Journal of Korean Society for Geospatial Information Science (대한공간정보학회지)

Korea Spatial Information Society (대한공간정보학회)
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Region-based Canopy Cover Mapping Using Airborne Lidar Data

항공 라이다 자료를 이용한 영역 기반 차폐율 지도 제작

  • 김용민 (서울대학교 건설환경공학부) ;
  • 어양담 (건국대학교 신기술융합학과) ;
  • 전민철 (건국대학교 신기술융합학과) ;
  • 김형태 (한국토지주택공사 토지주택연구원) ;
  • 김창재 (연세대학교 건설공학연구소)
  • Received : 2011.01.28
  • Accepted : 2011.02.24
  • Published : 2011.03.31
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Abstract

The main purpose of this paper is to make a map showing canopy cover by using airborne Lidar data based on region. Watershed algorithm was applied to elevation data to conduct segmentation, and then canopy cover was estimated through the regions extracted. In the process of transforming point data to raster, we solved the problems about overestimation and underestimation by using frequency method. Also, canopy cover map could be produced with various scales by differing level of segmentation and it provides more accurate and precise information than ones of ordinary public forest map.

본 연구는 항공 라이다 자료를 이용하여 영역 기반 차폐율 지도를 제작하는데 목적이 있다. 영역 기반 차폐율을 산정하기 위하여 대표적인 영역 분할 기법인 유역 분할(Watershed) 기법을 라이다 자료의 고도값에 적용하였으며, 추출된 영역들을 기반으로 차폐율을 산정하였다. 포인트 기반의 라이다 분류 자료를 래스터 자료로 변환하는 과정에서 빈도수 방법을 사용함으로써 포인트 기반의 차폐율 산정법에서 발생하는 과소 과대 추정 문제를 해결하였다. 또한, 분할의 정도를 달리함으로써 필요에 따라 다양한 축척의 차폐율 지도를 작성할 수 있었다. 제안 기법을 통해 제작된 차폐율 지도는 기존 임상도에서 제공하는 소밀도에 비해 보다 정확하고 세밀한 정보를 제공함을 확인할 수 있었다.

Keywords

References

  1. 전민철, 정태웅, 어양담, 김진광, (2010), 계절별 항공라이다 자료에 의한 수고 추정, 한국측량학회지, 제28권, 제 4호, pp.441-448.
  2. Chang, A. J., Eo, Y. D., Kim, S. W., Kim, Y. M. and Kim, Y. I. (2010), Canopy-cover thematic-map generation for Military Map products using remote sensing data in inaccessible areas, Landscape Ecological Engineering, DOI 10.1007/s11355-010-0132-1.
  3. Franklin, S. E., Hall, R. J., Smith, L. and Gerylo, G. R. (2003), Discrimination of conifer height, age, and crown closure classes using Landsat-5 TM imagery in the Canadian Northwest Territories, International Journal of Remote Sensing, Vol.24, No.9, pp.1823-1834. https://doi.org/10.1080/01431160210144589
  4. Jennings, S. B., Brown, N. D. and Sheil, D. (1999), Assessing forest canopies and understorey illumination: canopy closure, canopy cover and other measures. Forestry, Vol.72, No.1, pp.59-74. https://doi.org/10.1093/forestry/72.1.59
  5. Kusakabe, T., Tsuzuki, H. and Sueda, T. (2006), Long-range estimation of leaf area index using airborne laser altimetry in Siberian Boreal, Journal of the Japanese Forest Society, Vol.88, No.1, pp.21-29. https://doi.org/10.4005/jjfs.88.21
  6. Lefsky, M. A., Hudak, A. T., Cohen, W. B. and Acker, S. A. (2005), Geographic variability in lidar predictions of forest stand structure in the Pacific Northwest., Remote Sensing of Environment, Vol.95, pp.532-548. https://doi.org/10.1016/j.rse.2005.01.010
  7. Lowman, M. D. and Rinker, H. B. (2004). Forest canopies. 2nd ed. Elsevier Academic Press., pp.517.
  8. Morsdorf, F., Kotz, B., Meier, E., Itten, K. I. and Allgower, B. (2006), Estimation of LAI and fractional cover from small footprint airborne laser scanning data based on gap fraction, Remote Sensing of Environment, Vol.104, pp.50-61. https://doi.org/10.1016/j.rse.2006.04.019
  9. Sasaki, T., Imanishi, J., Ioki, K., Morimoto, Y. and Kitada, K. (2008), Estimation of leaf area index and canopy openness in broad-leaved forest using an airborne laser scanner in comparison with high-resolution near-infrared digital photography, Landscape and Ecological Engineering, Vol.4, No.1, pp.47-55. https://doi.org/10.1007/s11355-008-0041-8
  10. G. and Ranson, J. (2000), Modeling Lidar returns from forest canopies, IEEE transactions on geoscience and remote sensing, Vol.38, No.6, pp.2617-2626. https://doi.org/10.1109/36.885208
  11. Vincent, L. and Soille, p.(1991), Watersheds in digital spaces: an efficient algorithm based on immersion simulations, IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol.13, No.6, pp.583-598. https://doi.org/10.1109/34.87344
  12. Wulder, M., Niemann, K. O. and Goodenough, D. G. (2000), Local maximum filtering for the extraction of tree location and basal area for high spatial resolution imagery, Remote Sensing of Environment, Vol.73, No.1, pp.103-114. https://doi.org/10.1016/S0034-4257(00)00101-2
  13. Xu Y., Prather, J. W., Hampton, H. M., Aumack, E. N., Dickson, B. G. and Sisk, T. D. (2006), Advanced exploratory data analysis for mapping regional canopy cover. Photogrammetric Engineering and Remote Sensing, Vol.72, No.1, pp.31-38. https://doi.org/10.14358/PERS.72.1.31
  14. Yu, X., Hyyppa, J., Kukko, A., Maltamo, M. and Kaartinen, H. (2006), Change detection techniques for canopy height growth measurements using Airborne Laser Scanner data, Photogrammetric Engineering and Remote Sensing, Vol.72, No.12, pp.1339-1348. https://doi.org/10.14358/PERS.72.12.1339