paper
2021
Extremes & hazards
Application study
Classical ML (trees, GP, linear, kernels)China Meteorological Administration (CMA)Nanjing University of Information Science & Technology (NUIST) Journal
2021-02-10
018
Feb 2021
Yuan Shi, Chao Ren, Ming Luo et al.
Urban Climate
China Meteorological Administration (CMA), Nanjing University of Information Science & Technology (NUIST)
Combines WUDAPT urban morphology data with machine learning to spatially estimate heatwave patterns; the abstract is unavailable, so the details are limited.
Utilizing world urban database and access portal tools (WUDAPT) and machine learning to facilitate spatial estimation of heatwave patterns
In one sentence. Combines WUDAPT urban morphology data with machine learning to spatially estimate heatwave patterns; the abstract is unavailable, so the details are limited.
Labels
- Topic
- Extremes & hazards
- Type
- Application study
- Method
- Classical ML (trees, GP, linear, kernels)
- Domain
- Regional
- Data
- Other
- Status
- Research
- Identifiers
- DOI:10.1016/j.uclim.2021.100797 OpenAlex:W3128817464
- Added
- 2026-10-22
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