Team Name

Codeless

Team Members

Project Description

Codeless has produced a product that provides a solution to the challenge 'Bushfire Ready'. The hack is a bushfire awareness application readily available for the general public to download. The application features a fire hazard map with real time data that alerts users when weather conditions escalate. The map shows the areas that are most at risk of catching fire through the use of slope, vegetation and weather severity data sets. When conditions start getting dangerous, users will be aware and can take the necessary precautions. The map also shows the locations of fire emergency stations and water bodies in the case of emergencies. Wildlife distributions are shown in order to provide animal rescue with significant locations to focus on. This hack will increase bushfire awareness and help to prevent damage to property and the wildlife.

Data Story

Datasets Selected

1 – Bushfire Prone Areas

This dataset was developed by the CSIRO in conjunction with QFES in order to develop multi-scale site assessments for bushfire risk. It combines:

• Maximum Slope Data – considers tendency of fire fronts to move down a slope

• Vegetation Hazard Classes – categorises vegetation based on effectiveness as a fuel source

• Fire Weather Severity – considers climate and weather conditions that may cause or worsen bushfires

2 – Location of Emergency Services

This dataset simply logs the vector point locations of emergency service locations. We extracted the specific locations of QFES facilities from this set.

3 – Wetland Areas QLD (Water Bodies)

Wetland areas shows categorised wetland or water body areas.

4 – Generalised Distribution and Densities of QLD Wildlife

This map shows relative distributions and densities of QLD wildlife. It is georeferenced to their location, and indicates the type of fauna, by metrics such as species, class and family.

Map Development Methodology

1. Each map was unpacked and imported into ArcMap, which was set-up with a GDA1994 datum and UTM zone 56 projected coordinate system.

2. The raster datasets (all of set 1) where reclassified to 5 tiers, with the following conditions:

The Slope Dataset was classified for values of 1-5 where 5 represented the steepest slope (least desirable result)

The vegetation hazard class data was classified for values 1-5 where 5 represented the most flammable vegetation classes

The fire weather conditions data was classified for values 1-5 where 5 represented the worst conditions

1. Set 2 (Emergency Service Locations) was imported:

The data for QFES locations was extracted as its own vector point layer.

Euclidean distance tool was then used to determine tiered distance from these locations.

Distance data was reclassified into 5 sets, such that 5 represented locations furthest from fire response

1. Set 3 (Wetland Locations) was imported:

Vector polygon to raster conversion was performed to align data with other data in the project

The data was then reclassified to 2 categories 0 and no data. This follows the logic that the presence of a wetland will eliminate potential for fires, however the lack of a wetland does not positively contribute to fire hazard overall.

1. A raster calculation was performed and reclassified to give 5 colour-coded categories for the largest danger and hazard class.

2. Set 4 (Generalised wildlife locations and density) was imported:

Due to extremely high data volumes, data that met the criteria of significant, land-dwelling species was extracted as the most at-risk.

The data was converted to raster form, and classified by the two main animal classes remaining – reptile and mammal.