文献类型：期刊文献

英文题名：Modeling Gross Primary Production of a Typical Coastal Wetland in China Using MODIS Time Series and CO2 Eddy Flux Tower Data

作者：Kang, Xiaoming[1,2] Yan, Liang[1] Zhang, Xiaodong[1] Li, Yong[1] Tian, Dashuan[3] Peng, Changhui[2,4] Wu, Haidong[1] Wang, Jinzhi[1] Zhong, Lei[5]

第一作者：Kang, Xiaoming;康晓明

通信作者：Wang, JZ[1];Zhong, L[2]

机构：[1]Chinese Acad Forestry, Inst Wetland Res, Beijing Key Lab Wetland Serv & Restorat, Beijing 100091, Peoples R China;[2]Univ Quebec, Inst Environm Sci, Dept Biol Sci, Montreal, PQ C3H 3P8, Canada;[3]Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China;[4]Northwest Agr & Forest Univ, Coll Forestry, Ctr Ecol Forecasting & Global Change, Yangling 712100, Shaanxi, Peoples R China;[5]Tianjin Univ, Sch Environm Sci & Engn, China Australia Ctr Sustainable Urban Dev, Tianjin 300072, Peoples R China

年份：2018

卷号：10

期号：5

外文期刊名：REMOTE SENSING

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000435198400050)】；

基金：This work was supported by the National Key Research and Development Program of China (2017YFC0506203), the Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant and a Postdoctoral Fellowship to Xiaoming Kang from the University of Quebec at Montreal (UQAM), Canada, the National Natural Science Foundation of China (Grant No. 31770511, 41701113, 41403102,41403073). We thank the principal investigators of the MODIS data products as well as the Oak Ridge National Laboratory's (ORNL) Distributed Active Archive Center (DAAC) and the Earth Observation and Modeling Facility (EOMF), the University of Oklahoma. We thank the anonymous reviewers and editors for their valuable comments and suggestions on the earlier versions of the manuscript. We also thank Bingxue Wang for the suggestion of statistical analysis.

语种：英文

外文关键词：coastal wetland; eddy covariance; gross primary production; MODIS; vegetation indices; VPM

摘要：How to effectively combine remote sensing data with the eddy covariance (EC) technique to accurately quantify gross primary production (GPP) in coastal wetlands has been a challenge and is also important and necessary for carbon (C) budgets assessment and climate change studies at larger scales. In this study, a satellite-based Vegetation Photosynthesis Model (VPM) combined with EC measurement and Moderate Resolution Imaging Spectroradiometer (MODIS) data was used to evaluate the phenological characteristics and the biophysical performance of MODIS-based vegetation indices (VIs) and the feasibility of the model for simulating GPP of coastal wetland ecosystems. The results showed that greenness-related and water-related VIs can better identify the green-up and the senescence phases of coastal wetland vegetation, corresponds well with the C uptake period and the phenological patterns that were delineated by GPP from EC tower (GPP(EC)). Temperature can explain most of the seasonal variation in VIs and GPP(EC) fluxes. Both enhanced vegetation index (EVI) and water-sensitive land surface water index (LSWI) have a higher predictive power for simulating GPP in this coastal wetland. The comparisons between modeled GPP (GPP(VPM)) and GPP(EC) indicated that VPM model can commendably simulate the trajectories of the seasonal dynamics of GPP(EC) fluxes in terms of patterns and magnitudes, explaining about 85% of GPP(EC) changes over the study years (p < 0.0001). The results also demonstrate the potential of satellite-driven VPM model for modeling C uptake at large spatial and temporal scales in coastal wetlands, which can provide valuable production data for the assessment of global wetland C sink/source.