Student researcher

Dr Bryan Hally Research Leader

The project seeks to develop and test novel metrics to provide quantitative analysis of the effectiveness of prescribed burning using terrestrial (TLS) and airborne (ALS) LiDAR techniques. A series of case study sites of varying forest types will be measured pre- and post-burn, with terrestrial LiDAR used to provide metrics for localised study areas, coupled with the comparison and integration of airborne LiDAR to provide derived metrics over wider areas. These metrics will then be compared to existing vegetation assessment techniques to provide objective analysis of burn effectiveness in line with current assessment criteria. The research questions are:

  • Assessing the utility of LiDAR for quantifying the effects of wildfire in woody systems
  • Develop a model for sampling the wildfire environment at multiple spatial scales, utilising and expanding upon methods used for both terrestrial and airborne measurements
  • Integating the use of airborne and terrestrial LiDAR technologies to provide large-area assessments of fire-induced structural change
  • Relating the new metrics derived from these processes to existing visual methods of assessing fire severity, to allow a shirt to more objective assessment of the impact of fire on the environment.
Disaster landscape Attribution: Attributing Active Fire Using Simulated Fire Landscapes
18 Aug 2015
Active fires are inscreasingly being identified using satellite remote sensing to determine their size and...
Bryan Hally Conference Poster 2016
14 Aug 2016
Current methods of fire detection using remote sensing rely on contextual algorithms to characterise fire.
The diurnal cycle and its role in fire detection using Himawari-8
29 Jun 2017
Accurately estimating background temperatures is vital for identifying fire using remote sensing. New...
The problem of context – understanding the estimation of fire background temperature in South-Eastern Australia
19 Sep 2018
Satellite remote sensing provides a timely and efficient method of detecting fire, but choosing the right...