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.
A methodology for specifying the radiometric requirements for ocean color remote sensing systems is described. Consideration is given to the noise equivalent radiance, the saturation radiance, the polarization sensitivity, and the calibration and stability. The degree of polarization across a scan line for the CZCS and MODIS orbits is presented.
Significant progress has been made in the application of microwave remote sensing for measuring soil moisture. Both passive and active systems have demonstrated the capability for measuring soil moisture. However, several questions are still unresolved regarding the optimal instrument configuration and other target characteristics, such as roughness and vegetation. In addition, the most likely disciplines for using these data, agriculture and hydrology, do not currently possess adequate models or procedures for using these new data.
We have constructed a novel instrument for ground-based remote sensing, by mounting a UV-visible spectrometer on a telescope and observing the absorption by atmospheric constituents of light from stars. Potentially, the instrument can observe stratospheric O3, NO3, NO2, and OClO.
Thermal remote sensing instruments can function as environmental measuring tools, with capabilities leading toward new directions in functional landscape ecology. Theoretical deduction and phenomenological observation leads us to believe that the second law of thermodynamics requires that all dynamically systems develop in a manner which dissipates gradients as rapidly as possible within the constraints of the system at hand. The ramification of this requirement is that dynamical systems will evolve dissipative structures which grow and complexify over time. This perspective has allowed us to develop a framework for discussing ecosystem development and integrity. In the context of this framework we have developed measures of development and integrity for ecosystems. One set of these measures is based on destruction of the exergy content of incoming solar energy. More developed ecosystems will be more effective at dissipating the solar gradient (destroying its exergy content). This can be measured by the effective surface temperature of the ecosystem on a landscape scale. These surface temperatures are measured using airborne thermal scanners such as the Thermal Infrared Multispectral Scanner (TIMS) and the Airborne Thermal/Visible Land Application Sensor(ATLAS) sensors. An analysis of agriculture and forest ecosystems will be used to illustrate the concept of ecological thermodynamics and the development of ecosystems.
The effect of Faraday rotation on the remote sensing of soil moisture from space is investigated using the International Reference Ionosphere (IRI) to obtain electron density profiles and the International Geomagnetic Reference Field (IGRF) to model the magnetic field. With a judicious choice of satellite orbit (6 am, sunsynchronous) the errors caused by ignoring Faraday rotation are less than 1 K at incidence angles less than 40 degrees.
An assessment of the volume, composition, and duration of mare volcanism using remotely sensed data and how these factors are controlled by the distribution of heat producing elements.
This paper presents results of a project to port code for processing remotely sensed data from the UNIX environment to Windows. Factors considered during this process include time schedule, cost, resource availability, reuse of existing code, rapid interface development, ease of integration, and platform independence. The approach selected for this project used both Java and C. By using Java for the graphical user interface and C for the domain model, the strengths of both languages were utilized and the resulting code can easily be ported to other platforms. The advantages of this approach are discussed in this paper.
We review integrated photonics technology and the applications for space-based remote-sensing. We cover the state of the technology and its advantages in a variety of sensing applications, discussing some active programs implementing integrated photonic solutions and showing the potential for improved systems performance.
The overall objectives and strategies of the Center for Remote Sensing remain to provide a center for excellence for multidisciplinary scientific expertise to address land-related global habitability and earth observing systems scientific issues. Specific research projects that were underway during the final contract period include: digital classification of coniferous forest types in Michigan's northern lower peninsula; a physiographic ecosystem approach to remote classification and mapping; land surface change detection and inventory; analysis of radiant temperature data; and development of methodologies to assess possible impacts of man's changes of land surface on meteorological parameters. Significant progress in each of the five project areas has occurred. Summaries on each of the projects are provided.
The radiative transfer model (RTM) has a wide range of applications in satellite remote sensing and atmospheric radiation studies. For example, it can be used as a forward model for an inversion algorithm and a satellite data assimilation system, or as a L1 data simulator for pre-launch end-to-end satellite sensor performance studies. However, millions of line-by-line (LBL) radiative transfer calculations at fine monochromatic frequencies are needed in order to properly calculate spectral contributions of water vapor and trace gases in the atmosphere in infrared and solar spectral regions. Therefore, fast, and accurate radiative transfer models are needed. A Principal Component-based radiative transfer model (PCRTM) was developed at NASA Langley to fulfil this need. The PCRTM can simulate the top-of-atmosphere (TOA) radiance or reflectance spectra from 250 nm to 2000 micrometers with several orders of magnitude faster speed as compared to a LBL RTM. It is also extremely accurate compared to LBL RTM benchmarks. The PCRTM model has been developed for hyperspectral sensors such as AIRS, CrIS, IASI, NAST-I, SHIS, CPF, TEMPO, EMIT, OMI, and SCIAMACHY. By using the PCRTM as forward model for an inversion algorithm, one can reduce the data dimension significantly while maintaining original information content by compressing the TOA radiance spectrum into PC-scores. The PCRTM can directly compute the PC-scores and their derivatives with respect to retrieved parameters. Examples of using various PCRTM inversion algorithms to retrieve atmospheric temperature, water vapor, and trace gas profiles, as well as cloud and surface properties from satellite hyperspectral remote sensors will be given. Some of the algorithms have been transitioned to NASA's Goddard Earth Sciences Data and Information Services Center (GES DISC) for public access of high-quality L2 and L3 data.
