Comparison of gross primary productivity derived from GIMMS NDVI3g, GIMMS, and MODIS in Southeast Asia

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

Research output: Contribution to journalArticlepeer-review

71 Scopus citations

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.

Original languageEnglish
Pages (from-to)2108-2133
Number of pages26
JournalRemote Sensing
Volume6
Issue number3
DOIs
StatePublished - 2014

Funding

FundersFunder number
Japan Society for the Promotion of Science23310015, 24241008

    Keywords

    • GIMMS NDVI1g
    • GIMMS NDVI3g
    • GLOPEM-CEVSA
    • Gross Primary Productivity (GPP)
    • MOD15A2
    • MOD17A2
    • Southeast Asia

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