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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Utilization of Hydrologic Remote Sensing Data in Land Surface Modeling and Data Assimilation: Current Status and Challenges

Recent advances in remote sensing technologies have enabled the monitoring and measurement of the Earth's land surface at an unprecedented scale and frequency. The myriad of these land surface observations must be integrated with the state-of-the-art land surface model forecasts using data assimilation to generate spatially and temporally coherent estimates of environmental conditions. These analyses are of critical importance to real-world applications such as agricultural production, water resources management and flood, drought, weather and climate prediction. This need motivated the development of NASA Land Information System (LIS), which is an expert system encapsulating a suite of modeling, computational and data assimilation tools required to address challenging hydrological problems. LIS integrates the use of several community land surface models, use of ground and satellite based observations, data assimilation and uncertainty estimation techniques and high performance computing and data management tools to enable the assessment and prediction of hydrologic conditions at various spatial and temporal scales of interest. This presentation will focus on describing the results, challenges and lessons learned from the use of remote sensing data for improving land surface modeling, within LIS. More specifically, studies related to the improved estimation of soil moisture, snow and land surface temperature conditions through data assimilation will be discussed. The presentation will also address the characterization of uncertainty in the modeling process through Bayesian remote sensing and computational methods.

Kumar, Sujay V.↗
DOE OSTI2021

Advancing Enhanced Raman Spectroscopy to Detect and Measure NOW Pheromones (CPRB 2022 proposal)

Insect sex pheromones are chemical compounds that insects release to attract their partners over distances of hundreds of meters or even kilometers, in complete darkness and without any audible signals. Use of synthetic forms of key compounds have in some cases become an essential component of monitoring and/or managing key pests of agricultural crops, including navel orangeworm (Amyelois transitella) (NOW) in California tree nuts. These pheromone-based strategies can include monitoring, mating disruption, mass trapping, attract-and-kill and push-pull. There are currently multiple commercially available mating disruption products available for NOW and recent studies have demonstrated that they can be effectively used to reduce crop damage by this pest. Just how mating disruption works is not fully established and likely varies across products and target species. For instance, the extent to which synthetic pheromones compete with natural pheromone is not well understood, or in the case of monitoring, how efficaciously the insect follows the diffusing plumes, especially across large blocks and at plot borders. Furthermore, there may be specific conditions under which poor or impeded diffusion of synthetic pheromone diminishes the disruption effect, which could result in some males effectively locating females for reproduction. At the same time, many commercially available synthetic lures are also available, and growers have been effectively using them to track population development – although the attractive range of these lures remains unclear. That is, while pheromone lures can attract many moths, the relationship between trap capture and local populations, much less crop damage, remains unclear. Regardless of the emission source (aerosol puffers, meso emitters, lures etc.), we currently lack the ability to fully understand how these synthetic pheromone compounds diffuse away from their point-source of emission – and subsequently how this might affect the efficacy of mating disruption and/or the accuracy of monitoring efforts. Raman spectroscopy (RS) may offer a means to detect synthetic pheromone because of its analytical properties and recent technological advancements. In combination with nanostructured probes, RS has a demonstrated capability to detect volatiles at extremely low concentrations. While other methods for detecting pheromones have proven to be successful, such analytical methods like mass spectrometry (MS) gas chromatography (GC) require sampling in the fields and are not real-time. Other methods such as EAG/ EAD are also invasive (use antennas) but are of course valuable. Opto-electronic, micro and nano sensors just recently enticed interest. We fall in this latter category, proposing the use of optical spectroscopy (Raman) in a fiber aided by nanostructures to provide a chemical fingerprint without transductions and in real-time (i.e. no sampling). To date, we have been able to generate Raman signatures for the main chemicals in synthetic pheromones (a first for science, to the best of our knowledge), observe their trends at different concentrations, and also provide a clear distinction of such signatures in mixed samples via Principal Component Analysis (PCA) – all of which strengthens our conclusions on the ability of RS to detect emissions in more realistic conditions. We also established processes to enhance the detection sensitivity via preconcentration with Solid Phase Micro Extraction (SPME) fibers and Surface Enhanced Raman Spectroscopy (SERS) to increase the overall optical signals. Furthermore, we explored limitations and requirements for detecting from dispensers, lures, or live moths, including Dept. of Energy and CA State regulatory approvals. Finally, we setup some of our first “orchard in a box” experiments to measure pheromone diffusion along with developing appropriate models.

