Comparison of methods to estimate individual tree attributes using color aerial photographs and LiDAR data

  • Authors:

  • Anjin Chang;Jung Ok Kim;Kiyun Ryu;Yong Il Kim

  • Affiliations:

  • Department of Civil & Environmental Engineering, Seoul National University, Gwanak-Ku, Seoul, Korea;Department of Civil & Environmental Engineering, Seoul National University, Gwanak-Ku, Seoul, Korea;Department of Civil & Environmental Engineering, Seoul National University, Gwanak-Ku, Seoul, Korea;Department of Civil & Environmental Engineering, Seoul National University, Gwanak-Ku, Seoul, Korea

  • Venue:
  • WSEAS Transactions on Signal Processing
  • Year:
  • 2008

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Abstract

The main objective of this study was to compare methods to estimate the number of trees and individual tree height using LiDAR data and aerial photography. A Korean pine tree study area for these techniques was selected the methods of watershed segmentation, region-growing segmentation, and morphological filtering were compared to estimate their accuracy. The algorithm was initiated by developing a normalized digital surface model (NDSM). A tree region was then extracted using classification and elimination errors of the NDSM and the photograph. The NDSM of the tree region was prefiltered and information about individual trees was extracted by segmentation and morphological methods. By using local maximum filtering, the tree height was obtained. Field observations were compared with the predicted values for accuracy assessment. The accuracy test showed the watershed segmentation algorithm to be the best estimator for tree modeling. Regression models for the study area explained 80% of the tree numbers and 89% of the heights.