Estimation of chlorophyll-a using MERSI and MODIS images in Taihu Lake, China
基于MERSI和MODIS的太湖水体叶绿素a含量反演

The Chlorophyll-a (Chl-a) concentrations in water are of great importance to the monitoring of water quality and ecosystem balance. Remote sensing offers a convenient and systematical tool for the observations of water at a long time scale. In this paper, we present a study of Chl-a estimation using the reflectance models (MOD3: Rλ1-1-Rλ2-1)×Rλ3and MOD2:Rλ1-1×Rλ3) derived from the Medium Resolution Spectral Image (MERSI) onboard the newly launched FY-3A satellite and the Moderate Imaging Spectroradiometer (MODIS) onboard the AQUA platforms. Validation studies demonstrated that both models provided reliable estimates of Chl-a concentrations with determination coefficients R2 of 0.72~0.79 (MOD2) and 0.52~0.76 (MOD3) for MERSI standard band settings. This accuracy is slightly better than that of the MODIS results with R2 of 0.65~0.69 and 0.43~0.70 for MOD2 and MOD3, respectively. Comparison analysis between models and sensors indicated that the blue and near infrared wave ranges are of potential for Chl-a estimation. Besides, the higher spatial resolution of MERSI (250m) may explain the better performance for both models compared to that of MODIS. This research will be helpful for the development of future Chl-a estimation models using the satellite observations.