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At least 19 records

Global four-band spectral classification of Jupiter's clouds - Color/albedo units and trends

Voyager 2 digital images of Jupiter have been used to construct a global data base of cloud reflectance in four spectral bands: three wideband 'colors' with effective wavelengths at 431 nm, 564 nm, and 599 nm, plus the narrowband CH4 filter centered at 621 nm. This data base has been spectrally classified at 0.5 deg resolution to separate the complex scene into cloud color/albedo units on a pixel-by-pixel basis, revealing 20 distinct and five tentative units. These include both large, globally distributed units and very small, localized units. Global color maps and unit membership maps are used to highlight associations and trends.

Thompson, W. Reid↗

Characterization of MODIS VIS/NIR Spectral Band Detector-to-Detector Difference

MODIS has 36 spectral bands with wavelengths in the visible (VIS), near-infrared (NIR), shortwave infrared (SWTR), mid-wave infrared (MWIR), and long-wave infrared (LWIR). It makes observations at three nadir spatial resolutions: 0,25km for bands 1-2 with 40 detectors per band, 0.5km for bands 3-7 with 20 detectors per band, and 1km for bands 8-36 with 10 detectors per band. The VIS, NIR, and S\VIR spectral bands are the reflective solar bands (RSB), which are calibrated on-orbit by a solar diffuser (SD). In addition, MODIS lunar observations are used to track the RSB calibration stability. In this study, we examine detector-to-detector calibration difference for the VIStNIR spectral bands using the SD and lunar observations. The results will be compared with an independent analysis with additional information, such as polarization correction, derived from standard ocean color data products. The current MODIS RSB calibration approach only carries a band-averaged RVS (response versus scan angle) correction. The results from this study suggest that a detector-based RVS correction should be used to improve the L1B data quality, especially for several VIS bands in Terra MODIS due to large changes of the scan mirror's optical properties in recent years.

Xiong, X.↗

Evaluation of Spectral Band Adjustment Factors for Cross-Calibration of Visible Imagers

The NASA CERES EBAF dataset provides TOA SW and LW fluxes for long-term monitoring of the Earth’s energy balance and to validate climate models. The EBAF products, based on the Terra, Aqua, and NOAA20 CERES instrument observed radiances, rely on coincident measurements from the onboard MODIS or VIIRS imagers to determine cloud properties used for angular distribution model scene selection, which is required to convert the CERES observed radiances into flux values. Furthermore, CERES utilizes geostationary imager (GEO) hourly fluxes and clouds to infer the regional averaged daily flux in the SYN1deg product. A seamless transition of fluxes and clouds can only occur if the analogous MODIS, VIIRS, and GEO channels are properly inter-calibrated. The analogous band SRFs differ noticeably and require scene dependent spectral band adjustment factors (SBAF) for proper radiometric scaling between them. Given their disparate but overlapping SRFs, the coincident VIIRS I1 and M5 band TOA reflectance measurements provide the optimal opportunity to validate SBAFs over many surface and cloud conditions. The CERES project maintains SCIAMACHY, GOME-2, and Hyperion scene-stratified hyper-spectral reflectance measurements that can be convolved with sensor pair SRFs to compute the corresponding SBAF. This study highlights the SCIAMACHY, GOME-2, and Hyperion based SBAFs for different MODIS, VIIRS, and GEO inter-calibration targets, including all-sky tropical ocean (ATO), Libya-4, Dome-C, and deep convective clouds. To mitigate the observed sensor radiance fluctuations due to atmospheric absorption and aerosol variations, the Earth target observed radiances are correlated with multiple atmospheric parameters, such as precipitable water and ozone. The remaining M5 and I1 mean spectral band radiance difference should be resolved by the SBAF correction. The formulation of hyper-spectral sensor based SBAFs and validation methods can be verified in future utilizing high-accuracy, SI-traceable hyper-spectral measurements from CLARREO Pathfinder.

David R Doelling↗

Spectral band selection for classification of soil organic matter content

This paper describes the spectral-band-selection (SBS) algorithm of Chen and Landgrebe (1987, 1988, and 1989) and uses the algorithm to classify the organic matter content in the earth's surface soil. The effectiveness of the algorithm was evaluated comparing the results of classification of the soil organic matter using SBS bands with those obtained using Landsat MSS bands and TM bands, showing that the algorithm was successful in finding important spectral bands for classification of organic matter content. Using the calculated bands, the probabilities of correct classification for climate-stratified data were found to range from 0.910 to 0.980.

Henderson, Tracey L.↗

Degree of interdependence among atmospheric optical thicknesses in spectral bands between 0.36-2.4 micron

The degree of dependence among the atmospheric optical thicknesses that are measured in nonselective absorption bands is studied. The observations were made previously in many spectral bands within the range 0.36-2.4 micron from near sea level in two continents where urban and industrial pollutions were weak. The sample covariance matrices and corresponding eigenvalues and eigenvectors are computed. The two highest eigenvalues account for 90% of the total variance in 10 spectral bands within the range 0.4-1.6 micron. The linear regression of the optical thickness on the total precipitable water vapor is computed to determine the attenuation coefficient that is associated with water vapor. This coefficient shows a rapid power-law decrease with wavelength in the visible spectrum and indicates that numerous water particles of radius 0.03-0.06 micron cause the attenuation.

