{"help": "https://data.gov.au/data/api/3/action/help_show?name=package_show", "success": true, "result": {"archived": false, "author": "", "author_email": null, "contact_point": "unknown", "creator_user_id": "c2fbbe4a-4ba0-4945-808b-67454605a4cf", "duplicate_score": 2, "geospatial_topic": [], "id": "d0753fff-929a-4cf0-adb4-6e0fb28f9763", "isopen": false, "license_id": "CC-BY-4.0", "license_title": "CC-BY-4.0", "maintainer": "", "maintainer_email": "", "metadata_created": "2025-11-15T11:59:38.087791", "metadata_modified": "2026-01-10T07:40:17.789436", "name": "aus_footprints_kalgoorlie_boulder_trafalgar_elev", "notes": "This foundational spatial dataset provides the building footprint geometries and contextual attributes that enable all rooftop solar analyses in the Kalgoorlie-Boulder collection, serving as the essential geographic framework linking solar potential to specific locations.\n\nThe dataset integrates Microsoft Bing building footprints with Australian Bureau of Statistics mesh block boundaries, elevation derived from the Elvis \u2013 Elevation and Depth (Geoscience Australia) dataset, and 2021 Census dwelling counts, creating a comprehensive spatial reference for approximately 16,000 buildings across 530 mesh blocks. Each footprint includes geometric attributes, statistical geography codes (SA1-SA4, mesh block), topographic classification, elevation, and population context.\n\nThis resource enables users to filter solar datasets by administrative boundaries, analyse potential across different land use categories, relate solar capacity to population density, or develop custom spatial queries joining solar metrics with other urban datasets. It serves as the join key between solar irradiance/potential estimates and real-world building locations.\n\nCritical applications include spatial planning analysis (identifying high-potential zones for solar incentive programs), equity assessment (evaluating renewable energy access across socio-economic areas), and infrastructure planning (relating distributed generation potential to grid connection points). GIS analysts can use mesh block and SA codes to integrate solar data with ABS Census statistics, health data, or other spatially-referenced datasets.\n\nFootprints represent 2013-2018 building stock and may not capture recent construction. Elevation values support topographic context, but solar calculations use flat-roof assumptions. This is the recommended base layer for all spatial analyses using the solar datasets.\n\nComprehensive technical documentation, including data dictionary, usage examples, and processing methodology, is available in <a href=\"https://resources.aurin.org.au/ckan/resources/DataSet-Information.pdf\">here</a>; software stack details and calculation workflows are documented in <a href=\"https://resources.aurin.org.au/ckan/resources/Software_Stack.pdf\">here</a>.", "num_resources": 1, "num_tags": 5, "organization": {"id": "b0429d6f-82d8-4c5f-9325-37b64b9b1c48", "name": "school-of-electrical-engineering-computing-and-mathematical-sciences-curtin-university-australian-ur", "title": "School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University", "type": "organization", "description": "Our school brings together Curtin\u2019s core capabilities across electrical engineering, computing, physics and mathematics, to better understand and advance our data-driven world. We have built substantial knowledge in machine learning, cyber security, statistics and optimisation, digital transformation, radio astronomy, the Internet of Things, signal processing, embedded systems, renewable and power engineering. The school offers a range of undergraduate and postgraduate courses across these areas, which give students the skills they need to tackle the challenges of the future. The school attracts millions of dollars of research income each year, the majority of which is from industry, reflecting the focus of the school on demand driven research. The school is home to some of the largest institutes and centres at Curtin.", "image_url": "", "created": "2025-11-15T22:58:53.507896", "is_organization": true, "approval_status": "approved", "state": "active"}, "original_harvest_source": {"site_url": "https://data.aurin.org.au/", "href": "https://data.aurin.org.au/dataset/aus_footprints_kalgoorlie_boulder_trafalgar_elev", "title": "Australian Urban Research Infrastructure Network"}, "original_name": "aus_footprints_kalgoorlie_boulder_trafalgar_elev", "owner_org": "b0429d6f-82d8-4c5f-9325-37b64b9b1c48", "private": false, "promotion_level": "0", "remote_last_updated": "2025-12-23T05:41:38.599261", "spatial": "{\"type\": \"Polygon\", \"coordinates\": [[[121.42359807500652, -30.803203268101967], [121.53928549242828, -30.803203268101967], [121.53928549242828, -30.71136853194179], [121.42359807500652, -30.71136853194179], [121.42359807500652, -30.803203268101967]]]}", "spatial_coverage": "{\"type\": \"Polygon\", \"coordinates\": [[[121.42359807500652, -30.803203268101967], [121.53928549242828, -30.803203268101967], [121.53928549242828, -30.71136853194179], [121.42359807500652, -30.71136853194179], [121.42359807500652, -30.803203268101967]]]}", "state": "active", "temporal_coverage_from": "2025-10-16 06:57:17.522713", "title": "Kalgoorlie-Boulder Photo-Voltaic (PV) Potential Maps: Australian Footprints (Kalgoorlie, Boulder, Trafalgar)", "type": "dataset", "unpublished": false, "url": "", "version": "", "extras": [{"key": "harvest_object_id", "value": "389bb705-8110-4c72-9f5d-f31d20c4facc"}, {"key": "harvest_source_id", "value": "3b753826-54f7-43e3-8246-4b09aaee723f"}, {"key": "harvest_source_title", "value": "Australian Urban Research Infrastructure Network"}], "resources": [{"cache_last_updated": null, "cache_url": null, "created": "2025-10-16T06:57:17.524447", "datastore_active": false, "datastore_contains_all_records_of_source_file": false, "description": "Download this dataset via the AURIN Download Manager", "format": "HTML", "hash": "", "id": "4357b54b-076b-480f-9e98-ea23feaa18b6", "last_modified": null, "metadata_modified": "2026-01-10T07:40:17.823256", "mimetype": null, "mimetype_inner": null, "name": "AURIN Download Manager", "package_id": "d0753fff-929a-4cf0-adb4-6e0fb28f9763", "position": 0, "resource_type": "file", "size": null, "state": "active", "url": "https://adp-access.aurin.org.au/dataset/aus_footprints_kalgoorlie_boulder_trafalgar_elev", "url_type": null, "zip_extract": false}], "tags": [{"display_name": "PV Potential", "id": "3fc5ffe2-14f8-4d48-93cf-8d0f243a44fa", "name": "PV Potential", "state": "active", "vocabulary_id": null}, {"display_name": "PV Rooftops", "id": "2612481d-6d17-4a49-b711-743a47df5eaa", "name": "PV Rooftops", "state": "active", "vocabulary_id": null}, {"display_name": "Photo-Voltaic", "id": "10b08dc0-473f-4a27-ae96-a73848a59109", "name": "Photo-Voltaic", "state": "active", "vocabulary_id": null}, {"display_name": "Solar Irradiance Estimation", "id": "b492f980-23aa-4324-bf8a-d8a622d2837a", "name": "Solar Irradiance Estimation", "state": "active", "vocabulary_id": null}, {"display_name": "Urban Rooftop Aggregation", "id": "938017db-5128-4f59-b7a0-30218ff142a2", "name": "Urban Rooftop Aggregation", "state": "active", "vocabulary_id": null}], "groups": [], "relationships_as_subject": [], "relationships_as_object": []}}