ArticleiScience2023
Diurnal urban heat risk assessment using extreme air temperatures and real-time population data in Seoul.
Article in iScience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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
7 citing papers in PubMed.
- Spatial assessment of heat risk from deregulation of greenbelt in Seoul, South Korea.Scientific reports · 2026Article
- Global patterns of urban heat shaped by climate and morphology.Nature communications · 2026Article
- GeoAI: Beyond mapping earth and cities through explainability, adaptability, and sustainability.iScience · 2026Article
- Impacts of urban land-use change on land-surface heat exposure risk: spatial evidence from multi-source remote sensing in Zhejiang Province.Frontiers in public health · 2026Article
- Explainable Machine Learning for Heat-Related Illness Prediction: An XGBoost-SHAP Approach Using Korean Meteorological Data.Bioengineering (Basel, Switzerland) · 2025Article
- Evaluating the disaster response capacity of the Korean citizen corps in rural areas: A System Dynamics-GIS approach.iScience · 2025Article
- Shared insights for heat health risk adaptation in metropolitan areas of developing countries.iScience · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Previous heat risk assessments have limitations in obtaining accurate heat hazard sources and capturing population distributions, which change over time. This study proposes a diurnal heat risk assessment framework incorporating spatiotemporal air temperature and real-time population data. Daytime and nighttime heat risk maps were generated using hazard, exposure, and vulnerability components in Seoul during the summer of 2018. The hazard was derived from the daily extreme air temperatures obtained using the stacking machine learning model. Exposure was calculated using
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Registered trials
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.