Aerometrex Bushfire Fuel Load Mapping

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Drive FORESIGHT before it becomes HINDSIGHT

For more than 40 years, Aerometrex has been a leading supplier of ‘quantifiable knowledge’ to industries and Governments in Australia and across the world. After witnessing the devastation across the country over recent years, we sought to expand and deepen our engagement with industry, Government while also intensifying our research and development. The heightened focus was to ensure that we continued to provide the right knowledge, to the right people, at the right time. This expanded engagement combined with the research and development has resulted in world leading technology that provides clearer ‘visibility’ to all. This work has ensured that we can now provide the key missing pieces to the data that the Government, industry and the community need before the emergencies actually start. How much fuel is there, where is it located and what is it’s vertical structure? Why is knowing the fuel density and structure so important? - For a spark to move to a flame, then to a fire and then on to an ‘out of control’ situation, requires one variable more than any other – FUEL. Our solution provides clear and visible data on fuel load density and structure at any point. To put it simply, we know where the fuel is, and we know how much there is! That’s what we bring to your team – knowledge.

Contents The Very Real Cost Of Bushfires 3 The Missing Piece 6 Our Solution for Better Foresight 8 The Power of LIDAR 9 Fuel Density Mapping 16 The Way Forward 20



ustralia is no stranger to bushfires, the 2019-20 season, colloquially known as the Black Summer, proved to be unprecedented in many ways.

The first major bushfires began even before the official arrival of spring in June 2019. The situation worsened significantly at the beginning of November with increasing temperatures, a prolonged drought, and high winds. In mid-Jan 2020, a wave of heavy rain finally brought relief in some areas but was nowhere near sufficient to extinguish the fires. With great efforts from fire departments, emergency units, and volunteers across the nation, all fires were finally extinguished or contained by early March 2020 – nine months after the first ones began. Economists estimated that these bushfires may have cost us over A$103 billion in property damage and economic losses, making it Australia’s costliest natural disaster to date. Close to 80 percent of Australians were affected in some form or the other by the bushfires. There has been ongoing debate surrounding many aspects of the crisis, such as the underlying cause, the role of fire management practices and climate change, attracting significant international attention.


Bushfires and their impact on lives and livelihood


ushfires and their associated risk to property and the community are one of the most dangerous natural hazards Australian communities face. The ongoing effects of climate change are driving an increase in both the frequency and severity of natural hazards across Australia [1]. In the case of bushfire hazards, the bushfire season is set to increase in duration and catastrophic fire conditions are likely to become more common [2]. The 2019-20 bushfires devastated communities, destroyed wildlife populations, and led to extreme long-term impacts on the economy. The season showed us what damage wildfires can do, and how dangerous they can be for our communities and firefighters. An ANU poll estimated that 10.6 million, or over half of Australian adults, were anxious or worried for the safety of themselves, their close family, or their friends, due to the bushfire crisis. The scale of the disaster meant fire services across states were stretched in their capacity to respond, making it difficult to get to all fires fast enough. Additionally, fires started by lightning in remote areas made suppression difficult. Scientific experts and land management agencies


agree that severely below average fuel moisture attributed to record-breaking temperatures and drought, accompanied by severe fire weather, were the primary causes of the 2019–20 Australian bushfire season, and that these are likely to have been exacerbated by long-term trends of warmer and dryer weather observed over the Australian land mass. Recent studies suggest that Australian bushfires are becoming more extreme and less predictable, meaning that traditional bushfire management practices, bushfire prediction models and bushfire response techniques may be rendered less effective in the coming years [3]. In order to increase the Australian community’s preparedness and resilience to bushfire hazards, it is critical that we develop improved technologies to provide management experts, policy makers, front line firefighters and individuals in the community the best possible framework to prepare for, mitigate and suppress bushfire risks and hazards in Australia [4]. The 2019-20 season could have been even worse if conditions had combined to affect more population centres or if the drought had not caused a decline in grass fuel loads.



