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All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

SPASE: Current Uses, Tools, and Plans

The Space Physics Archive Search and Extract (SPASE) project is an international collaboration among Heliophysics (solar and space physics) groups concerned with data acquisition and archiving. Within this community there are a variety of old and new data centers, resident archives, "virtual observatories", etc. acquiring, holding, and distributing data. The main product of the SPASE group is an XML-based SPASE Data Model now in operational use to enable searches for and ultimate acquisition of data of interest to a researcher. The SPASE Data Model defines the content of resource descriptions (metadata). The intent is to describe all SCientifically usable Heliophysics data sets using the Data Model. Another product of the SPASE group, in collaboration with NASA's Virtual Observatories, is a set of tools and services which work with SPASE meta data. This includes Registry Services which can retrieve and render metadata using resource identifiers and facilitate the downloading of the data referenced by the meta data. The SPASE Data Model has also been used as a vocabulary in specialized data models. One example is the Heliophysics Event List Manager (HELM) model. The SPASE Data Model is also being expanded to provide the means for more detailed description of data sets with the aim of enabling more automated ingestion and use of the data through detailed format descriptions. The evolution is based on a number of lessons learned and feedback from our community. Some of the lessons learned are unique to Heliophysics, and some are common to the various data diSCiplines. We will discuss the present state of SPASE usage, the role the SPASE Data Model can play in speCialized data models and how we foresee the development direction in the future.

Thieman, J. R.↗
NASA NTRS2022

Polarization as a Discriminator of Light-Absorbing Impurities in or Above Snow

This conceptual study presents advanced radiative transfer computations of light polarization originating from a snowpack consisting of nonspherical grains and variable content of light-absorbing impurities, either embedded in the snowpack or (with the same optical properties) lofted above it in the form of atmospheric aerosols. The results highlight the importance of considering shapes other than spherical for the snow grains, which otherwise can lead to non-negligible errors in the retrieval of snow albedo from remote sensing observations. More importantly, it is found that polarimetric measurements provide a means to partition light-absorbing impurities embedded in the snowpack from absorbing aerosols aloft, a task traditionally prohibitive for sensors capable exclusively of measurements of total reflectance. Heritage techniques to obtain snow grain size from shortwave infrared observations of total reflectance are well established, as are those that leverage polarimetric, multiangular observations across the entire optical spectrum to characterize the optical and microphysical properties of atmospheric aerosols. The polarization signatures of near-infrared (e.g., 864 nm) observations carry critical information on snow grain shape. The prospected launch of space-borne polarimeters with proven accuracy, therefore, advocates for the development of data inversion schemes, to boost the accuracy of simultaneous retrievals of atmospheric and surface parameters in the polar and snow-covered regions, critical to climate studies.

light polarization↗
NASA NTRS2014

An Examination of the Nature of Global MODIS Cloud Regimes

We introduce global cloud regimes (previously also referred to as "weather states") derived from cloud retrievals that use measurements by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Aqua and Terra satellites. The regimes are obtained by applying clustering analysis on joint histograms of retrieved cloud top pressure and cloud optical thickness. By employing a compositing approach on data sets from satellites and other sources, we examine regime structural and thermodynamical characteristics. We establish that the MODIS cloud regimes tend to form in distinct dynamical and thermodynamical environments and have diverse profiles of cloud fraction and water content. When compositing radiative fluxes from the Clouds and the Earth's Radiant Energy System instrument and surface precipitation from the Global Precipitation Climatology Project, we find that regimes with a radiative warming effect on the atmosphere also produce the largest implied latent heat. Taken as a whole, the results of the study corroborate the usefulness of the cloud regime concept, reaffirm the fundamental nature of the regimes as appropriate building blocks for cloud system classification, clarify their association with standard cloud types, and underscore their distinct radiative and hydrological signatures.

radiation↗
NASA NTRS1995

Diabatic forcing and intialization with assimilation of cloud water and rainwater in a forecast model

