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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.

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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Observations of Ocean Primary Productivity Using MODIS

Measuring the magnitude and variability of oceanic net primary productivity (NPP) represents a key advancement toward our understanding of the dynamics of marine ecosystems and the role of the ocean in the global carbon cycle. MODIS observations make two new contributions in addition to continuing the bio-optical time series begun with Orbview-2's SeaWiFS sensor. First, MODIS provides weekly estimates of global ocean net primary productivity on weekly and annual time periods, and annual empirical estimates of carbon export production. Second, MODIS provides additional insight into the spatial and temporal variations in photosynthetic efficiency through the direct measurements of solar-stimulated chlorophyll fluorescence. The two different weekly productivity indexes (first developed by Behrenfeld & Falkowski and by Yoder, Ryan and Howard) are used to derive daily productivity as a function of chlorophyll biomass, incident daily surface irradiance, temperature, euphotic depth, and mixed layer depth. Comparisons between these two estimates using both SeaWiFS and MODIS data show significant model differences in spatial distribution after allowance for the different integration depths. Both estimates are strongly dependence on the accuracy of the chlorophyll determination. In addition, an empirical approach is taken on annual scales to estimate global NPP and export production. Estimates of solar stimulated fluorescence efficiency from chlorophyll have been shown to be inversely related to photosynthetic efficiency by Abbott and co-workers. MODIS provides the first global estimates of oceanic chlorophyll fluorescence, providing an important proof of concept. MODIS observations are revealing spatial patterns of fluorescence efficiency which show expected variations with phytoplankton photo-physiological parameters as measured during in-situ surveys. This has opened the way for research into utilizing this information to improve our understanding of oceanic NPP variability. Deriving the ocean bio-optical properties places severe demands on instrument performance (especially band to band precision) and atmospheric correction. Improvements in MODIS instrument characterization and calibration over the first 16 mission months have greatly improved the accuracy of the chlorophyll input fields and FLH, and therefore the estimates of NPP and fluorescence efficiency. Annual estimates now show the oceanic NPP accounts for 40-50% of the global total NPP, with significant interannual variations related to large scale ocean processes. Spatial variations in ocean NPP, and exported production, have significant effects on exchange of CO2 between the ocean and atmosphere. Further work is underway to improve both the primary productivity model functions, and to refine our understanding of the relationships between fluorescence efficiency and NPP estimates. We expect that the MODIS instruments will prove extremely useful in assessing the time dependencies of oceanic carbon uptake and effects of iron enrichment, within the global carbon cycle.

Esaias, Wayne E.↗
NASA NTRS2014

Near-Cloud Aerosol Properties from the 1 Km Resolution MODIS Ocean Product

This study examines aerosol properties in the vicinity of clouds by analyzing high-resolution atmospheric correction parameters provided in the MODIS (Moderate Resolution Imaging Spectroradiometer) ocean color product. The study analyzes data from a 2 week long period of September in 10 years, covering a large area in the northeast Atlantic Ocean. The results indicate that on the one hand, the Quality Assessment (QA) flags of the ocean color product successfully eliminate cloud-related uncertainties in ocean parameters such as chlorophyll content, but on the other hand, using the flags introduces a sampling bias in atmospheric products such as aerosol optical thickness (AOT) and Angstrom exponent. Therefore, researchers need to select QA flags by balancing the risks of increased retrieval uncertainties and sampling biases. Using an optimal set of QA flags, the results reveal substantial increases in optical thickness near clouds-on average the increase is 50% for the roughly half of pixels within 5 km from clouds and is accompanied by a roughly matching increase in particle size. Theoretical simulations show that the 50% increase in 550nm AOT changes instantaneous direct aerosol radiative forcing by up to 8W/m2 and that the radiative impact is significantly larger if observed near-cloud changes are attributed to aerosol particles as opposed to undetected cloud particles. These results underline that accounting for near-cloud areas and understanding the causes of near-cloud particle changes are critical for accurate calculations of direct aerosol radiative forcing.

near-cloud aerosols↗
NASA NTRS2003

Advancing Glaciological Applications of Remote Sensing with EO-1: (1) Mapping Snow Grain Size and Albedo on the Greenland Ice Sheet Using an Imaging Spectrometer, and (2) ALI Evaluation for Subtle Surface Topographic Mapping via Shape-from Shading

The Hyperion sensor, onboard NASA's Earth Observing-1 (EO-1) satellite,is an imaging spectroradiometer with 220 spectral bands over the spectral range from 0.4 - 2.5 microns. Over the course of summer 2001, the instrument acquired numerous images over the Greenland ice sheet. Our main motivation is to develop an accurate and robust approach for measuring the broadband albedo of snow from satellites. Satellite-derived estimates of broadband have typically been plagued with three problems: errors resulting from inaccurate atmospheric correction, particularly in the visible wavelengths from the conversion of reflectance to albedo (accounting for snow BRDE); and errors resulting from regression-based approaches used to convert narrowband albedo to broadband albedo. A typerspectral method has been developed that substantially reduces these three main sources of error and produces highly accurate estimates of snow albedo. This technique uses hyperspectral data from 0.98 - 1.06 microns, spanning a spectral absorption feature centered at 1.03 microns. A key aspect of this work is that this spectral range is within an atmospheric transmission window and reflectances are largely unaffected by atmospheric aerosols, water vapor, or ozone. In this investigation, we make broadband albedo measurements at four sites on the Greenland ice sheet: Summit, a high altitude station in central Greenland; the ETH/CU camp, a camp on the equilibrium line in western Greenland; Crawford Point, a site located between Summit and the ETH/CU camp; and Tunu, a site located in northeastern Greenland at 2000 m. altitude. Each of these sites has an automated weather station (AWS) that continually measures broadband albedo thereby providing validation data.

Source record↗
NASA NTRS2019

An Approach to Retrieve BRDF from Satellite and Airborne Measurements of Surface-Reflected Radiance Based on Decoupling of Atmospheric Radiative Transfer and Surface Reflection

Bi-directional Reflection Distribution Function (BRDF) defines anisotropy of the surface reflection. It is required to specify the boundary condition for radiative transfer (RT) modeling. Measurements of reflected radiance by satellite- and air-borne sensors provide information about anisotropy of surface reflection. Atmospheric correction needs to be performed to derive BRDF from the reflected radiance. Common approach for BRDF retrievals consists of the use of kernel-based BRDF and RT modeling that needs to be done anew at every step of the iterative process. The kernels’ weights are obtained by minimization of the difference between measured and modeled radiance. This study develops a new method of retrieving kernel-based BRDF that requires RT calculations to be done only once. The method employs the exact analytical expression of radiance at any atmospheric level through the solutions of two auxiliary atmosphere-only RT problems and the surface-reflected radiance at the surface level. The latter is related to BRDF and solutions of the auxiliary RT problems by a Fredholm integral equation of the second kind. The approach requires to perform RT calculations one time before the iterations. It can use observations taken at different atmospheric conditions assuming that surface conditions remain unchanged during the time span of observations. The algorithm accurately catches zero weights of the kernels that may be a concern if the number of kernels is greater than 3 in current mainstream approaches. The study presents numerical tests of the BRDF retrieval algorithm for various surface and atmospheric conditions.

Radkevich, Alexander↗
NASA NTRS2018

Seasonal and Interannual Assessment of Cloud Cover and Atmospheric Constituents Across the Amazon (2000 - 2015): Insights for Remote Sensing and Climate Analysis

