Assessing the Relationship between Land Use/Land Cover Change, NDVI, NDBI, and Land Surface Temperature: A 20-Year Analysis of Rupandehi District, Nepal

This research aims to explore changes in Land Use and Land Cover (LULC) and how LULC have an influence on the Land Surface Temperature (LST) in Rupandehi district.Multiple Landsat imagery across the two decades was utilized, particularly Landsat 7 ETM+ for 2003 and 2013, and Landsat 8 OLI/TIRS for 2023.Both QGIS and ArcGIS Pro were used for spectral indexing.LULC classification was performed in R using Random Forest, where 5 major classes were categorized.A confusion matrix that was also performed in R for all the years yielded above 91% accuracy with not higher than 9% Out-Of-Bag (OOB) error rate.Categorical change detection that was performed in ArcGIS Pro revealed a significant expansion of urban areas, where larger portions were gained from agricultural and forest areas.Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) were calculated to account for vegetation and urban features.The single-channel algorithm and thermal bands (Band 10 for Landsat 8 and Band 6 for Landsat 7) were used to compute LST.Regression analysis across the years for the NDVI and LST shows a negative correlation, while a positive correlation is observed between NDBI and LST.The outcomes of this analysis highlighted that the expansion of urban features has a substantial impact on increasing LST, which can lead to the Urban Heat Island (UHI) effect.In contrast, loss of vegetation also contributes to increasing surface temperatures.These results emphasize the importance of strategic urban planning and sustainable land management policy in the rapidly urbanizing district like Rupandehi.