Hacktoberfest 2026: le issue che i maintainer hanno segnato per ottobre, aperte e adatte ai principianti. Sfoglia le issue Hacktoberfest

[Data Source Proposal]: Farm dams of Western Australia (DPIRD-083)

Aperta
  • Qualcosa non va?
#581 0 commenti 0 reazioni 0 assegnatari Vedi su GitHub

Nessuno ha ancora preso questa issue.

Valutazione

Difficoltà
5/5
Tempo stimato
Più di una settimana
Idoneità per principianti
35/100
Tipo di issue
Funzionalità
Chiarezza
Abbastanza chiara
Stato di attività
Attiva
Stack tecnologico
python
Ambito
data

Direzione di ricerca

Start with the proposal’s dataset catalogue page and the related issue #580, which contains the imagery review and full list of suspected building footprints. Assess whether the proposed dam polygons can be incorporated into the water theme and the existing building filter, including licensing, data quality, and update considerations. Done means a decision on the proposal and, if accepted, an agreed integration approach.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

data-sources external
Dataset name

Farm dams of Western Australia (DPIRD-083)

Source URL

https://catalogue.data.wa.gov.au/dataset/farm-dams-of-the-south-west-agricultural-region-of-wa

Your relationship to this data

I publish or maintain it

Overture theme

Base, Buildings

Geographic coverage

Western Australia, concentrated in the South West agricultural region (99% of features are south of 29°S)

What the data would add

175,143 farm dam polygons, which would help Overture in two places:

  1. Base / water. Farm dams in WA are almost entirely missing from the water theme. Of 15,282 buildings found sitting on DPIRD dams, only 289 (1.9%) have their centre inside any polygon in base/water (release 2026-09-23.1).
  2. Buildings. As an input to the existing filter that excludes ML buildings crossing water. About 15,000 Microsoft ML footprints in WA are farm dams mistaken for buildings. A 100-hit imagery review found 99 not buildings. Details and the full list: #580

The dams are small: median 0.24 ha, and 97.6% under 1 ha. Most are too small for 30 m products like DEA Waterbodies to capture, which is the gap this fills.

License

CC-BY-4.0

Other license details

Requested attribution: © State of Western Australia, Department of Primary Industries and Regional Development.

Is this data already in OpenStreetMap?

No

Format, updates, and other details

Format: File Geodatabase, GeoPackage, GeoJSON and Shapefile downloads (SLIP account login), plus anonymous ArcGIS REST, WMS and WFS services, all linked from the catalogue page. Polygons with an objectid and no other attributes.
Updated: As required
Collection method: Deep-learning image segmentation of Vivid 2.0 satellite imagery, mostly captured 2018–2019, with each feature filtered by a second deep-learning classifier. Sites were preselected from the earlier South West farm dams dataset, DEA Waterbodies and Landgate's Medium Scale Topo Water polygons.
Known quality issues: within the South West agricultural region, the metadata estimates about 24,000 farm dams are missing and about 1,800 features are not farm dams. A subset was manually reviewed in QGIS. Some dams have been filled in or built over since the 2018–19 imagery.

Before submitting
  • I searched existing proposals and didn't find this dataset.
  • I understand that submitting a proposal doesn't guarantee Overture will add the data.
Lingua principale
Python
Stelle
1.2k
Fork
48
Merge medio
56m
PR unite (30g)
2

Preparare l'ambiente

Come iniziare

  1. Leggi tutta la issue e poi la guida ai contributi del progetto.
  2. Commenta sulla issue per dire che te ne occupi tu — evita che due persone facciano lo stesso lavoro.
  3. Fai un fork del repository e lavora su un branch.
  4. Apri una pull request che faccia riferimento al numero della issue.

Altre issue di OvertureMaps/data

Tutte le issue di OvertureMaps/data

Issue simili

Altre issue su Python

Ricevi le nuove issue nella tua casella

Un breve riepilogo di issue GitHub adatte ai principianti.