In this study, diabatic forcing, and liquid water assimilation techniques are tested in a semi-implicit hydrostatic regional forecast model containing explicit representations of grid-scale cloud water and rainwater. Diabatic forcing, in conjunction with diabatic contributions in the initialization, is found to help the forecast retain the diabatic signal found in the liquid water or heating rate data, consequently reducing the spinup time associated with grid-scale precipitation processes. Both observational Special Sensor Microwave/Imager (SSM/I) and model-generated data are used. A physical retrieval method incorporating SSM/I radiance data is utilized to estimate the 3D distribution of precipitating storms. In the retrieval method the relationship between precipitation distributions and upwelling microwave radiances is parameterized, based upon cloud ensemble-radiative model simulations. Regression formulae relating vertically integrated liquid and ice-phase precipitation amounts to latent heating rates are also derived from the cloud ensemble simulations. Thus, retrieved SSM/I precipitation structures can be used in conjunction with the regression-formulas to infer the 3D distribution of latent heating rates. These heating rates are used directly in the forecast model to help initiate Tropical Storm Emily (21 September 1987). The 14-h forecast of Emily's development yields atmospheric precipitation water contents that compare favorably with coincident SSM/I estimates.

Raymond, William H.↗
NASA NTRS1980

Evaluation of the effects of varying moisture contents on microwave thermal emissions from agriculture fields

Three tasks related to soil moisture sensing at microwave wavelengths were undertaken: (1) analysis of data at L, X and K sub 21 band wavelengths over bare and vegetated fields from the 1975 NASA sponsored flight experiment over Phoenix, Arizona; (2) modeling of vegetation canopy at microwave wavelengths taking into consideration both absorption and volume scattering effects; and (3) investigation of overall atmospheric effects at microwave wavelengths that can affect soil moisture retrieval. Data for both bare and vegetated fields are found to agree well with theoretical estimates. It is observed that the retrieval of surface and near surface soil moisture information is feasible through multi-spectral and multi-temporal analysis. It is also established that at long wavelengths, which are optimal for surface sensing, atmospheric effects are generally minimal. At shorter wavelengths, which are optimal for atmosheric retrieval, the background surface properties are also established.

Burke, H. H. K.↗
NASA NTRS1990

Intercomparison between microwave and infrared observations of precipitable water

The possible utility of observations by the TIROS-N Vertical Sounder system as a data base for a global climatology of atmospheric precipitable water is assessed. A comparison is described between the atmospheric precipitable water content (PWC) derived from IR observations by the High-Resolution Infrared Radiation Sounder (HIRS/2) of the TOVS system using the eigenvector regression technique and derived from microwave observations by the Special Sensor Microwave/Imager (SSM/I). It is suggested that the difference between the two data sets can largely be attributed to the eigenvector method used to retrieve PWC from the HIRS/2 observations. It is shown that in the regions of subsidence associated with the air motion around the subtropical zone of high pressure, the HIRS/2 tends to overestimate the PWC.

Tjemkes, Stephen A.↗
NASA NTRS1993

Flexible Weighting-And-Matching Scheme For Incomplete Data

Method for partial matching of data makes conventional electronic memory addressable via its contents. When implemented by suitable algorithm, method enables computer system containing memory to search memory for datum making exact or best approximate match to datum in query. Advantages are: requires neither long "learning" time nor "retraining" when additional data stored and attaches to each datum relative importance that can change with time without decreasing speed of retrieval. Responses include exact or approximate recollection, indications of ambiguity, avoidance, and even forgetfulness.

Wang, Lui↗
NASA NTRS2005

NASA GES DISC On-line Visualization and Analysis System for Gridded Remote Sensing Data

