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Let’s get technical


Product Description

The Geoscape Product Description (5mb PDF) provides detailed information on the dataset including scope, content and structure, quality, maintenance and delivery.


Online Data Delivery System Guide

The Online Data Delivery System is a warehouse to hold, check quality and distribute PSMA Australia’s suite of national spatial datasets. Read the guide.


Geoscape Product Brochure

The Geoscape Product Brochure gives a quick overview of the main features and benefits of Geoscape.

Frequently Asked Questions

What is Geoscape?

Geoscape is a suite of digital datasets representing buildings, surface cover and trees across the whole of Australia. The purpose of the Geoscape national dataset is to spatially represent building and related features for use by industry and government in digital applications and systems. It has links to other PSMA Australia products including G-NAF (addresses), CadLite (cadastre and property) and Administrative Boundaries (suburb/localities).

Why is a building’s data missing in Geoscape?

There may be a few reasons, such as:

  • the building may beconsidered smaller in area than 9m2
  • the building was missed by the DigitalGlobe process (generally ~99% of all buildings are captured, with usually only smaller buildings occasionally missed)

the building didn’t exist when DigitalGlobe captured their imagery.

Why are some height values not accurate for trees that are close to buildings?

Where tall features like buildings and trees exist, the terrain has been smoothed and areas in close proximity to some of these high features appear to have higher than expected terrain values. With higher than expected terrain values, tree pixels close to tall buildings or other tall trees may appear to have lower than expected resulting tree heights. We’re working closely with data contributors to fix this issue and expect tree heights will become more accurate in future releases of Geoscape.

Why are some roof material classifications incorrect?

We have identified an over-classification of buildings with a primary roof material of ‘Tile’. These are more evident in areas of industrial zoning and buildings with iron appearance. We’re working with data contributors keep improving the classification accuracy of roof materials.

How are you going to improve the data quality for surface cover?

Surface cover for both 2-metre and 30-metre resolution is captured and supplied to us in ‘strips’ defined by satellite coverage. Variation in ‘strips’ may be dependent on a number of factors including the classification, atmospheric corrections, weather, and season when the image was captured. We’re working with contributors to improve classification consistency for both datasets.

What are you doing to ensure accuracy when measuring heights in a new suburb with new buildings being erected?

Maximum Roof Heights and Average Eave Heights for buildings are dependent on the date of capture of source imagery, which is used in the creation of the Digital Surface Model. Where buildings are part of a new development or re-development, these heights are impacted. We’re investigating ways to identify or remediate the accuracy of heights across the dataset and specifically in new development or re-development areas.

When will you have an accurate reflection of ‘real world trees’?

Although we’ve tried to capture and represent real world trees as accurately as possible, a number of individual trees have not been captured in the trees dataset. We’re working to improve trees, including improvements to source heights, classifications and improved capture dates.

How are you moving forward with boundary alignment results? (State/Territory Mesh blocks)

The misalignment of boundaries has resulted in a building (BUILDING_PID = BLDNSW0001772595) being allocated a Mesh Block in a different state/territory. We’re working to fix some of the issues in the boundary misalignment to better reflect the allocation of Mesh Blocks, Suburbs/Localities and state/territories.

In regards to an over-classification of water in places like airports, how can you be certain that it was not a rainy day when the images were taken?

We’ve identified that in some areas of the 2m Surface Cover, specifically bitumen, there is an over-classification of water. Although most roads appear unaffected, areas like airport runways have a clear over-classification. We’re working with contributors to improve the classification of bitumen for future releases.


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