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.
| Language | English |
|---|---|
| Title of host publication | Databases Theory and Applications - 27th Australasian Database Conference, ADC 2016, Proceedings |
| Publisher | Springer-Verlag London Ltd. |
| Pages | 457-461 |
| Number of pages | 5 |
| Volume | 9877 LNCS |
| 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/ |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 9877 LNCS |
| ISSN (Print) | 03029743 |
| ISSN (Electronic) | 16113349 |
Conference
| Conference | Australasian Database Conference 2016 |
|---|---|
| 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 |
Cite this
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Data-driven prediction and visualisation of dynamic bushfire risks. / Rusu, Laura Irina; Vo, Hoang Tam; Wang, Ziyuan; Salehi, Mahsa; Phan, Anna.
Databases Theory and Applications - 27th Australasian Database Conference, ADC 2016, Proceedings. Vol. 9877 LNCS Springer-Verlag London Ltd., 2016. p. 457-461 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9877 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
TY - GEN
T1 - Data-driven prediction and visualisation of dynamic bushfire risks
AU - Rusu, Laura Irina
AU - Vo, Hoang Tam
AU - Wang, Ziyuan
AU - Salehi, Mahsa
AU - Phan, Anna
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84990061985&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-46922-5_39
DO - 10.1007/978-3-319-46922-5_39
M3 - Conference Paper
SN - 9783319469218
VL - 9877 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 457
EP - 461
BT - Databases Theory and Applications - 27th Australasian Database Conference, ADC 2016, Proceedings
PB - Springer-Verlag London Ltd.
ER -