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Modeling gross primary production of a temperate grassland ecosystem in Inner Mongolia, China, using MODIS imagery and climate data 被引量:13

Modeling gross primary production of a temperate grassland ecosystem in Inner Mongolia, China, using MODIS imagery and climate data
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摘要 Carbon fluxes in temperate grassland ecosystems are characterized by large inter-annual variations due to fluctuations in precipitation and land water availability. Since an eddy flux tower has been in operation in the Xilin Gol grassland, which belongs to typical temperate grassland in North China, in this study, observed eddy covariance flux data were used to critically evaluate the biophysical per- formance of different remote sensing vegetation indices in relation to carbon fluxes. Furthermore, vegetation photosynthesis model (VPM) was introduced to estimate gross primary production (GPP) of the grassland ecosystem for assessing its dependability. As defined by the input variables of VPM, Moderate Resolution Imaging Spectroradimeter (MODIS) and standard data product MOD09A1 were downloaded for calculating enhanced vegetation index (EVI) and land surface water index (LSWI). Measured air temperature (Ta) and photosynthetically active radiation (PAR) data were also included for model simulating. Field CO2 flux data, during the period from May, 2003 to September, 2005, were used to estimate the 'observed' GPP (GPPobs) for validation. The seasonal dynamics of GPP predicted from VPM (GPPVPM) was compared quite well (R2=0.903, N=111, p【0.0001) with the observed GPP. The ag- gregate GPPVPM for the study period was 641.5 g C·m?2, representing a ~6% over-estimation, compared with GPPobs. Additionally, GPP predicted from other two typical production efficiency model (PEM) represents either higher overestimation or lower underestimation to GPPobs. Results of this study demonstrate that VPM has potential for estimating site-level or regional grassland GPP, and might be an effective tool for scaling-up carbon fluxes. Carbon fluxes in temperate grassland ecosystems are characterized by large inter-annual variations due to fluctuations in precipitation and land water availability. Since an eddy flux tower has been in operation in the Xilin Gol grassland, which belongs to typical temperate grassland in North China, in this study, observed eddy covariance flux data were used to critically evaluate the biophysical performance of different remote sensing vegetation indices in relation to carbon fluxes. Furthermore, vegetation photosynthesis model (VPM) was introduced to estimate gross primary production (GPP) of the grassland ecosystem for assessing its dependability. As defined by the input variables of VPM, Moderate Resolution Imaging Spectroradimeter (MODIS) and standard data product MOD09A1 were downloaded for calculating enhanced vegetation index (EVI) and land surface water index (LSWI). Measured air temperature (Ta) and photosynthetically active radiation (PAR) data were also included for model simulating. Field CO2 flux data, during the period from May, 2003 to September, 2005, were used to estimate the “observed” GPP (GPP obs) for validation. The seasonal dynamics of GPP predicted from VPM (GPP VPM) was compared quite well (R 2=0.903, N=111, p<0.0001) with the observed GPP. The aggregate GPP VPM for the study period was 641.5 g C·m?2, representing a ~6% over-estimation, compared with GPP obs. Additionally, GPP predicted from other two typical production efficiency model (PEM) represents either higher overestimation or lower underestimation to GPP obs. Results of this study demonstrate that VPM has potential for estimating site-level or regional grassland GPP, and might be an effective tool for scaling-up carbon fluxes.
出处 《Science China Earth Sciences》 SCIE EI CAS 2008年第10期1501-1512,共12页 中国科学(地球科学英文版)
基金 the International Partnership Project of Chinese Academy of Sciences (Grant No. CXTD-Z2005-1) National Basic Research Program of China (Grant No. 2002CB412501) NASA Land Cover and Land Use Change (LCLUC) Program (Grant Nos. NAG5-11160, NNG05GH80G)
关键词 GPP EDDY COVARIANCE remote sensing Xilin GOL GPP eddy covariance remote sensing Xilin Gol
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