434 Million Tonnes

MILLION Hectares Burned



and 1 BILLION+ animals died


of CO2 Emitted

Buildings Destroyed


Image as seen on MetroMap

HEADER THE TEXT GOES MISSING HERE PIECE Accurate quantification of fuel loads to build more robust risk assessment models


uantifying bushfire fuel loads is a fundamental step in bushfire management and planning and is critical for better understanding the risks posed by bushfires to the community, the economy, and the environment. Numerous industry benchmark models and national standards rely on an accurate, quantitative assessments of the amount of vegetation fuel load to effectively model the behaviour, rate of spread and potential severity and impacts of a bushfire [5]. These models, combined with a detailed


understanding of the complex, dynamic relationship between the available fuel load, the regional topography and the local weather conditions at any point in time, are fundamental requirements needed to assess the potential risks posed by bushfire hazards to infrastructure, the community and individuals [6]. Before any regional bushfire behaviour modelling or risk and hazard assessments can be undertaken with confidence, a scientifically robust, subjective methodology of quantifying the amount of vegetation as a fuel source

Australia has a hugely diverse range of plant communities. The spatial distribution and physical structure of vegetation is critical in defining the fuel load properties of an ecosystem. However, many different species assemblages can have similar fuel properties and associated influences on bushfire behaviour [7]. When assessing overall fuel hazard in the field, vegetation is segmented into five fundamental vertical components defined by their height above ground: 1) Canopy fuel, 2) Bark fuel, 3) Elevated fuel, 4) Near-surface fuel and 5) Surface fuel or ground litter [8]. The attributes and structure of each vegetation layer have differing effects on bushfire dynamics. Vegetation and fuel characteristics have strong influences on bushfire behaviour including, but not limited to, rate of spread, flame height, fire-line intensity and suppression difficulty [9, 10]. Modern research has shown that not only defining the amount of available fuel within each vegetation layer but also quantifying the horizontal and vertical vegetation connectivity and continuity, is critical for estimating the potential fire behaviour, ease of suppression and developing effective fuel management practices to mitigate risk [11].

Historic and current fuel load assessment methods rely on direct and destructive field measurements that have been shown to be time and labour intensive, subjective, limited by local terrain and require detailed prior knowledge of end-member fuel types. Furthermore, given these localised methods, large amounts of generalisation and interpolation are required to produce regionalised fuel load estimates from a limited number of local point observations. The development of a subjective, quantitative method that would allow for the estimation of bushfire fuel loads across large areas represents a major potential expansion in the toolset available for bushfire risk mitigation and hazard reduction experts in the lead up to forthcoming fire seasons.


across large regions is required in order to produce a strong foundation upon which management programs and response strategies can be developed.

Furthermore, a detailed understanding of the distribution of high fuel loads across an area of interest as well as their proximity to homes and infrastructure would provide front line fire fighters with valuable, actionable information as they respond to, and attempt to suppress, active bushfire threats.


Drive FORESIGHT Before it becomes HINDSIGHT


ollowing on from the catastrophic 2019/2020 bushfire season, remote sensing technologies, such as Light Detecting and Ranging (LIDAR) have been identified as critical resources that have the potential to revolutionise bushfire management and response practices [4]. Airborne LIDAR is an active remote sensing technique which is used to produce high accuracy three dimensional models of the landscape. Up to two million individual laser pulses per second are emitted from a sensor within an aircraft as it flies above the area of interest. By measuring the time taken for each laser pulse to travel down to the surface and get reflected to the aircraft, the precise location of the point of reflectance can be calculated in three dimensions. Since LIDAR technology explicitly measures the landscape in three dimensions, it is often free of geometric distortions that can be associated with other imaging techniques. When an individual laser pulse is incident on a tree, shrub or any other vegetation, some of the energy is reflected back to the sensor from the very top of the vegetation and some energy penetrates through the canopy and accurately images the internal structure of the vegetation and even the


ground below. As a result of this penetrating power, Airborne LIDAR technology has been shown to be far more effective at accurately imaging vegetation structure in three dimensions and is more sensitive to variations in vegetation structure and density compared to other passive and active remote sensing techniques such as satellite imagery and RADAR [12, 13]. Recent studies in Australia have shown that in native Australian eucalypt forests, such as those common throughout the Adelaide hills, there is a strong statistical correlation between first order vegetation metrics derived from Airborne LIDAR (used as proxies for vegetation layer specific fuel loads) and field derived fuel load assessments, field based Overall Fuel Hazard Assessments (OFHA) and potential burn severity [14, 15 16]. The ability for LIDAR technology to measure vegetation structure, density, vertical connectivity and horizontal continuity below the tree canopy allows for the extraction of understorey fuel load estimates that would otherwise be fully obscured from view in satellite or aerial imagery by overlying canopy.

