@article{ref1,
title="Big data integration shows Australian bush-fire frequency is increasing significantly",
journal="Royal Society open science",
year="2016",
author="Dutta, Ritaban and Das, Aruneema and Aryal, Jagannath",
volume="3",
number="2",
pages="150241-150241",
abstract="Increasing Australian bush-fire frequencies over the last decade has indicated a major climatic change in coming future. Understanding such climatic change for Australian bush-fire is limited and there is an urgent need of scientific research, which is capable enough to contribute to Australian society. Frequency of bush-fire carries information on spatial, temporal and climatic aspects of bush-fire events and provides contextual information to model various climate data for accurately predicting future bush-fire hot spots. In this study, we develop an ensemble method based on a two-layered machine learning model to establish relationship between fire incidence and climatic data. In a 336 week data trial, we demonstrate that the model provides highly accurate bush-fire incidence hot-spot estimation (91% global accuracy) from the weekly climatic surfaces. Our analysis also indicates that Australian weekly bush-fire frequencies increased by 40% over the last 5 years, particularly during summer months, implicating a serious climatic shift.<p /> <p>Language: en</p>",
language="en",
issn="2054-5703",
doi="10.1098/rsos.150241",
url="http://dx.doi.org/10.1098/rsos.150241"
}