“Brightness temperature is an important fundamental observation in passive microwave remote sensing. It is an important input data for inverting key surface parameters such as surface temperature, soil moisture, and snow water equivalent. It has significant scientific value and application potential in the fields of meteorology, climate, and environmental remote sensing. The research progress in microwave remote sensing is introduced, and the research team has established a spatiotemporal spectral random forest reconstruction model to provide a solution to the AMSR2 brightness temperature orbital gap problem.”