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引用本文:沈明,段洪涛,曹志刚,薛坤,马荣华.适用于多种卫星数据的太湖水体漫衰减系数估算算法.湖泊科学,2017,29(6):1473-1484. DOI:10.18307/2017.0619
SHEN Ming,DUAN Hongtao,CAO Zhigang,XUE Kun,MA Ronghua.Remote sensing estimation algorithm of diffuse attenuation coefficient applicable to different satellite data in Lake Taihu, China. J. Lake Sci.2017,29(6):1473-1484. DOI:10.18307/2017.0619
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适用于多种卫星数据的太湖水体漫衰减系数估算算法
沈明1,2, 段洪涛1, 曹志刚1,2, 薛坤1, 马荣华1
1.中国科学院南京地理与湖泊研究所中国科学院流域地理学重点实验室, 南京 210008;2.中国科学院大学, 北京 100049
摘要:
下行漫衰减系数(Kd)是描述水下光场的重要参数,决定水体真光层深度,影响着浮游藻类初级生产力及其分布特征.基于2008-2013年太湖4次大规模野外试验数据,分析太湖水体漫衰减系数特征及其影响因素,建立适用于多种卫星数据且较高精度的太湖水体490 nm处下行漫衰减系数估算模型.结果表明:无机悬浮物是太湖水体漫衰减系数的主要影响因素;红绿波段比值(674 nm/555 nm)最适合于太湖Kd(490)估算,模型反演精度较高(N=72,R2=0.72,RMSE=0.89 m-1MAPE=21.58%);利用实测光谱数据,模拟得到MODIS/EOS、OLCI/Sentinel-3、GOCI/COMS和MSI/Sentinel-2等主要传感器波段的信号,构建适用于多种卫星传感器Kd(490)估算的红绿波段模型,建模精度较高(N=72,R2>0.7,RMSE<0.9 m-1MAPE<22.0%),且进行了验证(N=37,R2>0.7,RMSE<0.9 m-1MAPE<22.0%).
关键词:  太湖  漫衰减系数  遥感反射率
DOI:10.18307/2017.0619
分类号:
基金项目:江苏省杰出青年基金项目(BK20160049)、国家自然科学基金项目(41671358,41431176)和中国科学院青年创新促进会项目(2012238)联合资助.
Remote sensing estimation algorithm of diffuse attenuation coefficient applicable to different satellite data in Lake Taihu, China
SHEN Ming1,2, DUAN Hongtao1, CAO Zhigang1,2, XUE Kun1, MA Ronghua1
1.Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, P. R. China;2.University of Chinese Academy of Sciences, Beijing 100049, P. R. China
Abstract:
The downwelling diffuse attenuation coefficient (Kd) plays a critical role in underwater light field. It determines the euphotic depth, and affects the distribution characteristics of phytoplankton and primary productivity. Based on in situ data collected from 4 cruise surveys in Lake Taihu during 2008-2013, both the variations and driving factors of Kd were analyzed, and an algorithm to estimate downwelling diffuse attenuation coefficient at 490 nm for a variety of satellites' data was developed and validated. The results show that:(1) suspended particular inorganic matter is the decisive factor of Kd in Lake Taihu;(2) the algorithm of red-green band ratio is the most suitable for estimating Kd(490) in Lake Taihu (N=72, R2=0.72, RMSE=0.89 m-1, MAPE=21.58%);(3) with the simulated remote sensing reflectance of the main sensor bands such as MODIS/EOS, OLCI/Sentinel-3, GOCI/COMS and MSI/Sentinel-2, the red-green ratio algorithm to estimate Kd(490) was established for a variety of remote sensing sensors(N=72,R2>0.7,RMSE<0.9 m-1,MAPE<22.0%), and the validation was good as well(N=37,R2>0.7,RMSE<0.9 m-1,MAPE<22.0%).
Key words:  Lake Taihu  diffuse attenuation coefficient  remote sensing reflectance
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