Assessing Carbon Monoxide (CO) Source In Urbanized Area Using Sentinel-5P And Landsat-8

Carbon Monoxide (CO) is one of the air pollutant gases that can be analyzed using geospatial information to prevent its increasing in the atmosphere, particularly in a populated city. This study aimed to assess the CO distribution in the air and its contributor by utilizing Sentinel-5P and Landsat 8 OLI/TIRS satellite imagery. Satellite images were processed using Google Earth Engine. This research was conducted in several cities in East Java, including Surabaya city, Mojokerto city, and Mojokerto regency from 2018 - 2023. These three cities have different characteristics so that the CO concentrations were also different. Pearson correlation was conducted to determine the relationship between the CO detected from Sentinel-5P and Landsat-8 images and social factors in the city, such as population density, urban factors of building patterns and transportation factors. Urban factors were analyzed from Normalized Difference Built-up Index (NDBI) and Normalized Difference Vegetation Index (NDVI). While transportation factors were analyzed from the number of motor vehicles. Results showed the correlation coefficient varied for each city. For social factors, the highest correlation were in Mojokerto regency with 0.7329 in 2023. This indicates that increases population density could affects increase of CO concentration. The urban pattern extracted from building density were detected using Normalized Difference Built-up Index. This showed the NDBI in Surabaya city produced the highest correlation with coefficient of 0.6868 for 2022. This indicates that the denser of the building will affect the increase of CO. While vegetation density from Normalized Difference Vegetation Index showed that the highest correlation were found in Mojokerto city and Mojokerto regency with coeficient of 0.5706 in 2018. This showed the more extensive vegetation could reduce the CO. Transportation factors has produced the highest correlation for Mojokerto city (0.6774). This study indicates that an increase of the number of vehicles could affect in the increase of CO.