Publications

Zhao, F; Xia, L; Kylling, A; Shang, H; Yang, P (2022). Mapping global flying aircraft activities using Landsat 8 and cloud computing. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 184, 19-30.

Abstract
Satellite-based remote sensing might provide a potential way for monitoring the global flight activities and their environment impacts, while the remote sensing community pays less attention on it. In this study, we presented a flying aircraft detection algorithm which effectively handles the noise on Landsat 8 OLI cirrus band caused by energetic particles in the South Atlantic Anomaly region, and a new framework based on cloud infrastructure was proposed to map global flying aircraft activities from 2013 to 2020 using Landsat 8 Operational Land Imager (OLI) data. Validation was performed for 254 scenes recorded for various cloudy and surface conditions and vapor contents. The overall percentages of false alarms and omissions for these validation images were 5.37% and 7.80%, respectively. Limited to the resolution of Landsat data, cloud, the size and flight altitude of the aircraft, 42.99% flying aircraft were undetected compared with the FlightRadar24. Instead of using the Google Earth Engine, we employed more flexible cloud computing techniques, Google Cloud Storage and Google Calculation Engine, to construct our framework for the larger volume data. A total of 1.94 million Landsat images were analyzed to obtain the activities maps, and the results showed that globally flying aircraft increased by 25.85% from 2014 to 2019 (the year 2013 was excluded for the low coverage of Landsat scenes), with an annual rate of 4.31%. In 2020, flying aircraft were reduced by 40% compared with 2019 due to the influence of COVID-19 and traveling restrictions, and Europe was the most severely affected by COVID-19, with an 84.59% decline of flying aircraft in April 2020. This study provides a unique long-term supplement to monitor aviation activities and their climate impact.

DOI:
10.1016/j.isprsjprs.2021.12.003

ISSN:
1872-8235