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NASA NTRS2004

Harnessing Systems Engineering Methodology in Using Earth Science Research Data for Real Applications

For the last three decades, Earth science remote sensing technologies have been providing an enormous amount of useful data and information serving to broaden our understanding of the home planet as a system. NASA's Earth science program has deployed about 18 complex satellites and is in the process of defining and launching multiple observing systems in this decade. At the same time, the European Community and many other countries such as Russia, France, India, Japan, and China have also significantly contributed to Earth science research. To date, the majority of such efforts have concentrated on expanding our scientific understanding of the multiple nonlinear and chaotic processes of Earth's behavior. In recent years, legislators and stakeholders have put serious pressure on the science community to devote more attention to making use of scientific results for societal benefit. For instance, there are a number of areas such as energy forecasting, aviation safety, agricultural efficiency, disaster management, air quality and public health that can directly take advantage of Earth science results to analyze and predict large scale problems and conditions. This is becoming even more important now that we live in a global economy interconnected via the internet and transportation systems; regional environmental conditions can have far reaching impact across continental boundaries. These factors dictate requirements for global data that can help us assess and control the devastating problems of famine, water resources, wildfires, human health and more. To do this requires a serious, organized, and systematic approach that transfers fundamental research products to the applied sciences domain. This paper presents a systems engineering and management process that can effectively make such transfer of data to the user community. Examples are presented on how the above decision making framework can help in solving critical problems such as the spread of vector borne diseases, forecasts of harmful algal blooms as well as forest fires and wildfires, and the intercontinental transport of dust storms and pollution.

Habib, Shahid↗

DOE OSTI2022

Technical Performance and Cost Optimization of Unobtrusive Multi-static Serial LiDAR Imager (UMSLI) for Wide-area Surveillance and Identification of Marine Life at Marine Energy Installations

Florida Atlantic University developed an underwater optical monitoring system prototype - Unobtrusive Multi-static Serial LiDAR Imager (UMSLI) - suitable for marine energy full project lifecycle observation (baseline, commissioning, and decommissioning), with an automated real-time classification of marine animals. With precursor 2014 DOE funding (award DE-EE0006787), a prototype UMSLI was demonstrated in a controlled laboratory environment and achieved a TRL 6. This EERE DE-EE0007828 award aimed to both increase the TRL of the UMSLI by improving the technology performance (e.g., increase distance of marine animal target detection capability, add additional species classification capabilities, improve the system performance during the day, etc.) and reduce the cost. The UMSLI presents a novel application of underwater distributed Light Detection And Ranging (LiDAR), an advanced remote sensing method that uses light in the form of laser pulses for an application, this paired with an algorithm provides 360 degrees underwater detection, imaging, and classification of marine life. This solution for underwater monitoring of biota preserves the advantages of traditional optical and acoustic solutions while overcoming many associated disadvantages for marine energy site environmental monitoring, such as difficulties in species detection and classification in low light or night and turbid environments. This new approach is a purposefully designed, reconfigurable adaptation of an existing class 3B laser technology into one UMSLI instrument that can be easily mounted on or around different classes of marine energy equipment, such as devices to capture ocean current energy or wave energy. The system uses relatively low average power, utilizes far-red (> 635nm) laser illumination to be invisible and eye-safe to marine animals, is compact, and cost-effective. The equipment is designed for long-term, maintenance-free operations (i.e., current design is targeting more than 7 days continuous operation), to inherently generate a sparse primary dataset that only includes detected anomalies, and to allow robust real-time automated animal classification and identification with a low data bandwidth requirement. The technology’s overarching goal for application, is a system that can be deployed to collect pre-installation baseline species observations at a proposed marine energy deployment site with minimal post-processing overhead. The envisioned system will also produce high-resolution imagery of marine animals through a wide range of conditions and support automated tracking and notification of the presence of managed animals within established perimeters of marine energy equipment to satisfy deployed marine energy projects’ endangered and threatened species monitoring requirements. Through the current project, we demonstrated the UMSLI prototype in an operational environment and increased the UMSLI’s Technology Readiness Level from 6 to 7. The project resulted in many novel technologies, including: 1) an eye-safe red laser based, low-cost LiDAR system that can detect targets up to 10 meters distance; 2) the GAN-based machine learning underwater LiDAR image enhancement technique (this is the first known application of GAN technique in underwater LiDAR); 3) LiDAR-based real-time automated detection capabilities; and 4) a template matching based automated classification tool. These technologies build a solid foundation for future efforts to develop an extended range electro-optical monitoring system suitable for marine energy deployments. In addition to technology development, a key lesson learned is that addressing regulatory and safety requirements must be front and center in any marine energy monitoring applications.

