There are number of different approaches for the measurement of landslide hazard, including direct and indirect heuristic approaches, and deterministic, probabilistic, statistical and data mining approaches. In this session, we will focus on the latest and modern techniques in data mining to improve landslide hazard modelling, forecasting and prediction. Contributions on various aspects of data mining models in landslide hazard assessment are invited. We encourage contributions using various parameters (earth observation remote sensing based, lithological, geotechnical, hydrogeological, geomorphological and anthropological etc.), processes and mechanisms of slope failures and their modelling with the aid of GIS and data mining approaches. This session is thus aimed to bring together spatial modellers, earth observation scientists, field geologists, hazards assessors, computer scientists, engineering geologists and geomorphologists in order to discuss the latest methods in data mining approaches for landslide hazard assessment. The important and relevant contributions from this session will be published in the special issue of "Environmental and Engineering Geoscience" journal.