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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Night-time observations of snow using visible imagery

Consideration is given to the possibility of increasing the frequency of satellite snow cover observations in the visible range by using the light reflected off the moon as an illumination source for nighttime observations. Images obtained at night by DMSP satellites orbiting in the noon-midnight plane are presented which were obtained at various phases of the moon. It is concluded that DMSP visible imagery can be used to detect snow cover during those periods when the moon is over the local horizon and is between the first quarter phase and the last quarter phase, which amounts to around five additional days a month allowing for cloud cover. The high frequency of observation of a given area provided by a light-sensitivity imager would be an important feature of a dedicated water-resources satellite.

Foster, J. L.↗
NASA NTRS1997

Comparison of registration techniques for GOES visible imagery data

This paper briefly describes and then compares the effectiveness of five image registration approaches for GOES visible band imagery. The techniques compared are (1) NOAA "point" manual landmarking, (2) manual landmarking on extant feature (whole island, lake, etc.), (3) automatic phase correlation, (4) automatic spatial correlation on edge features, and (5) automatic spatial correlation of region boundaries derived from image segmentation.

Tilton, James C.↗
NASA NTRS1983

Observations of the earth using nighttime visible imagery

The earth as viewed from space in visible light at night reveals some features not easily discernible during the day such as aurora, forest fires, city lights and gas flares. In addition, those features having a high albedo such as snow and ice can be identified on many moonlit nights nearly as well as they can in sunlight. The Air Force DMSP satellites have been operating in the visible wavelengths at night since the mid 1960s. Most all other satellites having optical sensors are incapable of imaging at night. Imaging systems having improved light sensitivity in the visible portion of the spectrum should be considered when planning future earth resources satellite missions in order to utilize nighttime as well as daytime visual observations.

Foster, J. L.↗
NASA NTRS1983

Remote assessment of ocean color for interpretation of satellite visible imagery: A review

An assessment is presented of the state-of-the-art of remote, (satellite-based) Coastal Zone Color (CZCS) Scanning of color variations in the ocean due to phytoplankton. Attention is given to physical problems associated with ocean color remote sensing, in-water algorithms for the correction of atmospheric effects, constituent retrieval algorithms and application of the algorithms to CZCS imagery. The applicability of CZCS to both near-coast and mid-ocean waters is considered, and it is concluded that while differences between the two environments are complex, universal algorithms can be used for the case of mid-ocean waters, and site-specific algorithms are adequate for CZCS imaging of the near-coast oceanic environment. A short description of CVCS and some sample photographs are provided in an appendix.

Gordon, H. R.↗
NASA NTRS1988

Ice sheet studies using synthetic aperture radar

The objective was to demonstrate the utility of synthetic aperture radar in ice sheet studies. The major advantage of SAR imagery over visible imagery is the all-weather capability of radar and the ability to specify look angle. Available digital SAR imagery over ice sheets was collected and examined both qualitatively and quantitatively using corroborative data, such as LANDSAT imagery, to confirm feature identification and interpretations. A simple scattering model will be developed to assess the relative importance of surface topography, composition, and subsurface layering to the intensity of radar backscatter. Recommendations of system parameters will be made for optimal SAR operation over ice sheets.

Bindschadler, R.↗
NASA NTRS2003

NASA's Earth Observatory and Visible Earth: Imagery and Science on the Internet

The purpose of NASA s Earth Observatory and Visible Earth Web sites is to provide freely-accessible locations on the Internet where the public can obtain new satellite imagery (at resolutions up to a given sensor's maximum) and scientific information about our home planet. Climatic and environmental change are the sites main foci. As such, they both contain ample data visualizations and time-series animations that demonstrate geophysical parameters of particular scientific interest, with emphasis on how and why they vary over time. An Image Composite Editor (ICE) tool will be added to the Earth Observatory in October 2002 that will allow visitors to conduct basic analyses of available image data. For example, users may produce scatter plots to correlate images; or they may probe images to find the precise unit values per pixel of a given data product; or they may build their own true-color and false-color images using multi- spectral data. In particular, the sites are designed to be useful to the science community, public media, educators, and students.

