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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Characterization of vegetation by microwave and optical remote sensing

Two series of carefully controlled experiments were conducted. First, plots of important crops (corn, soybeans, and sorghum), prairie grasses (big bluestem, switchgrass, tal fescue, orchardgrass, bromegrass), and forage legumes (alfalfa, red clover, and crown vetch) were manipulated to produce wide ranges of phytomass, leaf area index, and canopy architecture. Second, coniferous forest canopies were simulated using small balsam fir trees grown in large pots of soil and arranged systematically on a large (5 m) platform. Rotating the platform produced many new canopies for frequency and spatial averaging of the backscatter signal. In both series of experiments, backscatter of 5.0 GHz (C-Band) was measured as a function of view angle and polarization. Biophysical measurements included leaf area index, fresh and dry phytomass, water content of canopy elements, canopy height, and soil roughness and moisture content. For a subset of the above plots, additional measurements were acquired to exercise microwave backscatter models. These measurements included size and shape of leaves, stems, and fruit and the probability density function of leaf and stem angles. The relationships of the backscattering coefficients and the biophysical properties of the canopies were evaluated using statistical correlations, analysis of variance, and regression analysis. Results from the corn density and balsam fir experiments are discussed and analyses of data from the other experiments are summarized.

Daughtry, C. S. T.↗
NASA NTRS2014

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

Soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) instrument are assimilated into the Noah land surface model (LSM) within the NASA Land Information System (LIS). Before assimilation, SMOS retrievals are bias-corrected to match the model climatological distribution using a Cumulative Distribution Function (CDF) matching approach. Data assimilation is done via the Ensemble Kalman Filter. The goal is to improve the representation of soil moisture within the LSM, and ultimately to improve numerical weather forecasts through better land surface initialization. We present a case study showing a large area of irrigation in the lower Mississippi River Valley, in an area with extensive rice agriculture. High soil moisture value in this region are observed by SMOS, but not captured in the forcing data. After assimilation, the model fields reflect the observed geographic patterns of soil moisture. Plans for a modeling experiment and operational use of the data are given. This work helps prepare for the assimilation of Soil Moisture Active/Passive (SMAP) retrievals in the near future.

Data Assimilation↗
NASA NTRS1977

Agricultural scene understanding

The author has identified the following significant results. The LACIE field measurement data were radiometrically calibrated. Calibration enabled valid comparisons of measurements from different dates, sensors, and/or locations. Thermal band canopy results included: (1) Wind velocity had a significant influence on the overhead radiance temperature and the effect was quantized. Biomass and soil temperatures, temperature gradient, and canopy geometry were altered. (2) Temperature gradient was a function of wind velocity. (3) Temperature gradient of the wheat canopy was relatively constant during the day. (4) The laser technique provided good quality geometric characterization.

Landgrebe, D. A.↗
NASA NTRS1982

Microwave remote sensing of soil moisture, volume 1

Multifrequency sensor data from NASA's C-130 aircraft were used to determine which of the all weather microwave sensors demonstrated the highest correlation to surface soil moisture over optimal bare soil conditions, and to develop and test techniques which use visible/infrared sensors to compensate for the vegetation effect in this sensor's response to soil moisture. The L-band passive microwave radiometer was found to be the most suitable single sensor system to estimate soil moisture over bare fields. The perpendicular vegetation index (PVI) as determined from the visible/infrared sensors was useful as a measure of the vegetation effect on the L-band radiometer response to soil moisture. A linear equation was developed to estimate percent field capacity as a function of L-band emissivity and the vegetation index. The prediction algorithm improves the estimation of moisture significantly over predictions from L-band emissivity alone.

Mcfarland, M. J.↗
NASA NTRS1982

Comparison of CEAS and Williams-type models for spring wheat yields in North Dakota and Minnesota

The CEAS and Williams-type yield models are both based on multiple regression analysis of historical time series data at CRD level. The CEAS model develops a separate relation for each CRD; the Williams-type model pools CRD data to regional level (groups of similar CRDs). Basic variables considered in the analyses are USDA yield, monthly mean temperature, monthly precipitation, and variables derived from these. The Williams-type model also used soil texture and topographic information. Technological trend is represented in both by piecewise linear functions of year. Indicators of yield reliability obtained from a ten-year bootstrap test of each model (1970-1979) demonstrate that the models are very similar in performance in all respects. Both models are about equally objective, adequate, timely, simple, and inexpensive. Both consider scientific knowledge on a broad scale but not in detail. Neither provides a good current measure of modeled yield reliability. The CEAS model is considered very slightly preferable for AgRISTARS applications.

Barnett, T. L.↗
NASA NTRS1985

Modelisation of the optical scattering behaviour of the vegetation canopies

The three dimensional model of Kimes (1984) which can treat three dimensional variability in heterogeneous scenes, was used to test and expand physical scattering mechanisms involved in reflectance distribution dynamics by analyzing modeling and field data. The major physical phenomena causing the directional scattering behavior of vegetation canopies are presented. These include the strong anisotropic properties of the soil, and the anisotropic scattering properties of the vegetation as described by the phase function of the leaves and the geometric effects caused by vertical layers of leaves. This knowledge serves as a basis for defining optimum directional view angles for remote sensing strategies. An example on using knowledge of the scattering behavior of vegetation to develop techniques for extracting vegetation parameters (spectral albedo) from directional reflectance data is presented.

Kimes, D. S.↗
NASA NTRS1990

Conceptual design of equipment to excavate and transport regolith from the lunar maria

NASA hopes to have a manned lunar outpost completed by 2005. In order to establish the base, regolith must be excavated from the lunar surface. Regolith will be used as a source for life-supporting elements and as radiation shielding for the lunar outpost. The design team from the University of Texas at Austin designed excavation and transportation equipment for initial operations of the lunar base. The design team also characterized the elements to be found in the regolith and determined the power required to excavate regolith. The characterization of the soil was based on a literature review of lunar geography. Power requirements for excavation were developed by adapting terrestrial equations for excavation power requirements and adapting them to lunar soil conditions. The design of the excavation and transportation equipment was broken into three functions: loosing, collecting, and transporting. A scarifier was selected to loosen, a bucket was selected to collect, and a load-haul system was selected to transport. The functions are powered by a modular fuel cell powered vehicle that provides power for motion of the equipment.

Detwiler, Mark↗
NASA NTRS2006

Analytical Derivation of the Vegetation Optical Depth from the Microwave Polarization Difference Index

A numerical solution for the canopy optical depth in an existing microwave-based land surface parameter retrieval model is presented. The optical depth is derived from the microwave polarization difference index and the dielectric constant of the soil. The original procedure used an approximation in the form of a logarithmic decay function to define this relationship, and was derived through a series of lengthy polynomials. These polynomials had to be recalculated when the scattering albedo or antenna incidence angle changes. The new procedure is computationally more efficient and accurate.

Meesters, Antoon G. C. A.↗
NASA NTRS2013

Re-Greening Sahel: 30 Years of Remote Sensing Data and Field Observations (Mali, Niger)

Desertification of the Sahel region has been debated for decades, while the concept of a "re-greening" Sahel appeared with satellite remote sensing data that allowed vegetation monitoring across wide regions and over increasingly long series of years (nowadays 30 years with the GIMMS-3g dataset). However, the scarcity of long-term field observations of vegetation in the Sahel prevents ground validation and deeper analysis of such trends. After assessing the consistency of the new GIMMS-3g NDVI product by comparison to three other AVHRR-NDVI datasets and MODIS NDVI, regional GIMMS-3g NDVI trends over 1981-2011 are analyzed. Trends are found positive and statistically significant almost everywhere in Sahel over the 1981-2011 period. Long-term field observations of the aboveground herbaceous layer mass have been collected within the Gourma region in Mali (1984-2011) and within the Fakara region in western Niger (1994-2011). These observations sample ecosystem and soil diversity, thus enabling estimation of averaged values representative of the Gourma and Fakara. NDVI measurements are found in good agreement with field observations, both over the Gourma and Fakara regions where re-greening and negative trends are observed respectively. A linear regression analysis performed between spatially averaged seasonal NDVI and a weighted average of field measurements explains 59% of the variability for the Gourma region over 1984-2011, and 38% for the Fakara region over 1994-2011. In the Gourma, which is a pastoral region, the re-greening trend is mainly observed over sandy soils, and attests for the ecosystem's resilience to the 1980s' drought, able to react to the more favorable rainfall of the 1990s and 2000s. However, contrasted changes in the landscape's functioning have occurred locally. An increase in erosion and run-off processes in association with decreasing or stable vegetation cover was observed over shallow soils, which occupy 30% of the area. In the agro-pastoral Fakara, the decreasing trends observed both from satellite NDVI and field assessments of herbaceous mass are hardly explained by rainfall. These results give confidence in the dominant positive trends in Sahelian greenness, but indicate that degradation trends can also be observed, both in situ and from satellite time series.

