P2.59 Atmospheric Processing for MASTER Imagery using Chemical Transport Models and MODTRAN4

Friday, 13 November 2009
Yaítza Luna-Cruz, NCAS, Washington, DC; and D. S. Tkacik and N. Clinton

The signal detected by a remote sensor is the overall result of three main radiative contributions: radiation scattered by the atmosphere to the sensor, radiation reflected by the target and directly transmitted to the sensor, and radiation reflected by the background and then diffusely transmitted to the sensor. The atmospheric contribution on these processes represents a bias on remote sensing measurements especially when the target is the ocean or land. An atmospheric correction must be implemented to reduce its effects and to produce unaltered, more accurate results. Our primary objective was to constrain atmospheric effects over Monterey Bay imagery obtained from the MODIS/ASTER (MASTER) airborne simulator and implement the correction in the retrieval of surface-relevant parameters in order to assess its impact. The point of interest was chosen at Monterey Bay, California, 36°57′34.99″ N, 121°56′2.32″ W. A MODerate spectral resolution atmospheric TRANsmittance algorithm and computer model (MODTRAN4) was used to retrieve the spectral absorption, transmission, emission, and scattering characteristics of a plane-parallel atmosphere. For the production of the model input, an eighteen-layer atmospheric profile of pressure, temperature, dew point temperature, and wind speed were extracted from the Weather Research and Forecasting model (WRF). This profile was used as an input in the STEM-2K3 chemical transport model to retrieve the concentrations at each vertical layer of the following gases: O3, CO, NO, SO2, NO2, NH3, HNO3. Techniques from Verhoef and Bach, (2003) were then implemented for the generation of six atmospheric parameters that describe the alteration of ground-emitted and –reflected radiation by atmospheric effects. Total transmittance, temperature, Normalized Difference Vegetation Index (NDVI) and Fluorescent Line Height (FLH) parameters were analyzed and compared using ENVI for two cases: the default gas setting and the input-gas setting. In all cases, there was a difference when the correction was applied. Atmospheric processing allows for the ability to distinguish between pixels with strong signals, notably in the retrieval of NDVI. MASTER's overestimation of surface temperature can be explained through this process.
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