Processing historical NOAA AVHRR data with precise geometric correction

We published a new article in MDPI Remote Sensing journal on new method to accurately process time series of AVHRR Local Area Coverage (LAC) data. You can read the entire paper here:

We developed a new workflow which can read all the AVHRR LAC level 1B  data over all the NOAA satellites, calibrate them, applied clock drift corrections, geometrically correct them using automated feature matching technique called SIFT and finally applied split window technique to the thermal bands to derive lake surface water temperature as a case study. We found that the SIFT based geometric correction followed by gcp filter using m.gcp.filter addon in GRASS GIS 7 is very efficient in performing image to image corrections on thousands of images.

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