Sahel↗
NASA NTRS1985

A Monte Carlo reflectance model for soil surfaces with three-dimensional structure

A Monte Carlo soil reflectance model has been developed to study the effect of macroscopic surface irregularities larger than the wavelength of incident flux. The model treats incoherent multiple scattering from Lambertian facets distributed on a periodic surface. Resulting bidirectional reflectance distribution functions are non-Lambertian and compare well with experimental trends reported in the literature. Examples showing the coupling of the Monte Carlo soil model to an adding bidirectional canopy of reflectance model are also given.

Cooper, K. D.↗
NASA NTRS2016

A Quasi-Global Approach to Improve Day-Time Satellite Surface Soil Moisture Anomalies through the Land Surface Temperature Input

Passive microwave observations from various spaceborne sensors have been linked to the soil moisture of the Earth's surface layer. A new generation of passive microwave sensors are dedicated to retrieving this variable and make observations in the single theoretically optimal L-band frequency (1-2 GHz). Previous generations of passive microwave sensors made observations in a range of higher frequencies, allowing for simultaneous estimation of additional variables required for solving the radiative transfer equation. One of these additional variables is land surface temperature, which plays a unique role in the radiative transfer equation and has an influence on the final quality of retrieved soil moisture anomalies. This study presents an optimization procedure for soil moisture retrievals through a quasi-global precipitation-based verification technique, the so-called Rvalue metric. Various land surface temperature scenarios were evaluated in which biases were added to an existing linear regression, specifically focusing on improving the skills to capture the temporal variability of soil moisture. We focus on the relative quality of the day-time (01:30 pm) observations from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), as these are theoretically most challenging due to the thermal equilibrium theory, and existing studies indicate that larger improvements are possible for these observations compared to their night-time (01:30 am) equivalent. Soil moisture data used in this study were retrieved through the Land Parameter Retrieval Model (LPRM), and in line with theory, both satellite paths show a unique and distinct degradation as a function of vegetation density. Both the ascending (01:30 pm) and descending (01:30 am) paths of the publicly available and widely used AMSR-E LPRM soil moisture products were used for benchmarking purposes. Several scenarios were employed in which the land surface temperature input for the radiative transfer was varied by imposing a bias on an existing regression. These scenarios were evaluated through the Rvalue technique, resulting in optimal bias values on top of this regression. In a next step, these optimal bias values were incorporated in order to re-calibrate the existing linear regression, resulting in a quasi-global uniform LST relation for day-time observations. In a final step, day-time soil moisture retrievals using the re-calibrated land surface temperature relation were again validated through the Rvalue technique. Results indicate an average increasing Rvalue of 16.5%, which indicates a better performance obtained through the re-calibration. This number was confirmed through an independent Triple Collocation verification over the same domain, demonstrating an average root mean square error reduction of 15.3%. Furthermore, a comparison against an extensive in situ database (679 stations) also indicates a generally higher quality for the re-calibrated dataset. Besides the improved day-time dataset, this study furthermore provides insights on the relative quality of soil moisture retrieved from AMSR-E's day- and night-time observations.

soil moisture↗
NASA NTRSDate not supplied

Using NASA Earth Observations to Identify Wildfire Impacts on Hydrologic Functions and Recovery in the Gila National Forest

Wildfires can dramatically influence both abiotic and biotic components of a landscape, including soil stability and chemistry; vegetation health, density, and composition; and water flow and quality. In addition to the immediate hazards posed by wildfires, subsequent hazards such as flooding and debris flow can impact the area. In New Mexico’s Gila National Forest, wildfire events have occurred with increasing frequency and severity over recent years, notably including the Whitewater Baldy Complex Fire (2012) and Silver Fire (2013), which burned over 290,000 acres and 138,698 acres, respectively, according to the Burned Area Emergency Response Team Executive Summary reports. Following a significant wildfire, land and resource management decisions are made, including when and where to focus vegetation and stream restoration efforts. This research is the result of a collaboration between the NASA DEVELOP National Program and the US Forest Service, which aimed to utilize NASA Earth observations to help inform those critical land management decisions. The project had two main objectives: 1) assess the efficacy of post-fire vegetation restoration efforts and 2) analyze the impact of burn events on the hydrology at the watershed-scale. To accomplish this first goal, data from Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imager (OLI) were used to study the vegetation health over time of treated and non-treated burn areas. To accomplish the latter, various aspects of stream behavior were examined in relation to burn events, including the runoff coefficient and “flashiness” of streams based on USGS stream gauge data and Integrated Multi-satelllite Retrievals for GPM (IMERG) precipitation data. This will allow land managers to better understand the complex ecological relationship between the cascading effects after wildfire and the greater forest ecosystem.

