Bioclimate-driven regression analysis is a widely used approach for modelling
ecological niches and zonation. Although the bioclimatic complexity of the
European continent is high, a particular combination of 12 climatic and
topographic covariates was recently found able to reliably reproduce the
ecological zoning of the Food and Agriculture Organization of the United
Nations (FAO) for forest resources assessment at pan-European scale, generating
the first fuzzy similarity map of FAO ecozones in Europe. The reproducible
procedure followed to derive this collection of bioclimatic indices is now
presented. It required an integration of data-transformation modules (D-TM)
using geospatial tools such as Geographic Information System (GIS) software,
and array-based mathematical implementation such as semantic array programming
(SemAP). Base variables, intermediate and final covariates are described and
semantically defined by providing the workflow of D-TMs and the mathematical
formulation following the SemAP notation. Source layers to derive base
variables were extracted by exclusively relying on global-scale public open
geodata in order for the same set of bioclimatic covariates to be reproducible
in any region worldwide. In particular, two freely available datasets were
exploited for temperature and precipitation (WorldClim) and elevation (Global
Multi-resolution Terrain Elevation Data). The working extent covers the
European continent to the Urals with a resolution of 30 arc-second. The
proposed set of bioclimatic covariates will be made available as open data in
the European Forest Data Centre (EFDAC). The forthcoming complete set of D-TM
codelets will enable the 12 covariates to be easily reproduced and expanded
through free software.Comment: 10 pages, 4 figures, 1 table, published in IEEE Earthzine 2014 Vol. 7
Issue 2, 877975+ 2nd quarter theme. Geospatial Semantic Array Programming.
Available: http://www.earthzine.org/?p=87797