Road crash locations, South Australia
liveOne row per location where a road crash was reported to South Australia Police from 2020 to 2024. Each row carries the site's coordinates, the number of crashes there, and counts of those crashes by severity (property damage, injury, serious injury, fatal), by type (rear end, hit fixed object, head on and others), at night, and involving a bicycle or a pedestrian, with the numbers of casualties, serious injuries and deaths.
The Department for Infrastructure and Transport releases a new five-year file each year.
Also called: Road Crash Locations in SA, SA crash sites, South Australian car accident locations, DIT road crash data.
- Is each row one crash?
- No. Each row is one location where crashes happened in the five years, with the number of crashes there and counts by severity, crash type and road user. The publisher's separate Road Crash Data files on the portal have one row per crash, without coordinates.
- Why does the file cover only five years?
- The publisher releases a new five-year file each year and keeps the earlier files on the portal. This dataset follows the newest file, so each release becomes a version here.
- Which coordinates are these?
- The publisher supplies the same file in GDA94 and GDA2020. This dataset uses the GDA2020 file, which is the current national datum.
Made for agents
Connect your AI agent
Any agent that connects to publicdata.au/mcp can find this dataset, read its 40 fields, count and filter across all 43,522 rows and diff its versions. Every answer names the version and carries Infrastructure and Transport's attribution. No key.
Then ask it: What does Road crash locations, South Australia hold, and what changed in the newest version?
claude mcp add --transport http publicdata https://publicdata.au/mcpOne command. No key, no account, no sign-up.
Settings, then Connectors, then Add custom connector, and paste https://publicdata.au/mcp.
On the web and in the desktop app.
https://publicdata.au/mcpStreamable HTTP. Cursor, VS Code or any client that connects to a remote MCP server.
Using https://publicdata.au/llms.txt, how many people died on Queensland roads in 2025, by month?For an assistant that reads the web and has no connector.
A dashboard over every row. Click to filter, add panels, share a link or embed a frame.
Query APIFilter and count from a URLaggregate?group=lga_2025_name&metric=sum.total_fatalities
Deaths by council area (lga 2025): 29 Unincorporated SA, 27 Salisbury, 25 Adelaide Hills, 22 Onkaparinga.
Download it as Excel, CSV, JSON and 9 more formats
Pick a format and a version. Excel is picked first because it opens in the tools most offices have. The URL is yours to keep. A dated version never changes.
In your own tools
Use it in Excel, R, Python and more
Excel and Power BI read the CSV from its address and refresh from it. The R and Python packages take any dataset on this site by its slug, so a new dataset needs no new release. The DuckDB file attaches read-only over HTTPS, and a query reads only the blocks it touches.
The dated URL in the code never changes. https://publicdata.au/d/sa-road-crash-locations/latest/ redirects to the newest version.
https://publicdata.au/d/sa-road-crash-locations/latest/data.csvIn Excel choose Data, then From Web, and paste this address. Excel keeps it, so Refresh All reads the newest version. A sheet holds about a million rows; past that, load the query to the Data Model.
https://publicdata.au/d/sa-road-crash-locations/latest/data.csvIn Power BI Desktop choose Get data, then Web, paste this address and choose Anonymous when asked how to sign in. A scheduled refresh reads the same address, so the report follows each new version.
library(publicdataau)
df <- pd_read("sa-road-crash-locations")
pd_attribution(df)install.packages("publicdataau"). pd_read() fetches the version's Parquet file; pd_rows() and pd_aggregate() ask the query API instead, and pd_connect() attaches the DuckDB file.
import publicdata_au as pd_au
df = pd_au.read("sa-road-crash-locations")
df.attrs["publicdata"]["attribution"]pip install "publicdata-au[pandas]". read() fetches the version's Parquet file; rows() and aggregate() ask the query API, and connect() attaches the DuckDB file.
INSTALL httpfs; LOAD httpfs;
ATTACH 'https://publicdata.au/d/sa-road-crash-locations/v/2025-09-19/data.duckdb' AS sa_road_crash_locations (READ_ONLY);
SELECT unique_loc, count(*) FROM sa_road_crash_locations.records GROUP BY 1 ORDER BY 2 DESC;The DuckDB file attaches read-only over HTTPS and only the blocks a query touches are read. Parquet works the same way: FROM read_parquet(url).
const res = await fetch("https://publicdata.au/api/v1/datasets/sa-road-crash-locations/aggregate?group=lga_2025_name&metric=sum.total_fatalities");
const { rows, publicdata } = await res.json();
console.log(rows, publicdata.attribution);The query API answers a page on any site as well as Node, with no key. It returns the rows and the attribution the licence asks for.
What is in it
Column names are made snake_case and the publisher's original header is kept beside each one. Blank cells are null. Nothing is added, removed, ranked or summarised. Cells were typed and the point geometry became longitude and latitude fields. The publisher's property names are kept beside every field in schema.json. Rows were left alone.
| Field | Type | Publisher's header | Note |
|---|---|---|---|
| unique_loc | string | unique_loc | The publisher's identifier for the location. Kept as text to preserve leading zeros. |
| longitude | number | (longitude) | Decimal degrees, GDA2020, from the point geometry. |
| latitude | number | (latitude) | Decimal degrees, GDA2020, from the point geometry. |
| total_crashes | integer | total_crashes | |
| cse_pdo | integer | cse_pdo | |
| cse_inj | integer | cse_inj | |
| cse_fat | integer | cse_fat | |
| cse_si | integer | cse_si | |
| total_casualties | integer | total_casualties | |
| total_fatalities | integer | total_fatalities | |
| total_serious_injuries | integer | total_serious_injuries | |
| cty_rear_end | integer | cty_rear_end | |
| cty_hit_fixed_object | integer | cty_hit_fixed_object | |
| cty_side_swipe | integer | cty_side_swipe | |
| cty_right_angle | integer | cty_right_angle | |
| cty_head_on | integer | cty_head_on | |
| cty_hit_pedestrian | integer | cty_hit_pedestrian | |
| cty_roll_over | integer | cty_roll_over | |
| cty_right_turn | integer | cty_right_turn | |
| cty_hit_parked_vehile | integer | cty_hit_parked_vehile | The publisher's header spells vehicle as vehile. |
| cty_hit_animal | integer | cty_hit_animal | |
| cty_hit_object_on_road | integer | cty_hit_object_on_road | |
| cty_left_road_oc | integer | cty_left_road_oc | |
| cty_other | integer | cty_other | |
| cty_unknown | integer | cty_unknown | |
| uty_bicycle | integer | uty_bicycle | |
| uty_pedestrian | integer | uty_pedestrian | |
| lco_night | integer | lco_night | |
| sa2_2021_code | string | (spine: sa2) | Code of the Statistical Area Level 2 (2021) the point falls in. Joined by location from abs-sa2-2021, not published by the publisher. |
| sa2_2021_name | string | (spine: sa2) | Name of the Statistical Area Level 2 (2021) the point falls in. Joined by location from abs-sa2-2021, not published by the publisher. |
| lga_2025_code | string | (spine: lga) | Code of the Local Government Area (2025) the point falls in. Joined by location from abs-lga-2025, not published by the publisher. |
| lga_2025_name | string | (spine: lga) | Name of the Local Government Area (2025) the point falls in. Joined by location from abs-lga-2025, not published by the publisher. |
| sal_2021_code | string | (spine: suburb) | Code of the Suburb and Locality (2021) the point falls in. Joined by location from abs-suburbs-localities-2021, not published by the publisher. |
| sal_2021_name | string | (spine: suburb) | Name of the Suburb and Locality (2021) the point falls in. Joined by location from abs-suburbs-localities-2021, not published by the publisher. |
| poa_2021_code | string | (spine: postcode) | Code of the Postal Area (2021) the point falls in. Joined by location from abs-postal-areas-2021, not published by the publisher. |
| poa_2021_name | string | (spine: postcode) | Name of the Postal Area (2021) the point falls in. Joined by location from abs-postal-areas-2021, not published by the publisher. |
| sed_2025_code | string | (spine: state_electorate) | Code of the State Electoral Division (2025) the point falls in. Joined by location from abs-state-electoral-divisions-2025, not published by the publisher. |
| sed_2025_name | string | (spine: state_electorate) | Name of the State Electoral Division (2025) the point falls in. Joined by location from abs-state-electoral-divisions-2025, not published by the publisher. |
| ced_2025_code | string | (spine: federal_electorate) | Code of the Commonwealth Electoral Division (2025) the point falls in. Joined by location from abs-federal-electoral-divisions-2025, not published by the publisher. |
| ced_2025_name | string | (spine: federal_electorate) | Name of the Commonwealth Electoral Division (2025) the point falls in. Joined by location from abs-federal-electoral-divisions-2025, not published by the publisher. |
Download this table as a data dictionary (Excel), or read it as a Frictionless Table Schema at schema.json. The key is unique_loc.
