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NASA NTRS1987

Hemispherical reflectance variations of vegetation canopies and implications for global and regional budget studies

The hemispherical reflectance (HR) variations of vegetation canopies are studied as a function of solar zenith angle, wavelength, and canopy characteristics (leaf area index, leaf orientation distribution, and leaf and soil optical properties). The radiative transfer model of Kimes (1984) is used to explain the radiative transfers that give rise to variations in the HR for various vegetation canopies as a function of sun angle. The results of this model are compared with those calculated from Sellers' (1985) analytical two-stream approximation. It is noted that the findings have significant implications for a wide range of global and regional energy budget studies.

Kimes, D. S.↗

NASA NTRS2007

TRMM-TMI Satellite Observed Soil Moisture and Vegetation Density (1998-2005) Show Strong Connection with El Nino in Eastern Australia

Spatiotemporal patterns in soil moisture and vegetation water content across mainland Australia were investigated from 1998 through 2005, using TRMMITMI passive microwave observations. The Empirical Orthogonal Function technique was used to extract dominant spatial and temporal patterns in retrieved estimates of moisture content for the top 1-cm of soil (theta) and vegetation moisture content (via optical depth tau). The dominant temporal theta and tau patterns were strongly correlated to El Nino/Southern Oscillation (ENSO) in spring (3 = 0.90), and to a progressively lesser extent autumn, summer and winter. The Indian Ocean Dipole (IOD) index also explained part of the variation in spring 8 and z. Cluster analysis suggested that the regions most affected by ENS0 are mainly located in eastern Australia. The results suggest that the drought conditions experienced in eastern Australia since 2000 an clearly expressed in these satellite observations have a strong connection with ENSO patterns.

Liu, Yi↗

NASA NTRS2019

Effects of Low-Shear Simulated Microgravity on Soil Bacterium Pantoea Agglomerans

A major stressor in the space environment is microgravity. Microgravity has profound effects on biological processes that are vital to normal functioning. This is most prevalently seen in microorganisms, which have altered growth rates and increased antibiotic susceptibility in microgravity. This is a concern for both astronauts and plants onboard spacecraft. Pantoea agglomerans is a soil bacterium that has been shown to be a plant growth promoter, plant pathogen, and an opportunistic pathogen to immunocompromised patients. Using the ground based microgravity analog, the Rotary Cell Culture System along with the High Aspect-Ratio Vessel, we analyzed the growth and the antibiotic susceptibility of Pantoea agglomerans grown in simulated microgravity. In certain parameters, we discovered an increased growth rate and no change in the antibiotic susceptibility. We found that there were differences in results when certain aspects of the protocol were altered. Further work will need to be conducted to get a better understanding of the changes in the microorganisms exposed to microgravity.

Microbial growth↗

NASA NTRS1985

Effects of temperature on remotely sensed mineral absorption features

The present paper provides the results from a series of laboratory experiments which were conducted to investigate the variable spectral behavior of diagnostic Fe(++) crystal field absorptions in common rock-forming minerals as a function of temperature. The general goal of the study is to refine existing techniques of mineralogic and chemical characterization, based on specific optical behavior which has been measured and correlated in a systematic way. It is pointed out that the presented work, taken together with a number of recent studies, provides new information on the manner in which specific features of mafic minerals combine in rocks and soil spectra, taking into account also variations of identification and subsequent interpretation as a function of planetary surface temperature. The obtained results are directly applicable to interpretation of remotely sensed data for many solar system objects, particularly Mars, asteroids, the moon, earth, and Mercury.

Singer, R. B.↗

NASA NTRS2020

Gila Water Resources II: Using Earth Observations to Identify Wildfire Impacts on Hydrologic Functions and Recovery in the Gila National Forest

