TY - JOUR
T1 - A novel three-band macroalgae detection index (TMI) for aquatic environments
AU - Nazeer, Majid
N1 - Funding Information:
The work was supported by the East China University of Technology [DHTP2018001]; Hong Kong Polytechnic University [P0044784]; Jiangxi Talent Programme [900/2120800004] The authors would like to thank, the USGS for the distribution of Landsat-8 and Landsat-9 OLI data products, ESA for providing the Sentinel-2B MSI and Sentinel-3B OLCI data products through Copernicus Data Hub, the Planet Team for providing access to the Planet Scope data, USGS Spectral Library for maintaining and making available the spectra of different materials freely available, Royal Belgian Institute of Natural Sciences (RBINS) for providing open-access to the ACOLITE software and the anonymous reviewers for their constructive feedback. This research was supported by The Hong Kong Polytechnic University’s Start-up Fund for RAPs under the Strategic Hiring Scheme (Project ID: P0044784) to Majid Nazeer and by East China University of Technology, Nanchang China through the Research Start-up Funding to Dr Weicheng Wu (Grant No. DHTP2018001) who is also supported by the Jiangxi Talent Programme (Grant No. 900/2120800004).
Funding Information:
This research was supported by The Hong Kong Polytechnic University’s Start-up Fund for RAPs under the Strategic Hiring Scheme (Project ID: P0044784) to Majid Nazeer and by East China University of Technology, Nanchang China through the Research Start-up Funding to Dr Weicheng Wu (Grant No. DHTP2018001) who is also supported by the Jiangxi Talent Programme (Grant No. 900/2120800004).
Publisher Copyright:
© 2023 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2023/4/23
Y1 - 2023/4/23
N2 - 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.
AB - 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.
KW - Algal bloom
KW - Landsat-8 OLI
KW - coastal water
KW - harmful algal bloom
KW - remote sensing
UR - http://www.scopus.com/inward/record.url?scp=85153326997&partnerID=8YFLogxK
U2 - 10.1080/01431161.2023.2202339
DO - 10.1080/01431161.2023.2202339
M3 - Journal article
SN - 0143-1161
VL - 44
SP - 2359
EP - 2381
JO - International Joural of Remote Sensing
JF - International Joural of Remote Sensing
IS - 7
ER -