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Variability and uncertainty challenges in scaling imaging spectroscopy retrievals and validations from leaves up to vegetation canopies

Citation

Malenovsky, Z and Homolova, L and Lukes, P and Buddenbaum, H and Verrelst, J and Alonso, L and Schaepman, ME and Lauret, N and Gastellu-Etchegorry, J-P, Variability and uncertainty challenges in scaling imaging spectroscopy retrievals and validations from leaves up to vegetation canopies, Surveys in Geophysics, 40, (3) pp. 631-656. ISSN 0169-3298 (2019) [Refereed Article]

Copyright Statement

Copyright 2019 Springer Nature B.V.

DOI: doi:10.1007/s10712-019-09534-y

Abstract

Imaging spectroscopy of vegetation requires methods for scaling and generalizing optical signals that are reflected, transmitted and emitted in the solar wavelength domain from single leaves and observed at the level of canopies by proximal sensing, airborne and satellite spectroradiometers. The upscaling embedded in imaging spectroscopy retrievals and validations of plant biochemical and structural traits is challenged by natural variability and measurement uncertainties. Sources of the leaf-to-canopy upscaling variability and uncertainties are reviewed with respect to: (1) implementation of retrieval algorithms and (2) their parameterization and validation of quantitative products through in situ field measurements. The challenges are outlined and discussed for empirical and physical leaf and canopy radiative transfer modelling components, considering both forward and inverse modes. Discussion on optical remote sensing validation schemes includes also description of a multiscale validation concept and its advantages. Impacts of intraspecific and interspecific variability on collected field and laboratory measurements of leaf biochemical traits and optical properties are demonstrated for selected plant species, and field measurement uncertainty sources are listed and discussed specifically for foliar pigments and canopy leaf area index. The review concludes with the main findings and suggestions as how to reduce uncertainties and include variability in scaling vegetation imaging spectroscopy signals and functional traits of single leaves up to observations of whole canopies.

Item Details

Item Type:Refereed Article
Keywords:quantitative remote sensing, imaging spectroscopy, retrieval of vegetation traits, radiative transfer models, inversion, variability, uncertainty, scaling, multiscale validation
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 Biological Sciences
UTAS Author:Malenovsky, Z (Dr Zbynek Malenovsky)
ID Code:132790
Year Published:2019
Funding Support:Australian Research Council (FT160100477)
Deposited By:Geography and Spatial Science
Deposited On:2019-05-20
Last Modified:2019-06-07
Downloads:0

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