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An introduction to Landslide Susceptibility Assessment Tools – Project Manager Suite

Landslide Susceptibility Assessment Tools - Project Manager Suite (LSAT PMS), an open-source, user-friendly program written in Python developed and released at the Federal Institute for Geosciences and Natural Resources (BGR). Although initially developed to conduct landslide susceptibility analyses, LSAT PMS is applicable for all types of spatial analyses related to supervised binary classification. The first LSAT PMS release supports analysis workflows based on the weight of evidence, logistic regression, artificial neural network, and analytical hierarchy process. Solution tailored toolbox and the implemented data management environment allow efficient import, preprocessing, analysis and postprocessing of the data. The graphical user interface facilitates the intuitive exploratory work with the data and the models. Developing LSAT PMS, we focus on the practical assessment of uncertainties and model evaluation to better characterise the capabilities and limitations of implemented methods. Therefore, LSAT PMS offers different subsampling techniques and an evaluation tool to evaluate and compare models generated by different methods. Introducing LSAT PMS, we hope to provide easy access to state-of-the-art methods for the non-programming community supporting scientific principles of openness, knowledge integrity, and replicability. The standardised project framework of LSAT PMS allows an easy sharing of the data and model results among peers. With the utilisation of standard data formats, analysis results are transferable among all GIS for further processing and advanced visualisation. The software, corresponding comprehensive documentation, and a test dataset are ready for download on BGR’s home page and GitHub. LSAT PMS is subject to further development.

Details

Author
Nick Schüßler, Jewgenij Torizin, Michael Fuchs
Institutionen
Bundesanstalt für Geowissenschaften und Rohstoffe, Germany
Veranstaltung
GeoKarlsruhe 2021
Datum
2021
DOI
10.48380/dggv-f4hb-az42