Data · dataset · 2025
AIR-PolSAR-Seg-2.0: Polarimetric SAR Ground Terrain Classification Dataset for Large-scale Complex Scenes
Listed in ScienceDB
The AIR-PolSAR-Seg-2.0 dataset aims to build a polarimetric SAR ground terrain classification dataset for large-scale complex scenes, promoting research and development in polarimetric synthetic aperture radar ground terrain classification within the field of SAR image interpretation.
Description
The dataset is composed of GF-3 L1A complex SAR images from three different regions, with a spatial resolution of 8 m and includes four polarimetric modes (HH, HV, VH, and VV), covering six typical ground terrain categories: water, vegetation, bareland, buildings, roads, and mountains.
The dataset exhibits characteristics of complex scenes, large scale, diverse scattering intensities, irregular boundary distributions, varying category scales, and unbalanced sample distribution. Additionally, the complete SAR images of the three scenes have been cropped into 24,672 slices of 512×512 pixels to facilitate experimental verification within a deep learning framework.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.radars.00041 ↗
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
- Computer Science & AI · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Geophysics 68% · Image 75%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.radars.00041 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:group:3706 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (68%) |
| concepts[field].local:field:computer-science-ai | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| 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 |