Search NASA⌕ Search

SEARCH · Search NASA

Results for “reflection data”

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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Guatemala and Panama Urban Development: Evaluating the Effects of Urban Expansion on Social and Environmental Vulnerability in Guatemala and Panama

Central America is experiencing rapid and unregulated urban expansion, which is contributing to an increase in socioeconomic and environmental risks including inequities in infrastructure and housing accessibility, biodiversity loss, vulnerability to natural disasters, and negative health outcomes. NASA DEVELOP, in partnership with NASA SERVIR, Sistema de la Integración Centroamericana (SICA), Secretariat of Central American Social Integration (SISCA), Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ), and Centro de Coordinación para la Prevención de los Desastres en América Central y República Dominicana (CEPRENEDAC), examined changes in urban extent, characterized roofing material type, and analyzed vulnerability within urban areas in two Central American cities, Guatemala City and Panama City. The team used land cover imagery from Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), and Landsat 9 OLI-2 to map urban extent, and surface reflectance data from Maxar Worldview to identify roofing material types. Socioeconomic and environmental data were used to assess vulnerability. Results depict how the two cities have expanded from 2000 to present day and highlight areas of greatest vulnerability within each urban area. The supervised classification of roofing materials performed well but could be improved with a few enhancements. Findings can help partner organizations improve monitoring of urbanization and inform their planning and decision-making while prioritizing disaster prevention, public health, and environmental integrity. Additionally, these case studies can be used to inform future, similar work elsewhere in Central America to aid in understanding urbanization and its associated challenges.

Jennifer Ruiz↗
NASA NTRSDate not supplied

Mineralogical Evidence for Environmental Change in the Clay-Sulfate Transition at Gale Crater, Mars

A primary reason for selecting Gale crater as the Mars Science Laboratory (MSL) Curiosity rover landing site was a clear mineralogical transition from Fe/Mg smectite in older strata to hydrated Mg sulfate salts in younger strata observed in orbital visible/shortwave-infrared reflectance data. This transition has been observed in other early-Hesperian terrains on Mars and has been hypothesized to signal a planet-wide change in climate from relatively warm and wet to cold and dry. Curiosity studied the sedimentology and geochemical and mineralogical composition of rocks in this “clay-sulfate transition” region from sols 3052 to 3572 (i.e., March 2021 to August 2022), with arrival at the sulfate unit on sol 3574. Here, we report on the mineralogical measurements made by the CheMin X-ray diffractometer of the six drill targets in the clay-sulfate transition and the first drill target in the sulfate unit. We use compositional data and sedimentological observations to interpret depositional and diagenetic environments and present hypotheses to explain the transition from clay minerals to hydrated Mg sulfates.

E. B. Rampe↗
NASA NTRS2018

Intercomparison of Field Methods for Acquiring Ground Reflectance at Railroad Valley Playa for Spectral Calibration of Satellite Data

Ground reflectance was acquired at the Railroad Valley Playa calibration site in Nevada USA using different methods of collection. The data was collected near the time and date of Landsat 8 OLI and Sentinel-2 satellite overpasses so an inter-comparison could be made with the reflectance products to determine which method was more suitable for vicarious calibration. The field spectrometers and reference panels were characterized before the field campaign. A continuous acquisition method was compared to stop and measure collections. Both acquisition methods were collected along an 80 m east-west transect as well as for a series of north-south transects over an 80 x 320 m area, with the stop and measure method being performed at random sampling locations. The measurements were performed using two field spectrometers by three teams of two people to compare the repeatability. The aim of the field campaign was to determine the variability due to the operator and the method of collection.

Lau, Ian C.↗
NASA NTRS2018

Intercomparison of Field Methods for Acquiring Ground Reflectance at Railroad Valley Playa for Spectral Calibration of Satellite Data

Ground reflectance was acquired at the Railroad Valley Playa calibration site in Nevada USA using different methods of collection. The data was collected near the time and date of Landsat 8 OLI and Sentinel-2 satellite overpasses so an inter-comparison could be made with the reflectance products to determine which method was more suitable for vicarious calibration. The field spectrometers and reference panels were characterized before the field campaign. A continuous acquisition method was compared to stop and measure collections. Both acquisition methods were collected along an 80 m east-west transect as well as for a series of north-south transects over an 80 x 320 m area, with the stop and measure method being performed at random sampling locations. The measurements were performed using two field spectrometers by three teams of two people to compare the repeatability. The aim of the field campaign was to determine the variability due to the operator and the method of collection.

