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.
The NGST wavefront control testbed (also known as DCATT) is being used to map out the accuracy and dynamic range of the baseline NGST wavefront control system.
The ship on the opposite page is a U. S. Steel Corporation tanker cruising through the ice-covered waters of the Great Lakes in the dead of winter. The ship's crew is able to navigate safely by plotting courses through open water or thin ice, a technique made possible by a multi-agency technology demonstration program in which NASA is a leading participant. Traditionally, the Great Lakes-St. Lawrence Seaway System is closed to shipping for more than three months of winter season because of ice blockage, particularly fluctuations in the thickness and location of ice cover due to storms, wind, currents and variable temperatures. Shippers have long sought a system of navigation that would allow year-round operation on the Lakes and produce enormous economic and fuel conservation benefits. Interrupted operations require that industrial firms stockpile materials to carry them through the impassable months, which is costly. Alternatively, they must haul cargos by more expensive overland transportation. Studies estimate the economic benefits of year-round Great Lakes shipping in the hundreds of millions of dollars annually and fuel consumption savings in the tens of millions of gallons. Under Project Icewarn, NASA, the U.S. Coast Guard and the National Oceanic Atmospheric Administration collaborated in development and demonstration of a system that permits safe year-round operations. It employs airborne radars, satellite communications relay and facsimile transmission to provide shippers and ships' masters up-to-date ice charts. Lewis Research Center contributed an accurate methods of measuring ice thickness by means of a special "short-pulse" type of radar. In a three-year demonstration program, Coast Guard aircraft equipped with Side-Looking Airborne Radar (SLAR) flew over the Great Lakes three or four times a week. The SLAR, which can penetrate clouds, provided large area readings of the type and distribution of ice cover. The information was supplemented by short-pulse radar measurements of ice thickness. The radar data was relayed by a NOAA satellite to a ground station where NOAA analyzed it and created picture maps, such as the one shown at lower left, showing where icebreakers can cut paths easily or where shipping can move through thin ice without the aid of icebreakers. The ice charts were then relayed directly to the wheelhouses of ships operating on the Lakes. Following up the success of the Great Lakes program, the icewarn team applied its system in another demonstration, this one a similarly successful application designed to aid Arctic coast shipping along the Alaskan North Slope. Further improvement of the ice-monitoring system is planned. Although aircraft-mounted radar is effective, satellites could provide more frequent data. After the launch this year of Seasat, an ocean-monitoring satellite, NASA will conduct tests to determine the ice-mapping capability and accuracy of satellite radar images.
A new spectral-spatial method for hyperspectral data classification is proposed. For a given hyperspectral image, probabilistic pixelwise classification is first applied. Then, hierarchical step-wise optimization algorithm is performed, by iteratively merging neighboring regions with the smallest Dissimilarity Criterion (DC) and recomputing class labels for new regions. The DC is computed by comparing region mean vectors, class labels and a number of pixels in the two regions under consideration. The algorithm is converged when all the pixels get involved in the region merging procedure. Experimental results are presented on two remote sensing hyperspectral images acquired by the AVIRIS and ROSIS sensors. The proposed approach improves classification accuracies and provides maps with more homogeneous regions, when compared to previously proposed classification techniques.
Following the end of the Angolan civil war in 2002, human and livestock populations have increased exponentially within Iona National Park. An ongoing drought since 2017 has brought these people and livestock into increasing competition with local wildlife for resources – highlighting a conservation challenge that will become more entrenched as the effects of anthropogenic climate change increase. In 2019, African Parks began co-managing Iona National Park in Angola with the Angolan government, hoping to enact scientifically grounded management strategies to meet this challenge. To accomplish this, African Parks needed contemporary and historic information on the spatial distribution of landcover types within Iona and adjacent areas. We constructed and applied a Random Forest classifier in Google Earth Engine to multispectral imagery gathered from Landsat 5, 7, 8 and Sentinel-1 and 2 to meet this need. Using the classifier, we generated a time-series of land cover maps between 1990–2023, from which landscape metrics and change detection analysis were calculated to show how certain habitats and formations had changed over time. The resulting maps have producer and user’s accuracies above 87% and show four broad landcover regions within the study area. Notably, we observed a decrease in the park’s diversity as per the Shannon Diversity Index – an index that considers the richness of classes, as well the evenness of their distribution. A lack of arid specific land cover indices and ground-truthed training data from earlier years limited the accuracy and resolution of our landcover maps. However, this project still demonstrates that Earth observations can be used to form the basis of conservation policy in arid environments, where ground-truth data may be difficult to obtain or non-existent.
