Visualising Potential Bushfire Risk for Addresses in Australia: A New Cloud-based Approach
25 October 2017
It’s well known that hundreds of thousands of Australian properties (e.g. residential, commercial and industrial) at the urban-bushland interface are very prone to damaging bushfires. Increasing population, urban encroachment into bushland and a dangerous warming climate all suggest that bushfire risk is on the increase.
Bushfire risk assessment has been a very active research field in Australia over the past few decades. Major topics in relation to emergency and insurance applications include:
developing metrics to quantify bushfire risk in space and time;
bushfire behaviour and propagation simulations taking into consideration a range of contributing factors (e.g. topography, weather and fuel loads); and
fire monitoring and fire scar mapping with modern Earth observation. Figure 1 below shows some more recent fires captured by Landsat-8 and Sentinel-2 satellite imagery were in the vicinity of settlement.
Figure 1: A few recent bushfires in Australia captured by satellite imagery.
The new cloud-based, automated approach we have developed focuses on visualising bushfire risk in terms of the distance between bushland and exposure locations, and the potential effect of fire penetration into urban areas. We believe this will help communicate bushfire risk to the public (including end users in emergency, insurance and the news media) in a more explicit and engaging way.
Figures 2 and 3 demonstrate animations specific to two bushfire-prone addresses in New South Wales and Western Australia, respectively.
Bushfire risk to areas adjacent to bushland may seem obvious but our visualisation approach includes four key features:
(1) highlighting major bushland that poses risk;
(2) calculating the shortest distance from an exposure location to nearby bushland;
(3) a dynamic representation of distance range changes (a future version may enhance this aspect); and
(4) for the first time that such an automated approach is developed for all addresses (or broadly, neighbourhoods and suburbs) at the national level.
For this work, the accuracy of classified bushland is very important. As the approach is generic, if a new bushland dataset is available, it can easily replace the old one for fresh calculation and rendering. If a user seeks more location-specific attributes such as the percentage of vegetation in an area of interest, we suggest the user obtain complementary location profile reports via PropertyLocation.com.au. Each animation or location profile report can be generated and delivered within seconds with the cloud-based platform.
Figure 2: Bushfire risk animation for an address in Sydney, NSW.
Figure 3: Bushfire risk animation for an address in WA.
At this point, it’s useful to take stock of our capabilities of producing location profile reports and complementary animations for addresses in Australia, the US (focus on the Contiguous US, CONUS), and the rest of the world. In general, high-resolution imagery and elevation data has been used for Australia and the US, while medium-resolution data adopted for the rest of the world. But note that the underling geospatial big data analytics is generic with the cloud platforms (PropertyLocation.com.au and PropertyLocation360.com), and if finer resolution data is available for a new region, the same type of analysis can be applied.
Figure 4 shows the progress so far:
Location profile reports with varying levels of details can be readily produced for any location.
Animation on bushfire risk is introduced in this blog. The same capability can be extended to CONUS using the unique data resources from BigData Earth, which were summarised in the previous blog.
Animation on flood risk by elevation (suitable for low-lying coastal areas and flat floodplains) has been developed.
Animation on flood risk by water levels and water depths (related to riverine flood and flash flood) is ongoing for larger coverage areas. Contracted regions and catchments always take precedence.
For details, please check many sample reports and animations at the above websites. For any more information, feel free to contact us.
Figure 4: BigData Earth’s progress in producing cloud-based, address-level location profile reports and animations.