42 ENGINEERING↗
DOE OSTI2021

Biofouling of filtration membranes in wastewater reuse: In situ visualization with confocal laser scanning microscopy

The filtration membranes utilized in advanced treatment of municipal wastewater are prone to biological fouling. Permeability loss and water recovery limitations due to fouling necessitate additional pretreatment and membrane cleaning, which raise the cost of water reuse. Better fouling mitigation calls for a deeper understanding of biofilm behavior on water reuse membranes. This study uses confocal microscopy to monitor biofouling under realistic conditions. To simulate water reuse, a miniature flow cell with microfiltration and ultrafiltration membranes was operated under typical filtration conditions using secondary effluent from California's East Bay Municipal Utility District. The growing biofilms were stained for extracellular polymeric substances and live and dead cells, and they were monitored in situ under filtration conditions with a confocal laser scanning microscope to produce 2-D and 3-D images. In situ image series revealed biofilm growth and removal processes including internal and external fouling, extracellular polymeric substance production, wrinkling, delamination, and film re-deposition. Additionally, changes in biofilm morphology between in situ and ex situ images highlighted limitations of ex situ imaging. Here, these results provide insight into the physical and biological mechanisms of biofouling in hopes of informing the development of improved techniques for biofouling mitigation.

ultrafiltration↗
DOE OSTI2020

Assessing atomically thin delta-doping of silicon using mid-infrared ellipsometry

Hydrogen lithography has been used to template phosphine-based surface chemistry to fabricate atomic-scale devices, a process we abbreviate as atomic precision advanced manufacturing (APAM). In this work, we use mid-infrared variable angle spectroscopic ellipsometry (IR-VASE) to characterize single-nanometer thickness phosphorus dopant layers (δ-layers) in silicon made using APAM compatible processes. A large Drude response is directly attributable to theδ-layer and can be used for nondestructive monitoring of the condition of the APAM layer when integrating additional processing steps. Furthermore, the carrier density and mobility extracted from our room temperature IR-VASE measurements are consistent with cryogenic magneto-transport measurements, showing that APAM δ-layers function at room temperature. Finally, the permittivity extracted from these measurements shows that the doping in the APAM δ-layers is so large that their low-frequency in-plane response is reminiscent of a silicide. However, there is no indication of a plasma resonance, likely due to reduced dimensionality and/or low scattering lifetime.

2D material↗
NASA NTRS1991

An overview of Space Communication Artificial Intelligence for Link Evaluation Terminal (SCAILET) Project

A software application to assist end-users of the link evaluation terminal (LET) for satellite communications is being developed. This software application incorporates artificial intelligence (AI) techniques and will be deployed as an interface to LET. The high burst rate (HBR) LET provides 30 GHz transmitting/20 GHz receiving (220/110 Mbps) capability for wideband communications technology experiments with the Advanced Communications Technology Satellite (ACTS). The HBR LET can monitor and evaluate the integrity of the HBR communications uplink and downlink to the ACTS satellite. The uplink HBR transmission is performed by bursting the bit-pattern as a modulated signal to the satellite. The HBR LET can determine the bit error rate (BER) under various atmospheric conditions by comparing the transmitted bit pattern with the received bit pattern. An algorithm for power augmentation will be applied to enhance the system's BER performance at reduced signal strength caused by adverse conditions.

