Pia Labenski

  • Karlsruher Institut für Technologie (KIT)
    Institut für Geographie und Geoökologie
    Kaiserstr. 12
    76131 Karlsruhe


  • Multispectral and LiDAR remote sensing
  • Machine and deep learning algorithms
  • Fuel and fire modeling for Central European forests


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. doi:10.1093/forestry/cpad026
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. doi:10.1016/j.rse.2023.113711
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, Article no: 102799. doi:10.1016/j.jag.2022.102799VolltextVolltext der Publikation als PDF-Dokument