The author has identified the following significant results. Analog processing of S190A and B color and infrared color transparencies showed that it is possible to evaluate the courses of the temporary snow line and the upper limit of vegetation growth over large areas. By transferring the results from S190A onto a topo-map 1:200,000, an accuracy of + or - 50 m could be achieved. With S190B transferred onto a map 1:100,000, an accuracy of + or - 20 m was reached. Digital processing of S192 multispectral data allowed a separation of snow and clouds by combining the information from channels 9, 15, and 18.
The author has identified the following significant results. LANDSAT imagery and supplementary aircraft photography of the New River drainage basin were subjected to a multilevel analysis using conventional photointerpretation methods, densitometric techniques, multispectral analysis, and statistical tests to determine the accuracy of LANDSAT-1 imagery for measuring strip mines of common size. The LANDSAT areas were compared with low altitude measurements. The average accuracy over all the mined land sample areas mapped from LANDSAT-1 was 90%. The discrimination of strip mine subcategories is somewhat limited on LANDSAT imagery. A mine site, whether active or inactive, can be inferred by lack of vegetation, by shape, or image texture. Mine ponds are difficult or impossible to detect because of their small size and turbidity. Unless bordered and contrasted with vegetation, haulage roads are impossible to delineate. Preparation plants and refuge areas are not detectable. Density slicing of LANDSAT band 7 proved most useful in the detection of reclamation progress within the mined areas. For most state requirements for year-round monitoring of surface mined land, LANDSAT is of limited value. However, for periodic updating of regional surface maps, LANDSAT may provide sufficient accuracies for some users.
The year 2002 brought advances on many fronts in our space exploration ventures. A new orbiter settled in at Mars and delivered tantalizing science results suggesting a vast store of water ice under the planet's surface, a discovery that may have profound consequences for exploring Mars. A long-lived spacecraft made its final fly-bys of Jupiter's moons, while another started its final approach toward Saturn and yet another flew by an asteroid on its way to a comet. A new ocean satellite began science observations, joined in Earth orbit by a pair of spacecraft measuring our home planets gravity field, as well as JPL instruments on NASA and Japanese satellites. A major new infrared observatory and a pair of Mars rovers were readied for launch. All told, JPL is now communicating with 14 spacecraft cast like gems across the velvet expanses of the solar system. It is a far cry from the early 1960's, when JPL engineers made prodigious efforts to get the first planetary explorers off the ground and into space - an achievement of which we were especially mindful this year, as 2002 marked the 40th anniversary of the first successful planetary mission, Mariner 2, which barely reached our closest planetary neighbor, Venus. Added to this anniversary were celebrations surrounding the 25th anniversaries of the launches of Voyagers 1 and 2, two remarkable spacecraft that are still flying and are actively probing the outer realms of the solar system. These events of the past and present provide an occasion for reflection on the remarkable era of exploration that we at the Jet Propulsion Laboratory are privileged to be a part of. As 2002 neared its end, the Laboratory had yet another reason for celebration, as a new five-year management contract between NASA and the California Institute of Technology was signed that calls for a closer working relationship with NASA and other NASA centers as a member of the 'One NASA' team. There is a strong emphasis on cost control and management, areas in which we can improve, enabling us to become more competitive. This new agreement again confirms NASA's trust and faith in Caltech and JPL, in which we should all take great pride. If the history of JPL were a book, we are on the verge of turning the page to one that promises to be one of the most exciting and busiest chapters in JPL's history. In 2003 and 2004, we will launch 11 spacecraft or major payloads. We will land two rovers on Mars; put a spacecraft in orbit around Saturn, deliver a probe to the surface of its largest moon, Titan, and map Titan's surface withimaging radar; send a spacecraft past a comet collecting samples from its tail, while another one is launched toward a comet impact; bring a capsule back to Earth with the first samples ever collected beyond the orbit of the Moon; map the skies in the ultraviolet as well as the infrared spectrum to unprecedented accuracy; and continue the mapping of ocean topography and winds on our home planet, Earth.