Shahidi, Anoosh K.↗
NASA NTRS2002

Flight Evaluation of the Army/NASA Variable Stability Fly-by-Wire Rotorcraft Aircrew Systems Concept Airborne Laboratory (RASCAL) JUH-60A

NASA Ames Research Center and the U.S. Army Aeroflight dynamics Directorate (AFDD) have performed initial flight evaluations of the Research Flight Control System (RFCS) integrated into the Army/NASA Rotorcraft Aircrew Systems Concepts Airborne Laboratory (RASCAL) JUH-GOA. The highly modified JUH-GOA Black Hawk helicopter is a full authority, high bandwidth, variable stability, in-flight simulator designed to support development of advanced flight control, sensor, and integrated display and control technologies in a fail safe environment. Preparation for flight test required an extensive hazard analysis and ground testing to ensure proper system operation. A hardware in the loop development facility was utilized to evaluate control law stability following software changes, assess servo hardover upset conditions during manual and monitor disengagements and provide pilot familiarization of test techniques and software changes prior to flight. First engagement of the RFCS was conducted on 31 Aug 2001. RFCS transfer system operation, envelope expansion and a limited rate monitor evaluation have been completed with low bandwidth and model following control laws. The presentation will discuss the following - System overview including aircraft modifications and integrated development facilities used with the RASCAL facility. - Preliminary hazard identification and mitigation prior to flight test. - Ground testing used to qualify the RFCS transfer system and verify fault monitor operation. - Flight test results of low-bandwidth and model following control law evaluations including maneuver agility, control limitations, fault monitor reliability, and recovery from manual and monitor disengagement. - Lessons learned including test techniques using a passive three-axis sidearm controller, the value of the development facility in reducing risk and crew coordination issues related to the operation of a full authority, variable stability platform. - Future research and modifications planned for the RASCAL aircraft.

Dave Arterburn↗
NASA NTRSDate not supplied

Enhanced Monitoring and Forecasting of South Asian Air Quality Episodes with Multi-Sensor Satellite Products and Dispersion Modeling

Air pollution and particulates represent a serious environmental, public health, and overarching societal concern in the Hindu Kush Himalaya (HKH) region of south-central Asia, especially during the boreal winter and spring months. Frequent contributors to poor air quality of the region include dust and particulate matter transport from the Middle East region and western India, persistent nocturnal fog and smog during the stable dry monsoon months, and biomass burning during the pre-monsoon months of boreal spring. Nocturnal and multi-day persistent stable fog and smog events can occur during the stable conditions of the dry monsoon months that lead to hazardous visibility reductions (e.g., at major airports such as Delhi, India)and poor air quality, particularly in urban corridors.Our project goal is therefore to design and implement a robust air quality and chemistry observation and modeling system using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) and the Weather Research and Forecasting coupled with Chemistry (WRF-Chem) models. This system effectively assimilates aerosol and trace gas retrievals from geostationary and polar-orbiting satellites to advance the monitoring and prediction capabilities of air quality and visibility reductions throughout the HKH region. For this presentation, we highlight several[multi-spectral] geostationary satellite products and dispersion modeling capabilities being developed and implemented for improved situational awareness and forecasting of air quality episodes.Launched in December 2018, the Advanced Meteorological Imager (AMI) aboard the Geostationary-Korean Multi-Purpose Satellite-2A (GEO-KOMPSAT-2A, or GK2A) provides 16 channels of multi-spectral information similar to the U.S. GOES-16/17 satellites. Proven community recipes for generating multi-spectral Red-Green-Blue (RGB) composite products to detect specific meteorological phenomena are applied to the AMI data for the HKH region. We implemented four such RGB products consisting of truecolor with Rayleigh correction to aid in smoke detection; dust RGB for monitoring larger particulate matter; nighttime microphysics for fog/smog detection;and natural color fire RGB and the shortwave 3.8 micron channel for fire hot-spot detection.We additionally configured HYSPLIT for dust/sand dispersion and concentration forecasts over HKH. The HYSPLIT dispersion simulations are initially being conducted with two different methodologies: (1) dust/sand lofting based on initializing plume releases from visual inspection of the dust RGB imagery; and (2) dust/sand release and dispersion using the internal HYSPLIT algorithm that determines lofting from input wind speeds and prescribed land use. The goal is to develop a near real-time HYSPLIT modeling solution for routinely simulating the transport and dispersion of dust plumes across the HKH region. This presentation illustrates these products and capabilities for various use cases from the 2019 to 2021 period, highlighting a particularly unhealthy episode during late March 2021 across Nepal.

