基于OLCI数据的洱海叶绿素a浓度估算
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摘要
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±5.72μg/L,洱海中部水域Chl.a浓度最低(9.00~12.00μg/L),北部水域浓度最高(12.00~22.76μg/L),南部水域浓度稍高(12.00~14.00μg/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8.33μg/L.
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 ThreeBand 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 6 S,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±5.72μg/L with the lowest in the middle waters(9.00-12.00μg/L)and the highest in the northern waters(12.00-22.76μg/L).Although the Chl.a concentration of the southern waters(12.00-14.00μg/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 8.33μg/L due to the"River Plume"caused by rainfall.
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 ThreeBand 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 6 S,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±5.72μg/L with the lowest in the middle waters(9.00-12.00μg/L)and the highest in the northern waters(12.00-22.76μg/L).Although the Chl.a concentration of the southern waters(12.00-14.00μg/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 8.33μg/L due to the"River Plume"caused by rainfall.
引文
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[5]Gordon HR,Morel AY eds.Remote assessment of ocean color for interpretation of satellite visible imagery:A review.Springer Science&Business Media,2012.
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[10]Yacobi YZ,Moses WJ,Kaganovsky S et al.NIR-red reflectance-based algorithms for chlorophyll-a estimation in mesotrophic inland and coastal waters:Lake Kinneret case study.Water Research,2011,45(7):2428-2436.
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[13]Philpot WD.The derivative ratio algorithm:avoiding atmospheric effects in remote sensing.IEEE Transactions on Geoscience and Remote Sensing,1991,29(3):350-357.
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[16]Zhang FF,Zhang B,Li JS et al.Validation of a synthetic chlorophyll index for remote estimates of chlorophyll-a in a turbid hypereutrophic lake.International Journal of Remote Sensing,2014,35(1):289-305.
[17]Matthews MW,Bernard S,Robertson L.An algorithm for detecting trophic status(chlorophyll-a),cyanobacterial-dominance,surface scums and floating vegetation in inland and coastal waters.Remote Sensing of Environment,2012,124(124):637-652.
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[19]Gitelson AA,Dall'Olmo G,Moses W et al.A simple semi-analytical model for remote estimation of chlorophyll-a in turbid waters:Validation.Remote Sensing of Environment,2008,112(9):3582-3593.
[20]Xu JP,Zhang B,Song KS et al.Estimation of chlorophyll-a concentration in Lake Xinmiao base on a semi-analytical model.Journal of Infrared and Millimeter Waves,2008,27(3):197-201.[徐京萍,张柏,宋开山等.基于半分析模型的新庙泡叶绿素a浓度反演研究.红外与毫米波学报,2008,27(3):197-201.]
[21]Zhou GH,Liu QH,Ma RH et al.Inversion of chlorophyll-a concentration in turbid water of Lake Taihu based on optimized multi-spectral combination.J Lake Sci,2008,20(2):153-159.DOI:10.18307/2008.0203.[周冠华,柳钦火,马荣华等.基于半分析模型的波段最优化组合反演混浊太湖水体叶绿素a.湖泊科学,2008,20(2):153-159.]
[22]Le CF,Li YM,Zha Y et al.A four-band semi-analytical model for estimating chlorophyll a in highly turbid lakes:The case of Taihu Lake,China.Remote Sensing of Environment,2009,113(6):1175-1182.
[23]Yang W,Matsushita B,Chen J et al.An enhanced three-band index for estimating chlorophyll-a in turbid case-ii waters:Case studies of Lake Kasumigaura,Japan,and Lake Dianchi,China.Geoscience&Remote Sensing Letters IEEE,2010,7(4):655-659.
[24]Liu G,Li YM,Lv H et al.Remote sensing of chlorophyll-a concentrations in Lake Hongze using long time series MERISobservations.Environmental Science,2017,9:1-20.[刘阁,李云梅,吕恒等.基于MERIS影像的洪泽湖叶绿素a浓度时空变化规律分析.环境科学,2017,9:1-20.]
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