Land Surface Temperature Assessment Using TIRS Data: A Case Study of Gorakhpur District, India

Abstract

Aim: The present study aims to retrieve land surface temperature (LST) using Landsat 8 Thermal Infrared Sensor (TIRS) data and to examine its relationship with selected land surface indices in order to assess spatial thermal variability, urban heat island characteristics, and environmental conditions in Gorakhpur District, India. Study Design: A geospatial analytical research design was employed, integrating satellite remote sensing techniques with spatial and statistical analysis to investigate interactions between surface temperature and land surface characteristics. Place and Duration of the Study: The study was conducted in Gorakhpur District, Uttar Pradesh, India, using cloud-free Landsat 8 imagery acquired during representative periods of the study years to capture prevailing urban thermal conditions. Methodology: LST was retrieved from Landsat 8 TIRS data through a systematic multi-step process involving radiometric calibration, atmospheric correction, and land surface emissivity estimation. Land surface emissivity was derived using vegetation-based approaches. Multispectral bands were used to compute land surface indices, including the Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), Built-Up Index (BUI), and Heat Load Index (HLI). Spatial mapping and correlation analyses were performed to examine relationships between LST and the derived indices and to evaluate the influence of land use/land cover patterns on surface thermal behavior. Results: The analysis revealed considerable spatial variation in LST across Gorakhpur District. Higher surface temperatures were predominantly associated with densely built-up and impervious surfaces, while areas with greater vegetation cover exhibited relatively lower temperatures. Vegetation indices showed strong negative correlations with LST, whereas built-up indicators displayed positive associations, reflecting the presence of urban heat island effects. Conclusion: The study confirms the reliability of Landsat 8 TIRS data for LST retrieval and urban thermal assessment. The observed relationships between LST and land surface indices highlight the significant role of vegetation and land use patterns in regulating urban surface temperatures. These findings provide valuable inputs for sustainable urban planning, environmental management, and climate change mitigation strategies in rapidly urbanizing regions.