摘要
随着太湖水体富营养化的日益严重和蓝藻水华爆发的逐年加剧,如何实现藻类的时空动态监测成为亟待解决的关键问题。本文在分析太湖水体光谱特征的基础上,总结了太湖藻类叶绿素浓度反演的几种常用方法:经验模型、半经验模型、分析模型、混合光谱模型、神经网络模型等,并分析了各自的优缺点;在比较了不同遥感数据源在反演估算中的应用特点后,提出新型卫星遥感数据具有遥感反演的应用优势;最后对太湖藻类的遥感监测研究中存在的问题及发展方向做出了分析和展望。
Along with the increasingly serious eutrophication and aggravation of algal blooms in Taihu Lake, how to achieve the dynamic monitoring of Taihu algae in the temporal and spatial scales becomes a key issue to be resolved. After analyzing the spectral characteristics of Taihu algae, the methods of chlorophyll concentration inversion and the different characteristics of remote sensing data in algae monitoring were addressed. Finally, the existing problems and the prediction of the future research tendency in Taihu algae monitoring were proposed.
出处
《遥感信息》
CSCD
2008年第4期102-108,共7页
Remote Sensing Information
基金
科技部973项目(2005CB422208)
国家自然科学基金项目(40671132)
关键词
太湖藻类
叶绿素A
遥感监测
Taihu algae
chlorophyll a
remote sensing monitoring