Madeline Allen↗
NASA NTRS1981

Dynamic study of the upper Sao Francisco River and the Tres Marias reservoir using MSS/LANDSAT images

The use of LANDSAT multispectral ban scanner imagery to verify the relationship between the behavior of the Tres Marias reservoir and the dynamics of the Sao Francisco River supply basin is described. The dispersion of suspended sediments and their concentration in the surface layers of the water are considered. A five year survey of the region during both dry and rainy seasons was performed. The drainage network was analyzed based on the patterns of dessication, water rises and soil use in the supply basin. Surface layers of the reservoir were tabulated as a function of the levels of gray in the imagery. In situ observations of water depth and reflectance were performed. Ground truth and LANDSAT data were correlated to determine the factors affecting the dynamics of the supply basin.

Dejesusparada, N.↗
NASA NTRS2011

A First-Order Radiative Transfer Model for Microwave Radiometry of Forest Canopies at L-Band

In this study, a first-order radiative transfer (RT) model is developed to more accurately account for vegetation canopy scattering by modifying the basic Tau-Omega model (the zero-order RT solution). In order to optimally utilize microwave radiometric data in soil moisture (SM) retrievals over vegetated landscapes, a quantitative understanding of the relationship between scattering mechanisms within vegetation canopies and the microwave brightness temperature is desirable. The first-order RT model is used to investigate this relationship and to perform a physical analysis of the scattered and emitted radiation from vegetated terrain. This model is based on an iterative solution (successive orders of scattering) of the RT equations up to the first order. This formulation adds a new scattering term to the . model. The additional term represents emission by particles (vegetation components) in the vegetation layer and emission by the ground that is scattered once by particles in the layer. The model is tested against 1.4-GHz brightness temperature measurements acquired over deciduous trees by a truck-mounted microwave instrument system called ComRAD in 2007. The model predictions are in good agreement with the data, and they give quantitative understanding for the influence of first-order scattering within the canopy on the brightness temperature. The model results show that the scattering term is significant for trees and modifications are necessary to the . model when applied to dense vegetation. Numerical simulations also indicate that the scattering term has a negligible dependence on SM and is mainly a function of the incidence angle and polarization of the microwave observation. Index Terms Emission,microwave radiometry, scattering, soil, vegetation.

Kurum, Mehmet↗
NASA NTRS1983

Dynamics of directional reflectance factor distributions for vegetation canopies

Directional reflectance factors that span the entire exitance hemisphere are collected on the ground for a variety of homogeneous vegetation canopies and bare soils. NOAA 6/7 AVHRR bands 1 (0.58-0.68 micron) and 2 (0.73-1.1 microns) are used. When possible, geometric measurements of leaf orientation distributions are taken simultaneously with each spectral measurement. Other supporting structural and optical measurements are made. These data sets are taken at various times of the day for each cover type. These unique sets, together with pertinent data in the literature, are used to investigate the dynamics of the directional reflectance factor distribution as a function of the geometric structure of the scene, solar zenith angle, and optical properties of the scene components (leaves and soil). For complete homogeneous vegetation canopies, the principal trend observed at all sun angles and spectral bands is a minimum reflectance near nadir and increasing reflectance with increasing off-nadir view angle for all azimuth directions.

