Forest canopy mortality during the 2018-2020 summer drought years in Central Europe: The application of a deep learning approach on aerial images across Luxembourg
Efficient monitoring of tree canopy mortality requires data that cover large areas and capture changes over time while being precise enough to detect changes at the canopy level. In the development of automated approaches, aerial images represent an under-exploited scale between high-resolution drone images and satellite data. Our aim herein was to use a deep learning model to automatically detect canopy mortality from high-resolution aerial images after severe drought events in the summers 2018–2020 in Luxembourg. We analysed canopy mortality for the years 2017–2020 using the EfficientUNet++,... Mehr ...
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Dokumenttyp: | doc-type:article |
Erscheinungsdatum: | 2024 |
Schlagwörter: | tree canopy mortality / monitoring / deep learning / ddc:550 |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-29520963 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://refubium.fu-berlin.de/handle/fub188/41738 |