基于光学分类的太湖水体叶绿素a浓度高光谱遥感  

Hyperspectral Remote Sensing of Chlorophyll a Concentrations in the Lake Taihu,Based on Water Optical Classification

作　　者：孙德勇[1] 周晓宇[1] 李云梅[2] 陈晓玲[3] 黄昌春[2] 龚绍琦[1] 

机构地区：[1]南京信息工程大学遥感学院,南京210044 [2]南京师范大学教育部虚拟地理环境重点实验室,南京210046 [3]武汉大学测绘遥感信息工程国家重点实验室,武汉430079

出　　处：《环境科学》2013年第8期3002-3009,共8页Environmental Science

基　　金：中国科学院数字地球重点实验室开放基金项目(2011LDE009);国家自然科学基金项目(41101340);武汉大学测绘遥感信息工程国家重点实验室开放基金项目[(11)重04];江苏高校优势学科建设工程项目

摘　　要：利用2006年11月、2008年11月、2010年5月和8月的太湖水体原位观测数据,在对水体进行光学分类的基础上,分别建立了针对各个类别水体的叶绿素a浓度高光谱反演模型.通过对每类水体各个模型的性能比较,结果表明:第一类水体,四波段模型为最优模型;第二类和第三类水体,一阶微分模型均为最优模型.同时,也比较了水体分类前后模型的表现,表明水体分类后模型在精度和稳定性上都有不同程度的提高.本研究结论对光学复杂混浊湖泊水体的水色遥感具有参考意义.Four field investigations into the Lake Taihu were carried out for collecting in situ observed data in Nov.,2006,Nov.,2008,May and Aug.,2010.On the basis of water optical classification,different retrieval algorithms were developed,specifically for different types of waters.The obtained optimal models were ①the four-band model for Type 1 water;②the first-order differential model for Type 2 and Type 3 waters.Meanwhile,an optimal retrieval model was also established using the same aggregated calibration data.Some comparisons were done between the developed models for the classified and non-classified waters.The compared results showed that models for the classified waters had better performances than that for the non-classified water,in both retrieval accuracy and model stability.The findings of this study are significant for promoting the development of water color remote sensing for optically complex turbid inland waters.

关 键 词：复杂混浊水体 光学分类 叶绿素A浓度 反演模型 太湖 

分 类 号：X87[环境科学与工程—环境工程]