SEARCH · Engineering Papers
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.
This paper focuses on the photogrammetric aspect of the data production and discusses quality of the global mapping as evaluated during the first two years of the mission.
Each area observed by MISR is imaged at all nine angles within a seven-minute period. MISR provides a unique approach to characterizing atmospheric aerosols, the surface, and the clouds. This paper provides examples of MISR products derived from imagery acquired during the first six months of data collection.
The in-flight calibration program for the EOS-AM1 Multi-angle Imaging SpectroRaidiometer (MISR) includes on-orbit calibration, characaterization of instrument properties and a calibration integrity process.
A plan for the ground-based validation of MISR aerosol retrieval is outlined. Activities occur in two phases: (1) pre-launch, work is focused on technique development and MISR algorithm validation using conventional ground-base methods and a MISR simulator (AirMISR) operating from the ER-2 aircraft to simulate MISR on-orbit observations. (2) Post-launch, the validation program relies on ground campaigns, underflights wit the MISR simulator and the use of local measurements fo aerosol loading and properties and irradiance measurements derived from the AERONET and ISIS networks.
UNKNOWN
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Transformations and losses of nitrogen (N) throughout the growing season can be costly. Methods in place to improve N management and facilitate split N applications during the growing season can be time consuming and logistically difficult. Remote sensing (RS) may be a method to rapidly assess temporal changes in crop N status and promote more efficient N management. This study was designed to evaluate the ability of three different RS platforms to predict N variability in corn (Zea mays L.) leaves during vegetative and early reproductive growth stages. Plots (15 x 15m) were established in the Coastal Plain (CP) and Appalachian Plateau (AP) physiographic regions each spring from 2000 to 2002 in a completely randomized design. Treatments consisted of four N rates (0, 56, 112, and 168 kg N/ha) applied as ammonium nitrate (NH4N03) replicated four time. Spectral measurements were acquired via spectroradiometer (lambda = 350 - 1050 nm), Airborne Terrestrial Applications Sensor (ATLAS) (lambda = 400 - 12,500 nm), and the IKONOS satellite (lambda = 450 - 900 nm). Spectroradiometer data were collected on a biweekly basis from V4 through R1. Due to the nature of - satellite and aircraft acquisitions, these data were acquired per availability. Chlorophyll meter (SPAD) and tissue N were collected as ancillary data along with each RS acquisition. Results showed vegetation indices derived from hand-held spectroradiometer measurements as early as V6-V8 were linearly related to yield and tissue N content. ATLAS data was correlated with tissue N at the AP site during the V6 stage (r2 = 0.66), but no significant relationships were observed at the CP site. No significant relationships were observed between plant N and IKONOS imagery. Using a combination of the greenness vegetation index (GNDVI) and the normalized difference vegetation index (NDVI), RS data acquired via ATLAS and the spectroradiometer could be used to evaluate tissue N variability and estimate corn yield variability under ideal growing conditions.
The Atmospheric Radiation Measurement (ARM) program (now Atmospheric System Research) was established, in part, to improve radiation models so that they could be used reliably to compute radiation fluxes through the atmosphere, given knowledge of the surface albedo, atmospheric gases, and the aerosol and cloud properties. Despite years of observations, discrepancies still exist between radiative transfer models and observations, particularly in the presence of clouds. Progress has been made at closing discrepancies in the spectral region beyond 3 micron, but the progress lags at shorter wavelengths. Ratios of observed visible and near infrared cloud albedo from aircraft and satellite have shown both localized and global discrepancies between model and observations that are, thus far, unexplained. The capabilities of shortwave surface spectrometry have been improved in recent years at the Southern Great Plains facility (SGP) of the ARM Climate Research Facility through the addition of new instrumentation, the Shortwave Array Spectroradiometer, and upgrades to existing instrumentation, the Shortwave Spectroradiometer and the Rotating Shadowband Spectroradiometer. An airborne-based instrument, the HydroRad Spectroradiometer, was also deployed at the ARM site during the Routine ARM Aerial Facility Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) field campaign. Using the new and upgraded spectral observations along with radiative transfer models, cloud scenes at the SGP are presented with the goal of characterizing the instrumentation and the cloud fields themselves.
The first five years of operation of the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) at the Lagrange one point have produced results that uniquely complement the data from currently operating low orbit Earth-observing instruments. In this paper we describe an updated unified approach to EPIC calibration. In this approach, calibration coefficients and their trends were obtained by comparing EPIC observations to the measurements from polar orbiting radiometers. In this study L1B reflectances from Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua and Terra satellites, Multi-angle Imaging Spectroradiometer (MISR) onboard Terra and Visible Infrared Imaging Radiometer (VIIRS) onboard the Suomi National Polar-orbiting Partnership (Suomi NPP) spacecraft were used to infer calibration coefficients for four EPIC visible and near-infrared channels: 443 nm, 551 nm, 680 nm, and 780 nm. EPIC Version three measurements made between June 2015 and August 2020 were used for comparison. The calibration procedure identifies the most homogeneous low Earth orbit radiometer scenes matching scattering angles that are temporarily and spatially collocated with EPIC observations. These scenes are used to determine reflectance to count (R/C) ratios in spectrally analogous channels. Seasonal average R/C ratios were analyzed to obtain EPIC calibration gains and trends. The trends for the full dataset period are not statistically significant except in the 443 nm channel. No significant changes in calibration were found after the instrument’s exit from safe hold in March 2020. The R/C ratios were also used to determine the differences in EPIC gains resulting from separate calibrations: against MODIS Aqua or Terra, as well as against forward or aftward MISR cameras. Statistical tests indicate that the differences between the two datasets are not significant except in the 780 nm channels where Aqua-derived coefficients may be around 2% lower compared to Terra. The dependence of EPIC calibration gains on the instrument scattering angle and on DSCOVR-Earth distance were investigated. Lastly, model Low Earth Orbit (LEO) reflectances calculated to match the EPIC viewing geometry were employed to study how EPIC calibration coefficients depend on EPIC-LEO viewing geometry differences. The effect of LEO and EPIC angular mismatch on calibration was shown to be small.
