Application of analytical hierarchy process and least-squares method for landslide susceptibility assessment along the Zhong-Wu natural gas pipeline, China

Landslides ◽  
2013 ◽  
Vol 10 (4) ◽  
pp. 481-492 ◽  
Author(s):  
Fengshan Ma ◽  
Jie Wang ◽  
Renmao Yuan ◽  
Haijun Zhao ◽  
Jie Guo
Keyword(s):  
Natural Gas ◽  
Least Squares ◽  
Analytical Hierarchy Process ◽  
Landslide Susceptibility ◽  
Least Squares Method ◽  
Gas Pipeline ◽  
Susceptibility Assessment ◽  
Landslide Susceptibility Assessment ◽  
Natural Gas Pipeline ◽  
Hierarchy Process

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

2021 ◽  
Author(s):  
Jewgenij Torizin ◽  
Nick Schüßler ◽  
Michael Fuchs
Keyword(s):  
Landslide Susceptibility ◽  
Binary Classification ◽  
Project Manager ◽  
Assessment Tools ◽  
Susceptibility Assessment ◽  
Standard Data ◽  
Landslide Susceptibility Assessment ◽  
Data Formats ◽  
Software Distribution ◽  
Hierarchy Process

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.

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