Systematic review of UAV-assisted airborne particulate matter measurement in urban areas
This systematic review aimed to investigate the applications of Unmanned Aerial Vehicle (UAV) for the measurement of airborne Particulate Matter (PM) concentrations in urban environments. To achieve this aim, a systematic literature review based on the Protocol of Preferred Reporting Items for Syste...
Published in: | REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT |
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Main Authors: | , , , , , , , , , , |
Format: | Review |
Language: | English |
Published: |
ELSEVIER
2024
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Online Access: | https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001333536600001 |
author |
Gohari Adel; Ahmad Anuar B.; Mokhtar Kasypi; Manan Teh Sabariah binti Abd; Oluwatosin Oloruntobi O.; Gismalla Mohammed S. M.; Latip Amir Sharifuddin Ab; Rostami Amir; Sholagberu Abdulkadir T.; Nahi Mohammed Hadi |
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spellingShingle |
Gohari Adel; Ahmad Anuar B.; Mokhtar Kasypi; Manan Teh Sabariah binti Abd; Oluwatosin Oloruntobi O.; Gismalla Mohammed S. M.; Latip Amir Sharifuddin Ab; Rostami Amir; Sholagberu Abdulkadir T.; Nahi Mohammed Hadi Systematic review of UAV-assisted airborne particulate matter measurement in urban areas Environmental Sciences & Ecology; Remote Sensing |
author_facet |
Gohari Adel; Ahmad Anuar B.; Mokhtar Kasypi; Manan Teh Sabariah binti Abd; Oluwatosin Oloruntobi O.; Gismalla Mohammed S. M.; Latip Amir Sharifuddin Ab; Rostami Amir; Sholagberu Abdulkadir T.; Nahi Mohammed Hadi |
author_sort |
Gohari |
spelling |
Gohari, Adel; Ahmad, Anuar B.; Mokhtar, Kasypi; Manan, Teh Sabariah binti Abd; Oluwatosin, Oloruntobi O.; Gismalla, Mohammed S. M.; Latip, Amir Sharifuddin Ab; Rostami, Amir; Sholagberu, Abdulkadir T.; Nahi, Mohammed Hadi Systematic review of UAV-assisted airborne particulate matter measurement in urban areas REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT English Review This systematic review aimed to investigate the applications of Unmanned Aerial Vehicle (UAV) for the measurement of airborne Particulate Matter (PM) concentrations in urban environments. To achieve this aim, a systematic literature review based on the Protocol of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) is performed to analyze the academic literature related to UAV-assisted PM estimation and monitoring in cities. Using a search string, we searched the two core academic databases, including Web of Science and Scopus, for documents published before August 13, 2023. Of the 115 records identified, 22 met the inclusion criteria. The results have shown that UAVs are being implemented for two urban PM measurement categories, including traffic-related PM and atmospheric PM. Successful conduction of relevant experiments confirms the contribution of UAVs in the measurement of vertical PM distributions in cities, which enable us to represent the results in three-dimensional, high-resolution, and realtime. UAVs are used as stand-alone technology for traffic-related PM distribution monitoring. In atmospheric PM studies, UAVs were integrated with other measurement technologies (e.g., lidar) or incorporated into models (e.g., land use regression) to provide high-resolution representations of PM distribution in three dimensions. Vertical observations showed higher PM concentrations at lower altitudes than at higher altitudes in the majority of case studies in both measurement categories. Factors associated with PM concentrations were also identified. ELSEVIER 2352-9385 2024 36 10.1016/j.rsase.2024.101368 Environmental Sciences & Ecology; Remote Sensing WOS:001333536600001 https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001333536600001 |
title |
Systematic review of UAV-assisted airborne particulate matter measurement in urban areas |
title_short |
Systematic review of UAV-assisted airborne particulate matter measurement in urban areas |
title_full |
Systematic review of UAV-assisted airborne particulate matter measurement in urban areas |
title_fullStr |
Systematic review of UAV-assisted airborne particulate matter measurement in urban areas |
title_full_unstemmed |
Systematic review of UAV-assisted airborne particulate matter measurement in urban areas |
title_sort |
Systematic review of UAV-assisted airborne particulate matter measurement in urban areas |
container_title |
REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT |
language |
English |
format |
Review |
description |
This systematic review aimed to investigate the applications of Unmanned Aerial Vehicle (UAV) for the measurement of airborne Particulate Matter (PM) concentrations in urban environments. To achieve this aim, a systematic literature review based on the Protocol of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) is performed to analyze the academic literature related to UAV-assisted PM estimation and monitoring in cities. Using a search string, we searched the two core academic databases, including Web of Science and Scopus, for documents published before August 13, 2023. Of the 115 records identified, 22 met the inclusion criteria. The results have shown that UAVs are being implemented for two urban PM measurement categories, including traffic-related PM and atmospheric PM. Successful conduction of relevant experiments confirms the contribution of UAVs in the measurement of vertical PM distributions in cities, which enable us to represent the results in three-dimensional, high-resolution, and realtime. UAVs are used as stand-alone technology for traffic-related PM distribution monitoring. In atmospheric PM studies, UAVs were integrated with other measurement technologies (e.g., lidar) or incorporated into models (e.g., land use regression) to provide high-resolution representations of PM distribution in three dimensions. Vertical observations showed higher PM concentrations at lower altitudes than at higher altitudes in the majority of case studies in both measurement categories. Factors associated with PM concentrations were also identified. |
publisher |
ELSEVIER |
issn |
2352-9385 |
publishDate |
2024 |
container_volume |
36 |
container_issue |
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doi_str_mv |
10.1016/j.rsase.2024.101368 |
topic |
Environmental Sciences & Ecology; Remote Sensing |
topic_facet |
Environmental Sciences & Ecology; Remote Sensing |
accesstype |
|
id |
WOS:001333536600001 |
url |
https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001333536600001 |
record_format |
wos |
collection |
Web of Science (WoS) |
_version_ |
1814778545317085184 |