Landslide Prediction Using Long Short Term Memory(LSTM)Neural Network on time series data in Pakistan

Landslides are the calamities responsible for the losses of lives and property at large. Early warning systems to predict the upcoming landslide can be of great advantage in developing a guide to control and alleviate these disasters. In this research, we have used artificial neural network (ANN) and long short term neural network (LSTM) for landslide prediction in Pakistan. The data has been collected from various regions of Pakistan including Jammu and Kashmir, Chitral, Gilgit Baltistan and Hazara division. A total of 12 parameters: surface pressure, specific humidity, surface runoff, rainfall, soil moisture at root level, soil moisture at 10cm, average temperature, transpiration, wind speed, aspect, slope and elevation are extracted for each location. The developed models have achieved accuracy greater than 95%.