@inproceedings{5d7c65cab8b94f4e8baf865e120ed505,
title = "The Association of Satellite Data with PM2.5 Data from Ground Monitoring Stations in Thailand",
abstract = "This study addresses the combination of satellite and ground particulate matter with a diameter less than 2.5 microns (PM2.5) in Thailand. Thailand's Pollution Control Department (PCD) and Bangkok's Air Quality and Noise Management Division gathered PM2.5 data between 2011 and 2020. NASA's Earth Observing System Data and Information System (EOSDIS) retrieves all MODIS satellite data. According to this study, Aerosol Optical Depth (AOD), Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), and Elevation (EV) may be employed as PM2.5 predictors from ground monitoring sites in Thailand. The model showed better performance when including time (Week of year (WOY), Year), indicating seasonal fluctuations in PM2.5. The generated model uses Spearman's correlation and stepwise regression model. This research determined which satellite data is appropriate for estimating PM2.5 in Thailand.",
keywords = "AOD, PM, Satellite data, Thailand, Variable selection",
author = "Suhaimee Buya and Sasiporn Usanavasin and Gokon Hideomi and Jessada Karnjana",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023 ; Conference date: 16-07-2023 Through 21-07-2023",
year = "2023",
doi = "10.1109/IGARSS52108.2023.10282670",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1533--1536",
booktitle = "IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings",
address = "United States",
}