Map of forest tree species for Poland based on Sentinel-2 data

Abstract

Abstract. Accurate information on forest tree species composition is vital for various scientific applications, as well as for forest inventory and management purposes. Country-wide, detailed species maps are a valuable resource for environmental management, conservation, research, and planning. Here, we performed the classification of 16 dominant tree species and genera in Poland using time series of Sentinel-2 imagery. To generate comprehensive spectral–temporal information, we created Sentinel-2 seasonal aggregations known as spectral–temporal metrics (STMs) within the Google Earth Engine (GEE). STMs were computed for short periods of 15–30 d during spring, summer, and autumn, covering multi-annual observations from 2018 to 2021. The Polish Forest Data Bank served as reference data, and, to obtain robust samples with pure stands only, the data were validated through automated and visual inspection based on very-high-resolution orthoimagery, resulting in 4500 polygons serving as training and test data. The forest mask was derived from available land cover datasets in GEE, namely the ESA WorldCover and Dynamic World dataset. Additionally, we incorporated various topographic and climatic variables from GEE to enhance classification accuracy. The random forest algorithm was employed for the classification process, and an area-adjusted accuracy assessment was conducted through cross-validation and test datasets. The results demonstrate that the country-wide forest stand species mapping achieved an accuracy exceeding 80 %; however, this varies greatly depending on species, region, and observation frequency. We provide freely accessible resources, including the forest tree species map and training and test data: https://doi.org/10.5281/zenodo.10180469 (Grabska-Szwagrzyk, 2023a).