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All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Evaluating the Use of Remote Sensing Data in the USAID Famine Early Warning Systems Network

The US Agency for International Development (USAID) s Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to food insecurity emergencies on three continents. FEWS NET uses satellite remote sensing and ground observations of rainfall and vegetation in order to provide information on drought, floods and other extreme weather events to decision makers. Previous research has presented results from a professional review questionnaire with FEWS NET expert end-users whose focus was to elicit Earth observation requirements. The review provided FEWS NET operational requirements and assessed the usefulness of additional remote sensing data. Here we analyzed 1342 food security update reports from FEWS NET. The reports consider the biophysical, socioeconomic, and contextual influences on the food security in 17 countries in Africa from 2000-2009. The objective was to evaluate the use of remote sensing information in comparison with other important factors in the evaluation of food security crises. The results show that all 17 countries use rainfall information, agricultural production statistics, food prices and food access parameters in their analysis of food security problems. The reports display large scale patterns that are strongly related to history of the FEWS NET program in each country. We found that rainfall data was used 84% of the time, remote sensing of vegetation 28% of the time, and gridded crop models 10%, reflecting the length of use of each product in the regions. More investment is needed in training personnel on remote sensing products to improve use of data products throughout the FEWS NET system.

Brown, Molly E.↗
NASA NTRS2012

A Computational Methodology for Simulating Thermal Loss Testing of the Advanced Stirling Convertor

The U.S. Department of Energy (DOE) and Lockheed Martin Space Systems Company (LMSSC) have been developing the Advanced Stirling Radioisotope Generator (ASRG) for use as a power system for space science missions. This generator would use two highefficiency Advanced Stirling Convertors (ASCs), developed by Sunpower Inc. and NASA Glenn Research Center (GRC). The ASCs convert thermal energy from a radioisotope heat source into electricity. As part of ground testing of these ASCs, different operating conditions are used to simulate expected mission conditions. These conditions require achieving a particular operating frequency, hot end and cold end temperatures, and specified electrical power output for a given net heat input. In an effort to improve net heat input predictions, numerous tasks have been performed which provided a more accurate value for net heat input into the ASCs, including the use of multidimensional numerical models. Validation test hardware has also been used to provide a direct comparison of numerical results and validate the multi-dimensional numerical models used to predict convertor net heat input and efficiency. These validation tests were designed to simulate the temperature profile of an operating Stirling convertor and resulted in a measured net heat input of 244.4 W. The methodology was applied to the multi-dimensional numerical model which resulted in a net heat input of 240.3 W. The computational methodology resulted in a value of net heat input that was 1.7 percent less than that measured during laboratory testing. The resulting computational methodology and results are discussed.

Reid, Terry V.↗
NASA NTRS2012

Evaluating the Use of Remote Sensing Data in the U.S. Agency for International Development Famine Early Warning Systems Network

The U.S. Agency for International Development (USAID)'s Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to food insecurity emergencies on three continents. FEWS NET uses satellite remote sensing and ground observations of rainfall and vegetation in order to provide information on drought, floods, and other extreme weather events to decision makers. Previous research has presented results from a professional review questionnaire with FEWS NET expert end-users whose focus was to elicit Earth observation requirements. The review provided FEWS NET operational requirements and assessed the usefulness of additional remote sensing data. We analyzed 1342 food security update reports from FEWS NET. The reports consider the biophysical, socioeconomic, and contextual influences on the food security in 17 countries in Africa from 2000 to 2009. The objective was to evaluate the use of remote sensing information in comparison with other important factors in the evaluation of food security crises. The results show that all 17 countries use rainfall information, agricultural production statistics, food prices, and food access parameters in their analysis of food security problems. The reports display large-scale patterns that are strongly related to history of the FEWS NET program in each country. We found that rainfall data were used 84% of the time, remote sensing of vegetation 28% of the time, and gridded crop models 10% of the time, reflecting the length of use of each product in the regions. More investment is needed in training personnel on remote sensing products to improve use of data products throughout the FEWS NET system.

