Predicting fine particulate matter (PM2.5) in the Greater London area: an ensemble approach using machine learning methods
- Submitting institution
-
Imperial College of Science, Technology and Medicine
- Unit of assessment
- 14 - Geography and Environmental Studies
- Output identifier
- 5114
- Type
- D - Journal article
- DOI
-
10.3390/rs12060914
- Title of journal
- Remote Sensing
- Article number
- ARTN 914
- First page
- 1
- Volume
- 12
- Issue
- 6
- ISSN
- 2072-4292
- Open access status
- Compliant
- Month of publication
- March
- Year of publication
- 2020
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
8
- Research group(s)
-
A - Air Pollution, Environmental Exposures and Public Health
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- -
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
