Evaluation of aerial remote sensing techniques for vegetation management in power line corridors

Mills, Steven J., Gerardo Castro, Marcos P., Li, Zhengrong, Cai, Jinhai, Hayward, Ross, Mejias, Luis and Walker, Rodney A. (2010) Evaluation of aerial remote sensing techniques for vegetation management in power line corridors. IEEE Transations on Geoscience and Remote Sensing, 48 9: 3379-3390. doi:10.1109/TGRS.2010.2046905


Author Mills, Steven J.
Gerardo Castro, Marcos P.
Li, Zhengrong
Cai, Jinhai
Hayward, Ross
Mejias, Luis
Walker, Rodney A.
Title Evaluation of aerial remote sensing techniques for vegetation management in power line corridors
Journal name IEEE Transations on Geoscience and Remote Sensing   Check publisher's open access policy
ISSN 0196-2892
Publication date 2010-09
Year available 2010
Sub-type Article (original research)
DOI 10.1109/TGRS.2010.2046905
Volume 48
Issue 9
Start page 3379
End page 3390
Total pages 12
Place of publication Piscataway, NJ, U.S.A.
Publisher Institute of Electrical and Electronics Engineers
Collection year 2011
Language eng
Abstract This paper presents an evaluation of airborne sensors for use in vegetation management in power-line corridors. Three integral stages in the management process are addressed, including the detection of trees, relative positioning with respect to the nearest power line, and vegetation height estimation. Image data, including multispectral and high resolution, are analyzed along with LiDAR data captured from fixed-wing aircraft. Ground truth data are then used to establish the accuracy and reliability of each sensor, thus providing a quantitative comparison of sensor options. Tree detection was achieved through crown delineation using a pulse-coupled neural network and morphologic reconstruction applied to multispectral imagery. Through testing, it was shown to achieve a detection rate of 96%, while the accuracy in segmenting groups of trees and single trees correctly was shown to be 75%. Relative positioning using LiDAR achieved root-mean-square-error (rmse) values of 1.4 and 2.1 m for cross-track distance and along-track position, respectively, while direct georeferencing achieved rmse of 3.1 m in both instances. The estimation of pole and tree heights measured with LiDAR had rmse values of 0.4 and 0.9 m, respectively, while stereo matching achieved 1.5 and 2.9 m. Overall, a small number of poles were missed with detection rates of 98% and 95% for LiDAR and stereo matching. © 2006 IEEE.
Keyword Image segmentation
Laser measurement applications
Power transmission lines
Stereo vision
Vegetation mapping
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status Non-UQ
Additional Notes Article # 5466249.

Document type: Journal Article
Sub-type: Article (original research)
Collections: Julius Kruttschnitt Mineral Research Centre Publications
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Created: Tue, 14 Dec 2010, 12:34:19 EST by Karen Holtham on behalf of Julius Kruttschnitt Mineral Research Centre