Patterns of relationship between PM10 from air monitoring quality station and AOT data from MODIS sensor onboard of Terra satellite

Main Article Content

Winai Suriya
Poramate Chunpang
Teerawong Laosuwan


Keywords : remote sensing, MODIS sensor, PM10, aerosol optical thickness, AOT, air quality index, AQI
Abstract
Thailand, especially in the northern region, often encounters the problem of having PM10 exceeding the normal standard level, which could do harm to people’s health. Mostly, such problem is caused by the burning of forest area and open area; this is clearly seen during January–April of every year. Also, the problem as mentioned is caused by the meteorological conditions and the terrains in the northern region that make it easy for PM10 to be accumulated. The aim of this study was to analyze the patterns of relationship between PM10 measured from the ground monitoring station and AOT data received from MODIS sensor onboard of Terra satellite in Phrae Province located in the northern region of Thailand. The method performed was by analyzing the correlation between PM10 data obtained from the ground monitoring station and the AOT data received from the MODIS sensor onboard of Terra satellite during January–April 2018. It was found from the study that the change of the intensity of PM10 and AOT in the climate was highly related; it appeared that the correlation coefficient (r) in January–April was 0.92, 0.91, 0.91 and 0.92, respectively. This research pointed out that during February– –April, the areas of Phrae Province had the level of PM10 that affected health. Besides, from the method in this research, it revealed AOT data received from MODIS sensor onboard of Terra satellite could be applied in order to follow up, monitor, and notify the spatial changes of PM10 efficiently.

Article Details

How to Cite
Suriya, W., Chunpang, P., & Laosuwan, T. (2021). Patterns of relationship between PM10 from air monitoring quality station and AOT data from MODIS sensor onboard of Terra satellite. Scientific Review Engineering and Environmental Sciences (SREES), 30(2), 236–249. https://doi.org/10.22630/PNIKS.2021.30.2.20
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