Wildfires have the potential to cause devastating and long-lasting impacts on ecological systems. In the Gila NF, wildfire events have occurred with increasing frequency and severity over recent years. These disturbances such as the historic Whitewater-Baldy Complex Fire (2012) and Silver Fire (2013) have raised concerns over post-fire soil erosion, flooding, debris flows, and vegetation recovery. Understanding the connection between burn events and ecological functions is crucial for developing effective land management practices within the Gila NF that ensure the conservation of the watershed. Our Gila Water Resources II team worked in partnership with the US Department of Agriculture (USDA) US Forest Service’s (USFS) Gila National Forest and Region 3. This project was designed to provide insight into the influence of wildfires on increased flooding events and to determine if restoration efforts in the Gila NF are having a beneficial and noticeable impact on recovery. The goals of this project included generating data-supported end products to inform land management decisions, including the prioritization of specific regions and time scales for post-fire restoration efforts. To understand recovery trends and hydrologic impact in the Gila NF between 2000 and 2020, this project used NASA EO and ancillary data, including, but not limited to, Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), USGS stream gauge data, and data provided by USDA USFS’s Gila National Forest and Region 3.

Water Resources↗

NASA NTRS1992

A model for inferring canopy and underlying soil temperatures from multi-directional measurements

A model is presented of thermal emission from a canopy/soil surface, where the soil and the leaves are at different temperatures, Tg and Tc, respectively. The temperature Tm corresponding to a radiometer reading is given by B sub lambda(Tm) = chi-B sub lambda(Tg) + (1-chi)B sub lambda(Tc), where B sub lambda denotes the Planck blackbody function at wavelength lambda, chi specifies the fraction of the field of view occupied by the soil at a given view direction, and an emissivity of 1.0 is assumed for the plants and the soil. It is observed that at large view zenith angles, only the plants are effectively seen, and therefore Tc can be determined from the observations a large zenith angles, to the extent that such observations are practical. Water stress can produce an increase of chi and thus tends to produce an exaggerated increase in the observed temperature compared to the actual increase in canopy temperature. These effects are analyzed for a simulated soybean canopy.

Otterman, J.↗

NASA NTRS1989

A physical model for predicting bidirectional reflectances over bare soil

While most previous attempts to retrieve soil surface optical property characteristics have proceeded through a fitting of empirical functions to the data, an optimization technique is presently applied to a physically-based surface reflectance model developed for the study of planetary surfaces. This inversion procedure is shown to allow the direct estimation of the single-scattering coefficient, two parameters describing the 'hot spot' phenomenon, and two parameters describing the scattering phase function. A comparison of inversion technique results with both synthetic data and actual observations shows the model to be capable of predicting the observed bidirectional reflectances as well as directional-hemispherical reflectances; it can also build the complete radiance field over the upward hemisphere.

Pinty, Bernard↗

NASA NTRS1995

Use of AIRSAR to identify woody shrub invasion and other indicators of desertification in the Jornada LTER

The replacement of semidesert grassland by woody shrubland is a widespread form of desertification. This change in physiognomy and species composition tends to sharply reduce the productivity of the land for grazing by domestic livestock, increase soil erosion and reduce soil fertility, and greatly alter many other aspects of ecosystem structure and functioning. Remote sensing methods are needed to assess and monitor shrubland encroachment. Detection of woody shrubs at low density would provide a particularly useful baseline on which to access changes, because an initially low shrub density often tends to increase even after cessation of the disturbance (e.g., overgrazing, drought, or fire suppression) responsible for triggering the initial stages of the invasion (Grover and Musick, 1990). Limited success has been achieved using optical remote sensing. In contrast to other forms of desertification, biomass does not consistently decrease with a shift from grassland to shrubland. Estimation of green vegetation amount (e.g., by NDVI) is thus of limited utility, unless the shrubs and herbaceous plants differ consistently in phenology and the area can be viewed during a season when only one of these is green. The objective of this study was to determine if the potential sensitivity of active microwave remote sensing to vegetation structure could be used to assess the degree of shrub invasion of grassland. Polarimetric Airborne Synthetic Aperture Radar (AIRSAR) data were acquired for a semiarid site containing varied mixtures of shrubs and herbaceous vegetation and compared with ground observations of vegetation type and other landsurface characteristics. In this preliminary report we examine the response of radar backscatter intensity to shrub density. The response of other multipolarization parameters will be examined in future work.

