Multiple-constraint inversion of SCOPE.

Evaluating the potential of GPP and SIF for the retrieval of plant functional traits

Javier Pacheco-Labrador*, Oscar Perez-Priego, Tarek S. El-Madany, Tommaso Julitta, Micol Rossini, Jinhong Guan, Gerardo Moreno, Nuno Carvalhais, M. Pilar Martín, Rosario Gonzalez-Cascon, Olaf Kolle, Markus Reischtein, Christiaan van der Tol, Arnaud Carrara, David Martini, Tiana W. Hammer, Heiko Moossen, Mirco Migliavacca

*Corresponding author for this work

Research output: Contribution to journalArticle

7 Citations (Scopus)
17 Downloads (Pure)

Abstract

The most recent efforts to provide remote sensing (RS) estimates of plant function rely on the combination of Radiative Transfer Models (RTM) and Soil-Vegetation-Atmosphere Transfer (SVAT) models, such as the Soil-Canopy Observation Photosynthesis and Energy fluxes (SCOPE) model. In this work we used ground spectroradiometric and chamber-based CO2 flux measurements in a nutrient manipulated Mediterranean grassland in order to: 1) develop a multiple-constraint inversion approach of SCOPE able to retrieve vegetation biochemical, structural as well as key functional traits, such as chlorophyll concentration (Cab), leaf area index (LAI), maximum carboxylation rate (Vcmax) and the Ball-Berry sensitivity parameter (m); and 2) compare the potential of the of gross primary production (GPP) and sun-induced fluorescence (SIF), together with up-welling Thermal Infrared (TIR) radiance and optical reflectance factors (RF), to estimate such parameters. The performance of the proposed inversion method as well as of the different sets of constraints was assessed with contemporary measurements of water and heat fluxes and leaf nitrogen content, using pattern-oriented model evaluation. 

The multiple-constraint inversion approach proposed together with the combination of optical RF and diel GPP and TIR data provided reliable estimates of parameters, and improved predicted water and heat fluxes. The addition of SIF to this scheme slightly improved the estimation of m. Parameter estimates were coherent with the variability imposed by the fertilization and the seasonality of the grassland. Results revealed that fertilization had an impact on Vcmax, while no significant differences were found for m. The combination of RF, SIF and diel TIR data weakly constrained functional traits. Approaches not including GPP failed to estimate LAI; however GPP overestimated Cab in the dry period. These problems might be related to the presence of high fractions of senescent leaves in the grassland. The proposed inversion approach together with pattern-oriented model evaluation open new perspectives for the retrieval of plant functional traits relevant for land surface models, and can be utilized at various research sites where hyperspectral remote sensing imagery and eddy covariance flux measurements are simultaneously taken.

Original languageEnglish
Article number111362
Pages (from-to)1-23
Number of pages23
JournalRemote Sensing of Environment
Volume234
DOIs
Publication statusPublished - 1 Dec 2019

Bibliographical note

Copyright the Author(s) 2019. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

  • SCOPE inversion
  • Plant functional traits
  • Hyperspectral
  • GPP
  • SIF
  • Thermal
  • Nutrient availability
  • Mediterranean grassland

Fingerprint Dive into the research topics of 'Multiple-constraint inversion of SCOPE. Evaluating the potential of GPP and SIF for the retrieval of plant functional traits'. Together they form a unique fingerprint.

Cite this