Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations

Faith Ann Heinsch, Maosheng Zhao, Steven W. Running, John S. Kimball, Ramakrishna R. Nemani, Kenneth J. Davis, Paul V. Bolstad, Bruce D. Cook, Ankur R. Desai, Daniel M. Ricciuto, Beverly E. Law, Walter C. Oechel, Hyojung Kwon, Hongyan Luo, Steven C. Wofsy, Allison L. Dunn, J. William Munger, Dennis D. Baldocchi, Liukang Xu, David Y. HollingerAndrew D. Richardson, Paul C. Stoy, Mario B S Siqueira, Russell Monson, Sean P. Burns, Lawrence B. Flanagan

Research output: Contribution to journalArticle

435 Citations (Scopus)

Abstract

The Moderate Resolution Spectroradiometer (MODIS) sensor has provided near real-time estimates of gross primary production (GPP) since March 2000. We compare four years (2000 to 2003) of satellite-based calculations of GPP with tower eddy CO 2 flux-based estimates across diverse land cover types and climate regimes. We examine the potential error contributions from meteorology, leaf area index (LAI)fPAR, and land cover. The error between annual GPP computed from NASA's Data Assimilation Office's (DAO) and tower-based meteorology is 28%, indicating that NASA's DAO global meteorology plays an important role in the accuracy of the GPP algorithm. Approximately 62% of MOD15-based estimates of LAI were within the estimates based on field optical measurements, although remaining values overestimated site values. Land cover presented the fewest errors, with most errors within the forest classes, reducing potential error. Tower-based and MODIS estimates of annual GPP compare favorably for most biomes, although MODIS GPP overestimates tower-based calculations by 20%-30%. Seasonally, summer estimates of MODIS GPP are closest to tower data, and spring estimates are the worst, most likely the result of the relatively rapid onset of leaf-out. The results of this study indicate, however, that the current MODIS GPP algorithm shows reasonable spatial patterns and temporal variability across a diverse range of biomes and climate regimes. So, while continued efforts are needed to isolate particular problems in specific biomes, we are optimistic about the general quality of these data, and continuation of the MOD17 GPP product will likely provide a key component of global terrestrial ecosystem analysis, providing continuous weekly measurements of global vegetation production.

Original languageEnglish (US)
Article number1645290
Pages (from-to)1908-1923
Number of pages16
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume44
Issue number7
DOIs
StatePublished - Jul 2006
Externally publishedYes

Fingerprint

spectroradiometers
towers
productivity
Towers
primary production
remote sensing
Remote sensing
eddy
Productivity
vortices
Fluxes
evaluation
estimates
Meteorology
biome
meteorology
leaf area index
land cover
assimilation
data assimilation

Keywords

  • AmeriFlux
  • CO eddy covariance flux [net ecosystem exchange (NEE)]
  • Gross primary production (GPP)
  • Moderate Resolution Imaging Spectroradiometer (MODIS)
  • Remote sensing
  • Terra

ASJC Scopus subject areas

  • Geochemistry and Petrology
  • Geophysics
  • Computers in Earth Sciences
  • Electrical and Electronic Engineering

Cite this

Heinsch, F. A., Zhao, M., Running, S. W., Kimball, J. S., Nemani, R. R., Davis, K. J., ... Flanagan, L. B. (2006). Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations. IEEE Transactions on Geoscience and Remote Sensing, 44(7), 1908-1923. [1645290]. https://doi.org/10.1109/TGRS.2005.853936

Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations. / Heinsch, Faith Ann; Zhao, Maosheng; Running, Steven W.; Kimball, John S.; Nemani, Ramakrishna R.; Davis, Kenneth J.; Bolstad, Paul V.; Cook, Bruce D.; Desai, Ankur R.; Ricciuto, Daniel M.; Law, Beverly E.; Oechel, Walter C.; Kwon, Hyojung; Luo, Hongyan; Wofsy, Steven C.; Dunn, Allison L.; Munger, J. William; Baldocchi, Dennis D.; Xu, Liukang; Hollinger, David Y.; Richardson, Andrew D.; Stoy, Paul C.; Siqueira, Mario B S; Monson, Russell; Burns, Sean P.; Flanagan, Lawrence B.

In: IEEE Transactions on Geoscience and Remote Sensing, Vol. 44, No. 7, 1645290, 07.2006, p. 1908-1923.

Research output: Contribution to journalArticle

Heinsch, FA, Zhao, M, Running, SW, Kimball, JS, Nemani, RR, Davis, KJ, Bolstad, PV, Cook, BD, Desai, AR, Ricciuto, DM, Law, BE, Oechel, WC, Kwon, H, Luo, H, Wofsy, SC, Dunn, AL, Munger, JW, Baldocchi, DD, Xu, L, Hollinger, DY, Richardson, AD, Stoy, PC, Siqueira, MBS, Monson, R, Burns, SP & Flanagan, LB 2006, 'Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations', IEEE Transactions on Geoscience and Remote Sensing, vol. 44, no. 7, 1645290, pp. 1908-1923. https://doi.org/10.1109/TGRS.2005.853936
Heinsch, Faith Ann ; Zhao, Maosheng ; Running, Steven W. ; Kimball, John S. ; Nemani, Ramakrishna R. ; Davis, Kenneth J. ; Bolstad, Paul V. ; Cook, Bruce D. ; Desai, Ankur R. ; Ricciuto, Daniel M. ; Law, Beverly E. ; Oechel, Walter C. ; Kwon, Hyojung ; Luo, Hongyan ; Wofsy, Steven C. ; Dunn, Allison L. ; Munger, J. William ; Baldocchi, Dennis D. ; Xu, Liukang ; Hollinger, David Y. ; Richardson, Andrew D. ; Stoy, Paul C. ; Siqueira, Mario B S ; Monson, Russell ; Burns, Sean P. ; Flanagan, Lawrence B. / Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations. In: IEEE Transactions on Geoscience and Remote Sensing. 2006 ; Vol. 44, No. 7. pp. 1908-1923.
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