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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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NASA NTRS2007

Ultra-Wideband Radar Measurements of Thickness of Snow Over Sea Ice

An accurate knowledge of snow thickness and its variability over sea ice is crucial for determining the overall polar heat and freshwater budget, which influences the global climate. Recently, algorithms have been developed to extract snow thicknesses from passive microwave satellite data. However, validation of these data over the large footprint of the passive microwave sensor has been a challenge. The only method used thus far has been with meter sticks during ship cruises. To address this problem, we developed an ultra wideband frequency-modulated continuous-wave (FM-CW) radar to measure snow thickness over sea ice. We made snow-thickness measurements over Antarctic sea ice by operating the radar from a sled during September and October, 2003. We performed radar measurements over 11 stations with varying snow thickness between 4 and 85 cm. We observed excellent agreement between radar estimates of snow thickness with physical measurements, achieving a correlation coefficient of 0.95 and a vertical resolution of about 3 cm.

Kanagaratnam, P.↗

NASA NTRS1992

Supervised fully polarimetric classification of the Black Forest test site: From MAESTROI to MAC Europe

A study on the performance of a supervised fully polarimetric maximum likelihood classifier for synthetic aperture radar (SAR) data when applied to a specific classification context: forest classification based on age classes and in the presence of a sloping terrain is presented. For the experimental part, the polarimetric AIRSAR data at P, L, and C-band, acquired over the German Black Forest near Freiburg in the frame of the 1989 MAESTRO-1 campaign and the 1991 MAC Europe campaign was used, MAESTRO-1 with an ESA/JRC sponsored campaign, and MAC Europe (Multi-sensor Aircraft Campaign); in both cases the multi-frequency polarimetric JPL Airborne Synthetic Aperture Radar (AIRSAR) radar was flown over a number of European test sites. The study is structured as follows. At first, the general characteristics of the classifier and the dependencies from some parameters, like frequency bands, feature vector, calibration, using test areas lying on a flat terrain are investigated. Once it is determined the optimal conditions for the classifier performance, we then move on to the study of the slope effect. The bulk of this work is performed using the Maestrol data set. Next the classifier performance with the MAC Europe data is considered. The study is divided into two stages: first some of the tests done on the Maestro data are repeated, to highlight the improvements due to the new processing scheme that delivers 16 look data. Second we experiment with multi images classification with two goals: to assess the possibility of using a training set measured from one image to classify areas in different images; and to classify areas on critical slopes using different viewing angles. The main points of the study are listed and some of the results obtained so far are highlighted.

Degrandi, G.↗

DOE OSTI2018

VMD fused radar--a hyper-volumetric ultra-low NAR sensor system

A system or method for a physical intrusion detection and assessment system is provided for determining a deliberate motion intrusion. The system includes first and second sensing device to sense physical data set within a predetermined space. A transducer module receives the first sensor physical data set and the second sensor physical data set and converts the first and second physical data sets into analog signals representative of the first and second physical data sets. A signal conditioning layer converts the first and second physical data analog signals to digital signals. A processor device correlates the first physical data set and the second physical data set and generates an alarm in response to identification of an intrusion in the space. A method and algorithms are applied to the data sets for determining whether a detected intrusion is associated with deliberate motion rather than random motion.

42 ENGINEERING↗

NASA NTRS2019

Validation of ICESat-2 ATLAS Bathymetry and Analysis of ATLAS’s Bathymetric Mapping Performance

NASA’s Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) was launched in September, 2018. The satellite carries a single instrument, ATLAS (Advanced Topographic Laser Altimeter System), a green wavelength, photon-counting lidar, enabling global measurement and monitoring of elevation with a primary focus on the cryosphere. Although bathymetric mapping was not one of the design goals for ATLAS, pre-launch work by our research team showed the potential to map bathymetry with ICESat-2, using data from MABEL (Multiple Altimeter Beam Experimental Lidar), NASA’s high-altitude airborne ATLAS emulator, and adapting the laser-radar equation for ATLAS specific parameters. However, many of the sensor variables were only approximations, which limited a full assessment of the bathymetric mapping capabilities of ICESat-2 during pre-launch studies. Following the successful launch, preliminary analyses of the geolocated photon returns have been conducted for a number of coastal sites, revealing several salient examples of seafloor detection in water depths of up to ~40 m. The geolocated seafloor photon returns cannot be taken as bathymetric measurements, however, since the algorithm used to generate them is not designed to account for the refraction that occurs at the air–water interface or the corresponding change in the speed of light in the water column. This paper presents the first early on-orbit validation of ICESat-2 bathymetry and quantification of the bathymetric mapping performance of ATLAS using data acquired over St. Thomas, U.S. Virgin Islands. A refraction correction, developed and tested in this work, is applied, after which the ICESat-2 bathymetry is compared against high-accuracy airborne topo-bathymetric lidar reference data collected by the U.S. Geological Survey (USGS) and the National Oceanic and Atmospheric Administration (NOAA). The results show agreement to within 0.43—0.60 m root mean square error (RMSE) over 1 m grid resolution for these early on-orbit data. Refraction-corrected bottom return photons are then inspected for four coastal locations around the globe in relation to Visible Infrared Imaging Radiometer Suite (VIIRS) K(d)(490) data to empirically determine the maximum depth mapping capability of ATLAS as a function of water clarity. It is demonstrated that ATLAS has a maximum depth mapping capability of nearly 1 Secchi in depth for water depths up to 38 m and K(d)(490) in the range of 0.05–0.12 per m. Collectively, these results indicate the great potential for bathymetric mapping with ICESat-2, offering a promising new tool to assist in filling the global void in nearshore bathymetry.

