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What data is available on a Property in DAS?
What data is available on a Property in DAS?
Updated over 2 weeks ago

DAS provides a comprehensive range of datasets to support informed decision-making about land and property. Below is an overview of the key data categories available within DAS, including how the data is displayed and sourced.
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These datasets are accessible when viewing a property and can be included in reports if selected. Additionally, each dataset within the DAS system includes an (i) information button, which provides details on how the data is calculated, sourced, or generated.
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πŸ“Œ Overview Tab

General Property Information

  • Addresses – Displays the addresses of buildings within the parcel, land area, title, or custom farm. If no formal postal address exists (common for rural properties), this field may be blank.

  • District (SA2) – Statistical Area Level 2 (SA2), as defined by the Australian Bureau of Statistics (ABS), representing gazetted suburbs or rural localities.

  • Shire/Local Authority – Local Government Area (LGA) boundaries, approximated by the ABS based on state and territory government definitions.

  • Agro-Ecological Region – Identifies one of 46 agro-ecological regions based on farming systems and environmental conditions.

Spatial & Identification Data

  • Area – Displays total land area (ha), calculated from the geographic polygon boundaries. Some farms may have disjointed polygons (separate pieces).

  • ID – A unique DAS identifier used for searching properties within the platform.

  • Planning Zone – Shows the spatial boundary of a planning zone, providing guidelines on land use, development, and protection.

  • Parcels – Lists parcel IDs and corresponding area (ha) per parcel.

Location Data

  • Nearest Population Centers – Shows the closest towns/cities, their distances, and estimated population.

  • Nearest Major Urban Center – Displays the closest large city and its distance from the property.

  • Directions – Provides a direct Google Maps link for navigation.

Buildings & Surface Water

  • Buildings – Lists building IDs and their total area (mΒ²).

  • Surface Water – Displays types of surface water (e.g., lakes, dams, rivers) and their total area (ha).


🌱 Land Use Tab

Land Classification & Agricultural Data

  • Agricultural Land Uses – Estimates primary land use based on management objectives, using the Australian Land Use and Management Classification (Version 8). Data varies from 2008 to 2023 depending on the mapping source.

  • Remnant Vegetation – Uses satellite imagery (25m resolution) to classify land as:

    • Forest (β‰₯20% canopy cover, β‰₯2m height, β‰₯0.2ha area)

    • Sparse-Woody (5-19% canopy cover)

    • Non-Woody

Soil & Terrain Data

  • Soil Types – Displays dominant soil types based on the Australian Soil Classification (ASC) at the order level.

  • Slope – Shows the average slope (Β°) of the land.

  • Elevation – Displays the average elevation (m) above sea level.

Crop Identification

  • Winter Crop ID – Uses AI, satellite imagery, and ground truth data to detect nine major crop types, plus vetch, pasture, and fallow land.

  • Summer Crop ID – Similar to winter crop ID but monitors eight major summer crops, with coverage across NSW, QLD, and VIC.

  • Last Data Update – Displays the latest recorded crop data.


πŸ“Š Output Tab

Potential Carrying Capacity

  • Non-Forested Area – Total area classified as non-woody or sparse-woody cover, based on satellite imagery.

  • DSE/ha – Dry Sheep Equivalent (DSE) benchmark per hectare (generalized).

  • DSE Total – Total DSE calculation for the property.

  • AE/ha – Adult Equivalent (AE) per hectare (calculated as DSE/ha Γ— 0.125).

  • AE Total – Total AE calculation for the property.

Long-Term Mean NPP (Net Primary Productivity)

  • Mean: X.XX kgC ha⁻¹ d⁻¹ – Measures plant productivity as kilograms of carbon stored per hectare per day. Uses 22+ years of data to smooth out seasonal variations.

Potential Crop Yield

  • Uses CSIRO's C-Crop Yield Prediction Algorithm for wheat, barley, and canola.

  • Estimates have a Β±32% margin of error due to variable factors like weather conditions, frost, and ripening effects.

  • Example Output:

    • Crop Type: Barley

    • Yield Estimate: 1.2 t/ha

    • Last Data Update: [Date]


🏑 Sale Tab

  • Valuer General Sales – Displays historical property sales data, including:

    • Date of Sale

    • Area of Sale (ha)

    • Price of Sale ($)

  • Sales are ordered from newest to oldest.


🌦 Climate Tab

Climate Data

  • Average Annual Rainfall – Displays long-term average (mm/year) based on the SILO climate database.

  • Growing Season – Classifies the primary growing season (Winter, Summer, or Perennial) based on median annual rainfall.

  • Nearest Weather Station – Lists the closest Bureau of Meteorology weather station and its distance from the property.

Rainfall Trends

  • Annual Rainfall Deciles – A trend chart comparing the property’s long-term rainfall with district averages.

  • Monthly Rainfall To Date – A year-to-date comparison of monthly rainfall against historical patterns.


⚠️ Risk Tab

Flood, Fire & Frost Risk

  • Flood Risk (0-5 Rating) – Based on 15 years of satellite-detected inundation records, estimating the likelihood of flooding.

  • Fire Risk (0-1 Rating) – Indicates potential fire intensity under catastrophic weather conditions (excludes probability assessment).

  • Frost Risk (X.XX Frost Days/Year) – Shows the average number of frost days per year (≀0Β°C temperatures) based on 1962-2024 data.

Rainfall Variability & Deficit

  • Rainfall Deficit – Identifies locations with significant rainfall deficits over the past 12 months compared to historical records (since 1900).

    • 1 in 10-year deficit: Below the 10th percentile

    • 1 in 20-year deficit: Below the 5th percentile

  • Rainfall Variability – Indicates whether an area’s rainfall is consistent (low variability) or highly irregular (high variability).


Final Notes

DAS provides powerful datasets that combine satellite imagery, AI-driven analytics, and official data sources to offer comprehensive insights into rural and agricultural properties.

πŸ“Œ If you have any questions or need further assistance, feel free to reach out!
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