Deep learning for spatiotemporal forecasting in Earth system science: a review
Manzhu Yu, Qunying Huang, Zhenlong Li
- ISSN / E-ISSN
- — / —
- DOI
- 10.1080/17538947.2024.2391952 ↗
- Volume · Issue · Pages
- 17 · 1 · —
- Publisher
- Taylor and Francis Ltd.
- Article URL
- https://doi.org/10.1080/17538947.2024.2391952 ↗
- Article details
- Unverified
Publication date (each date has its type and source)
19 Aug 2024
OpenAlex publication date · source: OpenAlex
| Type | Date | Source |
|---|---|---|
| OpenAlex publication date | 19 Aug 2024 | OpenAlex |
Keywords (as given): spatiotemporal prediction; deep learning; Earth system science; climate modeling; weather forecasting; disaster management; air quality modeling; hydrological modeling; renewable energy forecasting; oceanography; environmental monitoring; model interpretability; uncertainty quantification; domain adaptation; transfer learning; missing data handling
HEC Status at Publication Not the journal's current status
HEC Status at PublicationConclusive
HEC status at publication
Recognized
W
Based on the recorded HEC dataset applicable to the article's publication date. Listed as W in the HEC list for 2023–24.
- Journal
- International Journal of Digital Earth
- Publication date used
- 19 Aug 2024 (OpenAlex publication date)
- Applicable HEC period
- 2023–24 (version 1) · 01 Jul 2023 – 30 Sep 2024
- Category
- W
- Recognition status
- Recognized (OK_RECORD_FOUND)
- Source
- HJRS 2023-24 page 962, row 6698
- Verification status
- Verified against source · last verified 23 Sep 2026
This is an automatically generated summary based on the information available on the publication date. Terms & conditions apply.
