Comparison of Gross Primary Productivity Derived from GIMMS NDVI3g, GIMMS, and MODIS in Southeast Asia

Junbang Wang,Xiangming Xiao,Takashi Hirano,W Smith,Mei Huang,Hiroaki Kondo,Warwick Harris,Jingwei Dong,Nobuko Saigusa,Guicai Li,Jiyuan Liu,Yunfen Liu,Steven Running

doi:10.3390/rs6032108

Abstract

Gross primary production (GPP) plays an important role in the net ecosystem exchange of CO2 between the atmosphere and terrestrial ecosystems. It is particularly important to monitor GPP in Southeast Asia because of increasing rates of tropical forest degradation and deforestation in the region in recent decades. The newly available, improved, third generation Normalized Difference Vegetation Index (NDVI3g) from the Global Inventory Modelling and Mapping Studies (GIMMS) group provides a long temporal dataset, from July 1981 to December 2011, for terrestrial carbon cycle and climate response research. However, GIMMS NDVI3g-based GPP estimates are not yet available. We applied the GLOPEM-CEVSA model, which integrates an ecosystem process model and a production efficiency model, to estimate GPP in Southeast Asia based on three independent results of the fraction of photosynthetically active radiation absorbed by vegetation (FPAR) from GIMMS NDVI3g (GPPNDVI3g), GIMMS NDVI1g (GPPNDVI1g), and the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD15A2 FPAR product (GPPMOD15). The GPP results were validated using ground data from eddy flux towers located in different forest biomes, and comparisons were made among the three GPPs as well as the MOD17A2 GPP products (GPPMOD17). Based on validation with flux tower derived GPP estimates the results show that GPPNDVI3g is more accurate than GPPNDVI1g and is comparable in accuracy with GPPMOD15. In addition, GPPNDVI3g and GPPMOD15 have good spatial-temporal consistency. Our results indicate that GIMMS NDVI3g is an effective dataset for regional GPP simulation in Southeast Asia, capable of accurately tracking the variation and trends in long-term terrestrial ecosystem GPP dynamics.

Highlights

Gross primary production (GPP) is an essential flux of the net ecosystem exchange (NEE) of CO2 between the atmosphere and terrestrial ecosystems, and contributes to human welfare by regulating ecosystem functions [1,2,3,4]
A main component of the GLObal Production Efficiency Model (GLOPEM)-CEVSA modeling framework is the satellite-derived fraction of photosynthetically active radiation absorbed by vegetation (FPAR), which can be derived from satellite normalized difference vegetation index (NDVI) data
According to an eight-day interval GPP analysis shown in Figures 3 and 4, the seasonal changes of the modeled GPPs (GPPNDVI3g, GPPNDVI1g, GPPMOD15 and GPPMOD17) were more correlative with the eddy covariance derived GPP (GPPOBS) in the subtropical forest site (QYZ) than in the tropical forest site (PDF)

Summary

Introduction

Gross primary production (GPP) is an essential flux of the net ecosystem exchange (NEE) of CO2 between the atmosphere and terrestrial ecosystems, and contributes to human welfare by regulating ecosystem functions [1,2,3,4]. The net carbon fluxes from eddy covariance towers can be partitioned into the components GPP and ecosystem respiration (RE), which can be used to validate products developed by biogeochemical models and remotely sensed vegetation indices [4,8]. Two main methods exist for deriving large-scale estimates of GPP [9,10,11]: (1) the application of process-based, biogeochemical models that scale-up and extrapolate site-specific measurements [12,13,14]; and (2) the application of satellite data based on the concept of light use efficiency [9,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]. An integrated strategy was presented that combined the remote sensing-based GLObal Production Efficiency Model (GLOPEM) and the ecosystem process-based model, the Carbon Exchange between Vegetation, Soil and Atmosphere model (CEVSA)

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Methods

Results

Discussion

Conclusion