Charles Darwin University

CDU eSpace
Institutional Repository

CDU Staff and Student only

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

Ma, Xuanlong, Huete, Alfredo, Yu, Qiang, Restrepo-Coupe, Natalia, Beringer, Jason, Hutley, Lindsay B., Kanniah, Kasturi Devi, Cleverly, James and Eamus, Derek (2014). Parameterization of an ecosystem light-use-efficiency model for predicting savanna GPP using MODIS EVI. Remote Sensing of Environment: an interdisciplinary journal,154:253-271.

Document type: Journal Article
Citation counts:
Google Scholar Search Google Scholar

IRMA ID 84376995xPUB120
Title Parameterization of an ecosystem light-use-efficiency model for predicting savanna GPP using MODIS EVI
Author Ma, Xuanlong
Huete, Alfredo
Yu, Qiang
Restrepo-Coupe, Natalia
Beringer, Jason
Hutley, Lindsay B.
Kanniah, Kasturi Devi
Cleverly, James
Eamus, Derek
Journal Name Remote Sensing of Environment: an interdisciplinary journal
Publication Date 2014
Volume Number 154
ISSN 0034-4257   (check CDU catalogue open catalogue search in new window)
Scopus ID 2-s2.0-84923314090
Start Page 253
End Page 271
Total Pages 19
Place of Publication United States
Publisher Elsevier Inc.
HERDC Category C1 - Journal Article (DIISR)
Abstract 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 (GPPEC) 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 GPPEC well at both site- and cross-site levels (R2 = 0.84). The EVI relationship with GPPEC 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 (PARTOC) or top-of-atmosphere incident PAR (PARTOA) were parameterized and investigated. GPP predicted using the eLUE models correlated well with GPPEC, with R2 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 PARTOC and PARTOA, respectively, and were significantly improved compared to the MOD17 GPP product (R2 = 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 GPPEC and MODIS satellite product relationships, resulting in a consistent estimation of GPP across phenophases. The eLUE 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.

Keywords Remote Sensing
Ecosystem Function
Carbon Cycle
Gross Primary Production
DOI   (check subscription with CDU E-Gateway service for CDU Staff and Students  check subscription with CDU E-Gateway in new window)
Version Filter Type
Access Statistics: 101 Abstract Views  -  Detailed Statistics
Created: Wed, 19 Aug 2015, 12:26:25 CST