ED037-0022
Retrieving Brightness Temperatures Using Satellite Remote Sensing Measurements.

Monday, 14 December 2020
Poster
Mamadou Balde1, Zahra Sharifnezhadazizi2, Hamid Norouzi3, Reginald Blake3 and Reza Khanbilvardi4, (1)CUNY New York City College of Technology, Electrical Engineering Technology, Brooklyn, NY, United States, (2)CUNY City College of New York, Civil Engineering Department, New York, United States, (3)CUNY New York City College of Technology, Civil Engineering Department, Brooklyn, NY, United States, (4)CUNY City College of New York, Civil Engineering Department, New York, NY, United States
Abstract:
Light is electromagnetic radiation that travels with wavelike properties at a speed of 300 000km/s, the fastest travelling object known to mankind. Electromagnetic radiation results from the fluctuations of electric and magnetic fields that allow for the transportation of energy at the speed of light in vacuum. The properties of light enable the theoretical and experimental study of the surfaces and objects it interacts with along its path of travel from a distant observation point, that is remote sensing.

The landscape brightness temperature (Tb) data derived from satellite microwave remote sensing is closely linked to many land and atmospheric parameters such as surface energy budget, hydrological cycle activity, vegetation growing season dynamics, soil moisture, water vapor, land surface emissivity, freeze and thaw state. Various satellites record Tb at different microwave frequencies and spatial resolution; the data is not comprehensive in its singularity, it must be matched and compared with one another to build global diurnal cycle of Tb out the use of the satellite sensors. In this project , we investigated the utility of multi-frequency and dual polarization Tb measurements from the Global Precipitation Measurement (GPM) Microwave Imager (GMI) and the DMSP F16, F17 and F18 Special Sensor Microwave Imager Sounder (SSMIS) to map the global patterns and daily variations of Tb throughout a whole year. In the final step, the patterns were compared to each other to be validated and the optimum values were obtained.

<< Previous Abstract | Next Abstract >>