vegetation phenology over time, with the assistance of in situ carbon and water
flux data from the flux towers.
Data from eddy covariance flux tower sites have been widely used to evaluate
the PEMs at ecosystem and landscape levels. Long-term efforts are required to
validate satellite-based PEMs with the data from ground-based CO 2 eddy
covariance technique. Currently, six hundred CO 2 eddy flux towers are operated
across various biome types, with different land management and stages of disturbance and recovery. Abundant NEE data have been accumulated and are freely
available to scientific users. Through a community-based effort, many researchers
have partitioned the half-hourly NEE into GPP and ecosystem respiration, and
made the data available to users, such as the Ameriflux and Asiaflux websites.
Collaboration between the remote sensing community and the CO 2 flux tower
community will certainly help evaluate and improve satellite-based PEMs.
Acknowledgments This study was supported by research grants from the NASA Data Analysis
Program (NNX09AC39G, NNX11AJ35G), and the NSF EPSCoR program (NSF-0919466). The
site-specific climate and CO 2 flux tower data from the Mead flux tower site in Nebraska were
provided by the AmeriFlux network (http://public.ornl.gov/ameriflux/). We thank Drs. Shashi B.
Verma and Andrew E. Suyker for their effort in collecting field data at the Mead flux tower site in
Nebraska.
References
Baldocchi D, Valentini R, Running S, Oechel W, Dahlman R (1996) Strategies for measuring and
modelling carbon dioxide and water vapour fluxes over terrestrial ecosystems. Glob Change
Biol 2(3):159–168
Barton C, North P (2001) Remote sensing of canopy light use efficiency using the photochemical
reflectance index—model and sensitivity analysis. Remote Sens Environ 78:264–273
Cao MK, Woodward FI (1998a) Dynamic responses of terrestrial ecosystem carbon cycling to
global climate change. Nature 393(6682):249–252
Cao MK, Woodward FI (1998b) Net primary and ecosystem production and carbon stocks of
terrestrial ecosystems and their responses to climate change. Glob Change Biol 4(2):185–198
Chen M, Zhuang Q (2012) Spatially explicit parameterization of a terrestrial ecosystem model
and its application to the quantification of carbon dynamics of forest ecosystems in the
conterminous United States. Earth Interact 16(5):1–22
Chiesi M et al (2012) Use of BIOME-BGC to simulate water and carbon fluxes within
Mediterranean macchia. iForest-Biogeosci For 5(1): 38–43
Collatz GJ, Ball JT, Grivet C, Berry JA (1991) Physiological and environmental regulation of
stomatal conductance, photosynthesis and transpiration: a model that includes a laminar
boundary layer. Agr For Meteorol 54:107–136
Collatz GJ, Ribas-Carbon M, Ball JA (1992) Coupled photosynthesis-stomatal conductance
model for leaves of C 4 plants. Aust J Plant Physiol 19:519–538
Cong N et al (2012) Spring vegetation green-up date in China inferred from SPOT NDVI data: a
multiple model analysis. Agr For Meteorol 165:104–113
Cramer W et al (1999) Comparing global models of terrestrial net primary productivity (NPP):
overview and key results. Glob Chang Biol 5:1–15
144
X. Xiao et al.
flux data from the flux towers.
Data from eddy covariance flux tower sites have been widely used to evaluate
the PEMs at ecosystem and landscape levels. Long-term efforts are required to
validate satellite-based PEMs with the data from ground-based CO 2 eddy
covariance technique. Currently, six hundred CO 2 eddy flux towers are operated
across various biome types, with different land management and stages of disturbance and recovery. Abundant NEE data have been accumulated and are freely
available to scientific users. Through a community-based effort, many researchers
have partitioned the half-hourly NEE into GPP and ecosystem respiration, and
made the data available to users, such as the Ameriflux and Asiaflux websites.
Collaboration between the remote sensing community and the CO 2 flux tower
community will certainly help evaluate and improve satellite-based PEMs.
Acknowledgments This study was supported by research grants from the NASA Data Analysis
Program (NNX09AC39G, NNX11AJ35G), and the NSF EPSCoR program (NSF-0919466). The
site-specific climate and CO 2 flux tower data from the Mead flux tower site in Nebraska were
provided by the AmeriFlux network (http://public.ornl.gov/ameriflux/). We thank Drs. Shashi B.
Verma and Andrew E. Suyker for their effort in collecting field data at the Mead flux tower site in
Nebraska.
References
Baldocchi D, Valentini R, Running S, Oechel W, Dahlman R (1996) Strategies for measuring and
modelling carbon dioxide and water vapour fluxes over terrestrial ecosystems. Glob Change
Biol 2(3):159–168
Barton C, North P (2001) Remote sensing of canopy light use efficiency using the photochemical
reflectance index—model and sensitivity analysis. Remote Sens Environ 78:264–273
Cao MK, Woodward FI (1998a) Dynamic responses of terrestrial ecosystem carbon cycling to
global climate change. Nature 393(6682):249–252
Cao MK, Woodward FI (1998b) Net primary and ecosystem production and carbon stocks of
terrestrial ecosystems and their responses to climate change. Glob Change Biol 4(2):185–198
Chen M, Zhuang Q (2012) Spatially explicit parameterization of a terrestrial ecosystem model
and its application to the quantification of carbon dynamics of forest ecosystems in the
conterminous United States. Earth Interact 16(5):1–22
Chiesi M et al (2012) Use of BIOME-BGC to simulate water and carbon fluxes within
Mediterranean macchia. iForest-Biogeosci For 5(1): 38–43
Collatz GJ, Ball JT, Grivet C, Berry JA (1991) Physiological and environmental regulation of
stomatal conductance, photosynthesis and transpiration: a model that includes a laminar
boundary layer. Agr For Meteorol 54:107–136
Collatz GJ, Ribas-Carbon M, Ball JA (1992) Coupled photosynthesis-stomatal conductance
model for leaves of C 4 plants. Aust J Plant Physiol 19:519–538
Cong N et al (2012) Spring vegetation green-up date in China inferred from SPOT NDVI data: a
multiple model analysis. Agr For Meteorol 165:104–113
Cramer W et al (1999) Comparing global models of terrestrial net primary productivity (NPP):
overview and key results. Glob Chang Biol 5:1–15
144
X. Xiao et al.