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Reconciling satellite-derived atmospheric properties with fine-resolution land imagery: Insights for atmospheric correction

机译:将卫星衍生的大气特性与高分辨率的地面影像相协调:大气校正的见解

摘要

This paper investigates to what extent satellite measurements of atmospheric properties can be reconciled with fine-resolution land imagery, in order to improve the estimates of surface reflectance through physically based atmospheric correction. The analysis deals with mountainous area (Landsat scene of Peruvian Amazon/Andes, 72E and 13S), where the atmosphere is highly variable. Data from satellite sensors were used for characterization of the key atmospheric constituents: total water vapor (TWV), aerosol optical depth (AOD), and total ozone. Constituent time series revealed the season-dependent mean state of the atmosphere and its variability. Discrepancies between AOD from the Advanced Along-Track Scanning Radiometer (AATSR) and Moderate Resolution Imaging Spectroradiometer (MODIS) highlighted substantial uncertainty of atmospheric aerosol properties. The distribution of TWV and AOD over a Landsat scene was found to be exponentially related to ground elevation (mean R of 0.82 and 0.29, respectively). In consequence, the atmosphere-induced and seasonally varying bias of the top-of-atmosphere signal was also elevation dependent (e.g., mean Normalized Difference Vegetation Index bias at 500 m was 0.06 and at 4000 m was 0.01). We demonstrate that satellite measurements of key atmospheric constituents can be downscaled and gap filled with the proposed "background + anomalies" approach, to allow for a better compatibility with fine-resolution land surface imagery. Older images (i.e., predating the MODIS/ATSR era), without coincident atmospheric data, can be corrected using climatologies derived from time series of satellite retrievals. Averaging such climatologies over space compromises the quality of correction result to a much greater degree than averaging them over time. We conclude that the quality of both recent and older fine-resolution land surface imagery can be improved with satellite-based atmospheric data acquired to date. © 2011 by the American Geophysical Union.
机译:本文研究了在多大程度上可以将卫星大气测量结果与高分辨率的陆地图像相吻合,以便通过基于物理的大气校正来改进表面反射率的估算。该分析涉及山区(大气变化很大的山区)(秘鲁亚马逊河/安第斯山脉的Landsat景象,72E和13S)。来自卫星传感器的数据用于表征关键的大气成分:总水蒸气(TWV),气溶胶光学深度(AOD)和总臭氧。组成时间序列揭示了季节相关的大气平均状态及其变异性。高级沿轨扫描辐射计(AATSR)的AOD与中等分辨率成像光谱仪(MODIS)的AOD之间的差异突出表明了大气气溶胶特性的不确定性。发现在Landsat场景上TWV和AOD的分布与地面标高呈指数关系(平均R分别为0.82和0.29)。结果,大气引起的大气顶部信号的偏差和季节变化的偏差也与海拔有关(例如,在500 m处的平均归一化植被指数偏差为0.06,在4000 m处的平均值为0.01)。我们证明,可以缩小大气关键成分的卫星测量范围,并用建议的“背景+异常”方法填补空白,以便与高分辨率的地面图像更好地兼容。没有大气数据一致的较旧图像(即MODIS / ATSR时代之前的图像)可以使用从卫星检索的时间序列得出的气候来校正。在空间上对这些气候进行平均比在时间上对它们进行平均要严重得多,从而对校正结果的质量产生了较大的影响。我们得出的结论是,迄今为止,通过获取基于卫星的大气数据,可以提高近期和较早的高分辨率陆地表面图像的质量。 ©2011,美国地球物理联盟。

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