Fraser, R. S.↗

SNPP VIIRS Spectral Bands Co-Registration and Spatial Response Characterization

The Visible Infrared Imager Radiometer Suite (VIIRS) instrument onboard the Suomi National Polar‐orbiting Partnership (SNPP) satellite was launched on 28 October 2011. The VIIRS has 5 imagery spectral bands (I-bands), 16 moderate resolution spectral bands (M-bands) and a panchromatic day/night band (DNB). Performance of the VIIRS spatial response and band-to-band co-registration (BBR) was measured through intensive pre-launch tests. These measurements were made in the non-aggregated zones near the start (or end) of scan for the I-bands and M-bands and for a limited number of aggregation modes for the DNB in order to test requirement compliance. This paper presents results based on a recently re-processed pre-launch test data. Sensor (detector) spatial impulse responses in the scan direction are parameterized in terms of ground dynamic field of view (GDFOV), horizontal spatial resolution (HSR), modulation transfer function (MTF), ensquared energy (EE) and integrated out-of-pixel (IOOP) spatial response. Results are presented for the non-aggregation, 2-sample and 3-sample aggregation zones for the I-bands and M-bands, and for a limited number of aggregation modes for the DNB. On-orbit GDFOVs measured for the 5 I-bands in the scan direction using a straight bridge are also presented. Band-to-band co-registration (BBR) is quantified using the prelaunch measured band-to-band offsets. These offsets may be expressed as fractions of horizontal sampling intervals (HSIs), detector spatial response parameters GDFOV or HSR. BBR bases on HSIs in the non-aggregation, 2-sample and 3-sample aggregation zones are presented. BBR matrices based on scan direction GDFOV and HSR are compared to the BBR matrix based on HSI in the non-aggregation zone. We demonstrate that BBR based on GDFOV is a better representation of footprint overlap and so this definition should be used in BBR requirement specifications. We propose that HSR not be used as the primary image quality indicator, since we show that it is neither an adequate representation of the size of sensor spatial response nor an adequate measure of imaging quality.

Suomi NPP VIIRS↗

Optimum spectral bands for rock discrimination

Using stepwise discriminant analysis on spectral reflectance and spectral emissivity data collected by a Multispectral Scanner and Data System, mounted in an NC-130B aircraft and flown at an altitude of approximately 3 km, spectral bands were ranked as to their usefulness in separating specific rock types and rock alteration products in seven geologically diverse Utah sites. The optimum band for rock discrimination included the 1.18 to 1.30 micron interval, and the optimum combination of bands comprised the 1.18 to 1.30, 4.50 to 4.75, 0.46 to 0.50, 1.52 to 1.73, and 2.10 to 2.36 micron intervals. It is concluded that the spectral interval combination was more successful in differentiating geologic materials than either simulated Multispectral Scanner bands or simulated Thematic Mapper bands.

Siegrist, A. W.↗

An examination of spectral band ratioing to reduce the topographic effect on remotely sensed data

Spectral-band ratioing of radiance data is examined as a means of reducing the topographic effect in multispectral data. A ground-based nadir-pointing two-channel radiometer filtered for the red and photographic IR portions of the spectrum was used to measure the topographic effect associated with a uniform surface inclined from horizontal to 60 deg at 16 compass points and for several solar elevations. It is found that ratioing reduced the topographic effect in the field-measured radiance data by an average of 83%, that the remaining topographic effect could be further reduced by subtracting the scattered-light component of the global irradiance before ratioing, and that ratioing was not effective in reducing the topographic effect on shaded surfaces illuminated solely by scattered light. It is concluded that additional variations in ratios can be expected for Landsat data owing to sensor calibration and quantization.

Holben, B.↗

Thermal Infrared Spectral Band Detection Limits for Unidentified Surface Materials

Infrared emission spectra recorded by airborne or satellite spectrometers can be searched for spectral features to determine the composition of rocks on planetary surfaces. Surface materials are identified by detections of characteristic spectral bands. We show how to define whether to accept an observed spectral feature as a detection when the target material is unknown. We also use remotely sensed spectra measured by the Thermal Emission Spectrometer (TES) and the Spatially Enhanced Broadband Array Spectrograph System to illustrate the importance of instrument parameters and surface properties on band detection limits and how the variation in signal-to-noise ratio with wavelength affects the bands that are most detectable for a given instrument. The spectrometer's sampling interval, spectral resolution, signal-to-noise ratio as a function of wavelength, and the sample's surface properties influence whether the instrument can detect a spectral feature exhibited by a material. As an example, in the 6-13 micrometer wavelength region, massive carbonates exhibit two bands: a very strong, broad feature at approximately 6.5 micrometers and a less intense, sharper band at approximately 11.25 micrometers. Although the 6.5-micrometer band is stronger and broader in laboratory-measured spectra, the 11.25-micrometer band will cause a more detectable feature in TES spectra.

