Aircraft Detection above Clouds by Sentinel-2 MSI Parallax

Abstract

Detection of aircrafts in satellite images is a challenging problem when the background is strongly reflective clouds with varying transparency. We develop a fast and effective detection algorithm that can find almost all aircrafts above and between clouds in Sentinel-2 multispectral images. It exploits the time delay of a few seconds between the recorded multispectral images such that a moving aircraft is observed at different positions due to parallax effects. The aircraft speed, heading and altitude are also calculated accurately. Analysing images over the English Channel during fall 2020, we obtain a detection accuracy of 80%, where the most of the remaining were covered by clouds. We also analyse images in the 1.38 μm water absorption band, where only 61% of the aircrafts are detected.

Detection of Moving Objects in Earth Observation Satellite Images

“…In some cases, the altitude-speed ambiguity can be resolved from information in the image itself. For example, if the direction of an object's motion can be determined, and the object is not moving parallel to the satellite's orbit, the object's apparent motion can be resolved into two components: the actual velocity of the object, and an apparent velocity due to the parallax created by the satellite motion (Heiselberg & Heiselberg 2021). The latter allows a determination of the object's altitude.…”

“…The effect is well known and analyzed in previous articles. This effect has been studied by Etaya et al (2004) and Easson et al (2010) with images from QuickBird satellites, and by Heiselberg (2019) and Heiselberg & Heiselberg (2021) with images from Sentinel-2 satellites.…”

“…For example, the Quickbird satellite imaged the same scene in black and white and color with an 0.2 s delay that allows detection of motion (Easson et al 2010). Heiselberg (2019); Heiselberg & Heiselberg (2021) used the same general technique adapted to images from the multispectral Sentinal-2 satellite. Here we restrict our study to the data taken by Planet Labs SuperDove satellites although our discussion is applicable more generally to satellites with similar imaging characteristics.…”

Detecting Moving Trucks on Roads Using Sentinel-2 Data

“…We suggest using passive optical Sentinel-2 remote sensing data for detecting moving trucks on roads. The presented method exploits a temporal sensing offset of the Sentinel-2 multispectral instrument (MSI) [51][52][53][54][55]. Sentinel-2 data has global coverage, a regular 5-daily revisit, and mission continuity [54,56].…”

“…The displacements among the bands 7, 8 and 8A are depicted by a Cloud Displacement Index, composed of the band ratios and their spatial variance. P. and H. Heiselberg [51,52] exploited the altitude parallax and the movement effect for detecting ships and airplanes and calculated their speed based on the band displacement. The object detection was achieved by statistical thresholds, differentiating the target pixels from the background.…”