From Western Australia Government
JSON RDF ISO19115-3 XML

Deep Learning Impermeable Surfaces 2024 (LGATE-488)

Created 13/01/2025

Updated 01/04/2025

JSON RDF ISO19115-3 XML

Raster dataset containing the results from 4 separate binary deep learning models (Buildings, Roads, Footpaths & Impermeable Surfaces). The following classification is used: 0 - Any permeable, 1- Buildings, 2 - Roads, 3 - Footpaths, 4 - Any other impermeable. Best results are present in suburban areas.

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Additional Info

Field Value
Title Deep Learning Impermeable Surfaces 2024 (LGATE-488)
Language English
Licence custom_other
Landing Page https://devweb.dga.links.com.au/data/dataset/b871027b-5cdd-4c74-be1a-4f70382c6d38
Contact Point
Department of Planning (Western Australia)
corporate@planning.wa.gov.au
Geospatial Coverage http://www.ga.gov.au/place-names/PlaceDetails.jsp?fctext=RESV&fctext=POPL&fctext=STAT&submit1=GA7
Data Portal data.gov.au

Data Source

This dataset was originally found on data.gov.au "Deep Learning Impermeable Surfaces 2024 (LGATE-488)". Please visit the source to access the original metadata of the dataset:
https://devweb.dga.links.com.au/data/dataset/deep-learning-impermeable-surfaces-2024

Original dataset
Dataset copies

No duplicate datasets found.