Detection of the pine trees damaged by pine wilt disease using high spatial remote sensing data

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

Volumn 36, Issue , 2006, Pages

  Lee, S H ^a   Cho, H K ^a  

^a Korea Forest Research Institute   (South Korea)

Author keywords

Detection; High Spatial Image; Local Maximum Filter; Pine Wilt Disease

Indexed keywords

AERIAL PHOTOGRAPHY; ANTENNAS; ERROR DETECTION; FORESTRY; IMAGE ENHANCEMENT; IMAGE RESOLUTION; PIXELS; SATELLITES; STEREO IMAGE PROCESSING; TREES (MATHEMATICS);

HIGH RESOLUTION SATELLITE IMAGES; HIGH SPATIAL RESOLUTION; IMAGE TRANSFORMATIONS; LOCAL MAXIMUM; LOCAL MAXIMUM FILTERING; PINE WILT DISEASE; REMOTE SENSING DATA; SPATIAL IMAGES;

REMOTE SENSING;

EID: 85060421131     PISSN: 16821750     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (10)

1. Aplin, P., P. Atkinson, P. Curran, 1999. Fine Spatial Resolution Simulated Satellite Sensor Imagery for Land Cover Mapping in the United Kingdom. Remote Sensing of Environment, 68, pp.206-216.
2. Cho, N.C., C.U. Choi, S.W. Jeon and H.C. Jung, 2004. Research for verification and calibration of Multi-spectral aerial photographing system (PKNU 3). Proceedings of ACRS 2004, CD-ROM.
3. Enda, N., 1989. The Status of Pine Wilting Disease Caused by Bursaphelenchus xylophilus (Steiner et. Buhrer) Nickle and Its Control in Korea. Jour. of Korean Forest Society, 78(2), pp. 248-253.
4. Gougeon, F., 1998. Automatic individual tree crown delineation using a valley-following algorithm and a rule-based system. Proceedings of the International forum on Automated interpretation of high spatial resolution digital imagery for forestry, Victoria, BC, Canada, pp.11-23.
5. Korea Forest Service, 2005. http//www.foa.go.kr (accessed 1 Apr. 2006)
6. Lee E.K. and C.U. Choi, 2004. Research for Calibration and Correction of Multi-Spectral Aerial Photographing System (PKNU 3). J. Korean Association of Geographic Information Studies, 7(4), pp.142-154.
7. Pouliot, D.A., D.J. King, F.W. Bell and D.G. Pitt, 2002. Automated tree crown detection and delineation in high-resolution digital camera imagery of coniferous forest regeneration. Remote Sensing of Environment, 82(2-3), pp.322-334.
8. Reich, R.W. and R. Price, 1998. Detection and classification of forest damage caused by Tomentosus Root Rot using an airborne multispectral imager (CASI). Proceedings of the International forum on Automated interpretation of high spatial resolution digital imagery for forestry, Victoria, BC, Canada, pp. 179-185.
9. Toutin T. and P. Cheng, 2000. Demystification of IKONOS! EOM, 9(7), pp.17-21.
10. Wulder, M.A., K.O. Niemann and D.G. Goodenough, 2000. Local Maximum Filtering for the Extraction of Tree Locations and basal Area from High Spatial Resolution Imagery. Remote Sensing of Environment, 73, pp.103-114.