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http://dx.doi.org/10.7319/kogsis.2012.20.1.083

Estimation of Canopy Cover in Forest Using KOMPSAT-2 Satellite Images  

Chang, An-Jin (서울대학교 공학연구소)
Kim, Yong-Min (서울대학교 건설환경공학부)
Kim, Yong-Il (서울대학교 건설환경공학부)
Lee, Byoung-Kil (경기대학교 토목공학과)
Eo, Yan-Dam (건국대학교 신기술융합학과)
Publication Information
Journal of Korean Society for Geospatial Information Science / v.20, no.1, 2012 , pp. 83-91 More about this Journal
Abstract
Crown density, which is defined as the proportion of the forest floor concealed by tree crown, is important and useful information in various fields. Previous methods of measuring crown density have estimated crown density by interpreting aerial photographs or through a ground survey. These are time-consuming, labor-intensive, expensive and inconsistent approaches, as they involve a great deal of subjectivity and rely on the experience of the interpreter. In this study, the crown density of a forest in Korea was estimated using KOMPSAT-2 high-resolution satellite images. Using the image segmentation technique and stand information of the digital forest map, the forest area was divided into zones. The crown density for each segment was determined using the discriminant analysis method and the forest ratio method. The results showed that the accuracy of the discriminant analysis method was about 60%, while the accuracy of the forest ratio method was about 85%. The probability of extraction of candidate to update was verified by comparing the result with the digital forest map.
Keywords
Canopy Cover; Satellite Image; Forest Information; Geospatial Information System;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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1 Pitkanen, J., 2001, Individual Tree Detection in Digital Aerial Images by Combining Locally Adaptive Binarization and Local Maxima Methods, Canadian Journal of Forest Research, National Research Council of Canada, Vol.31, No.5, pp.832-844.   DOI   ScienceOn
2 Rautiainen, M., Stenberg, P. and Nilson, T., 2005, Estimating Canopy Cover in Scots Pine Stands, Silva Fennica, Finish Society of Forest Science, Vol.39, No.1, pp.137-142.
3 Chang, A., Eo, Y., S., Kim, Y. and Kim, Y., 2011, Canopy-Cover Thematic-Map Generation for Military Map Products using Remote Sensing Data in Inaccessible Areas, Landscape and Ecological Engineering, International Consortium of Landscape and Ecological Engineering, Vol.7, No.2, pp.263- 274.
4 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.   DOI
5 Gerylo, G. R., Hall, R. J., Franklin, S. E. and Smith, L., 2002, Empirical Relatiions between Landsat TM Spectral Response and Forest Stands Near Fort Simpson, Northwest Territories, Canada, Canadian Journal of Remote Sensing, Canadian Remote Sensing Society, Vol.28, No.1, pp.68-79.   DOI
6 Gonzales, R. C. and Woods, R. E., 2002, Digital Image Processing, Prentice Hall, Upper Saddle River.
7 Guyot, G., 1990, Optical Properties of Vegetation Canopies. In: Steven MD, Clark JA (eds) Application of remote sensing in agriculture, Butterworth, London, pp.19-43.
8 Ma, Z., Hart, M. M. and Rredmond, R. L., 2001, Mapping Vegetation Across Large Geographic Areas: Integration of Remote Sensing and GIS to Classify Multisource Data, Photogrammetry Engineering & Remote Sensing, American Society for Photogrammetry and Remote Sensing, Vol.69, No.4, pp.357-367.
9 Haralick, R. M., Shanmugam, K., Dinstein, I., 1973, Textural Features for Image Classification, IEEE Transaction on System, Man, and Cybernetics, Systems, Man, & Cybernetics Society, Vol.3, No.6, pp.610-621.   DOI
10 Kayitakire, F., Hamel, C. and Defourny, F., 2006, Retrieving Forest Sturcture Variables based on Image Texture Analysis and IKONOS-2 Imagery, Remote Sensing of Environment, Vol.102, No.3-4, pp.390- 401.   DOI
11 국립산림과학원, 2010, 정사항공사진을 활용한 제 5차 수치 임상도(1:25,000) 제작 매뉴얼, 국립산림과학원.
12 김기태, 조진우, 유환희, 2011, KOMSPAT-2호 위성영상을 이용한 도시지역 탄소저장량 추정, 한국지형공간정보학회지, 한국지형공간정보학회, 제19권, 2호, pp.49-54.
13 김선화, 이규성, 이지민, 2003, 임상 판독을 위한 IKONOS 다중분광 영상의 적용성 분석, 춘계학술대회논문집, 한국 GIS 학회, pp.1396-144.
14 김용민, 어양담, 전민철, 김형태, 김창재, 2011, 항공 라이다 자료를 이용한 영역 기반 차폐율 지도 제작, 한국지형공간정보학회지, 한국지형공간정보학회, 제19권, 1호, pp.29-36.
15 송문섭, 조심섭, 2004, SAS를 이용한 통계자료 분석, 자유아카데미.
16 유수홍, 허준, 정재훈, 한수희, 김경민, 2011, Landsat TM 위성영상과 비율영상을 적용한 지상부 탄소 저장량 추정 - kNN 알고리즘 및 회귀 모델을 중점적으로,한국지형공간정보학회지, 한국지형공간정보학회, 제19권, 2호, pp.39-48.
17 장안진, 유기윤, 김용일, 이병길, 2006, 컬러항공사진과 LiDAR 데이터를 이용한 수목 개체 및 수고 추정, 대한원격탐사학회지, 대한원격탐사학회, 제22권, 6호, pp.543-551.
18 장안진, 김형태, 2008, 항공사진과 Lidar 데이터를 이용한 산림지역의 바이오매스 추정에 관한 연구, 한국지리정보학회지, 한국지리정보학회, 제11권, 3호, pp.166-173.
19 정재훈, 허준, 유수홍, 김경민, 이정빈, 2010, kNN 알 고리즘과 계절별 Landsat TM 위성영상을 이용한 단양 군 지역의 지상부 바이오매스 탄소저장량 추정, 한국지형공간정보학회지, 한국지형공간정보학회, 제18권, 4 호, pp.119-129.
20 장안진, 2011, 위성영상을 이용한 영역 기반 수관 밀도 정보 추출, 2011년 추계학술대회 논문집, 한국지리정보학회, pp.142-143.
21 한유경, 2009, 세그먼트 기반의 Spatial Feature 추출을 통한 고해상도영상 분류정확도 개선, 석사학위논문, 서울대학교.
22 Carreiras, J. M. B., Pereira, J. M C. and Pereira J. S., 2006, Estimation of Tree Canopy Cover in Evergreen Oak Woodlands using Remote Sensing, Forest Ecology and Management, Elsevier B. V., Vol.223, No.1-3, pp.45-53.   DOI
23 국립산림과학원, 2008, 1:5:000 임상도 제작 방안 수립, 국립산림과학원.