Particulate Matter Concentration Mapping using MODIS Satellite Images and Regression Model

被引：0
作者：
Soolmaz Shamsaei
Mozhgan Ahmadi Nadoushan
Ahmad Jalalian
机构：
[1] Isfahan (Khorasgan) Branch,Department of Environmental Science
[2] Islamic Azad University,Department of Environmental Science, Waste and Wastewater Research Center
[3] Isfahan (Khorasgan) Branch,Department of Soil Science
[4] Islamic Azad University,undefined
[5] Isfahan (Khorasgan) Branch,undefined
[6] Islamic Azad University,undefined
来源：
Journal of the Indian Society of Remote Sensing | 2023年 / 51卷
关键词：
Aerosol optical depth; Air pollution; Isfahan; MODIS; PM 2.5; Regression model;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Particulate matter (PM) pollution is one of the most significant air quality concerns in industrial cities. The present study is an attempt to provide urban air pollution maps based on PM 2.5 parameters in Isfahan city in different seasons between 2018 and 2019 using ground-truth data and MODIS, which is capable of monitoring air quality at different scales (e.g., local, national, and global). Linear regression was established between the data obtained from the earth stations and Aerosol Optical Depth to produce an air pollution map based on PM 2.5 in Isfahan. Also, inverse distance weighting (IDW) was used to explore PM 2.5 concentrations and their spatial mapping by ground-level data. A spatial analysis of Isfahan’s pollution levels revealed that, in most seasons of the year, the southern and central regions have higher levels of PM 2.5 pollution, while the eastern regions have lower levels of PM 2.5 pollution. Results showed that in 2019, summer had the highest and winter had the lowest R2. The results indicated that the MODIS images can be used for air quality monitoring.
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页码：2355 / 2377
页数：22
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