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  • 标题:Airborne Lidar feature Selection for urban classification using random forests
  • 本地全文:下载
  • 作者:Nesrine Chehata ; Li Guo ; Clément Mallet
  • 期刊名称:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
  • 印刷版ISSN:2194-9042
  • 电子版ISSN:2194-9050
  • 出版年度:2009
  • 卷号:XXXVIII-3/W8
  • 页码:207-212
  • 出版社:Copernicus Publications
  • 摘要:Various multi-echo and Full-waveform (FW) lidar features can be processed. In this paper, multiple classifers are applied to lidar feature selection for urban scene classification. Random forests are used since they provide an accurate classification and run efficiently on large datasets. Moreover, they return measures of variable importance for each class. The feature selection is obtained by backward elimination of features depending on their importance. This is crucial to analyze the relevance of each lidar feature for the classification of urban scenes. The Random Forests classification using selected variables provide an overall accuracy of 94.35%
  • 关键词:Lidar; Full-waveform; Classification; Feature selection; Random Forests; Urban scenes
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