Articles | Volume 20, issue 12
Nat. Hazards Earth Syst. Sci., 20, 3455–3483, 2020
Nat. Hazards Earth Syst. Sci., 20, 3455–3483, 2020

Research article 16 Dec 2020

Research article | 16 Dec 2020

INSPIRE standards as a framework for artificial intelligence applications: a landslide example

Gioachino Roberti et al.

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Cited articles

Alvioli, M., Marchesini, I., Reichenbach, P., Rossi, M., Ardizzone, F., Fiorucci, F., and Guzzetti, F.: Automatic delineation of geomorphological slope units with r.slopeunits v1.0 and their optimization for landslide susceptibility modeling, Geosci. Model Dev., 9, 3975–3991,, 2016. a
Alvioli, M., Guzzetti, F., and Marchesini, I.: Parameter-free delineation of slope units and terrain subdivision of Italy, Geomorphology, 358, 107124,, 2020. a
Aristotle: The Categories, 350 BCE. a
Association of Professional Engineers and Geoscientists of British Columbia: Guidelines for Legislated Landslide Assessments for proposed residencial development in BC, EGBC, Burnaby, British Columbia, Canada, Tech. Rep. May, 2010. a
Baum, R. L., Savage, W. Z., and Jonathan W., G.: Trigrs – A Fortran Program for Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis, Version 2.0, USGS, Denver, Colorado, United States, Tech. rep., 2008. a
Short summary
We show how INSPIRE, the European initiative to standardize data across borders, can be used to produce explainable AI-based applications. We do so by producing landslide susceptibility maps for the Veneto region in Italy. EU countries are mandated by law to implement the INSPIRE data framework by 2021, but they are aligning and serving INSPIRE data at a slow pace. Our paper can provide a boost to INSPIRE implementation as it shows the value of standardized data.
Final-revised paper