Building Height

Insight Pack

Disclaimer

Geoscape Australia believes this publication to be correct at the time of printing and does not accept responsibility for any consequences arising from the use of the information herein. Readers should rely on their own skill and judgement to apply information to particular issues.

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Overview

The Building Height Insight Pack is a national digital dataset that provides building height information across all Australian states and territories. It includes attributes such as roof height, eave height, building volume and estimated floors, which are derived from building height information.

Detailed attribute definitions are provided in the data dictionary.

Technical Description

Coverage

The Building Height Insight Pack includes buildings that have height information available. This corresponds to buildings captured from aerial imagery in the Buildings product Buildings captured from satellite imagery do not have height attributes populated and are not included in this Insight Pack.

Linkages

The Building Height Insight Pack references buildings with height information associated. A building in the Buildings product with null values for height information will not be represented in the Building Height Insight Pack.

The building_pid attribute can be used to link the Building Height Insight Pack building_height table to the Buildings product buildings table. This is a 1:1 relationship - a building_height record will link to only one buildings record.

Data format

The Building Height Insight Pack is provided in the Pipe-Separated Values (PSV) file format and is an aspatial file.

Data Model

Data Dictionary

This data dictionary is applicable for the building_height insights pack.

Data dictionary for building_height

Attribute	Data Type	Description	Primary Key	Mandatory	10 Character Alias
building_pid	character string (15)	Persistent identifier for the building.	Yes	Yes	BLD_PID
date_created	date (yyyy-mm-dd)	The date of record creation for the building_height record.	No	Yes	DT_CREATE
date_modified	date (yyyy-mm-dd)	The most recent date that an attribute has been modified for the building_height record.	No	No	DT_MOD
roof_height	number (7,2)	The height of the tallest point on a building’s roof in metres.	No	Yes	ROOF_HGT
eave_height	number (7,2)	The average height of the part of a building’s roof that meets or overhangs the walls (eave) in metres.	No	Yes	EAVE_HGT
building_volume	number (10,2)	The volume of the building in cubic metres.	No	Yes	BLD_VOLUME
estimated_floors	number (3)	The estimated number of floors for the building.	No	Yes	EST_FLOOR
state	character string (3)	The abbreviated name of the State or Territory that the building is primarily within.	No	Yes	STATE

Thematic Quality

Thematic accuracy is defined as the accuracy of quantitative attributes, the correctness of non-quantitative attributes, and of the classification of features and their relationships. Data captured from aerial imagery represent the highest level of detail and quality within the dataset, while data captured from satellite imagery supports broad coverage and consistent identification.

Classification Correctness

Classification correctness is an assessment of the reliability of values assigned to features in the dataset in relation to their true ‘real world’ values.

Vertical Accuracy

Source elevation accuracy is dependent on the reference data used for the assignment of height and elevation attributes. Heights are derived either from satellite derived DSM or aerial derived stereo digitisation.

Source elevation data used for the derivation of building height attributes have absolute spatial accuracies described below:

• Absolute vertical (LE90) accuracy: ranging from 1m (aerial) to 2m (satellite).

• Relative vertical (LE90) accuracy: ranging from 1m (aerial) to 2m (satellite).

Multiple factors can impact the quality of the assigned elevation or height, these include but are not limited to:

• Age of source imagery: Where any imagery used within the production of the DSM is older than the date of construction of a building then the heights attributed to that building are likely to be erroneous.

• Correct classification of the feature: Where a building is not correctly defined (i.e. the highest point is not within the representation) then the height assigned to the feature has an increased likelihood of being erroneous.

• The omission of the feature: Where a building is not captured it cannot be assigned a height.

• Obscured building: Where a building is obscured by a tree or other feature then there is an increased likelihood of erroneous height values being assigned despite processes being run to

• Tree coverage surrounding a building: Where a building is surrounded by trees then the algorithm to calculate the roof height may struggle to obtain a representative ground elevation value. In these circumstances, there is an increased likelihood of an erroneous height assignment.

• The off-nadir angle of source imagery: Where imagery used for the classification of buildings is off-nadir the side of a building may be represented within the boundary of the footprint. Intersecting this part of the building against the DSM will return lower elevation values than those expected for the roof of the building. Where this occurs, there is an increased likelihood of an erroneous value being assigned to the eave height. The likelihood and impact of this issue are increased relative to the height of a building.

Frequency and Currency

The Building Height Insight Pack is updated on a quarterly release cycle in March, June, September and December.

The currency of individual building height records may vary across the dataset depending on when they were last captured or updated. Relevant dates are provided as attributes in the dataset.

More Information

For more information on the Building Height Insight Pack please contact Geoscape Australia Support.

Geoscape Australia Support

Geoscape Australia

Email: support@geoscape.com.au

Portal: support.geoscape.com.au

Web: www.geoscape.com.au