DESIGNING A DATABASE FOR A SYSTEM FOR MONITORING AVALANCHE ACTIVITY IN THE EAST KAZAKHSTAN REGION

Abstract

To monitor and predict avalanche activity, big data processing is necessary, and data formation can occur from different sources: meteorological data from open databases (DB) of the regional level - the National Hydrometeorological Service of Kazakhstan, international level - World Weather Information Service, Sentinel satellite data (European Space Agency), data from operational logs of LLP Kazselezashchita, data from metering devices installed on avalanche sites, metadata (photo, video materials and 3D models of slopes) and others.

An important task for further forecasting of avalanche activity is the correct design of the avalanche collection database. In this study, an infological database model has been designed, which will allow further application of traditional methods of avalanche forecasting and machine learning methods.

As a result, we identified information objects (entities) and built an infological database model (ER diagram), on the basis of which a database was designed for a system for monitoring and forecasting avalanche activity in East Kazakhstan region. Data sources and data acquisition technologies have also been identified.