A sample of 10 rows
The ten sites with the most crashes in the five years, most first. A blank cell is shown as null.
| unique_loc | longitude | latitude | total_crashes | cse_pdo | cse_inj | cse_fat | cse_si | total_casualties | total_fatalities | total_serious_injuries | cty_rear_end | cty_hit_fixed_object | cty_side_swipe | cty_right_angle | cty_head_on | cty_hit_pedestrian | cty_roll_over | cty_right_turn | cty_hit_parked_vehile | cty_hit_animal | cty_hit_object_on_road | cty_left_road_oc | cty_other | cty_unknown | uty_bicycle | uty_pedestrian | lco_night | sa2_2021_code | sa2_2021_name | lga_2025_code | lga_2025_name | sal_2021_code | sal_2021_name | poa_2021_code | poa_2021_name | sed_2025_code | sed_2025_name | ced_2025_code | ced_2025_name |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 13306231670362 | 138.623404838 | -34.927886033 | 119 | 102 | 17 | 0 | 1 | 18 | 0 | 1 | 16 | 6 | 12 | 85 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 26 | 401011001 | Adelaide | 40070 | Adelaide | 40002 | Adelaide | 5000 | 5000 | 40001 | Adelaide | 401 | Adelaide |
| 13323731666371 | 138.644042057 | -34.963349355 | 68 | 52 | 16 | 0 | 3 | 25 | 0 | 5 | 25 | 3 | 36 | 2 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 13 | 401071024 | Unley - Parkside | 47980 | Unley | 40999 | Myrtle Bank (SA) | 5064 | 5064 | 40044 | Unley | 410 | Sturt |
| 13337861674517 | 138.65649356 | -34.889452265 | 57 | 42 | 15 | 0 | 3 | 25 | 0 | 4 | 11 | 4 | 2 | 4 | 0 | 0 | 0 | 36 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 22 | 401051018 | Payneham - Felixstow | 45290 | Norwood Payneham and St Peters | 40515 | Glynde | 5070 | 5070 | 40020 | Hartley | 410 | Sturt |
| 13296901660049 | 138.616971843 | -35.021178223 | 49 | 42 | 7 | 0 | 0 | 7 | 0 | 0 | 1 | 1 | 11 | 36 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 6 | 403031067 | Blackwood | 44340 | Mitcham | 40119 | Blackwood (SA) | 5051 | 5051 | 40045 | Waite | 403 | Boothby |
| 13318741670399 | 138.637090477 | -34.927174839 | 49 | 33 | 16 | 0 | 1 | 22 | 0 | 1 | 0 | 0 | 0 | 30 | 0 | 0 | 1 | 18 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 8 | 401051017 | Norwood (SA) | 45290 | Norwood Payneham and St Peters | 41053 | Norwood (SA) | 5067 | 5067 | 40010 | Dunstan | 410 | Sturt |
| 13241231670939 | 138.552010461 | -34.924630208 | 48 | 30 | 18 | 0 | 4 | 26 | 0 | 5 | 3 | 2 | 0 | 1 | 0 | 0 | 0 | 42 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 19 | 404031108 | Richmond (SA) | 48410 | West Torrens | 41466 | Torrensville | 5031 | 5031 | 40046 | West Torrens | 401 | Adelaide |
| 13301521690823 | 138.610748976 | -34.743472739 | 44 | 29 | 15 | 0 | 0 | 16 | 0 | 0 | 3 | 1 | 0 | 40 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 19 | 402041048 | Salisbury North | 47140 | Salisbury | 40196 | Burton (SA) | 5110 | 5110 | 40038 | Ramsay | 409 | Spence |
| 13314021697661 | 138.621900805 | -34.681408679 | 44 | 34 | 10 | 0 | 1 | 12 | 0 | 1 | 6 | 4 | 15 | 16 | 0 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 11 | 402021035 | Virginia - Waterloo Corner | 45680 | Playford | 41133 | Penfield | 5121 | 5121 | 40042 | Taylor | 409 | Spence |
| 13288631676433 | 138.601905497 | -34.873661477 | 39 | 29 | 10 | 0 | 1 | 11 | 0 | 1 | 17 | 1 | 4 | 3 | 0 | 1 | 0 | 12 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 12 | 401061021 | Prospect | 46510 | Prospect | 41220 | Prospect (SA) | 5082 | 5082 | 40013 | Enfield | 401 | Adelaide |
| 13257791667717 | 138.57130707 | -34.953195246 | 37 | 25 | 12 | 0 | 1 | 14 | 0 | 1 | 3 | 0 | 1 | 3 | 0 | 0 | 0 | 30 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 404031107 | Plympton | 48410 | West Torrens | 40728 | Kurralta Park | 5037 | 5037 | 40002 | Badcoe | 401 | Adelaide |
The first row as JSON
As it appears in data.json.