The ability to use data stored in the current NASA Earth Observing System (EOS) archives for studying regional or global phenomena is highly dependent on having a detailed understanding of the data's internal structure and physical implementation. Gaining this understanding and applying it to data reduction is a time-consuming task that must be undertaken before the core investigation can begin. This is an especially difficult challenge when science objectives require users to deal with large multi-sensor data sets that are usually of different formats, structures, and resolutions. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has taken a major step towards meeting this challenge by developing an infrastructure with a Web interface that allows users to perform interactive analysis online without downloading any data, the GES-DISC Interactive Online Visualization and Analysis Infrastructure or "Giovanni." Giovanni provides interactive, online, analysis tools for data users to facilitate their research. There have been several instances of this interface created to serve TRMM users, Aerosol scientists, Ocean Color and Agriculture applications users. The first generation of these tools support gridded data only. The user selects geophysical parameters, area of interest, time period; and the system generates an output on screen in a matter of seconds. The currently available output options are: Area plot averaged or accumulated over any available data period for any rectangular area; Time plot time series averaged over any rectangular area; Hovmoller plots image view of any longitude-time and latitude-time cross sections; ASCII output for all plot types; Image animation for area plot. Another analysis suite deals with parameter intercomparison: scatter plots, temporal correlation maps, GIs-compatible outputs, etc. This allow user to focus on data content (i.e. science parameters) and eliminate the need for expensive learning, development and processing tasks that are redundantly incurred by an archive's user community. The current implementation utilizes the GrADS-DODS Server (GDS), and provides subsetting and analysis services across the Internet for any GrADS-readable dataset. The subsetting capability allows users to retrieve a specified temporal and/or spatial subdomain from a large dataset, eliminating the need to download everything simply to access a small relevant portion of a dataset. The analysis capability allows users to retrieve the results of an operation applied to one or more datasets on the server. We use this approach to read pre-processed binary files and/or to read and extract the needed parts directly from HDF or HDF-EOS files. These subsets then serve as inputs into GrADS analysis scripts. It can be used in a wide variety of Earth science applications: climate and weather events study and monitoring; modeling. It can be easily configured for new applications.

Leptoukh, Gregory G.↗
NASA NTRS2007

Space Environment Effects on Stability of Medications Flown on Space Shuttles and the International Space Station (ISS)

The purpose is to assess physical and chemical degradation of select pharmaceutical formulations from the Shuttle and ISS medical kits. Eleven pharmaceuticals dispensed as different dosage forms were selected based on their physical / chemical characteristics and susceptibility to environmental factors such as, temperature, humidity and light sensitivity. When available, ground-controls of the study medications with matching brand and lot numbers were used for comparison. Samples retrieved from flight were stored along with their matching controls in a temperature and humidity controlled environmental chamber. Temperature, humidity, and radiation data from the Shuttle and ISS were retrieved from onboard HOBO U12 Temp/RH Data Loggers, and from passive dosimeters. Physical and chemical analyses of the pharmaceuticals were conducted using validated United States Pharmacopeia (USP) methods. Results indicated degradation of 6 of the 11 formulations returned from space flights. Four formulations, Amoxicillin / Clavulanate, promethazine, sulfamethoxazole / trimethoprim, and ciprofloxacin tablets depicted discoloration after flight. Chemical content analyses using High or Ultra Performance Liquid Chromatography (HPLC / UPLC) methods revealed that dosage forms of Amoxicillin / Clavulanate, promethazine, sulfamethoxazole / trimethoprim, lidocaine, ciprofloxacin and mupirocin contained less than 95% of manufacturer s labeled claim of active drug compound. Shuttle and ISS environments affect stability and shelf life of certain mediations flown on these missions. Data analysis is in progress to examine the effect of specific space flight environmental factors on pharmaceutical stability. The degradation profiles generated from ground studies in analog environments will be useful in establishing predictive shelf-life profiles for medications intended for use during long-term space exploration missions.

Daniels, Vernie↗
NASA NTRS2020

Biomass Estimation from Simulated GEDI, ICESat-2 and NISAR Across Environmental Gradients in Sonoma County, California

