MMS 포인트 클라우드를 활용한 하천제방 경사도 자동 추출에 관한 연구

Translated title of the contribution: Automatic extraction of river levee slope using mms point cloud data

Cheolhwan Kim, Jisang Lee, Wonjun Choi, Wondae Kim, Hong Gyoo Sohn

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Continuous and periodic data acquisition must be preceded to maintain and manage the river facilities effectively. Adapting the existing general facilities methods, which include river surveying methods such as terrestrial laser scanners, total stations, and Global Navigation Satellite System (GNSS), has limitation in terms of its costs, manpower, and times to acquire spatial information since the river facilities are distributed across the wide and long area. On the other hand, the Mobile Mapping System (MMS) has comparative advantage in acquiring the data of river facilities since it constructs threedimensional spatial information while moving. By using the MMS, 184,646,009 points could be attained for Anyang stream with a length of 4 kilometers only in 20 minutes. Levee points were divided at intervals of 10 meters so that about 378 levee cross sections were generated. In addition, the water side maximum and average slope could be automatically calculated by separating slope plane form levee point cloud, and the accuracy of RMSE was confirmed by comparing with manually calculated slope. The reference slope was calculated manually by plotting point cloud of levee slope plane and selecting two points that use location information when calculating the slope. Also, as a result of comparing the water side slope with slope standard in basic river plan for Anyang stream, it is confirmed that inspecting the river facilities with the MMS point cloud is highly recommended than the existing river survey.

Translated title of the contributionAutomatic extraction of river levee slope using mms point cloud data
Original languageKorean
Pages (from-to)1425-1434
Number of pages10
JournalKorean Journal of Remote Sensing
Volume37
Issue number5-13
DOIs
Publication statusPublished - 2021

Bibliographical note

Publisher Copyright:
© 2021 Korean Society of Remote Sensing. All rights reserved.

All Science Journal Classification (ASJC) codes

  • Computers in Earth Sciences
  • Engineering (miscellaneous)
  • Earth and Planetary Sciences (miscellaneous)

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