Cahalane, Conor and Walsh, Daire and Magee, Aidan and Mannion, Sean and Lewis, Paul and McCarthy, Tim
(2017)
Sensor Pods: Multi-Resolution Surveys from
a Light Aircraft.
Interventions, 2 (1).
ISSN 2411-5134
Abstract
Airborne remote sensing, whether performed from conventional aerial survey platforms
such as light aircraft or the more recent Remotely Piloted Airborne Systems (RPAS) has the ability
to compliment mapping generated using earth-orbiting satellites, particularly for areas that may
experience prolonged cloud cover. Traditional aerial platforms are costly but capture spectral
resolution imagery over large areas. RPAS are relatively low-cost, and provide very-high resolution
imagery but this is limited to small areas. We believe that we are the first group to retrofit these new,
low-cost, lightweight sensors in a traditional aircraft. Unlike RPAS surveys which have a limited
payload, this is the first time that a method has been designed to operate four distinct RPAS sensors
simultaneously—hyperspectral, thermal, hyper, RGB, video. This means that imagery covering a
broad range of the spectrum captured during a single survey, through different imaging capture
techniques (frame, pushbroom, video) can be applied to investigate different multiple aspects of
the surrounding environment such as, soil moisture, vegetation vitality, topography or drainage,
etc. In this paper, we present the initial results validating our innovative hybrid system adapting
dedicated RPAS sensors for a light aircraft sensor pod, thereby providing the benefits of both
methodologies. Simultaneous image capture with a Nikon D800E SLR and a series of dedicated
RPAS sensors, including a FLIR thermal imager, a four-band multispectral camera and a 100-band
hyperspectral imager was enabled by integration in a single sensor pod operating from a Cessna c172.
However, to enable accurate sensor fusion for image analysis, each sensor must first be combined in
a common vehicle coordinate system and a method for triggering, time-stamping and calculating
the position/pose of each sensor at the time of image capture devised. Initial tests were carried
out over agricultural regions with geometric tests designed to assess the spatial accuracy of the
fused imagery in terms of its absolute and relative accuracy. The results demonstrate that by using
our innovative system, images captured simultaneously by the four sensors could be geometrically
corrected successfully and then co-registered and fused exhibiting a root-mean-square error (RMSE)
of approximately 10m independent of inertial measurements and ground control.
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