Lau, Ian C.↗
NASA NTRS1985

Multispectral, thermal infrared satellite data for geologic applications

The value of multispectral thermal infrared satellite data for geologic mapping was assessed, applying the principal component and canonical analysis techniques to the images of the central part of the Arabian Peninsula (a 200 x 300 km area). Low resolution thermal infrared (TIR) data from the Nimbus 5 Surface Composition Mapping Radiometer (SCMR) and the NOAA-7 Advanced Very High Resolution Radiometer (AVHRR) were used. Color images included an 8.8 micrometer (SCMR) and 3.7 and 10.8 micrometer (AVHRR-night) data, ratioed AVHRR day/night TIR data, ratioed AVHRR reflected radiation data, and transformed 8- and 10-band TIR plus reflected radiation data. The results clearly demonstrated the potential geologic value of multispectral TIR data. Igneous and metamorphic units could be separated as a class (although not from each other except for young calc-alkaline granites). Some previously unmapped extensions of mapped faults below thick sedimentary units could be delineated. No single enhancement technique displayed all the potential information, implying that they should be used together.

Blodget, H. W.↗
NASA NTRS2019

Evaluation of the Surface Reflectance Long-Term Data Record from AVHRR over Multiple Land Surface Types

In this work, we evaluate the performance of the AVHRR surface reflectance LTDR V4 using Landsat-5 Thematic Mapper (TM5) Collection-1 surface reflectance data over 440 globally distributed sites, which give a representative set of land surface types and climate conditions. Surface reflectance anisotropy effects were normalized using the VJB method, and spectral response differences were accounted for with spectral band adjustment factors (SBAFs) computed as a function of the Normalized Difference Vegetation Index (NDVI) from a set of over 100,000 hyperspectral spectra from Hyperion. The performance of the AVHRR record is reported in terms of the accuracy, precision, and uncertainty, as compared to the specifications of the reference product. Results show that the AVHRR record performance is close to the 0.071ρ+0.0071 specification defined in the original TM5 product evaluation.

LTDR↗
NASA NTRS1992

Learning class descriptions from a data base of spectral reflectance with multiple view angles

A learning program has been developed which combines 'learning by example' with the generate-and-test paradigm to furnish a robust learning environment capable of handling error-prone data. The problem is shown to be capable of learning class descriptions from positive and negative training examples of spectral and directional reflectance data taken from soil and vegetation. The program, which used AI techniques to automate very tedious processes, found the sequence of relationships that contained the most important information which could distinguish the classes.

Kimes, Daniel S.↗
NASA NTRS1990

Determination of surface reflectance and estimates of atmospheric optical depth and single scattering albedo from Landsat Thematic Mapper data

Groound-reflectance data on selected targets for calbiration of a Landsat TM image of Wind River Basin, Wyoming, acquired November 21, 1982 were examined. Field-derived calibration relationships together with Landsat radiometric calibration data are used to convert scanner DN values to spectral radiance for the TM bands and (together with a simplified homogeneous atmospheric model) to obtain estimates of single-scattering albedo and optical depth consistent with the derived path radiance and transmission properties of the atmosphere. These estimates are used to study the problems of evaluation of the magnitude of adjacency effects for reference targets, the assumption of isotropic properties, and the aggregate magnitude of multiple reflections between sky and ground. The radiance calibration equations are also used together with preflight measured signal/noise properties of the TM-4 system to estimate the noise-equivalent reflectance recoverable in practice from the system.

Conel, James E.↗
NASA NTRS1984

Study of spectral/radiometric characteristics of the thematic mapper for land use applications

The previous characterization of scan-related low-frequency noise was confirmed and extended through analysis of reflective-band data from another nighttime acquisition. Amplitude and phase relationships of the level shifts were determined for each detector in each of free full frames. Analysis of scan-direction-related signal droop effects in nighttime data from the reflective bands was begun with encouraging initial observations. Also, an effort to characterize high-frequency noise in the reflective bands through Fourier analysis of nighttime data was initiated. Recommendations are made relative to the choice of radiometric calibration constants in the thematic mapper image processing system for the routine processing of TM data. Non-linear (piece-wise linear) calibration curves are recommended.

