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NASA NTRS1973

Task 4: Lake Ice Surveillance, 1406

The author has identified the following significant results. Although it is readily recognized that there is a need for ground truth to provide adequate guidance for remote sensing data interpretation, it is noted that, in terms of radar remote sensing, this ground truth is often inadequate. It is necessary to make basic electrical and physical measurements of the surface and to some depth below it. A brief outline is presented of a ground truth scheme which uses measurements of the dielectric constant. Two portable instruments were designed specifically for this purpose; these were: (1) a Q-meter for measurement of dielectric constant and loss tangent; and (2) an instrument to measure electrical properties of the two operating frequencies of the imaging radar. Although extensive data are lacking, several general cases of radar-earth surface and interaction are described; also, examples of radar imagery and some data on ice and snow are presented. It is concluded that the next logical step is to begin to quantify the radar ground truth in preparation for machine interpretation and automatic data processing of the radar imagery.

Porcello, L. J.↗

NASA NTRS2001

GPS: A New Tool for Ocean Science

In this article, we demonstrate wind retrieval (estimate its speed) from reflected signals obtained by a GPS receiver on board an aircraft to illustrate the potential of using GPS for remote-sensing applications. Before showing those results, we provide some background on radar remote sensing and discuss the theoretical model we used to interpret reflection data. This model describes the power and correlation properties of the reflected GPS signals as a function of scattering geometry and environmental parameters related to the reflecting surface.

Komjathy, Attila↗

NASA NTRS1999

Radar Safety Interlock for a Remote Sensing System

A radar initiated interlock system which protects overflying aircraft from the laser radiation from the remote sensing systems located at Table Mountain Facility of the Jet Propulsion Laboratory is described in detail.

Radar Lidar↗

NASA NTRS1970

Recent advances in radar applications to agriculture

A series of remote radar sensing studies are summarized. These efforts comprise geoscience interpretations of such complex phenomena as those manifested in agricultural patterns. Considered are basic remote sensing needs in agriculture and the design and implementation of radar keys in the active microwave region as well as fine resolution radar imagery techniques for agriculture determinations and soil mapping.

Morain, S. A.↗

NASA NTRS1984

Evaluation of the radar response to land surfaces and volumes: Examination of theoretical models, target statistics, and applications

Four areas of L-band radar remote sensing of terrain were examined: (1) the behavior of the radar backscatter coefficient of distributed surface and volumes as a function of the targets' dielectric and geometric parameters and as a fnction of their physical parameters; (2) the correspondence of the angular behavior of the relative backscatter coefficient as extracted from SIR-B digital imagery and truck mounted L-band scatterometer measurements for about 100 fields; (3) the statistical behavior of SIR-B image density for targets that appear homogeneous on Thematic Mapper (TM) optical imagery and/or color IR photography; and (4) the applicability of SIR-B imagery both alone and in conjunction with TM imagery for the classification and monitoring of land cover and renewable resources.

Ulaby, F. T.↗

NASA NTRS2001

Spaceborne Microwave Instrument for High Resolution Remote Sensing of the Earth's Surface Using a Large-Aperture Mesh Antenna

This report describes a two-year study of a large-aperture, lightweight, deployable mesh antenna system for radiometer and radar remote sensing of the Earth from space. The study focused specifically on an instrument to measure ocean salinity and Soil moisture. Measurements of ocean salinity and soil moisture are of critical . importance in improving knowledge and prediction of key ocean and land surface processes, but are not currently obtainable from space. A mission using this instrument would be the first demonstration of deployable mesh antenna technology for remote sensing and could lead to potential applications in other remote sensing disciplines that require high spatial resolution measurements. The study concept features a rotating 6-m-diameter deployable mesh antenna, with radiometer and radar sensors, to measure microwave emission and backscatter from the Earth's surface. The sensors operate at L and S bands, with multiple polarizations and a constant look angle, scanning across a wide swath. The study included detailed analyses of science requirements, reflector and feedhorn design and performance, microwave emissivity measurements of mesh samples, design and test of lightweight radar electronic~., launch vehicle accommodations, rotational dynamics simulations, and an analysis of attitude control issues associated with the antenna and spacecraft, The goal of the study was to advance the technology readiness of the overall concept to a level appropriate for an Earth science emission.

