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Prof. Dr. Fabian Fassnacht


Institute of Geographical Sciences

Remote Sensing and Geoinformatics


Malteserstraße 74-100
Room H057
12249 Berlin

Office hours

Sprechstunde: wird noch bekanntgegeben
Office hour: tbd

Short CV

Since 04/2022: Professor for Remote Sensing and Geoinformatics, Institute of Geographical Sciences, Freie Universität Berlin

2021: Editor-in-Chief Forestry: An International Journal of Forest Research (OUP, Institute of Chartered Foresters)

2020: Senior Scientist, Institute of Geography and Geoecology, Karlsruhe Institute of Technology

2017+2019: Chinese Academy of Sciences President’s International Fellowship Initiative scholarship as visiting researcher, Northwest Institute of Plateau Biology, Xining, China.

2016: Associate Editor Forestry: An International Journal of Forest Research (OUP, Institute of Chartered Foresters)

2015: Fulbright visiting scholar scholarship to visit Colorado State University, USA

2014: Lecturer/PostDoc, Institute of Geography and Geoecology, Karlsruhe Institute of Technology

Since 2013: Guest lecturer at the Universidad de Chile, Chile.

2012: Research visit Universidad de Chile, Chile.

2010-2014: PhD University of Freiburg “Assessing the potential of imaging spectroscopy data to map tree species composition and bark beetle-related tree mortality”

SS 2022:

  • VL und PC-S Geographische Informationssysteme (BSc)
  • Projekt I WP Modul (MSc)

Research interest and expertise:

  • Applying remote sensing data to understand ecological patterns and processes of vegetation ecosystems
  • Understanding the link between vegetation traits and remotely sensed data
  • Development of work-flows to quantify and map forest attributes using remote sensing data
  • Work-flow development in the field of remote sensing to support a range of application fields including for example forest inventories, wildfire risk assessment, prevention and mitigation of grassland degradation
  • Development of concepts and work-flows to create synthetic remote sensing data enabling an improved understanding of the link between remotely sensed data and the addressed target variable

Project coordination and project proposals

  • FORZA - Reconstruction of FORest decline processes in the ZAgros forests of Western Iran using remote sensing and dendrochronology [Principal Investigator], 07/2020-06/2022, BMBF.
  • INSANE – INnovative Spatial information products for forest Applications using NEw satellite technologies [Principal Investigator], 04/2020-12/2021, DAAD.
  • Erweiterung des ökologischen, waldbaulichen und technischen Wissens zu Waldbränden (ErWiN); Teilvorhaben 1: Verbessertes Verständnis der Waldbranddynamik in deutschen Wäldern mittels Deep Learning und Feuerausbreitungssimulationen [Principal Investigator & Project coordinator] 06/2020-09/2023, Fachagentur Natürliche Rohstoffe e.V..
  • Regional Monitoring and Modeling of the Effects of Vegetation Restoration on Soil Erosion [Principal Investigator], 02/2019-06/2019, Chinesisch-Deutsches Zentrum für Wissenschaftsförderung (Workshop-Förderung).
  • SYSSIFOSS - Synthetic structural remote sensing data for improved forest inventory models [Principal Investigator], 05/2019-10/2022, DFG.
  • Assessing spatio-temporal impacts of global change on water and biomass production processes at catchment scale: a synergistic approach based on remote sensing and coupled hydrological models to improve sustainable management of forest ecosystems [Co-Investigator], 01/2017-03/2021 FONDECYT (Chile).
  • SaMovar - Satellite-based Monitoring of invasive species in central-Chile [Principal Investigator], 01/2016-06/2017, BMWi/DLR
  • Modellierung der klimatischen Standorteignung forstlich relevanter Baumarten [Co-Investigator], 01/2015 – 12/2016, LUBW / KLIMOPASS 37
  • WaldBiomasse [actively involved in project proposal], 05/2013-10/2015, BMWi/DLR.
  • ForestHype [actively involved in project proposal]07/2010-06/2013, BMWi/DLR.

Complete lists at:






Selected publications:

Labenski, P., Ewald, M., Schmidtlein, S., Heinsch, F.A., Fassnacht, F.E. (2023). Quantifying surface fuels for fire modelling in temperate forests using airborne lidar and Sentinel-2: potential and limitations. Remote Sensing of Environment, 295, 113711.

Fassnacht, F. E.; White, J.C.; Wulder, M.A.; Næsset, E. (2023) Remote sensing in forestry: current challenges, considerations and directions. Forestry - An International Journal of Forest Research. cpad024 https://doi.org/10.1093/forestry/cpad024

Ewald, M.; Labenski, P.; Westphal, E.; Metzsch-Zilligen, E.; Großhauser, M.; Fassnacht, F.E., 2023. Leaf litter combustion properties of Central European tree species. Forestry: An International Journal of Forest Research, cpad026

Schäfer, J.; Weiser, H.; Winiwarter, L.; Höfle, B.; Schmidtlein, S.; Fassnacht, F.E. (2023). Generating synthetic laser scanning data of forests by combining forest inventory information, a tree point cloud database and an open-source laser scanning simulator. Forestry - An International Journal of Forest Research. cpad006 https://doi.org/10.1093/forestry/cpad006

Weiser, H.; Schäfer, J.; Winiwarter, L.; Krašovec, N.; Fassnacht, F.E.; Höfle, B. (2022). Individual tree point clouds and tree measurements from multi-platform laser scanning in German forests. Earth System Science Data 14 (7), 2989-3012

Labenski, P.; Ewald, M.; Schmidtlein, S.; Fassnacht, F.E. (2022). Classifying surface fuel types based on forest stand photographs and satellite time series using deep learning. International Journal of Applied Earth Observation and Geoinformation, 109, 102799.

Fassnacht, F.E.; Müllerova, J.; Conti, L.; Malavasi, M.; Schmidtlein, S. (2022). About the link between spectral variation and biodiversity. Applied Vegetation Science, https://doi.org/10.1111/avsc.12643

Fassnacht, F. E.; Schmidt-Riese, E.; Kattenborn, T.; Hernández, J. (2021). Explaining Sentinel 2-based dNBR and RdNBR variability with reference data from the bird’s eye (UAS) perspective. International Journal of Applied Earth Observation and Geoinformation, 95, Article no: 102262. doi:10.1016/j.jag.2020.102262

Shafeian, E.; Fassnacht, F. E.; Latifi, H. (2021). Mapping fractional woody cover in an extensive semi-arid woodland area at different spatial grains with Sentinel-2 and very high-resolution data. International Journal of Applied Earth Observation and Geoinformation, 105, Art.-Nr.: 102621.

Li, L.; Fassnacht, F. E.; Bürgi, M. (2021). Using a landscape ecological perspective to analyze regime shifts in social–ecological systems: a case study on grassland degradation of the Tibetan Plateau. Landscape Ecology. doi:10.1007/s10980-021-01191-0

Senn, J. A.; Fassnacht, F. E.; Eichel, J.; Seitz, S.; Schmidtlein, S. (2020). A new concept for estimating the influence of vegetation on throughfall kinetic energy using aerial laser scanning. Earth Surface Processes and Landforms, 45 (7), 1487–1498. doi:10.1002/esp.4820

Modzelewska, A.; Fassnacht, F. E.; Stereńczak, K. (2020). Tree species identification within an extensive forest area with diverse management regimes using airborne hyperspectral data. International journal of applied earth observation and geoinformation, 84, Art.-Nr. 101960. doi:10.1016/j.jag.2019.101960

Kattenborn, T.; Fassnacht, F. E.; Schmidtlein, S. (2019). Differentiating plant functional types using reflectance: which traits make the difference?. Remote sensing in ecology and conservation, 5 (1), 5–19. doi:10.1002/rse2.86

Kattenborn, T.; Lopatin, J.; Förster, M.; Braun, A. C.; Fassnacht, F. E. (2019). UAV data as alternative to field sampling to map woody invasive species based on combined Sentinel-1 and Sentinel-2 data. Remote Sensing of Environment, 227, 61–73. doi:10.1016/j.rse.2019.03.025

Fassnacht, F. E.; Latifi, H.; Hartig, F. (2018). Using synthetic data to evaluate the benefits of large field plots for forest biomass estimation with LiDAR. Remote Sensing of Environment, 213, 115–128. doi:10.1016/j.rse.2018.05.007

Fassnacht, F. E.; Latifi, H.; Stereńczak, K.; Modzelewska, A.; Lefsky, M.; Waser, L. T.; Straub, C.; Ghosh, A. (2016). Review of studies on tree species classification from remotely sensed data. Remote Sensing of Environment, 186, 64–87. doi:10.1016/j.rse.2016.08.013

Fassnacht, F. E.; Latifi, H.; Ghosh, A.; Joshi, P. K.; Koch, B. (2014). Assessing the potential of hyperspectral imagery to map bark beetle-induced tree mortality. Remote Sensing of Environment, 140, 533–548. doi:10.1016/j.rse.2013.09.014

Fassnacht, F. E.; Hartig, F.; Latifi, H.; Berger, C.; Hernandez, J.; Corvalan, P.; Koch, B. (2014). Importance of sample size, data type and prediction method for remote sensing-based estimations of aboveground forest biomass. Remote Sensing of Environment, 154 (1), 102–114. doi:10.1016/j.rse.2014.07.028