One capture zone, with its name, its code and the date the boundary was created, and the zone's shape. The zone code matches the zone code on each capture in the crocodile captures table.

How often does it change?

The boundaries in the October 2026 version were all created on 9 June 2021. This site checks the file weekly and adds a dated version when it changes.

Datasets / Northern Territory / Lands, Planning and Environment / Crocodile capture zones and captures, Northern Territory

Crocodile capture zones, Northern Territory

Name: Crocodile capture zones, Northern Territory
Creator: Department of Lands, Planning and Environment
Published: 2026-10-04
License: https://creativecommons.org/licenses/by/4.0/

live

Publisher Department of Lands, Planning and EnvironmentUpdated when the zones changeLicence CC BY 4.0Latest 2026-10-04Rows 9Fields 3

The nine crocodile capture zones of the Northern Territory, from Upper Harbour, Lower Harbour and Shoal Bay around Darwin to Katherine, Borroloola, Litchfield and Nhulunbuy, with the Management Zone and the area outside it. Each row carries the zone name, its code and the date the boundary was created, with the zone's shape.

Also called: NT Crocodile Capture Zones, Darwin crocodile management zone map, Crocodile removal zones NT.

Part of Crocodile capture zones and captures, Northern Territory, 2 tables the publisher releases together: Crocodile captures, Northern Territory.

Before you use it

What is in each row?: One capture zone, with its name, its code and the date the boundary was created, and the zone's shape. The zone code matches the zone code on each capture in the crocodile captures table.
How often does it change?: The boundaries in the October 2026 version were all created on 9 June 2021. This site checks the file weekly and adds a dated version when it changes.

Made for agents

Connect your AI agent

Any agent that connects to publicdata.au/mcp can find this dataset, read its 3 fields, count and filter across all 9 rows and diff its versions. Every answer names the version and carries Lands, Planning and Environment's attribution. No key.

Then ask it: What does Crocodile capture zones, Northern Territory hold, and what changed in the newest version?

claude mcp add --transport http publicdata https://publicdata.au/mcp

One command. No key, no account, no sign-up.

https://publicdata.au/mcp

Streamable 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.

ExploreChart every row in your browser

A dashboard over every row. Click to filter, add panels, share a link or embed a frame.

Query APIFilter and count from a URL

aggregate?group=zone_name&metric=count

Zones by capture zone: 1 Upper Harbour, 1 Shoal Bay, 1 Outside Management Zone, 1 Nhulunbuy.

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.

Format

Version "Latest" redirects to the newest version and will change when the publisher releases again. A dated version never changes.

https://publicdata.au/d/nt-crocodile-capture-zones/latest/data.xlsx

Download

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/nt-crocodile-capture-zones/latest/ redirects to the newest version.

https://publicdata.au/d/nt-crocodile-capture-zones/latest/data.csv

In 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/nt-crocodile-capture-zones/latest/data.csv

In 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("nt-crocodile-capture-zones")
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("nt-crocodile-capture-zones")
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/nt-crocodile-capture-zones/v/2026-10-04/data.duckdb' AS nt_crocodile_capture_zones (READ_ONLY);
SELECT zone_code, count(*) FROM nt_crocodile_capture_zones.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/nt-crocodile-capture-zones/aggregate?group=zone_name&metric=count");
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 headers were made snake_case. The publisher's header is kept beside every field in schema.json. Rows were left alone.

Field	Type	Publisher's header	Note
zone_name	string	ZONENAME
zone_code	integer	ZONECODE
created	date	CREATED	The date the zone boundary was created.

Download this table as a data dictionary (Excel), or read it as a Frictionless Table Schema at schema.json. The key is zone_code.

A sample of 9 rows

From the latest version, newest first by created, then in the publisher's order, with every field. A blank cell is shown as null.

zone_name	zone_code	created
Borroloola	8	2021-06-09
Katherine Zone	2	2021-06-09
Litchfield	5	2021-06-09
Lower Harbour	3	2021-06-09
Nhulunbuy	9	2021-06-09
Management Zone	1	2021-06-09
Outside Management Zone	7	2021-06-09
Shoal Bay	6	2021-06-09
Upper Harbour	4	2021-06-09

The first row as JSON

As it appears in data.json.

