Abstract

Cross-calibration is a wildly used approach to radiometrically calibrate satellite sensors to meet uncertainty requirements. However, its accuracy is greatly influenced by bidirectional reflectance distribution function (BRDF) effects. To understand such influences, we analyzed the long-term BRDF characteristics of two commonly used cross-calibration targets (‘bright’ desert and ‘dark’ forest) using long-term (2002 – 2016) Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF products. BRDF characteristics derived by MODIS observations of both land cover types had 365-day cycles. Furthermore, both solar and sensor zenith angles showed more influence on BRDF than relative azimuth angles, and BRDF variations were approximately 10 times sensitive when solar or sensor zenith angles surpassed the boundary of 75°, which is therefore not recommended for selecting image pairs between target and reference satellite sensors for cross-calibration. Due to cloud cover, three prevailing interpolation methods (nearest, linear, and spline interpolation) were also assessed in their capacity to fill temporally missing BRDF products. Linear interpolation was preferred when valid MODIS scenes were more than two in five days, while nearest interpolation outperformed the other two methods for no more than two valid MODIS scenes in five days. In addition, BRDF look up tables (LUTs) were established for radiometrically cross-calibrating satellite sensors when BRDF products were unavailable. The LUTs were further validated with Landsat-8/Operational Land Imager (OLI) top of atmosphere (TOA) radiance simulated by the Second Simulation of the Satellite Signal in the Solar Spectrum model (6S) with BRDF effects corrected using the BRDF LUTs and MODIS BRDF products for typical geometries at two sites. High consistency was achieved with mean biases less than 0.3%, which suggests that BRDF LUTs could be used as alternatives when BRDF products are unavailable. These results provide guidelines to improve the accuracy of cross-calibration including image-matchup selecting criteria, efficient BRDF effect removal, and selection of potential calibration sites.

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