The author has identified the following significant results. The mapping of generalized land use (level 1) from ERTS 1 images was shown to be feasible with better than 95% accuracy in the Phoenix quadrangle. The accuracy of level 2 mapping in urban areas is still a problem. Updating existing maps also proved to be feasible, especially in water categories and agricultural uses; however, expanding urban growth has presented with accuracy. ERTS 1 film images indicated where areas of change were occurring, thus aiding focusing-in for more detailed investigation. ERTS color composite transparencies provided a cost effective source of information for land use mapping of very large regions at small map scales.
The author has identified the following significant results. Skylab/EREP S190A and S190B film products were optically enhanced and visually interpreted to extract data suitable for mapping coastal land use; inventorying wetlands vegetation; monitoring tidal conditions; observing suspended sediment patterns; charting surface currents; locating coastal fronts and water mass boundaries; monitoring industrial and municipal waste dumps in the ocean; and determining the size and flow direction of river, bay, and man-made discharge plumes. Film products were visually analyzed to identify and map ten land use and vegetation categories at a scale of 1:125,000. Thematic maps were compared with CARETS land use maps, resulting in classification accuracies of 50 to 98%. Digital tapes from S192 were used to prepare thematic land use maps. The resolutions of the S190A, S190B, and S192 systems were 20-40m, 10-20m, and 70-100m, respectively.
There are several hemispheric-scale satellite-derived snow-cover maps available, but none has been fully validated. For the period October 23 - December 25, 2000, we compare snow maps of North America derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the National Oceanic and Atmospheric Administration (NOAA) National Operational Hydrologic Remote Sensing Center (NOHRSC), which both rely on satellite data from the visible and near-infrared parts of the spectrum; we also compare MODIS and Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) passive-microwave snow maps. The maps derived from visible and near-infrared data are more accurate for mapping snow cover than are the passive-microwave-derived maps, however discrepancies exist as to the location and extent of the snow cover among those maps. The large (approx. 30 km) footprint of the SSM/I data and the difficulty in distinguishing wet and shallow snow from wet or snow-free ground, reveal differences up to 5.32 million sq km in the amount of snow mapped using MODIS versus SSM/I data. Algorithms that utilize both visible and passive-microwave data, which would take advantage of the all-weather mapping ability of the passive-microwave data, will be refined following the launch of the Advanced Microwave Scanning Radiometer (AMSR) in the fall of 2001.
This study demonstrates a globally applicable method for monitoring mangrove forest extent at high spatial resolution. A 2010 mangrove baseline was classified for 16 study areas using a combination of ALOS PALSAR and Landsat composite imagery within a random forests classifier. A novel map-to-image change method was used to detect annual and decadal changes in extent using ALOS PALSAR/JERS-1 imagery. The map-to-image method presented makes fewer assumptions of the data than existing methods, is less sensitive to variation between scenes due to environmental factors (e.g., tide or soil moisture) and is able to automatically identify a change threshold. Change maps were derived from the 2010 baseline to 1996 using JERS-1 SAR and to 2007, 2008 and 2009 using ALOS PALSAR. This study demonstrated results for 16 known hotspots of mangrove change distributed globally, with a total mangrove area of 2,529,760 ha. The method was demonstrated to have accuracies consistently in excess of 90% (overall accuracy: 92.2–93.3%, kappa: 0.86) for mapping baseline extent. The accuracies of the change maps were more variable and were dependent upon the time period between images and number of change features. Total change from 1996 to 2010 was 204,850 ha (127,990 ha gain, 76,860 ha loss), with the highest gains observed in French Guiana (15,570 ha) and the highest losses observed in East Kalimantan, Indonesia (23,003 ha). Changes in mangrove extent were the consequence of both natural and anthropogenic drivers, yielding net increases or decreases in extent dependent upon the study site. These updated maps are of importance to the mangrove research community, particularly as the continual updating of the baseline with currently available and anticipated spaceborne sensors. It is recommended that mangrove baselines are updated on at least a 5-year interval to suit the requirements of policy makers.
A higher resolution anomaly map of the Broken Ridge area (2 degree dipole spacing) was produced and reduced to the pole using quiet time data for this area. The map was compared with equally scaled maps of gravity anomaly, geoid undulation, and bathymetry. The ESMAP results were compared with a NASA MAGSAT map derived by averaging data in two-degree bins. A survey simulation was developed to model the accuracy of MAGSAT anomaly maps as a function of satellite altitude, instrument noise level, external noise model, and crustal anomaly field model. A preliminary analysis of the geophysical structure of Broken Ridge is presented and unresolved questions are listed.