16 TIDAL AND WAVE POWER↗

NASA NTRS2012

Recent Upgrades to NASA SPoRT Initialization Datasets for the Environmental Modeling System

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed several products for its National Weather Service (NWS) partners that can initialize specific fields for local model runs within the NOAA/NWS Science and Training Resource Center (STRC) Environmental Modeling System (EMS). In last year's NWA abstract on this topic, the suite of SPoRT products supported in the STRC EMS was presented, which includes a Sea Surface Temperature (SST) composite, a Great Lakes sea-ice extent, a Green Vegetation Fraction (GVF) composite, and NASA Land Information System (LIS) gridded output. This abstract and companion presentation describes recent upgrades made to the SST and GVF composites, as well as the real-time LIS runs. The Great Lakes sea-ice product is unchanged from 2011. The SPoRT SST composite product has been expanded geographically and as a result, the resolution has been coarsened from 1 km to 2 km to accommodate the larger domain. The expanded domain covers much of the northern hemisphere from eastern Asia to western Europe (0 N to 80 N latitude and 150 E to 10 E longitude). In addition, the NESDIS POES-GOES product was added to fill in gaps caused by the Moderate Resolution Imaging Spectroradiometer (MODIS) being unable to sense in cloudy regions, replacing the recently-lost Advanced Microwave Scanning Radiometer for EOS with negligible change to product fidelity. The SST product now runs twice per day for Terra and Aqua combined data collections from 0000 to 1200 UTC and from 1200 to 0000 UTC, with valid analysis times at 0600 and 1800 UTC. The twice-daily compositing technique reduces the overall latency of the previous version while still representing the diurnal cycle characteristics. The SST composites are available at approximately four hours after the end of each collection period (i.e. 1600 UTC for the nighttime analysis and 0400 UTC for the daytime analysis). The real-time MODIS GVF composite has only received minor updates in the past year. The domain was expanded slightly to extend further west, north, and east to improve coverage over parts of southern Canada. Minor adjustments were also made to the manner in which GVF is calculated from the distribution of maximum Normalized Difference Vegetation Index from MODIS. The presentation will highlight some examples of the substantial inter-annual change in GVF that occurred from 2010 to 2011 in the U.S. Southern Plains as a result of the summer 2011 drought, and the early vegetation green up across the eastern U.S. due to the very warm conditions in March 2012. Finally, the SPoRT LIS runs the operational Noah land surface model (LSM) in real time over much of the eastern half of the CONUS. The Noah LSM is continually cycled in real time, uncoupled to any model, and driven by operational atmospheric analyses over a long-term, multi-year integration. The LIS-Noah provides the STRC EMS with high-resolution (3 km) LSM initialization data that are in equilibrium with the operational analysis forcing. The Noah LSM within the SPoRT LIS has been upgraded from version 2.7.1 to version 3.2, which has improved look-up table attributes for several land surface quantities. The surface albedo field is now being adjusted based on the input real-time MODIS GVF, thereby improving the net radiation. Also, the LIS-Noah now uses the newer MODIS-based land use classification scheme (i.e. the International Biosphere-Geosphere Programme [IGBP]) that has a better depiction of urban corridors in areas where urban sprawl has occurred. STRC EMS users interested in initializing their LSM fields with high-resolution SPoRT LIS data should set up their model domain with the MODIS-IGBP 20-class land use database and select Noah as the LSM.

