Unmanned aircraft system (UAS)-mounted spectroradiometers offer a new capability to measure spectral reflectance and solar-induced chlorophyll fluorescence at detailed canopy scales. This capability offers potential for upscaling and comparison with airborne and space-borne observations [e.g., the upcoming European Space Agency (ESA) Fluorescence Explorer (FLEX) satellite mission]. In this respect, the accurate spatial characterization and georeferencing of the UAS acquisition footprints are essential to unravel the origin and spatial variability of optical signals acquired within the extent of airborne/satellite pixels. In this article, we present and validate a novel algorithm to georeference the footprint extent of a nonimaging spectroradiometer mounted on a multirotor UAS platform. We used information about the spectroradiometer position and orientation during flight and about topography of observed terrain to calculate the footprint geolocation. In a recursive process, the field of view (FOV) of the spectroradiometer projected on the ground. Multiple FOV ground projections retrieved during a spectroradiometer reading (i.e., a single integration time) were aggregated to calculate the footprint extent. The spatial accuracy of the footprint geolocation was validated by applying the georeferencing algorithm on checkpoint pixels of image acquired with a comounted digital camera. Geolocations of the checkpoint pixels, which served as a proxy for the spectroradiometer footprint, were successfully compared with surveyed ground checkpoints. Finally, the spectral and radiometric quality of UAS-Acquired reflectance signatures was compared with ground-measured reflectance of four natural targets (three different types of grass and a bare soil), and a strong agreement was observed.

Item Type:	Refereed Article
Keywords:	aerial spectroscopy, footprint, geolocation, geo- referencing, spectroradiometer, unmanned aerial vehicle (UAV), unmanned aircraft system (UAS)
Research Division:	Engineering
Research Group:	Geomatic engineering
Research Field:	Photogrammetry and remote sensing
Objective Division:	Expanding Knowledge
Objective Group:	Expanding knowledge
Objective Field:	Expanding knowledge in the environmental sciences
UTAS Author:	Lucieer, A (Professor Arko Lucieer)
UTAS Author:	Bendig, J (Ms Juliane Bendig)
UTAS Author:	Malenovsky, Z (Dr Zbynek Malenovsky)
ID Code:	139216
Year Published:	2020
Funding Support:	Australian Research Council (FT160100477)
Web of Science® Times Cited:	12
Deposited By:	Geography and Spatial Science
Deposited On:	2020-06-01
Last Modified:	2021-09-01
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