Yuan et al. (2025) An Evaluation of Soil Temperature Predictions Based on the Long Short-Term Memory Model and Remote Sensing Data

Identification

• Journal: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
• Year: 2025
• Date: 2025-12-01
• Authors: Ziqi Yuan, J. Gu, Yaoqi Lu, Yuwei Li
• DOI: 10.1109/jstars.2025.3638765

Research Groups

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Short Summary

This paper evaluates the performance of soil temperature predictions that are based on a Long Short-Term Memory (LSTM) model and utilize remote sensing data.

Objective

• To evaluate the accuracy and effectiveness of the Long Short-Term Memory (LSTM) model in predicting soil temperature, incorporating remote sensing data as input.

Study Configuration

• Spatial Scale: Information not available from the provided text.
• Temporal Scale: Information not available from the provided text.

Methodology and Data

• Models used: Long Short-Term Memory (LSTM) model.
• Data sources: Remote sensing data (specific types and platforms not detailed in the provided text).

Main Results

Information not available from the provided text.

Contributions

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Funding

Information not available from the provided text.

Citation

@article{Yuan2025Evaluation,
  author = {Yuan, Ziqi and Gu, J. and Lu, Yaoqi and Li, Yuwei},
  title = {An Evaluation of Soil Temperature Predictions Based on the Long Short-Term Memory Model and Remote Sensing Data},
  journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  year = {2025},
  doi = {10.1109/jstars.2025.3638765},
  url = {https://doi.org/10.1109/jstars.2025.3638765}
}