(12th World Lake Conference Taal 2007, p. 95)
Remote sensing technology takes on important role in hydrology fields for it can provide information of water resource quaiity and its environment of the water body on earth timely and effectively. This paper researches the usage of ASTER Images on water quality variation of Tai lake, whose investigated water quality data of summer are used to take main component analysis and cluster analysis, which can decide the most important effective index. Through analysis a separation of several indicators that affect water quality calculated by the degree of contribution. It was found that water quality of Tai lake suffered mainly by the suspended material and chlorophyll. According to the results of the analysis, the article focused on the chlorophyll and suspended material of Tai lake water through the ASTER 1 B Images.
Through the method of spectral analysis, 6 classes are derived by Mahalanobis-distance supervised classification: clean water, high-concentration SS (suspended material) water, high-concentration chlorophyll, some-concentration SS and some-concentration chlorophyll, the dimension of the zone researched and every main contaminating ingredient was calculated; and the total accuracy is 84.7965%, and the Kappa coefficient is 0.8174. NDVI extraction of different concentration chlorophyll was done to analyse the chlorophyll concentration variance of Tai lake. Same conclusion is gained as that from classification. Finally, along with the derived water quality information by classification and the situation quality surrounding the lake judged from the remote sensing ASTER images, the cause of pollution is analysed and the trend is predicted.
