Fiducial reference measurements for vegetation bio-geophysical variables: an end-to-end uncertainty evaluation framework

Brown, LA ORCID: https://orcid.org/0000-0003-4807-9056, Camacho, F, Garcia-Santos, V, Origo, N, Fuster, B, Morris, H, Pastor-Guzman, J, Sanchez-Zaparo, J, Morrone, R, Ryder, J, Nightingale, J, Boccia, V and Dash, J 2021, 'Fiducial reference measurements for vegetation bio-geophysical variables: an end-to-end uncertainty evaluation framework' , Remote Sensing, 13 (16) .

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Abstract

With a wide range of satellite-derived vegetation bio-geophysical products now available to users, validation efforts are required to assess their accuracy and fitness for purpose. Substantial progress in the validation of such products has been made over the last two decades, but quantification of the uncertainties associated with in situ reference measurements is rarely performed, and the incorporation of uncertainties within upscaling procedures is cursory at best. Since current validation practices assume that reference data represent the truth, our ability to reliably demonstrate compliance with product uncertainty requirements through conformity testing is limited. The Fiducial Reference Measurements for Vegetation (FRM4VEG) project, initiated by the European Space Agency, is aiming to address this challenge by applying metrological principles to vegetation and surface reflectance product validation. Following FRM principles, and in accordance with the International Standards Organisation’s (ISO) Guide to the Expression of Uncertainty in Measurement (GUM), for the first time, we describe an end-to-end uncertainty evaluation framework for reference data of two key vegetation bio-geophysical variables: the fraction of absorbed photosynthetically active radiation (FAPAR) and canopy chlorophyll content (CCC). The process involves quantifying the uncertainties associated with individual in situ reference measurements and incorporating these uncertainties within the upscaling procedure (as well as those associated with the high-spatial-resolution imagery used for upscaling). The framework was demonstrated in two field campaigns covering agricultural crops (Las Tiesas–Barrax, Spain) and deciduous broadleaf forest (Wytham Woods, UK). Providing high-spatial-resolution reference maps with per-pixel uncertainty estimates, the framework is applicable to a range of other bio-geophysical variables including leaf area index (LAI), the fraction of vegetation cover (FCOVER), and canopy water content (CWC). The proposed procedures will facilitate conformity testing of moderate spatial resolution vegetation bio-geophysical products in future validation exercises.

Item Type: Article
Schools: Schools > School of Computing, Science and Engineering
Journal or Publication Title: Remote Sensing
Publisher: MDPI
ISSN: 2072-4292
Funders: European Space Agency
Depositing User: LA Brown
Date Deposited: 28 Oct 2022 10:13
Last Modified: 28 Oct 2022 10:15
URI: https://usir.salford.ac.uk/id/eprint/65376

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