Remote sensing & climate modeling

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The aim of this sub-project is to generate spatially explicit input data for the modelling of GHG emissions from peatlands by means of innovative remote sensing techniques and to deliver climate data and climate projections.


Remote sensing

Manmade drainage and climate change induced drying up of peatlands leads to the oxidation of organic matter, which in turn brings along the emission of large amounts of GHGs and the subsidence of the peat surface. Monitoring the surface movement of peatlands provides therefore information on their emissions. To accomplish this task, we apply interferometric techniques to Sentinel 1 synthetic aperture radar data that are able to detect lifting and subsidence within a mm accuracy. The applied methods are the Persistent Scatterer Interferometry (Ferretti et al 2000, 2001) and the Small Baseline approach (Berardino et al. 2002). Besides, Sentinel 1 satellite data is used to derive the mowing dates of grassland on cultivated peatlands which represent an important information for the modelling of GHG emissions.
A cloud-computing based approach is further applied to extract NDVI time series over whole Bavaria from optical Sentinel 2 satellite data. Seasonal dynamics of the vitality of the peatland vegetation can be detected by this means. Finally, we derive spatially explicit evapotranspiration maps from optical LANDSAT data which are used to validate the hydrological models in sub-project 2.


Mean line-of-sight (LOS) velocity [mm/year] of the peatland surface in Schechenfilz and Weidfilz for the year 2018

Regional climate projections

This subproject provides observed meteorological data and climate projections for the modelling activities in the other subprojects. Regarding the historical period, the meteorological reference dataset SDCLIREF is available which was developed at the Department of Geography of LMU. In addition, 10 simulations out of the climate model large ensemble CRCM5-LE (Leduc et al. 2019) can be provided for the period 1980-2099. This data set is an output of the ClimEx project (funded by the Bavarian StMUV). Each simulation is run with slightly different initialisation parameters which lead to different manifestations of the same climate. This allows to reproduce the natural variability of the climate system. The climate projections for the future are based on the emission scenario RCP8.5 (Representative Concentration Pathway), the most extreme scenario available for which a strong temperature increase and reduction of summer precipitations is expected over whole Bavaria. By this means, it is possible to simulate situations of severe stress for the peatlands.


Mean monthly precipitation sums and average temperatures for the Schechenfilz for the period 1950-1999 compared to 2018, which was remarkably dry


Team of project 4

Ludwig-Maximilians University
Department of Geography
Research and teaching unit "Physical Geography and Remote Sensing"

  • Prof. Dr. Ralf Ludwig

  • Dr. Philip Marzahn

  • Dr. Verena Huber García