Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “remote sensing surface reflectance”

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.

At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Solar surface albedo estimation using remotely sensed spectral data

A solar albedo model based on converting narrow-band satellite-derived reflectance to four major spectral regions (ultraviolet, visible, near-infrared, and shortwave middle-infrared) and weighted by the relative supply of global solar radiation is studied and developed. Narrow-band to broad-band conversions within visible and near-infrared regions are shown to be accurate; however, the transformations are indicated to be surface-feature dependent. Atmospheric aerosol and illumination effects are indicated to be nearly insensitive to spectral region integrations for solar albedo estimation, but are shown to be significant factors affecting the spectral and canopy albedo. The erectophile and spherical canopy albedos were sensitive to atmospheric and illumination condition, whereas the planophile was relatively insensitive. The contribution of a shortwave middle-infrared reflectance to the canopy albedo is shown to be an important component, accounting for albedo changes to 16 percent with increasing vegetation.

Toll, David L.↗
NASA NTRS1983

Passive remote sensing of ocean optical propagation parameters

A method is described for producing a global data of ocean optical properties through the exploitation of optical remote sensing techniques. The diffuse attenuation, K, and the radiance reflectance factor R sub L, of the ocean surface waters can be derived from the radiance data provided by the Coastal Zone Color Scanner and compiled into a computer based atlas of these properties. While these remotely sensed values can only be directly related to the water properties in the first or upper attenuation length, extensive in water measurements have demonstrated that a useful correlation exists between the K that applies to the upper attenuation length, for example, and the mean K over the upper 100 or 200 meters of the ocean. Such an empirical finding greatly enhances the usefulness of this remotely sensed propagation parameter. Examples of the type of information being produced and archived for the atlas are presented.

Austin, R. W.↗
NASA NTRS2000

BOREAS Level-2 MAS Surface Reflectance and Temperature Images in BSQ Format

The BOReal Ecosystem-Atmosphere Study (BOREAS) Staff Science Aircraft Data Acquisition Program focused on providing the research teams with the remotely sensed aircraft data products they needed to compare and spatially extend point results. The MODIS Airborne Simulator (MAS) images, along with other remotely sensed data, were collected to provide spatially extensive information over the primary study areas. This information includes biophysical parameter maps such as surface reflectance and temperature. Collection of the MAS images occurred over the study areas during the 1994 field campaigns. The level-2 MAS data cover the dates of 21-Jul-1994, 24-Jul-1994, 04-Aug-1994, and 08-Aug-1994. The data are not geographically/geometrically corrected; however, files of relative X and Y coordinates for each image pixel were derived by using the C130 navigation data in a MAS scan model. The data are provided in binary image format files.

Hall, Forrest G.↗
NASA NTRS2022

Optimal Estimation Framework for Ocean Color Atmospheric Correction and Pixel-level Uncertainty Quantification

Ocean color remote sensing requires compensation for atmospheric scattering and absorption (aerosol, Rayleigh, and trace gases), referred to as atmospheric correction (AC). AC allows inference of parameters such as spectrally resolved remote sensing reflectance ( R rs )(λ) ; sr 1 ) at the ocean surface from the top-of-atmosphere reflectance. Often, the uncertainty of this process is not fully explored. Bayesian inference techniques provide a simultaneous AC and uncertainty assessment via a full posterior distribution of the relevant variables, given the prior distribution of those variables and the radiative transfer (RT) likelihood function. Given uncertainties in the algorithm inputs, the Bayesian framework enables better constraints on the AC process by using the complete spectral information compared to traditional approaches that use only a subset of bands for AC. This paper investigates a Bayesian inference research method (Optimal Estimation, OE) for ocean color AC by simultaneously retrieving atmospheric and ocean properties using all visible and near-infrared spectral bands. The OE algorithm analytically approximates the posterior distribution of parameters based on normality assumptions and provides a potentially viable operational algorithm with a reduced computational expense. We developed a Neural Network (NN) RT forward model look-up-table-based emulator to increase algorithm efficiency further and thus speed up the likelihood computations. We then applied the OE algorithm to synthetic data and observations from the MODerate resolution Imaging Spectroradiometer (MODIS) on NASA’s Aqua spacecraft. We compared the R rs )(λ) retrieval and its uncertainty estimates from the OE method with in-situ validation data from the SeaWiFS Bio-optical Archive and Storage System (SeaBASS) and Aerosol Robotic Network Ocean Color (AERONET-OC) datasets. The OE algorithm improved R rs )(λ) estimates relative to the NASA standard operational algorithm by improving all statistical metrics at 443, 555, and 667 nm. Unphysical negative R rs )(λ) , which often appear in complex water conditions, was reduced by a factor of 3. The OE-derived pixel-level R rs )(λ) uncertainty estimates were also assessed relative to in-situ data and were shown to have skill.

