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At least 217 records · Page 12

Remote sensing in Iowa agriculture

The author has identified the following significant results. Results include the estimation of forested and crop vegetation acreages using the ERTS-1 imagery. The methods used to achieve these estimates still require refinement, but the results appear promising. Practical applications would be directed toward achieving current land use inventories of these natural resources. This data is presently collected by sampling type surveys. If ERTS-1 can observe this and area estimates can be determined accurately, then a step forward has been achieved. Cost benefit relationship will have to be favorable. Problems still exist in these estimation techniques due to the diversity of the scene observed in the ERTS-1 imagery covering other part of Iowa. This is due to influence of topography and soils upon the adaptability of the vegetation to specific areas of the state. The state mosaic produced from ERTS-1 imagery shows these patterns very well. Research directed to acreage estimates is continuing.

Mahlstede, J. P.↗

Soil Moisture Data Assimilation to Estimate Irrigation Water Use

Knowledge of irrigation is essential to support food security, manage depleting water resources, and comprehensively understand the global water and energy cycles. Despite the importance of understanding irrigation, little consistent information exists on the amount of water that is applied for irrigation. In this study, we develop and evaluate a new method to predict daily to seasonal irrigation magnitude using a particle batch smoother data assimilation approach, where land surface model soil moisture is applied in different configurations to understand how characteristics of remotely sensed soil moisture may impact the performance of the method. The study employs a suite of synthetic data assimilation experiments, allowing for systematic diagnosis of known error sources. Assimilation of daily synthetic soil moisture observations with zero noise produces irrigation estimates with a seasonal bias of 0.66% and a correlation of 0.95 relative to a known truth irrigation. When synthetic observations were subjected to an irregular overpass interval and random noise similar to the Soil Moisture Active Passive satellite (0.04 cm(exp 3) cm(exp -3)), irrigation estimates produced a median seasonal bias of <1% and a correlation of 0.69. When systematic biases commensurate with those between NLDAS‐2 land surface models and Soil Moisture Active Passive are imposed, irrigation estimates show larger biases. In this application, the particle batch smoother outperformed the particle filter. The presented framework has the potential to provide new information into irrigation magnitude over spatially continuous domains, yet its broad applicability is contingent upon identifying new method(s) of determining irrigation schedule and correcting biases between observed and simulated soil moisture, as these errors markedly degraded performance.

R Abolafia-Rosenzweig↗

Estimation of Mass-Loss Rates from Emission Line Profiles in the UV Spectra of Cool Stars

The photon-scattering winds of cool, low-gravity stars (K-M giants and supergiants) produce absorption features in the strong chromospheric emission lines. This provides us with an opportunity to assess important parameters of the wind, including flow and turbulent velocities, the optical depth of the wind above the region of photon creation, and the star's mass-loss rate. We have used the Lamers et al. Sobolev with Exact Integration (SEI) radiative transfer code along with simple models of the outer atmospheric structure to compute synthetic line profiles for comparison with the observed line profiles. The SEI code has the advantage of being computationally fast and allows a great number of possible wind models to be examined. We therefore use it here to obtain initial first-order estimates of the wind parameters. More sophisticated, but more time-consuming and resource intensive calculations will be performed at a later date, using the SEI-deduced wind parameters as a starting point. A comparison of the profiles over a range of wind velocity laws, turbulence values, and line opacities allows us to constrain the wind parameters, and to estimate the mass-loss rates. We have applied this analysis technique (using lines of Mg II, 0 I, and Fe II) so far to four stars: the normal K5-giant alpha Tau, the hybrid K-giant gamma Dra, the K5 supergiant lambda Vel, and the M-giant gamma Cru. We present in this paper a description of the technique, including the assumptions which go into its use, an assessment of its robustness, and the results of our analysis.

Carpenter, K. G.↗

Practical Issues in Implementing Software Reliability Measurement

Many ways of estimating software systems' reliability, or reliability-related quantities, have been developed over the past several years. Of particular interest are methods that can be used to estimate a software system's fault content prior to test, or to discriminate between components that are fault-prone and those that are not. The results of these methods can be used to: 1) More accurately focus scarce fault identification resources on those portions of a software system most in need of it. 2) Estimate and forecast the risk of exposure to residual faults in a software system during operation, and develop risk and safety criteria to guide the release of a software system to fielded use. 3) Estimate the efficiency of test suites in detecting residual faults. 4) Estimate the stability of the software maintenance process.