King, Michael D.↗
NASA NTRS2010

Multi-Sensor Mud Detection

Robust mud detection is a critical perception requirement for Unmanned Ground Vehicle (UGV) autonomous offroad navigation. A military UGV stuck in a mud body during a mission may have to be sacrificed or rescued, both of which are unattractive options. There are several characteristics of mud that may be detectable with appropriate UGV-mounted sensors. For example, mud only occurs on the ground surface, is cooler than surrounding dry soil during the daytime under nominal weather conditions, is generally darker than surrounding dry soil in visible imagery, and is highly polarized. However, none of these cues are definitive on their own. Dry soil also occurs on the ground surface, shadows, snow, ice, and water can also be cooler than surrounding dry soil, shadows are also darker than surrounding dry soil in visible imagery, and cars, water, and some vegetation are also highly polarized. Shadows, snow, ice, water, cars, and vegetation can all be disambiguated from mud by using a suite of sensors that span multiple bands in the electromagnetic spectrum. Because there are military operations when it is imperative for UGV's to operate without emitting strong, detectable electromagnetic signals, passive sensors are desirable. JPL has developed a daytime mud detection capability using multiple passive imaging sensors. Cues for mud from multiple passive imaging sensors are fused into a single mud detection image using a rule base, and the resultant mud detection is localized in a terrain map using range data generated from a stereo pair of color cameras.

Rankin, Arturo L.↗
NASA NTRS1981

The application of Heat Capacity Mapping Mission (HCMM) thermal data to snow hydrology

The application of HCMM thermal infrared data to snow hydrology and the prediction of snowmelt runoff was evaluated. Data for the Salt Verde watershed in central Arizona and the southern Sierra Nevada in California were analyzed and compared to LANDSAT and NOAA satellite data, U-2 thermal data, and other correlative data. It was determined that HCMM thermal imagery provides data as accurate for snow mapping as does visible imagery, and that in comparison with the reslution of other satellite imagery, it may be the most useful. Data from the HCMM thermal channel, with careful calibration, provides useful snow surface temperature data for hydrological purposes. An approach to an automated method of analysis is presented.

Barnes, J. C.↗
NASA NTRS2017

Estimating the Relative Water Content of Leaves in a Cotton Canopy

Remotely sensing plant canopy water status remains a long-term goal of remote sensing research. Established approaches to estimating canopy water status the Crop Water Stress Index, the Water Deficit Index and the Equivalent Water Thickness involve measurements in the thermal or reflective infrared. Here we report plant water status estimates based upon analysis of polarized visible imagery of a cotton canopy measured by ground Multi-Spectral Polarization Imager (MSPI). Such estimators potentially provide access to the plant hydrological photochemistry that manifests scattering and absorption effects in the visible spectral region.Twice during one day, +- 3 hours from solar noon, we collected polarized imagery and relative water content data on a cotton test plot located at the Arid Land Agricultural Research Center, United States Department of Agriculture, Maricopa, AZ. The test plot, a small portion of a large cotton field, contained stressed plants ready for irrigation. The evening prior to data collection we irrigated several rows of plants within the test plot. Thus, ground MSPI imagery from both morning and afternoon included cotton plants with a range of water statuses. Data analysis includes classifying the polarized imagery into sunlit reflecting, sunlit transmitting, shaded foliage and bare soil. We estimate the leaf surface reflection and interior reflection based upon the per pixel polarization and sunview directions. We compare our cotton results with our prior polarization results for corn and soybean leaves measured in the lab and corn leaves measured in the field.

