Xiaohua Zhang, Hui Wang, Runchi Ji, Wenxiang Xue, Shuyuan Wang
{"title":"Research on Early Earth Disaster Recognition along Power Line Based on Multi-Source Satellite Remote Sensing","authors":"Xiaohua Zhang, Hui Wang, Runchi Ji, Wenxiang Xue, Shuyuan Wang","doi":"10.1109/REPE52765.2021.9617099","DOIUrl":null,"url":null,"abstract":"As the voltage level of the power grid continues to increase and the transmission distance increases year by year, ensuring the safety of transmission lines is crucial to economic and social development and residents' production and life. The environment along the transmission line is complicated, and the high-frequency, full-coverage risk assessment along the power line through manual is facing huge challenges, and it is urgent to find a suitable monitoring method. Satellite remote sensing has many advantages such as high measurement accuracy, wide coverage, all-weather, rich data volume and fast update. This article first analyzes the current results of the early identification of landslides, and introduces some of the research results into the early identification of ground disasters on power lines, and provides a way of adding and deleting specific influencing factors. After comprehensive analysis, the research area is confirmed Disaster factors and inducing factors. The data includes optical satellite data, SAR satellite data, DEM data, meteorological data, and geological data. Based on corresponding methods, additional and deleted hazard factors and hazard factors are extracted. During the operation of the risk assessment model, many influencing factors are divided into three calculation modes, and at the same time, the mechanism of the disaster-inducing factors is highlighted to realize the early identification of earth disasters. The analysis results of the disaster points identified by the risk model in this paper are completely consistent with the survey results, indicating that the model constructed in this paper can realize the early targeted identification of the ground disasters along the power line and the construction process is highly operable.","PeriodicalId":136285,"journal":{"name":"2021 IEEE 4th International Conference on Renewable Energy and Power Engineering (REPE)","volume":"176 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 4th International Conference on Renewable Energy and Power Engineering (REPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/REPE52765.2021.9617099","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
As the voltage level of the power grid continues to increase and the transmission distance increases year by year, ensuring the safety of transmission lines is crucial to economic and social development and residents' production and life. The environment along the transmission line is complicated, and the high-frequency, full-coverage risk assessment along the power line through manual is facing huge challenges, and it is urgent to find a suitable monitoring method. Satellite remote sensing has many advantages such as high measurement accuracy, wide coverage, all-weather, rich data volume and fast update. This article first analyzes the current results of the early identification of landslides, and introduces some of the research results into the early identification of ground disasters on power lines, and provides a way of adding and deleting specific influencing factors. After comprehensive analysis, the research area is confirmed Disaster factors and inducing factors. The data includes optical satellite data, SAR satellite data, DEM data, meteorological data, and geological data. Based on corresponding methods, additional and deleted hazard factors and hazard factors are extracted. During the operation of the risk assessment model, many influencing factors are divided into three calculation modes, and at the same time, the mechanism of the disaster-inducing factors is highlighted to realize the early identification of earth disasters. The analysis results of the disaster points identified by the risk model in this paper are completely consistent with the survey results, indicating that the model constructed in this paper can realize the early targeted identification of the ground disasters along the power line and the construction process is highly operable.