li (2026) AlphaEearth-for-Groundwater-Depth-Prediction

Identification

• Journal: Mendeley Data
• Year: 2026
• Date: 2026-01-19
• Authors: zhenxiong li
• DOI: 10.17632/ck7kx8dbpw

Research Groups

Not explicitly stated in the provided text. Contributor: zhenxiong li.

Short Summary

This paper presents AlphaEearth, a machine learning approach, for the prediction of groundwater depth.

Objective

• To develop and apply AlphaEearth for predicting groundwater depth.

Study Configuration

• Spatial Scale: Not available in the provided text.
• Temporal Scale: Not available in the provided text.

Methodology and Data

• Models used: AlphaEearth (categorized under Machine Learning).
• Data sources: Groundwater depth data (for prediction). Specific input data sources for the AlphaEearth model are not detailed in the provided text.

Main Results

Not available in the provided text.

Contributions

Not available in the provided text.

Funding

Not available in the provided text.

Citation

@article{li2026AlphaEearthforGroundwaterDepthPrediction,
  author = {li, zhenxiong},
  title = {AlphaEearth-for-Groundwater-Depth-Prediction},
  journal = {Mendeley Data},
  year = {2026},
  doi = {10.17632/ck7kx8dbpw},
  url = {https://doi.org/10.17632/ck7kx8dbpw}
}