senSCOPE: Modeling mixed canopies combining green and brown senesced leaves. Evaluation in a Mediterranean Grassland

REMOTE SENSING OF ENVIRONMENT

卷:257

Article

Pacheco-Labrador, Javier¹  El-Madany, Tarek S.¹  van der Tol, Christiaan²  Pilar Martin, M.³  Gonzalez-Cascon, Rosario⁴  Perez-Priego, Oscar⁵  Guan, Jinhong⁶  Moreno, Gerardo⁷  Carrara, Arnaud⁸  Reichstein, Markus¹  Migliavacca, Mirco¹ 

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

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

[3] CSIC, Environm Remote Sensing & Spect Lab SpecLab, C Albasanz 26-28, Madrid 28037, Spain

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

[5] Macquarie Univ, Dept Biol Sci, 6 Wallys Walk, Macquarie Pk, NSW 2109, Australia

[6] Northwest A&F Univ, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Shaanxi, Peoples R China

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

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

关键词: senSCOPE;    SCOPE;    Radiative transfer;    Photosynthesis;    Sun-induced fluorescence;    Senesced leaves;    Grassland;    Chlorophyll;    Plant functional traits;    Hyperspectral;    GPP;   

DOI  :  10.1016/j.rse.2021.112352

来源: Elsevier

【 摘 要 】

The coupling of radiative transfer, energy balance, and photosynthesis models has brought new opportunities to characterize vegetation functional properties from space. However, these models do not accurately represent processes in ecosystems characterized by mixtures of green vegetation and senescent plant material (SPM), in particular grasslands. These inaccuracies limit the retrieval of vegetation biophysical and functional properties. Green and senesced plants feature contrasting spectral properties and carry out different functions that current coupled models do not represent separately. Besides, senescent pigments' absorption features change as SPM decomposes, and neither is this process well parameterized in radiative transfer models. This manuscript aims at overcoming these limitations. On the one hand, we have developed senSCOPE, a version of the Soil-Canopy Observation of Photosynthesis and Energy fluxes (SCOPE) that separately represents light interaction and physiology of green and senesced leaves. On the other, we have characterized new specific absorption coefficients of senescent pigments (K-s) from optical measurements of SPM from a Mediterranean grassland. Sensitivity analyses revealed that compared to SCOPE, senSCOPE 1) predicts variables that respond more linearly to the faction of green leaf area; and 2) keeps high levels of absorbed photosynthetically active radiation in the green leaves, which leads to significant differences in leaf photosynthesis, non-photochemical quenching, and transpiration. Moreover, we compared SCOPE vs. senSCOPE's capability to provide estimates of functional and biophysical parameters of vegetation. We assimilated different combinations of reflectance factors (R), chlorophyll sun-induced fluorescence radiance in the O-2-A band (F-760), gross primary production (GPP), and thermal radiance (L-t) measured in a Mediterranean grassland. Besides, we compared the role of three different sets of K-s coefficients in the inversion of senSCOPE, two estimated from SPM. The performance of the inversions was assessed using field data and a pattern-oriented model evaluation approach. Unlike SCOPE, senSCOPE provided unbiased estimates of chlorophyll content (C-ab) during the dry season. The use of SPM-specific K-s improved the representation of R in the near-infrared wavelengths; and, consequently, the estimation of leaf area index (LAI). Compared with field LAI, the coefficient of determination R-2 increased from similar to 0.4 to similar to 0.6, depending on the inversion constraints. Compared with SCOPE, the new model and coefficients together reduced the root mean squared error between observed and modeled R (similar to 40%), F-760 (similar to 30%), and GPP (similar to 5%). Both models failed to represent L-t; in this case, senSCOPE featured larger uncertainties. The modeling approach we propose improves the simulation and retrieval of vegetation properties and function in grasslands. Further work is needed to test the applicability of senSCOPE in different ecosystems, improve the simulation of the thermal spectral domain, and better characterize the optical parameters of SPM. To do so, new databases of SPM optical and biophysical properties should be produced.

【 授权许可】

Free