Automated selection of suitable atmospheric calibration sites for satellite imagery

Ground calibration targets (GCTs) play a vital role in atmospheric correction of satellite sensor data in the optical region, but selecting suitable targets is a subjective and timeconsuming task. This paper describes a method to automatically select suitable GCTs, using a combination of remotely sensed multispectral and topographic data. Desirable characteristics for GCTs sites were identified from the literature, and used to devise a semi-automated workflow based on programs written in IDL combined with routines offered by ITTVIS ENVI and Definiens eCognition. Spatial statistics were used to assess local patterns of spatial uniformity, and endmember abundances (extracted using the SMACC algorithm) were used in a novel method to ensure a spread of calibration sites throughout the brightness range for each band. The result of this process was a map of candidate GCTs, classified according to their suitability.