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Object-based Analysis for Extraction of Dominant Tree Species

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  • SHAO, Meiyun
  • JING, Xia
  • WANG, Lu

Abstract

As forest is of great significance for our whole development and the sustainable plan is so focus on it. It is very urgent for us to have the whole distribution, stock volume and other related information about that. So the forest inventory program is on our schedule. Aiming at dealing with the problem in extraction of dominant tree species, we tested the highly hot method—object-based analysis. Based on the ALOS image data, we combined multi-resolution in eCognition software and fuzzy classification algorithm. Through analyzing the segmentation results, we basically extract the spruce, the pine, the birch and the oak of the study area. Both the spectral and spatial characteristics were derived from those objects, and with the help of GLCM, we got the differences of each species. We use confusion matrix to do the Classification accuracy assessment compared with the actual ground data and this method showed a comparatively good precision as 87% with the kappa coefficient 0.837.

Suggested Citation

  • SHAO, Meiyun & JING, Xia & WANG, Lu, 2015. "Object-based Analysis for Extraction of Dominant Tree Species," Asian Agricultural Research, USA-China Science and Culture Media Corporation, vol. 7(07), pages 1-3, July.
    • Handle: RePEc:ags:asagre:209849
    DOI: 10.22004/ag.econ.209849
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    Keywords

    Agribusiness;

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