Nikora, Allen P.↗

Landsat-based multiphase estimation of California's irrigated lands

Currently, inventory of California's irrigated lands is performed on a seven year cycle. Since 1975, the University of California in cooperation with NASA and the California Department of Water Resources has been developing and testing techniques to utilize a Landsat based remote sensing system to produce statewide estimates in a single year. The proposed system utilizes multiphase sampling, stratification and multitemporal Landsat imagery to produce the estimate. Early research concentrated on regional estimates to develop the techniques. This year, an inventory of the entire state of California is being performed. In addition, research on the utilization of digital analysis for estimating irrigated acreage and the determination of specific crop types (manual and digital analysis) is also underway.

Wall, S. L.↗

Safe Upper-Bounds Inference of Energy Consumption for Java Bytecode Applications

Many space applications such as sensor networks, on-board satellite-based platforms, on-board vehicle monitoring systems, etc. handle large amounts of data and analysis of such data is often critical for the scientific mission. Transmitting such large amounts of data to the remote control station for analysis is usually too expensive for time-critical applications. Instead, modern space applications are increasingly relying on autonomous on-board data analysis. All these applications face many resource constraints. A key requirement is to minimize energy consumption. Several approaches have been developed for estimating the energy consumption of such applications (e.g. [3, 1]) based on measuring actual consumption at run-time for large sets of random inputs. However, this approach has the limitation that it is in general not possible to cover all possible inputs. Using formal techniques offers the potential for inferring safe energy consumption bounds, thus being specially interesting for space exploration and safety-critical systems. We have proposed and implemented a general frame- work for resource usage analysis of Java bytecode [2]. The user defines a set of resource(s) of interest to be tracked and some annotations that describe the cost of some elementary elements of the program for those resources. These values can be constants or, more generally, functions of the input data sizes. The analysis then statically derives an upper bound on the amount of those resources that the program as a whole will consume or provide, also as functions of the input data sizes. This article develops a novel application of the analysis of [2] to inferring safe upper bounds on the energy consumption of Java bytecode applications. We first use a resource model that describes the cost of each bytecode instruction in terms of the joules it consumes. With this resource model, we then generate energy consumption cost relations, which are then used to infer safe upper bounds. How energy consumption for each bytecode instruction is measured is beyond the scope of this paper. Instead, this paper is about how to infer safe energy consumption estimations assuming that those energy consumption costs are provided. For concreteness, we use a simplified version of an existing resource model [1] in which an energy consumption cost for individual Java opcodes is defined.

Navas, Jorge↗

An ISRU Propellant Production System to Fully Fuel a Mars Ascent Vehicle

In-Situ Resource Utilization (ISRU) will enable the long term presence of humans beyond low earth orbit. Since 2009, oxygen production from the Mars atmosphere has been baselined as an enabling technology for Mars human exploration by NASA. However, using water from the Martian regolith in addition to the atmospheric CO2 would enable the production of both liquid Methane and liquid Oxygen, thus fully fueling a Mars return vehicle. A case study was performed to show how ISRU can support NASA's Evolvable Mars Campaign (EMC) using methane and oxygen production from Mars resources. A model was built and used to generate mass and power estimates of an end-to-end ISRU system including excavation and extraction water from Mars regolith, processing the Mars atmosphere, and liquefying the propellants. Even using the lowest yield regolith, a full ISRU system would weigh 1.7 mT while eliminating the need to transport 30 mT of ascent propellants from earth.

