Development of a spectral error model for surface bidirectional reflectance factor (BRF) retrieval

The calibration and validation (cal/val) of remote sensing data is an essential step in the development of reproducible remote sensing data products. A key element of the cal/val procedure is the atmospheric correction of the at-altitude imagery (apparent at-sensor bidirectional reflectance factor (BRF)) to achieve intrinsic reflectance properties of the surface (surface BRF). This requires a standard procedure for the estimation of surface BRF retrieval errors. We present here the fundamental concepts necessary for the development of a spectral surface BRF error model that we hope could eventually serve as a confidence indicator in any operational atmospheric correction system.