A novel three-band macroalgae detection index (TMI) for aquatic environments

Majid Nazeer, Mohammad M.M. Alsahli, Janet Elizabeth Nichol, Jiayi Pan, Weicheng Wu, Muhammad Bilal, Urooj Saeed

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Overgrowth of algae is a serious threat for aquatic ecosystems. This threat has occurred frequently in recent decades due to increased anthropogenic activities. Thus, understanding how the aquatic environment promotes algae growth by comprehensive monitoring is essential for protecting and sustaining aquatic ecosystems. We propose a novel Three band Macroalgae Index (TMI) using the green, red and near-infrared bands of Landsat-8 Operational Land Imager (OLI) as a robust remote sensing indicator for detecting and monitoring algae overgrowth in aquatic ecosystems. The proposed index has been tested in different water quality conditions in different aquatic environments. These conditions always vary between different images even if the study area is the same, e.g. atmospheric aerosols, refraction of water-leaving radiance according to sun and view angles, and sun glint on the surface which is influenced by waves and currents. Also, the six study areas were selected because of their water quality differences, including open ocean and inland lakes, e.g. Great Salt Lake being hypersaline waters, Lake St. Claire regarded as moderately eutrophic and open ocean waters in English Channel. A cross-comparison among the TMI and nine existing algal bloom indices indicated the superior performance of TMI (90%–100%), with reference to similarity to the OC2-based-TSI classifications. The performance of the existing indices was inconsistent across varying environmental and water quality conditions. This might be attributed to several factors including, uncertainty of shortwave infrared band retrievals used by some indices over turbid waters, and dependence of those indices on specific geographical location and/or sensor. The TMI overcame these issues and is therefore an alternative index for algal bloom detection in different water types, as it uses the wavebands which are commonly available on many remote sensing systems.

Original languageEnglish
Pages (from-to)2359-2381
Number of pages23
JournalInternational Journal of Remote Sensing
Volume44
Issue number7
DOIs
Publication statusPublished - Apr 2023

Keywords

  • Algal bloom
  • coastal water
  • harmful algal bloom
  • Landsat-8 OLI
  • remote sensing

ASJC Scopus subject areas

  • General Earth and Planetary Sciences

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