USAID↗
NASA NTRS1994

Sensitivity of Regional Climate to Deforestation in the Amazon Basin

The deforestation results in several adverse effect on the natural environment. The focus of this paper is on the effects of deforestation on land-surface processes and regional climate of the Amazon basin. In general, the effect of deforestation on climate are likely to depend on the scale of the defrosted area. In this study, we are interested in the effects due to deforestation of areas with a scale of about 250 km. Hence, a meso-scale climate model is used in performing numerical experiments on the sensitivity of regional climate to deforestation of areas with that size. It is found that deforestation results in less net surface radiation, less evaporation, less rainfall, and warmer surface temperature. The magnitude of the of the change in temperature is of the order 0.5 C, the magnitudes of the changes in the other variables are of the order of IO%. In order to verify some of he results of the numerical experiments, the model simulations of net surface radiation are compared to recent observations of net radiation over cleared and undisturbed forest in the Amazon. The results of the model and the observations agree in the following conclusion: the difference in net surface radiation between cleared and undisturbed forest is, almost, equally partioned between net solar radiation and net long-wave radiation. This finding contributes to our understanding of the basic physics in the deforestation problem.

Eltahir, Elfatih A. B.↗
NASA NTRS1998

Detecting a Terrestrial Biosphere Sink for Carbon Dioxide: Interannual Ecosystem Modeling for the Mid-1980s

There is considerable uncertainty as to whether interannual variability in climate and terrestrial ecosystem production is sufficient to explain observed variation in atmospheric carbon content over the past 20-30 years. In this paper, we investigated the response of net CO2 exchange in terrestrial ecosystems to interannual climate variability (1983 to 1988) using global satellite observations as drivers for the NASA-CASA (Carnegie-Ames-Stanford Approach) simulation model. This computer model of net ecosystem production (NEP) is calibrated for interannual simulations driven by monthly satellite vegetation index data (NDVI) from the NOAA Advanced Very High Resolution Radiometer (AVHRR) at 1 degree spatial resolution. Major results from NASA-CASA simulations suggest that from 1985 to 1988, the northern middle-latitude zone (between 30 and 60 degrees N) was the principal region driving progressive annual increases in global net primary production (NPP; i.e., the terrestrial biosphere sink for carbon). The average annual increase in NPP over this predominantly northern forest zone was on the order of +0.4 Pg (10 (exp 15) g) C per year. This increase resulted mainly from notable expansion of the growing season for plant carbon fixation toward the zonal latitude extremes, a pattern uniquely demonstrated in our regional visualization results. A net biosphere source flux of CO2 in 1983-1984, coinciding with an El Nino event, was followed by a major recovery of global NEP in 1985 which lasted through 1987 as a net carbon sink of between 0.4 and 2.6 Avg C per year. Analysis of model controls on NPP and soil heterotrophic CO2 fluxes (Rh) suggests that regional warming in northern forests can enhance ecosystem production significantly. In seasonally dry tropical zones, periodic drought and temperature drying effects may carry over with at least a two-year lag time to adversely impact ecosystem production. These yearly patterns in our model-predicted NEP are consistent in magnitude with the estimated exchange of CO2 by the terrestrial biosphere with the atmosphere, as determined by previous isotopic (delta (sup 13 C) convolution analysis. Ecosystem simulation results can help further target locations where net carbon sink fluxes have occurred in the past or may be verified in subsequent field studies.

Potter, Christopher S.↗
NASA NTRS1989

Cyclic variations in nitrogen uptake rate of soybean plants: ammonium as a nitrogen source

When NO3- is the sole nitrogen source in flowing solution culture, the net rate of nitrogen uptake by nonnodulated soybean (Glycine max L. Merr. cv Ransom) plants cycles between maxima and minima with a periodicity of oscillation that corresponds with the interval of leaf emergence. Since soybean plants accumulate similar quantities of nitrogen when either NH4+ or NO3- is the sole source in solution culture controlled at pH 6.0, an experiment was conducted to determine if the oscillations in net rate of nitrogen uptake also occur when NH4+ is the nitrogen source. During a 21-day period of vegetative development, net uptake of NH4+ was measured daily by ion chromatography as depletion of NH4+ from a replenished nutrient solution containing 1.0 millimolar NH4+. The net rate of NH4+ uptake oscillated with a periodicity that was similar to the interval of leaf emergence. Instances of negative net rates of uptake indicate that the transition between maxima and minima involved changes in influx and efflux components of net NH4+ uptake.

