{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T13:58:33Z","timestamp":1783605513690,"version":"3.55.0"},"reference-count":51,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2022,5,30]],"date-time":"2022-05-30T00:00:00Z","timestamp":1653868800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"imec Belgium through AAA funding","award":["EI2"],"award-info":[{"award-number":["EI2"]}]},{"name":"Internet of Things (IoT) team of imec-Netherlands","award":["EI2"],"award-info":[{"award-number":["EI2"]}]},{"name":"Flemish Government (AI Research Program)","award":["EI2"],"award-info":[{"award-number":["EI2"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Urban air quality mapping has been widely applied in urban planning, air pollution control and personal air pollution exposure assessment. Urban air quality maps are traditionally derived using measurements from fixed monitoring stations. Due to high cost, these stations are generally sparsely deployed in a few representative locations, leading to a highly generalized air quality map. In addition, urban air quality varies rapidly over short distances (&lt;1 km) and is influenced by meteorological conditions, road network and traffic flow. These variations are not well represented in coarse-grained air quality maps generated by conventional fixed-site monitoring methods but have important implications for characterizing heterogeneous personal air pollution exposures and identifying localized air pollution hotspots. Therefore, fine-grained urban air quality mapping is indispensable. In this context, supplementary low-cost mobile sensors make mobile air quality monitoring a promising alternative. Using sparse air quality measurements collected by mobile sensors and various contextual factors, especially traffic flow, we propose a context-aware locally adapted deep forest (CLADF) model to infer the distribution of NO2 by 100 m and 1 h resolution for fine-grained air quality mapping. The CLADF model exploits deep forest to construct a local model for each cluster consisting of nearest neighbor measurements in contextual feature space, and considers traffic flow as an important contextual feature. Extensive validation experiments were conducted using mobile NO2 measurements collected by 17 postal vans equipped with low-cost sensors operating in Antwerp, Belgium. The experimental results demonstrate that the CLADF model achieves the lowest RMSE as well as advances in accuracy and correlation, compared with various benchmark models, including random forest, deep forest, extreme gradient boosting and support vector regression.<\/jats:p>","DOI":"10.3390\/rs14112613","type":"journal-article","created":{"date-parts":[[2022,5,31]],"date-time":"2022-05-31T02:30:06Z","timestamp":1653964206000},"page":"2613","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Fine-Grained Urban Air Quality Mapping from Sparse Mobile Air Pollution Measurements and Dense Traffic Density"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8643-3816","authenticated-orcid":false,"given":"Xuening","family":"Qin","sequence":"first","affiliation":[{"name":"imec-TELIN-IPI, Department of Telecommunications and Information Processing, Ghent University, Sint-Pietersnieuwstraat 41, 9000 Ghent, Belgium"},{"name":"imec, Kapeldreef 75, 3001 Leuven, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tien Huu","family":"Do","sequence":"additional","affiliation":[{"name":"imec, Kapeldreef 75, 3001 Leuven, Belgium"},{"name":"Department of Electronics and Informatics, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3450-6531","authenticated-orcid":false,"given":"Jelle","family":"Hofman","sequence":"additional","affiliation":[{"name":"imec The Netherlands, High Tech Campus 31, 5656 Eindhoven, The Netherlands"},{"name":"Flemish Institute for Technological Research (VITO), Boeretang 200, 2400 Mol, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Esther Rodrigo","family":"Bonet","sequence":"additional","affiliation":[{"name":"imec, Kapeldreef 75, 3001 Leuven, Belgium"},{"name":"Department of Electronics and Informatics, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Valerio Panzica","family":"La Manna","sequence":"additional","affiliation":[{"name":"imec The Netherlands, High Tech Campus 31, 5656 Eindhoven, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9300-5860","authenticated-orcid":false,"given":"Nikos","family":"Deligiannis","sequence":"additional","affiliation":[{"name":"imec, Kapeldreef 75, 3001 Leuven, Belgium"},{"name":"Department of Electronics and Informatics, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wilfried","family":"Philips","sequence":"additional","affiliation":[{"name":"imec-TELIN-IPI, Department of Telecommunications and Information Processing, Ghent University, Sint-Pietersnieuwstraat 41, 9000 Ghent, Belgium"},{"name":"imec, Kapeldreef 75, 3001 Leuven, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,30]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (2021). 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