Remote Sensing Research Group

Southern Earth Observatory

Estimating wildfire fuel hazard in dry sclerophyll eucalypt forests from UAV-borne sensing technology  

| 0 comments

Classifying and quantifying fuel is complex and includes assessing a range of characteristics.

Fine fuel load has been considered one of the most significant fuel variables affecting the behaviour of fire and has been used to predict the rate of fire spread.

Tasmanian Ridgeway Site – dry schlerophyll forest with recent burn history.

 

Limited research has been conducted using UAV mounted laser scanners and cameras for the purpose of Structure from Motion (SfM) to measure below-canopy structure. Preliminary studies in native Australian forest stands have further demonstrated the use of UAV laser scanning and SfM to estimate various structural properties of a native stands. A research gap exists in assessing the accuracy of point clouds generated from UAVs in measuring surface and near-surface vegetation characteristics.

In order to address this literature gap, fieldwork (sponsored by the Bushfire and Natural Hazards CRC), was conducted at a patch of native dry sclerophyll eucalypt forest located southeast of Hobart, Tasmania, Australia. The objective of this work was to compare the accuracy of UAV SfM and UAV laser scanning in assessing height and cover. Direct measurements were taken within the plot as reference data. Terrestrial point clouds were also captured using terrestrial laser scanning and SfM as a further point of comparison. Analysis will commence in comparing these different forms of measurement to investigate the viability of UAV SfM and laser scanning in assessing fine fuel load.

 

Setting up direct measurement instrumentation.

Recording direct measurements of vegetation height and cover.

Research Fellow operating Terrestrial Laser Scanner in Tasmania

 

 

 

 

 

 

 

 

 

 

 

 

 

Researchers were given a tour of the TerraLuma – UAS Remote Sensing lab at the University of Tasmania

The collaboration used the UTAS UAS with airborne LiDAR sensor.

 

 

Text by: Samuel Hillman

Leave a Reply

Required fields are marked *.


Skip to toolbar