Remote Sensing↗
NASA NTRS2023

Using Orbiting Carbon Observatory-2 (OCO-2) column CO2 retrievals to rapidly detect and estimate biospheric surface carbon flux anomalies

The global carbon cycle is experiencing continued perturbations via increases in atmospheric carbon concentrations, which are partly reduced by terrestrial biosphere and ocean carbon uptake. Greenhouse gas satellites have been shown to be useful in retrieving atmospheric carbon concentrations and observing surface and atmospheric CO2 seasonal-to-interannual variations. However, limited attention has been placed on using satellite column CO2 retrievals to evaluate surface CO2 fluxes from the terrestrial biosphere without advanced inversion models at low latency. Such applications could be useful to monitor, in near real time, biosphere carbon fluxes during climatic anomalies like drought, heatwaves, and floods, before more complex terrestrial biosphere model outputs and/or advanced inversion modelling estimates become available. Here, we explore the ability of Orbiting Carbon Observatory-2 (OCO-2) column-averaged dry air CO2 (XCO2) retrievals to directly detect and estimate terrestrial biosphere CO2 flux anomalies using a simple mass-balance approach. An initial global analysis of surface–atmospheric CO2 coupling and transport conditions reveals that the western US, among a handful of other regions, is a feasible candidate for using XCO2 for detecting terrestrial biosphere CO2 flux anomalies. Using the CarbonTracker model reanalysis as a test bed, we first demonstrate that a well-established mass-balance approach can estimate monthly surface CO2 flux anomalies from XCO2 enhancements in the western United States. The method is optimal when the study domain is spatially extensive enough to account for atmospheric mixing and has favorable advection conditions with contributions primarily from one background region. We find that errors in individual soundings reduce the ability of OCO-2 XCO2 to estimate more frequent, smaller surface CO2 flux anomalies. However, we find that OCO-2 XCO2 can often detect and estimate large surface flux anomalies that leave an imprint on the atmospheric CO2 concentration anomalies beyond the retrieval error/uncertainty associated with the observations. OCO-2 can thus be useful for low-latency monitoring of the monthly timing and magnitude of extreme regional terrestrial biosphere carbon anomalies.

Andrew F. Feldman↗
NASA NTRS2010

Satellite Gravimetry Applied to Drought Monitoring

Near-surface wetness conditions change rapidly with the weather, which limits their usefulness as drought indicators. Deeper stores of water, including root-zone soil wetness and groundwater, portend longer-term weather trends and climate variations, thus they are well suited for quantifying droughts. However, the existing in situ networks for monitoring these variables suffer from significant discontinuities (short records and spatial undersampling), as well as the inherent human and mechanical errors associated with the soil moisture and groundwater observation. Remote sensing is a promising alternative, but standard remote sensors, which measure various wavelengths of light emitted or reflected from Earth's surface and atmosphere, can only directly detect wetness conditions within the first few centimeters of the land s surface. Such sensors include the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) C-band passive microwave measurement system on the National Aeronautic and Space Administration's (NASA) Aqua satellite, and the combined active and passive L-band microwave system currently under development for NASA's planned Soil Moisture Active Passive (SMAP) satellite mission. These instruments are sensitive to water as deep as the top 2 cm and 5 cm of the soil column, respectively, with the specific depth depending on vegetation cover. Thermal infrared (TIR) imaging has been used to infer water stored in the full root zone, with limitations: auxiliary information including soil grain size is required, the TIR temperature versus soil water content curve becomes flat as wetness increases, and dense vegetation and cloud cover impede measurement. Numerical models of land surface hydrology are another potential solution, but the quality of output from such models is limited by errors in the input data and tradeoffs between model realism and computational efficiency. This chapter is divided into eight sections, the next of which describes the theory behind satellite gravimetry. Following that is a summary of the GRACE mission and how hydrological information is gleaned from its gravity products. The fourth section provides examples of hydrological science enabled by GRACE. The fifth and sixth sections list the challenging aspects of GRACE derived hydrology data and how they are being overcome, including the use of data assimilation. The seventh section describes recent progress in applying GRACE for drought monitoring, including the development of new soil moisture and drought indicator products, and that is followed by a discussion of future prospects in satellite gravimetry based drought monitoring.

