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http://dx.doi.org/10.7747/JFES.2018.34.2.142

Development of a Semi-automatic Search Program for Crown Delineation Based on Watershed and Valley Following Algorithms  

Sim, Woodam (Division of Forest Sciences, College of Forest and Environmental Sciences, Kangwon National University)
Park, Jeongmook (Division of Forest Sciences, College of Forest and Environmental Sciences, Kangwon National University)
Lee, Jungsoo (Division of Forest Sciences, College of Forest and Environmental Sciences, Kangwon National University)
Publication Information
Journal of Forest and Environmental Science / v.34, no.2, 2018 , pp. 142-144 More about this Journal
Abstract
This paper discusses the development of semi-automatic search program for crown delineation in stand level. The crown of an individual tree was delineated by applying the Watershed (WS) and Valley Following (VF) algorithms. Unmanned Aerial Vehicle (UAV) images were used in the semi-automatic search program to delineate the crown area. The overall accuracy and Khat were used in accuracy assessment. WS algorithm's model showed the overall accuracy and Khat index of 0.80 and 0.59, respectively, in Plot 1. However, the overall accuracy and Khat of VF algorithm's model were 0.78 and 0.51, respectively, in Plot 2.
Keywords
LULUCF; UAV; crown delineation; Watershed algorithm; Valley Following algorithm;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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1 Couprie M, Bertrand G. 1997. Topological grayscale watershed transformation. Proc SPIE Vision Geometry 3168: 136-146.
2 Gougeon FA. 1995. A crown-following approach to the automatic delineation of individual tree crowns in high spatial resolution aerial images. Canadian J Rem Sens 21: 274-284.   DOI
3 Hyyppa HJ, Hyyppa JM. 2001. Effects of stand size on the accu- racy of remote sensing-based forest inventory. IEEE Trans Geosci Rem Sens 39: 2613-2621.   DOI
4 Intergovernmental Panel on Climate Change (IPCC). 2006. 2006 IPCC Guidelines for National Greenhouse Gas Inventories. IGES (Institute for Global Environmental Strategies).
5 Joshi C, Leeuw JD, Skidmore AK, Duren IC, Oosten H. 2006. Remotely sensed estimation of forest canopy density: a compar- ison of the performance of four methods. Int J Appl Earth Obs Geoinform 8: 84-95.   DOI
6 Lee GS, Kim SG, Choi YW. 2015. A comparative study of image classification method to detect water body based on UAS. J Korean Assoc Geogr Inf Stud 18: 113-127. (in Korean with English abstract)   DOI
7 Larsen M. 2007. Single tree species classification with a hypothetical multi-spectral satellite. Remote Sens Environ 110: 523-532.   DOI