Zhou et al. (2026) Comprehensive UAV and ground data for typical semiarid sites in the midstream of the Heihe River Basin

Identification

• Journal: Scientific Data
• Year: 2026
• Date: 2026-04-01
• Authors: Ji Zhou, Zheng Wang, Shaomin Liu, Mingsong Li, Jin Ma, Lingxuan Meng, Nanjie Feng
• DOI: 10.1038/s41597-026-07151-0

Research Groups

• School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, China
• State Key Laboratory of Earth Surface Processes and Hazards Risk Governance (ESPHR), Faculty of Geographical Science, Beijing Normal University, Beijing, China

Short Summary

This data descriptor presents a comprehensive multi-scale dataset from the MUlti-Scale Observation Experiment on land Surface temperature using UAV remote sensing (MUSOES-UAV). It comprises high-resolution UAV thermal infrared and multispectral imagery, complemented by ground-based observations, collected from June to October 2020 in the Heihe River Basin to advance understanding of semiarid land surface processes and validate remote sensing algorithms.

Objective

• To provide a comprehensive, multi-scale dataset of UAV thermal infrared and multispectral imagery, along with concurrent ground-based observations, for typical semiarid sites in the midstream of the Heihe River Basin to facilitate understanding of land surface processes and validate UAV remote sensing algorithms.

Study Configuration

• Spatial Scale: Typical semiarid sites in the midstream of the Heihe River Basin, China. Data includes high-resolution UAV imagery.
• Temporal Scale: June to October 2020.

Methodology and Data

• Models used: Pix4D Mapper (v4.7) for UAV image stitching and orthomosaic creation; OriginPro (v2024a) for data plotting and visualization; ArcMap (v10.2) for map production. Custom Python (v3.10) scripts were used for temperature drift correction (DRAT method) and relative radiometric normalization of multispectral images.
• Data sources:
  • UAV-borne: High-resolution thermal infrared (TIR) images, multispectral images.
  • Ground-based: TIR radiometer observations, automatic weather station observations.
  • Derived products: TIR brightness temperature mosaics, multispectral mosaics, Normalized Difference Vegetation Index (NDVI) maps.

Main Results

• A comprehensive multi-scale dataset was generated, including high-resolution UAV thermal infrared (TIR) brightness temperature mosaics, multispectral mosaics, and Normalized Difference Vegetation Index (NDVI) maps.
• The dataset also includes concurrent ground-based observations from TIR radiometers and automatic weather stations.
• UAV TIR data were corrected for temperature drift, and multispectral images underwent radiometric relative normalization to ensure data consistency and quality.

Contributions

• Provides a unique, comprehensive multi-scale dataset combining high-resolution UAV remote sensing data with ground-based observations for semiarid environments.
• Offers a foundational resource for monitoring environmental changes, and for developing and validating algorithms for UAV remote sensing applications, particularly concerning land surface temperature and vegetation dynamics.
• Enhances data reliability and utility through rigorous correction and normalization procedures for both thermal infrared and multispectral imagery.

Funding

• National Key Research and Development Program of China (Grant 2023YFF1303502).

Citation

@article{Zhou2026Comprehensive,
  author = {Zhou, Ji and Wang, Zheng and Liu, Shaomin and Li, Mingsong and Ma, Jin and Meng, Lingxuan and Feng, Nanjie},
  title = {Comprehensive UAV and ground data for typical semiarid sites in the midstream of the Heihe River Basin},
  journal = {Scientific Data},
  year = {2026},
  doi = {10.1038/s41597-026-07151-0},
  url = {https://doi.org/10.1038/s41597-026-07151-0}
}