Njoku, E.↗

NASA NTRS2024

Extending the Utility of Space-Borne Snow Water Equivalent Observations Over Vegetated Areas With Data Assimilation

Snow is a vital component of the earth system, yet no snow-focused satellite remote sensing platform currently exists. In this study, we investigate how synthetic observations of snow water equivalent (SWE) representative of a synthetic aperture radar remote sensing platform could improve spatiotemporal estimates of snowpack. We use a fraternal twin observing system simulation experiment, specifically investigating how much snow simulated using widely used models and forcing data could be improved by assimilating synthetic observations of SWE. We focus this study across a 24° x 37° domain in the western USA and Canada, simulating snow at 250 m resolution and hourly time steps in water year 2019. We perform two data assimilation experiments, including (1) a simulation excluding synthetic observations in forests where canopies obstruct remote sensing retrievals and (2) a simulation inferring snow distribution in forested grid cells using synthetic observations from nearby canopy-free grid cells. Results found that, relative to a nature run, or assumed true simulation of snow evolution, assimilating synthetic SWE observations improved average SWE biases at maximum snowpack timing in shrub, grass, crop, bare-ground, and wetland land cover types from 14 %, to within 1 %. However, forested grid cells contained a disproportionate amount of SWE volume. In forests, SWE mean absolute errors at the time of maximum snow volume were 111 mm and average SWE biases were on the order of 150 %. Here the data assimilation approach that estimated forest SWE using observations from the nearest canopy-free grid cells substantially improved these SWE biases (18 %) and the SWE mean absolute error (27 mm). Simulations employing data assimilation also improved estimates of the temporal evolution of both SWE and runoff, even in spring snowmelt periods when melting snow and high snow liquid water content prevented synthetic SWE retrievals. In fact, in the Upper Colorado River region, melt-season SWE biases were improved from 63 % to within 1 %, and the Nash–Sutcliffe efficiency of runoff improved from −2.59 to 0.22. These results demonstrate the value of data assimilation and a snow-focused globally relevant remote sensing platform for improving the characterization of SWE and associated water availability.

Justin Pflug↗

NASA NTRS2016

Digital Beamforming Synthetic Aperture Radar Developments at NASA Goddard Space Flight Center

Advanced Digital Beamforming (DBF) Synthetic Aperture Radar (SAR) technology is an area of research and development pursued at the NASA Goddard Space Flight Center (GSFC). Advanced SAR architectures enhances radar performance and opens a new set of capabilities in radar remote sensing. DBSAR-2 and EcoSAR are two state-of-the-art radar systems recently developed and tested. These new instruments employ multiple input-multiple output (MIMO) architectures characterized by multi-mode operation, software defined waveform generation, digital beamforming, and configurable radar parameters. The instruments have been developed to support several disciplines in Earth and Planetary sciences. This paper describes the radars advanced features and report on the latest SAR processing and calibration efforts.

Wide band↗

NASA NTRS1981

Geological terrain models

The initial phase of a program to determine the best interpretation strategy and sensor configuration for a radar remote sensing system for geologic applications is discussed. In this phase, terrain modeling and radar image simulation were used to perform parametric sensitivity studies. A relatively simple computer-generated terrain model is presented, and the data base, backscatter file, and transfer function for digital image simulation are described. Sets of images are presented that simulate the results obtained with an X-band radar from an altitude of 800 km and at three different terrain-illumination angles. The simulations include power maps, slant-range images, ground-range images, and ground-range images with statistical noise incorporated. It is concluded that digital image simulation and computer modeling provide cost-effective methods for evaluating terrain variations and sensor parameter changes, for predicting results, and for defining optimum sensor parameters.

Kaupp, V. H.↗

NASA NTRS1980

Microwave radar and radiometric remote sensing measurements of lake ice

Simultaneous microwave radar and spectral radiometric data were collected over Lake Erie during March 1978. A theoretical development is presented which interprets the data collected at nadir in terms of changes in the ice thickness and the electromagnetic attenuation coefficient. The theory also addresses the failure of the spectral radiometer to determine ice thickness through observations of quarter wavelength excursions in the reflectivity. Radar data collected off-nadir showed a substantially different behavior compared to that collected near nadir. This difference is attributed to a change in propagation characteristics from quasi-specular return from the ice-water interface to scattering from the rough air-ice interface.