Musick, H. Brad↗

NASA NTRS2014

Benchmarking a Soil Moisture Data Assimilation System for Agricultural Drought Monitoring

Despite considerable interest in the application of land surface data assimilation systems (LDAS) for agricultural drought applications, relatively little is known about the large-scale performance of such systems and, thus, the optimal methodological approach for implementing them. To address this need, this paper evaluates an LDAS for agricultural drought monitoring by benchmarking individual components of the system (i.e., a satellite soil moisture retrieval algorithm, a soil water balance model and a sequential data assimilation filter) against a series of linear models which perform the same function (i.e., have the same basic inputoutput structure) as the full system component. Benchmarking is based on the calculation of the lagged rank cross-correlation between the normalized difference vegetation index (NDVI) and soil moisture estimates acquired for various components of the system. Lagged soil moistureNDVI correlations obtained using individual LDAS components versus their linear analogs reveal the degree to which non-linearities andor complexities contained within each component actually contribute to the performance of the LDAS system as a whole. Here, a particular system based on surface soil moisture retrievals from the Land Parameter Retrieval Model (LPRM), a two-layer Palmer soil water balance model and an Ensemble Kalman filter (EnKF) is benchmarked. Results suggest significant room for improvement in each component of the system.

soil moisture↗

NASA NTRS1993

Synergism of active and passive microwave data for estimating bare surface soil moisture

Active and passive microwave sensors were applied effectively to the problem of estimating the surface soil moisture in a variety of environmental conditions. Research to date has shown that both types of sensors are also sensitive to the surface roughness and the vegetation cover. In estimating the soil moisture, the effect of the vegetation and roughness are often corrected either by acquiring multi-configuration (frequency and polarization) data or by adjusting the surface parameters in order to match the model predictions to the measured data. Due to the limitations on multi-configuration spaceborne data and the lack of a priori knowledge of the surface characteristics for parameter adjustments, it was suggested that the synergistic use of the sensors may improve the estimation of the soil moisture over the extreme range of naturally occurring soil and vegetation conditions. To investigate this problem, the backscattering and emission from a bare soil surface using the classical rough surface scattering theory were modeled. The model combines the small perturbation and the Kirchhoff approximations in conjunction with the Peak formulation to cover a wide range of surface roughness parameters with respect to frequency for both active and passive measurements. In this approach, the same analytical method was used to calculate the backscattering and emissivity. Therefore, the active and passive simulations can be combined at various polarizations and frequencies in order to estimate the soil moisture more actively. As a result, it is shown that (1) the emissivity is less dependent on the surface correlation length, (2) the ratio of the backscattering coefficient (HH) over the surface reflectivity (H) is almost independent of the soil moisture for a wide range of surface roughness, and (3) this ratio can be approximated as a linear function of the surface rms height. The results were compared with the data obtained by a multi-frequency radiometer-scatterometer system working at frequencies between 3.0 GHz to 11.0 GHz. The data were acquired over bare soil surfaces with moisture variations due to freezing and thawing and roughness changes due to rain and erosion. The model predictions are shown to be in reasonable agreement with the data. In addition, it was shown that the same ratio when calculated from the data shows almost no dependence on the soil moisture. Finally, a simple technique which combines the backscattering coefficient at HH polarization (active sensing) with the emissivity at H polarization (passive sensing) is suggested for retrieving the soil moisture from bare soil surfaces.

Saatchi, Sasan S.↗

NASA NTRS2012

Finite Element Analysis of Three Methods for Microwave Heating of Planetary Surfaces

In-Situ Resource Utilization will be Ground Breaking technology for sustained exploration of space. Volatiles are present in planetary regolith, but water by far has the most potential for effective utilization. The presence of water at the lunar poles and Mars opens the possibility of using the hydrogen for propellant on missions beyond Earth orbit. Likewise, the oxygen could be used for in-space propulsion for lunar ascent/descent and for space tugs from low lunar orbit to low Earth orbit. Water is also an effective radiation shielding material as well as a valuable expendable (water and oxygen) required for habitation in space. Because of the strong function of water vapor pressure with temperature, heating regolith effectively liberates water vapor by sublimation. Microwave energy will penetrate soil and heat from within, much more efficiently than heating from the surface with radiant heat. This is especially true under vacuum conditions since the heat transfer rate is very low. The depth of microwave penetration is a strong function of the microwave frequency and to a lesser extent on regolith dielectric properties. New methods for delivery of microwaves into lunar and planetary surfaces is being prototyped with laboratory experiments and modeled with COMSOL MultiPhysics. Recent results are discussed.

