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

Identification

• Journal: Mendeley Data
• Year: 2026
• Date: 2026-01-19
• Authors: zhenxiong li
• DOI: 10.17632/ck7kx8dbpw.1

Research Groups

• Contributor: zhenxiong li (Affiliation not specified in the provided metadata)

Short Summary

This entry describes a dataset related to "AlphaEearth" for the prediction of groundwater depth, categorized under machine learning applications.

Objective

• To provide or utilize a dataset for predicting groundwater depth using a method referred to as "AlphaEearth."

Study Configuration

• Spatial Scale: Not specified in the provided metadata.
• Temporal Scale: Not specified in the provided metadata.

Methodology and Data

• Models used: AlphaEearth (implied to be a Machine Learning model based on category).
• Data sources: The provided text is a dataset description; specific data sources used for model training/validation for AlphaEearth are not detailed.

Main Results

• Not applicable as the provided text describes a dataset, not research results.

Contributions

• The provision of a dataset or methodology (AlphaEearth) specifically designed or applied for groundwater depth prediction, potentially advancing machine learning applications in hydrogeology.

Funding

• Not specified in the provided metadata.

Citation

@article{li2026AlphaEearthforGroundwaterDepthPrediction,
  author = {li, zhenxiong},
  title = {AlphaEearth-for-Groundwater-Depth-Prediction},
  journal = {Mendeley Data},
  year = {2026},
  doi = {10.17632/ck7kx8dbpw.1},
  url = {https://doi.org/10.17632/ck7kx8dbpw.1}
}