M. V. Platonova, V. D. Kotler, A. V. Kukharskii, S. Y. Ivanov
{"title":"碳循环:用于森林生态系统监测实例的静电除尘器和无人飞行器数据处理方法","authors":"M. V. Platonova, V. D. Kotler, A. V. Kukharskii, S. Y. Ivanov","doi":"10.18303/2619-1563-2023-4-45","DOIUrl":null,"url":null,"abstract":"The review article provides a comprehensive overview of modern methods and approaches for processing large volumes of observational data in the context of monitoring forest ecosystems. The article shows examples of processing various data obtained using Earth remote sensing (ERS) and unmanned aerial vehicles (UAVs). Particular attention is paid to assessing the carbon cycle; the practice of using machine learning methods in processing monitoring data is also discussed in detail, as they play a key role in increasing the accuracy of the resulting estimates. The article also discusses modern geographic information systems designed for complex analysis of data from various natural complexes.","PeriodicalId":190530,"journal":{"name":"Russian Journal of Geophysical Technologies","volume":"43 24","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Carbon cycle: ESP and UAV data processing approaches for forest ecosystem monitoring examples\",\"authors\":\"M. V. Platonova, V. D. Kotler, A. V. Kukharskii, S. Y. Ivanov\",\"doi\":\"10.18303/2619-1563-2023-4-45\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The review article provides a comprehensive overview of modern methods and approaches for processing large volumes of observational data in the context of monitoring forest ecosystems. The article shows examples of processing various data obtained using Earth remote sensing (ERS) and unmanned aerial vehicles (UAVs). Particular attention is paid to assessing the carbon cycle; the practice of using machine learning methods in processing monitoring data is also discussed in detail, as they play a key role in increasing the accuracy of the resulting estimates. The article also discusses modern geographic information systems designed for complex analysis of data from various natural complexes.\",\"PeriodicalId\":190530,\"journal\":{\"name\":\"Russian Journal of Geophysical Technologies\",\"volume\":\"43 24\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Russian Journal of Geophysical Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18303/2619-1563-2023-4-45\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Russian Journal of Geophysical Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18303/2619-1563-2023-4-45","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Carbon cycle: ESP and UAV data processing approaches for forest ecosystem monitoring examples
The review article provides a comprehensive overview of modern methods and approaches for processing large volumes of observational data in the context of monitoring forest ecosystems. The article shows examples of processing various data obtained using Earth remote sensing (ERS) and unmanned aerial vehicles (UAVs). Particular attention is paid to assessing the carbon cycle; the practice of using machine learning methods in processing monitoring data is also discussed in detail, as they play a key role in increasing the accuracy of the resulting estimates. The article also discusses modern geographic information systems designed for complex analysis of data from various natural complexes.