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Illumination Geometry and Flying Height Influence Surface Reflectance and NDVI Derived from Multispectral UAS Imagery

1
School of GeoSciences, University of Edinburgh, Alexander Crum Brown Road, Edinburgh EH9 3FF, UK
2
Centre for Ecology and Hydrology, Bush Estate, Pencuik EH26 0QB, UK
*
Author to whom correspondence should be addressed.
Drones 2019, 3(3), 55; https://doi.org/10.3390/drones3030055
Received: 15 May 2019 / Revised: 2 July 2019 / Accepted: 2 July 2019 / Published: 8 July 2019
Small unmanned aerial systems (UAS) have allowed the mapping of vegetation at very high spatial resolution, but a lack of standardisation has led to uncertainties regarding data quality. For reflectance measurements and vegetation indices (Vis) to be comparable between sites and over time, careful flight planning and robust radiometric calibration procedures are required. Two sources of uncertainty that have received little attention until recently are illumination geometry and the effect of flying height. This study developed methods to quantify and visualise these effects in imagery from the Parrot Sequoia, a UAV-mounted multispectral sensor. Change in illumination geometry over one day (14 May 2018) had visible effects on both individual images and orthomosaics. Average near-infrared (NIR) reflectance and NDVI in regions of interest were slightly lower around solar noon, and the contrast between shadowed and well-illuminated areas increased over the day in all multispectral bands. Per-pixel differences in NDVI maps were spatially variable, and much larger than average differences in some areas. Results relating to flying height were inconclusive, though small increases in NIR reflectance with height were observed over a black sailcloth tarp. These results underline the need to consider illumination geometry when carrying out UAS vegetation surveys. View Full-Text
Keywords: remote sensing; data quality; multispectral imagery; NDVI; illumination geometry; anisotropic reflectance; radiometric calibration; UAV; Parrot Sequoia remote sensing; data quality; multispectral imagery; NDVI; illumination geometry; anisotropic reflectance; radiometric calibration; UAV; Parrot Sequoia
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Stow, D.; Nichol, C.J.; Wade, T.; Assmann, J.J.; Simpson, G.; Helfter, C. Illumination Geometry and Flying Height Influence Surface Reflectance and NDVI Derived from Multispectral UAS Imagery. Drones 2019, 3, 55.

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