基于海岸带高光谱成像仪影像的太湖蓝藻水华和水草识别  

Distinguishing Cyanobacteria Bloom and Aquatic Plants in Lake Taihu based on Hyperspectral Imager for the Coastal Ocean Images

作　　者：朱庆[1,2] 李俊生[2] 张方方[2] 申茜[2] 林卉[1] 王李娟[1] 朱琳[3] Qing Li Junsheng Zhang Fangfang Shen Qian Lin Hui Wang Lijuan Zhu Lin(College of Geodesy and Geomatics ,Jiangsu Normal University ,Xuzhou 221116,China Key Laboratory of Digital Earth, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences ,Beijing 100094,China Resource Environment and Tourism College, Capital Normal University ,Beijing 100048 ,China)

机构地区：[1]江苏师范大学测绘学院,江苏徐州221116 [2]中国科学院遥感与数字地球研究所数字地球重点实验室,北京100094 [3]首都师范大学资源环境与旅游学院,北京100048

出　　处：《遥感技术与应用》2016年第5期879-885,共7页Remote Sensing Technology and Application

基　　金：国家自然科学基金项目"基于软分类的太湖水体叶绿素a浓度反演与时空变化分析"(41471308)

摘　　要：水华与水草的同步监测对于研究湖泊水环境、生态特性以及水循环具有重要意义，相对于传统监测方法如实地调查，利用遥感手段具有大范围、长时间周期、高效率以及低成本等优势。基于海岸带高光谱成像仪HICO（Hyperspectral ImagerfortheCoastal Ocean）影像，利用叶绿素a光谱指数和藻蓝蛋白基线的水华和水草识别模型，提取太湖水华和水草分布图，经过检验，水华和水草的平均提取精度为93％和95％；通过水华和水草分布图的叠加分析了2010～2014年太湖水华和水草的分布规律，与相关文献的分析结果一致，进一步证实了识别方法的可靠性；将平均阈值与最佳阈值进行对比分析，提取水华与水草面积的精度分别为75．7％和84％，在对精度要求不高但对效率要求较高的情况下，可以利用平均阈值提取水华和水草，便于实现水华和水草的自动化提取及批处理。The synchronous monitoring for the cyanobacteria bloom and aquatic plants is of great signifi- cance for the study of lake water environment,ecology and the water cycle.Compared with traditional mo- nitoring methods, for instance,field investigation, using remote sensing technology with the advantages of large scope,long cycle,high efficiency and low cost.A model based on ＂Chlorophyll a Spectral Index＂ and ＂Baseline of Phycocyanin＂ was built to distinguish cyanobacteria bloom and aquatic plants in Lake Taihu by using Hyperspectral Imager for the Coastal Ocean （HICO） images.The average accuracy of cyanobacte- ria bloom and aquatic plants are 93%and 95% respectively. By overlapping the distribution maps of cya- nobacteria bloom and aquatic plants, the distribution rules of cyanobacteria bloom and aquatic plants in Lake Taihu from 2010 to 2014 were analyzed,which are consistent with the former results in the litera- tures.The average thresholds were used to extract cyanobacteria bloom and aquatic plants, and the accuracy are 75.7% and 84.0% respectively.If the efficiency is more desired than accuracy,then average thresholds ean be used to extract cyanobacteria bloom and aquatic plants.Which is convenient for realizing batch pro- cessing and the automation extraction of cyanobacteria bloom and aquatic plants.

关 键 词：太湖 水华 水草 叶绿素a光谱指数 藻蓝蛋白基线 

分 类 号：X87[环境科学与工程—环境工程] TP79[自动化与计算机技术—检测技术与自动化装置]