A method for operational calibration of AVHRR reflective time series data

We have developed an automatic method to monitor the AVHRR instrument sensitivity over time in the short-wave reflective channels to ensure that trends in the data series obtained by this instrument are real and not sensor artefacts. diometric calibration method uses the Multivariate Alteration Detection (MAD) algorithm to statistically select invariant features over land areas from multiple image-pairs that are compared to assess changes in the instrumentʹs calibration. This method requires no a priori regional knowledge and is globally applicable. A calibrated time series from Pseudo-Invariant Features located in central Australia are shown to have long-term trends removed. The resulting MAD-based calibration has a root mean squared error of ∼ 5–6% for both channels 1 and 2 and is in alignment with other approaches.