Data · dataset · 2026
Multi-modal dataset of frequently occurring birds in power grid
Listed in ScienceDB
To address the shortage of multimodal data for frequently occurring bird species in the precise prevention and control of bird-related faults in power grids, this study constructed and released a multimodal dataset of frequently occurring birds in power grids.
Description
The dataset focuses on 11 species of concern for power grid bird hazards, including Eurasian Goshawk, Black Stork, Common Crane, Common Kestrel, Eurasian Magpie, Black-winged Kite, Oriental Stork, Large-billed Crow, Carrion Crow, Little Egret, and Upland Buzzard.
It integrates three types of data: bird characteristic data, distribution prediction data, and image annotation data. The bird characteristic data were manually extracted from published literature and books and contain 15 fields, including species name, Latin name, activity rhythm, migration type, food preference, nesting location, habitat characteristics, human-induced flushing distance, noise tolerance, natural enemies, power grid hazard level, prevention and control measures, and references.
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The distribution prediction data were derived from GBIF occurrence records. MaxEnt and two-dimensional kernel density estimation were used to generate monthly relative activity intensity grids for the Beijing–Tianjin–Hebei region and national habitat suitability maps. The image data were obtained from GBIF.
After two rounds of manual screening and YOLOv8-assisted verification, 83,782 high-quality images were retained from 115,423 original photographs and annotated in YOLO format, yielding 119,276 bounding boxes, including 117,831 bird boxes and 1,445 nest boxes. The dataset is approximately 2 GB in size and includes jpg, tif, and csv formats. It can provide fundamental data support for mechanism analysis of bird-related power grid faults, intelligent bird recognition, bird hazard risk assessment, and differentiated prevention and control.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.zoology.0000f ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Bioinformatics and computational biology 71% · Image 75%
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.zoology.0000f | 9 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:group:3102 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (71%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[modality].local:modality:image | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |