Comprehensive UAV and ground data for typical semiarid sites in the midstream of the Heihe River Basin.

Ji Zhou, Ziwei Wang, Shaomin Liu, Mingsong Li, Jin Ma, Lingxuan Meng, Nanjie Feng

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In one paragraph

Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Ji ZhouSchool of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, 611731, China. jzhou233@uestc.edu.cn.

Ziwei WangSchool of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, 611731, China.ORCID http://orcid.org/0000-0002-4162-1204

Shaomin LiuState Key Laboratory of Earth Surface Processes and Hazards Risk Governance (ESPHR), Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China.

Mingsong LiSchool of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, 611731, China.

Jin MaSchool of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, 611731, China.

Lingxuan MengSchool of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, 611731, China.

Nanjie FengSchool of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, 611731, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding land surface processes in arid and semiarid environments is crucial for ecosystem dynamics and water management. This data descriptor presents a comprehensive dataset collected during the MUlti-Scale Observation Experiment on land Surface temperature using UAV remote sensing (MUSOES-UAV). Acquired from June to October 2020 at typical semiarid sites in the midstream of the Heihe River Basin, China, the dataset includes high-resolution thermal infrared (TIR) and multispectral images from a UAV. The TIR data were corrected for temperature drift, while the multispectral images underwent radiometric relative normalization to ensure data consistency. Concurrently, ground-based observations were collected from TIR radiometers and automatic weather stations. The final dataset consists of TIR brightness temperature mosaics, multispectral mosaics, and normalized difference vegetation index (NDVI) maps, complemented by the ground-based measurements. This multi-scale dataset is a valuable resource for monitoring environmental changes and provides a foundational basis for developing and validating algorithms for UAV remote sensing applications.

Identifiers

PMID41922366

DOI10.1038/s41597-026-07151-0

PMCPMC13212929

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.