Mars Surface↗

Estimating a Large Phased Array Antenna Radiation Pattern by Computer Electromagnetic Simulation

The design of a conformal antenna for use on UAV's (Unmanned Aerial Vehicle) and other aircraft can be enhanced with computational electromagnetic modeling to determine the expected radiation patterns of the antenna when mounted on the aircraft. However, detailed simulation of the antenna structure and the aircraft together requires significant computational resources and time which may not be available. This paper details several methods for estimating the radiation pattern of a 50 by 50-element patch antenna. The Conformal Lightweight Antenna Structures for Aeronautical Communication Technologies (CLASACT) Program aims to build and test a 14.25 gigaherz (Ku-band) conformal antenna on a NASA-owned UAV. The antenna is intended for satellite communications and will enable communication between a ground station and a UAV when the separation distance is too great for line-of-sight communication. It is estimated that a 2 degree beamwidth will be necessary, requiring a 50 by 50 array of patch elements. The narrow beamwidth requirement, together with an element spacing of 0.6 lambda means that the array length will be 30 wavelengths, electrically very large. Three methods of varying complexity are described for estimating the total far-field radiation pattern. The results are shown for each method in the form of a normalized power pattern.

Mackenzie, Anne I.↗

Shuttle Debris Impact Tool Assessment Using the Modern Design of Experiments

Computational tools have been developed to estimate thermal and mechanical reentry loads experienced by the Space Shuttle Orbiter as the result of cavities in the Thermal Protection System (TPS). Such cavities can be caused by impact from ice or insulating foam debris shed from the External Tank (ET) on liftoff. The reentry loads depend on cavity geometry and certain Shuttle state variables, among other factors. Certain simplifying assumptions have been made in the tool development about the cavity geometry variables. For example, the cavities are all modeled as shoeboxes , with rectangular cross-sections and planar walls. So an actual cavity is typically approximated with an idealized cavity described in terms of its length, width, and depth, as well as its entry angle, exit angle, and side angles (assumed to be the same for both sides). As part of a comprehensive assessment of the uncertainty in reentry loads estimated by the debris impact assessment tools, an effort has been initiated to quantify the component of the uncertainty that is due to imperfect geometry specifications for the debris impact cavities. The approach is to compute predicted loads for a set of geometry factor combinations sufficient to develop polynomial approximations to the complex, nonparametric underlying computational models. Such polynomial models are continuous and feature estimable, continuous derivatives, conditions that facilitate the propagation of independent variable errors. As an additional benefit, once the polynomial models have been developed, they require fewer computational resources to execute than the underlying finite element and computational fluid dynamics codes, and can generate reentry loads estimates in significantly less time. This provides a practical screening capability, in which a large number of debris impact cavities can be quickly classified either as harmless, or subject to additional analysis with the more comprehensive underlying computational tools. The polynomial models also provide useful insights into the sensitivity of reentry loads to various cavity geometry variables, and reveal complex interactions among those variables that indicate how the sensitivity of one variable depends on the level of one or more other variables. For example, the effect of cavity length on certain reentry loads depends on the depth of the cavity. Such interactions are clearly displayed in the polynomial response models.

DeLoach, R.↗

Evaluation of Satellite-Based Rainfall Estimates in the Lower Mekong River Basin (Southeast Asia)

Satellite-based precipitation is an essential tool for regional water resource applications that requires frequent observations of meteorological forcing, particularly in areas that have sparse rain gauge networks. To fully realize the utility of remotely sensed precipitation products in watershed modeling and decision-making, a thorough evaluation of the accuracy of satellite-based rainfall and regional gauge network estimates is needed. In this study, Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) 3B42 v.7 and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) daily rainfall estimates were compared with daily rain gauge observations from 2000 to 2014 in the Lower Mekong River Basin (LMRB) in Southeast Asia. Monthly, seasonal, and annual comparisons were performed, which included the calculations of correlation coefficient, coefficient of determination, bias, root mean square error (RMSE), and mean absolute error (MAE). Our validation test showed TMPA to correctly detect precipitation or no-precipitation 64.9% of all days and CHIRPS 66.8% of all days, compared to daily in-situ rainfall measurements. The accuracy of the satellite-based products varied greatly between the wet and dry seasons. Both TMPA and CHIRPS showed higher correlation with in-situ data during the wet season (June–September) as compared to the dry season (November–January). Additionally, both performed better on a monthly than an annual time-scale when compared to in-situ data. The satellite-based products showed wet biases during months that received higher cumulative precipitation. Based on a spatial correlation analysis, the average r-value of CHIRPS was much higher than TMPA across the basin. CHIRPS correlated better than TMPA at lower elevations and for monthly rainfall accumulation less than 500 mm. While both satellite-based products performed well, as compared to rain gauge measurements, the present research shows that CHIRPS might be better at representing precipitation over the LMRB than TMPA.

