Recognition of cyanobacteria bloom based on spectral analysis of remote sensing imagery

Based on the analysis of spectral curve and features of cyanobacteria bloom and other typical ground object,the normalized difference cyanobacteria bloom index(NDI_CB)was constructed to distinguish between cyanobacteria bloom and turbid water with the Landsat-7 ETM+ image in Lake Dianshan.In this study two other different vegetation indexes,normalized difference vegetation index(NDVI)and ratio vegetation index(RVI),together with NDI_CB,were applied to extracting the cyanobacteria bloom information from the same image via unsupervised classification method(k-means).The results show that NDI_CB is the best one for low-density cyanobacteria bloom extraction.In order to recognize the cyanobacteria bloom better,support vector machine(SVM)classification method was used to classify the image based on spectral features and NDI_CB,and to obtain the spatial distribution and the area of cyanobacteria bloom in Lake Dianshan.Through studying the laws of the cyanobacteria bloom distribution at a particular time,a sound,efficient and objective basis has been achieved for the ecological analysis of the prevention and the treatment of cyanobacteria bloom.