NASA Discipline Life Support Systems↗
NASA NTRS1995

Effect of pH and calcium on short-term NO3- fluxes in roots of barley seedlings

The effect of pH and Ca2+ on net NO3- uptake, influx, and efflux by intact roots of barley (Hordeum vulgare L.) seedlings was studied. Seedlings were induced with NO3- or NO2-. Net NO3- uptake and efflux, respectively, were determined by following its depletion from, and accumulation in, the external solution. Since roots of both uninduced and NO2(-)-induced seedlings contain little internal NO3- initial net uptake rates are equivalent to influx (M. Aslam, R.L. Travis, R.C. Huffaker [1994] Plant Physiol 106: 1293-1301). NO3-, uptake (influx) by these roots was little affected at acidic pH. In contrast, in NO3(-)-induced roots, which accumulate NO3-, net uptake rates decreased in response to acidic pH. Under these conditions, NO3- efflux was stimulated and was a function of root NO3- concentration. Conversely, at basic pH, NO3- uptake by NO3- and NO2(-)-induced and uninduced roots decreased, apparently because of the inhibition of influx. Calcium had little effect on NO3- uptake (influx) by NO2(-)-induced roots at either pH 3 or 6. However, in NO3(-)-induced roots, lack of Ca2+ at pH 3 significantly decreased net NO3- uptake and stimulated efflux. The results indicate that at acidic pH the decrease in net NO3- uptake is due to the stimulation of efflux, whereas at basic pH, it is due to the inhibition of influx.

Non-NASA Center↗
NASA NTRS2008

Famine Early Warning Systems and Remote Sensing Data

This book describes the interdisciplinary work of USAID's Famine Early Warning System Network (FEWS NET) and its influence on how food security crises are identified, documented and the kind of responses that result. The book describes FEWS NET's systems and methods for using satellite remote sensing to identify and describe how biophysical hazards impact the lives and livelihoods of the population where they occur. It presents several illustrative case studies that will demonstrate the integration of both physical and social science disciplines in its work. FEWS NET s operational needs have driven science in biophysical remote sensing applications through its collaboration with the US Geological Survey, the National Aeronautics and Space Administration, National Oceanographic and Atmospheric Administration, and US Department of Agriculture, as well as methodologies in the social science domain through its support of the US Agency for International Development, UNWorld Food Program and numerous international non-governmental organizations such as Save the Children, Oxfam and others. Because FEWS NET is an organization that must provide a global picture of food insecurity to decision makers, the information it relies on are by necessity observable and able to be documented. Thus many aspects of traditional livelihood analysis, for example, cannot be used by FEWS NET as they rely upon relationships, and ways of expressing power and knowledge at the local scale that cannot be easily scaled up to express variations in access to food at a community level. The book focuses on the ways that remote sensing information is transformed into an understanding of the actions that must be taken in order to ensure that lives and livelihoods are protected, including describing the remote sensing observations and models needed to identify hazards and the information gathering requirements and analytical frameworks needed to understand their impact. Its focus is primarily analysis conducted in Africa, but also touches upon FEWS NET s work in Central America, Haiti and Afghanistan. As an organization that seeks to integrate social and physical science methodologies and strategies into its work on a daily basis, it is a fascinating and rich example of interdisciplinary knowledge generation and innovation.

Brown, Molly E.↗
NASA NTRS2012

The Influence of Ozone Precursor Emissions from Four World Regions on Tropospheric Composition and Radiative Climate Forcing

