LAUSR

Abstract Land surface temperature (LST) plays a crucial role in many scientific applications, including climatology, hydrology, ecology, and agriculture. Multiple studies have successfully utilized daytime thermal infrared (TIR) data obtained from satellite platforms to retrieve LST data over agricultural lands for irrigation planning and monitoring plant health status. Yet, to our knowledge, the retrieval of nighttime LST over agricultural lands has not been investigated using high-resolution satellite TIR data. This study aims to examine the spatial variation of LST over a winter wheat crop field by using day and night-acquired satellite TIR data from Landsat-8 and ASTER L1T, respectively. In parallel with the LST data, we calculated spectral indices related to vegetation health and greenness (NDVI) and water-related indices (NDWI) from multi-source satellite platforms (Landsat-8 and Sentinel-2). Also, we calculated canopy biophysical and biochemical properties such as leaf area index (LAI) and canopy water content (CWC) from Sentinel-2 data. We assessed which spectral indices and canopy properties have a strong correlation with LST during the day and night using the Pearson correlation coefficient and ANOVA analysis. Results demonstrated significant differences (p