Systems engineering support for next generation land remote sensing systems
Principal Investigator(s)
Matthew Montanaro
Research Team Members
Tania Kleynhans
Project Description
The PI supports the radiometric calibration of the Landsat thermal band instruments for NASA. Specifically, this involves the on-orbit characterization and calibration of the Landsat 8/ Thermal Infrared Sensor (TIRS) instrument and the pre-flight calibration of the new TIRS-2 instrument for the upcoming Landsat 9 mission. The PI serves as the Deputy Calibration Lead for the TIRS-2 project and is a member of the Calibration and Validation team for the Landsat program.
The past year has focused mostly on the pre-flight calibration of the TIRS- 2 instrument. The main instrument-level characterization tests on the sensor has included electromagnetic interference (EMI) testing and thermal vacuum (TVAC) testing. We supported the EMI and TVAC testing at NASA Goddard Space Flight Center by writing test procedures, coordinating calibration activities with other systems leads, executing calibration data collection procedures, processing and analyzing image characterization datasets, writing requirement verification reports, and presenting results to project management. The main calibration categories include the characterization of the instrument’s radiometric, spectral, and spatial response and the delivery of calibration parameters and algorithms to USGS who will operate the Landsat 9 observatory after launch. Another major effort involved the measurement and optical modeling of the instrument’s stray light characteristics. The TIRS-2 optical design was modified over the TIRS-1 design to mitigate the stray light problem that plagued the TIRS-1 instrument. The PI led the stray light measurements and modeling of the TIRS-2 instrument and reported the results to the TIRS-2 and Landsat 9 project managers. Additionally, we supported the current Landsat 8 product development by helping to characterize and validate new land surface temperature products to be distributed to users. We worked with USGS to develop and implement a split window algorithm for land surface temperature and presented our findings at Landsat calibration and science team meetings.