A review on application of data mining techniques to combat natural disasters

TL;DR

This paper reviews how data mining techniques are used for predicting, detecting, and managing natural disasters, emphasizing data sources, current methods, and proposing a disaster management database framework for India.

Contribution

It provides a comprehensive review of data mining applications in disaster management and proposes a phased framework for a disaster database using open source Big Data tools for India.

Findings

Data sources include geological, satellite, remote sensing, and social media.

Current techniques vary across different disaster types.

A phased disaster management database framework for India is proposed.

Abstract

Thousands of human lives are lost every year around the globe, apart from significant damage on property, animal life, etc., due to natural disasters (e.g., earthquake, flood, tsunami, hurricane and other storms, landslides, cloudburst, heat wave, forest fire). In this paper, we focus on reviewing the application of data mining and analytical techniques designed so far for (i) prediction, (ii) detection, and (iii) development of appropriate disaster management strategy based on the collected data from disasters. A detailed description of availability of data from geological observatories (seismological, hydrological), satellites, remote sensing and newer sources like social networking sites as twitter is presented. An extensive and in-depth literature study on current techniques for disaster prediction, detection and management has been done and the results are summarized according to various types of disasters. Finally a framework for building a disaster management database for India hosted on open source Big Data platform like Hadoop in a phased manner has been proposed. The study has special focus on India which ranks among top five counties in terms of absolute number of the loss of human life.