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Estimating northern peatland CO2 exchange from MODIS time series data

Schubert, Per LU ; Eklundh, Lars LU ; Lund, Magnus LU and Nilsson, Mats (2010) In Remote Sensing of Environment 114(6). p.1178-1189
Abstract
Studies using satellite sensor-derived data as input to models for CO2 exchange show promising results for closed forest stands. There is a need for extending this approach to other land cover types, in order to carry out large-scale monitoring of CO2 exchange. In this study, three years of eddy covariance data from two peatlands in Sweden were averaged for 16-day composite periods and related to data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and modeled photosynthetic photon flux density (PPFD). Noise in the time series of MODIS 250 m vegetation indices was reduced by using double logistic curve fits. Smoothed normalized difference vegetation index (NDVI) showed saturation during summertime, and the enhanced... (More)
Studies using satellite sensor-derived data as input to models for CO2 exchange show promising results for closed forest stands. There is a need for extending this approach to other land cover types, in order to carry out large-scale monitoring of CO2 exchange. In this study, three years of eddy covariance data from two peatlands in Sweden were averaged for 16-day composite periods and related to data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and modeled photosynthetic photon flux density (PPFD). Noise in the time series of MODIS 250 m vegetation indices was reduced by using double logistic curve fits. Smoothed normalized difference vegetation index (NDVI) showed saturation during summertime, and the enhanced vegetation index (EVI) generally gave better results in explaining gross primary productivity (GPP). The strong linear relationships found between GPP and the product of EVI and modeled PPFD (R2 = 0.85 and 0.76) were only slightly stronger than for the product of EVI and MODIS daytime 1 km land surface temperature (LST) (R2 = 0.84 and 0.71). One probable reason for these results is that several controls on GPP were related to both modeled PPFD and daytime LST. Since ecosystem respiration (ER) was largely explained by diurnal LST in exponential relationships (R2 = 0.89 and 0.83), net ecosystem exchange (NEE) was directly related to diurnal LST in combination with the product of EVI and modeled PPFD in multiple exponential regressions (R2 = 0.81 and 0.73). Even though the R2 values were somewhat weaker for NEE, compared to GPP and ER, the RMSE values were much lower than if NEE would have been estimated as the sum of GPP and ER. The overall conclusion of this study is that regression models driven by satellite sensor-derived data and modeled PPFD can be used to estimate CO2 fluxes in peatlands. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Ecosystem respiration (ER), Enhanced vegetation index (EVI), Gross primary productivity (GPP), Land surface temperature (LST), Moderate Resolution Imaging Spectroradiometer (MODIS), Net ecosystem exchange (NEE), Peatland, Photosynthetic photon flux density (PPFD)
in
Remote Sensing of Environment
volume
114
issue
6
pages
1178 - 1189
publisher
Elsevier
external identifiers
  • WOS:000276865000004
  • Scopus:77949489151
ISSN
0034-4257
DOI
10.1016/j.rse.2010.01.005
project
BECC
language
English
LU publication?
yes
id
e07c408d-a0db-426c-8db2-67cf8da0465b (old id 1584124)
alternative location
http://dx.doi.org/10.1016/j.rse.2010.01.005
date added to LUP
2010-06-21 10:27:11
date last changed
2016-10-13 04:43:43
@misc{e07c408d-a0db-426c-8db2-67cf8da0465b,
  abstract     = {Studies using satellite sensor-derived data as input to models for CO2 exchange show promising results for closed forest stands. There is a need for extending this approach to other land cover types, in order to carry out large-scale monitoring of CO2 exchange. In this study, three years of eddy covariance data from two peatlands in Sweden were averaged for 16-day composite periods and related to data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and modeled photosynthetic photon flux density (PPFD). Noise in the time series of MODIS 250 m vegetation indices was reduced by using double logistic curve fits. Smoothed normalized difference vegetation index (NDVI) showed saturation during summertime, and the enhanced vegetation index (EVI) generally gave better results in explaining gross primary productivity (GPP). The strong linear relationships found between GPP and the product of EVI and modeled PPFD (R2 = 0.85 and 0.76) were only slightly stronger than for the product of EVI and MODIS daytime 1 km land surface temperature (LST) (R2 = 0.84 and 0.71). One probable reason for these results is that several controls on GPP were related to both modeled PPFD and daytime LST. Since ecosystem respiration (ER) was largely explained by diurnal LST in exponential relationships (R2 = 0.89 and 0.83), net ecosystem exchange (NEE) was directly related to diurnal LST in combination with the product of EVI and modeled PPFD in multiple exponential regressions (R2 = 0.81 and 0.73). Even though the R2 values were somewhat weaker for NEE, compared to GPP and ER, the RMSE values were much lower than if NEE would have been estimated as the sum of GPP and ER. The overall conclusion of this study is that regression models driven by satellite sensor-derived data and modeled PPFD can be used to estimate CO2 fluxes in peatlands.},
  author       = {Schubert, Per and Eklundh, Lars and Lund, Magnus and Nilsson, Mats},
  issn         = {0034-4257},
  keyword      = {Ecosystem respiration (ER),Enhanced vegetation index (EVI),Gross primary productivity (GPP),Land surface temperature (LST),Moderate Resolution Imaging Spectroradiometer (MODIS),Net ecosystem exchange (NEE),Peatland,Photosynthetic photon flux density (PPFD)},
  language     = {eng},
  number       = {6},
  pages        = {1178--1189},
  publisher    = {ARRAY(0x91242f8)},
  series       = {Remote Sensing of Environment},
  title        = {Estimating northern peatland CO2 exchange from MODIS time series data},
  url          = {http://dx.doi.org/10.1016/j.rse.2010.01.005},
  volume       = {114},
  year         = {2010},
}