The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XL-7/W3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W3, 489–494, 2015
https://doi.org/10.5194/isprsarchives-XL-7-W3-489-2015
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W3, 489–494, 2015
https://doi.org/10.5194/isprsarchives-XL-7-W3-489-2015

  29 Apr 2015

29 Apr 2015

Vegetation Height Estimation Near Power transmission poles Via satellite Stereo Images using 3D Depth Estimation Algorithms

A. Qayyum1, A. S. Malik1, M. N. M. Saad1, M. Iqbal1, F. Abdullah1, W. Rahseed1, T. A. R. B. T. Abdullah2, and A. Q. Ramli2 A. Qayyum et al.
  • 1Centre for Intelligent Signal and Imaging Research (CISIR),Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS 31750 Tronoh, Perak, Malaysia
  • 2Universiti Tenaga Nasional ,43000 Kajang ,Selangor, Malaysia

Keywords: QuickBird Satellite sensor, Pleiades satellite Sensor, Stereo matching techniques, Dynamic Programming, Graph-Cut, 3D depth approach

Abstract. Monitoring vegetation encroachment under overhead high voltage power line is a challenging problem for electricity distribution companies. Absence of proper monitoring could result in damage to the power lines and consequently cause blackout. This will affect electric power supply to industries, businesses, and daily life. Therefore, to avoid the blackouts, it is mandatory to monitor the vegetation/trees near power transmission lines. Unfortunately, the existing approaches are more time consuming and expensive. In this paper, we have proposed a novel approach to monitor the vegetation/trees near or under the power transmission poles using satellite stereo images, which were acquired using Pleiades satellites. The 3D depth of vegetation has been measured near power transmission lines using stereo algorithms. The area of interest scanned by Pleiades satellite sensors is 100 square kilometer. Our dataset covers power transmission poles in a state called Sabah in East Malaysia, encompassing a total of 52 poles in the area of 100 km. We have compared the results of Pleiades satellite stereo images using dynamic programming and Graph-Cut algorithms, consequently comparing satellites’ imaging sensors and Depth-estimation Algorithms. Our results show that Graph-Cut Algorithm performs better than dynamic programming (DP) in terms of accuracy and speed.