Small sample of a high resolution LIDAR data (left). Full classification (middle) allows for tree canopy to be removed to reveal near surface and elevated vegetation (right).









hroughout 2020, Aerometrex has undertaken an industry leading research project aimed at extending our current LIDAR derived vegetation mapping capabilities to include a set of targeted metrics specifically designed to quantitatively measure bushfire fuel loads across large areas of interest. The study has been carried out across an area of the Adelaide Hills, targeting the native heathy eucalypt forests within Belair National Park and surrounding areas. This region includes a wide range of bushfire fuel load hazard areas and bushfire risk zones previously assessed using nationally standardised methods by bushfire experts. The study is based on a world-leading suite of multidisciplinary datasets including Terrestrial LIDAR ground truths and standardised overall fuel hazard assessments at ten sites within Belair National Park, collected simultaneously with ultra-high-resolution Airborne LIDAR across the region. The project has three core objectives:


1. Undertake a detailed statistical assessment of the effectiveness of Airborne LIDAR to measure the threedimensional structure and density of the vegetation in native Australian bushland as well as along the urban-bush interface. 2. Develop an optimal LIDAR capture that provides the most accurate and costeffective foundation to produce regional fuel load estimates. 3. Develop a calibrated methodology to produce robust, accurate fuel load estimates across large areas of interest as well as fuel load information specific to individual properties.. Stage One of the research project has shown that Aerometrex has current capabilities to capture Airborne LIDAR data that allows for the vertical vegetation structure to be accurately imaged in threedimensions down to a height of 25 to 50 cm above ground, corresponding to the near-surface and elevated fuel load

layers [8]. This industry leading LIDAR capture and processing capabilities of Aerometrex has allowed our researchers to statistically model the effects of individual sensor and flight-planning parameters in order to define an optimal LIDAR resolution, capture geometry and processing methodology that provides the greatest degree of confidence in the derived targeted vegetation metrics, as well as being commercially and logistically viable across large areas of interest. Using the optimal capture as a foundational dataset, Aerometrex researchers have gone on to develop a set of targeted vegetation metrics that accurately define the density, vertical Upper Canopy

5m - Top of Canopy

Lower Canopy

2m - 5m

Elevated Near-surface Surface Fuel

connectivity and the horizontal continuity of the vegetation across the four key vegetation layers (near-surface, elevated lower canopy and upper canopy) which are analogous to those defined in South Australian bushfire fuel load assessment standards [8]. Proprietary algorithms were then developed that can be used to combine these fuel layer specific vegetation metrics into regional bushfire fuel load estimates that show strong statistical correlation with overall fuel assessments previously collected within the study area by bushfire management experts using South Australian standardised field methods.

0.6m - 2m 0.2m - 0.6m 0m -0.2m


Visibility of the



erometrex is uniquely poised to be able to provide Australia with multiresolution bushfire specific datasets in time for the upcoming bushfire season. This quantifiable knowledge can be provided to the relevant experts inside Government and industry to enable them to extrapolate out, on any given day, at any given hour, the relevant hazard and risk ratings which are based on this multiresolution bushfire specific dataset in combination with the current weather conditions. The key components here are data availability and scalability. This data can be scaled from a single metre by metre square, up through the needs of a single home, to a local community, onto a fire fighting team and right up to an entire region. It can be viewed as a simple online image or dissected within the necessary applications within Government and industry. This solution provides a wide range of data that is current, relevant, and most importantly, accurate. From wellestablished Airborne LIDAR derived topography and infrastructure products including Digital Terrain Models (DTM), slope maps, aspect maps to also providing high accuracy building footprints. In combination, this suite of Airborne LIDAR derived metrics has the potential to be