ICESat-2↗

NASA NTRS1975

A multisensor analysis of Nimbus-5 data recorded on 22 January 1973

The Nimbus 5 meteorological satellite has a full complement of radiation sensors. Data from these sensors were analyzed and intercompared for orbits 569 and 570. The electrically-scanning microwave radiometer (19.35-GHz region) delineated rain areas over the ocean off the U.S. east coast, in good agreement with radar imagery, and permitted the estimation of rainfall rates in this region. Residual ground water, from abnormal rainfall in the lower Mississippi Valley, was indicated under clear sky conditions by soil brightness temperature values in the Nimbus 5 electrically scanning microwave radiometer and U.S. Air Force Data Acquisition and Processing Program infrared data. The temperature-humidity infrared radiometer (6.7 micron and 11 micron) showed the height and spatial configuration of frontal clouds along the east coast and outlined the confluence of a polar jet stream with a broad subtropical jet stream along the U.S. Gulf Coast. Temperature profiles from three vertical temperature sounders are found to be in good agreement with related radiosonde ascents along orbit 569 from the subtropics to the Arctic Circle.

Allison, L. J.↗

NASA NTRS1993

Geographic information system for fusion and analysis of high-resolution remote sensing and ground data

We seek to combine high-resolution remotely sensed data with models and ground truth measurements, in the context of a Geographical Information System (GIS), integrated with specialized image processing software. We will use this integrated system to analyze the data from two Case Studies, one at a boreal forest site, the other a tropical forest site. We will assess the information content of the different components of the data, determine the optimum data combinations to study biogeophysical changes in the forest, assess the best way to visualize the results, and validate the models for the forest response to different radar wavelengths/polarizations. During the 1990's, unprecedented amounts of high-resolution images from space of the Earth's surface will become available to the applications scientist from the LANDSAT/TM series, European and Japanese ERS-1 satellites, RADARSAT and SIR-C missions. When the Earth Observation Systems (EOS) program is operational, the amount of data available for a particular site can only increase. The interdisciplinary scientist, seeking to use data from various sensors to study his site of interest, may be faced with massive difficulties in manipulating such large data sets, assessing their information content, determining the optimum combinations of data to study a particular parameter, visualizing his results and validating his model of the surface. The techniques to deal with these problems are also needed to support the analysis of data from NASA's current program of Multi-sensor Airborne Campaigns, which will also generate large volumes of data. In the Case Studies outlined in this proposal, we will have somewhat unique data sets. For the Bonanza Creek Experimental Forest (Case 1) calibrated DC-8 SAR (Synthetic Aperture Radar) data and extensive ground truth measurement are already at our disposal. The data set shows documented evidence to temporal change. The Belize Forest Experiment (Case 2) will produce calibrated DC-8 SAR and AVIRIS data, together with extensive measurements on the tropical rain forest itself. The extreme range of these sites, one an Arctic forest, the other a tropical rain forest, has been deliberately chosen to find common problems which can lead to generalized observations and unique problems with data which raise issues for the EOS System.