GET https://publicdata.au/d/sa-road-crash-locations/latest/data.json
{
"unique_loc": "06672192063094",
"longitude": 131.49268236900002,
"latitude": -31.38073715799993,
"total_crashes": 1,
"cse_pdo": 1,
"cse_inj": 0,
"cse_fat": 0,
"cse_si": 0,
"total_casualties": 0,
"total_fatalities": 0,
"total_serious_injuries": 0,
"cty_rear_end": 0,
"cty_hit_fixed_object": 1,
"cty_side_swipe": 0,
"cty_right_angle": 0,
"cty_head_on": 0,
"cty_hit_pedestrian": 0,
"cty_roll_over": 0,
"cty_right_turn": 0,
"cty_hit_parked_vehile": 0,
"cty_hit_animal": 0,
"cty_hit_object_on_road": 0,
"cty_left_road_oc": 0,
"cty_other": 0,
"cty_unknown": 0,
"uty_bicycle": 0,
"uty_pedestrian": 0,
"lco_night": 0,
"sa2_2021_code": "406011134",
"sa2_2021_name": "West Coast (SA)",
"lga_2025_code": "49399",
"lga_2025_name": "Unincorporated SA",
"sal_2021_code": "41669",
"sal_2021_name": "Yalata",
"poa_2021_code": "5690",
"poa_2021_name": "5690",
"sed_2025_code": "40015",
"sed_2025_name": "Flinders",
"ced_2025_code": "404",
"ced_2025_name": "Grey"
}
Query it without downloading
The query API returns only the rows you ask for, as JSON, NDJSON or CSV, from the same typed rows as the files. It needs no key. Build a query here and run it, then copy the URL or the code into your own work.
How filters work
Each filter is field=operator.value in the query string, and every filter must match. A number or date field compares as a number or date, and a text field compares as text. Values are case-sensitive except with ilike. Prefix not. to negate a filter, as not.eq.value.
| Operator | What it matches |
|---|---|
| eq.value | Equal to the value. |
| neq.value | Not equal to the value. A blank cell does not match. |
| gt.value | Greater than the value. |
| gte.value | Greater than or equal to the value. |
| lt.value | Less than the value. |
| lte.value | Less than or equal to the value. |
| like.*text* | Matches a pattern where * stands for any run of characters. Case-sensitive. |
| ilike.*text* | The same as like, ignoring case. |
| in.(a,b,c) | Equal to any value in the list. A value cannot contain a comma. |
| is.null | Blank in the source, or suppressed by the publisher. |
| Parameter | What it does |
|---|---|
| select | Fields to return, comma-separated. Every field when absent. |
| order | field.asc or field.desc, comma-separated. The publisher's row order when absent. |
| limit | Rows per page, 1 to 10,000. 100 when absent. |
| offset | Rows to skip. The next URL in each answer sets it for you. |
| group | On aggregate, fields to group by, comma-separated. |
| metric | On aggregate, count, sum.field, avg.field, min.field or max.field, comma-separated. count when absent. |
| format | json, ndjson or csv. JSON carries the provenance header, and the others carry it in response headers. |
Without a version the API answers from the newest loaded version, and that answer changes when the publisher releases again. Put versions/<date>/ before rows or aggregate for an answer that never changes. /api/v1/datasets/<slug>/versions lists the loaded versions. The 1 newest version is loaded; versions lists them.
The API allows 60 requests in 10 seconds from one address. Above that it answers 429 for 10 seconds with a Retry-After header, a RateLimit-Policy header and a JSON body that gives the limit. Every API answer carries the same RateLimit-Policy. A client should wait the Retry-After seconds, or read the files, which have no limit. openapi.json describes this dataset's query paths for client generators and agents.
https://publicdata.au/mcp is a remote MCP server over Streamable HTTP with the same tools, defined in the same place, so a tool added to the pages is added here too. It needs no key and no account. The row tools are held to the query API's limit of 60 queries in 10 seconds from one address, and each call is two queries because it also counts the matching rows. Add it to Claude Code with claude mcp add --transport http publicdata https://publicdata.au/mcp, add the URL in Claude as a custom connector, or give it to any client that connects to remote MCP servers. Each queryable dataset is also a resource at https://publicdata.au/d/<slug>/fields.json, which lists its fields with their types, the publisher's descriptions, their ranges and the values they hold, so an agent can read a dataset's shape before it writes a query.
What changed
One version for every release the publisher has made since this site started following the dataset. The date is the day the file changed on the portal.
- 2025-09-19 43,522 rows40 fieldszipb78b3d9e8fb1
versions.json · changes.json · history.tar.zst (1.4 MB, every version's Parquet and manifest)
Questions
How do I download Road crash locations as a CSV file?
Open https://publicdata.au/d/sa-road-crash-locations/latest/data.csv. It redirects to the newest dated version, which is https://publicdata.au/d/sa-road-crash-locations/v/2025-09-19/data.csv today. The same path serves Excel, JSON, GeoJSON, Parquet, SQLite, DuckDB, GeoPackage, GeoParquet, NDJSON, Arrow. A dated URL never changes, so use it when the file must stay the same.
Can I open Road crash locations in Excel?
Yes. https://publicdata.au/d/sa-road-crash-locations/v/2025-09-19/data.xlsx is a workbook with the 43,522 rows on a records sheet, the field list on a second sheet and the provenance on a third. The CSV also opens in Excel. https://publicdata.au/d/sa-road-crash-locations/v/2025-09-19/data.csv.gz is the CSV at about a tenth of the size.
What years does Road crash locations cover?
The current version covers the years since 2020. Each release from Infrastructure and Transport becomes a new dated version here, and earlier versions stay online.
How often is Road crash locations updated?
Infrastructure and Transport releases it yearly. This site checks the portal every week and adds a dated version when the file changes.
Can I use Road crash locations commercially?
Yes. CC BY 4.0 allows commercial use, redistribution and derived works as long as the attribution is kept. The attribution string is in this page's side column and inside every file.
Is this the official source for Road crash locations?
No. The publisher is Department for Infrastructure and Transport, and its page is https://data.sa.gov.au/data/dataset/road-crashes-in-sa. This site republishes the publisher's file without changing its content. The original sits beside every version as source.zip with its SHA-256, so the two can be compared.
What coordinate system does Road crash locations use?
Coordinates are longitude and latitude in GDA2020 (EPSG:7844), from the publisher's GDA2020 file. The GeoJSON file uses the same coordinates, which is what GeoJSON expects.
Which SA2, council area, suburb, postcode, state electorate and federal electorate is each row of Road crash locations in?
Each row with coordinates carries the SA2 (2021), Council area (LGA 2025), Suburb or locality (2021), Postcode (postal area 2021), State electorate (2025) and Federal electorate (2025) its point falls in, with the code of each. This site joins them by location against the ABS boundaries, https://publicdata.au/d/abs-sa2-2021/, https://publicdata.au/d/abs-lga-2025/, https://publicdata.au/d/abs-suburbs-localities-2021/, https://publicdata.au/d/abs-postal-areas-2021/, https://publicdata.au/d/abs-state-electoral-divisions-2025/, https://publicdata.au/d/abs-federal-electoral-divisions-2025/, and Infrastructure and Transport did not publish them. The schema marks each one as joined and names the boundary version. A row without coordinates, or a point outside every area, has them blank. Place columns from Australian Statistical Geography Standard (ASGS) Edition 3 boundaries, Australian Bureau of Statistics, licensed under CC BY 4.0.
What this site did to the data. Cells were typed, headers were renamed and the encoding was made UTF-8. Rows were left alone. The publisher's file sits beside every version as source.zip so the change can be checked.