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Volume 18
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10.3390/rs18010165
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Article

Satellite-Based Assessment of Marine Environmental Indicators and Their Variability in the South Pacific Island Regions: A National-Scale Perspective

by
Qunfei Hu
1,
Teng Li
1,*,†,
Yan Bai
1,
Xianqiang He
1,
Xueqian Chen
2,†,
Liangyu Chen
2,
Xiaochen Huang
2,
Meng Huang
2 and
Difeng Wang
1,3
1
State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China
2
East China Sea Area and Island Center, Ministry of Natural Resources, Shanghai 200136, China
3
Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Remote Sens. 2026, 18(1), 165; https://doi.org/10.3390/rs18010165
Submission received: 12 November 2025 / Revised: 26 December 2025 / Accepted: 31 December 2025 / Published: 4 January 2026
(This article belongs to the Special Issue Remote Sensing Applications in Ocean Observation (Third Edition))
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Abstract

The marine environment in the South Pacific Island Countries (SPICs) is sensitive and vulnerable to climate change. While large-scale changes in this region are well-documented, national-scale analyses that address management needs remain limited. This study evaluated the performance of satellite-derived datasets—including sea surface temperature (SST), sea surface salinity (SSS), Secchi disk depth (SDD), chlorophyll-a (Chl-a), net primary production (NPP), and sea level anomaly (SLA)—against in situ observations, and analyzed their spatial and temporal variability across 12 national Exclusive Economic Zones (EEZs) during 1998–2023. Validation results presented that current satellite datasets could provide applicable information for EEZ-scale analyses. In the past decades, the SPICs experienced a general increase in SST and SLA, accompanied by marked within-EEZ heterogeneity in Chl-a and NPP variations, with Papua New Guinea exhibiting the largest within-EEZ inter-annual variability. In addition to monitoring, satellite data would help to constrain the uncertainty of CMIP6 results in the SPICs, subject to the accuracy of specific products. By 2100, Nauru might experience the most vulnerable EEZ, while the marine environment in the French Polynesian EEZ can keep relatively stable among all 12 EEZs. Meanwhile, CMIP6 projections in the Southeastern EEZs are more sensitive to satellite-based constraints, showing pronounced adjustments. Our results demonstrate the potential of combining validated satellite data with CMIP6 models to provide national-scale decision support for climate adaptation and marine resource management in the SPICs.
Keywords: satellite; marine environment indicator; CMIP6; national-scale analysis; South Pacific Island satellite; marine environment indicator; CMIP6; national-scale analysis; South Pacific Island

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MDPI and ACS Style

Hu, Q.; Li, T.; Bai, Y.; He, X.; Chen, X.; Chen, L.; Huang, X.; Huang, M.; Wang, D. Satellite-Based Assessment of Marine Environmental Indicators and Their Variability in the South Pacific Island Regions: A National-Scale Perspective. Remote Sens. 2026, 18, 165. https://doi.org/10.3390/rs18010165

AMA Style

Hu Q, Li T, Bai Y, He X, Chen X, Chen L, Huang X, Huang M, Wang D. Satellite-Based Assessment of Marine Environmental Indicators and Their Variability in the South Pacific Island Regions: A National-Scale Perspective. Remote Sensing. 2026; 18(1):165. https://doi.org/10.3390/rs18010165

Chicago/Turabian Style

Hu, Qunfei, Teng Li, Yan Bai, Xianqiang He, Xueqian Chen, Liangyu Chen, Xiaochen Huang, Meng Huang, and Difeng Wang. 2026. "Satellite-Based Assessment of Marine Environmental Indicators and Their Variability in the South Pacific Island Regions: A National-Scale Perspective" Remote Sensing 18, no. 1: 165. https://doi.org/10.3390/rs18010165

APA Style

Hu, Q., Li, T., Bai, Y., He, X., Chen, X., Chen, L., Huang, X., Huang, M., & Wang, D. (2026). Satellite-Based Assessment of Marine Environmental Indicators and Their Variability in the South Pacific Island Regions: A National-Scale Perspective. Remote Sensing, 18(1), 165. https://doi.org/10.3390/rs18010165

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