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Results for “Microwave remote sensing”

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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Monitoring boreal ecosystem phenology with integrated active/passive microwave remote sensing

The important role of the high latitudes in the functioning of global processes is becoming well established. The size and remoteness of arctic and boreal ecosystems, however, pose a challenge to quantification of both terrestrial ecosystem processes and their feedbacks to regional and global climate conditions. Boreal and arctic regions form a complex land cover mosaic where vegetation structure, condition and distribution are strongly regulated by environmental factors such as moisture availability, permafrost, growing season length, disturbance and soil nutrients.

SeaWinds↗
NASA NTRS1997

Laboratory Measurements of Sea Ice: Connections to Microwave Remote Sensing

The connections between laboratory measurements and remote sensing observations of sea ice are explored. The focus of this paper is on thin ice which is more easily simulated in a laboratory environment. We summarize results of C-band scatterometer measurements and discuss how they may help in the interpretation of remote sensing data.

remote↗
NASA NTRS2018

Assimilation of Satellite Derived Soil Moisture Profiles into a Crop Modeling System for Robust Yield Estimates

Soil Moisture Measurement - Remote Sensing. - Microwave (MW) Remote Sensing: Physically based and quantitative in nature; Based on difference in dielectric constant; Coarse spatial resolution 25-40 km; Shallow SM estimation depth 0-5 cm (approx.); All weather capabilities (e.g. Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E), Soil Moisture and Ocean Salinity (SMOS), Soil Moisture Active Passive (SMAP) etc.) - Thermal Infrared (TIR) Remote Sensing: Indirect SM retrieval through energy flux estimations; Relatively better spatial resolution 1-10 km; Root-zone moisture retrieval capability; Can not penetrate through clouds, hence data gaps (e.g. Surface Energy Balance Algorithm for Land (SEBAL), Atmospheric Land Exchange Inverse (ALEXI) etc.)

SERVIR↗
NASA NTRS1977

International Symposium on Remote Sensing of Environment, 11th, University of Michigan, Ann Arbor, Mich., April 25-29, 1977, Proceedings. Volumes 1 & 2

Consideration is given to remote sensor development and sensor data analysis and interpretation, and to the following fields of application of remote sensors: geology and mineral resources, meteorology, agriculture, forestry and rangeland, ocean and coastal regions, and environmental quality. Attention is also given to economic and institutional issues and technology transfer in the field of remote sensing, to microwave remote sensing and to the current and future role of remote sensing in operational programs.

Source record↗
NASA NTRS1981

International Symposium on Remote Sensing of Environment, 15th, University of Michigan, Ann Arbor, MI, May 11-15, 1981, Proceedings. Volumes 1, 2 & 3

Developments related to advanced sensors and sensor systems are being examined, taking into account advanced aerospace remote sensing systems for global resource applications, spaceborne radar observation of the earth surface, a concept for an advanced earth resources satellite system, technologies for the multispectral mapping of earth resources, and the use of Landsat images and morphologic analogs in space exploration. Other topics discussed are related to modeling for terrain analysis, digital processing and analysis of remotely sensed data, microwave remote sensing, new discoveries from planetary remote sensing, and data base utilization. Advances in the area of luminescence are also considered along with future plans and prospects concerning the remote sensing of the earth from space.

Source record↗
NASA NTRS2009

Comment on Modified Stokes Parameters

It is common practice in passive microwave remote sensing (microwave radiometry) to express observables as temperatures and in the case of polarimetric radiometry to use what are called "Modified Stokes Parameters in Brightness Temperature" to describe the scene. However, definitions with slightly different normalization (with and without division by bandwidth) have appeared in the literature. The purpose of this manuscript is to present an analysis to clarify the meaning of terms in the definition and resolve the question of the proper normalization.