Freeman, Anthony↗

NASA NTRS2002

Detecting ocean surface wind using the TRMM precipitation radar

Although designed specifically for the measurement of precipitation in the atmosphere, the Precipitation Radar (PR) onboard the Tropical Rainfall Measuring Mission (TRMM) satellite alsomeasures the normalized radar cross-section at the Earth's surface. As such, this instrument providesan interesting opportunity to explore an alternative radar configuration in the satellite remote sensingnf ocean winds. In particular, it can measure the strength of the ocean winds in relatively higherspatial resolution as compared to the conventional scatterometer systems presently in use. The addition of wind sensing capability to precipitation radar also complements its rain profiling capabilitynicely and allows coincident wind and rain measurements. In this paper, we discuss the new ocean wind algorithm developed specifically for TRMM PR using maximum likelihood estimation. A uniquefeature of this wind algorithm is its capability to incorporate measurement sensitivity and noiseinformation consistently in both the along-track and cross-track directions. This PR wind algorithm hasbeen tested using data from the TRMM Microwave Imager (TMI) and NASA QuikSCAT scatterometer.Excellent agreement on the retrieved wind strengths is achieved among three sensors.

precipitation radar TRMM GPM CAMEX-4 ocean surface↗

NASA NTRS1996

Deforestation and Secondary Growth in Rondonia, Brazil from SIR-C SAR and Landsat.SPOT data

Covers problems with existing data collected with high-resolution optical sensors. They say active microwave sensors could complement other sensors in getting through things like cloud cover. They analyzed SIR-C data in combination with Landsat TM data, a 9-year time series of SPOT XS data, and a preliminary field survey. They report findings and draw conclusions, including that SARs operating at long radar wavelengths, with both like and cross-polarizations, are needed for tropical deforestation studies.

high-resolution optical sensors SIR-C SAR SPOT↗

NASA NTRS2011

Daily MODIS Data Trends of Hurricane-Induced Forest Impact and Early Recovery

We studied the use of daily satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors to assess wetland forest damage and recovery from Hurricane Katrina (29 August 2005 landfall). Processed MODIS daily vegetation index (VI) trends were consistent with previously determined impact and recovery patterns provided by the "snapshot" 25 m Landsat Thematic Mapper optical and RADARSAT-1 synthetic aperture radar satellite data. Phenological trends showed high 2004 and 2005 pre-hurricane temporal correspondence within bottomland hardwood forest communities, except during spring green-up, and temporal dissimilarity between these hardwoods and nearby cypress-tupelo swamp forests (Taxodium distichum [baldcypress] and Nyssa aquatica [water tupelo]). MODIS VI trend analyses established that one year after impact, cypress-tupelo and lightly impacted hardwood forests had recovered to near prehurricane conditions. In contrast, canopy recovery lagged in the moderately and severely damaged hardwood forests, possibly reflecting regeneration of pre-hurricane species and stand-level replacement by invasive trees.

Ramsey, Elijah, III↗

NASA NTRSDate not supplied

Developing the CRTM Active Sensor Module

Active sensors provide vertically resolved atmospheric and cloud information, however the assimilation of such observations into NWP models has been limited for several reasons including lack of reliable forward model. We present the development of CRTM active sensor module including its adjoint and tangent linear by taking advantage of current CRTM modules for calculating atmospheric transmittance and cloud absorption and scattering. Current CRTM cloud coefficients lack cloud backscattering information, thus we have implemented a new cloud scattering database generated using the discrete dipole technique that include backscattering coefficients. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.

CRTM↗

NASA NTRS1981

Method of interpretation of remotely sensed data and applications to land use

Instructional material describing a methodology of remote sensing data interpretation and examples of applicatons to land use survey are presented. The image interpretation elements are discussed for different types of sensor systems: aerial photographs, radar, and MSS/LANDSAT. Visual and automatic LANDSAT image interpretation is emphasized.

Parada, N. D. J.↗

NASA NTRS1991

Fourth Airborne Geoscience Workshop

The focus of the workshop was on how the airborne community can assist in achieving the goals of the Global Change Research Program. The many activities that employ airborne platforms and sensors were discussed: platforms and instrument development; airborne oceanography; lidar research; SAR measurements; Doppler radar; laser measurements; cloud physics; airborne experiments; airborne microwave measurements; and airborne data collection.

Source record↗

NASA NTRS2017

Active and Passive 3D Vector Radiative Transfer with Preferentially-Aligned Ice Particles

For the purposes of interpreting active (radar) and passive (radiometer) microwave and millimeter wave remote sensing data, we have constructed a consistent radiative transfer modeling framework to simulate the responses for arbitrary sensors with differing sensing geometries and hardware configurations. As part of this work, we have implemented a recent method for calculating the electromagnetic properties of individual ice crystals and snow flakes. These calculations will allow us to exploit polarized remote sensing observations to discriminate different particles types and elucidate dynamics of cloud and precipitating systems.