Estimates of the magnitude and distribution of aboveground carbon in Earth’s forests remain uncertain, yet knowledge of forest carbon content at a global scale is critical for forest management in support of climate mitigation. In light of this knowledge gap, several upcoming spaceborne missions aim to map forest aboveground biomass, and many new biomass products are expected from these datasets. As these new missions host different technologies, each with relative strengths and weaknesses for biomass retrieval, as well as different spatial resolutions, consistently comparing or combining biomass estimates from these new datasets will be challenging. This paper presents a demonstration of an inter-comparison of biomass estimates from simulations of three NASA missions (GEDI, ICESat-2 and NISAR) over Sonoma county in California, USA. We use a high resolution, locally calibrated airborne lidar map as our reference dataset, and emphasize the importance of considering uncertainties in both reference maps and spaceborne estimates when conducting biomass product validation. GEDI and ICESat-2 were simulated from airborne lidar point clouds, while UAVSAR’s L-band backscatter was used as a proxy for NISAR. To estimate biomass for the lidar missions we used GEDI’s footprint-level biomass algorithms, and also adapted these for application to ICESat-2. For UAVSAR, we developed a locally trained biomass model, calibrated against the ALS reference map. Each mission simulation was evaluated in comparison to the local reference map at its native product resolution (25 m, 100m transect, and 1 ha) yielding RMSEs of 57%, 75%, and 89% for GEDI, NISAR, and ICESat-2 respectively. RMSE values increased for GEDI’s power beam during simulated daytime conditions (64%), coverage beam during nighttime conditions (72%), and coverage beam daytime conditions (87%). We also test the application of GEDI’s biomass modeling framework for estimation of biomass from ICESat-2, and fine that ICESat-2 yields reasonable biomass estimates, particularly in relatively short, open canopies. Results suggest that while all three missions will produce datasets useful for biomass mapping, tall, dense canopies such as those found in Sonoma County present the greatest challenges for all three missions, while steep slopes also prove challenging for single-date SAR based biomass retrieval. Our methods provide guidance for the inter-comparison and validation of spaceborne biomass estimates through the use of airborne lidar reference maps, and could be repeated with on-orbit estimates in any area with high quality field plot and ALS data. These methods allow for regional interpretations and filtering of multi-mission biomass estimates toward improved wall-to-wall biomass maps through data fusion.

GEDI↗
DOE OSTI2022

Soil physical and thermal properties from soil samples at multiple locations at Teller Road Site, Seward Peninsula, Alaska, 2019

This dataset contains results of the laboratory analysis of soil samples collected across the watershed located at miles #27 along the Teller road, near Nome, AK. The dataset includes 124 soil samples retrieved from 52 locations during the first week of August 2019. The soil samples were collected in the top 1.2 m of soil with volume known samples, analyzed with a thermal analyser to infer thermal parameters (thermal conductivity, volumetric heat capacity and thermal diffusivity), and then processed in a lab for estimation of their bulk density, water content, carbon and nitrogen content, soil texture, and elemental fractions. This dataset has one csv file and one pdf file.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

Processing GPS Occultation Data To Characterize Atmosphere

GOAS [Global Positioning System (GPS) Occultation Analysis System] is a computer program that accepts signal-occultation data from GPS receivers aboard low-Earth-orbiting satellites and processes the data to characterize the terrestrial atmosphere and, in somewhat less comprehensive fashion, the ionosphere. GOAS is very robust and can be run in an unattended semi-operational processing mode. It features sophisticated retrieval algorithms that utilize the amplitudes and phases of the GPS signals. It incorporates a module that, using an assumed atmospheric refractivity profile, simulates the effects of the retrieval processing system, including the GPS receiver. GOAS utilizes the GIPSY software for precise determination of orbits as needed for calibration. The GOAS output for the Earth s troposphere and mid-to-lower stratosphere consists of high-resolution (<1 km) profiles of density, temperature, pressure, atmospheric refractivity, bending angles of signals, and water-vapor content versus altitude from the Earth s surface to an altitude of 30 km. The GOAS output for the ionosphere consists of electron-density profiles from an altitude of about 50 km to the altitude of a satellite, plus parameters related to the rapidly varying structure of the electron density, particularly in the E layer of the ionosphere.

Hajj, George↗
NASA NTRSDate not supplied

Ultraviolet/Visible Reflectance Spectra of Returned Samples of (162173) Ryugu Unexposed to Earth’s Atmosphere

Following the successful return of JAXA’s Hayabusa2 sample capsule, the material from asteroid (162173) Ryugu retrieved from the spacecraft retrieval container has been the subject of multi-pronged analyses [e.g., 1]. We undertook an effort to acquire reflectance spectra covering 200- to- 1100 nm of particles from Ryugu. This region probes the near-ultraviolet (NUV) to acquire reflectance spectra that cover the 250-nm Fresnel peak that can result from increased graphitization (reduced H content) of carbon-bearing materials. Laboratory tests show that increased graphitization could result from the effects of increased temperature, an effect of space weathering of materials closer to the Sun. Some ground-based reflectance spectra and space-based photometry of Ryugu show that reflectance is increasing with decreasing wavelength, suggesting the beginning of a UV upturn [2]. We sought evidence for space weathering (graphitization) of the Ryugu material at NUV wavelengths, by acquiring reflectance spectra of surface samples.