Malila, W. A.↗
NASA NTRS2019

Winter Wheat Yield Assessment from Landsat 8 and Sentinel-2 Data: Incorporating Surface Reflectance, Through Phenological Fitting, into Regression Yield Models

A combination of Landsat 8 and Sentinel-2 offers a high frequency of observations (3–5 days) at moderate spatial resolution (10–30 m), which is essential for crop yield studies. Existing methods traditionally apply vegetation indices (VIs) that incorporate surface reflectances (SRs) in two or more spectral bands into a single variable, and rarely address the incorporation of SRs into empirical regression models of crop yield. In this work, we address these issues by normalizing satellite data (both VIs and SRs) derived from NASA’s Harmonized Landsat Sentinel-2 (HLS) product, through a phenological fitting. We apply a quadratic function to fit VIs or SRs against accumulated growing degree days (AGDDs), which affects the rate of crop development. The derived phenological metrics for VIs and SRs, namely peak, area under curve (AUC), and fitting coefficients from a quadratic function, were used to build empirical regression winter wheat models at a regional scale in Ukraine for three years, 2016–2018. The best results were achieved for the model with near infrared (NIR) and red spectral bands and derived AUC, constant, linear, and quadratic coefficients of the quadratic model. The best model yielded a root mean square error (RMSE) of 0.201 t/ha (5.4%) and coefficient of determination R2 = 0.73 on cross-validation.

phenological fitting↗
NASA NTRS2002

Study of Tropospheric Ozone and UV Reflectivity Using TOMS Data

Perhaps the single most important result from the study of Chuang and Yung is that the interannual variability of the Earth's albedo (especially in Spring) on land is dominated by snow/ice, and not by clouds. This interannual variability could be the major driver of changes in the atmosphere and the biosphere. It is plausible that the interannual variability of snow/ice, through interactions with the atmosphere and biosphere, is responsible for the interannual variability of atmospheric CO2. By carefully studying the albedo variations off the Peru coast, we found evidence for indirect aerosol effect on clouds. Based on a detailed analysis of the cloud data obtained by the International Satellite Cloud Climatology Project (SCCP) in the years 1983-1991, we show that besides the reported 3 % variation in global cloudiness, the global mean cloud optical thickness (MCOT) also has significant variation which is out of phase with that of the global cloudiness. The combined effect of the two opposing variations may be a null effect on the cloud reflectivity. These results are consistent with the Total Ozone Mapping Spectrometer (TOMS) reflectively measurements. The MCOT variation is further shown to be correlated with both the solar cycle and the ENSO (El Nino Southern Oscillation) cycle. Our present analysis cannot distinguish which of the above two provides better correlation, although independent data from the High resolution Infrared Radiation Sounder (HIRS) from 1990 to 1996 favor the solar cycle. Future data are needed to identify the true cause of these changes.

Yung, Yuk L.↗
NASA NTRS2019

Experimentally-Derived Bidirectional Reflectance Distribution Function Data in Support of the Orbital Debris Program Office

The NASA Orbital Debris Program Office (ODPO) has used various optical assets to acquire photometric data of Earth-orbiting objects to define the orbital debris environment. To better characterize and model optical data acquired from ground-based telescopes, the Optical Measurements Center (OMC) at NASA Johnson Space Center emulates illumination conditions seen in space by using equipment and techniques that parallel telescopic observations and source-target-sensor orientations. One of the OMC goals is to improve the size calculation used for optical data by developing an optical-based Size Estimation Model. The current size estimation requires applying a Lambertian phase function, a set albedo value, and range to the observed magnitude. The first step to improving the sampled brightness of laboratory targets is to remove aspect-angle dependencies. Then, the volume of possible object viewing angles is sampled at 21 combinations of azimuth and zenith angles for each solar phase angle. Finally, the acquired images are input into an image processing program that generates approximations for the object’s Bidirectional Reflectance Distribution Function (BRDF) and phase function. The BRDF is a radiometric concept that identifies an object’s material composition by matching a BRDF approximated with photometric data collected by ground-based telescopes with a BRDF generated experimentally from a known object in the laboratory. This paper discusses the validation of experimental BRDF and phase function approximations produced in the OMC and how the findings will be incorporated into ODPO models. A Lambertian sphere is imaged and the subsequent experimental functions are scrutinized to confirm that they correspond to an object that has an isotropic luminance. With the image processing algorithm validated, test objects with varying optical properties are then imaged to confirm that the produced photometric functions are both unique and repeatable. Once the validation is complete, the OMC will be used to evaluate a subset of fragments from a hypervelocity impact test of a mock-up satellite and assess the appropriate phase function and size estimates using BRDF measurements for a large volume of targets composed of various shapes, sizes, and materials.