Case, Jonathan L.↗

NASA NTRS1987

Millimeter-wave imaging sensor data evaluation

A passive 3-mm radiometer system with a mechanically scanned antenna was built for use on a small aircraft or an Unmanned Aerial Vehicle to produce real near-real-time, moderate-resolution (0.5) images of the ground. One of the main advantages of this passive imaging sensor is that it is able to provide surveillance information through dust, smoke, fog and clouds when visual and IR systems are unusable. It can also be used for a variety of remote sensing applications, such as measurements of surface moisture, surface temperature, vegetation extent and snow cover. It is also possible to detect reflective objects under vegetation cover.

Wilson, William J.↗

NASA NTRS1994

A low-cost transportable ground station for capture and processing of direct broadcast EOS satellite data

The Earth Observing System (EOS), part of a cohesive national effort to study global change, will deploy a constellation of remote sensing spacecraft over a 15 year period. Science data from the EOS spacecraft will be processed and made available to a large community of earth scientists via NASA institutional facilities. A number of these spacecraft are also providing an additional interface to broadcast data directly to users. Direct broadcast of real-time science data from overhead spacecraft has valuable applications including validation of field measurements, planning science campaigns, and science and engineering education. The success and usefulness of EOS direct broadcast depends largely on the end-user cost of receiving the data. To extend this capability to the largest possible user base, the cost of receiving ground stations must be as low as possible. To achieve this goal, NASA Goddard Space Flight Center is developing a prototype low-cost transportable ground station for EOS direct broadcast data based on Very Large Scale Integration (VLSI) components and pipelined, multiprocessing architectures. The targeted reproduction cost of this system is less than $200K. This paper describes a prototype ground station and its constituent components.

Davis, Don↗

NASA NTRS2004

Adaptive Bio-Inspired Wireless Network Routing for Planetary Surface Exploration

Wireless mobile networks suffer connectivity loss when used in a terrain that has hills, and valleys when line of sight is interrupted or range is exceeded. To resolve this problem and achieve acceptable network performance, we have designed an adaptive, configurable, hybrid system to automatically route network packets along the best path between multiple geographically dispersed modules. This is very useful in planetary surface exploration, especially for ad-hoc mobile networks, where computational devices take an active part in creating a network infrastructure, and can actually be used to route data dynamically and even store data for later transmission between networks. Using inspiration from biological systems, this research proposes to use ant trail algorithms with multi-layered information maps (topographic maps, RF coverage maps) to determine the best route through ad-hoc network at real time. The determination of best route is a complex one, and requires research into the appropriate metrics, best method to identify the best path, optimizing traffic capacity, network performance, reliability, processing capabilities and cost. Real ants are capable of finding the shortest path from their nest to a food source without visual sensing through the use of pheromones. They are also able to adapt to changes in the environment using subtle clues. To use ant trail algorithms, we need to define the probability function. The artificial ant is, in this case, a software agent that moves from node to node on a network graph. The function to calculate the fitness (evaluate the better path) includes: length of the network edge, the coverage index, topology graph index, and pheromone trail left behind by other ant agents. Each agent modifies the environment in two different ways: 1) Local trail updating: As the ant moves between nodes it updates the amount of pheromone on the edge; and 2) Global trail updating: When all ants have completed a tour the ant that found the shortest route updates the edges in its path.

Alena, Richard I.↗

NASA NTRS2011

Near-Real Time Data for Space Weather Analyses: Present Status and Future

Assessments of the present state and future evolution of the space environment heavily relies on timely access to appropriate environmental measurements. These, near real-time (nrt), measurements provide a direct assessment of local or remote space environment conditions, they contribute to a more global description of Space Weather parameters through assimilative models, and they provide essential input into forecasting models. Unlike meteorology, however, the provision of these data is not a mainstream activity in the sense that critical space environment data are often derived from research rather than operational sensors. In addition, space research is a relatively immature field, where SUbstantial gaps in our knowledge impede our ability to optimally use available data streams. In this presentation, we provide examples of presently employed nrt data streams and their utility. We further discuss challenges and opportunities associated with the present approach to space weather forecasting. Finally, an outlook toward the future will be presented.

