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| 引用本文： | 李芸,杨志强,杨博.ɽ��LIDAR�������ݵĽײ�δֲ�̽�������[J].大地测量与地球动力学,2012,32(2):60-63. |
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| 作者姓名： | 李芸 杨志强 杨博 |
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| 作者单位： | 1. 长安大学测绘与空间信息研究所,西安,710054
2. 机械工业勘察设计研究院,西安,710043 |
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| 摘 要： | ??????LIDAR??????????????????????????????????????????????????????????????????LIDAR????????????????δ????????????????????????????????????÷?????????Ч????????????LIDAR???????????е???????????????????????????Ч????
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| 关 键 词： | ???LIDAR ?????? ???? ???? ?????? |
GROSS ERROR DETECTION AND ANALYSIS BY HIERARCHICAL CLASSIFICATION OF MOUNTAINOUS LIDAR DATA |
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| Li Yun
,
Yang Zhiqiang
,
Yang Bo.GROSS ERROR DETECTION AND ANALYSIS BY HIERARCHICAL CLASSIFICATION OF MOUNTAINOUS LIDAR DATA[J].Journal of Geodesy and Geodynamics,2012,32(2):60-63. |
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| Authors: | Li Yun Yang Zhiqiang Yang Bo |
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| Institution: | 1)Institute of Surveying and Spatial Information,Chang’an University,Xi’an 710054 2)China JK Institute of Engineering Investigation and Design,Xi’an 710043) |
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| Abstract: | Gross error detection is one of the important data processing steps of mountainous LIDAR point cloud data.Through analysing the features of gross error distribution,original LIDAR point cloud data can be divided into extreme outliers,outlier clusters and isolated points.On this basis,the idea of hierarchical gross error detection of mountainous LIDAR point cloud data is proposed,and an example of experimental data is verified.Experimental results show that the method can effectively remove gross errors from original mountainous LIDAR point cloud data,and,to a certain extent,improving the effect of pre-processing of point cloud. |
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| Keywords: | mountainous LIDAR gross error detection hierarchical method outlier clusters isolated points |
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