MEASUREMENT OF SPECTRAL REFLECTANCE USING AN INTEGRATING HEMISPHERE
Spectral reflectance by an integrating sphere reflectometer
SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Spectral reflectance by an integrating sphere reflectometer
The spectral reflectance of the Moon is an important property for studies of lunar geology, quantitative physical modeling of the moon, and in-flight calibration of spacecraft sensors. Previous studies have claimed that telescopic absolute reflectance values for the Moon are greater than laboratory reflectance measurements by a factor of two. In order to confirm these results, we performed ground-based observations of the lunar surface using a visible/near-infrared spectroradiometer and compared the measured lunar surface radiance to solar radiance corrected for atmospheric scattering and absorption. These data were compared to previously obtained laboratory reflectance measurements from Apollo soil samples.
Progress is reported in obtaining valuable results needed for the full interpretation of the spectral reflectance curves of solar system objects. The degree to which photometric geometry affects spectral reflectance curves was demonstrated. Various forms of photometric functions were compared and a function adequate for describing the scattering properties of low and moderately reflecting materials was developed and applied in a study of the phase coefficients of various materials, as well as in a study of how the shape of a body affects the spectral reflectance properties. The adequacy of the photometric function for Mars-like analogs was studied. The goniometer system is being converted to a computer driven mode. As soon as computer controls are integrated in the goniometer, the phase dependence 0.95 micron feature in meteorite spectra is scheduled to begin.
A technique is formulated for constructing spectral reflectance curve estimates from multispectral data obtained with the Viking lander camera. The multispectral data are limited to six spectral channels in the wavelength range from 0.4 to 1.1 micrometers and most of these channels exhibit appreciable out-of-band response. The output of each channel is expressed as a linear (integral) function of the (known) solar irradiance, atmospheric transmittance, and camera spectral responsivity and the (unknown) spectral responsivity and the (unknown) spectral reflectance. This produces six equations which are used to determine the coefficients in a representation of the spectral reflectance as a linear combination of known basis functions. Natural cubic spline reflectance estimates are produced for a variety of materials that can be reasonably expected to occur on Mars. In each case the dominant reflectance features are accurately reproduced, but small period features are lost due to the limited number of channels. This technique may be a valuable aid in selecting the number of spectral channels and their responsivity shapes when designing a multispectral imaging system.
A technique is presented for estimating spectral reflectance curves from multispectral image data even if the spectral samples are obtained from channels whose spectral responsivity is not narrowband. It is demonstrated that these reflectance estimates can be written as a linear combination of the spectral samples and that, analogous to Shannon's sampling theorem, if the spectral reflectance is a natural cubic spline, it can be estimated exactly provided the number of spectral channels is sufficiently large. Simulation results suggest that the accuracy of the spectral reflectance estimates is quite good and very insensitive to the spectral responsivity shapes.
The results are presented of spectral reflectance measurements on more than 150 individual meteorite specimens representing essentially all types and subtypes of meteorites. A brief review is provided of the nature of the compositional information contained in a reflection spectrum of a natural material. Attention is given to the spectral reflectance characteristics of mineral assemblages, and to meteorite class spectral characteristics.
The central hypothesis of this study has been that photosynthetic efficiency and capacity can be predicted from 'physiological reflectance indices' derived from spectral reflectance of leaves and canopies. I have approached this topic with a combination of laboratory and field experiments, and have also explored the potential of deriving a meaningful physiological index from imaging spectrometry (e.g. AVIRIS). A few highlights are presented below. The main emphasis has been on the 'Photochemical Reflectance Index' (PRI), derived from reflectance at 531 nm and 570 nm. Unlike most 'conventional' vegetation indices (e.g. NDVI), PRI changes rapidly both with illumination and physiological state, because it detects the interconversion of xanthophyll cycle pigments, which serve as photoregulatory pigments and control energy distribution for the photosynthetic system. This approach has differed dramatically from most remote sensing in that it has emphasized temporal variation in narrow-band spectral signatures, instead of spatial patterns of broadband indices. Our primary conclusion has been that PRI works well as an index of photosynthetic light-use efficiency at the leaf scale, much in the same way as the fluorescence index DeltaF/Fm. However, unlike DeltaF/Fm which must be measured at close scales, PRI can be sampled at a range of spatial scales, presenting the possibility of monitoring photosynthetic fluxes remotely.