Dandridge, Chelsea↗

A Survey and Evaluation of High Energy Liquid Chemical Propulsion Systems: Propellant Selection Criteria for Space Missions - Part 1

This report presents the results of a study to develop a procedure for evaluating liquid propellants in order (a) to select the most appropriate propellant (from among those under development) for each of several applications on each of the various missions in the NASA program, or (b) to select new propellants (from among those being proposed) for initiation or continuation of research and development. The analysis begins with a consideration of requirements--either for the specific application or for the various classes of applications. The known characteristics of the propellant or propellants to be evaluated are then put into a convenient form for evaluation. The next step is to determine whether or not there are requirements that simply cannot be met by the propellant. If the propellant passes this test, an optimum vehicle configuration using the propellant (and meeting all requirements) is estimated. (The configuration should be optimized with respect to the total resource consumption for all aspects of the mission, including R&D, production, logistics, and operation.) The total resource consumption for this configuration is then compared with that for similar configurations using other propellants (and meeting all requirements equally well). If all factors have been properly taken into account, this comparison of resource consumption will complete the evaluation. Such an evaluation may be performed several times, in increasing detail and with correspondingly increasing accuracy, as an R&D program proceeds, and the accuracy of the data as well as the cost of the next step in the program increase. The procedure is superior to those in common use in that it minimizes both the amount of analytical work and the number of points at which subjective value judgments are made.

LIQUID PROPELLANT↗

Multi-Sensor Remote Sensing of Forest Dynamics in Central Siberia

The forested regions of Siberia, Russia are vast and contain about a quarter of the world's forests that have not experienced harvesting. However, many Siberian forests are facing twin pressures of rapidly changing climate and increasing timber harvest activity. Monitoring the dynamics and mapping the structural parameters of the forest is important for understanding the causes and consequences of changes observed in these areas. Because of the inaccessibility and large extent of this forest, remote sensing data can play an important role for observing forest state and change. In Central Siberia, multi-sensor remote sensing data have been used to monitor forest disturbances and to map above-ground biomass from the Sayan Mountains in the south to the taiga-tundra boundaries in the north. Radar images from the Shuttle Imaging Radar-C (SIR-C)/XSAR mission were used for forest biomass estimation in the Sayan Mountains. Radar images from the Japanese Earth Resources Satellite-1 (JERS-1), European Remote Sensing Satellite-1 (ERS-1) and Canada's RADARSAT-1, and data from ETM+ on-board Landsat-7 were used to characterize forest disturbances from logging, fire, and insect damage in Boguchany and Priangare areas.

Ransom, K. J.↗

Quantifying the Sensitivity of Condition Incidence Parameters in the Evidence Library

One approach to quantifying spaceflight risk at NASA makes use event driven probabilistic techniques. The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is such a tool that estimates medical risk metrics via simulation and enables optimization of medical resources subject to mission constraints [1]. Previous analyses have informed medical set composition, exercise countermeasures, and water intake, where each analysis quantifies the risk associated with proposed variations in system design. As future mission profiles extend beyond Low-Earth Orbit (LEO) and lengthen in duration, understanding these risks and contributing factors is critical. MEDPRAT employs Monte Carlo sampling techniques to simulate missions and track the occurrence of medical events. These events follow fault-tree-like progressions through levels of severity and mitigation via medical treatment to many possible outcomes and these are reported throughout the mission. Making this possible, are the medical databases that contain evidence gathered by the Human Research Program (HRP). Quantifying the impact of uncertainty or variability in the input data is an important step in evaluating the credibility of modeling and simulation results. In this work, we investigate the sensitivity of medical risk metrics with respect to the condition incidence parameters within the Evidence Library (EL) [2] as the medical database input for MEDPRAT. The medical conditions, contained in the EL, are equipped with incidence rates that describe the likelihood that the condition will occur. These incidence rates reflect historical spaceflight data or when appropriate, terrestrial data. In this presentation, we will explore how uncertainty in these rates propagate to the medical risk described by MEDPRAT. These results identify the conditions and parameters with the largest contribution to medical risks.