Cotton Canopy↗
NASA NTRS2014

Sport Transition of JPSS VIIRS Imagery for Night-time Applications

The NASA/Short‐term Prediction, Research, and Transition (SPoRT) Program and NOAA/Cooperative Institute for Research in the Atmosphere (CIRA) work within the NOAA/Joint Polar Satellite System (JPSS) Proving Ground to demonstrate the unique capabilities of the VIIRS instrument. Very similar to MODIS, the VIIRS instrument provides many high‐resolution visible and infrared channels in a broad spectrum. In addition, VIIRS is equipped with a low‐light sensor that is able to detect light emissions from the land and atmosphere as well as reflected sunlight by the lunar surface. This band is referred to as the Day‐Night Band due to the sunlight being used at night to see cloud and topographic features just as one would typically see in day‐time visible imagery. NWS forecast offices that collaborate with SPoRT and CIRA have utilized MODIS imagery in operations, but have longed for more frequent passes of polar‐orbiting data. The VIIRS instrument enhances SPoRT collaborations with WFOs by providing another day and night‐time pass, and at times two additional passes due to its large swath width. This means that multi‐spectral, RGB imagery composites are more readily available to prepare users for their use in GOES‐R era and high‐resolution imagery for use in high‐latitudes is more frequently able to supplement standard GOES imagery within the SPoRT Hybrid GEO‐LEO product. The transition of VIIRS also introduces the new Day‐Night Band capability to forecast operations. An Intensive Evaluation Period (IEP) was conducted in Summer 2013 with a group of "Front Range" NWS offices related to VIIRS night‐time imagery. VIIRS single‐channel imagery is able to better analyze the specific location of fire hotspots and other land features, as well as provide a more true measurement of various cloud and aerosol properties than geostationary measurements, especially at night. Viewed within the SPoRT Hybrid imagery, the VIIRS data allows forecasters to better interpret the more frequent, but coarse GOES Imagery. Night‐time Microphysics and Dust RGB Imagery provides cloud analysis of cloud height, thickness, and composition in order for operational applications such as separating fog from low clouds, dust plume detection, and determining precipitating clouds in radar-void/ blocked regions. The Day‐Night Band has a particular benefit to seeing light from cities, fires, or other emissions as well as the reflection of moonlight off of clouds and smoke plumes, given the right lunar phase and angle. Examples from the VIIRS transition and IEP will be presented.

Fuell, Kevin↗
NASA NTRS1979

Quadratic image destriping

An algorithm for removing second-order detector banding effects (striping) from digital imagery is described. This quadratic destriping method is basically an extension of a linear method to one higher degree. It provides a nonlinear alternative between the two-parameter linear correction and a multilinear histogram equalization approach. The application of the proposed technique to GOES visible imagery is discussed, and its effectiveness is compared to existing methods.

Dalton, J. T.↗
NASA NTRS1984

Variations in surface current off the coasts of Canada as inferred from infrared satellite imagery

Infrared satellite images of sea surface temperature are used to infer changes in the surface currents off both the east and west coasts of Canada. Off the east coast, summer infrared temperature patterns suggest a close connection between the location of the continental slope and the path of the Labrador Current as marked by a strong change in the shape of the continental slope. In winter both infrared and visible imagery reveal the southward propagation of wavelike features in the ice patterns along the Labrador coast. A large number of images from the Canadian west coast were used to depict the evolution of surface temperature features. In winter and spring 150 km current meanders are fed energy by the baroclinic instability of the uniformly directed current which flows northwest in winter and southeast in spring. In summer the surface current is directed southeastward while below it an undercurrent flows to the northeast. Initiated by an interaction with the irregularities of the local continental slope 75 km current meanders begin to form. Energy is then fed non-linearly by baroclinic instability into longer scale 150 km meander which eventually shed to form separate eddies.