F Vilas↗
NASA NTRS1993

A petabyte size electronic library using the N-Gram memory engine

A model library containing petabytes of data is proposed by Triada, Ltd., Ann Arbor, Michigan. The library uses the newly patented N-Gram Memory Engine (Neurex), for storage, compression, and retrieval. Neurex splits data into two parts: a hierarchical network of associative memories that store 'information' from data and a permutation operator that preserves sequence. Neurex is expected to offer four advantages in mass storage systems. Neurex representations are dense, fully reversible, hence less expensive to store. Neurex becomes exponentially more stable with increasing data flow; thus its contents and the inverting algorithm may be mass produced for low cost distribution. Only a small permutation operator would be recalled from the library to recover data. Neurex may be enhanced to recall patterns using a partial pattern. Neurex nodes are measures of their pattern. Researchers might use nodes in statistical models to avoid costly sorting and counting procedures. Neurex subsumes a theory of learning and memory that the author believes extends information theory. Its first axiom is a symmetry principle: learning creates memory and memory evidences learning. The theory treats an information store that evolves from a null state to stationarity. A Neurex extracts information data without a priori knowledge; i.e., unlike neural networks, neither feedback nor training is required. The model consists of an energetically conservative field of uniformly distributed events with variable spatial and temporal scale, and an observer walking randomly through this field. A bank of band limited transducers (an 'eye'), each transducer in a bank being tuned to a sub-band, outputs signals upon registering events. Output signals are 'observed' by another transducer bank (a mid-brain), except the band limit of the second bank is narrower than the band limit of the first bank. The banks are arrayed as n 'levels' or 'time domains, td.' The banks are the hierarchical network (a cortex) and transducers are (associative) memories. A model Neurex was built and studied. Data were 50 MB to 10 GB samples of text, data base, and images: black/white, grey scale, and high resolution in several spectral bands. Memories at td, S(m(sub td)), were plotted against outputs of memories at td-1. S(m(sub td)) was Boltzman distributed, and memory frequencies exhibited self-organized criticality (SOC); i.e., 'l/f(sup beta)' after long exposures to data. Whereas output signals from level n may be encoded with B(sub output) = O(-log(2)f(sup beta)) bits, and input data encoded with B(sub input) = O((S(td)/S(td-1))(sup n)), B(sup output)/B(sub input) is much less than 1 always, the Neurex determines a canonical code for data and it is a lossless data compressor. Further tests are underway to confirm these results with more data types and larger samples.

Bugajski, Joseph M.↗
NASA NTRS2017

Estimating Surface Soil Moisture from SMAP Observations Using a Neural Network Technique

A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to March 2017 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observing System Model version 5 (GEOS-5) land modeling system, and Moderate Resolution Imaging Spectroradiometer-based vegetation water content. The NN was trained on GEOS-5 soil moisture target data, making the NN estimates consistent with the GEOS-5 climatology, such that they may ultimately be assimilated into this model without further bias correction. Evaluated against in situ soil moisture measurements, the average unbiased root mean square error (ubRMSE), correlation and anomaly correlation of the NN retrievals were 0.037 m(exp. 3)m(exp. -3), 0.70 and 0.66, respectively, against SMAP core validation site measurements and 0.026 m(exp. 3)m(exp. -3), 0.58 and 0.48, respectively, against International Soil Moisture Network (ISMN) measurements. At the core validation sites, the NN retrievals have a significantly higher skill than the GEOS-5 model estimates and a slightly lower correlation skill than the SMAP Level-2 Passive (L2P) product. The feasibility of the NN method was reflected by a lower ubRMSE compared to the L2P retrievals as well as a higher skill when ancillary parameters in physically-based retrievals were uncertain. Against ISMN measurements, the skill of the two retrieval products was more comparable. A triple collocation analysis against Advanced Microwave Scanning Radiometer 2 (AMSR2) and Advanced Scatterometer (ASCAT) soil moisture retrievals showed that the NN and L2P retrieval errors have a similar spatial distribution, but the NN retrieval errors are generally lower in densely vegetated regions and transition zones.

