Mapping Susceptibility With Open-Source Tools: A New Plugin for QGIS

In this study, a new tool for quantitative, data-driven susceptibility zoning (SZ) is presented. The SZ plugin has been implemented as QGIS to maximize its operational use within the geoscientific community. in fact commonly used open-source geographic information system. We have scripted Python, and developed it collection of functions that allow one pre-process input data, calculate susceptibility, then estimate quality classification results. can be carried out via number classifiers including weight evidence, frequency ratio, logistic regression, random forest, support vector machine, decision tree. allows any kind mapping units, fit model, test k-fold cross-validation, visualize relative receiving operating characteristic (ROC) curves. Moreover, method index (SI) plugin. A typical workflow described, application landslide Northeast India reported. data predisposing factors are open, analysis using regression evidence models. corresponding area under curve ROC curves reflects an optimal model prediction capacity. user-friendly graphical interface allowed us perform efficiently few steps.