Rodell, Matthew↗
NASA NTRS1985

Soft X-Ray Telescope (SXRT)

The soft X-ray telescope (SXRT) will provide direct images of the solar corona with spatial resolution of about 1 arcsecond. These images will show the global structure of the corona, the location and area of coronal holes, and the presence of even the smallest active regions and flares. The good spatial resolution will show the fine scale magnetic structure and changes in these phenomena. These observations are essential for monitoring, predicting, and understanding the solar magnetic cycle, coronal heating, solar flares, coronal mass ejections, and the solar wind. These observations complement those of the White Light Coronagraph and Ultra-Violet Coronal Spectrometer; the SXRT will detect active regions and coronal holes near the east limb, thereby giving a week or more of advanced warning for disturbed geomagnetic conditions at Earth. The instrument consists of a grazing incidence collecting mirror with a full disk film camera at the primary focus, and a secondary relay optic that feeds a CCD camera with a field of view about the size of an average active region.

Moore, R. L.↗
NASA NTRS1986

Soft X-ray telescope (SXRT)

The soft X-ray telescope (SXRT) will provide direct images of the solar corona with spatial resolution of about 1 arcsecond. These images will show the global structure of the corona, the location and area of coronal holes, and the presence of even the smallest active regions and flares. The good spatial resolution will show the fine scale magnetic structure and changes in these phenomena. These observations are essential for monitoring, predicting, and understanding the solar magnetic cycle, coronal heating, solar flares, coronal mass ejections, and the solar wind. These observations complement those of the White Light Coronagraph and Ultra-Violet Coronal Spectrometer; the SXRT will detect active regions and coronal holes near the east limb, thereby giving a week or more of advanced warning for disturbed geomagnetic conditions at Earth. The instrument consists of a grazing incidence collecting mirror with a full-disk film camera at the primary focus, and a secondary relay optic that feeds a CCD camera with a field of view about the size of an average active region.

Moore, R.↗
NASA NTRS2004

Oxidation of High-temperature Alloy Wires in Dry Oxygen and Water Vapor

Small diameter wires (150 to 250 microns) of the high temperature alloys Haynes 188, Haynes 230, Haynes 230, Haynes 214, Kanthal Al and PM2000 were oxidized at 1204 C in dry oxygen or 50% H2O /50% O2 for 70 Hours. The oxidation kinetics were monitored using a thermogravimetric technique. Oxide phase composition and morphology of the oxidized wires were determined by X-ray diffraction,field emission scanning electron microscopy, and energy dispersive spectroscopy. The alumina-forming alloys, Kanthal Al and PM2000, out-performed the chromia-forming alloys under this conditions. PM2000 was recommended as the most promising candidate for advanced hybrid seal applications for space reentry control surface seals or hypersonic propulsion system seals. This study also demonstrated that thermogravimetric analysis of small diameter wires is a powerful technique for the study of oxide volatility, oxide adherence, and breakaway oxidation.

