AI Summary & Key Takeaways
AI InsightThis study presents a simple methodology using open source satellite data to monitor LST and detect LST abnormalities on landfills.
📌 3 Key Takeaways
Abstract
With the increasing population and urbanization, the amount of municipal solid waste (MSW) is increasing day by day. As a result, problems such as odor, fire, and intense biogas formation originate from landfills. In order to detect and solve these problems, landfills should be monitored regularly. Geographic Information Systems (GIS) and Remote Sensing offer fast and practical solutions for the regular monitoring of landfills compared to field studies. In this study, Kömürcüoda landfill on the Anatolian side of Istanbul is monitored throughout 2022 with open source Landsat8/9 and Sentinel-2 satellite images. In this context, the surface temperature heterogeneity of the landfill was mapped by generating Land Surface Temperature (LST) images for the landfill from the Landsat thermal band. Points with statistically significant high - low LST values were determined with Hot Spot Analysis. The average annual LST for 2022 was calculated as 25.5 °C. It was observed that LST had the highest values during the summer season and the lowest values during the winter season. Additionally, it has been determined that there are persistent hot spots and cold spots in the landfill. This study presents a simple methodology using open source satellite data to monitor LST and detect LST abnormalities on landfills.