GET https://publicdata.au/d/nt-crocodile-capture-zones/latest/data.json
{
  "zone_name": "Borroloola",
  "zone_code": 8,
  "created": "2021-06-09"
}

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.

Try rows or aggregate for this dataset. The query builder needs JavaScript.

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.

2026-10-04
9 rows3 fieldszip8deebb530f62

versions.json · changes.json · history.tar.zst (1.2 MB, every version's Parquet and manifest)

Questions

How do I download Crocodile capture zones as a CSV file?

Open https://publicdata.au/d/nt-crocodile-capture-zones/latest/data.csv. It redirects to the newest dated version, which is https://publicdata.au/d/nt-crocodile-capture-zones/v/2026-10-04/data.csv today. The same path serves Excel, JSON, GeoJSON, Parquet, SQLite, DuckDB, GeoPackage, PMTiles, NDJSON, Arrow. A dated URL never changes, so use it when the file must stay the same.

Can I open Crocodile capture zones in Excel?

Yes. https://publicdata.au/d/nt-crocodile-capture-zones/v/2026-10-04/data.xlsx is a workbook with the 9 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/nt-crocodile-capture-zones/v/2026-10-04/data.csv.gz is the CSV at about a tenth of the size.

How often is Crocodile capture zones updated?

Lands, Planning and Environment releases it when the zones change. This site checks the portal every week and adds a dated version when the file changes.

Can I use Crocodile capture zones 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 Crocodile capture zones?

No. The publisher is Department of Lands, Planning and Environment, and its page is https://data.nt.gov.au/dataset/nt-crocodile-capture-zones-and-daily-count. 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 Crocodile capture zones use?

The publisher's shapefile is in GDA94 (EPSG:4283), moved to GDA2020 here. The GeoJSON file uses GDA2020 as well, which differs from the WGS84 GeoJSON expects by well under a metre.

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.

The publisher releases Crocodile capture zones and captures, Northern Territory as 2 files at once, so all 2 tables here share a version date.

Attribution and citation

The licence requires the publisher's attribution. We ask that you also name publicdata.au and link to the version you used.

Parks and Wildlife Commission of the Northern Territory, Northern Territory Government, NT Crocodile Capture Zones and Daily Count, https://data.nt.gov.au/dataset/nt-crocodile-capture-zones-and-daily-count, accessed 4 October 2026, licensed under CC BY 4.0. Serialised and versioned by National Digital at publicdata.au, https://publicdata.au/d/nt-crocodile-capture-zones/v/2026-10-04/

The attribution alone is inside every file. Harvard is the author-date form a report or a brief asks for. Paste the HTML on a web page so the links carry.

Licence record

Department of Lands, Planning and Environment states the licence, CC BY 4.0, on its own page, which was read and recorded here on 1 October 2026.

Every fetch reads the licence again and stops when it has changed. The fetch that made version 2026-10-04 read it from data.nt.gov.au on 4 October 2026.

Also published on

Hugging Faceload_dataset("National-Digital/nt-crocodile-capture-zones")
Kagglewith a starter notebook
ZenodoDOI 10.5281/zenodo.23140620

Each copy carries the same attribution and links back to this page.

For agents and tools

datapackage.jsonFrictionless data package pointing at the latest version
schema.jsonTable Schema for every field
schema.xlsxthe same field list as an Excel data dictionary
versions.jsonevery version with date, rows, fields and hash
changes.jsondiff for every consecutive pair
manifest.jsonwhere the bytes came from and when
Query APIfiltered rows and counts without a download
openapi.jsonOpenAPI 3.1 for this dataset's query paths
explore/charts and dashboards in the browser, shareable and embeddable
index.mdthis page as Markdown

This page carries a schema.org Dataset record and is listed in /.well-known/ard.json and /catalog.json.

Source

Department of Lands, Planning and Environment publishes this table on ftp-dlrm.nt.gov.au. Questions about the content go to the publisher. Questions about the files here go to corrections.

Fetched 4 October 2026. Source SHA-256 8deebb530f623784…

Improve this dataset

This page is built from register/nt-crocodile-capture-zones.yaml on GitHub. Anyone can propose a fix to it, such as a clearer description or a field the publisher renamed, as a pull request.

Report a file that differs from the publisher's · How to contribute