Understanding and Mitigating Hazards

Lake-Mountain-post-2009_2.jpg

Lake Mountain landscape post Black Saturday fires
Lake Mountain landscape post Black Saturday fires

Project Status:

This project seeks to optimise the use of earth observing systems for active fire monitoring by exploring issues of scale, accuracy and reliability, and to improve the mapping and estimation of post-fire severity and fuel change through empirical remote sensing observations. Outcomes will enable satellite measures of fire activity to be made, which in turn have the potential to inform or support efforts in bushfire response planning and fire rehabilitation efforts. A particular focus is on the analysis of data obtained from Himawari-8, which is able to provide updated imagery on a 10 minute basis.

This project seeks to optimise the use of earth observing systems for active fire monitoring by exploring issues of scale, accuracy and reliability, and to improve the mapping and estimation of post-fire severity and fuel change through empirical remote sensing observations. Understanding the trade-offs between sensors and their ability to map and measure fire-related attributes over a range of different landscapes and fire scenarios is important.

The study has is improving the accuracy of vegetation monitoring for flammability, as well as saving critical man hours, through the development of a beta smartphone application. Fuels3D, built on the Android platform, will allow land managers to rapidly collect imagery in the field, and uses computer vision and photogrammetric techniques to calculate measures of fuel and severity metrics.

Additionally, this project is leading Australian contributions to integrate and enhance Australianled existing disaster monitoring and reporting systems with next generation earth observation technology and systems from the German Aerospace Centre and other agencies.

Outcomes will enable satellite measures of fire activity to be made, which in turn have the potential to inform or support efforts in bushfire response planning and fire rehabilitation efforts. A particular focus is on the analysis of data obtained from Himawari-8, which is able to provide updated imagery on a 10 minute basis.

The project is currently using simulations and real world experiments to determine the accuracy with which fires can be detected, their temperature and shape determined, for a range of landscapes.

The project is also creating new techniques and protocols for the rapid attribution of fire landscapes (pre- and post-fire). These techniques seek to add quantitative vigour to existing fuel hazard estimation practices.

