Susceptibility Zoning plugin (SZ)

See also

You can find the plugin codes at this link

Introduction

This repository contains the code for a plugin for QGIS, called “Susceptibility Zoning plugin” (SZ-plugin), aiming at creating maps of susceptibility to various natural forcing elements.

The plugin has been developed with a main focus and application towards landslides susceptibility, but it can be applied to different types of natural events or inter-disciplinary applications.

The plugin uses several type of statistical model for susceptibility evaluation, such as:

  • Weight of Evidence

  • Frequency Ratio

  • Logistic Regression

  • Decision Tree

  • Support Vector Machine

  • Random Forest

The plugin allows to cross-validate the results by simple random selection of test/train samples or allows to cross-validate by k-fold cross-validation method.


Minimum requirements

Minimum tested version of QGIS is 3.28

Tested on:

  • Ubuntu 20.04 - QGIS 3.34

  • Windows 10 - QGIS 3.28/QGIS 3.34

  • MacOS Sonoma 14.4 - QGIS 3.28

Download and install

The SZ plugin is not an official QGIS plugin.

It can be installed on QGIS >= 3.28 adding the Plugin Repository to QGIS manage and install plugins: - flag show also experimental plugins

Show experimental plugins
  • add plugin repository

Add plugin repository
Edit plugin repository

or

cloning the GitHub repository or downloading it as zip file (and then unzipping it) and copying the sz_module folder in your local python/plugin folder (read here for more information).

Lunch QGIS 3.x, and abilitate the plugin from manage and install plugin/installed/sz_processing

Install A

or

cloning the GitHub repository or downloading it as zip file (and then unzipping it), and zip the folder sz_module to sz_module.zip. Finally you can install the plugin by using the menu install from zip.

Install B

At the end you should have the SZ plugin in your processing toolbox

Processing toolbox

GUI

The functions are grouped into 3 categories: * Data preparation * SI * SI k-fold * Classify SI

Data preparation functions can be used for data pre-processing SI functions run the statistic models for susceptibility, cross-validate by a simple random selection of train/test samples and evaluate the prediction capacity by ROC curves SI k-fold functions run the statistic models for susceptibility, cross-validate by k-fold method and evaluate the prediction capacity by ROC curves Classify SI functions allows to categorize the susceptibility index into n classes on the base of AUC maximization.

Input data of SI and SI k-fold functions

Input data for SI k-fold or SI functions should be a vector layer with a number of fields for independent variables and a field for the dependent variable classified binomially: 0 for absence, >0 for presence.

Input data

Test

A dataset and QGIS project are available in test folder to test the plugin.

Output A
Output B

Third-part libraries and plugins used

Tutorial

video tutorial: https://www.youtube.com/watch?v=XpsiCkVF11s

Application

Titti G, Sarretta A, Lombardo L, Crema S, Pasuto A and Borgatti L (2022) Mapping Susceptibility With Open-Source Tools: A New Plugin for QGIS. Front. Earth Sci. 10:842425. doi: 10.3389/feart.2022.842425

Referenced dataset

Publications

A few examples and references about applications

Titti G, Sarretta A, Lombardo L, Crema S, Pasuto A and Borgatti L (2022) Mapping Susceptibility With Open-Source Tools: A New Plugin for QGIS. Front. Earth Sci. 10:842425. doi: 10.3389/feart.2022.842425

Titti, G., van Westen, C., Borgatti, L., Pasuto, A., & Lombardo, L. (2021). When Enough Is Really Enough? On the Minimum Number of Landslides to Build Reliable Susceptibility Models. Geosciences, 11(11), 469.

Titti, G., Borgatti, L., Zou, Q., Cui, P., & Pasuto, A. (2021). Landslide susceptibility in the Belt and Road Countries: continental step of a multi-scale approach. Environmental Earth Sciences, 80(18), 1-18. 10.1007/s12665-021-09910-1

Titti, G., Borgatti, L., Zou, Q., Pasuto, A., 2019. Small-Scale landslide Susceptibility Assessment. The Case Study of the Southern Asia. Proceedings 30, 14. 10.3390/proceedings2019030014

Presentations

A list of presentations made about the plugin and its applications

Titti, Giacomo, Sarretta, Alessandro, Crema, Stefano, Pasuto, Alessandro, & Borgatti, Lisa. (2020, March). Sviluppo e applicazione del plugin Susceptibility zoning per il supporto alla pianificazione territoriale. Zenodo. 10.5281/zenodo.3723353

Credits

Giacomo Titti, Alessandro Sarretta and Luigi Lombardo, Padova, November 2021

please cite as: Giacomo Titti, Alessandro Sarretta and Luigi Lombardo. (2021). CNR-IRPI-Padova/SZ: SZ plugin (Version v1.0). Zenodo.

Contacts

If you have any problem, please write to giacomotitti@gmail.com or create new issue here