Journal of Digital Convergence (디지털융복합연구)

The Society of Digital Policy and Management (한국디지털정책학회)
권호 표지
DOI QR코드

DOI QR Code

Construction of Tree Management Information Using Point Cloud Data

포인트클라우드 데이터를 이용한 수목관리정보 구축 방안

  • Lee, Keun-Wang (Department of the Multimedia Science, Chungwoon University) ;
  • Park, Joon-Kyu (Department of Civil Engineering, Seoil University)
  • 이근왕 (청운대학교 멀티미디어학과) ;
  • 박준규 (서일대학교 토목공학과)
  • Received : 2020.10.20
  • Accepted : 2020.11.20
  • Published : 2020.11.28
Download PDF
⟨ Previous Next ⟩

Abstract

In order to establish an effective forest management plan, it is necessary to investigate tree management information such as tree height and DBH(Diameter at breast height). However, research on convergence and application of data acquisition technology to improve the efficiency of existing forest survey methods is insufficient. Therefore, in this study, tree management information was constructed and analyzed using point cloud data acquired through a 3D scanner. Data on the study site was acquired using fixed and mobile 3D scanners, and the efficiency of the mobile 3D scanner was presented through comparison of working hours. In addition, tree management information for object management was constructed by classifying vegetation by object using point cloud data, and by constructing information on chest height diameter and height. As a result of the accuracy evaluation compared with the conventional measurement method, the difference in tree height was 0.02-0.09m and DBH was 0.01-0.04m. If information on the location of vegetation and crowns of each object is constructed through additional research in the future, the efficiency of the work related to forest management information construction can be greatly increased.

효과적인 산림경영계획 수립을 위해서는 수고, 흉고직경 등 수목관리정보에 대한 조사가 필요하다. 하지만 기존의 산림조사 방법의 효율성을 향상시키기 위한 데이터 취득 기술의 융복합 및 적용에 대한 연구는 부족한 실정이다. 이에 본 연구에서는 3D 스캐너를 통해 취득되는 포인트클라우드 데이터를 활용하여 수목관리정보를 구축하고 분석하였다. 고정형 및 이동형 3D 스캐너를 이용하여 연구대상지에 대한 데이터를 취득하였으며, 작업시간 비교를 통해 이동형 3D 스캐너의 효율성을 제시하였다. 또한 포인트클라우드 데이터를 이용한 식생의 객체별 분류를 수행하고, 흉고직경 및 수고에 대한 정보를 구축함으로써 객체 관리가 가능한 수목관리정보를 구축하였다. 기존의 측정 방법과 비교한 정확도 평가 결과 수고는 0.02-0.09m, 흉고직경은 0.01-0.04m의 차이를 나타내었다. 향후 추가적인 연구를 통해 객체별 식생의 위치와 수관에 대한 정보를 구축한다면 산림관리정보 구축 관련 업무 효율성 증가에 기여할 것이다.

Keywords

References

  1. J. K. park & K. Y. Jung. (2020). Construction of 3D Geospatial Information for Development and Safety Management of Open-pit Mine. Korean Society Of Surveying, Geodesy, Photogrammetry and Cartography, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 38(1), 43-48. DOI: https://doi.org/10.7848/ksgpc.2020.38.1.43
  2. H. C. Yun & J. S. Lee. (2018). Accuracy Evaluation and Analysis of SLAM for the Advancement of Forest Investigation. Journal of the Korea Academia-Industrial cooperation Society, 19(12), 734-739. DOI : https://doi.org/10.5762/KAIS.2018.19.12.734
  3. H. D. Seo & E. M. Kim. (2019). Object Classification Using Point Cloud and True Ortho-image by Applying Random Forest and Support Vector Machine Techniques. Korean Society Of Surveying, Geodesy, Photogrammetry and Cartography, 37(6), 405-416. DOI: https://doi.org/10.7848/ksgpc.2019.37.6.405
  4. K. J. Bhang, T. Sarker & J. D. Lee (2018). Prediction of Urban Land Cover Change Using Multilayer Perceptron and Markov Chain Analysis. Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 36(2), 43-48. DOI: https://doi.org/10.7848/ksgpc.2018.36.2.85
  5. S. J. Jang, Y. T. Lee, K. Y. Lee, J. H. Lee & K. W. Chun. (2020). A Study of Disaster Prevention and Characteristics of Landslides Triggered by the 2019 Typhoon Mitag in Samcheok. Journal of The Korean Society of Hazard Mitigation, 20(2), 221-227. DOI : https://doi.org/10.9798/KOSHAM.2020.20.2.221
  6. J. K. Park & K. Y. Jung. (2018). Investigation and Analysis of Forest Geospatial Information Using Drone. Journal of the Korea Academia-Industrial cooperation Society, 19(2), 602-607. DOI : https://doi.org/10.5762/KAIS.2018.19.2.602
  7. Korea Forest Service (Sep. 11, 2018). News and Resource. http://www.forest.go.kr/
  8. S. K. Choi, J. W. Choi, S. W. Park, S. H. Jung & S. K. Lee. (2017). Applicability of Wind-Vegetation Model in Small Scale Sand Dunes. Journal of the Korean Society of Surveying,Geodesy, Photogrammetry and Cartography, 35(6), 545-552. DOI : https://doi.org/10.7848/ksgpc.2017.35.6.545
  9. J. K. Park & K. W. Lee. (2017). Analysis of Geospatial Information Construction Efficiency by 3D Laser Scanner Integrated with Total Station. Journal of the Korea Academia-Industrial cooperation Society, 18(12), 638-643. DOI : https://doi.org/10.5762/KAIS.2017.18.12.638
  10. J. H. Seong, K. R. Lee, Y. S. Kwon, Y. K. Han & W. H. Lee. (2020). A Study on Identification of the Heat Vulnerability Area Considering Spatial Autocorrelation - Case Study in Daegu. Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 38(4), 295-304. DOI : https://doi.org/10.7848/ksgpc.2020.38.4.295
  11. T. H. Kim & J. H. Youn. (2018). A study on 3D safety state information platform architecture design for realistic disaster management based on spatial information. Journal of the Korea Academia-Industrial cooperation Society, 20(4), 564-570. DOI : https://doi.org/10.5762/KAIS.2019.20.4.564
  12. S. C. lee, S. H. Choi & W. Cho. (2020). A Study of Visualization and Analysis Method about Plants Social Network Used for Planting Design - Focusing on Forest Vegetation Area in Busan Metropolitan City. KOREAN JOURNAL OF ENVIRONMENT AND ECOLOG, 34(3), 259-270. DOI : https://doi.org/10.13047/KJEE.2020.34.3.259
  13. J. K. Park & K. W. Lee. (2020). Analysis of Data Characteristics by UAV LiDAR Sensor. Journal of the Korea Academia-Industrial cooperation Society, 21(5), 1-6.. DOI : https://doi.org/10.5762/KAIS.2020.21.5.1
  14. Trimble Inc. (Sep. 11, 2020). Product. http://www.trimble.com/
  15. Greenvalley International (Sep. 11, 2020). Product. https://greenvalleyintl.com/