Soil Moisture Remote Sensing↗
DOE OSTI2026

Study of Epoxy Sealant Layer for Use in Tank Bottom Refurbishment for the DOE EM Tank Waste R&D Program

This study addresses the DOE National Laboratory Program on Hanford Tank Waste Cleanup Research and Development, focusing on tank waste retrieval, transport, and closure. Millions of gallons of high-level waste are stored in the double shell tanks (DSTs) at Hanford site. The waste is stored in the primary tank, while the secondary shell acts as a buffer between the primary tank and environment. The DSTs’ bottoms could be corroded due to the corrosive waste properties and contents. Therefore, they are being emptied, and refurbishment is needed before waste storage continues. SRNL addresses the refurbishment of still operational DSTs bottoms with a two-layer refurbishment approach. We propose that the bottom layer consists of a high-density cementitious material to shield the epoxy top layer from radioactive residuals, while the top layer serves as an epoxy sealant. This work focuses on the experimental evaluation on the formulation and testing of the epoxy layer.

Blue, Kareen [Savannah River National Laboratory (↗
NASA NTRS2001

Observed and Simulated Radiative and Microphysical Properties of Tropical Convective Storms

Increases in the ice content, albedo and cloud cover of tropical convective storms in a warmer climate produce a large negative contribution to cloud feedback in the GISS GCM. Unfortunately, the physics of convective upward water transport, detrainment, and ice sedimentation, and the relationship of microphysical to radiative properties, are all quite uncertain. We apply a clustering algorithm to TRMM satellite microwave rainfall retrievals to identify contiguous deep precipitating storms throughout the tropics. Each storm is characterized according to its size, albedo, OLR, rain rate, microphysical structure, and presence/absence of lightning. A similar analysis is applied to ISCCP data during the TOGA/COARE experiment to identify optically thick deep cloud systems and relate them to large-scale environmental conditions just before storm onset. We examine the statistics of these storms to understand the relative climatic roles of small and large storms and the factors that regulate convective storm size and albedo. The results are compared to GISS GCM simulated statistics of tropical convective storms to identify areas of agreement and disagreement.

DelGenio, Anthony D.↗
NASA NTRS1990

Multiband radar characterization of forest biomes

The utility of airborne and orbital SAR in classification, assessment, and monitoring of forest biomes is investigated through analysis of orbital synthetic aperature radar (SAR) and multifrequency and multipolarized airborne SAR imagery relying on image tone and texture. Preliminary airborne SAR experiments and truck-mounted scatterometer observations demonstrated that the three dimensional structural complexity of a forest, and the various scales of temporal dynamics in the microwave dielectric properties of both trees and the underlying substrate would severely limit empirical or semi-empirical approaches. As a consequence, it became necessary to develop a more profound understanding of the electromagnetic properties of a forest scene and their temporal dynamics through controlled experimentation coupled with theoretical development and verification. The concatenation of various models into a physically-based composite model treating the entire forest scene became the major objective of the study as this is the key to development of a series of robust retrieval algorithms for forest biophysical properties. In order to verify the performance of the component elements of the composite model, a series of controlled laboratory and field experiments were undertaken to: (1) develop techniques to measure the microwave dielectric properties of vegetation; (2) relate the microwave dielectric properties of vegetation to more readily measured characteristics such as density and moisture content; (3) calculate the radar cross-section of leaves, and cylinders; (4) improve backscatter models for rough surfaces; and (5) relate attenuation and phase delays during propagation through canopies to canopy properties. These modeling efforts, as validated by the measurements, were incorporated within a larger model known as the Michigan Microwave Canopy Scattering (MIMICS) Model.

Dobson, M. Craig↗