I suggest to take a look at the researches by Biswajeet Pradhan. I think he is a perfect researcher in landslide susceptibility.

Examples:

1. Pradhan, B., & Lee, S. (2010). Landslide susceptibility assessment and factor effect analysis: backpropagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modelling. Environmental Modelling & Software, 25(6), 747-759.

2. Pradhan, B., & Lee, S. (2010). Regional landslide susceptibility analysis using back-propagation neural network model at Cameron Highland, Malaysia. Landslides, 7(1), 13-30.

3. Pradhan, B., Seeni, M. I., & Nampak, H. (2017). Integration of LiDAR and QuickBird Data for Automatic Landslide Detection Using Object-Based Analysis and Random Forests. In Laser Scanning Applications in Landslide Assessment (pp. 69-81). Springer, Cham.

Thank you very much, but in this case, I'm more interested in not estimating the regional landslide hazard, but calculating the zone of defeat from a specific landslide

Hi,

For rock avalanches dynamic model :

http://clara-w.com/DANWReference2.pdf

For landslides stability - numerical modelling :

https://www.nat-hazards-earth-syst-sci.net/3/523/2003/nhess-3-523-2003.pdf

Thank you! Unfortunately CLARA-W Slope Stability Analysis in 2 or 3 dimensions has retired. SVSlope does not allow building similar models. I will try to understand the methodology of G. B. Crosta et al .

To do this, you can use the system "Eidos". The mathematical model of the Eidos system is based on the theory of information. It allows you to build a model that connects the values of the factors and the results of their actions. This requires examples of relevant observations (empirical data).

The Eidos-X++ system differs from other artificial intelligence systems in the following parameters:

- was developed in a universal setting, independent of the subject area. Therefore, it is universal and can be applied in many subject areas (http://lc.kubagro.ru/aidos/index.htm);

- is in full open free access (http://lc.kubagro.ru/aidos/_Aidos-X.htm), and with the relevant source texts (http://lc.kubagro.ru/__AIDOS-X.txt);

- is one of the first domestic systems of artificial intelligence of the personal level, i.e. it does not take special training in the field of technologies of artificial intelligence from the user (there is an act of introduction of system "Eidos" of 1987) (http://lc.kubagro.ru/aidos/aidos02/PR-4.htm);

- provides stable identification in a comparable form of strengh and direction of cause-effect relationships in incomplete noisy interdependent (nonlinear) data of very large dimension of numerical and non-numerical nature, measured in different types of scales (nominal, ordinal and numerical) and in different units of measurement (i.e. does not impose strict requirements to the data that can not be performed, and processes the data that is);

- contains a large number of local (supplied with the installation) and cloud educational and scientific applications (currently 31 and 154, respectively) (http://lc.kubagro.ru/aidos/Presentation_Aidos-online.pdf);

- provides multilingual interface support in 44 languages. Language databases are included in the installation and can be replenished automatically;

- supports on-line environment of knowledge accumulation and is widely used all over the world (http://aidos.byethost5.com/map5.php);

- the most time-consuming computationally, the operations of the synthesis models and implements recognition by using graphic processing unit (GPU) that some tasks can only support up to the solution of these tasks is several thousand times that really provides intelligent processing of big data, big information and big knowledge;

- provides transformation of the initial empirical data into information, and its knowledge and solution using this knowledge of classification problems, decision support and research of the subject area by studying its system-cognitive model, generating a very large number of tabular and graphical output forms (development of cognitive graphics), many of which have no analogues in other systems (examples of forms can be found in: http://lc.kubagro.ru/aidos/aidos18_LLS/aidos18_LLS.pdf);

- well imitates the human style of thinking: gives the results of the analysis, understandable to experts on the basis of their experience, intuition and professional competence.

I would suggest to use FLAC2D followed by FLAC3D software for single large landslide analysis. You can measure the FOS, displacement, velocity etc. whatever is your objective.