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Retrieving BRDFs from UAV-based Radiometers for Fiducial Reference Measurements: Caveats and Recommendations
Sebastian Schunke, Vincent Leroy and Yves Govaerts
Frontiers in Remote Sensing, 2023
Paper | Publisher version | Cite
Abstract #
Surface Bidirectional reflectance distribution function (BRDF) is a key intrinsic geophysical variable depending only on the characteristics of the observed medium. It is therefore the most suitable measurand to support the definition of fiducial reference measurements (FRM). Field acquisition of surface reflectance data relies on substantial assumptions and simplifications, often without accounting for their impact. For example, the BRDF is a theoretical concept and can never be measured in the field. In contrast, the hemispherical conical reflectance factor (HCRF), which is the measurand obtained during field campaigns, is impacted by all scene elements and is not intrinsic to the surface. This study analyses the impact of four parameters (atmospheric scattering, measurement device field of view cropping, acquisition duration, non-Lambertian reference panels) on HCRF estimation. Simulations are performed on a 3D vegetation scene, using the new radiative transfer model Eradiate. It is found that among the aforementioned parameters, atmospheric scattering alone leads to a relative root-mean-square error (RRMSE) of more than 10% between HCRF and reference Bidirectional reflectance factor (BRF).
Citation #
Text
Schunke, Sebastian, Vincent Leroy, and Yves Govaerts. 2023. ‘Retrieving BRDFs from UAV-based Radiometers for Fiducial Reference Measurements: Caveats and Recommendations’. Frontiers in Remote Sensing 4. https://doi.org/10.3389/frsen.2023.1285800.
BibTeX
@article{Schunke2023RetrievingBRDFsUAVbased,
title = {Retrieving {{BRDFs}} from {{UAV-based}} Radiometers for Fiducial Reference Measurements: Caveats and Recommendations},
author = {Schunke, Sebastian and Leroy, Vincent and Govaerts, Yves},
year = {2023},
journal = {Frontiers in Remote Sensing},
volume = {4},
issn = {2673-6187},
doi = {10.3389/frsen.2023.1285800},
}