Data · dataset · 2026
Spring migratory bird detection
Listed in GBIF
Muuttolintujen kevät (Spring migratory bird detection) is an application designed for collecting bird observations, supporting both professional researchers and citizen scientists.
Description
The app’s AI algorithm identifies bird species based on their sounds. Observations include for example, the probability of species identification, the timestamp of the audio sample, and the location.
In the published dataset, lat and lon are WGS84 coordinates snapped to the southwest corner of a grid cell. The grid resolution depends on the species sensitivity level. Coordinates are formatted to 3 decimal places.
Read the rest (3 more)
For species with no sensitivity rule (the majority), the 1 km grid is used. For sensitive species, a coarser grid (5-100 km) is used, or coordinates are removed entirely. The data_generalization field indicates the grid resolution (in km) applied to the coordinates for that record.
Possible values coordinates are snapped to: 1: 1 km grid (default for non-sensitive species, or species with no rule in the generalization table) 5: 5 km grid 10: 10 km grid 25: 25 km grid 50: 50 km grid 100: 100 km grid -1: Coordinates completely removed When data_generalization is anything other than 1, the following fields are also set to NA to prevent re-identification through linkage: rec_id, user_anon, time, len, dur, real_obs, rec_type, point_count_loc.
Documentation of fields: species: scientific species name prediction: prediction confidence value after species distribution model correction, 0...1 orig_prediction: prediction confidence value before species distribution model correction, 0...1 song_start: song start position in the recording, seconds rec_id: recording identifier (one recording can contain multiple results) result_id: result identifier feedback: isseen: indication from recorder whether they have seen the bird, boolean isheard: indication from recorder whether they have heard the bird, boolean user_anon: anonyumous user identifier time: observation datetime len: dur: real_obs: indication from recorder whether this is a real observation (as opposed to testing), boolean rec_type: type of recording, enum point_count_loc: name of the point count, string year: year YYYY lat: laltitude wgs84 decimal degrees, see above lon: laltitude wgs84 decimal degrees, see above data_generalization: data generalization code, enum
Links
Where it is published
- GBIF dataset page gbif.org/dataset/9ab7672c-3024-4e4c-a158-d60f3954d96d ↗
landing page · from gbif
- DOI doi.org/10.15468/rma6jt ↗
DOI / persistent id · from gbif
Catalogue records · 1
- GBIF API api.gbif.org/v1/dataset/9ab7672c-3024-4e4c-a158-d60f3954d96d ↗
metadata API · from gbif
Topics
- From keywords
- Life Sciences
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| GBIF | 9ab7672c-3024-4e4c-a158-d60f3954d96d | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · gbif | connector:gbif@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · gbif | connector:gbif@1.0.0 | |
| concepts[modality].local:modality:audio | enrichment · gbif | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:tabular | enrichment · gbif | keyword-concept-rules@1.0.0 | title+description (65%) |
| created_date | source · gbif | connector:gbif@1.0.0 | |
| description | source · gbif | connector:gbif@1.0.0 | /description |
| license | source · gbif | connector:gbif@1.0.0 | |
| publication_date | source · gbif | connector:gbif@1.0.0 | |
| temporal | source · gbif | connector:gbif@1.0.0 | |
| title | source · gbif | connector:gbif@1.0.0 | /title |
| updated_date | source · gbif | connector:gbif@1.0.0 |