The Habitat Map of Switzerland: A Remote Sensing, Composite Approach for a High Spatial and Thematic Resolution Product

Abstract

Habitat maps at high thematic and spatial resolution and broad extents are fundamental tools for biodiversity conservation, the planning of ecological networks and the management of ecosystem services. To derive a habitat map for Switzerland, we used a composite methodology bringing together the best available spatial data and distribution models. The approach relies on the segmentation and classification of high spatial resolution (1m) aerial imagery. Land cover data, as well as habitat and species distribution models built on Earth observation data from Sentinel 1 and 2, Landsat, Planetscope and LiDAR, inform the rule-based classification to habitats defined by the hierarchical Swiss Habitat Typology (TypoCH). A total of 84 habitats in 32 groups and 9 overarching classes are mapped in a spatially explicit manner across Switzerland. Validation and plausibility analysis with four independent datasets show that the mapping is broadly plausible, with good accuracy for most habitats, although with lower performance for fine-scale and linear habitats, habitats with restricted geographical distributions and those predominantly characterised by understorey species, especially forest habitats. The resulting map is a vector dataset available for interactive viewing and download from The resulting map is a vector dataset available for interactive viewing and download from the open EnviDat data sharing platform and the open EnviDat data sharing platform. The methodology is semi-automated to allow for updates over time.

Archetypes of social-ecological-technological systems for managing ecological infrastructure

“…Assuming that there will not be significant changes in the way EI is managed, we used the LULC predictions for 2060 as a proxy to represent the expected change in each archetype. We further analyzed the current habitat distribution (Price et al 2021) in the archetypes according to the habitat classification of Switzerland (Delarze et al 2015) by looking at the average percentage cover of habitats within each archetype. Lastly, the distribution of biodiversity, represented by the proportion of species richness (Honeck et al 2020) and the values of ecological connectivity based on the red deer (Cervus elaphus) using circuit theory (Honeck et al 2020) were normalized and analyzed across all archetypes by calculating the average percentages within each archetype (appendix C).…”

A family of process-based models to simulate landscape use by multiple taxa

“…This is particularly problematic if poorly detected, small or ephemeral habitat features are essential resources for seeding populations in the digitised landscape but missing from input landcover data. Incorporating on-the-ground survey information, structural descriptors from LiDAR data and future advances in very high resolution remote-sensing may help to address this issue and increase predictive power (Bradter et al 2020;Price et al 2023).…”

trophiCH - a national species-level trophic metaweb of 23k species for Switzerland

“…Firstly, we collected it along with interaction data where available. Secondly, we inferred habitat associations by intersecting species occurrence data 40 with the Habitat Map of Switzerland 131 . We used the st_intersection() function from the sf package 132,133 (version 1.0-15) in R 125 to intersect the point data with the polygonal habitat map.…”