Semi-automatic monitoring in monitoring the privacy of electricity transmission and super distribution lines in Yazd province using time series analysis of radar images, a case study of Jumhouri Blvd

Subject Areas : Journal of Radar and Optical Remote Sensing and GIS

Mahdieh  Rezaeyan ¹ (Senior expert in Remote Sensing and GIS)

Received: 2022-10-16 Accepted : 2022-12-19 Published : 2023-03-01

Keywords: Time series, Radar images, Sentinel 1 satellite, pixel-based algorithm, zero sigma dispersion coefficient,

Abstract :

Today, the electricity industry is considered one of the most vital industries of a country, and considering that the passage of electricity transmission lines in each region has different effects and radiation depending on its voltage, so in order to preserve human health, plant growth and prevent financial losses, Privacy must be respected. One of the optimal methods in semi-automatic monitoring and monitoring of illegal constructions is the use of remote sensing and the use of radar images. In this research, Sentinel1 radar time series images were used to monitor the security of transmission and super distribution lines, which after applying pre-processing Necessary in SNAP software, In order to extract the zero sigma dispersion coefficient of the images and make them binary, 100 sample points were taken as a statistical population from the Landsat images and the threshold limit of the construction of two images were calculated and the number 0.081003 was obtained as the threshold limit, and then by creating the privacy layer of the transmission network and overlaying it with the fuzzy images, the amount of interference The constructions were determined by the structure of the network privacy and also the illegal constructions were identified during one year with the pixel-based algorithm and at the end drone images were used for validation, the results of this research indicate that most of the illegal constructions can be identified using the method presented It was identified semi-automatically with 85-90% accuracy and increased the speed of identifying illegal constructions in privacy