Kirkland, Laurel E.↗

Measuring Crosstalk in MODIS Spectral Bands On-orbit Using the SRCA

Near-identical MODIS instruments launched on-board the Terra and Aqua spacecraft in 1999 and 2002, respectively. Each MODIS instrument has36 spectral bands covering 0.41 to 14.2μm mounted among four focal plane assemblies, along with a series of on-board calibrators (OBCs) used to characterize the instrument performance on-orbit. One such OBC is the Spectro-radiometric Calibration Assembly (SRCA), which is a multi-function calibrator, able to provide calibration sources to measure spatial, spectral, or radiometric properties of the MODIS bands depending on its configuration. The MODIS instrument performance, including measurements of the signal cross-contamination (crosstalk) between bands, was measured on-orbit during early-mission characterization for both instruments. This crosstalk test used the SRCA in its spatial mode while utilizing the thin slit, which is normally used for spectral calibrations. A similar crosstalk test was recently performed for Terra MODIS. Since the Terra safe mode event in 2016, the PVLWIR bands specifically (6.7-9.7μm) have shown increased influence from crosstalk. The process involved in preparing and performing this crosstalk test is included in this work, as well as the findings from the recent and previous SRCA-based crosstalk characterizations.

MODIS↗

A comparative study of the thematic mapper and Landsat spectral bands from field measurement data

Principal component and factor analysis techniques were applied to the spectral data collected over 27 field plots of various crops under varying agronomic conditions. The spectral data was integrated over the proposed thematic mapper bands and Landsat MSS spectral bands. The results were examined to compare the discrimination power of the thematic mapper. Previously announced in STAR as N81-33549

Badhwar, G. D.↗

Extreme Case of Spectral Band Difference Correction Between the OSIRIS-REX-NAVCAM2 and DSCOVR-EPIC Imagers

Earth-viewed images acquired during a recent asteroid intercept mission present a unique opportunity for radiometric calibration of visible imagers onboard a space exploration probe. Measurements from the CERES consistent DSCOVR-EPIC imager act as a reference in providing spatially, temporally, and angularly matched radiance values for deriving OSIRIS-REx-NavCam sensor calibration gains. The calibration is accomplished using an optimized all-sky tropical ocean ray-matching technique, which employs complex pixel remapping, navigation correction, and angular geometry consideration. Of critical consideration in this specific inter-calibration event is the extreme difference in spectral response function (SRF) width between the NavCam and EPIC imagers, which could cause a rather large bias. The NASA-LaRC SCIAMACHY based online spectral band adjustment factor (SBAF) calculation tool provides an empirical solution to such potential spectral-difference-induced biases through a high spectral- resolution hyper spectral convolution approach. The adjustments produced from this tool can effectively reduce the calibration gain bias of NavCam2 by nearly 6%, thereby adjusting the NavCam2 sensor to within 3.2% of its prelaunch calibration. These results highlight the capability of the SBAF tool to account for exceptionally disparate SRFs.

Scarino, Benjamin↗

Execution phase (C/D) spectral band characteristics of the EOS moderate resolution imaging spectrometer-Nadir (Modis-N) facility instrument

The Moderate Resolution Imaging Spectrometer (Modis) observing facility on the Earth Observing System (EOS) is composed of two instruments: Modis-Nadir (N) and Modis-Tilt (T). Modis-N has 36 spectral bands between 0.4 and 14.2 microns, with spatial resolution between 250 and 1000 meters. Modis-T has 32 bands with 10-15 nm bandwidths between 0.4 and 0.9 microns. Modis-T scans fore and aft +/- 50 degrees. Both instruments scan cross-track so as to provide daily (Modis-N) or once every two days (Modis-T) coverage at 705-km altitude. Both instruments are entering into the execution phases of their development in 1990. The bands of the Modis-N hve been chosen so as to provide key observations of land, ocean, and atmosphere parameters that will provide key data sets assisting in gaining an improved understanding of global processes.

Salomonson, Vincent V.↗

An Evaluation of Total Solar Reflectance and Spectral Band Ratioing Techniques for Estimating Soil Water Content

For several days in March of 1975, reflected solar radiation measurements were obtained from smooth and rough surfaces of wet, drying, and continually dry Avondale loam at Phoenix, Arizona, with pyranometers located 50 cm above the ground surface and a multispectral scanner flown at a 300-m height. The simple summation of the different band radiances measured by the multispectral scanner proved equally as good as the pyranometer data for estimating surface soil water content if the multispectral scanner data were standardized with respect to the intensity of incoming solar radiation or the reflected radiance from a reference surface, such as the continually dry soil. Without this means of standardization, multispectral scanner data are most useful in a spectral band ratioing context. Our results indicated that, for the bands used, no significant information on soil water content could be obtained by band ratioing. Thus the variability in soil water content should insignificantly affect soil-type discrimination based on identification of type-specific spectral signatures. Therefore remote sensing, conducted in the 0.4- to 1.0-micron wavelength region of the solar spectrum, would seem to be much More suited to identifying crop and soil types than to estimating of soil water content.

Reginato, R. J.↗