Submitted as: development and technical paper 23 Sep 2021

Submitted as: development and technical paper | 23 Sep 2021

Review status: this preprint is currently under review for the journal GMD.

Landslide Susceptibility Assessment Tools v1.0.0b – Project Manager Suite: A new modular toolkit for landslide susceptibility assessment

Jewgenij Torizin, Nick Schüßler, and Michael Fuchs Jewgenij Torizin et al.
  • Federal Institute for Geosciences and Natural Resources (BGR), Hanover, 30655, Germany

Abstract. This paper introduces the Landslide Susceptibility Assessment Tools – Project Manager Suite (LSAT PM), an open-source, easy-to-use software written in Python. Primarily developed to conduct landslide susceptibility analyses (LSA), it is not limited to this issue and applies to any other research dealing with supervised spatial binary classification. With its standardized project framework, LSAT PM provides efficient interactive data management supported by handy tools. The application utilizes standard data formats ensuring data transferability to all geographic information systems. LSAT PM has a modular structure allowing to extend the existing toolkit by additional analyses. The LSAT PM v1.0.0b implements heuristic and data-driven methods such as the analytical hierarchy process, weights of evidence, logistic regression, and artificial neural networks. The software was developed and tested over the years in different projects dealing with landslide susceptibility assessment. The emphasis on model uncertainties and statistical model evaluation makes the software a practical modeling tool. Also, it provides the possibility to explore and evaluate different LSA models, even those not created with LSAT PM. The software distribution package includes comprehensive documentation. A dataset for testing purposes of the software is available. LSAT PM is subject to continuous further development.

Jewgenij Torizin et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2021-247', Anonymous Referee #1, 07 Oct 2021
  • RC2: 'Comment on gmd-2021-247', Anonymous Referee #2, 29 Oct 2021

Jewgenij Torizin et al.

Data sets

LSAT-TestData GANP Project Team & Nick Schüßler

Model code and software

LSAT PM v1.0.0b Jewgenij Torizin and Nick Schüßler

Jewgenij Torizin et al.


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Short summary
With LSAT PM we introduce an open-source, standalone, easy-to-use application that supports scientific principles of openness, knowledge integrity, and replicability. Doing so, we want to share our experience in the implementation of heuristic and data-driven landslide susceptibility assessment methods such as Analytic Hierarchy Process, Weights of Evidence, Logistic Regression, and Artificial Neural Networks. A test dataset is available.