ABSTRACT Previous studies in the US Virgin Islands (USVI) have shown that land-based sources of pollution associated with watershed development coupled with climate is causing coral reef degradation. A good indicator that can be used to assess stress on these environments is the water quality. Conventional assessment methods based on in-situ measurements are timely and costly. Satellite remote sensing techniques offer better spatial coverage and temporal resolution to accurately characterize the dynamic nature of Water Quality Parameters (WQPs, chlorophyll-a), total suspended sediments (TSM), and coloured-dissolved organic matter). However, the interference of multiple optically active WQPs that characterize the water column as well as reflectance from the bottom substrates poses a challenge especially in shallow coastal environments such as the USVI. The optical properties of USVI waters are a function of multiple WQPs with chlorophyll-a values ranging from 0.10 to 2.35 μg L−1 and TSM values from 8.97 to 15.7 mg L−1. In this study, field data were combined with NASA’s Landsat Operational Land Imager (OLI) sensor data to specifically model chlorophyll-a variability in the USVI waters based on spectral indices approach. Landsat OLI spectral-based model produced promising results for characterizing the variability of chlorophyll-a in the USVI (coefficient of determination (R 2) = 0.70; root-mean-square error (RMSE) = 0.042 μg L−1). Model developed in this study will significantly improve near-real time and long-term water quality monitoring in USVI and this will potentially help to provide insight to factors contributing to coral reef decline.

中文翻译：

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Landsat 8 OLI在美属维尔京群岛近海监测中的应用

摘要 先前在美属维尔京群岛 (USVI) 的研究表明，与流域开发和气候相关的陆上污染源正在导致珊瑚礁退化。可用于评估这些环境压力的一个很好的指标是水质。基于原位测量的传统评估方法既及时又昂贵。卫星遥感技术提供更好的空间覆盖和时间分辨率，以准确表征水质参数（WQP、叶绿素-a）、总悬浮沉积物（TSM）和有色溶解有机物的动态特性。然而，表征水柱的多个光学活性 WQP 的干扰以及来自底部基底的反射构成了挑战，尤其是在 USVI 等浅海沿海环境中。USVI 水的光学特性是多个 WQP 的函数，叶绿素 a 值范围为 0.10 至 2.35 μg L-1，TSM 值范围为 8.97 至 15.7 mg L-1。在这项研究中，现场数据与 NASA 的 Landsat Operational Land Imager (OLI) 传感器数据相结合，以基于光谱指数方法专门模拟 USVI 水域中叶绿素 a 的变化。Landsat OLI 基于光谱的模型为表征 USVI 中叶绿素-a 的变异性产生了有希望的结果（决定系数 (R 2) = 0.70；均方根误差 (RMSE) = 0.042 μg L−1）。