Swift, C. T.↗

NASA NTRS2009

Winter QPF Sensitivities to Snow Parameterizations and Comparisons to NASA CloudSat Observations

Steady increases in computing power have allowed for numerical weather prediction models to be initialized and run at high spatial resolution, permitting a transition from larger scale parameterizations of the effects of clouds and precipitation to the simulation of specific microphysical processes and hydrometeor size distributions. Although still relatively coarse in comparison to true cloud resolving models, these high resolution forecasts (on the order of 4 km or less) have demonstrated value in the prediction of severe storm mode and evolution and are being explored for use in winter weather events . Several single-moment bulk water microphysics schemes are available within the latest release of the Weather Research and Forecast (WRF) model suite, including the NASA Goddard Cumulus Ensemble, which incorporate some assumptions in the size distribution of a small number of hydrometeor classes in order to predict their evolution, advection and precipitation within the forecast domain. Although many of these schemes produce similar forecasts of events on the synoptic scale, there are often significant details regarding precipitation and cloud cover, as well as the distribution of water mass among the constituent hydrometeor classes. Unfortunately, validating data for cloud resolving model simulations are sparse. Field campaigns require in-cloud measurements of hydrometeors from aircraft in coordination with extensive and coincident ground based measurements. Radar remote sensing is utilized to detect the spatial coverage and structure of precipitation. Here, two radar systems characterize the structure of winter precipitation for comparison to equivalent features within a forecast model: a 3 GHz, Weather Surveillance Radar-1988 Doppler (WSR-88D) based in Omaha, Nebraska, and the 94 GHz NASA CloudSat Cloud Profiling Radar, a spaceborne instrument and member of the afternoon or "A-Train" of polar orbiting satellites tasked with cataloguing global cloud characteristics. Each system provides a unique perspective. The WSR-88D operates in a surveillance mode, sampling cloud volumes of Rayleigh scatterers where reflectivity is proportional to the sixth moment of the size distribution of equivalent spheres. The CloudSat radar provides enhanced sensitivity to smaller cloud ice crystals aloft, as well as consistent vertical profiles along each orbit. However, CloudSat reflectivity signatures are complicated somewhat by resonant Mie scattering effects and significant attenuation in the presence of cloud or rain water. Here, both radar systems are applied to a case of light to moderate snowfall within the warm frontal zone of a cold season, synoptic scale storm. Radars allow for an evaluation of the accuracy of a single-moment scheme in replicating precipitation structures, based on the bulk statistical properties of precipitation as suggested by reflectivity signatures.

Molthan, Andrew↗

NASA NTRS2016

Near Real-Time Flood Monitoring and Impact Assessment Systems

Floods are the costliest natural disaster, causing approximately 6.8 million deaths in the twentieth century alone. Worldwide economic flood damage estimates in 2012 exceed $19 Billion USD. Extended duration floods also pose longer term threats to food security, water, sanitation, hygiene, and community livelihoods, particularly in developing countries. Projections by the Intergovernmental Panel on Climate Change (IPCC) suggest that precipitation extremes, rainfall intensity, storm intensity, and variability are increasing due to climate change. Increasing hydrologic uncertainty will likely lead to unprecedented extreme flood events. As such, there is a vital need to enhance and further develop traditional techniques used to rapidly assess flooding and extend analytical methods to estimate impacted population and infrastructure. Measuring flood extent in situ is generally impractical, time consuming, and can be inaccurate. Remotely sensed imagery acquired from space-borne and airborne sensors provides a viable platform for consistent and rapid wall-to-wall monitoring of large flood events through time. Terabytes of freely available satellite imagery are made available online each day by NASA, ESA, and other international space research institutions. Advances in cloud computing and data storage technologies allow researchers to leverage these satellite data and apply analytical methods at scale. Repeat-survey earth observations help provide insight about how natural phenomena change through time, including the progression and recession of floodwaters. In recent years, cloud-penetrating radar remote sensing techniques (e.g., Synthetic Aperture Radar) and high temporal resolution imagery platforms (e.g., MODIS and its 1-day return period), along with high performance computing infrastructure, have enabled significant advances in software systems that provide flood warning, assessments, and hazard reduction potential. By incorporating social and economic data, researchers can develop systems that automatically quantify the socioeconomic impacts resulting from flood disaster events.

