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Modeling Vegetation Reflectance from Satellite Remote Sensing Data

机译:利用卫星遥感数据模拟植被反射率

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摘要

The development of better techniques for land vegetation cover and forest ecosystems monitoring is a major requirement for local, regional and global policy and global change science. The influence of climatic variability and anthropogenic activities on the condition of the vegetation (agricultural fields, forests, sparse) is growing up continuously. In order to characterize current and future state of vegetation and localize zones of changes must be defined the proper criteria. Vegetation land cover monitoring by satellite remote sensing data is one of the most important application of satellite imagery. Vegetation reflectance has variations with sun zenith angle, view zenith angle, and terrain slope angle. To better providing of this these effects corrections in the visible and near-infrared region of electromagnetic spectrum, was used a three parameters model and was developed a simple physical model of vegetation reflectance, by assuming a homogeneous and closed vegetation canopy with randomly oriented leaves. Multiple scattering theory was used to extend the model to function for both near-infrared and visible light. This paper aims to improve the model to be used to correct satellite imagery for bidirectional and topographic effects. Thresholding based on biophysical variables derived from time trajectories of satellite data was applied for classifying using Landsat TM and ETM, SAR ERS-1 imagery for Cernica forested area in the Eastern part of Bucharest town, Romania. Classification accuracies are function of the class, comparison method and season of the year.
机译:开发更好的土地植被覆盖和森林生态系统监测技术是地方,区域和全球政策以及全球变化科学的主要要求。气候变化和人为活动对植被(农业田地,森林,稀疏)状况的影响不断增长。为了表征植被的当前和未来状态并确定变化的局部区域,必须定义适当的标准。通过卫星遥感数据监测植被覆盖是卫星图像最重要的应用之一。植被反射率随太阳天顶角,视野天顶角和地形倾斜角而变化。为了更好地在电磁波谱的可见光和近红外区域中提供这些效果校正,使用了三个参数模型,并通过假设均质且封闭的,带有随机定向叶片的植被冠层,开发了一个简单的植被反射率物理模型。使用多重散射理论将模型扩展为对近红外和可见光均起作用。本文旨在改进用于校正卫星图像双向和地形影响的模型。基于源自卫星数据时间轨迹的生物物理变量的阈值化方法,通过使用Landsat TM和ETM SAR ERS-1图像对罗马尼亚布加勒斯特镇东部切尔尼察林区进行了分类。分类准确度是班级的功能,比较方法和一年中的季节。

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