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

Remote Sensing

Junbang Wang⁷  Jingwei Dong³  Jiyuan Liu⁷  Mei Huang⁷  Guicai Li⁴  Steven W. Running⁸  W. Kolby Smith⁸  Warwick Harris¹  Nobuko Saigusa⁵  Hiroaki Kondo⁶  Yunfen Liu⁷  Takashi Hirano² 

[1] Landcare Research, P.O. Box 69040, Lincoln 7640, New Zealand; E-Mail:;Research Faculty of Agriculture, Hokkaido University, Sapporo 060-8589, Japan; E-Mail:;Department of Microbiology and Plant Biology, and Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA; E-Mail:;National Satellite Meteorological Center, China Meteorological Administration, Beijing 100101, China; E-Mail:;Center for Global Environmental Research, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba Ibaraki 305-8506, Japan; E-Mail:;Research Institute for Environmental Management Technology, National Institute of Advanced Industrial Science and Technology, 16-1 Onogawa, Tsukuba 305-8569, Japan; E-Mail:;Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; E-Mails:;Numerical Terradynamic Simulation Group, College of Forestry and Conservation, University of Montana, 32 Campus Drive, Missoula, MT 59812, USA; E-Mails:

关键词: Gross Primary Productivity (GPP);    GIMMS NDVI3g;    GLOPEM-CEVSA;    GIMMS NDVI1g;    MOD15A2;    MOD17A2;    Southeast Asia;   

DOI  :  10.3390/rs6032108

来源: mdpi

【 摘 要 】

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 (GPP_NDVI3g), GIMMS NDVI1g (GPP_NDVI1g), and the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD15A2 FPAR product (GPP_MOD15). 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 (GPP_MOD17). Based on validation with flux tower derived GPP estimates the results show that GPP_NDVI3g is more accurate than GPP_NDVI1g and is comparable in accuracy with GPP_MOD15. In addition, GPP_NDVI3g and GPP_MOD15 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.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland