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, William K Smith, Warwick Harris, Nobuko Saigusa, Hiroaki Kondo, Yunfen Liu, Takashi Hirano, Xiangming Xiao

Research output: Contribution to journalArticle

34 Citations (Scopus)

Abstract

Gross primary production (GPP) plays an important role in the net ecosystem exchange of CO 2 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 GPPNDVI1g 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.

Original languageEnglish (US)
Pages (from-to)2108-2133
Number of pages26
JournalRemote Sensing
Volume6
Issue number3
DOIs
StatePublished - Jan 1 2014

Fingerprint

MODIS
primary production
productivity
modeling
comparison
Southeast Asia
terrestrial ecosystem
net ecosystem exchange
photosynthetically active radiation
biome
carbon cycle
NDVI
tropical forest
deforestation
eddy

Keywords

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

Cite this

Wang, J., Dong, J., Liu, J., Huang, M., Li, G., Running, S. W., ... Xiao, X. (2014). Comparison of gross primary productivity derived from GIMMS NDVI3g, GIMMS, and MODIS in Southeast Asia. Remote Sensing, 6(3), 2108-2133. https://doi.org/10.3390/rs6032108

Comparison of gross primary productivity derived from GIMMS NDVI3g, GIMMS, and MODIS in Southeast Asia. / Wang, Junbang; Dong, Jingwei; Liu, Jiyuan; Huang, Mei; Li, Guicai; Running, Steven W.; Smith, William K; Harris, Warwick; Saigusa, Nobuko; Kondo, Hiroaki; Liu, Yunfen; Hirano, Takashi; Xiao, Xiangming.

In: Remote Sensing, Vol. 6, No. 3, 01.01.2014, p. 2108-2133.

Research output: Contribution to journalArticle

Wang, J, Dong, J, Liu, J, Huang, M, Li, G, Running, SW, Smith, WK, Harris, W, Saigusa, N, Kondo, H, Liu, Y, Hirano, T & Xiao, X 2014, 'Comparison of gross primary productivity derived from GIMMS NDVI3g, GIMMS, and MODIS in Southeast Asia', Remote Sensing, vol. 6, no. 3, pp. 2108-2133. https://doi.org/10.3390/rs6032108
Wang, Junbang ; Dong, Jingwei ; Liu, Jiyuan ; Huang, Mei ; Li, Guicai ; Running, Steven W. ; Smith, William K ; Harris, Warwick ; Saigusa, Nobuko ; Kondo, Hiroaki ; Liu, Yunfen ; Hirano, Takashi ; Xiao, Xiangming. / Comparison of gross primary productivity derived from GIMMS NDVI3g, GIMMS, and MODIS in Southeast Asia. In: Remote Sensing. 2014 ; Vol. 6, No. 3. pp. 2108-2133.
@article{209186fb9bc6411e83eb81dd6c5751cd,
title = "Comparison of gross primary productivity derived from GIMMS NDVI3g, GIMMS, and MODIS in Southeast Asia",
abstract = "Gross primary production (GPP) plays an important role in the net ecosystem exchange of CO 2 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 GPPNDVI1g 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.",
keywords = "GIMMS NDVI1g, GIMMS NDVI3g, GLOPEM-CEVSA, Gross Primary Productivity (GPP), MOD15A2, MOD17A2, Southeast Asia",
author = "Junbang Wang and Jingwei Dong and Jiyuan Liu and Mei Huang and Guicai Li and Running, {Steven W.} and Smith, {William K} and Warwick Harris and Nobuko Saigusa and Hiroaki Kondo and Yunfen Liu and Takashi Hirano and Xiangming Xiao",
year = "2014",
month = "1",
day = "1",
doi = "10.3390/rs6032108",
language = "English (US)",
volume = "6",
pages = "2108--2133",
journal = "Remote Sensing",
issn = "2072-4292",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "3",

}

TY - JOUR

T1 - Comparison of gross primary productivity derived from GIMMS NDVI3g, GIMMS, and MODIS in Southeast Asia

AU - Wang, Junbang

AU - Dong, Jingwei

AU - Liu, Jiyuan

AU - Huang, Mei

AU - Li, Guicai

AU - Running, Steven W.

AU - Smith, William K

AU - Harris, Warwick

AU - Saigusa, Nobuko

AU - Kondo, Hiroaki

AU - Liu, Yunfen

AU - Hirano, Takashi

AU - Xiao, Xiangming

PY - 2014/1/1

Y1 - 2014/1/1

N2 - Gross primary production (GPP) plays an important role in the net ecosystem exchange of CO 2 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 GPPNDVI1g 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.

AB - Gross primary production (GPP) plays an important role in the net ecosystem exchange of CO 2 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 GPPNDVI1g 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.

KW - GIMMS NDVI1g

KW - GIMMS NDVI3g

KW - GLOPEM-CEVSA

KW - Gross Primary Productivity (GPP)

KW - MOD15A2

KW - MOD17A2

KW - Southeast Asia

UR - http://www.scopus.com/inward/record.url?scp=84896973495&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84896973495&partnerID=8YFLogxK

U2 - 10.3390/rs6032108

DO - 10.3390/rs6032108

M3 - Article

VL - 6

SP - 2108

EP - 2133

JO - Remote Sensing

JF - Remote Sensing

SN - 2072-4292

IS - 3

ER -