Ashish Gupta's post on Goodwall - Landslides are a damaging natural hazard because of their difficulty in forecasting, and fast onset that limits emergency responses. We propose to declare a new variable - 'cascade' as a probabilistic parameter of landslide occurrence. We will train the model on data procured from NDMA of India, local newspapers and television reports. We will develop a multi-platform application to collect landslide reports from users with all the relevant geographical information. The data will be modelled using AI techniques such as Deep Neural Networks, Expectation Maximisation, and Maximum Likelihood Estimation. Input variables will consist of a large number of geomorphological and climatological parameters such as soil type, precipitation, slope, topographic curvature, distance from drainage, lithology, which will then be used to extend and regionalise the 'cascade' variable to a high-resolution grid covering India. The 'cascade' variable will help in forecasting future landslide occurence depending on precipitation levels over a certain grid. Team members: 1. Ashish Gupta 2. Mohit Anand 3. Dhiraj Saharia Advisor: Professor Manabendra Saharia #o172020challenge2 #o172020