Three methods of estimating tree attributes using remote sensing data

Authors:
An Jin Chang;Jung Ok Kim;Kiyun Yu;Yong Il Kim
Affiliations:
School of Civil, Urban & Geo-System Engineering, Seoul National University, Shinrim-Dong, Gwanak-Ku, Seoul, Korea;School of Civil, Urban & Geo-System Engineering, Seoul National University, Shinrim-Dong, Gwanak-Ku, Seoul, Korea;School of Civil, Urban & Geo-System Engineering, Seoul National University, Shinrim-Dong, Gwanak-Ku, Seoul, Korea;School of Civil, Urban & Geo-System Engineering, Seoul National University, Shinrim-Dong, Gwanak-Ku, Seoul, Korea
Venue:
SSIP'07 Proceedings of the 7th WSEAS International Conference on Signal, Speech and Image Processing
Year:
2007

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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 remote sensing data. 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) and classification with LiDAR data and aerial photography. 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.