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NASA NTRS2018

Northern Hemisphere Surface Freeze-Thaw Product from Aquarius L-Band Radiometers

In the Northern Hemisphere, seasonal changes in surface freeze–thaw (FT) cycles are an important component of surface energy, hydrological and eco-biogeochemical processes that must be accurately monitored. This paper presents the weekly polar-gridded Aquarius passive L-band surface freeze–thaw product (FT-AP) distributed on the Equal-Area Scalable Earth Grid version 2.0, above the parallel 50 N, with a spatial resolution of 36 km36 km. The FT-AP classification algorithm is based on a seasonal threshold approach using the normalized polarization ratio, references for frozen and thawed conditions and optimized thresholds. To evaluate the uncertainties of the product, we compared it with another satellite FT product also derived from passive microwave observations but at higher frequency: the resampled 37 GHz FT Earth Science Data Record (FTESDR). The assessment was carried out during the overlapping period between 2011 and 2014. Results show that 77.1% of their common grid cells have an agreement better than 80 %. Their differences vary with land cover type (tundra, forest and open land) and freezing and thawing periods. The best agreement is obtained during the thawing transition and over forest areas, with differences between product mean freeze or thaw onsets of under 0.4 weeks. Over tundra, FT-AP tends to detect freeze onset 2–5 weeks earlier than FT-ESDR, likely due to FT sensitivity to the different frequencies used. Analysis with mean surface air temperature time series from six in situ meteorological stations shows that the main discrepancies between FT-AP and FT-ESDR are related to false frozen retrievals in summer for some regions with FT-AP. The Aquarius product is distributed by the U.S. National Snow and Ice Data Center (NSIDC) at https://nsidc.org/data/aq3_ft/versions/5 with the DOI https://doi.org/10.5067/OV4R18NL3BQR.

Prince, Michael↗

NASA NTRS1996

Spectral imaging applications: Remote sensing, environmental monitoring, medicine, military operations, factory automation and manufacturing

This paper reviews the activities at OKSI related to imaging spectroscopy presenting current and future applications of the technology. The authors discuss the development of several systems including hardware, signal processing, data classification algorithms and benchmarking techniques to determine algorithm performance. Signal processing for each application is tailored by incorporating the phenomenology appropriate to the process, into the algorithms. Pixel signatures are classified using techniques such as principal component analyses, generalized eigenvalue analysis and novel very fast neural network methods. The major hyperspectral imaging systems developed at OKSI include the Intelligent Missile Seeker (IMS) demonstration project for real-time target/decoy discrimination, and the Thermal InfraRed Imaging Spectrometer (TIRIS) for detection and tracking of toxic plumes and gases. In addition, systems for applications in medical photodiagnosis, manufacturing technology, and for crop monitoring are also under development.

National Defense↗

NASA NTRS2017

Meteoroid Bulk Density and Ceplecha Types

The determination of asteroid bulk density is an important aspect of Near Earth Object (NEO) characterization. A fraction of meteoroids originate from asteroids (including some NEOs), thus in lieu of mutual perturbations, satellites, or expensive spacecraft missions, a study of meteoroid bulk densities can potentially provide useful insights into the densities of NEOs and PHOs (Potentially Hazardous Objects). Meteoroid bulk density is still inherently difficult to measure, and is most often determined by modeling the ablation of the meteoroid. One approach towards determining a meteoroid density distribution entails using a more easily measured proxy for the densities, then calibrating the proxy with known densities from meteorite falls, ablation modelling, and other sources. An obvious proxy choice is the Ceplecha type, KB (Ceplecha, 1958), which is thought to indicate the strength of a meteoroid and often correlated to different bulk densities in literature. KB is calculated using the air density at the beginning height of the meteor, the initial velocity, and the zenith angle of the radiant; quantities more readily determined than meteoroid bulk density itself. Numerical values of K(sub B) are sorted into groups (A, B, C, etc.), which have been matched to meteorite falls or meteor showers with known composition such as the porous Draconids. An extensive survey was conducted to establish the strength of the relationship between bulk density and K(sub B), specifically looking at those that additionally determined K(sub B) for the meteors. In examining the modeling of high-resolution meteor data from Kikwaya et al. (2011), the correlation between K(sub B) and bulk density was not as strong as hoped. However, a distinct split by dynamical type was seen with Jovian Tisserand parameter (T(sub J)), with meteoroids from Halley Type comets (T(sub J) < 2) exhibiting much lower bulk densities than those originating from Jupiter Family comets and asteroids (T(sub J) > 2). Therefore, this work indicates that the dynamical classification of a meteoroid is a better indicator of the density than the strength proxy, a somewhat surprising result.

