Thermal infrared imaging for mapping lava flows
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The physical properties of the grains, as evidenced by their infrared emission, correlated with the morphology.
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Existing and planned space missions to a variety of planetary and satellite surfaces produce an ever increasing volume of spectral data. Understanding the scientific informational content in this large data volume is a daunting task. Fortunately various statistical approaches are available to assess such data sets. Here we discuss an automated classification scheme based on Kohonen Self-organizing maps (SOM) we have developed. The SUM process produces an output layer were spectra having similar properties lie in close proximity to each other. One major effort is partitioning this output layer into appropriate regions. This is prefonned by defining dosed regions based upon the strength of the boundaries between adjacent cells in the SOM output layer. We use the Davies-Bouldin index as a measure of the inter-class similarities and intra-class dissimilarities that determines the optimum partition of the output layer, and hence number of SOM clusters. This allows us to identify the natural number of clusters formed from the spectral data. Mineral spectral libraries prepared at Arizona State University (ASU) and John Hopkins University (JHU) are used to test and evaluate the classification scheme. We label the library sample spectra in a hierarchical scheme with class, subclass, and mineral group names. We use a portion of the spectra to train the SOM, i.e. produce the output layer, while the remaining spectra are used to test the SOM. The test spectra are presented to the SOM output layer and assigned membership to the appropriate cluster. We then evaluate these assignments to assess the scientific meaning and accuracy of the derived SOM classes as they relate to the labels. We demonstrate that unsupervised classification by SOMs can be a useful component in autonomous systems designed to identify mineral species from reflectance and emissivity spectra in the therrnal IR.
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The preflight calibration testing of TIRS evaluates the performance of the instrument at the component, subsystem and system level, The overall objective is to provide an instrument that is well calibrated and well characterized with specification compliant data that will ensure the data continuity of Landsat from the previous missions to the LDCM, The TIRS flight build unit and the flight instrument were assessed through a series of calibration tests at NASA Goddard Space Flight Center. Instrument-level requirements played a strong role in defining the test equipment and procedures used for the calibration in the thermal/vacuum chamber. The calibration ground support equipment (CGSE), manufactured by MEI and ATK Corporation, was used to measure the optical, radiometric and geometric characteristics of TIRS, The CGSE operates in three test configurations: GeoRad (geometric, radiometric and spatial), flood source and spectral, TIRS was evaluated though the following tests: bright target recovery, radiometry, spectral response, spatial shape, scatter, stray light, focus, and uniformity, Data were obtained for the instrument and various subsystems under conditions simulating those on orbit In the spectral configuration, a monochromator system with a blackbody source is used for in-band and out-of-band relative spectral response characterization, In the flood source configuration the entire focal plane array is illuminated simultaneously to investigate pixel-to-pixel uniformity and dead or inoperable pixels, The remaining tests were executed in the GeoRad configuration and use a NIST calibrated cavity blackbody source, The NIST calibration is transferred to the TIRS sensor and to the blackbody source on-board TIRS, The onboard calibrator will be the primary calibration source for the TIRS sensor on orbit.
Since Cassini's arrival at Titan, ppm levels of benzene (C6H6) as well as large positive ions, which may be polycyclic aromatic hydrocarbons (PAHs). have been detected in the atmosphere. Aromatic molecules. photolytically active in the ultraviolet, may be important in the formation of the organic aerosol comprising the Titan haze layer even when present at low mixing ratios. Yet there have not been laboratory simulations exploring the impact of these molecules as precursors to Titan's organic aerosol. Observations of Titan by the Cassini Composite Infrared Spectrometer (CIRS) in the far-infrared (far-IR) between 560 and 20/cm (approx. 18 to 500 microns) and in the mid-infrared (mid-IR) between 1500 and 600/cm (approx. 7 to 17 microns) have been used to infer the vertical variations of Titan's aerosol from the surface to an altitude of 300 km in the far-IR and between 150 and 350 km in the mid-IR. Titan's aerosol has several observed emission features which cannot be reproduced using currently available optical constants from laboratory-generated Titan aerosol analogs, including a broad far-IR feature centered approximately at 140/cm (71 microns).
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NASA or NOAA Earth-observing satellites are not the only space-based TIR platforms. The European Space Agency (ESA), the Chinese, and other countries have in orbit or plan to launch TIR remote sensing systems. Satellite remote sensing provides an excellent opportunity to study land-atmosphere energy exchanges at the regional scale. A predominant application of TIR data has been in inferring evaporation, evapotranspiration (ET), and soil moisture. In addition to using TIR data for ET and soil moisture analysis over vegetated surfaces, there is also a need for using these data for assessment of drought conditions. The concept of ecological thermodynamics provides a quantification of surface energy fluxes for landscape characterization in relation to the overall amount of energy input and output from specific land cover types.
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