Title |
Big data integration shows Australian bush-fire frequency is increasing significantly
|
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Published in |
Royal Society Open Science, February 2016
|
DOI | 10.1098/rsos.150241 |
Pubmed ID | |
Authors |
Ritaban Dutta, Aruneema Das, Jagannath Aryal |
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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Australia | 22 | 27% |
United Kingdom | 6 | 7% |
Spain | 4 | 5% |
United States | 2 | 2% |
Nigeria | 1 | 1% |
Belgium | 1 | 1% |
Brazil | 1 | 1% |
Canada | 1 | 1% |
Germany | 1 | 1% |
Other | 3 | 4% |
Unknown | 41 | 49% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 74 | 89% |
Scientists | 5 | 6% |
Science communicators (journalists, bloggers, editors) | 2 | 2% |
Practitioners (doctors, other healthcare professionals) | 2 | 2% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | <1% |
Unknown | 160 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 36 | 22% |
Student > Master | 20 | 12% |
Student > Ph. D. Student | 19 | 12% |
Student > Bachelor | 15 | 9% |
Other | 8 | 5% |
Other | 22 | 14% |
Unknown | 41 | 25% |
Readers by discipline | Count | As % |
---|---|---|
Environmental Science | 34 | 21% |
Engineering | 14 | 9% |
Earth and Planetary Sciences | 14 | 9% |
Computer Science | 13 | 8% |
Agricultural and Biological Sciences | 8 | 5% |
Other | 23 | 14% |
Unknown | 55 | 34% |