Satellite Imagery-Based PM10 Air Parameter Analysis in Makassar City Nurul Masyiah Rani Harusi1,2*, Rizieq Akbar Mubarak 1,2 , Sumarni Hamid Aly1,2, Mitani Yasuhiro3 , Khaerul Amru4,2
1Department of Environmental Engineering, Facutly of Engineering, University of Hasanuddin, St. Poros Malino KM. 6, Bontomarannu, Gowa, South Sulawesi, 92172, Indonesia
2 Transportation and Air Quality Research Group, University of Hasanuddin, St. Perintis Kemerdekaan No. KM. 10, Makassar, South Sulawesi, 90245, Indonesia
3Department of Civil Engineering, Faculty of Engineering, University of Kyushu, Fukuoka, 819-0395, Japan
4Research Center for Environmental and Clean Technology, National Research, and Innovation Agency (BRIN), Geotech Building 820, Puspuptek Sorong, South Tangerang, Indonesia
Abstract
Air pollution caused by particulate matter (PM10) remains a pressing environmental issue in major urban centers, particularly in Makassar City, where rapid population growth and the increasing number of vehicles significantly contribute to deteriorating air quality. Conventional monitoring methods are constrained by the limited coverage of Air Quality Monitoring Stations, which fail to capture the spatial variability of pollutants. This study applies remote sensing techniques using Landsat 8 Operational Land Imager (OLI) data to estimate PM10 concentrations across Makassar. Two established algorithms were implemented: Othman (2010), which utilizes visible bands (Blue, Green, Red), and Mozafari (2019), which employs coastal/aerosol, green, and red bands combined with the Normalized Difference Vegetation Index (NDVI) to account for vegetation effects. Data preprocessing, atmospheric correction, and algorithmic modeling were performed on the Google Earth Engine platform. Spatial analysis revealed elevated concentrations along major road corridors and commercial-industrial areas, particularly on 6/2 divided and 4/2 divided roads, where traffic volumes are highest. In contrast, residential and green spaces exhibited relatively lower values, confirming the influence of land use and road type on particulate distribution. The integration of remote sensing with GIS-based analysis successfully highlights pollution hotspots, demonstrating the potential of satellite-based monitoring as a complementary tool to conventional air quality networks.
Keywords: Air quality, Particulate Matter, Landsat 8, Remote sensing, Makassar Metropolitan City
