Ground Filtering Algorithms for Airborne LiDAR Data: A Review of Critical Issues

نویسندگان

  • Xuelian Meng
  • Nate Currit
  • Kaiguang Zhao
چکیده

This paper reviews LiDAR ground filtering algorithms used in the process of creating Digital Elevation Models. We discuss critical issues for the development and application of LiDAR ground filtering algorithms, including filtering procedures for different feature types, and criteria for study site selection, accuracy assessment, and algorithm classification. This review highlights three feature types for which current ground filtering algorithms are suboptimal, and which can be improved upon in future studies: surfaces with rough terrain or discontinuous slope, dense forest areas that laser beams cannot penetrate, and regions with low vegetation that is often ignored by ground filters.

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عنوان ژورنال:
  • Remote Sensing

دوره 2  شماره 

صفحات  -

تاریخ انتشار 2010