Samenvatting

A program that automatically detects auroral events in all-sky images taken by the all-sky camera of IRF has been written. Current programs that automatically detect the aurora in all-sky images using the RGB color system often miss strong aurora and sometimes interprets clouds as aurora. To improve the detection of aurora in all-sky images, filtering in the HSL colorspace has been investigated in this thesis. The aurora in the images have been detected in three different strengths. The first filter has soft requirements and is able to detect faint aurora, but also captures noise. The second filter is capturing most aurora except in cloudy days, where the last filter has a good accuracy on finding aurora with a minimum amount of noise in every situation. The program also determines the strength of the aurora by taking the strongest part and classifying the aurora as regular or strong aurora. If an event is identified as strong aurora, the UT of occurring will be saved in an event list after double checking with eye identification.

The strong aurora events are used to examine a possible correlation between infrasound and aurora, what was reported at Fairbanks in Alaska but not confirmed. This thesis investigates if there is a correlation between the strong aurora events captured by the IRF all-sky camera and the data of the infrasound array at the same location. No correlation has yet been found with the currently available infrasound data. This could mean that the strength of the aurora is not a sufficient parameter to find the type of aurora that generates infrasound at the ground. Also have the auroral infrasonic waves detected in Alaska been measured with an infrasound array that was sensitive to lower frequencies than the array used in Kiruna.