ArticleScientific data2026
Daily air temperature estimates at 30-meter resolution in the Chongqing Metropolitan Area, China, 2016-2024.
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- Daily air temperature estimates at 30-meter resolution in the Chongqing Metropolitan Area, China, 2016-2024.Scientific data · 2026Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High-resolution air temperature (Ta) data are essential for environmental monitoring, public health evaluation, and urban climate adaptation, particularly in mountainous megacities with sharp spatial gradients. This study presents a gridded daily Ta dataset at 30 m resolution for the Chongqing Metropolitan Circle, China, spanning 2016 to 2024. This area features a unique topography of alternating ridge-valley corridors, creating strong microclimatic contrasts within densely populated urban areas. The dataset was generated using a Spatially Varying Coefficient Model with Sign Preservation (SVCM-SP) framework that integrates multi-year Landsat-derived land surface temperature, digital elevation, and observations from an average of 215 meteorological stations per year, with an average inter-station distance of 37.7 km. Validation at both daily and monthly scales confirms high spatial and temporal consistency across complex terrain and seasonal conditions. The dataset provides fine-scale daily maximum and minimum temperature estimates and supports diverse applications such as heatwave risk assessment, urban climate research, and adaptation policy design in rapidly urbanizing mountainous regions.
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Registered trials
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