%0 Journal Article %T 基于OLCI数据的洱海叶绿素a浓度估算 %T Estimation of chlorophyll-a concentration in Lake Erhai based on OLCI data %A 毕顺 %A 李云梅 %A 吕恒 %A 朱利 %A 牟蒙 %A 雷少华 %A 徐杰 %A 温爽 %A 丁潇蕾 %A BI,Shun %A LI,Yunmei %A LV,Heng %A ZHU,Li %A MU,Meng %A LEI,Shaohua %A XU,Jie %A WEN,Shuang %A DING,Xiaolei %J 湖泊科学 %J Journal of Lake Sciences %@ 1003-5427 %V 30 %N 3 %D 2018 %P 701-712 %K 叶绿素a;洱海;海陆颜色仪(OLCI);富营养化 %K Chlorophyll-a;Lake Erhai;ocean and land colour instrument (OLCI);eutrophication %X 海陆颜色仪(OLCI)是搭载在Sentinel-3上的新型水色遥感传感器,其对于内陆清洁水体水质遥感监测的适用性有待验证.本研究以评价水体富营养化程度的重要参数叶绿素a(Chl.a)浓度为指标,以高原湖泊洱海为研究区,基于2017年4月19日共20个星地同步实验数据,建立了3种可应用于OLCI数据的Chl.a浓度遥感估算模型(波段比值模型、三波段模型以及FLH模型),并估算了当日洱海Chl.a浓度的空间分布.结果表明:(1)选用波段Oa8(665 nm)、Oa11(708.75 nm)和Oa12(753.75 nm)构建的三波段模型最适用于洱海水域的Chl.a浓度估算,其平均绝对误差百分比为12.37%,低于波段比值模型的16.04%和FLH模型的13.50%;(2)对OLCI使用的大气校正方法中,基于去瑞利散射的暗像元法对估算模型的适用性要优于6S、FLAASH以及QUAC方法;(3)洱海OLCI影像中近岸水体受邻近效应影响严重,近红外波段Oa12(753.75 nm)受陆地邻近效应影响的距离为1~2个像元,而Oa8(665 nm)、Oa10(681.25 nm)和Oa11(708.75 nm)波段为1个像元;(4)2017年4月19日全湖Chl.a浓度均值为12.15±5.72 μg/L,洱海中部水域Chl.a浓度最低(9.00~12.00 μg/L),北部水域浓度最高(12.00~22.76 μg/L),南部水域浓度稍高(12.00~14.00 μg/L),阳南溪与波罗江入湖口受降雨径流的影响出现"羽流现象",导致Chl.a浓度偏低,约为8.33 μg/L. %X Ocean and land colour instrument(OLCI) is a new ocean colour remote sensor mounted on Sentinel-3, and its applicability to water quality monitoring of inland clean water is to be verified. Chlorophyll-a (Chl.a) concentration is an important water quality parameter for measuring the eutrophication of Lake Erhai. Based on the in-situ samples taken from April 19, 2017, the performance of three Chl.a estimation models (including Band-Ratio Model, Three-Band Model and FLH Model) was evaluated in this study and the spatial distribution of Chl.a concentrations in Lake Erhai was estimated. The results showed that:(1) The Three-Band Model by Oa8, Oa11 and Oa12 was most suitable for the estimation of Chl.a concentration in Lake Erhai, the mean absolute percent error was 12.37%, lower than the Band-Ratio Model(16.04%) and FLH Model(13.50%); (2) Among atmospheric correction methods for OLCI, the application of the dark pixel method based on the rayleigh-scattering correction was better than that of the 6S, FLAASH and QUAC methods; (3) The near shore water pixels in the OLCI image of Lake Erhai were affected seriously by the land adjacency effect, and the distance of the land adjacency effect at the near-infrared band (Oa12) was 1~2 pixels while the Oa8, Oa10 and Oa11 bands were 1 pixel; (4) On April 19, 2017, the average Chl.a concentration of the whole Lake Erhai was 12.15±5.72 μg/L with the lowest in the middle waters (9.00-12.00 μg/L) and the highest in the northern waters (12.00-22.76 μg/L). Although the Chl.a concentration of the southern waters (12.00-14.00 μg/L) was a little higher than that of the middle waters, the lowest concentration in the estuary of the Yangnan River and the Boluo River was around 8.33 μg/L due to the "River Plume" caused by rainfall. %R 10.18307/2018.0312 %U http://www.jlakes.org/ch/reader/view_abstract.aspx %1 JIS Version 3.0.0