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引用本文:陶慜,段洪涛,齐琳,张玉超,马荣华.一种基于MODIS影像可业务化运行的巢湖水体叶绿素a估算算法.湖泊科学,2015,27(6):1140-1150. DOI:10.18307/2015.0620
TAO Min,DUAN Hongtao,QI Lin,ZHANG Yuchao,MA Ronghua.An operational algorithm to estimate chlorophyll-a concentrations in Lake Chaohu from MODIS imagery. J. Lake Sci.2015,27(6):1140-1150. DOI:10.18307/2015.0620
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一种基于MODIS影像可业务化运行的巢湖水体叶绿素a估算算法
陶慜1,2, 段洪涛1, 齐琳1,2, 张玉超1, 马荣华1
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, 南京 210008;2.中国科学院大学, 北京 100049
摘要:
现有水色卫星主要是针对大洋清洁水体设计,内陆浑浊水体多数波段经常饱和;而发展可以业务化运行的内陆水体叶绿素a算法,为生产实践服务,一直是水色遥感的重点和难点之一. 利用2013年巢湖星地同步数据(N=55),通过经验正交函数(empirical orthogonal function,EOF)分析方法,选用MODIS唯一不饱和的4个波段(469、555、645、859 nm)数据进行分解,然后回归建模;并使用第三方独立的巢湖实测数据(N=40)进行验证(R2=0.63,URMSE=85.46%). 结果表明:该算法用于MODIS影像上,空间分布合理,季节差异明显,且在高悬浮物水体、不同气溶胶条件下均有很好的抗扰动性. 实践证明EOF算法可以应用于业务化运行的内陆水体叶绿素a浓度估算,并对其他水色参数反演具有一定的借鉴意义.
关键词:  业务化运行  叶绿素a  MODIS  经验正交函数  内陆水体  巢湖
DOI:10.18307/2015.0620
分类号:
基金项目:国家高技术研究发展计划”863”项目(2014AA06A509)和国家自然科学基金重点项目(41431176)联合资助.
An operational algorithm to estimate chlorophyll-a concentrations in Lake Chaohu from MODIS imagery
TAO Min1,2, DUAN Hongtao1, QI Lin1,2, ZHANG Yuchao1, MA Ronghua1
1.State Key Laboratory of Lake Science and Environment, 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:
Ocean color satellite is mainly designed for oceanic waters, but most of their bands are easily saturated in highly turbid waters. It's a great challenge to monitor water quality using satellites, because there are no operational algorithm to estimate chlorophyll-a concentration (Chl.a) in inland waters. In this paper, a novel approach based on the Empirical Orthogonal Function (EOF) analysis was developed using the spectral variance from the Rayleigh-corrected reflectance data (Rrc) at 469, 555, 645 and 859 nm, and Chl.a was estimated by considering the regression relationships between the spectral variance and 55 concurrent field measurements. The validation was then performed using independent data (N=40) from other laboratory, with R2=0.63, URMSE=85.46%. Application of the algorithm to MODIS images showed that spatial distribution patterns and seasonal changes are reasonable. Besides, this algorithm is immune to perturbations from thick aerosols and different sediments. Hence, we suggest that EOF algorithm could be applied to estimate Chl.a concentrations in inland waters.
Key words:  Operational algorithm  chlorophyll-a  MODIS  empirical orthogonal function  inland water  Lake Chaohu
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