Hesse, Michael↗

NASA NTRS2021

Bias-Correcting Carbon Fluxes Derived From Land-Surface Satellite Data for Retrospective and Near Real-Time Assimilation Systems

The ability to monitor and understand natural and anthropogenic variability in atmospheric carbon dioxide(CO2) is a growing need of many stakeholders across the world. Systems that assimilate satellite observations, given their short latency and dense spatial coverage, into high resolution global models are valuable, if not essential, tools for addressing this need. A notable drawback of modern assimilation systems is the long latency of many vital in-put datasets, e.g., inventories, in situ measurements, and re-processed remote-sensing data can trail the current date by months to years. This paper describes techniques for bias-correcting surface fluxes derived from satellite observations of the Earth’s surface to be consistent with constraints from inventories and in situ CO2 datasets. The techniques are applicable in both short-term forecasts and retrospective simulations, thus taking advantage of the coverage and short latency of satellite data while reproducing the major features of long-term inventory and in situ records. Our approach begins with a standard collection of diagnostic fluxes which incorporate a variety of remote-sensing driver data, viz. vegetation indices, fire radiative power, and nighttime lights. We then apply an empirical sink so that global budgets of the diagnostic fluxes match given atmospheric and oceanic growth rates for each year. This step removes coherent, systematic flux errors that produce biases inCO2which mask the signals an assimilation system hopes to capture. Depending on the simulation mode, the empirical sink uses different choices of atmospheric growth rates: estimates based on observations in retrospective mode and projections based on seasonal fore-casts of sea surface temperature in forecasting mode. The retrospective fluxes, when used in simulations with NASA’s Goddard Earth Observing System (GEOS), reproduce marine boundary layer measurements with comparable skill to those using fluxes from a modern inversion system. The forecasted fluxes show promising accuracy in their application to the analysis of changes in the carbon cycle as they occur.

CO2↗

NASA NTRSDate not supplied

Feasibility of using Low-Cost COTS Sensors for Particulate Monitoring in Space Missions

Real-time measurement of particles suspended in the spacecraft cabin is of great importance to verify that maximum allowable dust concentrations are not exceeded. This is primarily to protect astronaut health, but also has implications for dust-sensitive equipment. Recently, there is growing interest in low-cost commercial off-the-shelf (COTS) particle sensors by air quality researchers for their ability to map concentrations of airborne particulate matter in various terrestrial settings. In addition to low cost (< $2,000), the compact size and minimal weight of these sensors make them a potential choice for space missions. The detection mechanism for these aerosol sensors is typically measurement of light scattered by particles as they flow through a sensing volume. The amount of scattered light for detection depends on the particle size, shape, density, and refractive index of the particle material. Ideally, particle instruments should be calibrated with reference instruments for each different type of aerosol measurement. In this study we review multiple parameters that may impact the performance of state-of-the-art low-cost aerosol sensors. Environmental factors such as temperature, relative humidity, low ambient pressure, radiation and charge environment, partial-gravity and microgravity can affect the accuracy of particle measurements. Characteristics of the dust aerosols including particle size distribution, aerosol composition, refractive index, morphology and concentration levels also affect the measurement accuracy. Finally, we look at these parameters and issues with respect to an example COTS low-cost aerosol sensor. Instrument performance specifications are evaluated, and experiments are performed to measure real-time concentrations of Arizona Road Dust (a terrestrial reference test dust) and lunar dust simulant in a laboratory chamber. Overall, this study provides insight for evaluating spacecraft particulate monitoring technologies and raises questions to be answered before incorporating low-cost COTS sensors in future space missions to dusty destinations.