Opila, Elizabeth J.↗
NASA NTRS2011

Effects of Hygrothermal Cycling on the Chemical, Thermal, and Mechanical Properties of 862/W Epoxy Resin

The hygrothermal aging characteristics of an epoxy resin were characterized over 1 year, which included 908 temperature and humidity cycles. The epoxy resin quickly showed evidence of aging through color change and increased brittleness. The influence of aging on the material s glass transition temperature (Tg) was evaluated by Differential Scanning Calorimetry (DSC) and Dynamic Mechanical Analysis (DMA). The Tg remained relatively constant throughout the year long cyclic aging profile. The chemical composition was monitored by Fourier Transform Infrared Spectroscopy (FTIR) where evidence of chemical aging and advancement of cure was noted. The tensile strength of the resin was tested as it aged. This property was severely affected by the aging process in the form of reduced ductility and embrittlement. Detailed chemical evaluation suggests many aging mechanisms are taking place during exposure to hygrothermal conditions. This paper details the influence of processes such as: advancement of cure, chemical degradation, and physical aging on the chemical and physical properties of the epoxy resin.

Miller, Sandi G.↗
DOE OSTI2021

Artificial Reasoning System for Symptom-Based Conditional Failure Probability Estimation Using Bayesian Network

Advances in nuclear power technologies require enhanced capabilities for operator advice and autonomous control. One of the first tasks in the development of such capabilities is the formulation of symptom-based conditional failure probabilities for structures, systems, and components (SSCs) of interest, for which the primary goal is to aid plant personnel in deducing the probabilistic performance status of the monitored SSCs and in detecting impending faults/failure. The task of conditional failure probability estimation is a bidirectional inference problem and shall be logically tackled by the Bayesian network (BN) approach. As a knowledge-based artificial intelligence tool and a probabilistic graphical model, BN offers the capability of reasoning under uncertainty and graphical representation emulating the physical behavior of the target SSC. This paper provides a systematic overview of the BN technique and the software tools for handling implementation of BN models, along with the associated knowledge representation and reasoning paradigm. Both operational data and expert judgement can be readily incorporated into the knowledge base of a BN model. The challenges with data availability are highlighted, and the general approach to target SSC identification is presented. Our focus is upon failure-prone and risk-important balance of plant assets, especially cases having strong operator involvement. An exemplary case study on the failure of a motor-driven centrifugal pump is also conducted to demonstrate the usefulness and technical feasibility of the proposed artificial reasoning system using an expert system shell.

Zhao, Xingang↗
DOE OSTI2024

Photovoltaic Analysis and Response Support (PARS) Platform for Solar Situational Awareness and Resiliency Services

The project's primary objective is to develop a digital-twin based Photovoltaic (PV) Analysis and Response Support (PARS) platform, which aims to provide real-time situational awareness and optimal response plans. This platform is designed to enhance the performance of hybrid PV systems, making them competitive with or even superior to conventional generation resources. The PARS platform enabled the project team to develop and evaluate an extensive suite of grid support functionalities for the hybrid PV systems to enhance grid performance, across key areas including visibility, dispatchability, security, resilience, and reliability. Given the global push toward achieving 100% clean energy by 2035, there is a significant increase in the integration of inverter-based resources (IBRs) throughout the energy grid. Effectively managing the inherent variability and uncertainty associated with IBRs is crucial for ensuring cost-effectiveness, reliability, and security in both the main grid and islanded microgrids. Constrained to a limited array of IEEE test systems or standard feeder models, traditional IBR modeling struggles to assimilate new field data, accurately reflect system dynamics, and adapt to the evolving energy landscape. In our project, we embraced a Digital Twin (DT) strategy for crafting the PARS platform. A digital twin acts as a precise virtual counterpart of a physical system, built on historical data and continuously honed with real-time insights. This enables the high-fidelity DT to accurately mirror current system operations and forecast future scenarios. Consequently, the PARS platform becomes an ideal environment for testing and refining monitoring, control, power, and energy management algorithms designed to boost hybrid PV system performance. The defining feature of the PARS platform, distinguishing it from other advanced simulation tools, is its exceptional adaptability. This is achieved by employing actual network topologies and utilizing real-time field data for fine-tuning and calibration, ensuring a close emulation of real-world conditions. The project deliverables include: 1) High-fidelity IBR models and tools for real-time parameterization, utilizing real-time field measurements to refine IBR models for enhanced accuracy and performance; 2) Grid-forming and Grid-following capabilities to deliver resilience services, including blackstart, voltage and frequency support, cold-load pick-up, power reserves, and three-phase load balancing across grid-connected and microgrid settings; 3) Machine learning-based forecasting tools and methods for generating synthetic data and topologies, creating diverse and realistic simulation environments for evaluating varied operational scenarios; 4) Advanced microgrid power and energy management algorithms for optimizing the integration and operation of PV, storage, and demand response resources within both feeder and community scales. The power grid data sets are provided by four utility companies in North Carolina and the New York Power Administration. Acting as industry advisors, our industry partners communicated stakeholder needs and regulatory standards to the research teams, aiding technology transfer by incorporating the developed methodologies into their daily operations. This collaboration ensures that the PARS platform, functioning as a power system digital twin, enhances our understanding of IBR dynamic behaviors and enables the development and evaluation of IBR control functions that match or exceed the capabilities of conventional synchronous generators.

