world, among which are recurrent blooms of Ulva prolifera and Sargassum horneri in the Yellow Sea and East China Sea. While satellite remote sensing has often been used to estimate their distributions and abundance as well as to trace their origins, because the algae mats are often much smaller than the size of an image pixel, it is unclear to what extent they can be detected and discriminated from each other in satellite imagery. Using data collected from laboratory experiments and by the Sentinel-3 OLCI (Ocean and Land Colour Instrument) and Sentinel-2 MSI (Multi Spectral Instrument) satellite instruments, we conduct simulated experiments to determine the lower detection limit and discrimination limit for these two macroalgae in different water environments and under different atmospheric conditions. For OLCI, the detection limit for both macroalgae is about 0.5% of a pixel, while the discrimination limit varies between 0.8% for clear water and 2% for turbid water. For MSI, the detection limit is about 2%, while the discrimination limit is about 6% for all water types. Below these two limits, detection and discrimination of macroalgae in these regions using the two sensors are subject to large uncertainties, thus requiring additional caution when interpreting algae areas and tracing algae origins.

Identifiants

pubmed: 33980441
pii: S1568-9883(21)00028-7
doi: 10.1016/j.hal.2021.102001
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

102001

Informations de copyright

Copyright © 2021. Published by Elsevier B.V.

Auteurs

Lin Qi (L)

School of Marine Sciences, Sun Yat-Sen University (SYSU), Guangzhou, China; Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China.

Chuanmin Hu (C)

College of Marine Science, University of South Florida, St. Petersburg, FL, USA. Electronic address: huc@usf.edu.

Articles similaires

Humans Neoplasms Male Female Middle Aged
Humans Male Female Aged Middle Aged
Humans Retrospective Studies Male Critical Illness Female

Classifications MeSH