Emery, W. J.↗
NASA NTRS1983

The inference of tropical cyclone dynamics using GOES VISSR/VAS data

The sequence of events observed during tropical cyclone Emily, was suggested as a possible mechanism for cyclogenesis. Geostationary Operational Environmental Satellite (GOES) East VISSR/VAS sensors were used. The VISSR visible imagery obtained every 15 minutes was used to define the low tropospheric cyclonic vortex and upper tropospheric horizontal convergence. The VAS water vapor (channels 9 and 10) and carbon dioxide (channels 3 and 4) channels were used to infer upper and middle tropospheric subsidence by monitoring the Adiabatic compressional drying and warming, respectively, occurring within this layer. Evidence of an existing lower tropospheric cyclonic vortex was seen. The satellite derived wind vectors (length of vector is proportional to wind velocity, where the strongest winds were approximately 35 knots) are superimposed on the GOES visible image of tropical storm Emily. Vectors and low level clouds depict the center of the cyclonic vortex immediately south of the large convective cell in the center of the image. Upper tropospheric cloud tracers and rawinsonde reports along the Eastern United States suggest that the southwesterly environmental upper atmospheric flow is converging with the outflow from the convective cell north of the vortex.

Rodgers, E. B.↗
NASA NTRS1976

Advanced atmospheric sounder and imaging radiometer /AASIR/ for STORMSAT

The principal mission of the three-axis stabilized STORMSAT spacecraft is to provide the necessary meteorological data for tracking, studying the detailed structure, and modeling mesoscale weather phenomena. In the area of mesoscale events, the following meteorological objectives are indicated: high-quality imagery, visible and infrared; wind velocity from cloud tracers (1 m/sec), atmospheric temperature profiles (1 K), and atmospheric humidity sounding. These objectives are reflected in the functional characteristics of the AASIR, which is a second generation meteorological sensor based on the Visible Infrared Spin-Scan Radiometer (VISSR) and the Atmospheric Sounder (VAS). The AASIR design and interface constraints with the STORMSAT spacecraft is discussed.

Chase, S. C.↗
NASA NTRS1978

Remote sensing of the atmosphere from environmental satellites

The paper outlines the basis of remote sensing in satellite meteorology, the evolution of remote sensors, examples of practical applications, and a prospectus of future developments. The meteorological satellites use instrumentation sensitive to different regions of the electromagnetic spectrum to observe and measure atmospheric and surface properties. In the ultraviolet, solar variability is measured and total atmospheric ozone determined. In the visible, imagery of cloud systems provides better location of storms in data-sparse areas, observes ice and snow boundaries, and monitors floods. Capabilities of microwave imagery are discussed along with successful uses of geosynchronous satellites. Future environmental satellite programs are discussed in some detail, including GARP, TIROS-N and CLIMSAT.

Allison, L. J.↗
NASA NTRS1979

Remote sensing of snow and ice

This paper reviews remote sensing of snow and ice, techniques for improved monitoring, and incorporation of the new data into forecasting and management systems. The snowcover interpretation of visible and infrared data from satellites, automated digital methods, radiative transfer modeling to calculate the solar reflectance of snow, and models using snowcover input data and elevation zones for calculating snowmelt are discussed. The use of visible and near infrared techniques for inferring snow properties, microwave monitoring of snowpack characteristics, use of Landsat images for collecting glacier data, monitoring of river ice with visible imagery from NOAA satellites, use of sequential imagery for tracking ice flow movement, and microwave studies of sea ice are described. Applications of snow and ice research to commercial use are examined, and it is concluded that a major problem to be solved is characterization of snow and ice in nature, since assigning of the correct properties to a real system to be modeled has been difficult.

Rango, A.↗
NASA NTRS1981

An Automated Technique for Estimating Daily Precipitation over the State of Virginia

Digital IR and visible imagery obtained from a geostationary satellite located over the equator at 75 deg west latitude were provided by NASA and used to obtain a linear relationship between cloud top temperature and hourly precipitation. Two computer programs written in FORTRAN were used. The first program computes the satellite estimate field from the hourly digital IR imagery. The second program computes the final estimate for the entire state area by comparing five preliminary estimates of 24 hour precipitation with control raingage readings and determining which of the five methods gives the best estimate for the day. The final estimate is then produced by incorporating control gage readings into the winning method. In presenting reliable precipitation estimates for every cell in Virginia in near real time on a daily on going basis, the techniques require on the order of 125 to 150 daily gage readings by dependable, highly motivated observers distributed as uniformly as feasible across the state.

Follansbee, W. A.↗