The Polar Terrestrial Environmental Systems Research Group at the Alfred-Wegener-Institut has multiple field trips a year that, among other goals, aim to collect data to monitor the landcover and vegetation dynamics in the Arctic region. Vegetation dynamics can provide an insight into the effects of global warming on the environment. The aim of the current project is to employ Machine Learning and Deep learning methods to analyse this data to gain better insights into the dynamics of the vegetation species and how these are changing over time. In order to accomplish this goal, various types of Remote Sensing data is used such as Sentinel-2, Landsat 7/8 as well as drone data collected in the field. The ultimate goal is to develop a fusion method that can utilise the available data to create a comprehensive overview of vegetation dynamics of the past, present and future.
- F. van Geffen, B. Heim, U. Herzschuh, L. Pestryakova, E. Zakharov, R. Hänsch, B. Demir, B. Kleinschmit, M.Förster, and S. Kruse. SiDro Forest: Siberian drone-mapped forest inventory. (Oral presentation), Arctic Science Summit Week, Portugal/Online, 19-26 March 2021.
- F. van Geffen, B. Heim, U. Herzschuh, L. Pestryakova, E. Zakharov, R. Hänsch, B. Demir, B. Kleinschmit, M.Förster, and S. Kruse. SiDro Forest: Siberian drone-mapped forest inventory. (PICO presentation), EGU General Assembly, Online, 19-30 April 2021, EGU21-15106. https://doi.org/10.5194/egusphere-egu21-15106
- F. van Geffen, B. Heim, F. Brieger, R. Geng, I. Shevtsova, L Schulte, S. Stuenzl, N. Bernhardt, E. Troeva, L. Pestryakova, E. Zakharov, B. Pflug, U. Herzschuh, and S. Kruse. SiDroForest: A comprehensive forest inventory of Siberian boreal forest investigations including drone-based point clouds, individually labelled trees, synthetically generated tree crowns and Sentinel-2 labelled image patches. https://essd.copernicus.org/preprints/essd-2021-281/ [Preprint]