Table 3 Remote sensing products used for habitat modelling and mapping at 100 m resolution.
From: EUNIS habitat maps: enhancing thematic and spatial resolution for Europe through machine learning
Type | Predictor | Spatial coverage, native resolution & temporal range | Data source |
|---|---|---|---|
Vegetation phenology and productivity | Europe, 10 m 2017–2021 | Copernicus Land Monitoring Service (CLMS)81 | |
LENGTH: Length of season (number of days between start and end)82 | |||
LSLOPE: Slope of the green-up season (PPI × day-1)83 | |||
Leaf area Index | LAI_SUMMER: Leaf area index in summer (m²/m²) | Global, 300 m 2014–2021 | Copernicus Land Monitoring Service (CLMS)86 |
LAI_SPRING: Leaf area index in spring (m²/m²) | |||
Inundation | INUND_SEASON: Inundation seasonality | Global, 100 m 1984–2021 | High-resolution mapping of global surface water and its long-term changes54 |
Canopy structure | TCD: Tree canopy cover density (%) | Europe, 10 m 2020 | Copernicus Land Monitoring Service (CLMS)87 |
CANOPY_HEIGHT: Height of the tree canopy (m) | Global, 10 m 2020 | Lang et al.52 | |
Land cover | Proportion (%) of pixels of each landcover class in a 100 m radius | Global, 10 m 2020 | ESA WorldCover55 |