Post fire field work
17 November, 2017
New journal articles and reports on CRC research are available online.
PhD researcher Bryan Hally won best paper at a remote sensing conference in India.
14 November, 2017
CRC research on mapping fires and vegetation has won several awards recently.
19 April, 2017
New journal articles and reports on CRC research are available online.
St Andrews prescribed burn
3 April, 2017
Research is improving the accuracy of vegetation monitoring for flammability through the development of a beta smartphone application. Fuels3D will allow land managers to rapidly collect imagery in the field to calculate measures of fuel and severity metrics.
14 September, 2016
New journal articles and reports on CRC research are available online.
16 August, 2016
New journal articles and reports on CRC research are available online.
A prescribed burn in St Andrews, Victoria
4 March, 2016
Fire managers need to accurately monitor prescribed burns and bushfires to better assess how they affect fuels and how they reduce fire risk. A project at the Bushfire and Natural Hazards CRC uses satellite technology to more accurately map bushfires.
Fire Australia magazine 2015/16 edition
29 February, 2016
The Summer 2015/2016 edition of Fire Australia magazine features key research that’s making an impact on the fire, emergency services and land management sectors.
Year Type Citation
2017 Conference Paper Rumsewicz, M. Research proceedings from the 2017 Bushfire and Natural Hazards CRC and AFAC Conference. Bushfire and Natural Hazards CRC & AFAC annual conference 2017 (Bushfire and Natural Hazards CRC, 2017).
2017 Conference Paper Wallace, L. et al. Mapping the efficacy of an Australian fuel reduction burn using Fuels3D point clouds. AFAC17 (Bushfire and Natural Hazards CRC, 2017).
2017 Conference Paper Hally, B., Wallace, L., Reinke, K., Wickramasinghe, C. & Jones, S. Enhanced estimation of background temperature for fire detection using new geostationary sensors. AFAC17 (Bushfire and Natural Hazards CRC, 2017).
2017 Journal Article Hally, B., Wallace, L., Reinke, K. & Jones, S. A Broad-Area Method for the Diurnal Characterisation of Upwelling Medium Wave Infrared Radiation. Remote Sensing 9, (2017).
2017 Report Jones, S., Reinke, K. & Wallace, L. Disaster landscape attribution: annual report 2016-17. (Bushfire and Natural Hazards CRC, 2017).
2017 Report Jones, S., Reinke, K., Mitchell, S., McConachie, F. & Holland, C. Advances in the remote sensing of active fires: a review. (Bushfire and Natural Hazards CRC, 2017).
2017 Report Wallace, L., Reinke, K. & Jones, S. Emerging technologies for estimating fuel hazard. (Bushfire and Natural Hazards CRC, 2017).
2016 Journal Article Wallace, L., Gupta, V., Reinke, K. & Jones, S. An Assessment of Pre- and Post Fire Near Surface Fuel Hazard in an Australian Dry Sclerophyll Forest Using Point Cloud Data Captured Using a Terrestrial Laser Scanner. Remote Sensing 8, (2016).
2016 Journal Article Mitchell, S., Jones, S., Reinke, K., Lorenz, E. & Reulke, R. Assessing the utility of the TET-1 hotspot detection and characterization algorithm for determining wildfire size and temperature. International Journal of Remote Sensing 37, 4731-4747 (2016).
2016 Report Jones, S., Reinke, K. & Wallace, L. Disaster landscape attribution: fire surveillance and hazard mapping, data scaling and validation: Annual project report. (Bushfire and Natural Hazards CRC, 2016).
2015 Journal Article Gupta, V., Reinke, K., Jones, S., Wallace, L. & Holden, L. Assessing Metrics for Estimating Fire Induced Change in the Forest Understorey Structure Using Terrestrial Laser Scanning. Remote Sensing 7, 8180-8201 (2015).
2015 Presentation Jones, S. & Reinke, K. Disaster landscape attribution, active fire detection and hazard mapping. (2015).
2015 Report Jones, S. & Reinke, K. Disaster landscape attribution: Annual project report 2014-2015. (Bushfire and Natural Hazards CRC, 2015).
2015 Report Jones, S. Disaster Landscape Attribution: Fire Surveillance and Hazard Mapping, Data Scaling and Validation Annual Report 2014. (2015).
Disaster landscape attribution: Thermal anomaly and hazard mapping
25 Aug 2014

This project seeks to (1) optimize the use of earth observing systems for active fire monitoring by exploring issues of scale, accuracy and reliability, and (2) to improve the mapping and estimation of post-fire severity and fuel change through empirical remote sensing observations.

Key Topics:
Disaster landscape attribution
18 Aug 2015

Understanding the utility of thermal remote sensing systems for active fire detection and monitoring. Exploring issues of scale, accuracy and reliability through simulations and field validation.

Disaster Landscape Attribution: Low Cost 3D Monitoring of Fuel Hazard
18 Aug 2015

In the last decade A range of sensing technologies, techniques and platforms have emerged to capture 3D structural information. This project explores these systems as alternative quantitative solutions to traditional fuel hazard and fire severity evaluations. 

Luke Wallace Conference Poster 2016
14 Aug 2016

This project aims to attribute fire landscapes using the latest remote sensing technology.

The detection and surveillance of active fire using Himawari-8
29 Jun 2017

Himawari-8 presents exciting opportunities to map fires in near real time. Exploiting information across temporal and spatial domains enables a new paradigm in fire detection and surveillance.

Fuels3D: what's the point?
29 Jun 2017

The Fuels3D app provides a low cost data collection method for estimating fuel hazard metrics. Testing of the app has demonstrated that it provides significantly greater repeatability and improved quantification of metrics than visual assessments.

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