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. Hollinger; Andrew D. Richardson; Paul C. Stoy; Mario B.S. Siqueira; Russell K. Monson; Sean P. Burns; Lawrence B. Flanagan

doi:10.1109/TGRS.2005.853936

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 K. Monson, Sean P. Burns, Lawrence B. Flanagan

Forest Resources

Research output: Contribution to journal › Article › peer-review

564 Scopus citations

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 language	English (US)
Article number	1645290
Pages (from-to)	1908-1923
Number of pages	16
Journal	IEEE Transactions on Geoscience and Remote Sensing
Volume	44
Issue number	7
DOIs	https://doi.org/10.1109/TGRS.2005.853936
State	Published - Jul 2006

Bibliographical note

Funding Information:
Manuscript received October 1, 2004; revised April 25, 2005. This work was supported in part by the U.S. National Aeronautics and Space Administration (NASA) Earth Science Enterprise under MODIS Contract NAS5-31368. Eddy covariance flux tower sites are part of both the AmeriFlux and Fluxnet networks and are funded through a number of agencies, including the Department of Energy (DOE), the National Institute for Global Environmental Change (NIGEC), and NASA. F. A. Heinsch, M. Zhao, S. W. Running, and J. S. Kimball are with The University of Montana, Missoula, MT 59812 USA (e-mail: faithann@ ntsg.umt.edu). R. R. Nemani was with The University of Montana, Missoula, MT 59812 USA. He is now with NASA’s Ames Research Center, Moffett Field, CA 94035 USA. K. J. Davis, A. R. Desai, and D. M. Ricciuto are with The Pennsylvania State University, State College, PA 16804 USA. P. V. Bolstad and B. D. Cook are with the University of Minnesota, St. Paul, MN 55108 USA. B. E. Law is with Oregon State University, Corvallis, OR 97331 USA. W. C. Oechel and H. Luo are with San Diego State University, San Diego, CA 92182 USA. H. Kwon was with San Diego State University, San Diego, CA 92182 USA. She is now with The University of Wyoming, Laramie, WY 82071 USA. S. C. Wofsy, A. L. Dunn, and J. W. Munger are with Harvard University, Cambridge, MA 02138 USA. D. D. Baldocchi is with the University of California at Berkeley, Berkeley, CA 94720 USA. L. Xu was with the University of California at Berkeley, Berkeley, CA 94720 USA. He is now with LI-COR Biosciences, Lincoln, NE 68504 USA. D. Y. Hollinger is with the USDA Forest Service Northeast Research Station, Durham, NH 03824 USA. A. D. Richardson is with the University of New Hampshire, Durham, NH 03824. P. C. Stoy and M. B. S. Siqueira are with Duke University, Durham, NC 27708 USA. R. K. Monson and S. P. Burns are with the University of Colorado, Boulder, CO 80309 USA. L. B. Flanagan is with the University of Lethbridge, Lethbridge, AB T1K 3M4 Canada. Digital Object Identifier 10.1109/TGRS.2005.853936

Keywords

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

Access

10.1109/TGRS.2005.853936

OpenUrl availability

Full text

Cite this

Heinsch, F. A., Zhao, M., Running, S. W., Kimball, J. S., Nemani, R. R., Davis, K. J., Bolstad, P. V., Cook, B. D., Desai, A. R., Ricciuto, D. M., Law, B. E., Oechel, W. C., Kwon, H., Luo, H., Wofsy, S. C., Dunn, A. L., Munger, J. W., Baldocchi, D. D., Xu, L., ... 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. Article 1645290. https://doi.org/10.1109/TGRS.2005.853936

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, RK, 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

@article{fbc20240cb5447aba0d520d2b309c217,

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

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.",

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

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

note = "Funding Information: Manuscript received October 1, 2004; revised April 25, 2005. This work was supported in part by the U.S. National Aeronautics and Space Administration (NASA) Earth Science Enterprise under MODIS Contract NAS5-31368. Eddy covariance flux tower sites are part of both the AmeriFlux and Fluxnet networks and are funded through a number of agencies, including the Department of Energy (DOE), the National Institute for Global Environmental Change (NIGEC), and NASA. F. A. Heinsch, M. Zhao, S. W. Running, and J. S. Kimball are with The University of Montana, Missoula, MT 59812 USA (e-mail: faithann@ ntsg.umt.edu). R. R. Nemani was with The University of Montana, Missoula, MT 59812 USA. He is now with NASA{\textquoteright}s Ames Research Center, Moffett Field, CA 94035 USA. K. J. Davis, A. R. Desai, and D. M. Ricciuto are with The Pennsylvania State University, State College, PA 16804 USA. P. V. Bolstad and B. D. Cook are with the University of Minnesota, St. Paul, MN 55108 USA. B. E. Law is with Oregon State University, Corvallis, OR 97331 USA. W. C. Oechel and H. Luo are with San Diego State University, San Diego, CA 92182 USA. H. Kwon was with San Diego State University, San Diego, CA 92182 USA. She is now with The University of Wyoming, Laramie, WY 82071 USA. S. C. Wofsy, A. L. Dunn, and J. W. Munger are with Harvard University, Cambridge, MA 02138 USA. D. D. Baldocchi is with the University of California at Berkeley, Berkeley, CA 94720 USA. L. Xu was with the University of California at Berkeley, Berkeley, CA 94720 USA. He is now with LI-COR Biosciences, Lincoln, NE 68504 USA. D. Y. Hollinger is with the USDA Forest Service Northeast Research Station, Durham, NH 03824 USA. A. D. Richardson is with the University of New Hampshire, Durham, NH 03824. P. C. Stoy and M. B. S. Siqueira are with Duke University, Durham, NC 27708 USA. R. K. Monson and S. P. Burns are with the University of Colorado, Boulder, CO 80309 USA. L. B. Flanagan is with the University of Lethbridge, Lethbridge, AB T1K 3M4 Canada. Digital Object Identifier 10.1109/TGRS.2005.853936",

