Recognition of Cyanobacteria Bloom Based on Spectral Analysis of Remote Sensing Imagery

Abstract:

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 Landsat7 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.