Evaluation of ocean chlorophyll-a remote sensing algorithms using in situ fluorescence data in Southern Brazilian Coastal Waters

IF 1 4区 地球科学 Q3 MARINE & FRESHWATER BIOLOGY Ocean and Coastal Research Pub Date : 2021-04-23 DOI:10.1590/2675-2824069.20-014gsdms
Gabriel Serrato de Mendonça Silva, C. Garcia
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引用次数: 5

Abstract

Abstract A performance evaluation of ocean color chlorophyll-a algorithms was conducted based on the in situ fluorescence chlorophyll concentration (Fchl) measured by a sensor on the buoy SiMCosta-SC01 in coastal waters of South Brazil. The operational algorithms are used in MODIS and VIIRS sensors to derive satellite chlorophyll concentration (Csat). Fchl values were successfully corrected for nonphotochemical quenching (NPQ) by an interpolation of sunrise and sunset daily measurements. A laboratory-derived calibration coefficient was applied to convert the unquenching Fchl values into chlorophyll concentration (Cflu). Overall, linear regression analysis between Cflu and Csat for both sensors showed good results, with the coefficient of determination (R2) varying between 0.88 and 0.96, slopes between 0.92 and 1.02 and intercepts between -0.17 and 0.13. The MODIS algorithm (R2 = 0.96, slope = 1.02, RMSE = 0.16 mg m-3, BIAS = 0.16 mg m-3, for N = 222 and time interval ±1 h) presented slightly better performance than VIIRS (R2 = 0.92, slope = 0.96, RMSE = 0.25 mg m-3, BIAS = -0.25 mg m-3, for N = 284 and time interval ±1 h). These results represent the most comprehensive satellite data analysis for this region, suggesting that the approach may be applicable to other SiMCosta buoys.
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利用巴西南部沿海水域原位荧光数据的海洋叶绿素遥感算法评估
摘要基于巴西南部沿海水域SiMCosta-SC01浮标上的传感器测量的原位荧光叶绿素浓度(Fchl),对海洋颜色叶绿素A算法进行了性能评估。该运算算法用于MODIS和VIIRS传感器,以推导卫星叶绿素浓度(Csat)。Fchl值通过日出和日落每日测量值的插值成功地校正了非光化学猝灭(NPQ)。应用实验室推导的校准系数将未抑制的Fchl值转换为叶绿素浓度(Cflu)。总体而言,两种传感器的Cflu和Csat之间的线性回归分析显示出良好的结果,确定系数(R2)在0.88和0.96之间变化,斜率在0.92和1.02之间,截距在-0.17和0.13之间。MODIS算法(R2=0.96,斜率=1.02,RMSE=0.16 mg m-3,BIAS=0.16 mg m-1,对于N=222,时间间隔±1 h)的性能略好于VIIRS(R2=0.92,斜率=0.96,RMSE=0.025 mg m-3;对于N=284,时间间隔?h)。这些结果代表了该地区最全面的卫星数据分析,表明该方法可能适用于其他SiMCosta浮标。
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1.60
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12.50%
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21
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