Ethridge, Edwin↗

NASA NTRS1994

Asymmetry parameters of the phase function for densely packed scattering grains

Spatial correlation among densely packed particles can substantially change their single-scattering properties, thus making questionable the applicability of the independent scattering approximation in calculations of light scattering by planetary regoliths. The same problem arises in geophysics in light scattering computations for snow, frosts, and bare soil. In this paper, we use a dense-medium light-scattering theory based on the introduction of the static structure factor to calculate asymmetry parameters of the phase function for densely packed particles with real refractive indices 1.31 and 1.66, approximating water ice and soil particles, respectively, and imaginary refractive indices 0, 0.01, and 0.3. For sparsely distributed, independently scattering grains, the calculated asymmetry parameters are always positive and always larger than those for densely packed particles. For densely packed grains, the asymmetry parameters may be negative but only for radius-to-wavelength ratios from about 0.1 to about 0.4. With decreasing particle size, the calculated asymmetry parameters tend to zero independently of the compaction state. In the geometrical optics regime, the asymmetry parameters for densely packed scatterers are positive and very close to those for independently scattering grains. These results may have important implications for remote sensing of the Earth and solid planetary surfaces. In particular, it is demonstrated that negative asymmetry parameters derived with some approximate multiple-scattering theories may be physically irrelevant and can be the result of using an inaccurate bidirectional reflection function combined with the ill-conditionally of the inverse scattering problem.

Mishchenko, Michael I.↗

NASA NTRS1994

The response to gravity is correlated with the number of statoliths in Chara rhizoids

In contrast to higher plants, Chara rhizoids have single membrane-bound compartments that appear to function as statoliths. Rhizoids were generated by germinating zygotes of Chara in either soil water (SW) medium or artificial pond water (APW) medium. Differential-interference-contrast microscopy demonstrated that rhizoids form SW-grown plants typically contain 50 to 60 statoliths per cell, whereas rhizoids from APW-grown plants contain 5 to 10 statoliths per cell. Rhizoids from SW are more responsive to gravity than rhizoids from APW because (a) SW rhizoids were oriented to gravity during vertical growth, whereas APW rhizoids were relatively disoriented, and (b) curvature of SW rhizoids was 3 to 4 times greater throughout the time course of curvature. The growth rate of APW rhizoids was significantly greater than that of SW-grown rhizoids. This latter result suggests that APW rhizoids are not limited in their ability for gravitropic curvature by growth and that these rhizoids are impaired in the early stages of gravitropism (i.e. gravity perception). Plants grown in APW appeared to be healthy because of their growth rate and the vigorous cytoplasmic streaming observed in the rhizoids. This study is comparable to earlier studies of gravitropism in starch-deficient mutants of higher plants and provides support for the role of statoliths in gravity perception.

Non-NASA Center↗

NASA NTRSDate not supplied

TIME-SERIES SOIL MOISTURE RETRIEVAL USING S-BAND BACKSCATTER MEASUREMENTS FROM THE SMEX02 CAMPAIGN

S-band observations from NASA’s Passive/Active L/S Band (PALS) radar from theSMEX02 campaign were used to estimate soil moisture. The “alpha”method is applied for this process, in which a time series of ratios of normalized radar cross section values at successive measurements is used to infer the corresponding soil moisture time series given ancillary information on the minimum and maximum soil moisture values expected over the time series. Results are examined as a function of the polarization and crop type. The results show reasonable retrieval performance, indicating the potential of usingS-band observations from the future NASA/ISRO SAR(NISAR)mission.

Dustin Horton↗

NASA NTRS1992

LAI inversion from optical reflectance using a neural network trained with a multiple scattering model

The inversion of the leaf area index (LAI) canopy parameter from optical spectral reflectance measurements is obtained using a backpropagation artificial neural network trained using input-output pairs generated by a multiple scattering reflectance model. The problem of LAI estimation over sparse canopies (LAI < 1.0) with varying soil reflectance backgrounds is particularly difficult. Standard multiple regression methods applied to canopies within a single homogeneous soil type yield good results but perform unacceptably when applied across soil boundaries, resulting in absolute percentage errors of >1000 percent for low LAI. Minimization methods applied to merit functions constructed from differences between measured reflectances and predicted reflectances using multiple-scattering models are unacceptably sensitive to a good initial guess for the desired parameter. In contrast, the neural network reported generally yields absolute percentage errors of <30 percent when weighting coefficients trained on one soil type were applied to predicted canopy reflectance at a different soil background.

