Abstract
The potential impact of bushfires is a significant concern for communities and fire response agencies, and the ability to predict the fire risk timely and accurately is critical. However, that cannot be achieved without accessing and processing very large amounts of data in almost real time. We demonstrate a data-driven fire risk prediction system that leverages big geospatial and meteorological data, where the results are visualised and made available to communities and fire agencies for risk mitigation strategies.
Original language | English |
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Title of host publication | Databases Theory and Applications |
Subtitle of host publication | 27th Australasian Database Conference, ADC 2016, Sydney, NSW, September 28–29, 2016, Proceedings |
Editors | Muhammad Aamir Cheema, Wenjie Zhang, Lijun Chang |
Place of Publication | Cham Switzerland |
Publisher | Springer |
Pages | 457-461 |
Number of pages | 5 |
ISBN (Electronic) | 9783319469225 |
ISBN (Print) | 9783319469218 |
DOIs | |
Publication status | Published - 2016 |
Externally published | Yes |
Event | Australasian Database Conference 2016 - The University of New South Wales, Sydney, Australia Duration: 28 Sep 2016 → 29 Sep 2016 Conference number: 27th https://adc2016.cse.unsw.edu.au/ https://link.springer.com/book/10.1007/978-3-319-46922-5 (Proceedings) |
Publication series
Name | Lecture Notes in Computer Science |
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Publisher | Springer |
Volume | 9877 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | Australasian Database Conference 2016 |
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Abbreviated title | ADC 2016 |
Country | Australia |
City | Sydney |
Period | 28/09/16 → 29/09/16 |
Other | The Australasian Database Conference series is an annual forum for sharing the latest research progresses and novel applications of database systems, data driven applications and data analytics for researchers and practitioners in these areas from Australia, New Zealand and in the world. |
Internet address |