首页> 外文会议>IEEE International Geoscience and Remote Sensing Symposium >A synergistic approach to atmospheric correction of NEON's airborne hyperspectral data utilizing airborne solar spectral flux radiometers, ground based radiometers, and airborne hyperspectral imagers
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A synergistic approach to atmospheric correction of NEON's airborne hyperspectral data utilizing airborne solar spectral flux radiometers, ground based radiometers, and airborne hyperspectral imagers

机译:利用机载太阳能光谱通量辐射尺,基于辐射尺寸的辐射尺寸的霓虹空中高光谱数据的大气校正协同方法

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A wide variety of critical information regarding bioclimate, biodiversity, and biogeochemistry is embedded in airborne hyperspectral imagery. Most, if not all of the primary signal relies upon first deriving the surface reflectance of land cover and vegetation from measured hyperspectral radiance. This places stringent requirements on terrain, and atmospheric correction algorithms to accurately derive surface reflectance properties. An observatory designed to measure bioclimate, biodiversity, and biogeochemistry variables from surface reflectance must take great care in developing an approach which chooses algorithms with the highest accuracy, along with providing those algorithms with data necessary to describe the physical mechanisms that affect the measured at sensor radiance. Such an approach is in development with the Airborne Observation Platform (AOP) part of the National Ecological Observatory Network (NEON). NEON is a continental-scale ecological observation platform designed to collect and disseminate data to enable the understanding and forecasting of the impacts of climate change, land use change, and invasive species on ecology [1].
机译:关于生物气候,生物多样性和生物地球化学的各种关键信息嵌入了空气中的高光谱图像中。大多数情况下,如果不是所有主要信号依赖于首次导出陆地覆盖的表面反射和从测量的超光线辐射的植被。这对地形和大气校正算法有严格的要求,以准确地推出表面反射性能。从表面反射率测量生物气候,生物多样性和生物地球化学变量的天文台必须非常注意开发一种选择具有最高精度的算法的方法,以及提供那些具有所需数据的算法来描述影响在传感器上测量的物理机制所需的数据辐射。这种方法正在开发与国家生态天文台网络(霓虹灯)的空中观察平台(AOP)的开发。霓虹灯是一个大陆级生态观察平台,旨在收集和传播数据,以实现气候变化,土地利用变化和生态物种对生态学的影响的理解和预测[1]。

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