Data · dataset · 2025
A sample dataset for erosion gullies remote sensing recognition in typical Northeast China’s black soil region
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The agricultural activities are considerably affected by soil erosion, with erosion gullies representing a prominent manifestation of this issue in Northeast China’s black soil region.
Description
Therefore, accurate identification and detection of erosion gullies based on remote sensing are pivotal for safeguarding arable land. Here we provide a sample dataset for erosion gullies remote sensing recognition in typical Northeast China’s black soil region, i.e., Hailun City of Heilongjiang Province.
The very high resolution remote sensing image is derived from Google Earth with a spatial resolution of 0.6 m/pixel. Each sample is 224*224 pixels in size with two categories, i.e., erosion gullies and else. A total of 10,000 samples are provided, with positive and negative samples in a ratio of 1:1.
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Besides, the sample dataset is split into training, validation and testing dataset with a ratio of 6:2:2. The sample dataset is from the paper in National Remote Sensing Bulletin, please refer to this paper for details.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.24849 ↗
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
- Geomatic engineering 71% · Image 75% · Satellite remote sensing 65%
Provenance · 1 source records, 14 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.24849 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:group:4013 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (71%) |
| 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%) |
| concepts[modality].local:modality:remote-sensing | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (65%) |
| 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 |