lunar dust↗

DOE OSTI2021

Label-free DNA biosensing by topological light confinement

Large-area and transparent all-dielectric metasurfaces sustaining photonic bound states in the continuum (BICs) provide a set of fundamental advantages for ultrasensitive biosensing. BICs bridge the gap of large effective mode volume with large experimental quality factor. Relying on the transduction mechanism of reactive sensing principle, herein, we first numerically study the potential of subwavelength confinement driven by topological decoupling from free space radiation for BIC-based biosensing. Then, we experimentally combine this capability with minimal and low-cost optical setup, applying the devised quasi-BIC resonator for PNA/DNA selective biosensing with real-time monitoring of the binding event. A sensitivity of 20 molecules per micron squared is achieved, i.e. ≃0.01 pg. Further enhancement can easily be envisaged, pointing out the possibility of single-molecule regime. This work aims at a precise and ultrasensitive approach for developing low-cost point-of-care tools suitable for routine disease prescreening analyses in laboratory, also adaptable to industrial production control.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2001

Earth Science System of the Future: Observing, Processing, and Delivering Data Products Directly to Users

Advancement of our predictive capabilities will require new scientific knowledge, improvement of our modeling capabilities, and new observation strategies to generate the complex data sets needed by coupled modeling networks. New observation strategies must support remote sensing from a variety of vantage points and will include "sensorwebs" of small satellites in low Earth orbit, large aperture sensors in Geostationary orbits, and sentinel satellites at L1 and L2 to provide day/night views of the entire globe. Onboard data processing and high speed computing and communications will enable near real-time tailoring and delivery of information products (i.e., predictions) directly to users.

Crisp, David↗

NASA NTRS2002

Real Time Monitoring of Flooding from Microwave Satellite Observations

We have developed a new method for making high-resolution flood extent maps (e.g., at the 30-100 m scale of digital elevation models) in real-time from low-resolution (20-70 km) passive microwave observations. The method builds a "flood-potential" database from elevations and historic flood imagery and uses it to create a flood-extent map consistent with the observed open water fraction. Microwave radiometric measurements are useful for flood monitoring because they sense surface water in clear-or-cloudy conditions and can provide more timely data (e.g., compared to radars) from relatively wide swath widths and an increasing number of available platforms (DMSP, ADEOS-II, Terra, NPOESS, GPM). The chief disadvantages for flood mapping are the radiometers' low resolution and the need for local calibration of the relationship between radiances and open-water fraction. We present our method for transforming microwave sensor-scale open water fraction estimates into high-resolution flood extent maps and describe 30-day flood map sequences generated during a retrospective study of the 1993 Great Midwest Flood. We discuss the method's potential improvement through as yet unimplemented algorithm enhancements and expected advancements in microwave radiometry (e.g., improved resolution and atmospheric correction).

Galantowicz, John F.↗

NASA NTRS2011

Flying Unmanned Aircraft: A Pilot's Perspective

The National Aeronautics and Space Administration (NASA) is pioneering various Unmanned Aircraft System (UAS) technologies and procedures which may enable routine access to the National Airspace System (NAS), with an aim for Next Gen NAS. These tools will aid in the development of technologies and integrated capabilities that will enable high value missions for science, security, and defense, and open the door to low-cost, extreme-duration, stratospheric flight. A century of aviation evolution has resulted in accepted standards and best practices in the design of human-machine interfaces, the displays and controls of which serve to optimize safe and efficient flight operations and situational awareness. The current proliferation of non-standard, aircraft-specific flight crew interfaces in UAS, coupled with the inherent limitations of operating UAS without in-situ sensory input and feedback (aural, visual, and vestibular cues), has increased the risk of mishaps associated with the design of the "cockpit." The examples of current non- or sub- standard design features range from "annoying" and "inefficient", to those that are difficult to manipulate or interpret in a timely manner, as well as to those that are "burdensome" and "unsafe." A concerted effort is required to establish best practices and standards for the human-machine interfaces, for the pilot as well as the air traffic controller. In addition, roles, responsibilities, knowledge, and skill sets are subject to redefining the terms, "pilot" and "air traffic controller", with respect to operating UAS, especially in the Next-Gen NAS. The knowledge, skill sets, training, and qualification standards for UAS operations must be established, and reflect the aircraft-specific human-machine interfaces and control methods. NASA s recent experiences flying its MQ-9 Ikhana in the NAS for extended duration, has enabled both NASA and the FAA to realize the full potential for UAS, as well as understand the implications of current limitations. Ikhana is a Predator-B/Reaper UAS, built by General Atomics, Aeronautical Systems, Inc., and modified for research. Since 2007, the aircraft has been flown seasonally with a wing-mounted pod containing an infrared scanner, utilized to provide real-time wildfire geo-location data to various fire-fighting agencies in the western U.S. The multi-agency effort included an extensive process to obtain flight clearance from the FAA to operate under special provisions, given that UAS in general do not fully comply with current airspace regulations (e.g. sense-and-avoid requirements).

