Parameterization of an ecosystem light-use-efficiency model for predicting savanna GPP using MODIS EVI

REMOTE SENSING OF ENVIRONMENT

卷:154

Article

Ma, Xuanlong^1,2  Huete, Alfredo²  Yu, Qiang^2,3  Restrepo-Coupe, Natalia²  Beringer, Jason⁴  Hutley, Lindsay B.⁵  Kanniah, Kasturi Devi⁶  Cleverly, James^2,7  Eamus, Derek^2,7,8 

[1] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China

[2] Univ Technol Sydney, Plant Funct Biol & Climate Change Cluster C3, Broadway, NSW 2007, Australia

[3] Univ Chinese Acad Sci, Beijing 100049, Peoples R China

[4] Monash Univ, Sch Geog & Environm Sci, Melbourne, Vic 3800, Australia

[5] Charles Darwin Univ, Res Inst Environm & Livelihoods, Casuarina, NT 0909, Australia

[6] Univ Teknol Malaysia, Fac Geoinformat & Real Estate, Dept Geoinformat, Skudai 81310, Kagawa, Malaysia

[7] Univ Technol Sydney, Australian Supersite Network, Terr Ecosyst Res Network, Sydney, NSW 2007, Australia

[8] Univ Technol Sydney, Natl Ctr Groundwater Res & Training, Sydney, NSW 2007, Australia

关键词: Remote Sensing;    Ecosystem Function;    Carbon Cycle;    Photosynthesis;    Phenology;    Gross Primary Production;   

DOI  :  10.1016/j.rse.2014.08.025

来源: Elsevier

【 摘 要 】

Accurate estimation of carbon fluxes across space and time is of great importance for quantifying global carbon balances. Current production efficiency models for calculation of gross primary production (GPP) depend on estimates of light-use-efficiency (LUE) obtained from look-up tables based on biome type and coarse-resolution meteorological inputs that can introduce uncertainties. Plant function is especially difficult to parameterize in the savanna biome due to the presence of varying mixtures of multiple plant functional types (PFTs) with distinct phenologies and responses to environmental factors. The objective of this study was to find a simple and robust method to accurately up-scale savanna GPP from local, eddy covariance (EC) flux tower GPP measures to regional scales utilizing entirely remote sensing oservations. Here we assessed seasonal patterns of Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation products with seasonal EC tower GPP (GPP(EC)) at four sites along an ecological rainfall gradient (the North Australian Tropical Transect, NATT) encompassing tropical wet to dry savannas. The enhanced vegetation index (EVI) tracked the seasonal variations of GPP(EC) well at both site- and cross-site levels (R-2 = 0.84). The EVI relationship with GPP(EC) was further strengthened through coupling with ecosystem light-use-efficiency (eLUE), defined as the ratio of GPP to photosynthetically active radiation (PAR). Two savanna landscape eLUE models, driven by top-of-canopy incident PAR (PAR(TOC)) or top-of-atmosphere incident PAR (PAR(TOA)) were parameterized and investigated. GPP predicted using the eLUE models correlated well with GPP(EC), with R-2 of 0.85 (RMSE = 0.76 g C m(-2) d(-1)) and 0.88 (RMSE = 0.70 g C m(-2) d(-1)) for PAR(TOC) and PAR(TOA), respectively, and were significantly improved compared to the MOD17 GPP product (R-2 = 0.58, RMSE = 1.43 g C m(-2) d(-1)). The eLUE model also minimized the seasonal hysteresis observed between green-up and brown-down in CPPEC and MODIS satellite product relationships, resulting in a consistent estimation of GPP across phenophases. The eWE model effectively integrated the effects of variations in canopy photosynthetic capacity and environmental stress on photosynthesis, thus simplifying the up-scaling of carbon fluxes from tower to regional scale. The results from this study demonstrated that region-wide savanna GPP can be accurately estimated entirely with remote sensing observations without dependency on coarse-resolution ground meteorology or estimation of light-use-efficiency parameters. (C) 2014 Elsevier Inc. All rights reserved.

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