The quantitative assessment of cloud cover and atmospheric constituents improves our ability to exploit the climate feedback into the Amazon basin. In the 21st century, three droughts have already occurred in the Amazonia (e.g. 2005, 2010, 2015), inducing regional changes in the seasonal patterns of atmospheric constituents. In addition to climate, the atmospheric dynamic and attenuation properties are long-term challenges for satellite-based remote sensing of this ecosystem: high cloudiness, abundant water vapor content and biomass burning season. Therefore, while climatology analysis supports the understanding of atmospheric variability and trends, it also offers valuable insights for remote sensing applications. In this study, we evaluate the seasonal and interannual variability of cloud cover and atmospheric constituents (aerosol loading, water vapor and ozone content) over the Amazon basin, with focus on both climate analysis and remote sensing implications. We take the advantage of new atmosphere daily products at 1 km resolution derived from Multi-Angle Implementation for Atmospheric Correction (MAIAC) algorithm developed for Moderate Resolution Imaging Spectroradiometer (MODIS) data. An intercomparison of Aerosol Robotic Network (AERONET) and MAIAC aerosol optical depth (AOD) and columnar water vapor (CWV) showed quantitative information with a correlation coefficient higher than 0.81. Our results show distinct regional patterns of cloud cover across the Amazon basin: northwestern region presets a persistent cloud cover (> 80%) throughout the year, while low cloud cover (0-20%) occurs in the southern Amazon during the dry season. The cloud-free period in the southern Amazon is followed by an increase in the atmospheric burden due to fire emissions. Our results reveal that AOD records are changing in terms of area and intensity. During the 2005 and 2010 droughts, the positive AOD anomalies (δ > 0.1) occurred over 39.03% (240.3 million ha) and 27.14% (165.99 million ha) of total basin in the SON season, respectively. In contrast, the recent 2015 drought occurred towards the end of year (October through December) and these anomalies were observed over 23.72% (145 million ha) affecting areas in the central and eastern Amazon unlike previous droughts. The water vapor presents high concentration values (4.0-5.0 g/sq.cm) in the wet season (DJF), while we observed a strong spatial gradient from northwestern to southeastern of the basin during the dry season. In addition, we also found a positive trend of water vapor content ( ∼0.3 g/sq.cm) between 2000 and 2015. The total ozone typically varies between 220 and 270 DU, and it has a seasonal change of ∼25-35 DU from wet season to dry season caused by large emissions of ozone precursors and long-range transport. Finally, while this study contributes to climatological analysis of atmospheric constituents, the remote sensing users can also understand the regional constraints caused by atmospheric attenuation, such as high aerosol loading and cloud obstacles for surface observations.

ozone↗
NASA NTRS1984

Atmospheric Effects on Remote Sensing of the Earth's Surface

The main causes and magnitude of the atmospheric effects on remote sensing of the Earth's surface are determined. Theoretical study as well as measurements are included. The knowledge gained from this study will be used to develop atmospheric correction algorithms and to test them with satellite data. In a theoretical investigation of the relative effects of the aerosol optical thickness, absorption, and size distribution on remote sensing, it was found that aerosol absorption has a significant effect on satellite measurements of surface reflectivity. The absorption effect is stronger for high than for low surface reflectances. The aerosol optical thickness is dominant for small surface reflectances. The accuracy of clustering algorithms depends on both parameters. The vegetation index, however, is affected by the optical thickness but only weakly affected by the absorption. A laboratory simulation of the atmospheric effect on the radiance of sunlight scattered from the Earth's surface-atmosphere system was performed. This experiment verified the existence of the adjacency effect (the effect of a bright field on the radiance detected above a dark field) and was used to test 3-D radiative transfer models. In a theoretical study it was found that atmospheric scattering resulting from the adjacency effect reduces the separability between surface classes.

Fraser, R. E.↗
NASA NTRS2004

Time-Variable Gravity from Satellite Laser-Ranging: The Low-Degree Components and Their Connections with Geophysical/Climatic Changes

Satellite laser-ranging (SLR) has been observing the tiny variations in Earth s global gravity for over 2 decades. The oblateness of the Earth's gravity field, J2, has been observed to undergo a secular decrease of J2 due mainly to the post-glacial rebound of the mantle. Sometime around 1998 this trend reversed quite suddenly. This reversal persisted until 2001, at which point the atmosphere-corrected time series appears to have reversed yet again towards normal. This anomaly signifies a large interannual change in global mass distribution. A number of possible causes have been considered, with oceanic mass redistribution as the leading candidate although other effects, such as glacial melting and core effects may be contributing. In fact, a strong correlation has been found between the J2 variability and the Pacific decadal oscillation. It is relatively more difficult to solve for corresponding signals in the shorter wavelength harmonics from the existing SLR-derived time variable gravity results, although it appears that geophysical fluid mass transport is being observed. For example, the recovered J3 time series shows remarkable agreement with NCEP-derived estimates of atmospheric gravity variations. Likewise, some of the non-zonal harmonic components have significant interannual signal that appears to be related to mass transport related to climatic effects such as El Nino Southern Oscillation. We will present recent updates on the J2 evolution, as well as a monthly time sequence of low-degree component map of the time-variable gravity complete through degree 4, and examine possible geophysical/climatic causes.

Chao, Benjamin F.↗
NASA NTRS2002

Decadal Changes in Global Ocean Annual Primary Production

The Sea-viewing Wide Field-of-View Sensor (SeaWiFS) has produced the first multi-year time series of global ocean chlorophyll observations since the demise of the Coastal Zone Color Scanner (CZCS) in 1986. Global observations from 1997-present from SeaWiFS combined with observations from 1979-1986 from the CZCS should in principle provide an opportunity to observe decadal changes in global ocean annual primary production, since chlorophyll is the primary driver for estimates of primary production. However, incompatibilities between algorithms have so far precluded quantitative analysis. We have developed and applied compatible processing methods for the CZCS, using modern advances in atmospheric correction and consistent bio-optical algorithms to advance the CZCS archive to comparable quality with SeaWiFS. We applied blending methodologies, where in situ data observations are incorporated into the CZCS and SeaWiFS data records, to provide improvement of the residuals. These re-analyzed, blended data records provide maximum compatibility and permit, for the first time, a quantitative analysis of the changes in global ocean primary production in the early-to-mid 1980's and the present, using synoptic satellite observations. An intercomparison of the global and regional primary production from these blended satellite observations is important to understand global climate change and the effects on ocean biota. Photosynthesis by chlorophyll-containing phytoplankton is responsible for biotic uptake of carbon in the oceans and potentially ultimately from the atmosphere. Global ocean annual primary decreased from the CZCS record to SeaWiFS, by nearly 6% from the early 1980s to the present. Annual primary production in the high latitudes was responsible for most of the decadal change. Conversely, primary production in the low latitudes generally increased, with the exception of the tropical Pacific. The differences and similarities of the two data records provide evidence of how the Earth's climate may be changing and how ocean biota respond. Furthermore, the results have implications for the ocean carbon cycle.

Gregg, Watson↗
NASA NTRS2002

ENVISAT Land Surface Processes

This is a progress report of the 2nd phase of the project ENVISAT- Land Surface Processes, which has a 3-year scope. In this project, preparative research is carried out aiming at the retrieval of land surface characteristics from the ENVISAT sensors MERIS and AATSR, for assimilation into a system for Numerical Weather Prediction (NWP). Where in the 1st phase a number of first shot experiments were carried out (aiming at gaining experience with the retrievals and data assimilation procedures), the current 2nd phase has put more emphasis on the assessment and improvement of the quality of the retrieved products. The forthcoming phase will be devoted mainly to the data assimilation experiments and the assessment of the added value of the future ENVISAT products for NWP forecast skill. Referring to the retrieval of albedo, leaf area index and atmospheric corrections, preliminary radiative transfer calculations have been carried out that should enable the retrieval of these parameters once AATSR and MERIS data become available. However, much of this work is still to be carried out. An essential part of work in this area is the design and implementation of software that enables an efficient use of MODTRAN(sub 4) radiative transfer code, and during the current project phase familiarization with these new components has been achieved. Significant progress has been made with the retrieval of component temperatures from directional ATSR-images, and the calculation of surface turbulent heat fluxes from these data. The impact of vegetation cover on the retrieved component temperatures appears manageable, and preliminary comparison of foliage temperature to air temperatures were encouraging. The calculation of surface fluxes using the SEBI concept,which includes a detailed model of the surface roughness ratio, appeared to give results that were in reasonable agreement with local measurements with scintillometer devices. The specification of the atmospheric boundary conditions appears a crucial component, and the use of first guess estimates from the RACMO models partially explains the success. Earlier data assimilation experiments with directional surface temperatures have been analysed a bit further and were also compared to results obtained from directly modeling the surface roughness ratio. Results between these calculations and the data assimilation results appeared well comparable, but a full test in which the surface roughness model is allowed to play a free role during the data assimilation process has yet to be carried out. A considerable number of tasks that have yet to be carried out during Phase 3 has been formulated.

