Title:
Framework for Multi-Asset Comparison and Rapid Down-selection for Earth Observation Missions
Framework for Multi-Asset Comparison and Rapid Down-selection for Earth Observation Missions
Author(s)
Gilleron, Jerome
Muehlberg, Marc
Payan, Alexia P.
Choi, Youngjun
Briceno, Simon
Mavris, Dimitri N.
Muehlberg, Marc
Payan, Alexia P.
Choi, Youngjun
Briceno, Simon
Mavris, Dimitri N.
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Abstract
Observing the Earth, whether it be from space or from the air, has become easier in recent
years with the advent of new space-borne and airborne technologies. First, satellites constantly
provide data about almost any point on the globe with varying resolutions and in various
spectral bands. Second,Unmanned Aerial Vehicles (UAV) are becoming more readily accessible
to the public and may be rapidly deployed to take high resolution images of ground features or
areas of interest. Third, manned aircraft may be used to image large areas of land at a higher
resolution than satellites and have been used regularly in disaster monitoring and surveillance
missions. However, when multiple heterogeneous assets compete to perform a given aerial
imaging mission, deciding which asset is better suited and/or less costly to operate in a timely
manner is challenging. Every acquisition mode is different, resolution values are computed
differently and there currently does not exist a common framework to compare UAV, manned
aircraft and satellites. To address this challenge, this paper describes a methodology to rapidly
compare various types of aerial assets (such as UAVs and manned aircraft) and space assets
(such as satellites) to decide which one would be better able to perform an Earth observation
mission depending on a set of requirements. To demonstrate the proposed methodology, this
paper executes numerical simulations with three different representative scenarii in California.
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Date Issued
2019
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Paper