Cyanobacterial blooms can have negative effects on human health and local ecosystems. Field monitoring of cyanobacterial blooms can be costly, but satellite remote sensing has shown utility for more efficient spatial and temporal monitoring across the United States. Here, satellite imagery was used to assess the annual frequency of surface cyanobacterial blooms, defined for each satellite pixel as the percentage of images for that pixel throughout the year exhibiting detectable cyanobacteria. Cyanobacterial frequency was assessed across 2,196 large lakes in 46 states across the continental United States (CONUS) using imagery from the European Space Agency’s Ocean and Land Colour Imager for the years 2017 through 2019. In 2019, across all satellite pixels considered, annual bloom frequency had a median value of 4% and a maximum value of 100%, the latter indicating that for those satellite pixels, a cyanobacterial bloom was detected by the satellite sensor for every satellite image considered. In addition to annual pixel-scale cyanobacterial frequency, results were summarized at the lake- and state-scales by averaging annual pixel-scale results across each lake and state. For 2019, average annual lake-scale frequencies also had a maximum value of 100%, and Oregon and Ohio had the highest average annual state-scale frequencies at 65% and 52%. Pixel-scale frequency results can assist in identifying portions of a lake that are more prone to cyanobacterial blooms, while lake- and state-scale frequency results can assist in the prioritization of sampling resources and mitigation efforts. Satellite imagery is limited by the presence of snow and ice, as imagery collected in these conditions are quality flagged and discarded. Thus, annual bloom frequencies within nine climate regions were investigated to determine whether missing data biased results in climate regions more prone to snow and ice, given that their annual summaries would be weighted toward the summer months when cyanobacterial blooms tend to occur. Results were unbiased by the time period selected in most climate regions, but a large bias was observed for the Northwest Rockies and Plains climate region. Moderate biases were observed for the Ohio Valley and the Southeast climate regions. Finally, a clustering analysis was used to identify areas of high and low cyanobacterial frequency across CONUS based on average annual lake-scale cyanobacterial frequencies for 2019. Several clusters were identified that transcended state, watershed, and eco-regional boundaries. Combined with additional data, results from the clustering analysis may offer insight regarding large-scale drivers of cyanobacterial blooms.
In this presentation, we apply the adjoint sensitivity analysis of radiative transfer in thermal IR to the general case of the analytic evaluation of the weighting functions of atmospheric parameters together with the partial derivatives for the surface parameters. Applications to remote sensing of atmospheres of Mars and Venus are discussed.
Terrestrial test sites and aircraft flights used in preparing for remote sensing from Earth orbital spacecraft
Atmospheric limitations on remote sensing of sea surface roughness by reflected daylight
ERTS-1 remote sensing to aid resources management in Republic of Mali
Research performed on NASA and USDA remote sensing projects are reviewed and include: (1) the 1971 Corn Blight Watch Experiment; (2) crop identification; (3) soil mapping; (4) land use inventories; (5) geologic mapping; and (6) forest and water resources data collection. The extent to which ERTS images and airborne data were used is indicated along with computer implementation. A field and laboratory spectroradiometer system is described together with the LARSYS software system, both of which were widely used during the research. Abstracts are included of 160 technical reports published as a result of the work.
Information is provided on how a potential user of remote sensing technology can gain access to all of the products and services he will need to get started. It was envisioned that these include data, training, hardware, and software. A very brief tutorial summary of the fundamentals of the technology is presented.
Results from quantitative analysis show that airplane remotely sensed spectral data can be used to quantify and map an acid-waste dump in terms of its particulate iron concentration. These same data, however, could not be used to map the dump in terms of total suspended solids, organic suspended solids, or inorganic suspended solids concentrations. A single-variable equation using the ratio of band 2 (440 to 490 nm) radiance to band 4 (540 to 580 nm) radiance was used to quantify the iron concentration in the acid-waste dump. The acid waste that was mapped varied in age from freshly dumped to 31/2 hr. Particulate iron concentrations in the acid waste were estimated to range up to 1.1 mg/l at a depth of 0.46 m. A classification technique was developed to identify pixels in the data set affected by sun glitter.