vandenHurk, B. J. J. M.↗
NASA NTRS2003

Precision Agriculture: Changing the Face of Farming

To a large extent our work has grown out of the remote sensing technology and conceptual framework developed by geologists. For example the drive to look at the physics of reflectance and atmospheric corrections is rooted in work done in the early 1980s by the United States Geological Survey and NASA. Our work on emissivity and thermal behavior of plants pulls on research done using the Thermal Infrared Multispectral Scanner, an instrument originally conceived for geologic applications. Even our ability to geometrically map the airborne imagery onto the globe was explicitly developed because of need to map sediment flow patterns in along the coast of Louisiana. Growing from this base we have learned much in the last few years and believe our integration of geologic remote sensing with the other fields of expertise was a wise investment. Clearly none of the specialties alone could develop, let alone test, the basic approach we are now finding so powerful. This is the path that will ultimately give the information needed by the farmer. We also recognize how small a portion of the total problem has been solved. Having developed the basic logic, built proto-type tools and performed initial tests everything else remains to be done. And problems, scientific and practical, are everywhere. We have not established sensitivities. We have not robustly segregated the contributions of crop residue, soil moisture, shadows, plant and soil to the energy leaving the surface. What we do is extremely expensive and difficult. It is experimental in methodology and uses research oriented tools. We are constantly alive to the practicality of moving our results into commercial applications. We know another airborne instrument will have to be available. Atmospheric parameters will have to be measured automatically. The software will have to be re-written for speed. At times the list of problems seems endless. But the potential is also enormous. Agriculture is a huge portion of our economy. Just a one percent increase in efficiency is a $2,000,000 change. We all depend on farmers, literally for the bread we eat. No other activity of man even has an impact on the land that farming has. If application of precision agriculture can nelp farmers manage their land better, we all may benefit.

Rickman, D.↗
NASA NTRS2017

Airborne Hyperspectral Sensing of Monitoring Harmful Algal Blooms in the Great Lakes Region: System Calibration and Validation

Harmful algal blooms (HABs) in Lake Erie have been prominent in recent years. The bloom in 2014 reached a severe level causing the State of Ohio to declare a state of emergency. At that time NASA Glenn Research Center was requested by stakeholders to help monitor the blooms in Lake Erie. Glenn conducted flights twice a week in August and September and assembled and distributed the HAB information to the shoreline water resource managers using its hyperspectral imaging sensor (in development since 2006), the S􀂱3 Viking aircraft, and funding resources from the NASA Headquarters Earth Science Division. Since then, the State of Ohio, National Oceanic and Atmospheric Administration (NOAA), and U.S. Environmental Protection Agency (EPA) have elevated their funding and activities for observing, monitoring, and addressing the root cause of HABs. Also, the communities and stakeholders have persistently requested NASA Glenn􀂶s participation in HAB observation. Abundant field campaigns and sample analyses have been funded by Ohio and NOAA, which provided a great opportunity for NASA to advance science and airborne hyperspectral remote sensing economically. Capitalizing on this opportunity to advance the science of algal blooms and remote sensing, NASA Glenn conducted the Airborne Hyperspectral Observation of harmful algal blooms campaign in 2015 that was, in many respects, twice as large as the 2014 campaign. Focusing mostly on Lake Erie, but also including other small inland lakes and the Ohio River, the campaign was conducted in partnership with a large number of partners specializing in marine science and remote sensing. Airborne hyperspectral observation of HABs holds promise to distinguish potential HABs from nuisance blooms, determine their concentrations, and delineate their movement in an augmented spatial and temporal resolution and under clouds􀂲all of which are excellent complements to satellite observations. Working with collaborators at several Ohio and Michigan institutions as well as one in South Dakota and one in Alabama, this effort was able to provide next-day georeferenced estimates of cyanobacteria and scum concentrations. Very prompt processing and analysis of the hyperspectral imagery is necessary for the information to be acted upon. For example, a next-day report of an overflight over the Ohio River indicated that a bloom could be present as far downstream as the Cincinnati intake, but the Ohio EPA had not received visual reports of a bloom that far downstream. Water samples were obtained at the Cincinnati water intake, based on the flight data, and detected microcystins in the source water. The flight data helped State and municipal authorities realize the potential extent of that bloom, and triggered response sampling, before the visual river-wide scums started forming. The present document describes the process that was utilized to take raw remote sensing data and create information products; this includes system calibration and validation, efforts to correct atmospheric effects, and algorithms that produce the data products. Furthermore, successful research into improved algorithms for expanding the capability to delineate in water constituents is included. Finally, comparisons that show expected relationships between ground-based measurements and hyperspectral imager version 2 (HSI2) data results are presented, giving confidence in the remote sensing products.

Hyperspectral Imaging↗
NASA NTRS1972

A simplified model for the gravitational potential of the atmosphere and its effect on the geoid

The earth's atmosphere is considered as made up of oblate spheroidal layers of variable density lying over an oblate spheroidal earth. The gravitational attraction of the atmosphere at exterior points is computed and its contribution to the usual spherical harmonic gravitational expansion is assessed. The potential is also found for points at the bottom of the model atmosphere. This latter result is of interest for determination of the potential at the surface of the geoid. The atmospheric correction to the geoid determination from satellite coefficients is given.

