Insights About the Spatial and Temporal Characteristics of the Relationships Between Land Surface Temperature and Vegetation Abundance and Topographic Elements in Arid to Semiarid Environments

This study utilized multiple linear regression (MLR) and geographically weighted regression (GWR) to explore the connections between land surface temperature (LST) and four critical factors (vegetation abundance, elevation, slope, aspect of slope) in Jordan, an arid to semiarid country, during daytime and nighttime across all seasons in one year, yielding important insights. (1) Rates of change in LST in response to variations in vegetation abundance and elevation were consistently negative in both daytime and nighttime throughout all seasons. However, daytime showed a stronger influence of vegetation abundance, while nighttime had a more pronounced effect from elevation. (2) Rates of change in LST in response to changes in slope and aspect of slope were consistently negative during daytime and positive during nighttime across all seasons. (3) The most influential factor on LST varied by season, with vegetation abundance and slope being significant during daytime, while slope and elevation played significant roles during nighttime. (4) LST lapse rates consistently displayed negative values, with nighttime lapse rates being higher across all seasons. Overall, this research highlights GWR’s advantages over MLR in capturing local nuances in LST-influencing factor relationships. However, it also emphasizes the need for additional variables to fully explain year-round variations.