Zhao (2025) Daily All-Weather 30 m Land Surface Temperature over the Wanglang National Nature Reserve in 2022

Identification

• Journal: Open MIND
• Year: 2025
• Date: 2025-11-21
• Authors: Zhao, Junli
• DOI: 10.5281/zenodo.17668662

Research Groups

• Zhao, Junli

Short Summary

This dataset provides daily, all-weather land surface temperature (LST) at 30 m spatial resolution for the Wanglang National Nature Reserve in 2022, generated through an integrated reconstruction–downscaling framework to mitigate cloud contamination and coarse thermal infrared resolution.

Objective

• To provide a daily, all-weather land surface temperature (LST) dataset at 30 m spatial resolution for the Wanglang National Nature Reserve in Sichuan, China, for the year 2022.

Study Configuration

• Spatial Scale: Wanglang National Nature Reserve, Sichuan, China, at 30 m resolution.
• Temporal Scale: Daily data for the year 2022.

Methodology and Data

• Models used: An integrated reconstruction–downscaling framework.
• Data sources: Implicitly, satellite thermal infrared data, processed to mitigate cloud contamination and coarse resolution.

Main Results

• A comprehensive daily, all-weather land surface temperature (LST) dataset at 30 m spatial resolution for the Wanglang National Nature Reserve for the entire year 2022.

Contributions

• Provides a high-resolution (30 m) daily LST product that overcomes common limitations of cloud cover and coarse thermal infrared resolution, offering a valuable resource for regional ecological and environmental research.

Funding

• Not specified in the provided text.

Citation

@article{Zhao2025Daily,
  author = {Zhao, Junli},
  title = {Daily All-Weather 30 m Land Surface Temperature over the Wanglang National Nature Reserve in 2022},
  journal = {Open MIND},
  year = {2025},
  doi = {10.5281/zenodo.17668662},
  url = {https://doi.org/10.5281/zenodo.17668662}
}