year = "2006",

month = jul,

doi = "10.1109/TGRS.2005.853936",

language = "English (US)",

volume = "44",

pages = "1908--1923",

journal = "IEEE Transactions on Geoscience and Remote Sensing",

issn = "0196-2892",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "7",

}

TY - JOUR

T1 - Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations

AU - Heinsch, Faith Ann

AU - Zhao, Maosheng

AU - Running, Steven W.

AU - Kimball, John S.

AU - Nemani, Ramakrishna R.

AU - Davis, Kenneth J.

AU - Bolstad, Paul V.

AU - Cook, Bruce D.

AU - Desai, Ankur R.

AU - Ricciuto, Daniel M.

AU - Law, Beverly E.

AU - Oechel, Walter C.

AU - Kwon, Hyojung

AU - Luo, Hongyan

AU - Wofsy, Steven C.

AU - Dunn, Allison L.

AU - Munger, J. William

AU - Baldocchi, Dennis D.

AU - Xu, Liukang

AU - Hollinger, David Y.

AU - Richardson, Andrew D.

AU - Stoy, Paul C.

AU - Siqueira, Mario B.S.

AU - Monson, Russell K.

AU - Burns, Sean P.

AU - Flanagan, Lawrence B.

N1 - Funding Information: Manuscript received October 1, 2004; revised April 25, 2005. This work was supported in part by the U.S. National Aeronautics and Space Administration (NASA) Earth Science Enterprise under MODIS Contract NAS5-31368. Eddy covariance flux tower sites are part of both the AmeriFlux and Fluxnet networks and are funded through a number of agencies, including the Department of Energy (DOE), the National Institute for Global Environmental Change (NIGEC), and NASA. F. A. Heinsch, M. Zhao, S. W. Running, and J. S. Kimball are with The University of Montana, Missoula, MT 59812 USA (e-mail: faithann@ ntsg.umt.edu). R. R. Nemani was with The University of Montana, Missoula, MT 59812 USA. He is now with NASA’s Ames Research Center, Moffett Field, CA 94035 USA. K. J. Davis, A. R. Desai, and D. M. Ricciuto are with The Pennsylvania State University, State College, PA 16804 USA. P. V. Bolstad and B. D. Cook are with the University of Minnesota, St. Paul, MN 55108 USA. B. E. Law is with Oregon State University, Corvallis, OR 97331 USA. W. C. Oechel and H. Luo are with San Diego State University, San Diego, CA 92182 USA. H. Kwon was with San Diego State University, San Diego, CA 92182 USA. She is now with The University of Wyoming, Laramie, WY 82071 USA. S. C. Wofsy, A. L. Dunn, and J. W. Munger are with Harvard University, Cambridge, MA 02138 USA. D. D. Baldocchi is with the University of California at Berkeley, Berkeley, CA 94720 USA. L. Xu was with the University of California at Berkeley, Berkeley, CA 94720 USA. He is now with LI-COR Biosciences, Lincoln, NE 68504 USA. D. Y. Hollinger is with the USDA Forest Service Northeast Research Station, Durham, NH 03824 USA. A. D. Richardson is with the University of New Hampshire, Durham, NH 03824. P. C. Stoy and M. B. S. Siqueira are with Duke University, Durham, NC 27708 USA. R. K. Monson and S. P. Burns are with the University of Colorado, Boulder, CO 80309 USA. L. B. Flanagan is with the University of Lethbridge, Lethbridge, AB T1K 3M4 Canada. Digital Object Identifier 10.1109/TGRS.2005.853936

PY - 2006/7

Y1 - 2006/7

N2 - 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.

AB - 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.

KW - AmeriFlux

KW - CO eddy covariance flux [net ecosystem exchange (NEE)]

KW - Gross primary production (GPP)

KW - Moderate Resolution Imaging Spectroradiometer (MODIS)

KW - Remote sensing

KW - Terra

UR - http://www.scopus.com/inward/record.url?scp=33746335642&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33746335642&partnerID=8YFLogxK

U2 - 10.1109/TGRS.2005.853936

DO - 10.1109/TGRS.2005.853936

M3 - Article

AN - SCOPUS:33746335642

SN - 0196-2892

VL - 44

SP - 1908

EP - 1923

JO - IEEE Transactions on Geoscience and Remote Sensing

JF - IEEE Transactions on Geoscience and Remote Sensing

IS - 7

M1 - 1645290

ER -

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

Abstract

Bibliographical note

Keywords

Access

OpenUrl availability

Other files and links

Fingerprint

Cite this