디지털융복합연구 (Journal of Digital Convergence)

  • 제19권12호
  • /
  • Pages.377-382
  • /
  • 2021
  • /
  • 2713-6434(pISSN)
  • /
  • 2713-6442(eISSN)
한국디지털정책학회 (The Society of Digital Policy and Management)
권호 표지
DOI QR코드

DOI QR Code

과학적인 산림자원관리를 위한 해외 산림공간정보 구축 및 활용 동향 조사

Research on the Trend of Establishment and Utilization of Overseas Forest Geospatial Information for Scientific Forest Resource Management

  • 박준규 (서일대학교 토목공학과) ;
  • 이근왕 (청운대학교 멀티미디어학과)
  • Park, Joon-Kyu (Department of Civil Engineering, Seoil University) ;
  • Lee, Keun-Wang (Department of the Multimedia Science, Chungwoon University)
  • 투고 : 2021.11.06
  • 심사 : 2021.12.20
  • 발행 : 2021.12.28
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

산림자원관리의 선진화를 위해서는 산림 관련 산업 종사자의 고령화와 인력 중심의 현장조사 체계 등의 문제해결이 필요하다. 이에 본 연구에서는 과학적인 산림자원관리를 위해 최신 기술이 적용된 해외 산림공간정보 구축 및 활용동향을 조사하여 국내 적용 방안을 파악하고자 하였다. 해외에서는 산림공간정보 구축 및 활용에 사진측량 및 LiDAR 기술이 활용되고 있었다. 사진측량의 경우 식생의 체적, 흉고직경, 수고 측정 등에 이용되었으며, LiDAR는 흉고직경 및 수고 측정에 적용된 사례가 있었다. 해외 사례에 대한 분석을 통해 사진측량 및 LiDAR를 활용한 산림공간정보 구축방안을 파악하였으며, LiDAR가 사진측량에 비해 높은 정확도를 나타냄을 알 수 있었다. 향후 다양한 LiDAR 센서를 이용한 산림공간정보의 구축을 수행하고, 정확도 및 작업 효율에 대한 분석이 이루어진다면 국내 산림공간정보 구축에 있어 새로운 기술의 활용 가능성을 제시할 수 있을 것이다.

In order to advance forest resource management, it is necessary to solve problems such as the aging of forest-related industry workers and the field investigation system centered on manpower. Therefore, in this study, the trend of establishment and utilization of overseas forest geospatial information applied with the latest technology for scientific forest resource management was investigated to identify the domestic application plan. Overseas, photogrammetry and LiDAR technologies were being used to construct and utilize forest geospatial information. In the case of photogrammetry, it was used to measure the volume of vegetation, diameter, and tree height. And LiDAR technology has been applied to the measurement of diameter, and tree height. Through the analysis of overseas cases, it was identified how to construct forest geospatial information using photogrammetry and LiDAR, and it was found that LiDAR showed higher accuracy than photogrammetry. In the future, if the construction of forest geospatial information using various LiDAR sensors are performed and the accuracy and work efficiency are analyzed, it will be possible to present the possibility of using new technologies in the construction of forest geospatial information in Korea.

키워드

과제정보

This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science and ICT(No. NRF-2021R1F1A1061677)

