Data · dataset · 2024
A dataset of annual surface water distribution in the Yellow River Basin from 1986 to 2023
Listed in ScienceDB
This study is based on the Google Earth Engine (GEE) cloud computing platform and integrates multi-source land satellite (Landsat 5/7/8/9) remote sensing images to construct a surface water advance algorithm for the Yellow River Basin.
Description
The dataset of surface water distribution in the Yellow River Basin from 1986 to 2023 was produced, including surface water frequency data (WBF) and surface water category data (SWC). By evaluating the accuracy of the water extraction results, the overall accuracy OA reached 97.60%, with a Kappa coefficient of 0.95.
The two sets of data produced in this study are both raster data, using the WGS84 geographic coordinate system with a spatial resolution of 30 meters. The file types are both *. tif files and the file naming format is YYYY. tif (YYYY is the corresponding year). The frequency data of surface water has band values ranging from 0 to 1 (floating-point type), and the band values of surface water category data are 0 (non water body), 1 (seasonal water body), and 2 (permanent water body).
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The production dataset of this study is publicly available, with a spatial resolution of 30 meters. The dataset can be viewed, read, and statistically analyzed in remote sensing software such as ENVI, Arc GIS, and QGIS.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.j00001.00796 ↗
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
- Image 65% · Satellite remote sensing 65% · Surface water hydrology 77%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.j00001.00796 | 10 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:field:370704 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (77%) |
| 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 (65%) |
| 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 |