Pollution from Highways Detection Using Winter UAV Data

This study identified and evaluated the association between metal content and UAV data to monitor pollution from roadways. A total of 18 mixed snow samples were collected at the end of winter, utilizing a 1 m long and 10 cm wide snow collection tube, from either side of the Caspian Highway (Moscow-T...

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Veröffentlicht in:Drones (Basel) 2023-03, Vol.7 (3), p.178
Hauptverfasser: Baah, Gabriel A., Savin, Igor Yu, Vernyuk, Yuri I.
Format: Artikel
Sprache:eng
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Zusammenfassung:This study identified and evaluated the association between metal content and UAV data to monitor pollution from roadways. A total of 18 mixed snow samples were collected at the end of winter, utilizing a 1 m long and 10 cm wide snow collection tube, from either side of the Caspian Highway (Moscow-Tambo-Astrakhan) in Moscow. Inductively coupled plasma optical emission spectrometry (ICP-OES) was used to examine the chemical composition of the samples, yielding 35 chemical elements (metals). UAV data and laboratory findings were calculated and examined. Regression estimates demonstrated the possibility of using remote sensing data to identify Al, Ba, Fe, K, and Na metals in snow cover near roadways due to dust dispersal. This discovery supports the argument that UAV sensing data can be utilized to monitor air pollution from roadways.
ISSN:2504-446X
2504-446X
DOI:10.3390/drones7030178