It is pointed out that many recent advances in the finite-difference solution of elliptic equations have been limited to regions whose boundary contours coincide with coordinate lines of the Cartesian coordinate system. The reason for this is related to the fact that in the case of an arbitrary curvilinear coordinate system the original equation becomes much more complex. However, there is no added complexity if an orthogonal coordinate system is generated from a conformal mapping. In the present investigation, a finite difference method developed for the construction of conformal mappings has been generalized to construct quasi-conformal mappings. It is expected that the use of more sophisticated numerical algorithms could lead to improvements in both speed and accuracy. Quasi-conformal mappings have applications not only in the solution of elliptic equations but also in other areas such as orthogonal mesh generation on surfaces and the solution of certain fluid flow problems.
The accuracy of adaptively chosen, mapped polynomial approximations is studied for functions with steep gradients or discontinuities. It is shown that, for steep gradient functions, one can obtain spectral accuracy in the original coordinate system by using polynomial approximations in a transformed coordinate system with substantially fewer collocation points than are necessary using polynomial expansion directly in the original, physical, coordinate system. It is also shown that one can avoid the usual Gibbs oscillation associated with steep gradient solutions of hyperbolic pde's by approximation in suitably chosen coordinate systems. Continuous, high gradient solutions are computed with spectral accuracy (as measured in the physical coordinate system). Discontinuous solutions associated with nonlinear hyperbolic equations can be accurately computed by using an artificial viscosity chosen to smooth out the solution in the mapped, computational domain. Thus, shocks can be effectively resolved on a scale that is subgrid to the resolution available with collocation only in the physical domain. Examples with Fourier and Chebyshev collocation are given.
The accuracy of adaptively chosen, mapped polynomial approximations is studied for functions with steep gradients or discontinuities. It is shown that, for steep gradient functions, one can obtain spectral accuracy in the original coordinate system by using polynomial approximations in a transformed coordinate system with substantially fewer collocation points than are necessary using polynomial expansion directly in the original, physical, coordinate system. It is also shown that one can avoid the usual Gibbs oscillation associated with steep gradient solutions of hyperbolic pde's by approximation in suitably chosen coordinate systems. Continuous, high gradient solutions are computed with spectral accuracy (as measured in the physical coordinate system). Discontinuous solutions associated with nonlinear hyperbolic equations can be accurately computed by using an artificial viscosity chosen to smooth out the solution in the mapped, computational domain. Thus, shocks can be effectively resolved on a scale that is subgrid to the resolution available with collocation only in the physical domain. Examples with Fourier and Chebyshev collocation are given.
The NASA New Frontiers OSIRIS-REx spacecraft executed a flawless launch on September 8, 2016 to begin its 23-month journey to near-Earth asteroid (101955). The primary objective of the OSIRIS-REx mission is to collect and return to Earth a pristine sample of regolith from the asteroid surface. The sampling event will occur after a two-year period of remote sensing that will ensure a high probability of successful sampling of a region on the asteroid surface having high science value and within well-defined geological context. The OSIRIS-REx instrument payload includes three high-resolution cameras (OCAMS), a visible and near-infrared spectrometer (OVIRS), a thermal imaging spectrometer (OTES), an X-ray imaging spectrometer (REXIS), and a laser altimeter (OLA). As the spacecraft follows its nominal outbound-cruise trajectory, the propulsion, power, communications, and science instruments have undergone basic functional tests, with no major issues. Outbound cruise science investigations include a search for Earth Trojan asteroids as the spacecraft approaches the Sun-Earth L4 Lagrangian point in February 2017. Additional instrument checkouts and calibrations will be carried out during the Earth gravity assist maneuver in September 2017. During the Earth-moon flyby, visual and spectral images will be acquired to validate instrument command sequences planned for Bennu remote sensing. The asteroid Bennu remote sensing campaign will yield high resolution maps of the temperature and thermal inertia, distributions of major minerals and concentrations of organic matter across the asteroid surface. A high resolution 3d shape model including local surface slopes and a high-resolution gravity field will also be determined. Together, these data will be used to generate four separate maps that will be used to select the sampling site(s). The Safety map will identify hazardous and safe operational regions on the asteroid surface. The Deliverability map will quantify the accuracy with which the navigation team can deliver the spacecraft to and from specific sites on the asteroid surface. The Sampleability map quantifies the regolith properties, providing an estimation of how much material would be sampled at different points on the surface. The final Science Value map synthesizes the chemical, mineralogical, and geological, observations to identify the areas of the asteroid surface with the highest science value. Here, priority is given to organic, water-rich regions that have been minimally altered by surface processes. Asteroid surface samples will be acquired with a touch-and-go sample acquisition system (TAGSAM) that uses high purity pressurized N2 gas to mobilize regolith into a stainless steel canister. Although the mission requirement is to collect at least 60 g of material, tests of the TAGSAM routinely exceeded 300 g of simulant in micro-gravity tests. After acquiring the sample, the spacecraft will depart Bennu in 2021 to begin its return journey, with the sample return capsule landing at the Utah Test and Training Range on September 23, 2023. The OSIRIS-REx science team will carry out a series of detailed chemical, mineralogical, isotopic, and spectral studies that will be used to determine the origin and history of Bennu and to relate high spatial resolution sample studies to the global geological context from remote sensing. The outline of the sample analysis plan is described in a companion abstract.
Aquarius is an L-band instrument designed to measure sea surface salinity from space. The instrument was launched in 2011 and data acquisition ended in June 2015 when control of the spacecraft was lost. Aquarius produced global maps of salinity with accuracy of 0.2 psu (Practical Salinity Unit) and special resolution of 150 kilometers as well as other products such as global maps of RFI (Radio Frequency Interference) and soil moisture. The mission will formally end December 2017.
A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must for food and water security analysis. Precise and accurate global cropland extent maps, indicating cropland and non-cropland areas, is a starting point to develop high-level products such as crop watering methods (irrigated or rainfed), cropping intensities (e.g., single, double, or continuous cropping), crop types, cropland fallows, as well as assessment of cropland productivity (productivity per unit of land), and crop water productivity (productivity per unit of water). Uncertainties associated with the cropland extent map have cascading effects on all higher-level cropland products. However, precise and accurate cropland extent maps at high spatial resolution over large areas (e.g., continents or the globe) are challenging to produce due to the small-holder dominant agricultural systems like those found in most of Africa and Asia. Cloud-based Geospatial computing platforms and multi-date, multi-sensor satellite image inventories on Google Earth Engine offer opportunities for mapping croplands with precision and accuracy over large areas that satisfy the requirements of broad range of applications. Such maps are expected to provide highly significant improvements compared to existing products, which tend to be coarser in resolution, and often fail to capture fragmented small-holder farms especially in regions with high dynamic change within and across years. To overcome these limitations, in this research we present an approach for cropland extent mapping at high spatial resolution (30-m or better) using the 10-day, 10 to 20-m, Sentinel-2 data in combination with 16-day, 30-m, Landsat-8 data on Google Earth Engine (GEE). First, nominal 30-m resolution satellite imagery composites were created from 36,924 scenes of Sentinel-2 and Landsat-8 images for the entire African continent in 2015-2016. These composites were generated using a median-mosaic of five bands (blue, green, red, near-infrared, NDVI) during each of the two periods (period 1: January-June 2016 and period 2: July-December 2015) plus a 30-m slope layer derived from the Shuttle Radar Topographic Mission (SRTM) elevation dataset. Second, we selected Cropland/Non-cropland training samples (sample size 9791) from various sources in GEE to create pixel-based classifications. As supervised classification algorithm, Random Forest (RF) was used as the primary classifier because of its efficiency, and when over-fitting issues of RF happened due to the noise of input training data, Support Vector Machine (SVM) was applied to compensate for such defects in specific areas. Third, the Recursive Hierarchical Segmentation (RHSeg) algorithm was employed to generate an object-oriented segmentation layer based on spectral and spatial properties from the same input data. This layer was merged with the pixel-based classification to improve segmentation accuracy. Accuracies of the merged 30-m crop extent product were computed using an error matrix approach in which 1754 independent validation samples were used. In addition, a comparison was performed with other available cropland maps as well as with LULC maps to show spatial similarity. Finally, the cropland area results derived from the map were compared with UN FAO statistics. The independent accuracy assessment showed a weighted overall accuracy of 94, with a producers accuracy of 85.9 (or omission error of 14.1), and users accuracy of 68.5 (commission error of 31.5) for the cropland class. The total net cropland area (TNCA) of Africa was estimated as 313 Mha for the nominal year 2015.