Ozone (O3) precursor emissions influence regional and global climate and air quality through changes in tropospheric O3 and oxidants, which also influence methane (CH4) and sulfate aerosols (SO4 (sup 2-)). We examine changes in the tropospheric composition of O3, CH4, SO4 (sup 2-) and global net radiative forcing (RF) for 20% reductions in global CH4 burden and in anthropogenic O3 precursor emissions (NOx, NMVOC, and CO) from four regions (East Asia, Europe and Northern Africa, North America, and South Asia) using the Task Force on Hemispheric Transport of Air Pollution Source-Receptor global chemical transport model (CTM) simulations, assessing uncertainty (mean plus or minus 1 standard deviation) across multiple CTMs. We evaluate steady state O3 responses, including long-term feedbacks via CH4. With a radiative transfer model that includes greenhouse gases and the aerosol direct effect, we find that regional NOx reductions produce global, annually averaged positive net RFs (0.2 plus or minus 0.6 to 1.7 2 mWm(sup -2)/Tg N yr(sup -1), with some variation among models. Negative net RFs result from reductions in global CH4 (-162.6 plus or minus 2 mWm(sup -2) for a change from 1760 to 1408 ppbv CH4) and regional NMVOC (-0.4 plus or minus 0.2 to 0.7 plus or minus 0.2 mWm(sup -2)/Tg C yr(sup -1) and CO emissions (-0.13 plus or minus 0.02 to -0.15 plus or minus 0.02 mWm(sup-2)/Tg CO yr(sup-1). Including the effect of O3 on CO2 uptake by vegetation likely makes these net RFs more negative by -1.9 to- 5.2 mWm(sup -2)/Tg N yr(sup -1), -0.2 to -0.7 mWm(sup -2)/Tg C yr(sup -1), and -0.02 to -0.05 mWm(sup -2)/ Tg CO yr(sup -1). Net RF impacts reflect the distribution of concentration changes, where RF is affected locally by changes in SO4 (sup -2), regionally to hemispherically by O3, and globally by CH4. Global annual average SO4 2 responses to oxidant changes range from 0.4 plus or minus 2.6 to -1.9 plus or minus 1.3 Gg for NOx reductions, 0.1 plus or minus 1.2 to -0.9 plus or minus 0.8 Gg for NMVOC reductions, and -0.09 plus or minus 0.5 to -0.9 plus or minus 0.8 Gg for CO reductions, suggesting additional research is needed. The 100-year global warming potentials (GWP(sub 100)) are calculated for the global CH4 reduction (20.9 plus or minus 3.7 without stratospheric O3 or water vapor, 24.2 plus or minus 4.2 including those components), and for the regional NOx, NMVOC, and CO reductions (18.7 plus or minus 25.9 to 1.9 plus or minus 8.7 for NOx, 4.8 plus or minus 1.7 to 8.3 plus or minus 1.9 for NMVOC, and 1.5 plus or minus 0.4 to 1.7 plus or minus 0.5 for CO). Variation in GWP(sub 100) for NOx, NMVOC, and CO suggests that regionally specific GWPs may be necessary and could support the inclusion of O3 precursors in future policies that address air quality and climate change simultaneously. Both global net RF and GWP100 are more sensitive to NOx and NMVOC reductions from South Asia than the other three regions.

ozone↗
NASA NTRS1982

Ion extraction capabilities of closely spaced grids

The ion extraction capabilities of accelerator systems with small screen hole diameters (less than 2.0 mm) are investigated at net-accelerating voltages of 100, 300, and 500 V. Results show that the impingement-limited perveance is not dramatically affected by reductions in screen hole diameter to 1.0 mm, but impingement-limited performance was found to be dependent on the grid separation distance, the discharge-to-total accelerating voltage ratio, and the net-to-total accelerating voltage ratio. Results obtained using small hole diameters and closely spaced grids indicate a new mode of grid operation where high current density operation can be achieved with a specified net acceleration voltage by operating the grids at a high rather than low net-to-total acceleration voltage. Beam current densities as high as 25 mA/sq cm were obtained using grids with 1.0 mm diameter holes operating at a net accelerating voltage of 500 V.

Rovang, D. C.↗
NASA NTRS1988

A study of cloud-generated radiative heating and its generation of available potential energy. I - Theoretical background. II - Results for a climatological zonal mean January

The effect of radiative heating and cooling by clouds on the available potential energy (APE) is theoretically discussed. It is shown that the cloud radiative contribution to the generation of APE is determined by the net cloud radiative heating and the efficiency factor, which is a function of the temperature distribution of the atmosphere. Results are presented for low and middle cloud effects for three atmospheric layers. Cloud radiative heating is found to be a single function of cloud optical thickness for all classes designed in terms of cloud top heights and optical thickness. Low clouds at low latitudes destroy APE an midclouds generate APE. A concept is developed to relate the cloud radiative heating to cloud heights and optical depths. Cloud-generated radiative heating is computed for January zonal mean conditions for low and midclouds. For both cases, the strongest influence is found in the low troposphere, with marked differences in signs and magnitudes. At extratropical latitudes, both cloud classes generate net radiative cooling. In the tropics, the effect of low cloud changes from net cooling to the net heating as the optical thickness increases, and midclouds cause net heating. A mechanism is described whereby this dependence produces a strong positive feedback effect on the development of SST anomalies in the tropical oceans.