Smith, James A.↗

NASA NTRS1977

Effects of soil maturation on grain size-dependence of trapped solar gases

A description is presented of a simple two-part model which relates the retention of solar-wind-implanted noble gases and N in different grain sizes of lunar soils to the maturation level of that soil. It is assumed that concentrations of solar-wind gases are implanted into surfaces of soil grains in inverse proportion to grain diameter and that differences in irradiation probability and surface saturation as a function of grain diameter generally are not a major factor. The model demonstrates that incorporation of a major fraction of this surface-correlated gas into constructional particles such as agglutinates causes much of the gas to become volume-correlated in mature soils. This volume-correlated gas produces a relative enrichment in gas concentrations in coarser grains and a selective enrichment of more retentive gases (e.g., N) over less retentive gases (e.g., He). It is shown that the maturity model plays a major role in determining the complexities of the distribution of solar-wind gases in soils.

Bogard, D. D.↗

NASA NTRS1997

Assay of the Martian Regolith with Neutrons

The purpose of the research is to combine experiments and Monte Carlo transport of neutrons through volume of soil in an attempt to model neutron leakage from planetary surfaces. Emphasis is given to the change of neutron spectra as a function of water content and location. During the first stage of effort, two experiments were conducted in which leakage of neutrons from a Pu-Be source through about 30 g/cm(exp 2) of soil were measured with several counters. A Monte Carlo code, MCNP, has been used to model many of the 100 individual runs of the experiment. Hydrogen is the element that has the most dramatic effect on the neutron spectrum and its effect on the neutron spectrum is almost the same whether it is in the form of water or polyethylene. In order to simulate various water configurations, sheets of polyethylene have been used between layers of soil as well as water in several concentrations up to 18%. Comparison of experimental results to theoretical predictions made with the MCNP code were disappointing for low concentrations of water. We have made extensive calculations to see if room return could be the cause of the discrepancies. Water concentrations of the 'dry' soil were measured by two different laboratories and differed only by 0.5%. We have made calculations to optimize the next experiment and are investigating other methods of determining the water content of 'dry' soil.

Drake, Darrell M.↗

NASA NTRS2023

Towards Soil Moisture Profile Estimation in the Root Zone Using L- and P-Band Radiometer Observations: A Coherent Modelling Approach

Precision irrigation management and crop water stress assessment rely on accurate estimation of root zone soil moisture. However, only the top 5cm soil moisture can be estimated using the two current passive microwave satellite missions, Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP), which operate at L-band (wavelength of ~21cm). Since the contributing depth of the soil to brightness temperature increases with observation wavelength, it is expected that a P-band (wavelength of ~40cm) radiometer could potentially provide soil moisture information from deeper layers of the soil profile. Moreover, by combining both L- and P- bands, it is hypothesized that the soil moisture profile can be estimated even beyond their individual observation depths. The aim of this study was to demonstrate the potential of combined L-band and P-band radiometer observations to estimate the soil moisture profile under flat bare soil using a stratified coherent forward model. Brightness temperature observations at L-band and P-band from a tower based experimental site across a dry (April 2019) and a wet (March 2020) period, covering different soil moisture profile shapes, were used in this study. Results from an initial synthetic study showed that the performance of a combined L-band and P-band approach was better than the performance of using either band individually, with an average depth over which reliable soil moisture profile information could be estimated (i.e. with a target root mean square error (RMSE) of less than 0.04 m3/m3) being 20cm for linear and 15cm for second-order polynomial functions. Other functions were also tested but found to have a poorer performance. Applying the method to the tower-based brightness temperature achieved an average estimation depth of 28cm (20cm) and 5cm (5cm) during the dry and wet periods respectively when using a second-order polynomial (linear) function. These findings highlight the opportunity of a satellite mission with L-band and P-band observations to accurately estimate the soil moisture profile to as deep as 30cm globally.

Foad Brakhasi↗