utilised by state and local government bushfire management experts as fundamental inputs that allow for the regional assessment of bushfire fuel hazards and the calculation of Bushfire Attack Level (BAL) ratings for individual dwellings [6]. With the data being fully available to areas inside Government, we can also provide an enhanced opportunity for the Government to fully empower the communities across Australia to be pro-active this season in saving their homes and lives. The datasets “It is important for emergency planners at all levels of government to have the best available information and input from appropriate experts and organisations. Relevant expertise and, importantly, local knowledge, may be needed from a range of government and non-government sources, including private sector operators, critical infrastructure providers, charities, medical practitioners, and wildlife and stock welfare groups. We have heard that some groups could have been better integrated, at the appropriate level, into natural disaster planning and management.â€? Royal Commission into National Natural Disaster Arrangements Š Commonwealth of Australia 2020.

1. High resolution aerial imagery with white dotted

2. Airborne LIDAR derived Near Surface (0.25m to 0.70m)

line showing the park boundary.

fuel density map.

3. Airborne LIDAR derived Elevated (0.70m to

4. Airborne LIDAR derived Lower Canopy (2.00m to 5.00m)

2.00m) fuel density map.

fuel density map.



5 . An Overall Fuel Density Index map generated by

6. A Vertical Connectivity map showing the vertical

combining all three fuel layers.

connectivity of the understorey vegetation (below 5m).




will also represent a powerful benchmark dataset that can be used to transition away from reactionary policies and planning and develop proactive management and mitigation practices and targets aimed at building community resilience in years to come. At your fingertips will be both a visual and spatial information database that the



Government can provide to all relevant agencies, councils, fire crews and even down to every individual household. In combination, our LIDAR derived bushfire fuel metrics provide a quantitative description of the spatial distribution and density of the fuel load as well as its horizontal continuity and vertical connectivity. 17

High accuracy LIDAR derived topographical datasets It is possible to derive very highresolution topographical datasets alongside regional fuel load metrics from a single optimised LIDAR capture. Valuable datasets such as aerial imagery, Digital Terrain Models (DTM), Slope Maps and Aspect Maps provide end-users with an accurate 3D model of the landscape. These datasets represent standardised inputs that are commonly used within fire behaviour, severity and rate of spread models (e.g. PEHONIX and Spark). By combining these datasets with Aerometrex’s fuel load metrics, it is possible for fire management experts to gain a detailed understanding of the relationship between the bushfire fuel complex and the local terrain allowing for well informed decision making, response plans and mitigaation policies.


1) High resolution aerial imagery, captured simultaneously to LIDAR data with a spatial resolution of 7cm 2) High accuracy Digital Terrain Model (DTM) and contours showing the bare-earth surface with a resolution of 25cm, enabling the qualitative investigations of the location and condition of access tracks. 3) High accuracy Slope Map which can be used for first order, qualitative assessments of ease of access to an area of interest. 4) High accuracy aspect map showing the direction of slope which can be compared to sun angle and wind direction.

Nationally Standardised Datasets Bushfire Attack Level (BAL) High resolution, property-scale fuel load attributes can be tailored to reflect specific attributes and parameters that are used for the calculation of national standard indices such as the Bushfire Attack Level, as defined by Australian Standard 3959, Construction of buildings in bushfire-prone areas (2009). Aerometrex’s property specific bushfire fuel

load metrics allow for the remote, automatic calculation of BAL for both existing dwelling and proposed future developments. Top Image: The overall fuel load within one hundred metres of a dwelling (white polygon). Bottom Image: The effective slope of the terrain (vectors) and zones of significant elevated fuel (blue) within 100 m of the same dwelling.



Significant Elevated Fuel Load




bove all else, a fire needs fuel to ignite, fuel to burn, fuel to grow. A fire needs fuel to survive. The risk and hazard levels associated with any region can change based on temperature, wind direction or strength and a multitude of ancillary variables, but if there is no fuel, there is no risk.

identify where to minimise the risks for the year ahead. This baseline data and ongoing seasonal change detection provides you with, for the first time, a science driven and data focused approach to fuel load awareness ensuring leading edge management across the wider regional areas of Australia.