14 SOLAR ENERGY↗
DOE OSTI2025

Boiler Health Monitoring Using a Hybrid First Principles-Artificial Intelligence Model

Due to increased penetration of the intermittent renewables to the grid, pulverized coal (PC) plants are being forced to cycle their load frequently and rapidly, operate at low load condition for sustained period, and start up and shut down several hundred times in a year in the worst case. These severe operations are causing substantial damage to the boiler components compromising the reliability of PC plants. An online health monitoring tool can be instrumental in understanding the impacts of load-following and can eventually help PC plants to develop advanced process control strategies for improved flexibility without compromising safety nor reliability.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS1995

Toward Soil Spatial Information Systems (SSIS) for global modeling and ecosystem management

The general objective is to conduct research to contribute toward the realization of a world soils and terrain (SOTER) database, which can stand alone or be incorporated into a more complete and comprehensive natural resources digital information system. The following specific objectives are focussed on: (1) to conduct research related to (a) translation and correlation of different soil classification systems to the SOTER database legend and (b) the inferfacing of disparate data sets in support of the SOTER Project; (2) to examine the potential use of AVHRR (Advanced Very High Resolution Radiometer) data for delineating meaningful soils and terrain boundaries for small scale soil survey (range of scale: 1:250,000 to 1:1,000,000) and terrestrial ecosystem assessment and monitoring; and (3) to determine the potential use of high dimensional spectral data (220 reflectance bands with 10 m spatial resolution) for delineating meaningful soils boundaries and conditions for the purpose of detailed soil survey and land management.

Baumgardner, Marion F.↗
NASA NTRS1995

Sensor Systems for Space Life Sciences

Sensors 2000! (S2K!) is a NASA Ames Research Center engineering initiative designed to provide biosensor and bio-instrumentation systems technology expertise to NASA's life sciences spaceflight programs. S2K! covers the full spectrum of sensor technology applications, ranging from spaceflight hardware design and fabrication to advanced technology development, transfer and commercialization. S2K! is currently developing sensor systems for space biomedical applications on BION (a Russian biosatellite focused on Rhesus Monkey physiology) and NEUROLAB (a Space Shuttle flight devoted to neuroscience). It's Advanced Technology Development-Biosensors (ATD-B) project focuses efforts in five principle areas: biotelemetry Systems, chemical and biological sensors, physiological sensors, advanced instrumentation architectures, and data and information management. Technologies already developed and tested included, application-specific sensors, preamplifier hybrids, modular programmable signal conditioners, power conditioning and distribution systems, and a fully implantable dual channel biotelemeter. Systems currently under development include a portable receiver system compatible with an off-the-shelf analog biotelemeter, a 4 channel digital biotelemetry system which monitors pH, a multichannel, g-processor based PCM biotelemetry system, and hand-held personal monitoring systems. S2K! technology easily lends itself to telescience and telemedicine applications as a front-end measurement and data acquisition device, suitable for obtaining and configuring physiological information, and processing that information under control from a remote location.

Somps, Chris J.↗