同济大学学报（自然科学版）2011，Vol.39Issue(8)：1247-1252,6.DOI:10.3969/j.issn.0253-374x.2011.08.028
基于遥感影像光谱分析的蓝藻水华识别方法
Recognition of Cyanobacteria Bloom Based on Spectral Analysis of Remote Sensing Imagery
摘要
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 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, wereapplied 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.关键词
归一化蓝藻指数/光谱分析/蓝藻识别/支持向量机分类Key words
normalized difference cyanobacteria bloom index/ spectral analysis/ recognition of cyanobacteria bloom/ support vector machine classificatin分类
信息技术与安全科学引用本文复制引用
林怡,潘琛,陈映鹰,任文伟..基于遥感影像光谱分析的蓝藻水华识别方法[J].同济大学学报（自然科学版）,2011,39(8):1247-1252,6.基金项目
科技部国际科技合作计划(2009DFA92310) （2009DFA92310）
