Modeling Gross Primary Production by Integrating Satellite Data and Coordinated Flux Measurements in Arid and Semi-Arid China

作     者：WANG He-Song JIA Gen-Suo FENG Jin-Ming ZHAO Tian-Bao MA Zhu-Guo 

作者机构：Key Laboratory of Regional Climate-Environment Research for Temperate East Asia Institute of Atmospheric Physics Chinese Academy of Sciences Beo＇ing 100029 China Graduate University of Chinese Academy of Sciences Beijing 100049 China 

出 版 物：《Atmospheric and Oceanic Science Letters》 (大气和海洋科学快报（英文版）)

年 卷 期：2010年第3卷第1期

页      面：7-13页

学科分类：0810[工学-信息与通信工程] 08[工学] 082503[工学-航空宇航制造工程] 081002[工学-信号与信息处理] 0825[工学-航空宇航科学与技术] 

基　　金：supported by the National Basic Research Program of China (Grant Nos. 2009CB723904 and 2006CB400500) 

主　　题：gross primary production vegetation photo- synthesis model eddy covariance remote sensing coordinated observation arid and semiarid areas 

摘      要：Assessing large-scale patterns of gross primary production (GPP) in arid and semi-arid (ASA) areas is important for both scientific and practical *** sensing-based models,which integrate satellite data with input from ground-based meteorological measurements and vegetation characteristics,improve spatially extended estimates of vegetation productivity with high *** this study,the authors simulated GPP in ASA areas by integrating moderate resolution imaging spectral radiometer (MODIS) data with eddy covariance and meteorological measurements at the flux tower sites using the Vegetation Photosynthesis Model (VPM),which is a remote sensing-based model for analyzing the spatial pattern of GPP in different land cover *** field data were collected by coordinating observations at nine stations in *** results indicate that in the region during the growing season GPP was highest in cropland sites,second highest in woodland sites,and lowest in grassland *** captured the temporal and spatial characteristics of GPP for different land covers in ASA ***,Enhanced Vegetation Index (EVI) had a strong liner relationship with GPP in densely vegetated areas,while the Normalized Difference Vegetation Index (NDVI) had a strong liner relationship with GPP over less dense *** study demonstrates the potential of satellite-driven models for scaling-up GPP,which is a key component for studying the carbon cycle at regional and global scales.