Mapping forest tree species and pixel-level uncertainty using satellite observations and Swedish National Forest Inventory data

Description This repository contains the data, scripts, and documentation supporting the study “Mapping forest tree species and pixel-level uncertainty using satellite observations and Swedish National Forest Inventory data” by Abdulhakim Abdi and Fan Wang. The materials include tree species classification raster, a pixel-level entropy raster representing classification uncertainty, and spatially continuous, entropy-weighted tree species, as wel as the R implementation for deriving these fractions. Together, these resources enable large-area analyses of forest composition, uncertainty propagation, and the spatial characterization of forest stands across southern Sweden. Contents TreeSpecies_Classification_XGB.tif — Discrete raster (8-bit unsigned integer) of dominant tree species predicted by an XGBoost model trained on Sentinel-1/2 and topographic data. TreeSpecies_Entropy_XGB.tif — Continuous raster (16-bit unsigned integer) containing per-pixel Shannon entropy values (0–Hmax), quantifying classification uncertainty. Weighted_Fraction_XXXX.tif (XXXX = Tree species) — Continuous rasters (Float32, 0–100%) representing local, entropy-weighted fractional cover of each tree species computed within a moving Gaussian window. Each file corresponds to one of the eight dominant species (Norway spruce, Scots pine, Birch, Beech, Oak, Alder, Aspen, and Other species). An additional “Weighted_Fraction_Unknown.tif” layer represents the proportion of unclassified or masked pixels within the window. TreeSpecies_FractionMapping.R — R script that computes local (moving-window) species fractions with optional entropy weighting, producing 0–100% fractional cover maps for each species and an additional “Unknown” fraction layer. Spatial characteristics Property Specification Geographic coverage Southern Sweden (Skåne, Blekinge, Halland, Kronoberg, Jönköping, and Kalmar counties) Extent 307020, 6132480 : 609300, 6450120 (EPSG:3006 – SWEREF99 TM) Projection Projected (UTM), units in meters Spatial resolution 10 × 10 m Raster dimensions 30,228 × 31,764 pixels Origin 307020, 6,450,120