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Method to calibrate the coordinates of transmission towers based on satellite images.

Authors :
MA Yutang
PAN Hao
ZHOU Fangrong
HUANG Ran
ZHAO Jianeng
LUO Jiqiang
LIU Jing
SUN Haoxuan
JIAA Weie
ZHANG Tao
Source :
Remote Sensing for Natural Resources; Jun2022, Vol. 34 Issue 2, p63-71, 9p
Publication Year :
2022

Abstract

In order to realize the refined line inspection management of transmission lines' improve its operation and maintenance efficiency, realize satellite intelligent inspection, and accurately find the defects and hidden dangers of towers and transmission lines, the paper took the coordinates of transmission line towers in Kunming City, Yunnan Province as an example and proposed a method to calibrate the coordinates of transmission towers using satellite images. The method first uses the reference base - map data as the basis to match the control points and uses the digital elevation model % DEM) to perform geometric correction on the original remote sensing image. Then combined with such technologies as shadow detection and edge detection and visual interpretation, the calibrated tower coordinates are obtained. The experiment verified the geometric con'ection accuracy of the SuperView - 1 % SV1) and Gaofen -- 2 % GF2 ) sateHite images in the Kunming area, and the errors in the plane after conbection were 0.931 and 1.387 m, respectively. In addition, the experiment verified the calibration accuracy of the old tower coordinates on the two lines. The results show that the plane accuracy of the tower has increased from 13. 811 m and 8. 256 m to 5. 970 m and 5. 104 m, respectively, which meets the basic power grid requirements. This method can realize the calibration of the tower coordinates, reduce the workload of manual inspection, and improve the efficiency of line inspection. With the explosive growth of remote sensing image data, multi -- source images from the space and ground will continue to be combined, and the technology for the positioning of transmission towers based on satellite remote sensing images will have a broader development prospect. [ABSTRACT FROM AUTHOR]

Details

Language :
Chinese
ISSN :
2097034X
Volume :
34
Issue :
2
Database :
Complementary Index
Journal :
Remote Sensing for Natural Resources
Publication Type :
Academic Journal
Accession number :
157743001
Full Text :
https://doi.org/10.6046/zrzyg.2021207