Vegetation height estimation near power transmission poles via satellite stereo images using 3D depth estimation algorithms

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.