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. 2020 Mar 17;20(6):1658.
doi: 10.3390/s20061658.

Aerial Imagery Based on Commercial Flights as Remote Sensing Platform

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Free PMC article

Aerial Imagery Based on Commercial Flights as Remote Sensing Platform

Toni Mastelic et al. Sensors (Basel). .
Free PMC article

Abstract

Remote sensing is commonly performed via airborne platforms such as satellites, specialized aircraft, and unmanned aerial systems (UASs), which perform airborne photography using mounted cameras. However, they are limited by their coverage (UASs), irregular flyover frequency (aircraft), and/or low spatial resolution (satellites) due to their high altitude. In this paper, we examine the utilization of commercial flights as an airborne platform for remote sensing. Namely, we simulate a situation where all aircraft on commercial flights are equipped with a mounted camera used for airborne photography. The simulation is used to estimate coverage, the temporal and spatial resolution of aerial imagery acquired this way, as well as the storage capacity required for storing all imagery data. The results show that Europe is 83.28 percent covered with an average of one aerial photography every half an hour and a ground sampling distance of 0.96 meters per pixel. Capturing such imagery results in 20 million images or four petabytes of image data per day. More detailed results are given in the paper for separate countries/territories in Europe, individual commercial airlines and alliances, as well as three different cameras.

Keywords: aerial imagery; commercial flights; land coverage; remote sensing; spatial; temporal.

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Visualization of all flight trajectories from the dataset (map tiles by ESRI, ArcGIS licensed under the ESRI Master License Agreement).
Figure 2
Figure 2
Field of view (FOV ) in relation to the angle of view (AOV) and aircraft altitude h.
Figure 3
Figure 3
Example of trajectory interpolation and field of view polygons for three aircraft (map tiles by Stamen Design, under CC BY 3.0. Data by OpenStreetMap, under Open Data Commons Open Database License).
Figure 4
Figure 4
Forward and lateral overlap in aerial imagery.
Figure 5
Figure 5
Area covered by the dataset.
Figure 6
Figure 6
Land coverage of the entirety of Europe by individual cameras.
Figure 7
Figure 7
Land coverage of European countries/territories by all flights with Imperx T9040.
Figure 8
Figure 8
Land coverage by all flights (background red) and individual alliances (monochrome bars) with Imperx T9040.
Figure 9
Figure 9
Land coverage by individual alliances with Imperx T9040.
Figure 10
Figure 10
Cumulative land coverage by individual airlines within alliances with Imperx T9040.
Figure 11
Figure 11
Cumulative land coverage by top 30 airlines with Imperx T9040.
Figure 12
Figure 12
Land coverage by number of airlines flying over with Imperx T9040.
Figure 13
Figure 13
Number of flyovers by all fights with Imperx T9040.
Figure 14
Figure 14
Temporal frequency (number of flyovers in a single day) for all flights using Imperx T9040.
Figure 15
Figure 15
Temporal frequency for individual alliances with Imperx T9040.
Figure 16
Figure 16
Spatial resolution expressed as GSD for individual countries/territories with the three cameras.
Figure 17
Figure 17
Spatial resolution expressed as average GSD for all flights with Imperx T9040.
Figure 18
Figure 18
Number of acquired images in a single day for the entirety of Europe from all flights.
Figure 19
Figure 19
Storage required for storing images for the entirety of Europe in a single day from all flights.
Figure 20
Figure 20
Storage required for storing aerial images taken from all flights with Imperx T9040.
Figure 21
Figure 21
Storage required for storing images for individual countries/territories with Imperx T9040.
Figure 22
Figure 22
Storage required for storing images of the entirety of Europe by individual alliances and airlines.
Figure 23
Figure 23
Global flight network (source: Wikimedia Commons, https://commons.wikimedia.org/wiki/File:World-airline-routemap-2009.png).
Figure 24
Figure 24
Cloud fractional cover (Source: Deutscher Wetterdienst, www.dwd.de).

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