Aerometrex is providing a unique and viable path forward for Government, industry, and the community as whole. By understanding and visualising the data that you cannot ‘see’ with satellite, aerial or drone imagery, you gain valuable insight into the fuel load density and its location underneath the tree canopy. It is this information that helps prepare for the future and helps you save lives. By understanding this information, you are better prepared to protect our communities.

By covering the critical locations of access roads, regional communities, and residential areas, you will have the appropriate information available when you need it – before a fire can begin. This will enable you to provide a pro-active stance in combination with the strong reactive approach that has been used to date.

We can provides you with this fuel load density mapping at critical times during the year. At the start of summer to help prepare for what is to come, and then an update at start of the winter to ensure you

Image as seen on MetroMap

References [1] Sharples, J.J., Cary, G.J., Fox-Hughes, P., Mooney, S., Evans, J.P., Fletcher, M.S., Fromm, M., Grierson, P.F., McRae, R. and Baker, P., 2016. Natural hazards in Australia: extreme bushfire. Climatic Change, 139(1), pp.85-99. [2] Colvin, R., Crimp, S., Lewis, S. and Howden, M., 2020. Implications of Climate Change for Future Disasters. In Natural Hazards and Disaster Justice (pp. 25-48). Palgrave Macmillan, Singapore. [3] Royal Commission into National Natural Disaster Arrangements: interim observations, 2020. Commonwealth of Australia. [4] Final Report of the NSW Bushfire Inquiry, 2020. Department of Premier and Cabinet (NSW) [5] Cruz, M., Sullivan, A., Leaonard, R., Malkin, S., Matthews, S., Gould, J., McCaw, W., Alexander, M., 2014. Fire Behaviour Knowledge in Australia: A synthesis of disciplinary and stakeholder knowledge on fire spread prediction capability and application. 1st ed. Australia: Bushfire CRC. [6] AS 3959: Construction of buildings in bushfire-prone areas, 2019. Standards Australia [7] Bradstock, R.A., Williams, J.E. and Gill, M.A. eds., 2002. Flammable Australia: the fire regimes and biodiversity of a continent. Cambridge University Press. [8] Overall Fuel Hazard Guide for South Australia, 2012. 2nd ed. Australia: Department of Environment and Natural Resources. [9] Cheney, N.P., Gould, J.S., McCaw, W.L. and Anderson, W.R., 2012. Predicting fire behaviour in dry eucalypt forest in southern Australia. Forest Ecology and Management, 280, pp.120-131. [10] Cruz, M.G., Matthews, S., Gould, J., Ellis, P., Henderson, M., Knight, I. and Watters, J., 2010. Fire dynamics in mallee-heath: fuel, weather and fire behaviour prediction in south Australian semi-arid shrublands. Bushfire Cooperative Research Centre, Report A, 10. [11] Gould, J.S., McCaw, W.L., Cheney, N.P., Ellis, P.F. and Matthews, S. eds., 2008. Field guide: fire in dry eucalypt forest: fuel assessment and fire behaviour prediction in dry eucalypt forest. CSIRO Publishing. [12] Chen, Q. 2013. Lidar remote sensing of vegetation biomass. In: Weng, Q. & Wang, G. (eds.) Remote sensing of natural resources [13] Dong, P. & Chen, Q. 2017. LiDAR for Forest Applications. LiDAR remote sensing and applications. CRC Press. [14] Chen, Y., 2017. LiDAR Application in Forest Fuel Measurements for Bushfire Hazard Mitigation (Doctoral dissertation, Faculty of Science, Monash University). [15] Leavesly, A., (2018). LIDAR Derived Fuel Map of the ACT. In Bushfire and Natural Hazards CRC & AFAC conference. Perth, 5 – 8 September 2018. Australia: Bushfire and Natural Hazards CRC. [16] Price, O.F. and Gordon, C.E., 2016. The potential for LiDAR technology to map fire fuel hazard over large areas of Australian forest. Journal of environmental management, 181, pp.663-673. [17] Independent Review into South Australia’s 2019-20 Bushfire Season. June 2020 Government of South Australia 21

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