Atmospheric correction↗
NASA NTRS1989

Infrared spectroscopy (2.3-20 microns) for the geological interpretation of remotely-sensed multispectral thermal infrared data

The spectral radiance and spectral reflectance of natural weathered surfaces of common sedimentary and igneous rocks is determined from in situ and in the laboratory measurements. In situ spectral radiance measurements (5-14 microns) were made with a portable spectral radiometer and were used to derive the spectral emissivity of the rocks. The spectral reflectance measurements (2.3-20 microns) were made in a laboratory with a Fourier transform IR spectrometer with a diffuse reflectance accessory. Good agreement is found between the two techniques. The field portable spectrometer has a larger field of view and the in situ data provide more accurate measurements of the intensity of spectral features related to temperature and atmospheric effects.

Bartholomew, Mary Jane↗
NASA NTRS2024

Global Sensitivity Analysis of Simulated Remote Sensing Polarimetric Observations Over Snow

This study presents a detailed theoretical assessment of the information content of passive polarimetric observations over snow scenes, using a global sensitivity analysis (GSA) method. Conventional sensitivity studies focus on varying a single parameter while keeping all other parameters fixed. In contrast, the GSA correctly addresses the covariance of state parameters across their entire parameter space, hence favoring a more correct interpretation of inversion algorithms and the optimal design of their state vectors. The forward simulations exploit a vector radiative transfer model to obtain the Stokes vector emerging at the top of the atmosphere for different solar zenith angles, when the bottom boundary consists of a vertically resolved snowpack of non-spherical grains. The presence of light-absorbing particulates (LAPs), either embedded in the snow or aloft in the atmosphere above in the form of aerosols, is also considered. The results are presented for a set of wavelengths spanning the visible (VIS), near-infrared (NIR), and shortwave infrared (SWIR) region of the spectrum. The GSA correctly captures the expected, high sensitivity of the reflectance to LAPs in the VIS–NIR and to grain size at different depths in the snowpack in the NIR–SWIR. With adequate viewing geometries, mono-angle measurements of total reflectance in the VIS–SWIR (akin to those of the Moderate Resolution Imaging Spectroradiometer, MODIS) resolve grain size in the top layer of the snowpack sufficiently well. The addition of multi-angle polarimetric observations in the VIS–NIR provides information on grain shape and microscale roughness. The simultaneous sensitivity in the VIS–NIR to both aerosols and snow-embedded impurities can be disentangled by extending the spectral range to the SWIR, which contains information on aerosol optical depth while remaining essentially unaffected when the same particulates are mixed with the snow. Multi-angle polarimetric observations can therefore (i) effectively partition LAPs between the atmosphere and the surface, which represents a notorious challenge for snow remote sensing based on measurements of total reflectance only and (ii) lead to better estimates of grain shape and roughness and, in turn, the asymmetry parameter, which is critical for the determination of albedo. The retrieval uncertainties are minimized when the degree of linear polarization is used in place of the polarized reflectance. The Sobol indices, which are the main metric for the GSA, were used to select the state parameters in retrievals performed on data simulated for multiple instrument configurations. Improvements in retrieval quality with the addition of measurements of polarization, multi-angle views, and different spectral channels reflect the information content, identified by the Sobol indices, relative to each configuration. The results encourage the development of new remote sensing algorithms that fully leverage multi-angle and polarimetric capabilities of modern remote sensors. They can also aid flight planning activities, since the optimal exploitation of the information content of multi-angle measurements depends on the viewing geometry. The better characterization of surface and atmospheric parameters in snow-covered regions advances research opportunities for scientists of the cryosphere and ultimately benefits albedo estimates in climate models.

remote sensing↗
NASA NTRS1974

Seasonal canopy reflectance patterns of wheat, sorghum and soybean

The author has identified the following significant results. Reflectance characteristics of agronomic crops are of major importance in the energy exchanges of a surface. In addition, unique reflectance patterns may be an aid in crop identification by means of remote sensing. This study suggests that the ratio of the reflectances of the 545-nm to to the 655-nm wavebands provides information about the viewed surface, regardless of the crop. The reflectance ratio is less than unity early and late in the growing season. For all crops studied, the ratio closely followed crop growth and development and appeared to be more desirable than the near-infrared reflectance as an index of growth.

