Multi-source satellite remote sensing of harmful algal blooms in the East China Sea: cross-sensor comparison of GOCI, Sentinel-2 and Sentinel-3

Introduction Harmful algal blooms (HABs) represent recurring coastal ecological hazards that threaten aquaculture, marine ecosystems and near‑shore environmental safety. Satellite remote sensing provides essential observational capacity for HAB monitoring; nevertheless, systematic quantitative inter‑comparisons between geostationary GOCI‑II and polar‑orbiting Sentinel‑2 MSI / Sentinel‑3 OLCI for identical bloom events remain limited. This study addresses the complementary strengths and limitations of these three ocean‑colour sensors for East China Sea HAB observation. Methods We selected two well‑documented HAB episodes occurring in the East China Sea during 2021 (30 April and 22 September). GOCI‑II, Sentinel‑2 MSI and Sentinel‑3 OLCI datasets were processed using sensor‑matched atmospheric correction schemes (standard GOCI‑II ocean‑colour processing, ACOLITE‑DSF for Sentinel‑2, C2RCC for Sentinel‑3 OLCI). Six spectral indices including NDCI, RBD, NRTI, RAB, PDI and DI were applied for bloom detection. Spatial‑degradation experiments at 20 m, 300 m and 500 m were implemented to separate geometric scale‑related effects on bloom area and boundary representation. Near‑simultaneous overpass comparisons and hourly GOCI‑II time‑series tracking were performed to quantify inter‑sensor discrepancies and intra‑day bloom dynamics. Results Under ~10‑minute near‑coincident overpass on 30 April 2021, GOCI‑II mapped a bloom area of 901.52 km² versus 571.52 km² from Sentinel‑2B; the difference originated jointly from spatial resolution, spectral configuration, atmospheric correction and detection thresholds, while bloom advection exerted minor influence. On 22 September 2021, hourly GOCI‑II observations captured a complete intra‑day bloom cycle: bloom optical‑anomaly area varied from 37.30 km² up to a peak of 760.20 km² and declined to 107.67 km², accompanied by a 45.74 km centroid displacement, a dynamic that single polar‑orbiting snapshots only partially captured. Spatial degradation analysis demonstrated that boundary‑length loss exceeded 76 – 85 % at coarser resolutions, whereas total‑area deviations ranged from −14.8 % to +11.0 %, highlighting Sentinel‑2’s unique value for fine‑scale near‑shore boundary delineation. Even after resolution normalisation, substantial spatial mismatch persisted among sensor bloom products (IoU as low as 0.014). Discussion Individual sensors exhibit distinct trade‑offs: GOCI‑II delivers high‑frequency temporal screening, Sentinel‑2 provides fine‑scale spatial detail, and Sentinel‑3 OLCI supplies rich spectral information for regional contextual analysis. Accordingly, we propose a conditional three‑stage multi‑source synergistic workflow: GOCI‑II for rapid hourly screening and drift tracking, Sentinel‑2 MSI for priority‑zone fine‑scale inspection, and Sentinel‑3 OLCI for regional spectral validation and cross‑sensor consistency checking. Discrepancies across sensors stem from combined effects of spectral band configuration, atmospheric correction, index thresholds and sampling timing. Limitations include only two analysed bloom events and absence of dense pixel‑level in‑situ ground truth. Further multi‑event validation with harmonised atmospheric correction is required to generalise this conditional monitoring template for operational HAB early‑warning in optically‑complex East Asian coastal waters.

Authors

Institutions

Publication Details

Journal
Frontiers in Marine Science
Published
2026-10-26
DOI
https://doi.org/10.3389/fmars.2026.1966777
Primary Topic
Marine and coastal ecosystems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multi-source satellite remote sensing of harmful algal blooms in the East China Sea: cross-sensor comparison of GOCI, Sentinel-2 and Sentinel-3

Chengxin Zhang, Honghua Shi
Frontiers in Marine Science
Marine and coastal ecosystems
article

Multi-source satellite remote sensing of harmful algal blooms in the East China Sea: cross-sensor comparison of GOCI, Sentinel-2 and Sentinel-3

Chengxin Zhang, Honghua Shi
article en

Abstract

Introduction Harmful algal blooms (HABs) represent recurring coastal ecological hazards that threaten aquaculture, marine ecosystems and near‑shore environmental safety. Satellite remote sensing provides essential observational capacity for HAB monitoring; nevertheless, systematic quantitative inter‑comparisons between geostationary GOCI‑II and polar‑orbiting Sentinel‑2 MSI / Sentinel‑3 OLCI for identical bloom events remain limited. This study addresses the complementary strengths and limitations of these three ocean‑colour sensors for East China Sea HAB observation. Methods We selected two well‑documented HAB episodes occurring in the East China Sea during 2021 (30 April and 22 September). GOCI‑II, Sentinel‑2 MSI and Sentinel‑3 OLCI datasets were processed using sensor‑matched atmospheric correction schemes (standard GOCI‑II ocean‑colour processing, ACOLITE‑DSF for Sentinel‑2, C2RCC for Sentinel‑3 OLCI). Six spectral indices including NDCI, RBD, NRTI, RAB, PDI and DI were applied for bloom detection. Spatial‑degradation experiments at 20 m, 300 m and 500 m were implemented to separate geometric scale‑related effects on bloom area and boundary representation. Near‑simultaneous overpass comparisons and hourly GOCI‑II time‑series tracking were performed to quantify inter‑sensor discrepancies and intra‑day bloom dynamics. Results Under ~10‑minute near‑coincident overpass on 30 April 2021, GOCI‑II mapped a bloom area of 901.52 km² versus 571.52 km² from Sentinel‑2B; the difference originated jointly from spatial resolution, spectral configuration, atmospheric correction and detection thresholds, while bloom advection exerted minor influence. On 22 September 2021, hourly GOCI‑II observations captured a complete intra‑day bloom cycle: bloom optical‑anomaly area varied from 37.30 km² up to a peak of 760.20 km² and declined to 107.67 km², accompanied by a 45.74 km centroid displacement, a dynamic that single polar‑orbiting snapshots only partially captured. Spatial degradation analysis demonstrated that boundary‑length loss exceeded 76 – 85 % at coarser resolutions, whereas total‑area deviations ranged from −14.8 % to +11.0 %, highlighting Sentinel‑2’s unique value for fine‑scale near‑shore boundary delineation. Even after resolution normalisation, substantial spatial mismatch persisted among sensor bloom products (IoU as low as 0.014). Discussion Individual sensors exhibit distinct trade‑offs: GOCI‑II delivers high‑frequency temporal screening, Sentinel‑2 provides fine‑scale spatial detail, and Sentinel‑3 OLCI supplies rich spectral information for regional contextual analysis. Accordingly, we propose a conditional three‑stage multi‑source synergistic workflow: GOCI‑II for rapid hourly screening and drift tracking, Sentinel‑2 MSI for priority‑zone fine‑scale inspection, and Sentinel‑3 OLCI for regional spectral validation and cross‑sensor consistency checking. Discrepancies across sensors stem from combined effects of spectral band configuration, atmospheric correction, index thresholds and sampling timing. Limitations include only two analysed bloom events and absence of dense pixel‑level in‑situ ground truth. Further multi‑event validation with harmonised atmospheric correction is required to generalise this conditional monitoring template for operational HAB early‑warning in optically‑complex East Asian coastal waters.

Frontiers in Marine ScienceVol. 13
Ministry of Natural Resources (CN), Shandong University of Science and Technology (CN)
Openalex Percentile: Top 17%
Marine and coastal ecosystems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon