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Coupled retrieval of aerosol optical thickness, columnar water vapor and surface reflectance maps from ENVISAT/MERIS data over land

机译:从陆地上的ENVISAT / MERIS数据中耦合获取气溶胶光学厚度,柱状水蒸气和表面反射率图

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摘要

An algorithm for the derivation of atmospheric parameters and surface reflectance data from MEdium Resolution Imaging Specrometer Instrument (MERIS) on board ENVIronmental SATellite (ENVISAT) images has been developed. Geo-rectified aerosol optical thickness (AOT), columnar water vapor (CWV) and spectral surface reflectance maps are generated from MERIS Level-1b data over land. The algorithm has been implemented so that AOT, CWV and reflectance products are provided on an operational manner, making no use of ancillary parameters apart from those attached to MERIS products. For this reason, it has been named Self-Contained Atmospheric Parameters Estimation from MERIS data (SCAPE-M). The fundamental basis of the algorithm and applicable error figures are presented in the first part of this paper. In particular, errors of +/- 0.03, +/- 4% and +/- 8% have been estimated for AOT, CWV and surface reflectance retrievals, respectively, by means of a sensitivity analysis based on a synthetic data set simulated under a usual MERIS scene configuration over land targets. The assumption of a fixed aerosol model, the coarse spatial resolution of the AOT product and the neglection of surface reflectance directional effects were also identified as limitations of SCAPE-M. Validation results are detailed in the second part of the paper. Comparison of SCAPE-M AOT retrievals with data from AErosol RObotic NETwork (AERONET) stations showed an average Root Mean Square Error (RMSE) of 0.05, and an average correlation coefficient R-2 of about 0.7-0.8. R-2 values grew up to more than 0.9 in the case of CWV after comparison with the same stations. A good correlation is also found with the MERIS Level-2 ESA CWV product. Retrieved surface reflectance maps have been successfully compared with reflectance data derived from the Compact High Resolution Imaging Spectrometer (CHRIS) on board the PRoject for On-Board Autonomy (PROBA) in the first place. Reflectance retrievals have also been compared with reflectance data derived from MERIS images by the Bremen AErosol Retrieval (BAER) method. A good correlation in the red and near-infrared bands was found, although a considerably higher proportion of pixels was successfully processed by SCAPE-M. (C) 2008 Elsevier Inc. All rights reserved.
机译:已经开发了一种从环境卫星图像(ENVISAT)图像上的中分辨率成像光谱仪(MERIS)导出大气参数和表面反射率数据的算法。地理校正的气溶胶光学厚度(AOT),柱状水蒸气(CWV)和光谱表面反射率图是根据陆地上的MERIS Level-1b数据生成的。该算法已实现,因此可以以可操作的方式提供AOT,CWV和反射率产品,除了附加到MERIS产品的参数外,不使用任何辅助参数。因此,已将其命名为根据MERIS数据(SCAPE-M)进行的自包含大气参数估计。本文的第一部分介绍了该算法的基本基础和适用的误差系数。尤其是,通过基于在ATM下模拟的合成数据集的灵敏度分析,已针对AOT,CWV和表面反射率检索分别估计了+/- 0.03,+ /-4%和+/- 8%的误差。通常在陆地目标上进行MERIS场景配置。固定气溶胶模型的假设,AOT产品的粗糙空间分辨率以及对表面反射率方向效应的忽视也被认为是SCAPE-M的局限性。验证结果将在本文的第二部分中详细介绍。将SCAPE-M AOT检索结果与AErosol机器人网络(AERONET)站的数据进行比较,发现平均均方根误差(RMSE)为0.05,平均相关系数R-2为0.7-0.8。与相同台站比较后,在CWV情况下,R-2值增长到0.9以上。还发现MERIS Level-2 ESA CWV产品具有良好的相关性。首先,已成功将获取的表面反射率图与从车载自动驾驶舱(PROBA)上的紧凑型高分辨率成像光谱仪(CHRIS)获得的反射率数据进行了比较。还通过不来梅AErosol检索(BAER)方法将反射率检索结果与从MERIS图像获得的反射率数据进行了比较。尽管在SCAPE-M中成功处理了相当大比例的像素,但在红色和近红外波段中发现了良好的相关性。 (C)2008 Elsevier Inc.保留所有权利。

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