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Exploring drought-induced tree mortality in Luxembourg using aerial imagery and environmental data

Schwarz, Selina ORCID iD icon; Haffter, Rosa; Werner, Christian; Fassnacht, Fabian ORCID iD icon; Ruehr, Nadine ORCID iD icon

Abstract (englisch):

The changes in the climate system over the last decades have led to an increase in the frequency of droughts globally. A recent example are the summers of 2018 and 2019 in Central Europe, during which forests suffered under harsh drought conditions. Forests are pivotal for humankind, they cover about 31% of the global land area and are a net sink of about 20% of anthropogenic CO2 emissions. Thus, increases in tree mortality in response to drought extremes can result in large, yet uncertain, feedbacks to the climate system.

Here, we study drought-related tree mortality in response to the European 2018 drought event. More specifically, we seek to identify site and stand characteristics that might lead to higher mortality rates. We use high-resolution orthophotos of the country of Luxembourg and deep learning classification algorithms to create a dataset of tree mortality between 2017 and 2019 for the whole of Luxembourg at individual tree level. To train the image classification algorithm we use a hand delineated data set of ~8.000 dead trees in a catchment area of Luxembourg. We then select data sets of environmental variables related to site characteristics, including Temperature, Precipitation, Soil Type, Ground Water, Forest Type and Topography to explain the variance in tree mortality between 2017 and 2019, using a Generalized Additive Model (GAM).
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Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung – Atmosphärische Umweltforschung (IMK-IFU)
Publikationstyp Vortrag
Publikationsdatum 04.08.2021
Sprache Englisch
Identifikator KITopen-ID: 1000141152
HGF-Programm 12.11.24 (POF IV, LK 01) Adaptation of natural landscapes to climate change
Veranstaltung 4th Ecological Society of America. Annual Meeting (2021), Online, 02.08.2021 – 06.08.2021
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