巢湖水体POC浓度遥感反演算法与验证  

A novel algorithm to estimate POC concentrations in Chaohu Lake,China

作　　者：吴静汇 段洪涛[1] 张玉超[1] 马荣华[1] 

机构地区：[1]中国科学院南京地理与湖泊研究所湖泊与环境国家重点实验室,江苏南京210008 [2]中国科学院大学,北京100039

出　　处：《红外与毫米波学报》2015年第6期750-756,共7页Journal of Infrared and Millimeter Waves

基　　金：国家自然科学基金(41431176)~~

摘　　要：基于2013年巢湖实测数据,根据颗粒性有机碳(Particulate Organic Carbon,POC)浓度与叶绿素a之间的高度相关性,采用Gons和Simis算法估算浮游植物色素吸收a_(ph)(665),继而实现对POC浓度间接反演。结果表明,Gons和Simis算法可用于蓝藻水华未覆盖内陆水体POC浓度的估算;Gons算法(RMSE_(rel)=21.90%)相对于Simis算法(RMSE_(rel)=23.81%)可以更好地反演POC的浓度。Gons和Simis算法在巢湖POC反演中取得了较好的结果,可以结合MERIS卫星用于巢湖水体POC估算。也可以为内陆湖泊水体碳循环研究提供技术和数据支撑,具有重要的科学研究意义。Based on in situ data from Chaohu Lake,a novel algorithm was developed to estimate POC concentrations in eutrophic lakes. This two-step algorithm examined changes in absorption a_（ph）（ 665）and associated to POC concentrations though a measured relationship between a_（ph）（ 665） POC determined in extensive measurements in this large eutrophic lake. Two different a_（ph）（ 665） algorithms were explored. While both provided good estimates of POC concentrations,Gons algorithm（ RMSE_（rel） =21. 90%） was superior to that of Simis（ RMSE_（rel） = 23. 81%）. This approach was developed for mediumspectral resolution satellite senors,such as MERIS or Sentinel 3-OLCI. The application of this approach will provide new insights to our understanding of the aquatic carbon cycle in inland waters.

关 键 词：颗粒有机碳 叶绿素A 色素吸收 生物光学模型 

分 类 号：X122[环境科学与工程—环境科学]