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Improving global scale land cover classifications with multi-directional POLDER data and a decision tree classifier

机译:使用多向POLDER数据和决策树分类器改善全球规模的土地覆盖分类

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Several investigations indicate that the Bidirectional Reflectance Distribution Function (BRDF) contains information that can be used to complement spectral information for improved land cover classification accuracies. Prior studies on the addition of BRDF information to improve land cover classifications have been conducted primarily at local or regional scales. Thus, the potential benefits of adding BRDF information to improve global to continental scale land cover classification have not yet been explored. Here we examine the impact of multidirectional global scale data from the first Polarization and Directionality of Earth Reflectances (POLDER) spacecraft instrument flown on the Advanced Earth Observing Satellite (ADEOS-1) platform on overall classification accuracy and per-class accuracies for 15 land cover categories specified by the International Geosphere Biosphere Programme (IGBP).
机译:多项研究表明,双向反射率分布函数(BRDF)包含可用于补充光谱信息的信息,以提高土地覆盖分类的准确性。先前主要在地方或区域范围内进行了有关添加BRDF信息以改善土地覆盖分类的研究。因此,尚未探索添加BRDF信息以改善全球到大陆范围的土地覆被分类的潜在好处。在这里,我们研究了从先进的地球观测卫星(ADEOS-1)平台上飞行的首个地球反射偏振和方向性(POLDER)航天器仪器获得的多方向全球规模数据对15个土地覆盖的总体分类精度和每类精度的影响国际地球圈生物圈计划(IGBP)指定的类别。

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