Geodiversity data for Europe at 1-km and 10-km resolutions

The European geodiversity data provides a novel perspective on the
diversity of non-living nature over large spatial extents. These data
describe geological, pedological, geomorphological, and hydrological
diversity, including 78 different geofeatures. Geofeatures refer to
individual features that each component of geodiversity (geology,
pedology, geomorphology, and hydrology) consists of, such as soil types in
the case of pedology. This standardized and accessible geodiversity
dataset facilitates comparability for geodiversity research across Europe
and can be used for multiple purposes, from studying geodiversity patterns
to geodiversity–biodiversity relationship and more. Moreover, the
methodology (described in Toivanen et al. 2024) establishes a grid-based
approach for quantifying geodiversity, which is suitable for large extents
and can be applied in other regions worldwide. This grid-based
geodiversity dataset, available at resolutions of 1-km and 10-km, includes
ready-to-use georichness variables (as GEOtiff files), and provides
information on the presence and coverage of individual geofeatures that
can be used to calculate different measures of geodiversity (as csv
files). The data on georichness can be utilized in its entirety,
representing the overall geodiversity, or with selected geodiversity
components as individual richness layers describing geological,
pedological, geomorphological or hydrological feature richness. One key
objective of this geodiversity data is to provide complimentary
environmental variables for biodiversity modelling and conservation
studies. However, the choice of geodiversity data (richness or other
index), the scale of analysis (1-km or 10-km), and the specific variables
(overall geodiversity or individual components) should be determined by
the research question and context. This is a dataset from: Toivanen, M. et
al. (2024). Geodiversity data for Europe. Philosophical Transactions of
the Royal Society A. https://dx.doi.org/10.1098/rsta.2023.0173 (accepted
for publication 2023-10-19)