Orbital Debris Program Office (ODPO)↗
NASA NTRS2022

Aerosol Models from the AERONET Database: Application to Surface Reflectance Validation Satellite Data

Aerosols play a critical role in radiative transfer within the atmosphere, and they have a significant impact on climate change. In this paper, we propose and implement a framework for developing an aerosol model using their microphysical properties. Such microphysical properties as the size distribution, the complex refractive index, and the percentage of sphericity are derived from the global AERosol RObotic NETwork (AERONET). These measurements, however, are typically retrieved when almucantar measurement procedures are performed (i.e., early mornings and late afternoons with clear sky) and might not have a temporal correspondence to a satellite overpass time, so a valid validation of satellite-derived products cannot be carried out. To address this problem of temporal inconsistency of satellite and ground-based measurements, we developed an approach to retrieve these microphysical properties (and the corresponding aerosol model) using the optical thickness at 440 nm, τ440, and the Ångström coefficient between 440 and 870 nm, α440–870. Such aerosol models were developed for 851 AERONET sites within the last 28 years. Obtained results suggest that empirically microphysical properties can be retrieved with uncertainties of up to 23 %. An exception is the imaginary part of the refractive index ni, for which the derived uncertainties reach up to 38 %. These specific parametric models of aerosol can be used for the studies when retrieval of microphysical properties is required as well as validation of satellite-derived products over land. Specifically, we demonstrate the usefulness of the aerosol models to validate surface reflectance records over land derived from optical remote sensing sensors. We then quantify the propagation of uncertainties in the surface reflectance due to uncertainties with the aerosol model retrieval that is used as a reference from radiative transfer simulations. Results indicate that individual aerosol microphysical properties can impact uncertainties in surface reflectance retrievals between 3.5 × 10(exp -5) to 1 × 10(exp -3) (in reflectance units). The overall impact of microphysical properties combined yields an overall uncertainty in surface reflectance <0.004 (in reflectance units). That corresponds, for example, to 1 to 3 % of the retrieved surface reflectance in the red spectral band (620–670 nm) by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. These uncertainty values are well below the specification (0.005 + 0.05ρ; ρ is the retrieved surface reflectance) used for the MODIS atmospheric correction.

Jean-Claude Roger↗
NASA NTRS2009

Changes in Cloud and Aerosol Cover (1980-2006) from Reflectivity Time Series Using SeaWiFS, N7-TOMS, EP-TOMS, SBUV-2, and OMI Radiance Data

The amount of solar radiation reflected back to space or reaching the Earth's surface is primarily governed by the amount of cloud cover and, to a much lesser extent, by Rayleigh scatteri ng, aerosols, and various absorbing gases (e.g., O3, NO2, H2O). A useful measure of the effect of cloud plus aerosol cover is given by the amount that the 331 run Lambert Equivalent Reflectivity (LER) ofa scene exceeds the surfuce reflectivity for snow/ice-free scenes after Rayleigh scattering has been removed. Twenty-eight years of reflectivity data are available by overlapping data from several satellites: N7 (Nimbus 7, TOMS; 331 nm) from 1979 to 1992, SBUV-2 series (Solar Backscatter Ultraviolet, NOAA; 331 nm) 1985 to 2007, EP (Earth-Probe, TOMS; 331 nm) 1997 to 2006, SW (SeaWiFS; 412 nm) 1998 to 2006, and OMI (Ozone Measuring Instrument; 331 nm) 2004-2007. Only N7 and SW have a sufficiently long data record, Sun-synchronous orbits, and are adequately calibrated for long-term reflectivity trend estimation. Reflectivity data derived from these instruments and the SBUV-2 series are compared during the overlapping years. Key issues in determining long-term reflecti vity changes that have occurred during the N7 and SW operating periods are discussed. The largest reflectivity changes in the 412 nm SW LER and 331 nm EP LER are found to occur near the equator and are associated with a large EI Nino-Southern Oscillation event. Most other changes that have occurred are regional, such as the apparent cloud decrease over northern Europe since 1998. The fractional occurrence (fraction of days) of high reflectivity values over Hudson Bay, Canada (snow/ice and clouds) appears to have decreased when comparing reflectivity data from 1980 to 1992 to 1997-2006, suggesting shorter duration of ice in Hudson Bay since 1980.

Herman, J. R.↗
NASA NTRSDate not supplied

Statistical Classification of Biosignature Information: Combining Elemental, Molecular, Reflectance, and Raman Data to Increase Life Detection Confidence

Planetary exploration missions seeking past or present signs of life carry not just a single instrument, but a suite. There is a need to study how these multiple data types can be combined to create “composite” biosignatures [1]. Algorithmic methods using existing data on living and non-living systems, though limited by the n = 1 of Earth, can nonetheless be informative. We assembled a database of 1277 measurements spanning 16 representative systems either indicative or non-indicative of life. Five classification (machine learning) methods were used on each individual data type, then on the entire set. This abstract summarizes the results; the data is described in more detail in [2], and methods in [3].

Biosignatures↗