基于改进气溶胶模型的内陆及近岸水体水色遥感大气校正算法及应用

卫星遥感监测技术为湖泊水环境及其长时序变化过程的有效评估提供了海量观测数据，能有效弥补常规监测方法的缺陷，以提高湖泊水环境监测的范围和准确度，是实现湖泊大范围可持续发展的关键技术。然而，由于卫星总信号中可反映水体特征的有效信号占比较低，大多数为大气辐射信号的干扰，严重限制了内陆湖泊水环境遥感监测应用。因此，提高水体定量化遥感监测的精度需要从根本上提高从传感器信号中提取水体有效信息的精度，即提高大气校正精度。水色遥感大气校正，即大气程辐射信号的剔除，是实现一切水色参数定量化反演及水环境监测的基础前提。其基本思路为消除大气中的吸收、散射效应和水体表面反射信号，主要包括大气分子的吸收和散射、大气气溶胶的吸收和散射、以及水体表面镜面反射等。

由于内陆区域水体和水体上空大气受人类活动影响，具有水体光学特征复杂，水体上空大气光学特征动态变化强等特点，因此将海洋水色遥感大气校正算法应用于内陆水体时精度较低，其中现有标准气溶胶模型无法准确表征内陆区域大气气溶胶状况也是导致大气校正精度低的关键。因此需要在研究内陆气溶胶分布特征的基础上，对内陆水体大气校正算法进行优化。

基于上述问题，本文提出一种适用于内陆和近岸水体的大气校正算法，ACLANC（Atmospheric Correction algorithm for inLand And Nearshore Coastal waters）。该算法利用水体附近陆地表面的插值后气溶胶光学厚度（aerosol optical depth，AOD）数据作为直接输入参数，同时通过6SV辐射传输模型（Second Simulation of the Satellite Signal in the Solar Spectrum-Vector）中大陆型气溶胶模型以及SeaDAS（SeaWiFS Data Analysis System）软件中近似气溶胶模型（即r85f20模型）以模拟气溶胶散射反射率。经全球实测光谱数据验证表明，ACLANC算法在MODIS传感器可见光波段遥感反射率（remote sensing reflectance，R_rs）与实测数据具有较好的一致性，平均R²为0.77±0.09，无偏百分比误差为28.7±9.8%。ACLANC算法在R_rs校正精度以及数据覆盖范围方面表现均优于现有的大气校正算法，该算法可有效提高R_rs产品的精度。算法不确定度模拟分析结果表明，ACLANC算法误差主要源于气溶胶光学厚度产品，占算法总误差的50%以上，且该误差随AOD的减小逐步增加。在浑浊气溶胶环境下，气溶胶模型对算法误差的贡献高达50%，其中SeaDAS软件固定气溶胶模型贡献约30%的误差。

考虑内陆和近岸水域大气校正时使用标准气溶胶模型导致结果具有较大不确定性的问题，利用全球内陆区域1475个AERONET（Aerosol Robotic Network）站点的实测气溶胶数据，分析内陆区域气溶胶光学特性的空间和季节特征，刻画内陆区域气溶胶时空分布状况，以构建基于地理网格的全球内陆气溶胶模型。本文将全球划分为5°×5°地理网格，利用AERONET气溶胶数据月尺度均值，构建网格化气溶胶模型，共3207个，覆盖全球310个地理网格。同时，本文为所有气溶胶模型建立了相关的气溶胶查找表，并将其应用于大气校正算法。经星地同步数据验证，结果表明使用新气溶胶模型可以大大提高大气校正R_rs的精度。在此基础上，建立基于改进气溶胶模型的适用于内陆水体水色遥感应用的精确大气校正算法。

在上述基于改进气溶胶模型的大气校正算法基础上，考虑不同类型水体光学特征的差异，利用全球野外实测光谱数据和准分析算法构建适用于大范围不同类型水体的半解析水体透明度估算模型。经实测水体透明度数据验证，该反演模型的绝对平均误差为23.6%。基于精确大气校正R_rs获取全国2003-2020年湖库水体透明度时空分布。分析结果表明，全国湖库水体透明度的空间分布状况为西高东低，在2003-2020年之间，全国湖库水体透明度总体呈现显著上升的趋势（Z>0，p<0.05），尤其是在2012年之后，水体透明度上升趋势增加。此外，2015年全国湖库水体透明度的异常突增是由于青藏高原中部区域湖泊水体透明度异常现象所致。该异常现象是受2015年强厄尔尼诺控制的湖泊水动力系统变化的表征。

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