Adams, Ian S.↗

NASA NTRS2018

The Global Precipitation Measurement (GPM) Mission's Scientific Achievements and Societal Contributions: Reviewing Four Years of Advanced Rain and Snow Observations

Precipitation represents a life-critical energy and hydrologic exchange between the Earth’s atmosphere and its surface. As such, knowledge of where, when, and how much rain and snow falls is essential for scientific research and societal applications. Building on the 17-year success of the Tropical Rainfall Measurement Mission (TRMM), the Global Precipitation Measurement (GPM) Core Observatory (GPM-CO) is the first U.S. National Aeronautical and Space Administration (NASA) satellite mission specifically designed with sensors to observe the structure and intensities of both rain and falling snow. The GPM-CO has proved to be a worthy successor to TRMM, extending and improving high-quality active and passive microwave observations across all times of day. The GPM-CO launched in early 2014, is a joint mission between NASA and the Japanese Aerospace Exploration Agency (JAXA), with sensors that include the NASA-provided GPM Microwave Imager and the JAXA-provided Dual-frequency Precipitation Radar. These sensors were devised with high accuracy standards enabling them to be used as a reference for inter-calibrating a constellation of partner satellite data. These intercalibrated partner satellite retrievals are used with infrared data to produce merged precipitation estimates at temporal scales of 30 minutes and spatial scales of 0.1° x 0.1°. Precipitation estimates from the GPM-CO and partner constellation satellites, provided in near real time and later reprocessed with all ancillary data, are an indispensable source of precipitation data for operational and scientific users. Advances have been made using GPM data, primarily in improving sensor calibration, retrieval algorithms, and ground validation measurements, and used to further our understanding of the characteristics of liquid and frozen precipitation and the science of water and hydrological cycles for climate/weather forecasting. These advances have extended to societal benefits related to water resources, operational numerical weather prediction, hurricane monitoring, prediction, and disaster response, extremes, and disease.

Applications↗

NASA NTRS1980

Observation of the Grand Canyon wall structure with an airborne imaging radar

The paper reports on radar images of the Grand Canyon region obtained with the Jet Propulsion Laboratory L-band (25 cm wavelength) airborne synthetic aperture radar in order to determine the capability of such a system to observe wall stratifications compared with optical sensors. Comparisons are made between these and Landsat images of the same area. Finally, it is noted that the observations do not furnish any new information on the geology of the Grant Canyon, rather, they add to the data base which is required in the interpretation of radar images from unknown remote regions such as the surface of Venus.

Elachi, C.↗

DOE OSTI2025

Respiration Signal Pattern Analysis for Doppler Radar Sensor with Passive Node and Its Application in Occupancy Sensing of a Stationary Subject

Doppler radar node occupancy sensors are promising for applications in smart buildings due to their simple circuits and price advantage compared to quadrature radar sensors. However, single-channel sensitivity limitations may result in low sensitivity and misinterpreted motion rates if the detected subject is at or close to “null” points. We designed and tested a novel method to eliminate such limits, demonstrating that passive nodes can be used to detect a sedentary person regardless of position. This method is based on characteristics of chest motion due to respiration, found via both simulations and experiments based on a sinusoidal model and a more realistic model of cardiorespiratory motion. In addition, respiratory rate variability is considered to distinguish a true human presence from a mechanical target. Sensor node data were collected simultaneously with an infrared camera system, which provided a respiration signal reference, to test the algorithm with 19 human subjects and a mechanical target. The results indicate that a human presence was detected with 100% accuracy and successfully differentiated from a mechanical target in a controlled environment. The developed method can greatly improve the occupancy detection accuracy of single-channel radar-based occupancy sensors and facilitate their adoption in smart building applications.

Song, Chenyan↗

NASA NTRS2021

Applications of a CloudSat-TRMM and CloudSat-GPM Satellite Coincidence Dataset

The Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR) (Ku- and Ka-band, or 14 and 35 GHz) provides the capability to resolve the precipitation structure under moderate to heavy precipitation conditions. In this manuscript, the use of near-coincident observations between GPM and the CloudSat Profiling Radar (CPR) (W-band, or 94 GHz) are demonstrated to extend the capability of representing light rain and cold-season precipitation from DPR and the GPM passive microwave constellation sensors. These unique triple-frequency data have opened up applications related to cold-season precipitation, ice microphysics, and light rainfall and surface emissivity effects.

GPM↗

NASA NTRS1978

Synthetic Aperture Radar (SAR) data processing

The available and optimal methods for generating SAR imagery for NASA applications were identified. The SAR image quality and data processing requirements associated with these applications were studied. Mathematical operations and algorithms required to process sensor data into SAR imagery were defined. The architecture of SAR image formation processors was discussed, and technology necessary to implement the SAR data processors used in both general purpose and dedicated imaging systems was addressed.

Beckner, F. L.↗