Ahamed, Aakash↗

NASA NTRS1987

Remote sensing from space; Proceedings of Symposium 3, Workshop V, and Topical Meeting A2 of the Twenty-sixth COSPAR Plenary Meeting, Toulouse, France, June 30-July 11, 1986

Various papers on remote sensing from space are presented. The use of such remote sensing to study terrestrial patterns and processes is examined, including the relevant processes and theories, observed vegetation and surface climate parameters, derived terrestrial processes, atmospheric effects, and new sensors. Quantitative radar remote sensing of land and oceanic surface features is addressed, including systems, calibration, simulation, data evaluation for vegetational studies, altimetry, sea ice monitoring, and oil slick detection. The use of satellite observations for weather prediction is discussed.

Goward, S. N.↗

NASA NTRS1981

Coherent optical determination of the leaf angle distribution of corn

A coherent optical technique for the diffraction analysis of an image is presented. Developments in radar remote sensing shows a need to understand plant geometry and its relationship to plant moisture, soil moisture, and the radar backscattering coefficient. A corn plant changes its leaf angle distribution, as a function of time, from a uniform distribution to one that is strongly vertical. It is shown that plant and soil moisture may have an effect on plant geometry.

Ulaby, F. T.↗

NASA NTRS1990

Radar detection of flooding beneath the forest canopy - A review

Synthetic aperture radar remote sensing is a promising tool for detection of flooding on forested floodplains. The brigtht appearance of flooded forests on radar images results from double-bounce reflections between smooth water surfaces and tree trunks or branches. Enhanced backscattering at L-band has been shown to occur in a wide variety of forest types, including cypress-tupelo swamps, temperate bottomland hardwoods, spruce bogs, mangroves and tropical floodplain forests. Lack of enhancement is a function of both stand density and branching structure. According to models and measurements, the magnitude of the enhancement is about 3 to 10 dB. Steep incidence angles (20-30 deg) are optimal for detection of flooding, since some forest types exhibit bright returns only at steeper angles. P-band should prove useful for floodwater mapping in dense stands, and multifrequency polarimetric analysis should allow flooded forests to be distinguished from marshes.

Hess, Laura L.↗

NASA NTRS1976

An integrated approach to the remote sensing of floating ice

Review article on remote sensing applications to glaciology. Ice parameters sensed include: ice cover vs open water, ice thickness, distribution and morphology of ice formations, vertical resolution of ice thickness, ice salinity (percolation and drainage of brine; flushing of ice body with fresh water), first-year ice and multiyear ice, ice growth rate and surface heat flux, divergence of ice packs, snow cover masking ice, behavior of ice shelves, icebergs, lake ice and river ice; time changes. Sensing techniques discussed include: satellite photographic surveys, thermal IR, passive and active microwave studies, microwave radiometry, microwave scatterometry, side-looking radar, and synthetic aperture radar. Remote sensing of large aquatic mammals and operational ice forecasting are also discussed.

Campbell, W. J.↗

NASA NTRS1992

Radar measurement of forested areas during OTTER

To test a forest ecosystem model in the OTTER (Oregon ecosystem research) project, it is desirable to find forest canopy parameters via radar remote sensing measurements. Conventionally, forest biomass, along with quantities such as the leaf area index, drive the model. It is shown that the radar backscatter is not uniquely related to biomass. A sensitivity study is carried out using a forward scattering model to determine the variation of radar cross section as a function of several forest parameters. The results are used to find suitable quantities to recover via radar experiments. A parameter estimation scheme is developed to calculate some preliminary statistical properties of the forest.

Moghaddam, M.↗

NASA NTRS2008

Reconfigurable L-Band Radar

The reconfigurable L-Band radar is an ongoing development at NASA/GSFC that exploits the capability inherently in phased array radar systems with a state-of-the-art data acquisition and real-time processor in order to enable multi-mode measurement techniques in a single radar architecture. The development leverages on the L-Band Imaging Scatterometer, a radar system designed for the development and testing of new radar techniques; and the custom-built DBSAR processor, a highly reconfigurable, high speed data acquisition and processing system. The radar modes currently implemented include scatterometer, synthetic aperture radar, and altimetry; and plans to add new modes such as radiometry and bi-static GNSS signals are being formulated. This development is aimed at enhancing the radar remote sensing capabilities for airborne and spaceborne applications in support of Earth Science and planetary exploration This paper describes the design of the radar and processor systems, explains the operational modes, and discusses preliminary measurements and future plans.

Rincon, Rafael F.↗