EGU General Assembly 2022
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

High-resolution sensing of alpine vegetation location properties by multi-source earth observation techniques

Martin Rutzinger1, Andreas Kollert1, Andreas Mayr1, Lukas Müller1, Benedikt Hiebl1, Magnus Bremer1,2, and Stefan Dullinger3
Martin Rutzinger et al.
  • 1Department of Geography, University of Innsbruck, Innsbruck, Austria (
  • 2Institute for Interdisciplinary Mountain Research, Austrian Academy of Sciences, Innsbruck, Austria (
  • 3Department of Botany and Biodiversity Research, University of Vienna, Vienna, Austria (

Vegetation cover and plant species distribution in high mountain regions strongly depend on climatic, topographic, and geomorphic conditions, which often vary at small spatial scales. This contribution presents a concept and first results for producing high-resolution maps of soil and surface temperature, snow cover and geomorphic disturbance. These datasets will allow us to infer a variety of variables key to alpine plant life, such as temperature sums and their seasonal variation as well as timing and duration of snow cover. Close-range and satellite remote sensing time-series are used in combination with extended fieldwork and meteorological records to bridge different acquisition scales in space and time. Analysis and modeling will benefit from a high-density sampling scheme for soil temperature, snow cover and vegetation that balances the statistical representation of study site properties (such as topography and vegetation cover) against practical limitations, such as site accessibility in high-alpine environments. By integrating micro-scale location properties with existing and newly developed process models, we strive to get a better understanding of how micro-, local-, or regional factors, and the interaction among these, govern the distribution of alpine flora now and in a warming climate.


This work has been conducted within the MICROCLIM project (, which has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 883669).

How to cite: Rutzinger, M., Kollert, A., Mayr, A., Müller, L., Hiebl, B., Bremer, M., and Dullinger, S.: High-resolution sensing of alpine vegetation location properties by multi-source earth observation techniques, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7040,, 2022.