How Do We Calculate Risk?

At DAS, we provide powerful risk assessment tools that help users evaluate potential environmental hazards affecting agricultural and rural properties. Our risk datasets are sourced from authoritative institutions, leveraging satellite imagery, climate models, and historical weather data to deliver precise, actionable insights.

Each risk dataset provides a unique perspective on environmental challenges, ensuring you can make informed decisions for property management, insurance, and investment.
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Source: CSIRO
Our flood risk assessment is based on historical inundation data from satellite remote sensing, covering records from 2001 to 2015. The index reflects the likelihood of a location experiencing flooding based on past occurrences, providing a valuable indicator of flood-prone areas.
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Source: CSIRO
DAS uses a Bushfire Intensity Index, which models fire behavior under catastrophic fire weather conditions. This index considers vegetation type, fuel load, and topography to estimate the potential intensity of a fire, should one occur. The risk is classified on a 1 to 5 scale, where 5 represents the highest fire intensity.
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Source: Australian Bureau of Meteorology (BoM)
Frost risk is calculated using long-term temperature datasets from BoM’s SILO database. The dataset measures the annual average number of frost days, defined as days where the minimum temperature falls below 0°C. This data helps assess the likelihood of frost damage to crops and infrastructure.
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Source: CSIRO
Rainfall deficit identifies areas experiencing significant reductions in rainfall compared to historical trends. The 12-month rainfall total is compared against data since 1900, classifying areas into:

Source: Bureau of Meteorology (BoM)
This dataset measures the consistency of rainfall patterns across different regions. Areas with low variability experience stable rainfall year after year, while high variability indicates unpredictable weather patterns with extreme wet and dry periods.
The variability index is categorized as:

Risk datasets are integrated into the Risk Panel inside DAS, alongside climate data and market insights. Users can visually explore risk factors and overlay them with other datasets to make informed, data-driven decisions.
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By leveraging these datasets, DAS provides a holistic risk assessment framework, enabling better planning, risk mitigation, and smarter agricultural investments.