Data Processing and Analysis Approach to Retrieve Carbon Dioxide Weighted-Column Mixing Ratio and 2-[Formula Omitted]m Reflectance With an Airborne Laser Absorption Spectrometer
We describe the data processing and analysis algorithms used for high-precision retrievals of CO2 weighted-column mixing ratio and 2-[Formula Omitted] surface reflectance from the Carbon Dioxide Laser Absorption Spectrometer (CO2LAS). The CO2LAS at the Jet Propulsion Laboratory, Pasadena, CA, USA, i...
Gespeichert in:
Veröffentlicht in: | IEEE transactions on geoscience and remote sensing 2019-01, Vol.57 (2), p.958 |
---|---|
Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | We describe the data processing and analysis algorithms used for high-precision retrievals of CO2 weighted-column mixing ratio and 2-[Formula Omitted] surface reflectance from the Carbon Dioxide Laser Absorption Spectrometer (CO2LAS). The CO2LAS at the Jet Propulsion Laboratory, Pasadena, CA, USA, is one of the instruments designed to demonstrate capabilities needed for the NASA Active Sensing over Nights, Days, and Seasons mission concept. The integrated path differential absorption technique is used in CO2 retrieval. The along-track spatial resolution for the airborne measurements described here ranges from 10 m to 1 km. Our approach employs heterodyne detection of two laser signals reflected off earth’s surface. Frequency domain processing enables return signal peak detection and high-fidelity power estimation. We compensate for range to ground variations using a digital elevation model and emphasize the importance of reflectance weighting in time averaging of the surface elevation. Quality control filters are applied, as well as a statistical methodology to filter laser speckle fluctuations. Reflectance is also retrieved on the scale of a few meters of ground track. Our data processing workflow and example retrievals are presented. |
---|---|
ISSN: | 0196-2892 1558-0644 |
DOI: | 10.1109/TGRS.2018.2863711 |