Pestana, Mark E.↗

NASA NTRS2021

Algorithm Theoretical Basis Document (ATBD) - Stream Stage Measurements: V2.5.1 Water Level Products from Satellite Radar Altimetry

In response to the 2018 NASA ROSES Applied Sciences/Water Resources (NASA HQ Program Official: Dr. Brad Doorn) call for proposals, the “Integration of Remotely Sensed Streamflow Data into Alaska Water Resource Management Agency Operations” project with Principal Investigator (PI) Jack Eggleston USGS, was successful, and had the ultimate goal of creating a series of remotely sensed or derived Alaska river parameters for integration into NWIS. These parameters included surface water height and average reach surface water slope (from altimetry), average reach width (from Landsat imagery), and an associated river discharge derived via theoretical means. The surface water height products were required to have both archival and near real time components, noting the availability of ~25years of potential measurements, and accepting the temporal resolution (10-35days) of the suite of radar altimeters. Each surface water level product was expected to be a continuous time series of observation with a sufficient accuracy to highlight monthly, seasonal and interannual variation. The designated set of river reaches were chosen for their geographical distribution, their reach width, and the presence of a radar altimeter mission satellite overpass. This document describes the procedure associated with the creation of these altimetric surface water level products and is relevant to product Version 2.5.1 available from the Global Water Monitor (GWM) web portal.

Altimetry↗

NASA NTRSDate not supplied

Air Quality Data Fusion with Sensors, Satellites, and Models

Global forecasting models, satellite remote sensing, and ground-based regulatory and low-cost monitors all have strengths and weaknesses with respect to providing locally relevant information about air quality. This presentation will give a brief overview of these data sources and then discuss a method for combining them via data fusion to support near-real-time air quality estimation and forecasting at sub-city scales. The basic idea behind the approach will be summarized, followed by an update on recent developments towards creating an operational system using Google Earth Engine and on quantifying uncertainties related to data fusion outputs.

Carl Malings↗

DOE OSTI2023

Systems and methods for monitoring fuel cell membrane degradation

Systems and methods for real-time continuous monitoring of fuel cell membrane degradation are provided. At least one microsensor can be used as an inline sensor integrated at the cathode exhaust and/or the anode exhaust of a fuel cell, such as a proton exchange membrane fuel cell (PEMFC)). The microsensor can monitor the PEMFC degradation status by sensing the emission of fluoride.

Dong, Dongmei↗

DOE OSTI2024

Systems and methods for monitoring fuel cell membrane degradation

Dong, Dongmei↗

DOE OSTI2024

Framework of compressive sensing and data compression for 4D-STEM

Four-dimensional Scanning Transmission Electron Microscopy (4D-STEM) is a powerful technique for high-resolution and high-precision materials characterization at multiple length scales, including the characterization of beam-sensitive materials. However, the field of view of 4D-STEM is relatively small, which in absence of live processing is limited by the data size required for storage. Furthermore, the rectilinear scan approach currently employed in 4D-STEM places a resolution- and signal-dependent dose limit for the study of beam sensitive materials. Improving 4D-STEM data and dose efficiency, by keeping the data size manageable while limiting the amount of electron dose, is thus critical for broader applications. Here we introduce a general method for reconstructing 4D-STEM data with subsampling in both real and reciprocal spaces at high fidelity. The approach is first tested on the subsampled datasets created from a full 4D-STEM dataset, and then demonstrated experimentally using random scan in real-space. The same reconstruction algorithm can also be used for compression of 4D-STEM datasets, leading to a large reduction (100 times or more) in data size, while retaining the fine features of 4D-STEM imaging, for crystalline samples.

4D-STEM↗