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Derivation of Calibration Coefficients for OCM-2 Sensor for Coastal Waters

机译:沿海水域OCM-2传感器校准系数的推导

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The radiometric calibration coefficients that are required to enhance the preflight calibration coefficients to improve the performance of the Ocean Colour Monitor (OCM-2) onboard the Indian Remote Sensing Satellite (IRS) are determined using in-situ measurements in coastal waters around southern India. These coefficients were applied to OCM-2 data acquired over coastal waters off Point Calimere (Palk Strait) and Gulf of Mannar of the Bay of Bengal, and are compared with similar coefficients included in the SeaDAS software and those provided by the Space Application Centre (SAC). Two atmospheric correction algorithms were used in conjunction with these coefficients to obtain the water-leaving radiances (Lw) from OCM-2 data, namely the CAAS algorithm and SeaDAS algorithm. An evaluation of the results of these coefficients and atmospheric correction algorithms showed large deviations in Lw values derived with the SAC (positive deviation) coefficients and SeaDAS (negative deviation) coefficients when applied to OCM-2 data along with the SeaDAS atmospheric correction algorithm. The deviations were less remarkable with new coefficients when the same (SeaDAS) atmospheric correction algorithm was used. However, application all three coefficients to OCM-2 using the CAAS algorithm showed a similar trend but with less deviations with respect to in-situ Lw data. The results obtained with the new coefficients showed good agreement with the in-situ water-leaving radiances (except channels 412-443nm). These results suggest that the new calibration coefficients can be used along with the CAAS atmospheric correction algorithm to improve the performance of OCM-2 sensor for quantitative assessments of the various water constituents in coastal waters (including bloom) around India.
机译:使用印度南部附近沿海水域的原位测量确定增强飞行前校准系数以改善印度洋遥感卫星(IRS)上的海洋色彩监控器(OCM-2)性能所需的辐射校准系数。这些系数适用于在比尔卡利米尔角(Palk Strait)和孟加拉湾Mannar湾沿海水域采集的OCM-2数据,并与SeaDAS软件和空间应用中心提供的相似系数进行了比较( SAC)。结合这些系数使用了两种大气校正算法,以从OCM-2数据获得出水辐射率(Lw),即CAAS算法和SeaDAS算法。对这些系数和大气校正算法的结果进行的评估显示,当与SeaDAS大气校正算法一起应用于OCM-2数据时,由SAC(正偏差)系数和SeaDAS(负偏差)系数得出的Lw值存在较大偏差。当使用相同的(SeaDAS)大气校正算法时,新系数的偏差不太明显。但是,使用CAAS算法将这三个系数应用于OCM-2均显示出相似的趋势,但相对于原位Lw数据的偏差较小。使用新系数获得的结果显示与原位放水辐射度(通道412-443nm除外)吻合良好。这些结果表明,可以将新的校准系数与CAAS大气校正算法一起使用,以提高OCM-2传感器的性能,以定量评估印度周围沿海水域(包括水华)的各种水成分。

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