Applying Deep Learning and Machine Learning Algorithms to Estimate PM Concentration Using Satellite Data and Meteorological Data

Air pollution, particularly fine particulate matter (PM<inline-formula><tex-math notation="LaTeX">_{2.5}</tex-math></inline-formula>), poses significant health risks and environmental challenges worldwide. Therefore, it is essential to monitor air pollution to effec...

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Veröffentlicht in:	IEEE journal of selected topics in applied earth observations and remote sensing S. 1 - 18
Hauptverfasser:	Thapa, Ishwor, Devkota, Bidur, Lamichhane, Badri Raj, Devkota, Bhawana Poudel, Dhakal, Raju, Horanont, Teerayut
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 11.10.2025
Schlagworte:	Accuracy Air pollution Atmospheric modeling Deep Learning Google Earth Engine Machine Learning MODIS Monitoring PM<inline-formula xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"> <tex-math notation="LaTeX"> _{2.5}</tex-math> </inline-formula> Predictive models Public healthcare Remote sensing Satellites Sentinel-5P Support vector machines
ISSN:	1939-1404, 2151-1535
Online-Zugang:	Volltext
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