Table 4 F1-score, precision and recall from the ensemble forecasting models for the EVA and the three validation datasets: Netherlands (NL), Austria (AT) and the French Forest Inventory (IFN).
From: EUNIS habitat maps: enhancing thematic and spatial resolution for Europe through machine learning
Strategy | F1-score | Precision | Recall | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
EVA | NL | AT | IFN | EVA | NL | AT | IFN | EVA | NL | AT | IFN | |
MA2 - Littoral biogenic habitats | 0.87 ± 0.11 | 0.76 ± 0.34 | 0.82 ± 0.18 | 0.74 ± 0.33 | 0.95 ± 0.06 | 0.80 ± 0.36 | ||||||
N – coastal habitats | 0.81 ± 0.09 | 0.82 ± 0.09 | 0.75 ± 0.15 | 0.84 ± 0.06 | 0.92 ± 0.07 | 0.83 ± 0.18 | ||||||
Q – Wetlands | 0.73 ± 0.13 | 0.95 ± 0.06 | 0.56 ± 0.46 | 0.67 ± 0.19 | 0.95 ± 0.08 | 0.55 ± 0.45 | 0.86 ± 0.09 | 0.96 ± 0.07 | 0.57 ± 0.46 | |||
R – Grasslands | 0.66 ± 0.17 | 0.40 ± 0.32 | 0.37 ± 0.35 | 0.78 ± 0.15 | 0.57 ± 0.42 | 0.45 ± 0.39 | 0.59 ± 0.18 | 0.37 ± 0.33 | 0.37 ± 0.36 | |||
S - Scrub and Tundra | 0.83 ± 0.12 | 0.46 ± 0.39 | 0.31 ± 0.42 | 0.89 ± 0.06 | 0.49 ± 0.41 | 0.31 ± 0.42 | 0.79 ± 0.15 | 0.46 ± 0.41 | 0.31 ± 0.43 | |||
T – Forests | 0.61 ± 0.20 | 0.38 ± 0.31 | 0.33 ± 0.39 | 0.48 ± 0.32 | 0.77 ± 0.15 | 0.47 ± 0.36 | 0.34 ± 0.40 | 0.78 ± 0.32 | 0.55 ± 0.23 | 0.37 ± 0.35 | 0.32 ± 0.39 | 0.40 ± 0.33 |
U - Sparsely vegetated | 0.94 ± 0.03 | 0.81 ± 0.22 | 0.35 ± 0.40 | 0.95 ± 0.03 | 0.96 ± 0.05 | 0.34 ± 0.39 | 0.94 ± 0.03 | 0.78 ± 0.31 | 0.36 ± 0.23 | |||