Le Vine, D.M.↗
NASA NTRS1978

Remote sensing of snowpack with microwave radiometers for hydrologic applications

A microwave remote sensing of snowpack experiment is described and some preliminary data presented. A mobile field laboratory consisting of a four-frequency (5, 10.7, 18 and 37 GHz), all with dual linear (vertical and horizontal) polarizations, microwave radiometer system attached to a truck-mounted aerial lift was used to study the microwave emission characteristics of snowpacks in the Colorado Rocky Mountains during the winter of 1977-78. The influence of snowpack physical parameters such as water equivalent, grain size, and melt-freeze cycle on its microwave brightness temperature and its implications to the application of microwave radiometric technique to remote sensing of snowpack for runoff prediction are discussed.

Shiue, J. C.↗
NASA NTRS2021

Sensitivity of Wide Bandwidth Radiometer for Remote Sensing of Ocean Salinity

Passive microwave remote sensing of sea surface salinity from space is currently being done with measurements in the 27 MHz wide spectral window at 1.413 GHz (L-band) protected for passive use. Modern L-band instruments, such as the radiometers on SMOS and Aquarius, have demonstrated the feasibility of monitoring surface salinity from space, and they have also demonstrated the need for better accuracy, especially in cold water. Proposals to improve accuracy have largely involved adding measurement at more frequencies. For example, adding lower frequencies to improve the sensitivity to salinity in cold water and adding higher frequencies to enable simultaneous retrieval of sea surface temperature which is needed in the retrieval of salinity. These strategies involve trade-offs, some obvious such as the effects of interference from anthropogenic sources of radio frequency radiation (RFI) when operating outside the protected band and the loss of spatial resolution at lower frequencies. But, some are more subtle and arise because of the dependence of the retrieval of salinity on other parameters of the ocean surface, in particular, water temperature and roughness (wind speed). The effect of these interdependencies on the potential accuracy of salinity remote sensing in the frequency range 0.3 – 3.0 GHz is examined here to gain insight into the potential for future wide bandwidth instruments for remote sensing of salinity and the optimization of their design. There is benefit including the low frequencies, especially for cold water, but a danger of increased error including frequencies above 1.5 - 2.0 GHz depending on temperature.

Microwave Remote Sensing↗
NASA NTRS2016

RFI and Remote Sensing of the Earth from Space

Passive microwave remote sensing of the Earth from space provides information essential for understanding the Earth's environment and its evolution. Parameters such as soil moisture, sea surface temperature and salinity, and profiles of atmospheric temperature and humidity are measured at frequencies determined by the physics (e.g. sensitivity to changes in desired parameters) and by the availability of suitable spectrum free from interference. Interference from manmade sources (radio frequency interference) is an impediment that in many cases limits the potential for accurate measurements from space. A review is presented here of the frequencies employed in passive microwave remote sensing of the Earth from space and the associated experience with RFI.

RFI↗
NASA NTRS2000

Proposed Definitions of Some Technical Terms Frequently Used in Microwave Radiometry for Remote Sensing

The use of microwave radiometry for remote sensing is a relatively young field. As a result, there are no standard definitions of many frequently used technical terms; a lot of which are conventional usages carried-over from optical remote sensing, and a lot more are shared with electrical or microwave engineering. Sometimes the divergent notions and assumptions originating from a different field may cause ambiguity or confusions. It is proposed that we establish a list of frequently used terms, together with their 'standard' definitions and hope that they will gradually gain general acceptance by the remote sensing community. It would be even more useful if the IEEE community can set up a standard committee of sort to develop and maintain the standards. To minimize the effort, the existing terms should be kept or reinterpreted as much as possible. For example, the term 'Instantaneous Field of View' (IFOV), originally coming from the optical remote sensing field, is now appearing in microwave remote sensing literature frequently. The IFOV refers to the 'beam width' or the 'diameter' of the beam's geometrical projection on earth surface. Since the definition of 'beam width' is different for an optical system versus a microwave antenna, the use of IFOV in microwave radiometry needed to be clarified. Also, the meaning of the IFOV will be different depending upon whether the beam is scanning or not, and how the scanning takes place, e.g. 'continuous scanning' vs 'stare-and-step scan.' From this one term alone, it is clear that more subtle meanings must be spell out in detail and a 'standard' definition would help in understanding and comparing systems and data in the literature. A selected list of terms with their suggested definitions will be discussed in this presentation.

Shiue, James C.↗