Pia Labenski
- PhD student
- Group: Vegetation
- pia labenski ∂does-not-exist.kit edu
Karlsruher Institut für Technologie (KIT)
Institut für Geographie und Geoökologie
Kaiserstr. 12
76131 Karlsruhe
Germany
Topics
- Multispectral and LiDAR remote sensing
- Machine and deep learning algorithms
- Fuel and fire modeling for Central European forests
Labenski, P. (2024, June 19). Assessing fuels in European temperate forests and heathlands using remote sensing. PhD dissertation. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000171668
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.2022.102799