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Validating a Dynamic Global Vegetation Model with Remotely Sensed Vegetation Index

机译:验证具有遥感植被指数的动态全球植被模型

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The present study aims to evaluate the ability of IBIS model to capture the difference in vegetation characteristics among six major biomes in the Northeast China Transect and to calibrate the simulated LAI by IBIS, using the product of MODIS LAI (Leaf Area Index). The results showed that IBIS simulated a little lower growing season LAI over temperate evergreen conifer forest and boreal evergreen forest, while it overestimated LAI relative to MODIS in non-growing season. IBIS performed poorly on LAI over savanna, grassland and shrub land, compared with MODIS and it nearly simulated higher LAI throughout the year. Based on regression analysis, the simulating LAI by IBIS (Integrated Biosphere Simulator) presented a significant linear correlation with that from MODIS over temperate evergreen conifer forest in spring and winter, boreal evergreen forest throughout the year and grassland from summer to early autumn. Therefore, it was help to adjust the model parameters over these plant functional types to calibrate the estimated LAI in a large spatial scale.
机译:本研究旨在评估宜必思模型在东北地区横切中占据六个主要生物群体中植被特征的能力,并使用Modis Lai(叶面积指数)的产品来校准模拟Lai。结果表明,宜必思模拟了温带常绿针叶树森林和北方常绿森林的一点较低的生长季节赖,而在非生长季节中,它高估了赖斯。与Modis相比,宜必思对荔枝,草原和灌木土地进行了莱西纳,草原和灌木陆地的表现差。基于回归分析,通过夏天和冬季,夏季和草原在春季到初秋的春季和冬季温带温带常绿针叶树林的模拟赖斯,从夏天和冬季的温带常绿森林的模拟相关性。因此,有助于调整这些植物功能类型上的模型参数,以校准估计的LAI以大的空间尺度。

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