Dayglow removal from FUV auroral images

Abstract

Aurora study is a key area in understanding the connection and interaction of the solar-terrestrial system. Auroral events are monitored on the global scale at the Far Ultraviolet (FUV) spectrum by satellite-based sensors. However, the existence of dayglow emission significantly limits scientists is the ability to determine the location and the size of auroral ovals. A dynamic methodology to remove day airglow emission from the LBHL band UVI images on the Polar satellite is presented in this paper. First, the methodology identifies the geomagnetic latitude bound of the night side auroral oval. Then, the maximum range of geomagnetic latitude bound of the auroral is inferred based on the domain knowledge. Using the non-auroral dayglow pixels, a multi-variable regression fit of the intensity as function of the cosine of the solar zenith angle and cosine of the satellite viewing zenith angle is obtained. The methodology then uses this fitting function to estimate the dayglow intensity and to remove its effect in the LBHL band FUV images. This methodology does not require an external source of input solar flux and the dayglow removal is solely based on individual images. Experiment results show that dayglow effect is removed significantly from the original LBHL FUV images.Using this methodology, the performance of auroral oval detection algorithms is significantly improved.

The semiannual variation of transpolar arc incidence and its relationship to the Russell–McPherron effect

“…We exclude the time periods from statistics whenever the aurora image is incomplete, missing, or fuzzy, and we cannot thus be certain that a TPA has occurred. Dayglow strongly affects the polar imaging in both hemispheres, so during these times we use the auroral images in which the contamination caused by dayglow has been reduced using an image processing technique (Li X et al, 2004). Figure 1 shows typical examples of auroral ovals and TPA events.…”

The Auroral Planetary Imaging and Spectroscopy (APIS) service

“…The uncertainty of the model background in the auroral regions was estimated for Saturn to be less than 10%, and less for Uranus. For the sake of completeness, we also tested an alternate numerical background model, developed for FUV auroral images in the case of the Earth and based on the sum of the cosines of the observation and solar zenith angles [12]. This did not provide background models of higher accuracy though.…”

Background removal from global auroral images: Data-driven dayglow modeling

“…Reistad et al (2013Reistad et al ( , 2014Reistad et al ( , 2016 followed a similar approach but binned the intensities in each pixel by to account for the viewing geometry and used the binned median instead of the mean. Li X et al (2004) fitted the function to Polar UVI images, and Laundal and Østgaard (2009) and Laundal et al (2010b) fitted a two-dimensional polynomial to IMAGE and Polar FUV images while ignoring emissions from auroral latitudes. The background intensity has also been determined regionally by dividing images in circular sectors around the magnetic pole and then fitting a Gaussian/double Gaussian (intended to represent the aurora) plus a second-order polynomial (non-aurora) to the latitudinal intensity profiles to find the boundaries of the oval (Carbary et al, 2003;Laundal et al, 2010a;Longden et al, 2010).…”