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...

詳細記述

書誌詳細

主要な著者:	Bipro Acharjee, Monim Abdullah, Mahmudul Hasan, Hritwik Roy, Toqi Tahmid Fahim, Mohammad Mizanur Rahman
フォーマット:	Online
言語:	英語
出版事項:	Journal of Science 2026
主題:	Air pollution analysis, K-means clustering, Multi-pollutant assessment, District-level air quality mapping, Google Earth Engine (GEE)
オンライン･アクセス:	http://journals.juniv.edu/index.php/jos/article/view/425
タグ:	タグ追加 タグなし, このレコードへの初めてのタグを付けませんか!