Opt Express. 2023 Apr 10;31(8):12756-12777. doi: 10.1364/OE.481861.
Cross-calibration methods are widely used in high-precision remote sensor calibrations and ensure observational consistency between sensors. Because two sensors must be observed under the same or similar conditions, the cross-calibration frequency is greatly reduced; performing cross-calibrations on Aqua/Terra MODIS, Sentinel-2A/Sentinel-2B MSI and other similar sensors is difficult due to synchronous-observation limitations. Additionally, few studies have cross-calibrated water-vapor-observation bands sensitive to atmospheric changes. In recent years, standard automated observation sites and unified processing technology networks, such as an Automated Radiative Calibration Network (RadCalNet) and an automated vicarious calibration system (AVCS), have provided automatic observation data and means for independently, continuously monitoring sensors, thus offering new cross-calibration references and bridges. We propose an AVCS-based cross-calibration method. By limiting the observational-condition differences when two remote sensors transit over wide temporal ranges through AVCS observation data, we improve the cross-calibration opportunity. Thereby, cross-calibrations and observation consistency evaluations between the abovementioned instruments are realized. The influence of AVCS-measurement uncertainties on the cross-calibration is analyzed. The consistency between the MODIS cross-calibration and sensor observation is within 3% (5% in SWIR bands); that for the MSI is within 1% (2.2% in the water-vapor-observation band); and for the cross-calibration of Aqua MODIS and the two MSI, the consistency between the cross-calibration-predicted TOA reflectance and the sensor-measured TOA reflectance was within 3.8%. Thus, the absolute AVCS-measurement uncertainty is also reduced, especially in the water-vapor-observation band. This method can be applied to cross-calibrations and measurement consistency evaluations of other remote sensors. Later, the spectral-difference influences on cross-calibrations will be further studied.
交叉校准方法被广泛应用于高精度遥感传感器校准中，以确保传感器之间的观测一致性。由于两个传感器必须在相同或相似的条件下进行观测，因此交叉校准的频率大大降低；由于同步观测的限制，对 Aqua/Terra MODIS、Sentinel-2A/Sentinel-2B MSI 等类似传感器进行交叉校准较为困难。此外，很少有研究对敏感大气变化的水汽观测波段进行交叉校准。近年来，标准自动化观测站点和统一处理技术网络，如自动辐射校准网络（RadCalNet）和自动化替代校准系统（AVCS），为自动观测数据和独立、连续监测传感器提供了手段，从而为交叉校准提供了新的参考和桥梁。我们提出了一种基于 AVCS 的交叉校准方法。通过限制两个远程传感器在宽时间范围内通过 AVCS 观测数据过境时的观测条件差异，我们提高了交叉校准的机会。从而实现了上述仪器之间的交叉校准和观测一致性评估。分析了 AVCS 测量不确定性对交叉校准的影响。MODIS 交叉校准与传感器观测之间的一致性在 3%以内（SWIR 波段内为 5%）；MSI 之间的一致性在 1%以内（水汽观测波段内为 2.2%）；对于 Aqua MODIS 和两个 MSI 的交叉校准，交叉校准预测的 TOA 反射率与传感器测量的 TOA 反射率之间的一致性在 3.8%以内。因此，绝对 AVCS 测量不确定性也降低了，特别是在水汽观测波段。该方法可应用于其他遥感传感器的交叉校准和测量一致性评估。之后，将进一步研究光谱差异对交叉校准的影响。