Madden, S. J., Jr.↗
NASA NTRS1976

Variability of wetland reflectance and its effect on automatic catergorization of satellite imagery

The author has identified the following significant results. A technique for training automated analysis of satellite multispectral data based on in situ measurements of target reflectance was tested and applied in delineating cover communities in Delaware's tidal wetlands. Land cover categorization of data from the same overpass in four test wetland areas was carried out using a four category classification system. The tests indicate that training data based on in situ reflectance measurements and atmospheric correction of LANDSAT data can produce comparable accuracy of categorization to that achieved using more conventional relative radiance training. Analysis of the four wetlands cover categories (salt marsh cordgrass, salt hay, water, and unvegetated tidal flat) produced average categorization accuracies of 82.1% by conventional relative radiance training and 81.4% by use of in situ reflectance measurements.

Klemas, V.↗
NASA NTRS1977

Statistics of the residual refraction errors in laser ranging data

A theoretical model for the range error covariance was derived by assuming that the residual refraction errors are due entirely to errors in the meteorological data which are used to calculate the atmospheric correction. The properties of the covariance function are illustrated by evaluating the theoretical model for the special case of a dense network of weather stations uniformly distributed within a circle.

Gardner, C. S.↗
NASA NTRS1977

Variability of wetland reflectance and its effect on automatic categorization of satellite imagery

The author has identified the following significant results. Land cover categorization of data from the same overpass in four test wetland areas was carried out using a four category classification system. The tests indicate that training data based on in situ reflectance measurements and atmospheric correction of LANDSAT data can produce comparable accuracy of categorization to that achieved using more than four wetlands cover categories (salt marsh cordgrass, salt hay, unvegetated, and water tidal flat) produced overall classification accuracies of 85% by conventional and relative radiance training and 81% by use of in situ measurements. Overall mapping accuracies were 76% and 72% respectively.

Klemas, V.↗
NASA NTRS1976

Advanced Sensors and Applications Study (ASAS)

The present EOD requirements for sensors in the space shuttle era are reported with emphasis on those applications which were deemed important enough to warrant separate sections. The application areas developed are: (1) agriculture; (2) atmospheric corrections; (3) cartography; (4) coastal studies; (5) forestry; (6) geology; (7) hydrology; (8) land use; (9) oceanography; and (10) soil moisture. For each application area. The following aspects were covered: (1) specific goals and techniques, (2) individual sensor requirements including types, bands, resolution, etc.; (3) definition of mission requirements, type orbits, coverages, etc.; and (4) discussion of anticipated problem areas and solutions. The remote sensors required for these application areas include; (1) camera systems; (2) multispectral scanners; (3) microwave scatterometers; (4) synthetic aperture radars; (5) microwave radiometers; and (6) vidicons. The emphasis in the remote sensor area was on the evaluation of present technology implications about future systems.

Chism, S. B.↗
NASA NTRS1976

The tasselled cap - A graphic description of the spectral-temporal development of agricultural crops as seen by Landsat

The time trajectories of agricultural data points as seen in Landsat signal space form a pattern suggestive of a tasselled woolly cap. Most of the important crop phenomena can be described using this three dimensional construct: the distribution of signals from bare soil, the processes of green development, yellow development, and shadowing and harvesting. A linear preprocessing transformation which isolates green development, yellow development and soil brightness is used to reduce the dimension of the signal space. Specific measurable pattern elements of the tasselled cap are used to estimate and correct atmospheric haze and moisture effects.

Kauth, R. J.↗
NASA NTRS1979

Multispectral Resource Sampler - An experimental satellite sensor for the mid-1980s

An experimental pushbroom scan sensor, the Multispectral Resource Sampler (MRS), being developed by NASA for a future earth orbiting flight is presented. This sensor will provide new earth survey capabilities beyond those of current sensor systems, with a ground resolution of 15 m over a swath width of 15 km in four bands. The four arrays are aligned on a common focal surface requiring no beamsplitters, thus causing a spatial separation on the ground which requires computer processing to register the bands. Along track pointing permits stereo coverage at variable base/height ratios and atmospheric correction experiments, while across track pointing will provide repeat coverage, from a Landsat-type orbit, of every 1 to 3 days. The MRS can be used for experiments in crop discrimination and status, rock discrimination, land use classification, and forestry.

Schnetzler, C. C.↗