Building Solar

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.

This work is copyright. Apart from any use as permitted under the Copyright Act 1968, no part may be reproduced by any process without prior written permission of Geoscape Australia.

Overview

The Building Solar Insight Pack is a national digital dataset representing solar information at the building level for each State and Territory in Australia. Solar information such as a solar flag (Yes/No presence of solar), solar area (combined area of all solar arrays relating to a building) and daily estimated power of these arrays are provided at the building level .

Geoscape Australia welcomes your feedback on our Building Solar Insight Pack. We also publish regular updates on the development of our products on the Geoscape website ( www.geoscape.com.au ).

Technical Description

Linkages

The Building Solar Insight Pack references buildings with solar information associated. A building in the Buildings product that has not been assessed for solar information will not be represented in the Building Solar Insight Pack.

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

Data format

The Building Solar 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_solar insights pack.

Data dictionary for building_solar

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_solar record.	No	Yes	DT_CREATE
date_modified	date (yyyy-mm-dd)	The most recent date that an attribute has been modified for the building_solar record.	No	No	DT_MOD
date_last_captured	date (yyyy-mm-dd)	The date of the image used for the most recent update of the solar_flag field.	No	Yes	DT_LST_CPT
capture_resolution	character string (6)	Resolution in centimeters of the imagery source used to capture the solar information.	No	Yes	CAPT_RES
capture_method	character string (20)	Type of imagery source used to capture the solar information (e.g. Aerial, Satellite, etc.).	No	Yes	CAPT_MTHD
solar_flag	character string (3)	Describes whether a visible photovoltaic solar panel is identified for the building (Yes/No).	No	Yes	SOLAR_FLAG
solar_area	number (10,2)	Total area of solar arrays related to the building in square meters.	No	No	SOLAR_AREA
daily_estimated_power	number (10,2)	Estimation of the power generated on an average day by all solar arrays for the building in kilowatt hours.	No	No	D_EST_PWR
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.

The rate of classification correctness of solar presence has been measured at above 85% where a photovoltaic solar panel is visible within the source imagery. Where a photovoltaic solar panel is not visible in the source imagery it is expected that the rate of classification correctness (in the negative) is greater than 90%. Other types of solar panels (e.g. solar hot water) may be captured and included in error.

Frequency and Currency

The Building Solar Insight Pack is released on a quarterly schedule for the months of March, June, September and December.

More Information

For more information on the Building Solar 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