2015 年 35 巻 3 号 p. 129-139
In this study, 215 MERIS images were used to estimate the chlorophyll-a concentration between 2003 and 2012 in Lake Kasumigaura, Japan. The MERIS level 1b data were first processed using an atmospheric correction algorithm. The atmospherically corrected remote-sensing reflectances were then input into a chlorophyll-a retrieval algorithm for estimating chlorophyll-a concentration. Finally, the MERIS-derived chlorophyll-aconcentrations were compared to the measured chlorophyll-a concentrations obtained from the Lake Kasumigaura database. The results showed that the MERIS data in tandem with the atmospheric correction and water quality retrieval algorithms achieved acceptable accuracy for all test sites with a normalized mean absolute error (NMAE) in the range of 24% to 34%, a root mean squared error (RMSE) in the range of 17.16 to 31.30mg m-3, and a correlation coefficient (R) in the range of 0.73 to 0.78. In addition, the MERIS-derived chlorophyll-a concentrations also showed seasonal and yearly variations similar to those of the measured chlorophyll-a concentrations (R between 0.59 and 0.78, p<0.001). These findings show the potential for satellite data to be used instead of field measurements for monitoring water quality.