Kanemasu, E. T.↗
NASA NTRS1995

Satellite-Sensor Calibration Verification Using the Cloud-Shadow Method

An atmospheric-correction method which uses cloud-shaded pixels together with pixels in a neighboring region of similar optical properties is described. This cloud-shadow method uses the difference between the total radiance values observed at the sensor for these two regions, thus removing the nearly identical atmospheric radiance contributions to the two signals (e.g. path radiance and Fresnel-reflected skylight). What remains is largely due to solar photons backscattered from beneath the sea to dominate the residual signal. Normalization by the direct solar irradiance reaching the sea surface and correction for some second-order effects provides the remote-sensing reflectance of the ocean at the location of the neighbor region, providing a known 'ground target' spectrum for use in testing the calibration of the sensor. A similar approach may be useful for land targets if horizontal homogeneity of scene reflectance exists about the shadow. Monte Carlo calculations have been used to correct for adjacency effects and to estimate the differences in the skylight reaching the shadowed and neighbor pixels.

Reinersman, P.↗
NASA NTRS1983

Frost grain size metamorphism - Implications for remote sensing of planetary surfaces

The effective grain size of a material on a planetary surface affects the strength of absorption features observed in the reflectance of a particulate surface. In the case of a planetary surface containing volatile ices, the absorption characteristics can change in connection with processes leading to a change in the grain size of the material. The present investigation is concerned with an evaluation regarding the occurrence of such processes and the implications for remote sensing applications. It is found that quantitative modeling of the kinetics of grain growth and destruction by thermal and nonthermal processes can provide a means to reconcile apparent optical paths in the volatile portions of planetary surfaces with the physical history of those surfaces. Attention is also given to conditions in the case of the Pluto/Triton system, Uranus and Saturnian satellites, and the Galilean system.

Clark, R. N.↗
NASA NTRS2001

Sensible Success

Commercial remote sensing uses satellite imagery to provide valuable information about the planet's features. By capturing light reflected from the Earth's surface with cameras or sensor systems, usually mounted on an orbiting satellite, data is obtained for business enterprises with an interest in land feature distribution. Remote sensing is practical when applied to large-area coverage, such as agricultural monitoring, regional mapping, environmental assessment, and infrastructure planning. For example, cellular service providers use satellite imagery to select the most ideal location for a communication tower. Crowsey Incorporated has the ability to use remote sensing capabilities to conduct spatial geographic visualizations and other remote-sensing services. Presently, the company has found a demand for these services in the area of litigation support. By using spatial information and analyses, Crowsey helps litigators understand and visualize complex issues and then to communicate a clear argument, with complete indisputable evidence. Crowsey Incorporated is a proud partner in NASA's Mississippi Space Commerce Initiative, with research offices at the John C. Stennis Space Center.

Source record↗
NASA NTRS1989

Thermal infrared (2.5-13.5-micron) spectroscopic remote sensing of igneous rock types on particulate planetary surfaces

The compositional significance of outstanding spectral features in the reflectance spectra of particulate igneous rocks was investigated by analyzing directional reflectance spectra, obtained with an FTIR spectrophotometer at 2.17-13.5 microns, of a suite of well-characterized igneous rocks ground to fine particle size. It was found that, using spectral features associated with the principal Christiansen frequency and with a region of relative transparency between the Si-O stretching and bending bands, it is possible to identify general rock type using the Walter and Salisbury (1989) SCFM chemical index, SCFM, defined as SCFM = SiO2/(SiO2 + CaO + FeO + MgO). It is emphasized, however, that the appearance and the wavelength of these features may be affected by environmental factors.

Salisbury, John W.↗
DOE OSTI2024

Grass Evolutionary Lineages Can Be Identified Using Hyperspectral Leaf Reflectance

Hyperspectral remote sensing has the potential to map numerous attributes of the Earth’s surface, including spatial patterns of biological diversity. Grasslands are one of the largest biomes on Earth. Accurate mapping of grassland biodiversity relies on spectral discrimination of endmembers of species or plant functional types. We focused on spectral separation of grass lineages that dominate global grassy biomes: Andropogoneae (C 4 ), Chloridoideae (C 4 ), and Pooideae (C 3 ). We examined leaf reflectance spectra (350–2,500 nm) from 43 grass species representing these grass lineages from four representative grassland sites in the Great Plains region of North America. Here, we assessed the utility of leaf reflectance data for classification of grass species into three major lineages and by collection site. Classifications had very high accuracy (94%) that were robust to site differences in species and environment. We also show an information loss using multispectral sensors, that is, classification accuracy of grass lineages using spectral bands provided by current multispectral satellites is much lower (accuracy of 85.2% and 61.3% using Sentinel 2 and Landsat 8 bands, respectively). Our results suggest that hyperspectral data have an exciting potential for mapping grass functional types as informed by phylogeny. Leaf-level hyperspectral separability of grass lineages is consistent with the potential increase in biodiversity and functional information content from the next generation of satellite-based spectrometers.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1994