Kimes, D. S.↗
NASA NTRS1993

Galileo photometry of Apollo landing sites

As of December 1992, the Galileo spacecraft performed its second and final flyby (EM2), of the Earth-Moon system, during which it acquired Solid State Imaging (SSI) camera images of the lunar surface suitable for photometric analysis using Hapke's, photometric model. These images, together with those from the first flyby (EM1) in December 1989, provide observations of all of the Apollo landing sites over a wide range of photometric geometries and at eight broadband filter wavelengths ranging from 0.41 micron to 0.99 micron. We have completed a preliminary photometric analysis of Apollo landing sites visible in EM1 images and developed a new strategy for a more complete analysis of the combined EM1 and EM2 data sets in conjunction with telescopic observations and spectrogoniometric measurements of returned lunar samples. No existing single data set, whether from spacecraft flyby, telescopic observation, or laboratory analysis of returned samples, describes completely the light scattering behavior of a particular location on the Moon at all angles of incidence (i), emission (e), and phase angles (a). Earthbased telescopic observations of particular lunar sites provide good coverage of incidence nad phase angles, but their range in emission angle is limited to only a few degrees because of the Moon's synchronous rotation. Spacecraft flyby observations from Galileo are now available for specific lunar features at many photometric geometries unobtainable from Earth; however, this data set lacks coverage at very small phase angles (a less than 13 deg) important for distinguishing the well-known 'opposition effect'. Spectrogoniometric measurements from returned lunar samples can provide photometric coverage at almost any geometry; however, mechanical properties of prepared particulate laboratory samples, such as particle compaction and macroscopic roughness, likely differ from those on the lunar surface. In this study, we have developed methods for the simultaneous analysis of all three types of data: we combine Galileo and telescopic observations to obtain the most complete coverage with photometric geometry, and use spectrogoniometric observations of lunar soils to help distinguish the photometric effects of macroscopic roughness from those caused by particle phase function behavior (i.e., the directional scattering properties of regolith particles).

Helfenstein, P.↗
NASA NTRS1999

The MSP 2001 Mars Environmental Compatibility Assessment (MECA)

A chemical analysis of soil-water mixtures and the first microscopic images of martian soil will be among the results to be returned by the Mars Environmental Compatibility Assessment (MECA) payload on the Mars Surveyor Program 2001 Lander. Sponsored by the Human Exploration and Development of Space (HEDS) enterprise, MECA's primary goal is to evaluate potential geochemical and environmental hazards that may confront future martian explorers, and to guide HEDS scientists in the development of high fidelity Mars soil simulants. As a survey of soil properties, the MECA data set will also be rich in information relevant to basic geology, paleoclimate, and exobiology. The integrated MECA payload contains a wet-chemistry laboratory, a microscopy station, an electrometer to characterize the electrostatics of the soil and its environment, and arrays of material patches to study the abrasive and adhesive properties of soil grains. MECA is allocated a mass of 10 kg and a peak power usage of 15 W within an enclosure of 35 x 25 x 15 cm. The Wet Chemistry Laboratory (WCL) consists of four identical cells that will accept samples from surface and subsurface regions accessible to the Lander's robotic arm, mix them with water, and perform extensive analysis of the solution. Ion-selective electrodes and related sensors will evaluate total dissolved solids, redox potential, pH, and the concentration of many soluble ions and gases. Cyclic voltammetry will address oxidants, and anodic stripping voltammetry will probe potentially hazardous trace metals. MECA's microscopy station combines optical and atomic-force microscopy (AFM) in a controlled illumination environment to image dust and soil particles from millimeters to nanometers in size. Careful selection of substrates and an abrasion tool allows experimental study of size distribution, adhesion, abrasion, hardness, color, shape, aggregation, magnetic and other properties. Mounted on the end of the robot arm, MECA's electrometer consists of four types of sensors: an electric field meter, several triboelectricity monitors, an ion gauge, and a thermometer. Tempered only by ultra-violet- light-induced ions and a low-voltage break-down threshold, the dry, cold, dusty martian environment presents an imposing electrostatic hazard to both robots and humans. In addition, the electrostatic environment is key to transport of dust and, consequently, martian meteorology. MECA will also observe natural dust accumulation on engineering materials. Viewed with the robot arm camera, the abrasion and adhesion plates are strategically placed to allow direct observation of the inter-action between materials and soils on a macroscopic scale. Materials of graded hardness are placed directly under the robot arm scoop to sense wear and soil hardness. A second array, placed on the lander deck, is deployed after the dust plume of landing has settled. It can be manipulated in a primitive fashion by the arm, first having dirt deposited on it from the scoop and subsequently shaken clean. Dust accumulation as a function of conductivity, magnetic field strength, and other parameters will be explored. The MECA instruments described above will assess potential hazards that the Martian soil might present to human explorers and their equipment. In addition, MECA will provide information on the composition of ancient surface water environments, observing microscopic evidence of geological (and biological?) processes, inferring soil and dust transport, comminution and weathering mechanisms, and characterizing soil horizons that might be encountered during excavation. Additional information is contained in the original extended abstract.

Hecht, M. H.↗