Publication:
VOLUME ESTIMATION OF FUEL LOAD FOR HAZARD REDUCTION BURNING: A VOXEL APPROACH

dc.contributor.advisor Zlatanova, Sisi
dc.contributor.advisor Barton, Jack
dc.contributor.advisor Gorte, Ben
dc.contributor.author Eusuf, Muhammad Saadmann R Sabeek
dc.date.accessioned 2022-12-20T02:44:32Z
dc.date.available 2022-12-20T02:44:32Z
dc.date.issued 2022
dc.date.submitted 2022-12-19T23:48:00Z
dc.description.abstract The year 2020 started with more than 100 fires burning across Australia. Bushfire is a phenomenon that cannot be mitigated completely by human intervention; however, better management practices can help counter the increasing severity of fires. Hazard Reduction (HR) burning has become one of the resolute applications in the management of fire-prone ecosystems worldwide, where certain vegetation is deliberately burned under controlled circumstances to thin the fuel to reduce the severity of the bushfires. As the climate changes drastically, the severity of fires is predicted to increase in the coming years. Therefore, it becomes increasingly important to investigate automatic approaches to prevent, reduce and monitor the cause and movement of bushfires. Methods of assessing FL levels in Australia are commonly based on visual assessment guidelines, such as those described in the Overall Fuel Hazard Assessment Guide (OFHAG). The overall aim of this research is to investigate the use of LiDAR to estimate the volume of fuel load to assist in the planning of HR burning, an approach that could quantify the accumulation of elevated and near-surface FL with less time and cost. This research focuses on an innovative approach based on a voxel representation. A voxel is a volumetric pixel, a quantum unit of volume, and a numeric value of x, y and z to signify a value on a regular grid in a three-dimensional space. Voxels are beneficial for processing large pointcloud data and, specifically, computing volumes. Pointcloud data provides valuable three-dimensional information by capturing forest structural characteristics. The output of this research is to create a digitised map of the accumulation of fuel (vegetation) points at elevated fuel and near-surface fuel stratum based on the point density of the pointcloud dataset for Vermont Place Park, Newcastle, Australia. The output of this information is relayed through a digital map of fuel accumulation at elevated and near-surface fuel stratum. The result of this research provides a rough idea of where the highest amount of fuel is accumulated to assist in planning of an HR burn. This will help the fire practitioners/land managers determine at which location in the forest profile should be prioritised for HR burning. There is a short window to conduct HR burning that is why it is prevalent that a tool that can provide information on fuel at a fast pace could help the fire practitioner/land managers.
dc.identifier.uri http://hdl.handle.net/1959.4/100879
dc.language English
dc.language.iso en
dc.publisher UNSW, Sydney
dc.rights CC BY 4.0
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.subject.other Bushfire Mitigation
dc.subject.other Hazard Reduction Burn
dc.subject.other Voxel
dc.subject.other Fuel Load
dc.subject.other LiDAR Point Cloud data
dc.title VOLUME ESTIMATION OF FUEL LOAD FOR HAZARD REDUCTION BURNING: A VOXEL APPROACH
dc.type Thesis
dcterms.accessRights open access
dcterms.rightsHolder Eusuf, Muhammad Saadmann R Sabeek
dspace.entity.type Publication
unsw.accessRights.uri https://purl.org/coar/access_right/c_abf2
unsw.date.workflow 2022-12-19
unsw.identifier.doi https://doi.org/10.26190/unsworks/24586
unsw.relation.faculty Other UNSW
unsw.relation.faculty Arts Design & Architecture
unsw.relation.school School of Built Environment
unsw.relation.school School of Built Environment
unsw.relation.school School of Built Environment
unsw.subject.fieldofresearchcode 33 BUILT ENVIRONMENT AND DESIGN
unsw.thesis.degreetype Masters Thesis
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