Articles | Volume 16, issue 6
https://doi.org/10.5194/essd-16-2877-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-2877-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
20 Jun 2024
Data description paper |
| 20 Jun 2024
| 20 Jun 2024
Map of forest tree species for Poland based on Sentinel-2 data
Ewa Grabska-Szwagrzyk
CORRESPONDING AUTHOR
Institute of Geography and Spatial Management, Jagiellonian University, Gronostajowa 7, 30-387 Kraków, Poland
Dirk Tiede
Department of Geoinformatics – Z_GIS, University of Salzburg, Schillerstr. 30, 5020 Salzburg, Austria
Martin Sudmanns
Department of Geoinformatics – Z_GIS, University of Salzburg, Schillerstr. 30, 5020 Salzburg, Austria
Jacek Kozak
Institute of Geography and Spatial Management, Jagiellonian University, Gronostajowa 7, 30-387 Kraków, Poland
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Cited
16 citations as recorded by crossref.
- Mapping Nine Dominant Tree Species in the Korean Peninsula Using U-Net and Harmonic Analysis of Sentinel-2 Imagery J. Lee et al. 10.7780/kjrs.2025.41.2.1.1
- What can Sentinel-2 time series tell us about the phenology of dominant deciduous tree species in Poland? E. Grabska et al. 10.1093/forestry/cpaf064
- Forest practitioners’ requirements for remote sensing-based canopy height, wood-volume, tree species, and disturbance products F. Fassnacht et al. 10.1093/forestry/cpae021
- A Sentinel-2 machine learning dataset for tree species classification in Germany M. Freudenberg et al. 10.5194/essd-17-351-2025
- TS2GNet: A temporal–spatial–spectral multidomain guided network for classifying hyperspectral tree species using multiseason satellite imagery K. Xu et al. 10.1016/j.jag.2025.104715
- Tree species from space: a new product for Germany based on Sentinel-1 and -2 time series M. Wegler et al. 10.1080/01431161.2025.2530236
- Comparison of Sentinel-2 Multitemporal Approaches for Tree Species Mapping Within Natura 2000 Riparian Forest Y. Rueva et al. 10.3390/rs17183194
- Temporal generalization in evergreen leaf type classification using tailored Sentinel-2 composites P. Hofinger et al. 10.1016/j.ecoinf.2025.103167
- Mapping tree species fractions in temperate mixed forests using Sentinel-2 time series and synthetically mixed training data D. Klehr et al. 10.1016/j.rse.2025.114740
- A Novel Large Vision Foundation Model-Based Approach for Generating High-Resolution Canopy Height Maps in Plantations for Precision Forestry Management S. Tan et al. 10.34133/remotesensing.0880
- Comprehensive mapping of individual living and dead tree species using leaf-on and leaf-off ALS and CIR data in a complex temperate forest M. Lisiewicz et al. 10.1093/forestry/cpaf007
- Sentinel-2 vs. PlanetScope: Comparison and combination for tree species classification in two central European forest ecosystems A. Daryaei et al. 10.1016/j.rsase.2025.101617
- Map of forest tree species for Poland based on Sentinel-2 data E. Grabska-Szwagrzyk et al. 10.5194/essd-16-2877-2024
- Classification of Tree Species in Poland Using CNNs Tabular-to-Pseudo Image Approach Based on Sentinel-2 Annual Seasonality Data Ł. Mikołajczyk et al. 10.3390/f16071039
- Multi-indicator deterministic model based on time series of Sentinel-2, to assess the degree of natural succession on the abandoned arable areas M. Kozak et al. 10.2478/cag-2024-0017
- Map of forest tree species for Poland based on Sentinel-2 data E. Grabska-Szwagrzyk et al. 10.5194/essd-16-2877-2024
15 citations as recorded by crossref.
- Mapping Nine Dominant Tree Species in the Korean Peninsula Using U-Net and Harmonic Analysis of Sentinel-2 Imagery J. Lee et al. 10.7780/kjrs.2025.41.2.1.1
- What can Sentinel-2 time series tell us about the phenology of dominant deciduous tree species in Poland? E. Grabska et al. 10.1093/forestry/cpaf064
- Forest practitioners’ requirements for remote sensing-based canopy height, wood-volume, tree species, and disturbance products F. Fassnacht et al. 10.1093/forestry/cpae021
- A Sentinel-2 machine learning dataset for tree species classification in Germany M. Freudenberg et al. 10.5194/essd-17-351-2025
- TS2GNet: A temporal–spatial–spectral multidomain guided network for classifying hyperspectral tree species using multiseason satellite imagery K. Xu et al. 10.1016/j.jag.2025.104715
- Tree species from space: a new product for Germany based on Sentinel-1 and -2 time series M. Wegler et al. 10.1080/01431161.2025.2530236
- Comparison of Sentinel-2 Multitemporal Approaches for Tree Species Mapping Within Natura 2000 Riparian Forest Y. Rueva et al. 10.3390/rs17183194
- Temporal generalization in evergreen leaf type classification using tailored Sentinel-2 composites P. Hofinger et al. 10.1016/j.ecoinf.2025.103167
- Mapping tree species fractions in temperate mixed forests using Sentinel-2 time series and synthetically mixed training data D. Klehr et al. 10.1016/j.rse.2025.114740
- A Novel Large Vision Foundation Model-Based Approach for Generating High-Resolution Canopy Height Maps in Plantations for Precision Forestry Management S. Tan et al. 10.34133/remotesensing.0880
- Comprehensive mapping of individual living and dead tree species using leaf-on and leaf-off ALS and CIR data in a complex temperate forest M. Lisiewicz et al. 10.1093/forestry/cpaf007
- Sentinel-2 vs. PlanetScope: Comparison and combination for tree species classification in two central European forest ecosystems A. Daryaei et al. 10.1016/j.rsase.2025.101617
- Map of forest tree species for Poland based on Sentinel-2 data E. Grabska-Szwagrzyk et al. 10.5194/essd-16-2877-2024
- Classification of Tree Species in Poland Using CNNs Tabular-to-Pseudo Image Approach Based on Sentinel-2 Annual Seasonality Data Ł. Mikołajczyk et al. 10.3390/f16071039
- Multi-indicator deterministic model based on time series of Sentinel-2, to assess the degree of natural succession on the abandoned arable areas M. Kozak et al. 10.2478/cag-2024-0017
1 citations as recorded by crossref.
Latest update: 29 Oct 2025
Short summary
We accurately mapped 16 dominant tree species and genera in Poland using Sentinel-2 observations from short periods in spring, summer, and autumn (2018–2021). The classification achieved more than 80% accuracy in country-wide forest species mapping, with variation based on species, region, and observation frequency. Freely accessible resources, including the forest tree species map and training and test data, can be found at https://doi.org/10.5281/zenodo.10180469.
We accurately mapped 16 dominant tree species and genera in Poland using Sentinel-2 observations...
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