{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T04:51:15Z","timestamp":1777438275459,"version":"3.51.4"},"reference-count":53,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2019,6,20]],"date-time":"2019-06-20T00:00:00Z","timestamp":1560988800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Geosciences"],"abstract":"<jats:p>The hydrographic basin of Ribeira Grande (S. Miguel Island, Azores) has a set of characteristics that enhance the occurrence of shallow slides that have been triggered by rainfall and earthquakes. Two landslide inventories were built according to the landslide triggers: Landslide Inventory 2 (LI 2), which includes 174 earthquake-triggered shallow slides occurred in 2005; and Landslide Inventory 1 (LI 1), which includes 442 shallow slides triggered by rainfall in several periods from 2005 to 2016. Both landslide inventories were characterized and compared from the morphometric point of view and were used individually to produce susceptibility models to failure using a simple bivariate state-of-the-art statistical method (the Information Value). The landslide susceptibility Models were validated using success rates, prediction rates, and Kappa statistics. The results show that shallow slides triggered by rainfall and earthquakes in the study area have different morphometric characteristics. It was verified that models produced with LI 1 are very effective in predicting the spatial location of LI 2, but the same does not happen in the inverse situation. Finally, landslide susceptibility models developed with LI 1 and LI 2 for the upper sector of the hydrographic basin (where most landslides occurred), and latter applied to the complete watershed, present more modest predictive results but are more reliable to characterize the landslide susceptibility in the study area.<\/jats:p>","DOI":"10.3390\/geosciences9060268","type":"journal-article","created":{"date-parts":[[2019,6,20]],"date-time":"2019-06-20T10:49:59Z","timestamp":1561027799000},"page":"268","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Landslide Susceptibility Assessment at the Basin Scale for Rainfall- and Earthquake-Triggered Shallow Slides"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7047-8371","authenticated-orcid":false,"given":"Cristina","family":"Gordo","sequence":"first","affiliation":[{"name":"Centre of Geographical Studies, Institute of Geography and Spatial Planning, University of Lisbon, Rua Branca Edm\u00e9e Marques, 1600-276 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3953-673X","authenticated-orcid":false,"given":"Jos\u00e9 Lu\u00eds","family":"Z\u00eazere","sequence":"additional","affiliation":[{"name":"Centre of Geographical Studies, Institute of Geography and Spatial Planning, University of Lisbon, Rua Branca Edm\u00e9e Marques, 1600-276 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3633-7110","authenticated-orcid":false,"given":"Rui","family":"Marques","sequence":"additional","affiliation":[{"name":"Research Institute for Volcanology and Risk Assessment, University of Azores, Rua M\u00e3e de Deus, 9500-501 Ponta Delgada, Portugal"},{"name":"Centre for Information and Seismovolcanic Surveilance of the Azores, University of the Azores, Rua M\u00e3e de Deus, 9500-501 Ponta Delgada, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2019,6,20]]},"reference":[{"key":"ref_1","unstructured":"Glade, T., and Crozier, M.J. 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