<![CDATA[Land surface temperature (LST) is crucial for various applications like agriculture, hydrology, urban planning, and climate analysis. Rapid urbanization and climate change have intensified LST variations, particularly in agriculturally dependent regions like Ethiopia, where temperature fluctuations directly impact livelihoods. However, localized LST dynamics in areas such as Injibara town and Banja District remain understudied, despite their sensitivity to climate variability and urban heat effects. This study addresses the gap by estimating LST using Landsat 9 data and analyzing its correlation with Normalized Difference Vegetation Index (NDVI). Landsat 9, launched in 2021, provides enhanced imaging capabilities and advanced sensors compared to its predecessors. Data from the United States Geological Survey (USGS) Earth Explorer website were processed using ArcGIS 10.8. LST was derived using the emissivity equation model incorporating land surface emissivity (LSE) and brightness temperature calculations. NDVI analysis revealed values ranging from -0.03 to 1, with high vegetation (0.35 – 1) concentrated in government and private forests in the northwest, while low vegetation (-0.03–0.15) dominated urban areas, barren lands, and unproductive regions in the south and southeast. The LST results indicated the highest temperatures (38-43°C) were in the northwest and southeast lowland regions, while the lowest temperatures (14-22°C) were in the central highlands. Approximately 40.8% of the area exhibited temperatures between 29-32°C. The study result revealed a negative relationship (R2=0.2506) between LST and NDVI, indicating that higher vegetation cover is associated with lower temperatures. To support regional climate resilience, we recommend integrating green infrastructure in urban planning, prioritizing afforestation in Banja’s lowlands, and expanding research to other Ethiopian agro-ecological zones using high spatial resolution data for comparative analysis.]]>
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