Stuhlmann, R.↗
NASA NTRS1990

Can the chirality of the ISM be measured

Many moderately complex carbon-based molecules of the type associated with biological systems can exist in one of two mirror-image forms (left-handed and right-handed), which can be distinguished on the basis of their influence on the state of polarization of a light beam. Both forms are possible in nature; yet in living organisms it is invariably the rule that one of these two species predominates. This gives rise to a net chirality. One possible explanation for the net chirality is that the early earth was somehow seeded from the ISM with an excess of chiral organic compounds which led to the development of life forms which are based on left-handed amino acids and right-handed sugars. Molecular spectroscopy of the interstellar medium (ISM) has revealed a complex variety of molecular species similar to those thought to have been available in the oceans and atmospheres of the earth at the time life formed. The detection of such molecules demonstrates the generality of the chemical processes occurring in both environments. If this generality extends to the processes which produce chirality, it may be possible to detect a net chirality in the ISM. This is of particular interest because determining whether or not net chirality exists elsewhere in the universe is an essential aspect of understanding how life developed on earth and how widely distributed it might be. Researchers report preliminary results of a feasibility study to determine whether or not a net chirality in the ISM can be measured. If laboratory results identify candidate chiral molecules that might exist in the ISM, the next step in this feasibility study will be to estimate the detectability of the chiral signature in astrophysical environments.

Pendleton, Y.↗
NASA NTRS1990

Overcoming rule-based rigidity and connectionist limitations through massively-parallel case-based reasoning

Symbol manipulation as used in traditional Artificial Intelligence has been criticized by neural net researchers for being excessively inflexible and sequential. On the other hand, the application of neural net techniques to the types of high-level cognitive processing studied in traditional artificial intelligence presents major problems as well. A promising way out of this impasse is to build neural net models that accomplish massively parallel case-based reasoning. Case-based reasoning, which has received much attention recently, is essentially the same as analogy-based reasoning, and avoids many of the problems leveled at traditional artificial intelligence. Further problems are avoided by doing many strands of case-based reasoning in parallel, and by implementing the whole system as a neural net. In addition, such a system provides an approach to some aspects of the problems of noise, uncertainty and novelty in reasoning systems. The current neural net system (Conposit), which performs standard rule-based reasoning, is being modified into a massively parallel case-based reasoning version.

Barnden, John↗
NASA NTRS1989

Carbon balance and productivity of Lemna gibba, a candidate plant for CELSS

The photosynthesis and productivity of Lemna gibba is analyzed for CELSS based plant growth. Net photosynthesis of Lemna gibba is determined as a function of incident photosynthetic photon flux (PPF), with the light coming from above, below, or from both directions. Light from below is about 75 percent as effective as from above when the stand is sparse, but much less so with dense stands. High rates of photosynthesis are measured at 750 micromol / sq m per sec PPF and 1500 micromol/ mol CO2 at densities up to 660 g fresh weight (FW)/ sq m with young cultures. The analysis includes diagrams illustrating the net photosynthesis response to bilateral lighting of a sparse stand of low assimilate Lemna gibba; the effect of stand density on the net photosynthesis response to bilateral lighting of high assimilate Lemna gibba; the net photosynthesis response to ambient CO2 of sparse stands of Lemna gibba; and the time course of net photosynthesis and respiration per unit chamber and per unit dry weight of Lemna gibba.

Gale, J.↗
NASA NTRS1990

Cloud types and the tropical earth radiation budget

Nimbus-7 cloud and earth radiation budget data are compared in a study of the effects of clouds on the tropical radiation budget. The data consist of daily averages over fixed 500 sq km target areas, and the months of July 1979 and January 1980 were chosen to show the effect of seasonal changes. Six climate regions, consisting of 14 to 24 target areas each, were picked for intensive analysis because they exemplified the range in the tropical cloud/net radiation interactions. It is found that the net radiation is strongly influenced by the average cloud type and amount present, but most net radiation values could be produced by several combinations of cloud types and amount. The regions of highest net radiation (greater than 125 W/sq m) tend to have medium to heavy cloud cover. In these cases, thin medium-altitude clouds predominate. Their cloud tops are normally too warm to be classified as cirrus by the Nimbus cloud algorithm. In the tropical oceans there are large regions where the total regional cloud cover varies from 20 to 90 percent, but with little regional difference in the net radiation. The monsoon and rain areas are high net radiation regions.

