ArticleScientific data2022
Fine-scale population spatialization data of China in 2018 based on real location-based big data.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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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Who cites it
4 citing papers in PubMed.
- Article
- Multi-resolution dataset of electricity consumption in Chinese cities.Scientific data · 2025Article
- Inequality in mortality risk of older adults between rural and urban areas exposure to temperature variations in China.BMC public health · 2025Article
- Monthly electricity consumption data at 1 km × 1 km grid for 280 cities in China from 2012 to 2019.Scientific data · 2024Article
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Authors and funding
8 authors.
Funding
Abstract
Accurate location-based big data has a high resolution and a direct interaction with human activities, allowing for fine-scale population spatial data to be realized. We take the average of Tencent user location big data as a measure of ambient population. The county-level statistical population data in 2018 was used as the assigned input data. The log linear spatially weighted regression model was used to establish the relationship between location data and statistical data to allocate the latter to a 0.01° grid, and the ambient population data of mainland China was obtained. Extracting street-level (lower than county-level) statistics for accuracy testing, we found that POP2018 has the best fit with the actual permanent population (R
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