Spatio-temporal behavior of brightness temperature in Tel-Aviv and its application to air temperature monitoring.

This study applies remote sensing technology to assess and examine the spatial and temporal Brightness Temperature (BT) profile in the city of Tel-Aviv, Israel over the last 30 years using Landsat imagery. The location of warmest and coldest zones are constant over the studied period. Distinct diurnal and temporal BT behavior divide the city into four different segments. As an example of future application, we applied mixed regression models with daily random slopes to correlate Landsat BT data with monitored air temperature (Tair) measurements using 14 images for 1989-2014. Our preliminary results show a good model performance with R(2) = 0.81. Furthermore, based on the model's results, we analyzed the spatial profile of Tair within the study domain for representative days.