.png){kind=icon}
Return
Fully Automatic Point Cloud Analysis for Powerline Corridor Mapping
.png){kind=icon}
PRE
AI
DOI：10.1109/TGRS.2020.2989470.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Powerline inspection is an important task for electric power management. Corridor mapping, i.e., the task of surveying the surroundings of the line and detecting potentially hazardous vegetation and objects, is performed by aerial light detection and ranging (LiDAR) survey. To this purpose, the main tasks are automatic extraction of the wires and measurement of the distance of objects close to the line. In this article, we present a new fully automated solution, which does not use time-consuming line fitting method, but is based on simple geometrical assumptions and relies on the fact that wire points are isolated, sparse and widely separated from all other points in the data set. In particular, we detect and classify pylons by local-maxima strategy. Then, a new reference system, having its origin on the first pylon and y-axis toward the second one, is defined. In this new reference system, transverse sections of the raw point cloud are extracted; by iterating such procedure for all detected pylons, we are able to detect the wire bundle. Obstacles are then automatically detected according to corridor mapping requirements. The algorithm is tested on two relevant data sets.
Keywords:
Data analysis
geospatial analysis
laser applications
maintenance engineering
power distribution lines
remote sensing
unmanned aerial vehicles (UAVs)
Journal
IF:
8.6
Papers:
2.1W
Citations:
10.7W
Organization
Cited Papers
Synthesis and structure-activity studies of SH2 binding peptides containing hydrolytically stable analogs of O -phosphotyrosine.png)
Peptides
PeptidesIF0
PREAI
ShareSaveShareSaveShareSaveShareSaveShareSaveShareSaveShareSaveLiDAR-Based Real-Time Detection and Modeling of Power Lines for Unmanned Aerial VehiclesSENSORS
OAAI
SENSORSIF3.5
OAAIShareSave
View more