Dhuria, Harbans L.↗
NASA NTRS1991

Load limiting energy absorbing lightweight debris catcher

In the representative embodiment of the invention disclosed, a load limiting, energy absorbing net is arranged to overlay a normally-covered vent opening in the rear bulkhead of the space orbiter vehicle. Spatially-disposed flexible retainer straps are extended from the net and respectively secured to bulkhead brackets spaced around the vent opening. The intermediate portions of the straps are doubled over and stitched together in a pattern enabling the doubled-over portions to progressively separate at a predicable load designed to be well below the tensile capability of the straps as the stitches are successively torn apart by the forces imposed on the retainer members whenever the cover plate is explosively separated from the bulkhead and propelled into the net. By arranging these stitches to be successively torn away at a load below the strap strength in response to forces acting on the retainers that are less than the combined strength of the retainers, this tearing action serves as a predictable compact energy absorber for safely halting the cover plate as the retainers are extended as the net is deployed. The invention further includes a block of an energy-absorbing material positioned in the net for receiving loose debris produced by the explosive release of the cover plate.

Kahn, Jon B.↗
NASA NTRS1991

Neural network technologies

A whole new arena of computer technologies is now beginning to form. Still in its infancy, neural network technology is a biologically inspired methodology which draws on nature's own cognitive processes. The Software Technology Branch has provided a software tool, Neural Execution and Training System (NETS), to industry, government, and academia to facilitate and expedite the use of this technology. NETS is written in the C programming language and can be executed on a variety of machines. Once a network has been debugged, NETS can produce a C source code which implements the network. This code can then be incorporated into other software systems. Described here are various software projects currently under development with NETS and the anticipated future enhancements to NETS and the technology.

Villarreal, James A.↗
NASA NTRS1993

Application of neural network to remote sensing of soil moisture using theoretical polarimetric backscattering coefficients

This paper investigates the potential application of neural network to inversion of soil moisture using polarimetric remote sensing data. The neural network used for the inversion of soil parameters is multi-layer perceptron trained with the back-propagation algorithm. The training data include the polarimetric backscattering coefficients obtained from theoretical surface scattering models together with an assumed nominal range of soil parameters which are comprised of the soil permittivity and surface roughness parameters. Soil permittivity is calculated from the soil moisture and the assumed soil texture based on an empirical formula at C-, L-, and P-bands. The rough surface parameters for the soil surface, which is described by the Gaussian random process, are the root-mean-square (rms) height and correlation length. For the rough surface scattering, small perturbation method is used for the L-band frequency, and Kirchhoff approximation is used for the C-band frequency to obtain the corresponding backscattering coefficients. During the training, the backscattering coefficients are the inputs to the neural net and the output from the net are compared with the desired soil parameters to adjust the interconnecting weights. The process is repeated for each input-output data entry and then for the entire training data until convergence is reached. After training, the backscattering coefficients are applied to the trained neural net to retrieve the soil parameters which are compared with the desired soil parameters to verify the effectiveness of this technique. Several cases are examined. First, for simplicity, the correlation length and rms height of the soil surface are fixed while soil moisture is varied. Soil moisture obtained using the neural networks with either L-band or C-band backscattering coefficients for the HH and VV polarizations as inputs is in good agreement with the desired soil moisture. The neural net output matches the desired output for the soil moisture range of 16 to 60 percent for the C-band case. The next case investigated is to vary both soil moisture and rms height while keeping the correlation length fixed. For this case, C-band backscattering coefficients are not sufficient for retrieving two parameters because the Kirchhoff approximation gives the same HH and VV backscattering coefficients. Therefore, the backscattering coefficients at two different frequency bands are necessary to find both the soil moisture and rms height. Finally, the neural nets are also applied to simultaneously invert soil moisture, rms height, and correlation length. Overall, the soil moisture retrieved from the neural network agrees very well with the desired soil moisture. This suggests that the neural network shows potential for retrieval of soil parameters from remote sensing data.

Wang, L.↗