Daniele de Rigo
EC, JRC (IES); POLIMI, DEIB;
Maieutike Research Initiative
Guest Co- Editors:
Margherita Di Leo
EC, JRC (IES); OSGeo Charter
Associate Editor EMS; iEMSs Board
(free software licensing)
Free software programmer;
This paper proposes a semi-quantitative integrated methodology for a robust assessment of soil erosion rates in data-poor regions affected by landslide activity. It combines heuristic, empirical and probabilistic approaches. The architecture might contribute as a novel component to simplify future integrated analyses of the potential impact of wildfires or vegetation types and distributions on sediment transport from water-induced landslides and erosion.
Applying Geospatial Semantic Array Programming for a Reproducible Set of Bioclimatic Indices in Europe
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.
Studying the impacts of climate change requires looking at ranges of variables that transect a broad range of sectors. Geospatial Semantic Array Programming (GeoSemAP) offers the potential to help create a cross-discipline vocabulary for discussing data and processes used in geospatial studies. Within this field, the PESETA II project offers an example of how GeoSemAPs can be used to address the ecological challenges associated with a shifting climate.