E. P. Zharikova, Y. U. Grigoryev, I. N. Alkhimenko, A. L. Grigoryeva
{"title":"Intelligent System for Detecting Environmental Problems Based on Multispectral Satellite Images","authors":"E. P. Zharikova, Y. U. Grigoryev, I. N. Alkhimenko, A. L. Grigoryeva","doi":"10.3103/S0005105525700566","DOIUrl":null,"url":null,"abstract":"<p>This paper describes the development of an intelligent system for detecting environmental problems based on multispectral satellite images. The functionality of the system is based on machine learning algorithms and provides the ability to highlight areas of environmental problems based on the analysis of each individual pixel of the image. The article describes the system architecture, data collection and preprocessing process, model development and training. The evaluation of the results of the system is based on real data. The effectiveness of application of the developments obtained as a result of the study for the tasks of monitoring the environmental state of the Earth’s surface for large territories is confirmed. The use of software modules provides the ability to respond quickly to emerging environmental abnormal situations.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"59 3","pages":"154 - 159"},"PeriodicalIF":0.5000,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.3103/S0005105525700566","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
This paper describes the development of an intelligent system for detecting environmental problems based on multispectral satellite images. The functionality of the system is based on machine learning algorithms and provides the ability to highlight areas of environmental problems based on the analysis of each individual pixel of the image. The article describes the system architecture, data collection and preprocessing process, model development and training. The evaluation of the results of the system is based on real data. The effectiveness of application of the developments obtained as a result of the study for the tasks of monitoring the environmental state of the Earth’s surface for large territories is confirmed. The use of software modules provides the ability to respond quickly to emerging environmental abnormal situations.
期刊介绍:
Automatic Documentation and Mathematical Linguistics is an international peer reviewed journal that covers all aspects of automation of information processes and systems, as well as algorithms and methods for automatic language analysis. Emphasis is on the practical applications of new technologies and techniques for information analysis and processing.