D. Shaimardanov, A. Atnabaev, D. Mukhametov, L. Pavlova
{"title":"Status and Prospects for the Use of Remote Sensing Data for the Detection of Wildfires","authors":"D. Shaimardanov, A. Atnabaev, D. Mukhametov, L. Pavlova","doi":"10.33619/2414-2948/104/10","DOIUrl":null,"url":null,"abstract":"The article discusses the problem of fires as a serious threat to life, economy and ecosystems, highlighting the need for early detection and suppression of fires. The potential of the combination of Earth remote sensing and neural networks for rapid and accurate detection of natural fires is studied. The significance of applying artificial intelligence, the development of deep learning methods for neural network models, to analyze space images and detect early signs of fires is emphasized. The article also provides examples of successful projects and research in the field of wildfire detection. The final part of the paper emphasizes the need for further research and development of neural network training methods, expansion of training datasets and improvement of space imagery acquisition technologies for effective control and prevention of fires, in order to protect the environment and minimize damage to people.","PeriodicalId":505704,"journal":{"name":"Bulletin of Science and Practice","volume":"45 39","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bulletin of Science and Practice","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33619/2414-2948/104/10","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The article discusses the problem of fires as a serious threat to life, economy and ecosystems, highlighting the need for early detection and suppression of fires. The potential of the combination of Earth remote sensing and neural networks for rapid and accurate detection of natural fires is studied. The significance of applying artificial intelligence, the development of deep learning methods for neural network models, to analyze space images and detect early signs of fires is emphasized. The article also provides examples of successful projects and research in the field of wildfire detection. The final part of the paper emphasizes the need for further research and development of neural network training methods, expansion of training datasets and improvement of space imagery acquisition technologies for effective control and prevention of fires, in order to protect the environment and minimize damage to people.