Spatiotemporal Analysis and Machine Learning-Based Profiling of Atmospheric Pollutants Using Sentinel-5P TROPOMI Satellite Data at Tier-Two Administrative Units in Bangladesh.

Air pollution poses a critical environmental and public health threat in Bangladesh, yet a comprehensive, multi pollutant analysis at a high administrative resolution has been lacking. This study bridges this gap by leveraging the high-resolution capabilities of Sentinel-5P TROPOMI satellite data an...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Bipro Acharjee, Monim Abdullah, Mahmudul Hasan, Hritwik Roy, Toqi Tahmid Fahim, Mohammad Mizanur Rahman
Aineistotyyppi:	Online
Kieli:	englanti
Julkaistu:	Journal of Science 2026
Aiheet:	Air pollution analysis, K-means clustering, Multi-pollutant assessment, District-level air quality mapping, Google Earth Engine (GEE)
Linkit:	http://journals.juniv.edu/index.php/jos/article/view/425
Tagit:	Lisää tagi Ei tageja, Lisää ensimmäinen tagi!