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首页> 外文期刊>Sensors >Simultaneous Measurements of Chlorophyll Concentration by Lidar, Fluorometry, above-Water Radiometry, and Ocean Color MODIS Images in the Southwestern Atlantic
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Simultaneous Measurements of Chlorophyll Concentration by Lidar, Fluorometry, above-Water Radiometry, and Ocean Color MODIS Images in the Southwestern Atlantic

机译:利用激光雷达,荧光法,水上放射线法和西南大西洋的海洋颜色MODIS图像同时测量叶绿素浓度

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Comparisons between in situ measurements of surface chlorophyll-a concentration (CHL) and ocean color remote sensing estimates were conducted during an oceanographic cruise on the Brazilian Southeastern continental shelf and slope, Southwestern South Atlantic. In situ values were based on fluorometry, above-water radiometry and lidar fluorosensor. Three empirical algorithms were used to estimate CHL from radiometric measurements: Ocean Chlorophyll 3 bands (OC3MRAD), Ocean Chlorophyll 4 bands (OC4v4RAD), and Ocean Chlorophyll 2 bands (OC2v4RAD). The satellite estimates of CHL were derived from data collected by the MODerate-resolution Imaging Spectroradiometer (MODIS) with a nominal 1.1 km resolution at nadir. Three algorithms were used to estimate chlorophyll concentrations from MODIS data: one empirical - OC3MSAT, and two semi-analytical - Garver, Siegel, Maritorena version 01 (GSM01SAT), and CarderSAT. In the present work, MODIS, lidar and in situ above-water radiometry and fluorometry are briefly described and the estimated values of chlorophyll retrieved by these techniques are compared. The chlorophyll concentration in the study area was in the range 0.01 to 0.2 mg/m3. In general, the empirical algorithms applied to the in situ radiometric and satellite data showed a tendency to overestimate CHL with a mean difference between estimated and measured values of as much as 0.17 mg/m3 (OC2v4RAD). The semi-analytical GSM01 algorithm applied to MODIS data performed better (rmse 0.28, rmse-L 0.08, mean diff. -0.01 mg/m3) than the Carder and the empirical OC3M algorithms (rmse 1.14 and 0.36, rmse-L 0.34 and 0.11, mean diff. 0.17 and 0.02 mg/m3, respectively). We find that rmsd values between MODIS relative to the in situ radiometric measurements are < 26%, i.e., there is a trend towards overestimation of RRS by MODIS for the stations considered in this work. Other authors have already reported over and under estimation of MODIS remotely sensed reflectance due to several errors in the bio-optical algorithm performance, in the satellite sensor calibration, and in the atmospheric-correction algorithm.
机译:在巴西东南部大陆架和西南大西洋西南部陆坡进行海洋航行时,对表面叶绿素a浓度(CHL)和海洋颜色遥感估计值的原位测量进行了比较。原位值基于荧光测定法,水上辐射测定法和激光雷达荧光传感器。三种经验算法用于通过辐射测量来估计CHL:海洋叶绿素3条带(OC3M RAD ),海洋叶绿素4条带(OC4v4 RAD )和海洋叶绿素2条带( OC2v4 RAD )。 CHL的卫星估算值是从中等分辨率成像光谱仪(MODIS)在最低点标称分辨率为1.1 km的数据中得出的。根据MODIS数据,使用三种算法估算叶绿素浓度:一种是经验模型-OC3M SAT ,另外两种是半分析模型-Garver,Siegel和Maritorena版本01(GSM01 SAT ),和Carder SAT 。在本工作中,简要描述了MODIS,激光雷达以及原位水上放射线法和荧光法,并比较了通过这些技术回收的叶绿素的估计值。研究区域的叶绿素浓度范围为0.01至0.2 mg / m 3 。通常,应用于原位辐射和卫星数据的经验算法显示出高估CHL的趋势,估计值和测量值之间的平均差高达0.17 mg / m 3 (OC2v4 RAD )。与Carder和经验性OC3M算法(均方根1.14和均方根)相比,应用于MODIS数据的半解析GSM01算法表现更好(均方根0.28,均方根-L 0.08,平均差异-0.01 mg / m 3 )。分别为0.36,rmse-L 0.34和0.11,平均衍射分别为0.17和0.02 mg / m 3 。我们发现,相对于原位辐射测量,MODIS之间的rmsd值<26%,即,对于本工作中所考虑的站点,MODIS倾向于高估R RS 。其他作者已经报告了由于生物光学算法性能,卫星传感器校准以及大气校正算法中的一些错误而导致的MODIS遥感反射率的高估和低估。

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