Effects of canopy photosynthesis saturation on the estimation of gross primary productivity from MODIS data in a tropical forest
Publication: Research - peer-review › Journal article – Annual report year: 2012
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Effects of canopy photosynthesis saturation on the estimation of gross primary productivity from MODIS data in a tropical forest. / Propastin, P.; Ibrom, Andreas; Knohl, A.; Erasmi, S.
In: Remote Sensing of Environment, Vol. 121, 2012, p. 252-260.Publication: Research - peer-review › Journal article – Annual report year: 2012
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TY - JOUR
T1 - Effects of canopy photosynthesis saturation on the estimation of gross primary productivity from MODIS data in a tropical forest
A1 - Propastin,P.
A1 - Ibrom,Andreas
A1 - Knohl,A.
A1 - Erasmi,S.
AU - Propastin,P.
AU - Ibrom,Andreas
AU - Knohl,A.
AU - Erasmi,S.
PB - Elsevier Inc.
PY - 2012
Y1 - 2012
N2 - The Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) product (GPPMOD17A2) was evaluated against GPP from the eddy covariance flux measurements (GPPm) at a CO2 flux tower test site in a tropical rainforest in Sulawesi, Indonesia. The dynamics of 8-day GPPMOD17A2 averages generally showed similarities with observed values for the period 2004–2005 (r-value is 0.66, RMSE=1.31gCm−2d−1). However, the results revealed some underestimation of GPP by the MOD17A2 product during phases of low photosynthetic production while it overestimated GPP during phases with clear sky conditions. Obviously, these seasonal differences are caused by too large seasonal amplitudes in GPPMOD17A2. The observed inconsistencies of the GPPMOD17A2with GPPm were traced to the inputs of the MODIS GPP algorithm, including fraction of absorbed photosynthetically active radiation (fAPAR) and light use efficiency (εg). This showed that underestimation of low values is caused by several uncertainties in the MODIS fAPAR input, whereas overestimation at high irradiance is caused by the MODIS light use efficiency approach which does not account for saturation of canopy photosynthesis under clear sky conditions. The performance of the MODIS GPP algorithm has been improved through the use of a site-validated fAPAR data set and a novel approach for εg adjustment which allows for saturation of gross photosynthesis at high irradiance. Our study revealed a weakness of a commonly used light use efficiency approach to estimate global GPP at the example of a moist tropical rain forest in Indonesia and demonstrated a potential need for MOD17 enhancement.
AB - The Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) product (GPPMOD17A2) was evaluated against GPP from the eddy covariance flux measurements (GPPm) at a CO2 flux tower test site in a tropical rainforest in Sulawesi, Indonesia. The dynamics of 8-day GPPMOD17A2 averages generally showed similarities with observed values for the period 2004–2005 (r-value is 0.66, RMSE=1.31gCm−2d−1). However, the results revealed some underestimation of GPP by the MOD17A2 product during phases of low photosynthetic production while it overestimated GPP during phases with clear sky conditions. Obviously, these seasonal differences are caused by too large seasonal amplitudes in GPPMOD17A2. The observed inconsistencies of the GPPMOD17A2with GPPm were traced to the inputs of the MODIS GPP algorithm, including fraction of absorbed photosynthetically active radiation (fAPAR) and light use efficiency (εg). This showed that underestimation of low values is caused by several uncertainties in the MODIS fAPAR input, whereas overestimation at high irradiance is caused by the MODIS light use efficiency approach which does not account for saturation of canopy photosynthesis under clear sky conditions. The performance of the MODIS GPP algorithm has been improved through the use of a site-validated fAPAR data set and a novel approach for εg adjustment which allows for saturation of gross photosynthesis at high irradiance. Our study revealed a weakness of a commonly used light use efficiency approach to estimate global GPP at the example of a moist tropical rain forest in Indonesia and demonstrated a potential need for MOD17 enhancement.
KW - Gross primary production
KW - MODIS
KW - Light use efficiency
KW - FAPAR
KW - Tropical rainforest
KW - Sulawesi
U2 - 10.1016/j.rse.2012.02.005
DO - 10.1016/j.rse.2012.02.005
JO - Remote Sensing of Environment
JF - Remote Sensing of Environment
SN - 0034-4257
VL - 121
SP - 252
EP - 260
ER -