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Evaluation of the MODIS LAI algorithm at a coniferous forest site in Finland

机译:芬兰针叶林林地MODIS LAI算法的评估

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摘要

Leaf area index (LAI) collected in a needle-leaf forest site near Ruokolahti, Finland, during a field campaign in June 14-21, 2000, was used to validate Moderate Resolution Imaging Spectroradiometer (MODIS) LAI algorithm. The field LAI data was first related to 30-m resolution Enhanced Thermal Mapper Plus (ETM+) images using empirical methods to create a high-resolution LAI map. The analysis of empirical approaches indicates that preliminary segmentation of the image followed by empirical modeling with the resulting patches, was an effective approach to developing an LAI validation surface. Comparison of the aggregated high-resolution LAI map and corresponding MODIS LAI retrievals suggests satisfactory behavior of the MODIS LAI algorithm although variation in MODIS LAI product is higher than expected, The MODIS algorithm, adjusted to high resolution, generally overestimates the LAI due to the influence of the understory vegetation. This indicates the need for improvements in the algorithm.. An improved correlation between field measurements and the reduced simple ratio (RSR) suggests that the shortwave infrared (SWIR) band may provide valuable information for needle-leaf forests.
机译:在2000年6月14日至21日的野战期间,在芬兰Ruokolahti附近的针叶林站点收集的叶面积指数(LAI)用于验证中等分辨率成像光谱仪(MODIS)LAI算法。首先使用经验方法将现场LAI数据与30米分辨率的增强型热成像仪Plus(ETM +)图像相关,以创建高分辨率LAI地图。对经验方法的分析表明,对图像进行初步分割,然后对所得斑块进行经验建模,是开发LAI验证表面的有效方法。聚合后的高分辨率LAI图和相应的MODIS LAI检索结果的比较表明,尽管MODIS LAI产品的变化高于预期,但MODIS LAI算法的行为令人满意。由于受到影响,调整为高分辨率的MODIS算法通常高估了LAI底层植被。这表明需要改进算法。实地测量与降低的简单比率(RSR)之间的改进的相关性表明,短波红外(SWIR)波段可能为针叶林提供有价值的信息。

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