Abstract Remote sensing data are most useful if they are available with sufficient precision, accuracy, spatiotemporal and spectral sampling, as well as continuity across decades. The Landsat and Sentinel series, as well other satellites are currently covering significant parts of this observational trade space. It can be expected that growing demands and budget constraints will require new capabilities in orbit that can address as many observables as possible with a single instrument. Recent optical performance improvements of imaging spectrometers make them true alternatives to traditional multispectral imagers. However, they are much more adaptable to a wide range of Earth observation needs due to the combination of continuous high spectral sampling with spatial sampling consistent with previous sensors (e.g., Landsat). Unfortunately, there is a knowledge gap in demonstrating that imaging spectroscopy data can substitute for multi-spectral data while sustaining the long-term record. Thus, the objective of this analysis is to test the hypothesis that imaging spectroscopy data compare radiometrically with multi-spectral data to within 5%. Using a coincident Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) flight with over-passing Operational Land Imager (OLI) data on Landsat 8, we document a procedure for simulating OLI multi-spectral bands from AVIRIS data, evaluate influencing factors on the observed radiance, and assess the difference in top-of-atmosphere radiance as compared to OLI. The procedure for simulating OLI data include spectral convolution, accounting for the minimal atmospheric effects between the two sensors, and spatial resampling. The remaining differences between the simulated and the real OLI data result mainly from differences in sensor calibration, surface bi-directional reflectance, and spatial sampling. The median relative radiometric difference for each band ranges from −8.3% to 0.6%. After bias-correction to minimize potential calibration discrepancies, we find no more than a 1.2% relative difference. This analysis therefore successfully demonstrates that imaging spectrometer data can contribute to Landsat-type or other multi-spectral data records. It also shows that cross-calibration from a spectrometer to a radiometer can be easily performed as a result of the imaging spectrometer high spectral sampling and its ability to recreate multi-spectral response functions.

中文翻译：

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成像光谱仪模拟 Landsat：机载可见红外成像光谱仪 (AVIRIS) 和操作陆地成像仪 (OLI) 数据的案例研究

摘要 如果遥感数据具有足够的精度、准确度、时空和光谱采样以及跨越数十年的连续性，则它们是最有用的。Landsat 和 Sentinel 系列以及其他卫星目前正在覆盖这一观测贸易空间的重要部分。可以预期，不断增长的需求和预算限制将需要新的轨道能力，这些能力可以用单个仪器处理尽可能多的可观测对象。最近成像光谱仪的光学性能改进使其成为传统多光谱成像仪的真正替代品。然而，由于连续高光谱采样与与先前传感器（例如 Landsat）一致的空间采样相结合，它们更能适应广泛的地球观测需求。很遗憾，在证明成像光谱数据可以替代多光谱数据同时保持长期记录方面存在知识差距。因此，该分析的目的是检验成像光谱数据与多光谱数据在辐射测量上的比较在 5% 以内的假设。使用重合机载可见光/红外成像光谱仪 (AVIRIS) 飞行以及 Landsat 8 上的超通操作陆地成像仪 (OLI) 数据，我们记录了从 AVIRIS 数据模拟 OLI 多光谱波段的程序，评估对观测辐射的影响因素，并评估与 OLI 相比的大气顶部辐射差异。模拟 OLI 数据的过程包括光谱卷积、考虑两个传感器之间的最小大气影响以及空间重采样。模拟和真实 OLI 数据之间的其余差异主要源于传感器校准、表面双向反射和空间采样的差异。每个波段的中位相对辐射差异范围从 -8.3% 到 0.6%。在进行偏差校正以最小化潜在校准差异后，我们发现相对差异不超过 1.2%。因此，该分析成功地证明了成像光谱仪数据可以有助于 Landsat 类型或其他多光谱数据记录。它还表明，由于成像光谱仪的高光谱采样及其重建多光谱响应函数的能力，可以轻松执行从光谱仪到辐射计的交叉校准。表面双向反射和空间采样。每个波段的中位相对辐射差异范围从 -8.3% 到 0.6%。在进行偏差校正以最小化潜在校准差异后，我们发现相对差异不超过 1.2%。因此，该分析成功地证明了成像光谱仪数据可以有助于 Landsat 类型或其他多光谱数据记录。它还表明，由于成像光谱仪的高光谱采样及其重建多光谱响应函数的能力，可以轻松执行从光谱仪到辐射计的交叉校准。表面双向反射和空间采样。每个波段的中位相对辐射差异范围从 -8.3% 到 0.6%。在进行偏差校正以最小化潜在校准差异后，我们发现相对差异不超过 1.2%。因此，该分析成功地证明了成像光谱仪数据可以有助于 Landsat 类型或其他多光谱数据记录。它还表明，由于成像光谱仪的高光谱采样及其重建多光谱响应函数的能力，可以轻松执行从光谱仪到辐射计的交叉校准。我们发现不超过 1.2% 的相对差异。因此，该分析成功地证明了成像光谱仪数据可以有助于 Landsat 类型或其他多光谱数据记录。它还表明，由于成像光谱仪的高光谱采样及其重建多光谱响应函数的能力，可以轻松执行从光谱仪到辐射计的交叉校准。我们发现不超过 1.2% 的相对差异。因此，该分析成功地证明了成像光谱仪数据可以有助于 Landsat 类型或其他多光谱数据记录。它还表明，由于成像光谱仪的高光谱采样及其重新创建多光谱响应函数的能力，可以轻松执行从光谱仪到辐射计的交叉校准。