Multiple-constraint inversion of SCOPE. Evaluating the potential of GPP and SIF for the retrieval of plant functional traits

REMOTE SENSING OF ENVIRONMENT

卷:234

Article

Pacheco-Labrador, Javier¹  Perez-Priego, Oscar^1,9  El-Madany, Tarek S.¹  Julitta, Tommaso²  Rossini, Micol³  Guan, Jinhong¹  Moreno, Gerardo⁴  Carvalhais, Nuno¹  Pilar Martin, M.⁵  Gonzalez-Cascon, Rosario⁶  Kolle, Olaf¹  Reischtein, Markus¹  van der Tol, Christiaan⁷  Carrara, Arnaud⁸  Martini, David¹  Hammer, Tiana W.¹  Moossen, Heiko¹  Migliavacca, Mirco¹ 

[1] Max Planck Inst Biogeochem, Hans Knoll Str 10, D-07745 Jena, Germany

[2] JB Hyperspectral Devices UG, Bot Garten 33, D-40225 Dusseldorf, Germany

[3] Univ Milano Bicocca, Remote Sensing Environm Dynam Lab, Dept Earth & Environm Sci DISAT, Piazza Sci 1, I-20126 Milan, Italy

[4] INDEHESA Univ Extremadura, Forest Res Grp, Plasencia 10600, Spain

[5] CSIC, Spanish Natl Res Council, Environm Remote Sensing & Spect Lab, SpecLab,IEGD,CCHS, C Albasanz 26-28, Madrid 28037, Spain

[6] Natl Inst Agr & Food Res & Technol, INIA, Dept Environm, Km 7,5, Madrid 28040, Spain

[7] Univ Twente, Fac Geoinformat Sci & Earth Observat, ITC, POB 217, NL-7500 AE Enschede, Netherlands

[8] Fdn Ctr Estudios Ambientales Mediterraneo, CEAM, Charles Darwin 14,Parc Tecnol, Paterna 46980, Spain

[9] Macquarie Univ, Dept Biol Sci, Balaclava Rd, Macquarie Pk, NSW 2109, Australia

关键词: SCOPE inversion;    Plant functional traits;    Hyperspectral;    GPP;    SIF;    Thermal;    Nutrient availability;    Mediterranean grassland;   

DOI  :  10.1016/j.rse.2019.111362

来源: Elsevier

【 摘 要 】

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 spectro-radiometric 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 (C-ab), leaf area index (LAI), maximum carboxylation rate (V-cmax) 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 V-cmax while no significant differences were found for m. The combination of RF, SIF and die] TIR data weakly constrained functional traits. Approaches not including GPP failed to estimate LAI; however GPP overestimated C-ab, 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.

【 授权许可】

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