基于OLCI数据的福建近海悬浮物浓度遥感反演

悬浮物（TSM）是评估水质的重要指标，也是水色遥感反演的核心参数之一.海陆色度仪（OLCI）是新一代海洋水色传感器，具有良好的光谱及时空分辨率.为有效监测福建近海悬浮物浓度的时空变化，本文结合OLCI遥感数据和现场实测悬浮物浓度数据，使用CatBoost、随机森林和多元回归方法，分别构建悬浮物浓度反演模型，最后使用验证集对比分析不同模型的反演精度.结果表明，CatBoost模型估算精度最高，均方根误差（RMSE）为2.76 mg·L^-1，平均绝对百分比误差（MAPE）为23.67%，决定系数R²为0.89.使用CatBoost模型对2017—2018年多时相OLCI影像进行TSM浓度遥感反演，结果发现，福建近海TSM浓度变化显著，但总体呈现近岸高于远岸、北部高于南部、江河入海口和港湾处高于周围其他海域、春季高于夏季的时空分布特征.本研究可为福建近海的悬浮物浓度监测提供一种有效的方法，也进一步证明了OLCI影像良好的水色反演能力，可作为水质监测的有效遥感数据源.

Retrieving total suspended matter concentration in Fujian coastal waters using OLCI data

Total suspended matter (TSM) is an important indicator to evaluate water quality, and is also one of the key parameters for ocean color remote sensing inversion. The Ocean and Land Color Instrument (OLCI) is a new generation of ocean water color sensor with well spectral and spatio-temporal resolution. This paper adopted CatBoost, Random Forest and multiple regression methods to establish the TSM concentration inversion model based on OLCI data and in-situ observations, and the validation dataset was used to evaluate the model accuracy. The results showed that the CatBoost model had the highest accuracy with RMSE of 2.76 mg·L^-1, MAPE of 23.67%, and R² of 0.89. Finally, the CatBoost model was applied to the time-series OLCI images to obtain the distribution of TSM concentration in Fujian coastal waters. The results indicated that the spatial and temporal variation of TSM concentration was significant, and the general pattern presents that the near-shore is higher than the far-shore, north region is higher than south region, estuaries and harbors are higher than other region, spring is higher than summer. This study provides a new method for retrieving TSM concentration, and further proves the good water color inversion ability of OLCI images, which can provide an effective remote sensing data for water quality monitoring in the Fujian Province.