Determination of chlorophyll a content of the Lake Taihu, China using Landsat-5 TM data

Measurements of chlorophyll a (chl-a), along with various transformations such as the trophic state indices of Carlson (1977), are widely used to indicate trophic state of lakes by lake management agencies and organizations. The integration of water quality models, in situ data and remote sensing data provide a new method to measure the content of chl-a, which can also provide spatial distribution information. This paper focused on developing and applying remote sensing algorithms to determine the chl-a content of such turbid, mesotrophic to highly eutrophic lake waters, using Lake Taihu, China as a case study. Landsat-5 TM data and synchronous in situ measurements were used. A Pearson correlation matrix indicated that the ratio of TM4 to TM3 has the strongest relationship with chl-a. A four-coefficient regression model using TM4/TM3 ratio and TM1, TM2 was a reliable predicator of chl-a (r²=0.837) for waters with chl-a concentration between 5 mgm^-3 and 100 mgm^-3. This model underpredict the values at very high chl-a concentration values (higher than 100 mgm^-3), while overpredicting the values at very low chl-a concentration (lower than 5 mgm^-3)