Data · dataset · 2026
A dataset of monthly temperature vegetation dryness index along the Loess Plateau from 2000 to 2024
Listed in ScienceDB
The ecology of the Loess Plateau is fragile, and drought disasters have constrained the security and social development of the region.
Description
It is urgent to carry out research on drought monitoring. Soil moisture content is an important indicator reflecting drought conditions, and the Temperature Vegetation Dryness Index (TVDI) can invert surface soil moisture to monitor and reflect regional drought conditions.
This dataset is based on the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) products of MODIS satellite data. Through processing such as format conversion, image cropping, and projection conversion, combined with SRTM DEM data, the NDVI-LST feature space characteristics are used to extract the dry and wet edges of the feature space, and obtain the monthly temperature vegetation drought index dataset of the Loess Plateau region from 2000 to 2024.
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The spatial range of this dataset is 33 ° 43 ′ -41 ° 16 ′ N and 100 ° 54 ′ -114 ° 33 ′ E. The data format is GeoTiff and the spatial resolution is 1 km. Through relative verification of actual evapotranspiration data and temperature vegetation drought index, there is a negative correlation between the two, which is good and meets the research needs of evaluating ecological engineering effects and optimizing ecological restoration strategies in the study area.
This dataset can reflect the spatiotemporal changes of surface drought on the Loess Plateau in the past 20 years, providing basic data support for scientific research on drought disaster monitoring and ecosystem response mechanisms on the Loess Plateau.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.j00001.01419 ↗
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 75%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.j00001.01419 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| 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_text | source · scidb cn | connector:scidb_cn@1.0.0 | |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |