The University of Maryland Baltimore County (UMBC) airborne Visible-Near Infrared (VNIR) hyperspectral sensor is a grating spectrometer that collects data in the 380 to 985 nm spectral range with spectral resolution as high as 1.15 nm. This imager is a push-broom type sensor utilizing a two dimensional charge coupled device (CCD, 480×640) camera to collect the spectral information along a single line on the ground perpendicular to the aircraft flight line. The UMBC sensor can provide measurements for a variety of studies, including land development and land use, cultivated and natural vegetation and forestry, and water turbidity and coastal environments. Due to the sensor's wealth of spectral bands, high signal-to-noise, and narrow band widths, a number of atmospheric constituents can be also detected that can be incorporated into atmospheric correction models to benefit the retrievals of surface properties. We present a detailed description of the sensor as well as preliminary results of its calibration in this paper. Related on-going research and some potential applications of this sensor are summarized.
The Measurements of Pollution In The Troposphere (MOPITT) instrument is designed to measure the spatial and temporal variation of the carbon monoxide (CO) profile and total column amount in the troposphere from the space. MOPITT channels are sensitive to both thermal emission from the surface and target gas absorption and emission. Surface temperature and emissivity are retrieved simultaneously with the CO profile. To obtain the desired 10% precision for the retrieved CO from MOPITT measurements, it is important to understand MOPITT CO channel sensitivity to surface temperature and emissivity and the impacts of the effects of any errors in retrieved skin temperature and emissivity on retrieved CO for various underlying surfaces. To demonstrate the impacts of the surface temperature and emissivity on the retrieval of the tropospheric CO profile, simulation studies are performed. The collocated Moderate Resolution Imaging Spectroradiometer (MODIS) surface products are used to assess the accuracy of the retrieved MOPITT surface temperature and emissivity.
The measurements of Pollution in the Troposphere (MOPITT) instrument aboard the Earth Observing System (EOS) Terra spacecraft measures tropospheric CO and CH4 by use of a nadir-viewing geometry. MOPITT cloud algorithm detects and removes measurements contaminated by clouds before retrieving CO profiles and CO and CH4 total columns. The collocation between MOPITT and MODIS is also established and MODIS cloud mask will be used in the MOPITT cloud algorithm. The cloud detection results in the use of MOPITT data alone agree with MODIS cloud mask for more than 80% of the tested cases.
This paper will serve as an overview of the challenges to the recovery of information on atmospheric CO and CH4 from the measurements made by the MOPITT instrument that has been described by Drummond et al. It will also provide a context and introduction to several of the following papers that go into greater detail on particular topics, and outline plans for the data processing. Here we briefly outline the principles of correlation radiometry as used by MOPITT, and introduce the principles behind the retrievals. After noting plans for data processing, we discuss our approach to data validation, and the ability to see global distributions of CO in the MOPITT data.
The Measurements Of Pollution In The Troposphere (MOPITT) experiment will measure the amount of methane and carbon monoxide in the Earth's atmosphere utilizing spectroscopy in the near Infrared (IR) (2.2, 2.3, and 4.7 micrometer). In this wavelength region, clouds confound the retrieval of methane and carbon monoxide by shielding both the surface and atmospheric emission below the clouds from MOPITT. A technique has been developed to detect cloudy pixels, and an algorithm has been developed to estimate clear sky radiance from cloud contaminated pixels. This process is validated using images from the MODIS Airborne Simulator (MAS). MAS images are comprised of 50 m pixels in comparison to the larger 22 km MOPITT pixels. We aggregate the higher resolution MAS data to simulate MOPITT pixels. The aggregation is analyzed for clear and cloudy conditions and a cloud fraction is calculated. The aggregate is then averaged to recreate the scene that MOPITT would have seen. The cloud detection algorithms are applied to the degraded MAS image. The results are compared to validate the techniques imbedded in the standard MOPITT processing stream.
The Measurement Of Pollution In The Troposphere (MOPITT) instrument, which will be launched on the Terra spacecraft, is designed to measure the tropospheric CO and CH4 at a nadir-viewing geometry. The measurements are taken at 4.7 micrometer in the thermal region, and 2.3 and 2.2 micrometer in the solar region for CO mixing ratio retrieval, CO total column amount and CH4 column amount retrieval, respectively. To ensure the required measurement accuracy, it is critical to identify and remove any cloud contamination to the channel signals. In this study, we develop an algorithm to detect the cloudy pixels, to reconstruct clear column radiance for pixels with partial cloud covers, and to estimate equivalent cloud top positions under overcast conditions to enable CO profile retrievals above clouds. The MOPITT channel radiances, as well as the first guess calculations, are simulated using a fast forward model with input atmospheric profiles from ancillary data sets. The precision of the retrieved CO profiles and total column amounts in cloudy atmospheres is within the expected plus or minus 10% range. Validations of the cloud detecting thresholds with MODIS Airborne Simulator (MAS) data and MATR (MOPITT Airborne Test Radiometer) measurements are also carried out and will be presented separately.
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