邬明权等:Combining remote sensing and eddy covariance data to monitor the gross primary production of an estuarine wetland ecosystem in East China
被阅读 933 次
2015-10-23
Combining remote sensing and eddy covariance data to monitor the gross primary production of an estuarine wetland ecosystem in East China
作者:Wu, MQ (Wu, Mingquan)[ 1 ] ; Muhammad, S (Muhammad, Shakir)[ 1 ] ; Chen, F (Chen, Fang)[ 2 ] ; Niu, Z (Niu, Zheng)[ 1 ] ; Wang, CY (Wang, Changyao)[ 1 ]
ENVIRONMENTAL SCIENCE-PROCESSES & IMPACTS
卷: 17  期: 4  页: 753-762
DOI: 10.1039/c5em00061k
出版年: 2015
 
摘要
Wetland ecosystems are very important for ecological diversity and have a strong ability to sequester carbon. Through comparisons with field measured eddy covariance data, we evaluated the relationships between the light use efficiency (LUE) index and the enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), and land surface temperature (LST). Consequently, we have proposed a new model for the estimation of gross primary production (GPP) for wetland ecosystems using Moderate Resolution Imaging Spectroradiometer (MODIS) products, including these vegetation indices, LST and the fraction of photosynthetically active radiation (FAPAR) absorbed by the active vegetation. This model was developed and validated for a study site on Chongming Island, Shanghai, China. Our results show that photosynthetically active radiation (PAR) was highly correlated with the LST, with a coefficient of determination (R-2) of 0.59 (p < 0.001). Vegetation indices, such as EVI, NDVI and LST, were highly correlated with LUE. We found that the product of vegetation indices (VIs) and a modified form of LST (T-e) can be used to estimate LUE, with an R-2 of 0.82 (P < 0.0001) and an RMSE of 0.054 kg C per mol PAR. This new model can provide reliable estimates of GPP (R-2 of 0.87 and RMSE of 0.009 kg C m(-2) 8 d(-1) (P < 0.0001)).
 
通讯作者地址: Wu, MQ (通讯作者)
Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing, Peoples R China.
地址:
[ 1 ] Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing, Peoples R China
[ 2 ] Chinese Acad Sci, Lab Digital Earth Sci, Inst Remote Sensing & Digital Earth, Beijing, Peoples R China