  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.
