Big data integration shows Australian bush-fire frequency is increasing significantly

被引:89
作者
Dutta, Ritaban [1 ]
Das, Aruneema [2 ]
Aryal, Jagannath [3 ]
机构
[1] CSIRO Data61, Hobart, Tas 7001, Australia
[2] Univ Tasmania, Sch Med, Hobart, Tas 7000, Australia
[3] Univ Tasmania, Sch Land & Food, Hobart, Tas 7001, Australia
来源
ROYAL SOCIETY OPEN SCIENCE | 2016年 / 3卷 / 02期
关键词
bush-fire frequency; ensemble machine learning; big data; climatic shift; decision science; CLIMATE; BEHAVIOR; REGIMES;
D O I
10.1098/rsos.150241
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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 hotspot 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.
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页数:11
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