End User representatives
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 postfire 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.
Researchers are developing approaches that provide new information to assist fire agencies in responding to fire management tasks and future proof their practices to parallel developments in remote sensing.
The project is systematically addressing the provision of rapid, timely, and highquality information from multi-scale remote sensing systems. It is developing enhanced metrics on active fire extent, intensity and configuration as well as bushfire landscape attributes.
The study aims to bridge significant information and knowledge gaps that currently prevent optimal use of satellite technology. These include accuracy and reliability issues in active fire surveillance, quantitative estimates of post-fire severity, a lack of product validation, and out-of-date approaches to collecting information on landscape condition.
This work is leading Australia’s contribution to integrate and enhance existing disaster monitoring and reporting systems with next generation earth observation technology and systems from the German Aerospace Centre and other agencies.
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.
An Android-based smartphone app called Fuels3D has been developed to collect imagery describing fuel hazard. These images are used to create 3D point cloud assessments of the fuel hazard.
The project has conducted field experiments and collected datasets that have been shared in publications and conferences for end-users, continued work in synthetic landscape modelling for fire detection and tracking, and trialled fire temperate mapping and monitoring using manual and electronic pyrometers during a prescribed burn in Victoria. Publications have included four journal articles and five conference papers.
|21 Mar 2014||Monitoring and prediction||7.35 MB (7.35 MB)||flood, modelling, multi-hazard|
|08 Sep 2014||The effect of the degree of grass curing on the behaviour of grassland fires||17.65 MB (17.65 MB)||fire|
|27 Oct 2014||The effect of the degree of grass curing on the behaviour of grassland fires||fire, propagation|
|05 Dec 2014||Thermal anomaly and hazard mapping||670.97 KB (670.97 KB)||fire, forecasting|
|26 Feb 2016||Fire Australia Summer 2015-16||11.81 MB (11.81 MB)||earthquake, fire impacts, volunteering|
|03 Apr 2016||Monitoring and prediction - cluster overview||0 bytes (0 bytes)||forecasting, multi-hazard, scenario analysis|
|24 Oct 2016||Disaster landscape attribution, active fire detection and hazard mapping||1.9 MB (1.9 MB)||fire, fire impacts, remote sensing|
|28 Nov 2016||Monitoring and predicting natural hazards||853.18 KB (853.18 KB)||forecasting, modelling, severe weather|
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.
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.
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.
This project aims to attribute fire landscapes using the latest remote sensing technology.
|Improving flood forecast skill using remote sensing data||Assoc Prof Valentijn Pauwels||Monash University|
|Mapping bushfire hazard and impacts||Prof Albert van Dijk||Australian National University|
|Disaster landscape attribution: thermal anomaly surveillance and hazard mapping, data scaling and validation||Prof Simon Jones||RMIT University|
|Fire spread prediction across fuel types||Dr Khalid Moinuddin||Victoria University|