Direct and indirect methods for correcting the aerosol effect on remote sensing

Aspects of aerosol studies and remote sensing are reviewed. Aerosol scatters solar radiation before it reaches the surface and scatters and absorbs it again after it is reflected from the surface and before it reaches the satellite sensor. The effect is spectrally and spatially dependent. Therefore atmospheric aerosol (dust, smoke and air pollution particles) has a significant effect on remote sensing. Correction for the aerosol effect was never achieved on an operational basis though several case studies were demonstrated. Correction can be done in a direct way by deriving the aerosol loading from the image itself and correcting for it using the appropriate radiative transfer model or by an indirect way, by defining remote sensing functions that are less dependent on the aerosol loading. To some degree this was already achieved in global remote sensing of vegetation where a composite of several days of NDVI (Normalized Difference Vegetation Index) measurements, choosing the maximal value, was used instead of a single cloud screened value. The Atmospheric Resistant Vegetation Index (ARVI) introduced recently for the NASA Earth Observing System EOS-MODIS is the most appropriate example of indirect correction, where the index is defined in such a way that the atmospheric effect in the blue spectral channel cancels to a large degree the atmospheric in the red channel in computations of a vegetation index. Atmospheric corrections can also use aerosol climatology and ground based instrumentation.

Kaufman, Yoram J.↗
NASA NTRS1982

Atmospheric radiation model for water surfaces

An atmospheric correction model was extended to account for various atmospheric radiation components in remotely sensed data. Components such as the atmospheric path radiance which results from singly scattered sky radiation specularly reflected by the water surface are considered. A component which is referred to as the virtual Sun path radiance, i.e. the singly scattered path radiance which results from the solar radiation which is specularly reflected by the water surface is also considered. These atmospheric radiation components are coded into a computer program for the analysis of multispectral remote sensor data over the Great Lakes of the United States. The user must know certain parameters, such as the visibility or spectral optical thickness of the atmosphere and the geometry of the sensor with respect to the Sun and the target elements under investigation.

Turner, R. E.↗
NASA NTRS1975

Electromagnetic reflection from multi-layered snow models

The remote sensing of snow-pack characteristics with surface installations or an airborne system could have important applications in water-resource management and flood prediction. To derive some insight into such applications, the electromagnetic response of multilayered snow models is analyzed in this paper. Normally incident plane waves at frequencies ranging from 1 MHz to 10 GHz are assumed, and amplitude reflection coefficients are calculated for models having various snow-layer combinations, including ice layers. Layers are defined by thickness, permittivity, and conductivity; the electrical parameters are constant or prescribed functions of frequency. To illustrate the effect of various layering combinations, results are given in the form of curves of amplitude reflection coefficients versus frequency for a variety of models. Under simplifying assumptions, the snow thickness and effective dielectric constant can be estimated from the variations of reflection coefficient as a function of frequency.

Linlor, W. I.↗
NASA NTRS1981

Remote sensing of sea surface temperature in the 3.7 micron CO2 band

The main sources of error in remote sensing of sea surface temperature are discussed. The interfering effects of reflected solar radiation, reflected thermal flux, clouds and haze and atmospheric attenuation are examined. The components of measured sea surface radiances, such as clear column radiance, surface emission, atmospheric emission, reflected thermal downward flux, and reflection of solar flux, are analytically presented. The use of the 3.7 micron region window to obtain the radiance to four percent accuracy is discussed. The advantages to be obtained by the use of narrow bandpass channels are assessed.

Chahine, M. T.↗
NASA NTRS1984

Geologic mapping using thermal images

Thermal radiance data from the Heat Capacity Mapping Mission (HCMM) satellite has been used to measure surface reflectance data and to provide additional material composition information through remote sensing. The primary goal was to investigate the utility of HCMM data for geologic applications. Three techniques were used for displaying and combining thermal and visible near infrared (VNIR) data for two desert areas in southern California (Trona and Pisgah): color additive composites (CAC) for day and night IR and day VNIR, principal components, and calculation of thermal inertia images. The HCMM thermal data were more effective than Landsat data in producing separation of compositionally different areas including volcanic and intrusive rocks. The satellite CAC data produced an image for a 1 x 2 degree area, and the color picture was enlarged to a scale of 1:250,000. Playa composition, moisture content, presence of standing water, and vegetation cover were displayed in a variety of colors according to physical characteristics. Areas such as sand dunes were not distinguishable because of the coarse 500-mm HCMM resolution. HCMM thermal data have shown a new dimension to geologic remote sensing, and future satellite missions should allow the continued development of the thermal infrared data for geology.

Abrams, M. J.↗