Ian Lim↗

Extraction of Volatiles from Regolith or Soil on Mars, the Moon, and Asteroids

NASA's Advanced Exploration Systems ISRU Technology Project is evaluating concepts to extract water from all resource types Near-term objectives: Produce high-fidelity mass, power, and volume estimates for mining and processing systems Identify critical challenges for development focus Begin demonstration of component and subsystem technologies in relevant environment Several processor types: Closed processors either partially or completely sealed during processing Open air processors operates at Mars ambient conditions In-situ processors Extract product directly without excavation of raw resource Design features Elimination of sweep gas reduces dust particles in water condensate Pressure maintained by height of soil in hopper Model developed to evaluate key design parameters Geometry: conveyor diameter, screw diameter, shaft diameter, flight spacing and pitch Operational: screw speed vs. screw length (residence time) Thermal: Heat flux, heat transfer to soil Testing to demonstrate feasibility and performance Agglomeration, clogging Pressure rise forced flow to condenser.

Extration↗

Calibration of a turbidity meter for making estimates of total suspended solids concentrations and beam attenuation coefficients in field experiments

Management of water resources such as a reservoir requires using analytical models which describe such parameters as the suspended sediment field. To select or develop an appropriate model requires making many measurements to describe the distribution of this parameter in the water column. One potential method for making those measurements expeditiously is to measure light transmission or turbidity and relate that parameter to total suspended solids concentrations. An instrument which may be used for this purpose was calibrated by generating curves of transmission measurements plotted against measured values of total suspended solids concentrations and beam attenuation coefficients. Results of these experiments indicate that field measurements made with this instrument using curves generated in this study should correlate with total suspended solids concentrations and beam attenuation coefficients in the water column within 20 percent.

Usry, J. W.↗

An efficient sparse matrix multiplication scheme for the CYBER 205 computer

This paper describes the development of an efficient algorithm for computing the product of a matrix and vector on a CYBER 205 vector computer. The desire to provide software which allows the user to choose between the often conflicting goals of minimizing central processing unit (CPU) time or storage requirements has led to a diagonal-based algorithm in which one of four types of storage is selected for each diagonal. The candidate storage types employed were chosen to be efficient on the CYBER 205 for diagonals which have nonzero structure which is dense, moderately sparse, very sparse and short, or very sparse and long; however, for many densities, no diagonal type is most efficient with respect to both resource requirements, and a trade-off must be made. For each diagonal, an initialization subroutine estimates the CPU time and storage required for each storage type based on results from previously performed numerical experimentation. These requirements are adjusted by weights provided by the user which reflect the relative importance the user places on the two resources. The adjusted resource requirements are then compared to select the most efficient storage and computational scheme.

Lambiotte, Jules J., Jr.↗

Have GRACE Satellites Overestimated Groundwater Depletion in the Northwest India Aquifer?

The Northwest India Aquifer (NWIA) has been shown to have the highest groundwater depletion (GWD) rate globally, threatening crop production and sustainability of groundwater resources. Gravity Recovery and Climate Experiment (GRACE) satellites have been emerging as a powerful tool to evaluate GWD with ancillary data. Accurate GWD estimation is, however, challenging because of uncertainties in GRACE data processing. We evaluated GWD rates over the NWIA using a variety of approaches, including newly developed constrained forward modeling resulting in a GWD rate of 3.1 plus or minus 0.1 centimeters per acre (or 14 plus or minus 0.4 cubic kilometers per acre) for Jan 2005-Dec 2010, consistent with the GWD rate (2.8 centimeters per acre or 12.3 cubic kilometers per acre) from groundwater-level monitoring data. Published studies (e.g., 4 plus or minus 1 centimeter per acre or 18 plus or minus 4.4 cubic kilometers per acre) may overestimate GWD over this region. This study highlights uncertainties in GWD estimates and the importance of incorporating a priori information to refine spatial patterns of GRACE signals that could be more useful in groundwater resource management and need to be paid more attention in future studies.

Long, Di↗