Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Luanjie Chen"'
Publikováno v:
Remote Sensing, Vol 16, Iss 1, p 145 (2023)
The increasing frequency and magnitude of landslides underscore the growing importance of landslide prediction in light of factors like climate change. Traditional methods, including physics-based methods and empirical methods, are beset by high cost
Externí odkaz:
https://doaj.org/article/3ad0fe6cb5d3478d976cedb425f18488
Publikováno v:
Remote Sensing, Vol 15, Iss 20, p 4931 (2023)
Present approaches in PV (Photovoltaic) detection are known to be scalable to a larger area using machine learning classification and have improved accuracy on a regional scale with deep learning diagnostics. However, it may cause false detection, ti
Externí odkaz:
https://doaj.org/article/3f438bbff1f546a88d994c99f0614109
Publikováno v:
Remote Sensing, Vol 15, Iss 18, p 4403 (2023)
Currently, there is a wealth of data and expert knowledge available on monitoring agro-meteorological disasters. However, there is still a lack of technical means to organically integrate and analyze heterogeneous data sources in a collaborative mann
Externí odkaz:
https://doaj.org/article/9672ab0490964c888994181239adad14
Publikováno v:
Remote Sensing, Vol 15, Iss 8, p 2126 (2023)
Landslides pose a significant threat to human lives and property, making the development of accurate and reliable landslide prediction methods essential. With the rapid advancement of multi-source remote sensing techniques and machine learning, remot
Externí odkaz:
https://doaj.org/article/cdb4eca9b81d442e81f66fc7951114e4
Publikováno v:
Remote Sensing, Vol 14, Iss 17, p 4391 (2022)
Forest fires destroy the ecological environment and cause large property loss. There is much research in the field of geographic information that revolves around forest fires. The traditional forest fire prediction methods hardly consider multi-sourc
Externí odkaz:
https://doaj.org/article/50ed2584687f4c6489dca3037b21214e
Publikováno v:
Remote Sensing, Vol 14, Iss 14, p 3496 (2022)
Forest fires have frequently occurred and caused great harm to people’s lives. Many researchers use machine learning techniques to predict forest fires by considering spatio-temporal data features. However, it is difficult to efficiently obtain the
Externí odkaz:
https://doaj.org/article/167413375220443d83c46bbceea51b54