Vermote Eric, Justice Chris, Claverie Martin, Franch Belen
NASA/GSFC Code 619, Greenbelt, MD, USA.
University of Maryland, Dept. of Geographical Sciences, College Park, MD, USA.
Remote Sens Environ. 2016 Apr 28;Volume 185(Iss 2):46-56. doi: 10.1016/j.rse.2016.04.008.
The surface reflectance, i.e., satellite derived top of atmosphere (TOA) reflectance corrected for the temporally, spatially and spectrally varying scattering and absorbing effects of atmospheric gases and aerosols, is needed to monitor the land surface reliably. For this reason, the surface reflectance, and not TOA reflectance, is used to generate the greater majority of global land products, for example, from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) sensors. Even if atmospheric effects are minimized by sensor design, atmospheric effects are still challenging to correct. In particular, the strong impact of aerosols in the Visible and Near Infrared spectral range can be difficult to correct, because they can be highly discrete in space and time (e.g., smoke plumes) and because of the complex scattering and absorbing properties of aerosols that vary spectrally and with aerosol size, shape, chemistry and density. This paper presents the Landsat 8 Operational Land Imager (OLI) atmospheric correction algorithm that has been developed using the Second Simulation of the Satellite Signal in the Solar Spectrum Vectorial (6SV) model, refined to take advantage of the narrow OLI spectral bands (compared to Thematic Mapper/Enhanced Thematic Mapper (TM/ETM+)), improved radiometric resolution and signal-to-noise. In addition, the algorithm uses the new OLI Coastal aerosol band (0.433-0.450μm), which is particularly helpful for retrieving aerosol properties, as it covers shorter wavelengths than the conventional Landsat, TM and ETM+ blue bands. A cloud and cloud shadow mask has also been developed using the "cirrus" band (1.360-1.390 μm) available on OLI, and the thermal infrared bands from the Thermal Infrared Sensor (TIRS) instrument. The performance of the surface reflectance product from OLI is analyzed over the Aerosol Robotic Network (AERONET) sites using accurate atmospheric correction (based on in situ measurements of the atmospheric properties), by comparison with the MODIS Bidirectional Reflectance Distribution Function (BRDF) adjusted surface reflectance product and by comparison of OLI derived broadband albedo from United States Surface Radiation Budget Network (US SURFRAD) measurements.
为了可靠地监测陆地表面，需要用到地表反射率，即经大气气体和气溶胶随时间、空间和光谱变化的散射与吸收效应校正后的卫星反演大气层顶（TOA）反射率。因此，在生成绝大多数全球陆地产品时，例如来自中分辨率成像光谱仪（MODIS）和可见红外成像辐射仪套件（VIIRS）传感器的数据，使用的是地表反射率而非TOA反射率。即便通过传感器设计将大气效应降至最低，大气效应的校正仍具有挑战性。特别是，气溶胶在可见光和近红外光谱范围内的强烈影响可能难以校正，这是因为它们在空间和时间上可能高度离散（例如烟羽），还因为气溶胶复杂的散射和吸收特性会随光谱以及气溶胶的大小、形状、化学组成和密度而变化。本文介绍了陆地卫星8号业务陆地成像仪（OLI）的大气校正算法，该算法是利用太阳光谱矢量中的卫星信号二次模拟（6SV）模型开发的，并进行了优化，以利用OLI窄光谱带（与专题制图仪/增强专题制图仪（TM/ETM+）相比）、改进的辐射分辨率和信噪比。此外，该算法使用了新的OLI海岸气溶胶波段（0.433 - 0.450μm），这对于反演气溶胶特性特别有帮助，因为它覆盖的波长比传统陆地卫星、TM和ETM+的蓝波段更短。还利用OLI上的“卷云”波段（1.360 - 1.390μm）以及热红外传感器（TIRS）仪器的热红外波段开发了云及云影掩膜。通过与基于大气特性现场测量的精确大气校正（在气溶胶机器人网络（AERONET）站点上）、与MODIS双向反射分布函数（BRDF）调整后的地表反射率产品进行比较，以及与美国地表辐射收支网络（US SURFRAD）测量得到的OLI反演宽带反照率进行比较，分析了OLI地表反射率产品的性能。
