Enhancing air pollution mapping with autonomous UAV networks for extended coverage and consistency

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dc.contributor.authorBakirci, Murat
dc.date.accessioned2025-03-17T12:27:26Z
dc.date.available2025-03-17T12:27:26Z
dc.date.issued2024
dc.departmentTarsus Üniversitesi
dc.description.abstractIn the context of today's pressing air pollution challenges, accurate and consistent air pollution mapping plays a pivotal role in understanding pollutant distribution and identifying pollution sources. While current technologies, including sensors and unmanned aerial vehicles (UAVs), have begun to address this issue, the full potential of UAV-based solutions remains largely untapped. This pioneering numerical study demonstrates the effective feasibility of precise and consistent air pollution mapping in local areas that exceed the coverage capacity of a single UAV. The approach involves employing multiple UAVs, which requires rigorous mission planning encompassing various complex stages. These stages include subdividing the mapping area into manageable subareas, evaluating the technical capabilities of each UAV, assigning specific tasks to UAVs, and conducting individual mapping operations. By endowing UAVs with full autonomy, horizontal air pollution maps are generated across different layers within the designated area. This method's distinct advantage is its simultaneous acquisition of vertical profiles at all points within the study region, eliminating the need for additional efforts. Through strategic technical analysis, it was revealed that each UAV's mission coverage area could be expanded by over 30%, leading to more consistent air pollution mapping. Furthermore, this finding suggests a reduction of up to 25% in the total number of UAVs required for studies covering significantly larger areas.
dc.identifier.doi10.1016/j.atmosres.2024.107480
dc.identifier.issn0169-8095
dc.identifier.issn1873-2895
dc.identifier.scopus2-s2.0-85193430098
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.atmosres.2024.107480
dc.identifier.urihttps://hdl.handle.net/20.500.13099/2255
dc.identifier.volume306
dc.identifier.wosWOS:001243239100001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorBakirci, Murat
dc.language.isoen
dc.publisherElsevier Science Inc
dc.relation.ispartofAtmospheric Research
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250316
dc.subjectAir pollution
dc.subjectPollution mapping
dc.subjectUnmanned aerial vehicle
dc.subjectMulti-UAV system
dc.subjectSimulation
dc.titleEnhancing air pollution mapping with autonomous UAV networks for extended coverage and consistency
dc.typeArticle

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