Landsat TM image feature extraction and analysis of algal bloom in Taihu Lake

This study developed an approach to the extraction and characterization of blue-green algal blooms of the study area Taihu Lake of China with the Landsat 5 TM imagery. Spectral feature of typical material within Taihu Lake were first compared, and the most sensitive spectral bands to blue-green algal blooms determined. Eight spectral indices were then designed using multiple TM spectral bands in order to maximize spectral contrast of different materials. The spectral curves describing the variation of reflectance at individual bands with the spectral indices were plotted, and the TM imagery was segmented using as thresholds the step-jumping points of the reflectance curves. The results indicate that the proposed multiple band-based spectral index NDAI2 (NDAI2 = (B4-B1)*(B5-B3)/(B4+B5+B1+B3) performed better than traditional vegetation indices NDVI and RVI in the extraction of blue-green algal information. In addition, this study indicates that the image segmentation using the points where reflectance has a sudden change resulted in a robust result, as well as a good applicability.