Spectral reflectance data were collected from detached snapbean leaves in the laboratory with a multiband radiometer. Four experiments were designed to study the spectral response resulting from changes in leaf cover, relative water content of leaves, and leaf water potential. Spectral regions included in the analysis were red (630-690 nm), NIR (760-900 nm), and mid-IR (2.08-2.35 microns). The red and mid-IR bands showed sensitivity to changes in both leaf cover and relative water content of leaves. The NIR was only highly sensitive to changes in leaf cover. Results provided evidence that mid-IR reflectance was governed primarily by leaf moisture content, although soil reflectance was an important factor when leaf cover was less than 100 percent. High correlations between leaf water potentials and reflectance were attributed to covariances with relative water content of leaves and leaf cover.
Integrating sphere reflectometer for measuring absolute hemispherical spectral reflectance of surfaces
IR spectral reflectance of some common minerals and use in identifying extraterrestrial surfaces
Spectral reflection of metals and alloys at low temperatures graphically represented as function of wavelength
Spectral reflectivity curves for Mars light and dark areas and seasonal changes of dark area simulated in laboratory
Spectral reflectance of carbon dioxide and water frosts at 0.8-3.2 microns, growing frosts in cold vacuum chamber from high purity gases
Galilean satellites spectral reflectivity from photometric observations during Jupiter apparitions
Saturn rings spectral reflectivity measurement and compositional implications concerning water frosts and silicates
The spectral reflectance (0.32-1.06 microns) of Mercury was measured during two elongations, September-October 1974 and March 1975. The spectra are much improved over the previously available measurements. The reflectance increases almost linearly with wavelength, and no electronic transition absorption bands are evident to the precision of the data. The new spectra agree very well with the reflectance of mature lunar mare and upland soils and are not similar to those of any other observed solar system object. This suggests that the surface materials and the weathering processes controlling their optical properties are similar for both the moon and Mercury. Differences between the spectra for the two-observation periods may indicate differences in the average composition for the different regions of Mercury observed.
Earth's reflectivity is among the key parameters of climate research. National Aeronautics and Space Administration (NASA)'s Earth Polychromatic Imaging Camera (EPIC) onboard National Oceanic and Atmospheric Administration (NOAA)'s Deep Space Climate Observatory (DSCOVR) spacecraft provides spectral reflectance of the entire sunlit Earth in the near backscattering direction every 65 to 110 min. Unlike EPIC, sensors onboard the Earth Orbiting Satellites (EOS) sample reflectance over swaths at a specific local solar time (LST) or over a fixed area. Such intrinsic sampling limits result in an apparent Earth's reflectivity. We generated spectral reflectance over sampling areas using EPIC data. The difference between the EPIC and EOS estimates is an uncertainty in Earth's reflectivity. We developed an Earth Reflector Type Index (ERTI) to discriminate between major Earth atmosphere components: clouds, cloud-free ocean, bare and vegetated land. Temporal variations in Earth's reflectivity are mostly determined by clouds. The sampling area of EOS sensors may not be sufficient to represent cloud variability, resulting in biased estimates. Taking EPIC reflectivity as a reference, low-earth-orbiting-measurements at the sensor-specific LST tend to overestimate EPIC values by 0.8% to 8%. Biases in geostationary orbiting approximations due to a limited sampling area are between −0.7% and 12%. Analyses of ERTI-based Earth component reflectivity indicate that the disagreement between EPIC and EOS estimates depends on the sampling area, observation time and vary between −10% and 23%.
A technique for evaluating the construction of spectral reflectance curves from multispectral data obtained with the Viking lander cameras is presented. The multispectral data is limited to 6 channels in the wave-length range 0.4 to 1.1 microns, and several of the channels suffer from appreciable out-of-band response. The technique represents the estimated reflectance curves as a linear combination of known basic functions with coefficients determined to minimize the error in the representation, and it permits all channels, with and without out-of-band response, to contribute equally valid information. The technique is evaluated for known spectral reflectance curves of 8 materials felt likely to be present on the Martian surface. The technique provides an essentially exact fit if the the reflectance curve has no pronounced maxima and minima. Even if the curve has pronounced maxima and minima, the fit is good and reveals the most dominant features. Since only 6 samples are available some short period features are lost. This loss is almost certainly due to undersampling rather than out-of-band channel response.