Comparison of MODIS, eddy covariance determined and physiologically modelled gross primary production (GPP) in a Douglas-fir forest stand
Comparison of MODIS, eddy covariance determined and physiologically modelled gross primary production (GPP) in a Douglas-fir forest stand
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DOI：
10.1016/j.rse.2006.09.010
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发表时间：
2007-04
影响因子：
13.5
通讯作者：
N. Coops;T. Black;R. Jassal;J. A. Trofymow;K. Morgenstern
中科院分区：
文献类型：
--
作者：
N. Coops;T. Black;R. Jassal;J. A. Trofymow;K. Morgenstern
陆地碳净吸收量的数量及其年际变化是一个重要问题，未来潜在的固碳受大气CO2增加和气候变化的影响。然而，由于土壤，气候和植被特征以及测量大空间区域碳积累的困难，陆地生产力发生显着的细尺度变化，测量和模拟的碳积累的差异的评估是一项具有挑战性的任务。中分辨率成像光谱仪提供了一种从空间和时间上例行监测初级生产总值的手段。然而，它是至关重要的比较和对比的时间动态的C和水通量与地面网络测量，或使用生理模型估计。在本文中，使用多种方法，我们的目标是确定是否存在任何系统性的偏见，无论是在中分辨率成像光谱仪，或模拟的通量估计，相对于测量的万年青，针叶温带雨林温哥华岛，加拿大。结果表明，8天的GPP预测与一个简单的生理模式（3PGS），强迫使用当地的气象和冠层特征，匹配测量通量非常好（r2=0.86，p<0.001）涡度协方差（EC）和模拟GPP之间没有显着差异（p<0.001）。此外，模拟供水密切匹配测得的相对有效土壤含水量在网站上。使用冠层的光合有效辐射（fPAR）算法的MODIS部分的特点，略有减少的对应性的预测，由于大量的不成功的检索（83%），由于太阳角度，雪和云。基于MODIS GPP算法的GPP预测，强制使用当地气象和冠层特征，也与EC测量值高度相关（r2=0.89，p<0.001），但这些估计值在预测GPP时有偏差。基于最新的中分辨率成像分光仪再处理（4.5号数据集）的GPP估计值仍然高度相关（r2=0.88，p<0.001），但也是最有偏差的，估计值比欧洲共同体测量的GPP低30%。在该网站的GPP的变化大部分是由光合有效辐射的吸收解释。我们还比较了夜间呼吸，在现场测量超过2年的最低8天的MODIS地表温度，并发现一个显着的关系（r2=0.57），类似于其他研究。
Quantification of the magnitude of net terrestrial carbon (C) uptake, and how it varies inter-annually, is an important question with future potential sequestration influenced by both increased atmospheric CO2and changing climate. However the assessment of differences in measured and modeled C accumulation is a challenging task due to the significant fine scale variation occurring in terrestrial productivity due to soil, climate and vegetation characteristics as well as difficulties in measuring carbon accumulation over large spatial areas. The Moderate Resolution Imaging Spectroradiometer (MODIS) offers a means of monitoring gross primary production (GPP), both spatially and temporally, routinely from space. However it is critical to compare and contrast the temporal dynamics of the C and water fluxes with those measured from ground-based networks, or estimated using physiological models. In this paper, using a number of approaches, our objective is to determine if any systematic biases exists in either the MODIS, or the modeled estimates of fluxes, relative to the measurements made over an evergreen, needleleaf temperate rainforest on Vancouver Island, Canada. Results indicate that 8-day GPP as predicted with a simple physiological model (3PGS), forced using local meteorology and canopy characteristics, matched measured fluxes very well (r2=0.86, p<0.001) with no significant difference between eddy covariance (EC) and modeled GPP (p<0.001). In addition, modeled water supply closely matched measured relative available soil water content at the site. Using canopy characteristics from the MODIS fraction of photosynthetically active radiation (fPAR) algorithm, slightly reduced the correspondence of the predictions due to a large number of unsuccessful retrievals (83%) due to sun angle, snow and cloud. Predictions of GPP based on the MODIS GPP algorithm, forced using local meteorology and canopy characteristics, were also highly correlated with EC measurements (r2=0.89, p<0.001) however these estimates were biased under predicting GPP. Estimates of GPP based on the most recent MODIS reprocessing (collection 4.5) remained highly correlated (r2=0.88, p<0.001) yet were also the most biased with the estimates being 30% less than the EC-measured GPP. Most of the variance in GPP at the site was explained by the absorbed photosynthetically active radiation. We also compared the nighttime respiration as measured over 2 years at the site with the minimum 8-day MODIS land surface temperature and found a significant relationship (r2=0.57), similar to other studies.