Preprints
https://doi.org/10.5194/egusphere-2026-6509
https://doi.org/10.5194/egusphere-2026-6509
05 Nov 2026
 | 05 Nov 2026
Status: this preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).

Brief communication: Landsifier 2 – Python-based Software for Automated Landslide Type Classification

Nico Schlauf, Kushanav Bhuyan, Manan Kapoor, Lorenzo Nava, Kamal Rana, Atakan Aral, and Ugur Ozturk

Abstract. Most mapped landslide inventories lack movement-type and trigger information, limiting their value for process-based research and hazard assessment. Here, we present Landsifier 2, an open-source Python library that enriches polygon inventories using three-dimensional geometry, topological descriptors, and configurable classification. Building on our existing trigger identification, this revamped library adds movement-type prediction, customizable classes, and geospatial outputs with class probabilities. Applications to independently labelled and previously undocumented inventories demonstrate its flexibility. Landsifier 2 provides a reproducible means of transforming landslide inventories into informative datasets for comparative geomorphology and hazard assessment.

Competing interests: At least one of the (co-)authors is a member of the editorial board of Natural Hazards and Earth System Sciences.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
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Nico Schlauf, Kushanav Bhuyan, Manan Kapoor, Lorenzo Nava, Kamal Rana, Atakan Aral, and Ugur Ozturk

Status: open (until 17 Dec 2026)

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Nico Schlauf, Kushanav Bhuyan, Manan Kapoor, Lorenzo Nava, Kamal Rana, Atakan Aral, and Ugur Ozturk
Nico Schlauf, Kushanav Bhuyan, Manan Kapoor, Lorenzo Nava, Kamal Rana, Atakan Aral, and Ugur Ozturk
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Latest update: 05 Nov 2026
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Short summary
Maps may show where landslides occur, but often not how they move or what caused them. We developed freely available software that examines landslide shapes and surrounding terrain to help identify different types of movement. Tests in several regions show that it can fill gaps in existing landslide records. As landslides threaten lives and infrastructure, closing these information gaps is urgently needed to better understand their behaviour and support more reliable hazard assessments.
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