참고문헌

  1. T. H. Kim & J. H. Youn. (2019). 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.2019.22.1.621
  2. J. K. Park & K. Y. Jung. (2021). Accuracy Evaluation of Earthwork Volume Calculation According to Terrain Model Generation Method, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 39(1), 47-54. DOI: https://doi.org/10.7848/ksgpc.2021.39.1.47
  3. J. P. Seo, K. D. Kim, C. S. Woo, C. W. Lee & H. H. Lee. (2020). Evaluation of Field Application and Estimation of Bedload Discharge in the Forest Watershed using the Hydrophone, Journal of the Korea Academia-Industrial cooperation Society, 21(12), 807-818. DOI: https://doi.org/10.5762/KAIS.2020.21.12.807
  4. C. B. Park & J. S. Choi. (2021). Characteristics of Management of Facilities and Healing Programmes for Forest Therapy, Journal of the Korea Academia-Industrial cooperation Society, 22(2), 468-474. DOI: https://doi.org/10.5762/KAIS.2021.22.2.468
  5. Y. C. Lee, J. O. Kang & S. J. Oh. (2021). Drone Image based Time Series Analysis for the Range of Eradication of Clover in Lawn, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 39(1), 47-54. DOI: https://doi.org/10.7848/ksgpc.2021.39.4.211
  6. S. I. Baek, S. Y. Koh & W. K. Kim. (2020). Calculation of correction coefficients for the RedEdge-MX multispectral camera through intercalibration with a hyperspectral sensor, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 38(6), 707-716. DOI: https://doi.org/10.7848/ksgpc.2020.38.6.707
  7. Korea Forest Service. (2021). Status of forestry. https://www.forest.go.kr/
  8. J. K. Park & M. K. Oh. (2020). Application of Object Modeling and AR for Forest Field Investigation, Journal of the Korea Academia-Industrial cooperation Society, 21(12), 411-416. DOI: https://doi.org/10.5762/KAIS.2020.21.12.411
  9. J. M. Cho, J. S. Lee & B. G. Lee. (2021). A Study on the Accuracy Evaluation of UAV Photogrammetry using Oblique and Vertical Images, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 39(1), 41-46. DOI: https://doi.org/10.7848/ksgpc.2021.39.1.41
  10. J. Guerra-Hernandez, D. N. Cosenza, A. Cardil, C. A. Silva, B. Botequim, P. Soares, M. Silva, E. Gonzalez-Ferreiro & R. A. Diaz-Varela. (2019). Predicting Growing Stock Volume of Eucalyptus Plantations Using 3-D Point Clouds Derived from UAV Imagery and ALS Data, Forests, 10(905). DOI: https://doi.org/10.3390/f10100905
  11. J. Schumacher, M. Rattay, M. Kirchhofer, P. Adler & G. Kandler. (2019). Combination of Multi-Temporal Sentinel 2 Images and Aerial Image Based Canopy Height Models for Timber Volume Modelling, Forests, 10(746). DOI: https://doi.org/10.3390/f10090746
  12. J Roberts, A. Koeser, A. Abd-Elrahman, B. Wilkinson, G. Hansen, S. Landry & A.Perez. (2019). Mobile Terrestrial Photogrammetry for Street Tree Mapping and Measurements, Forests, 10(701). DOI: https://doi.org/10.3390/f10080701
  13. J Strunk, P. Packalen, P. Gould, D. Gatziolis, C. Maki, H. Andersen & R. J. McGaughey. (2019). Large Area Forest Yield Estimation with Pushbroom Digital Aerial Photogrammetry, Forests, 10(701). DOI: https://doi.org/10.3390/f10050397
  14. L. Wallace, C. Bellman, B. Hally, J. Hernandez. S. Jones & S. Hillman. (2019). Assessing the Ability of Image Based Point Clouds Captured from a UAV to Measure the Terrain in the Presence of Canopy Cover, Forests, 10(284). DOI: https://doi.org/10.3390/f10030284
  15. S. Ganz, Y. Kaber & P. Adler. (2019). Measuring Tree Height with Remote Sensing-A Comparison of Photogrammetric and LiDAR Data with Different Field Measurements, Forests, 10(694). DOI: https://doi.org/10.3390/f10080694
  16. B. D. Perugia, F. Giannetti, G. Chirici & D. Travaglini. (2019). Influence of Scan Density on the Estimation of Single-Tree Attributes by Hand-Held Mobile Laser Scanning, Forests, 10(277). DOI: https://doi.org/10.3390/f10030277
  17. Geoslam. (2021). Zeb 1. https://www.geoslam.com
  18. N. Puletti, M. Grotti & R. Scotti. (2019). Evaluating the Eccentricities of Poplar Stem Profiles with Terrestrial Laser Scanning, Forests, 10(239). DOI: https://doi.org/10.3390/f10030239
  19. S. H. Kim, J. C. Kim, S. W. Lee, H. G. Jo, S. A. Seo, J. S. Lim & I. B. Jeong. (2013). Guidebook of The 6th National Forest Inventory and Forest Health Monitoring, p.95, Guidebook, Korea Forestry Promotion Institute, ISBN: 978-89-98575-06-9