International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume XLIII-B3-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1199–1206, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1199-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1199–1206, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1199-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  21 Aug 2020

21 Aug 2020

VOLUME ESTIMATION OF FUEL LOAD FOR HAZARD REDUCTION BURNING: FIRST RESULTS TO A VOXEL APPROACH

M. S. R. S. Eusuf, J. Barton, B. Gorte, and S. Zlatanova M. S. R. S. Eusuf et al.
  • Geospatial Research Innovation Development (GRID), Faculty of Built Environment, UNSW, Sydney, Australia

Keywords: Bushfire Fuel, LiDAR, Voxels, Hazard Reduction Burning, Disaster Mitigation

Abstract. In 2019/20 over 100 severe bushfires burned across the continent of Australia. The severity of these fires was exacerbated by many factors, including macroclimatic effects of global warming and, at the meso and micro scales, land management practices. The bushfire phenomenon cannot be stopped, however better management practices can help counter the increasing severity of fires. Hazard reduction burning is a method where certain vegetation is deliberately burned under controlled circumstances to thin the fuel to reduce the severity of bushfires. Fuel load is an important parameter to assess when hazard reduction burning, as the accumulation of vegetation in a forest profile affects the intensity of the burn. Conventional methods of measuring fuel load are time consuming and costly, and therefore it becomes increasingly important to investigate automated approaches for assessing fuel loads. This paper provides an overview of hazard reduction burning while explaining the methods to quantify fuel load. Then the paper presents our voxel approach in estimating the volume of fuel loads. The first results regarding different voxel resolutions are reported and analysed. This paper concludes with future steps and developments.