The construction of the Stanford Spectral Digital Data Acquisition System is described. The objective of the system is to record both the spectral distribution of incoming radiation from the rock samples measured by the spectroradiometer (Exotech Model 10-34 Circular Variable Filter Infrared Spectroradiometer) together with other weather information. This system is designed for both laboratory and field measurement programs. The multichannel inputs (8 channels) of the system are as follows: Ch 1 the Spectro-radiometer, Ch 2 the radiometer (PRT-5), and Ch 3 to Ch 8 for the weather information. The system records data from channel 1 and channel 2 alternately for 48 times, before a fast sweep across the six weather channels, to form a single scan in the scan counter. The operation is illustrated in a block diagram, and the theory of operation is described. The outputs are written on a 7-track magnetic tape with IBM compatible form. The format of the tape and the playback computer programs are included. The micro-pac digital modules and a CIPHER model 70 tape recorder (Cipher Data Products) are used. One of the major characteristics of this system is that it is externally clocked by the spectroradiometer instead of taking data at intervals of various wavelengths by using internal-clocking.
A technique was developed to obtain bidirectional reflectance data from natural surfaces by using a folding mirror to transfer the reflected energy from the test surface to a spectroradiometer. The folding mirror was a first surface reflector made by stretching Mylar vacuum coated with aluminum over a light weight frame. The optically folding mirror was positioned over the test surfaces with a moveable platform for both laboratory and field tests. Field tests were conducted using a tethered balloon system to position the folding mirror. A spectroradiometer was designed and built specifically for this investigation. The spectroradiometer had an angular field of view of twenty-four minutes in one axis and ten minutes in the other axis. The radiometer was capable of detecting energies in small bandwidths throughout the electromagnetic spectrum from 0.3 microns to 3.0 microns. Bidirectional reflectance data and variations in the data with source angles were obtained for Saint Augustine grass, Bermuda grass, and a black alluvium soil from the Mississippi River delta.
An optical imager, called the Scanning Imaging Spectroradiometer (SIS), was built for NASA in the early 1970's. Later, the Solidstate Array Spectroradiometer (SAS) was developed on the basis on a substitution of a Charge Injection Device (CID) array for the vidicon of the SIS. The Advanced Solidstate Array Spectroradiometer (ASAS) represents an improvement of the SAS. ASAS is a solidstate multispectral optical imaging radiometer which is currently the most versatile instrument of its type in the visible part of the spectrum. The instrument is capable of absolute radiometric measurements in all of its 32 bands. ASAS can be easily mounted in small aircraft as well as high altitude craft such as the U-2, taking into account also the possibility of a use in the Space Shuttle. The instrument consists of three separate subsystems. Attention is given to the optics, the detector array, data storage, data retrieval, and system performance.
A method for using congruent atmospheric path aircraft-satellite observations to calibrate a satellite radiometer is presented. A calibrated spectroradiometer aboard a NASA ER-2 aircraft at an altitude of 19 km above White Sands (New Mexico) was oriented to view White Sands at the overpass time of the NOAA-11 AVHRR instrument along the same view vector as the satellite instrument. The data from six flights between November 1988 and October 1990 were transformed into corresponding estimates of AVHRR channel radiance at the satellite (derived from the aircraft measurements), and average counts (from the AVHRR measurements), both averaged across the footprint of the spectroradiometer. Prelaunch measurements of the AVHRR spectral response profiles are assumed, and the radiance spectrum measured by the spectroradiometer was adjusted to satellite altitude using the LOWTRAN-7 computer code. Results show reduced gains in both channel 1 (0.65 micron) and channel 2 (0.85 micron), compared to prelaunch values, with little further reduction in gain after 200 days in orbit. Results for the gain ratio (channel 1/channel 2), which is important for the calculation of the normalized vegetation index, show constant in-orbit values 5 percent above the prelaunch value.
Statistical classification of remotely sensed images attempts to discriminate between surface cover types on the basis of the spectral response recorded by a sensor. It is well known that surfaces reflect incident radiation as a function of wavelength producing a spectral signature specific to the material under investigation. Multispectral and hyperspectral sensors sample the spectral response over tens and even hundreds of wavelength bands to capture the variation of spectral response with wavelength. Classification algorithms then exploit these differences in spectral response to distinguish between materials of interest. Sensors of this type, however, collect detailed spectral information from one direction (usually nadir); consequently, do not consider the directional nature of reflectance potentially detectable at different sensor view angles. Improvements in sensor technology have resulted in remote sensing platforms capable of detecting reflected energy across wavelengths (spectral signatures) and from multiple view angles (angular signatures) in the fore and aft directions. Sensors of this type include: the moderate resolution imaging spectroradiometer (MODIS), the multiangle imaging spectroradiometer (MISR), and the airborne solid-state array spectroradiometer (ASAS). A goal of this paper, then, is to explore the utility of Bidirectional Reflectance Distribution Function (BRDF) models in the selection of optimal view angles for the classification of remotely sensed images by employing a strategy of searching for the maximum difference between surface BRDFs. After a brief discussion of directional reflect ante in Section 2, attention is directed to the Beard-Maxwell BRDF model and its use in predicting the bidirectional reflectance of a surface. The selection of optimal viewing angles is addressed in Section 3, followed by conclusions and future work in Section 4.