湖泊水体颜色作为水体光学特性的直观反映，是湖泊生态系统的重要气候变量。近年来，基于卫星遥感反演湖泊水色的Forel-Ule指数 (FUI) 被广泛用于指示大区域湖泊生态与水质的时空变化。多源卫星协同观测可显著提升观测频率和时空覆盖范围，但其反演一致性问题亟需解决。本研究以青藏高原6个典型湖泊为研究区，基于Landsat 5/TM、Landsat 7/ETM+、Landsat 8/OLI和MODIS地表反射率产品，提出一种多源卫星数据反演湖泊水色指数FUI的一致性校正方法，以校正卫星光谱响应函数及地表反射率产品系统偏差导致的色度角和FUI反演差异。首先，采用水体模拟数据集的多项式校正方法，对各卫星传感器可见光波段反演的色度角进行光谱响应校正；其次，利用在6个湖泊获取的112,830组地表反射率同步观测数据对，构建MODIS与Landsat TM、ETM+、OLI反演色度角之间的线性回归模型，进行交叉定标校正；最后，基于同步观测数据对及长时间序列FUI多源数据反演结果，系统评估校正前后多源卫星数据在像元尺度和时间序列尺度上的一致性。结果表明，校正后色度角与FUI反演结果一致性显著提升 (R2 > 0.95，MAPE < 10%)，且4种卫星数据反演的湖泊年均FUI变化趋势一致。本研究为Landsat TM、ETM+、OLI与MODIS多源卫星数据协同反演湖泊水色参量提供重要方法依据。

Objective: The color of lake water, as a direct reflection of its optical properties, is an important climate variable of lake ecosystems. In recent years, the Forel-Ule Index (FUI) drived from satellite remote sensing has been widely used to indicate the spatiotemporal variations in lake ecology and water quality over large areas. Multi-source satellite observations can significantly improve observation frequency and spatiotemporal coverage; however, the consistency of FUI retrieval across different satellites remains a challenge. Method: This study focuses on six typical lakes on the Tibetan Plateau and develops a consistency correction method for FUI retrieval using multi-source satellite data, including Landsat 5/TM, Landsat 7/ETM+, Landsat 8/OLI, and MODIS surface reflectance products. The method aims to correct the retrieval differences in hue angles and FUI caused by variations in satellite spectral response functions and systematic biases in surface reflectance products. First, a polynomial correction approach based on a water body simulation dataset is applied to perform spectral response correction for the hue angles drived from the visible bands of different satellite sensors. Second, using 112,830 pairs of surface reflectance synchronous observations from the six lakes, a linear regression model is established between MODIS and Landsat TM, ETM+, and OLI retrievals of hue angles for cross-correction. Finally, the consistency of multi-source satellite data is systematically evaluated at both the pixel scale and the time series scale based on the synchronous observations and long-term FUI retrievals. Result : Results show that the consistency of the drived hue angles and FUI significantly improves after correction (R2 > 0.95, MAPE < 10%), and the annual mean FUI trends derived from the four satellite datasets are consistent. Conclusion : This study provides an important methodological reference for the synergistic retrieval of lake water color parameters using Landsat TM, ETM+, OLI, and MODIS multi-source satellite data.