How to easily use ANN for prediction mapping using GIS data?

Artificial Neural Network (ANN) is one of the advanced Artificial Intelligence (AI) component, through many applications, vary from social, medical and applied engineering, ANN proves high reliability and validity enhanced by multiple setting options.

Using ANN with Spatial data, increases the confidence in the obtained results, especially when it compare to regression or classification based techniques. as called by many researchers and academician especially in prediction mapping applications.

Together, step by step with school–bus speed, will cover the following points comprehensively (data, code and other materials are provided) using NeuralNet Package in R and Landslides data and thematics maps.

Produce training and testing data using automated tools in QGIS OR SKIP THIS STEP AND USE YOUR OWN TRAINING AND TESTING DATA

Run Neural net function with training data and testing data

Plot NN function network

Pairwise NN model results of Explanatories and Response Data

Generalized Weights plot of Explanatories and Response Data

Variables importance using NNET Package function

Run NNET function

Plot NNET function network

Variables importance using NNET

Sensitivity analysis of Explanatories and Response Data

Run Neural net function for prediction with validation data

Prediction Validation results with AUC value and ROC plot

Produce prediction map using Raster data

Import and process thematic maps like, resampling, stacking, categorical to numeric conversion.