A simple and effective method for monitoring floating green macroalgae blooms: a case study in the Yellow Sea.


Journal

Optics express
ISSN: 1094-4087
Titre abrégé: Opt Express
Pays: United States
ID NLM: 101137103

Informations de publication

Date de publication:
18 Feb 2019
Historique:
entrez: 17 3 2019
pubmed: 17 3 2019
medline: 18 5 2019
Statut: ppublish

Résumé

Several algorithms have been proposed to detect floating macroalgae blooms in the global ocean. However, some of them are difficult or even impossible to routinely apply by non-experts because of performing a sophisticated atmospheric correction scheme or due to the mismatch in spectral bands from one sensor to another. Here, a generic, simple and effective method, referred to as the Floating Green Tide Index (FGTI), was proposed to detect floating green macroalgae blooms (GMB). The FGTI was defined as the difference between greenness and wetness features extracted from digital number (DN) observation through Tasseled Cap Transformation analysis, providing the advantage of bypassing the atmospheric correction procedure. Through cross-index and cross-sensor comparisons, the FGTI showed similar performance to the existing VB-FAH (Virtual-Baseline Floating macroAlgae Height) and FAI (Floating Algae Index) algorithms but proved more robust than the traditional NDVI (Normalized Difference Vegetation Index) in terms of response to perturbations by environmental conditions, viewing geometry, sun glint, and thin cloud contamination. Given the requirement for spectral bands in the current and planned satellite sensors, the FGTI design can easily be extended to any satellite sensor, and therefore provide an excellent data resource for studying GMB in any part of the global ocean.

Identifiants

pubmed: 30876071
pii: 404803
doi: 10.1364/OE.27.004528
doi:

Substances chimiques

Water Pollutants 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

4528-4548

Auteurs

Articles similaires

Selecting optimal software code descriptors-The case of Java.

Yegor Bugayenko, Zamira Kholmatova, Artem Kruglov et al.
1.00
Software Algorithms Programming Languages
1.00
Humans Magnetic Resonance Imaging Brain Infant, Newborn Infant, Premature
India Carbon Sequestration Environmental Monitoring Carbon Biomass
Humans Algorithms Software Artificial Intelligence Computer Simulation

Classifications MeSH