Ensemble averaging using remote sensing data to model spatiotemporal PM10 concentrations in sparsely monitored South Africa
- UPSpace Home
- →
- Education Innovation
- →
- Research Articles (Education Innovation)
- →
- View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.
| dc.contributor.author | Arowosegbe, Oluwaseyi Olalekan
|
|
| dc.contributor.author | Roeoesli, Martin
|
|
| dc.contributor.author | Kuenzli, Nino
|
|
| dc.contributor.author | Saucy, Apolline
|
|
| dc.contributor.author | Adebayo-Ojo, Temitope Christina
|
|
| dc.contributor.author | Schwartz, Joel
|
|
| dc.contributor.author | Kebalepile, Moses Mogakolodi
|
|
| dc.contributor.author | Jeebhay, Mohamed Fareed
|
|
| dc.contributor.author | Dalvie, Mohamed Aqiel
|
|
| dc.contributor.author | De Hoogh, Kees
|
|
| dc.date.accessioned | 2023-06-14T09:57:43Z | |
| dc.date.available | 2023-06-14T09:57:43Z | |
| dc.date.issued | 2022-10 | |
| dc.description | DATA AVAILABILITY : Data will be made available on request. | en_US |
| dc.description.abstract | Please read abstract in the article. | en_US |
| dc.description.department | Education Innovation | en_US |
| dc.description.librarian | hj2023 | en_US |
| dc.description.sponsorship | This study is part of the Joint South Africa and Swiss Chair in Global Environmental Health (SARChI), funded by the South African National Research Foundation and the Swiss State Secretariat for Education, Research, and Innovation. O.O.A. is a recipient of a Swiss Government Excellence Scholarship. | en_US |
| dc.description.uri | https://www.elsevier.com/locate/envpol | en_US |
| dc.identifier.citation | Arowosegbe, O.O., Röösli, M., Künzli, N. et al. 2022, Ensemble averaging using remote sensing data to model spatiotemporal PM10 concentrations in sparsely monitored South Africa', Environmental Pollution, vol. 310, art. 119883, pp. 1-10, doi : 10.1016/j.envpol.2022.119883. | en_US |
| dc.identifier.issn | 0269-7491 (print) | |
| dc.identifier.issn | 1873-6424 (online) | |
| dc.identifier.other | 10.1016/j.envpol.2022.119883 | |
| dc.identifier.uri | http://hdl.handle.net/2263/91120 | |
| dc.language.iso | en | en_US |
| dc.publisher | Elsevier | en_US |
| dc.rights | © 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). | en_US |
| dc.subject | Ensemble averaging | en_US |
| dc.subject | Particulate matter (PM2.5) | en_US |
| dc.subject | Satellite observations | en_US |
| dc.subject | Machine learning | en_US |
| dc.subject | SDG-11: Sustainable cities and communities | en_US |
| dc.title | Ensemble averaging using remote sensing data to model spatiotemporal PM10 concentrations in sparsely monitored South Africa | en_US |
| dc.type | Article | en_US |
