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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Assimilation of SPOT/VEGETATION NDVI data into a sahelian vegetation dynamics model
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Assimilation of SPOT/VEGETATION NDVI data into a sahelian vegetation dynamics model

机译:将SPOT / VEGETATION NDVI数据同化为萨赫勒植被动力学模型

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This paper presents a method to monitor the dynamics of herbaceous vegetation in the Sahel. The approach is based on the assimilation of Normalized Difference Vegetation Index (NDVI) data acquired by the VEGETATION instrument on board SPOT 4/5 into a simple sahelian vegetation dynamics model. The study region is located in the Gourma region of Mali. The vegetation dynamics model is coupled with a radiative transfer model (the SAIL model). First, it is checked that the coupled models allow for a realistic simulation of the seasonal and interannual variability of NDVI over three sampling sites from 1999 to 2004. The data assimilation scheme relies on a parameter identification technique based on an Evolution Strategies algorithm. The simulated above-ground herbage mass resulting from NDVI assimilation is then compared to ground measurements performed over 13 study sites during the period 1999-2004. The assimilation scheme performs well with 404 kg DM/ha of average error (n=126 points) and a correlation coefficient of r=0.80 (to be compared to the 463 kg DM/ha and r=0.60 of the model performance without data assimilation). Finally, the sensitivity of the herbage mass model estimates to the quality of the meteorological forcing (rainfall and net radiation) is analyzed thanks to a stochastic approach. (C) 2007 Elsevier Inc. All rights reserved.
机译:本文提出了一种监测萨赫勒地区草本植物动态的方法。该方法基于将SPOT 4/5上的VEGETATION仪器获取的归一化植被指数(NDVI)数据同化为简单的萨赫勒植被动力学模型。研究区域位于马里的古尔马地区。植被动力学模型与辐射传输模型(SAIL模型)耦合。首先,检查耦合模型是否可以真实模拟1999年至2004年三个采样点上NDVI的季节和年际变化。数据同化方案依赖于基于Evolution Strategies算法的参数识别技术。然后将NDVI同化产生的模拟地上牧草质量与1999-2004年期间在13个研究地点进行的地面测量进行比较。该同化方案在404 kg DM / ha的平均误差(n = 126个点)和相关系数r = 0.80(与无数据同化的463 kg DM / ha和r = 0.60的模型性能进行比较)下表现良好)。最后,由于采用了随机方法,因此分析了牧草质量模型估计值对气象强迫质量(降雨和净辐射)的敏感性。 (C)2007 Elsevier Inc.保留所有权利。

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