Blaauw, R. C.↗

NASA NTRS2021

Mapping Boreal Forest Spruce Beetle Health Status at the Individual Crown Scale Using Fused Spectral and Structural Data

The frequency and severity of spruce bark beetle outbreaks are increasing in boreal forests leading to widespread tree mortality and fuel conditions promoting extreme wildfire. Detection of beetle infestation is a forest health monitoring (FHM) priority but is hampered by the challenges of detecting early stage (“green”) attack from the air. There is indication that green stage might be detected from vertical gradients of spectral data or from shortwave infrared information distributed within a single crown. To evaluate the efficacy of discriminating “non-infested”, “green”, and “dead” health statuses at the landscape scale in Alaska, USA, this study conducted spectral and structural fusion of data from: (1) Unoccupied aerial vehicle (UAV) multispectral (6 cm) + structure from motion point clouds (~700 pts per sq. m); and (2) Goddard Lidar Hyperspectral Thermal (G-LiHT) hyperspectral (400 to 1000 nm, 0.5 m) + SWIR-band lidar (~32 pts per sq.m). We achieved 78% accuracy for all three health statuses using spectral + structural fusion from either UAV or G-LiHT and 97% accuracy for non-infested/dead using G-LiHT. We confirm that UAV 3D spectral (e.g., greenness above versus below median height in crown) and lidar apparent reflectance metrics (e.g., mean reflectance at 99th percentile height in crown), are of high value, perhaps capturing the vertical gradient of needle degradation. In most classification exercises, UAV accuracy was lower than G-LiHT indicating that collecting ultra-high spatial resolution data might be less important than high spectral resolution information. While the value of passive optical spectral information was largely confined to the discrimination of non-infested versus dead crowns, G-LiHT hyperspectral band selection (~400, 675, 755, and 940 nm) could inform future FHM mission planning regarding optimal wavelengths for this task. Interestingly, the selected regions mostly did not align with the band designations for our UAV multispectral data but do correspond to, e.g., Sentinel-2 red edge bands, suggesting a path forward for moderate scale bark beetle detection when paired with suitable structural data.

Janice Cessna↗

NASA NTRS2012

The Analysis of the Contribution of Human Factors to the In-Flight Loss of Control Accidents

In-flight loss of control (LOC) is currently the leading cause of fatal accidents based on various commercial aircraft accident statistics. As the Next Generation Air Transportation System (NextGen) emerges, new contributing factors leading to LOC are anticipated. The NASA Aviation Safety Program (AvSP), along with other aviation agencies and communities are actively developing safety products to mitigate the LOC risk. This paper discusses the approach used to construct a generic integrated LOC accident framework (LOCAF) model based on a detailed review of LOC accidents over the past two decades. The LOCAF model is comprised of causal factors from the domain of human factors, aircraft system component failures, and atmospheric environment. The multiple interdependent causal factors are expressed in an Object-Oriented Bayesian belief network. In addition to predicting the likelihood of LOC accident occurrence, the system-level integrated LOCAF model is able to evaluate the impact of new safety technology products developed in AvSP. This provides valuable information to decision makers in strategizing NASA's aviation safety technology portfolio. The focus of this paper is on the analysis of human causal factors in the model, including the contributions from flight crew and maintenance workers. The Human Factors Analysis and Classification System (HFACS) taxonomy was used to develop human related causal factors. The preliminary results from the baseline LOCAF model are also presented.

Ancel, Ersin↗

NASA NTRSDate not supplied

Comparing the Regional Variability of Emission Factors of Greenhouse Gases Over Different Landscape During FIREX-AQ Campaign

Biomass burning (wildfires, prescribed and agricultural burning) is one of the major sources of trace gases and particulate emissions and annual variability in growth rates. Biomass burning can impact local, regional, and global air quality, as well as climate. Measurements of emissions from biomass burning are crucial to a better understanding of how it influences and interacts with biogeochemical cycles. High resolution in-situ measurements were recorded onboard the NASA DC-8 aircraft during the FIREX-AQ (Fire Influence on Regional to Global Environments and Air Quality) airborne field campaign July-September, 2019, which was conducted over the continental U.S. Fire emission factors (EF) are essential input for emissions models used to develop biomass burning emission inventories. Here we present the Emission Ratio (ER), MCE (Modified Combustion Efficiency), and EF (Emission Factor) of CO2, CO, and CH4, which constitute the majority of carbon emitted from the wildland, prescribed, and agricultural fires. EFCO2, EFCO, and EFCH4 from the Wildland fires at Williams Flats, WA (primarily Douglas Fir, Ponderosa pine, wheatgrass: 50-75%), ranged from 1527 – 1820 g/kg (Avg. 1641±42), 6.5 – 174.1 g/kg (110.5±24.1), and 0.7 – 11.3 g/kg (6.2±1.9), respectively. EFs from the Arizona CASTLE fire, with somewhat different fuel sources (primarily Ponderosa pine, Douglas fir: 40-70%) ranged from 1266 – 1667 g/kg (1596±59), 99.5 – 344.5 g/kg (136.7±36.8), and 0.4 – 9.2 g/kg (7.2±1.7), respectively. Another primary driver of EFs is likely fire weather. Detailed variability of greenhouse gas EFs will be examined and presented in accordance with different fuels and fire conditions at burned areas, specifically within unique wildland and croplands, using the FCCS (Fuel Characteristic Classification System) 30m land cover identification and the Cropland Data Layer (CDL).

Biomass burning↗

NASA NTRSDate not supplied

Comparing the regional variability of emission factors of greenhouse gases over different landscape during FIREX-AQ campaign

Biomass burning↗

NASA NTRS2010

Peak Wind Tool for General Forecasting

The expected peak wind speed of the day is an important forecast element in the 45th Weather Squadron's (45 WS) daily 24-Hour and Weekly Planning Forecasts. The forecasts are used for ground and space launch operations at the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The 45 WS also issues wind advisories for KSC/CCAFS when they expect wind gusts to meet or exceed 25 kt, 35 kt and 50 kt thresholds at any level from the surface to 300 ft. The 45 WS forecasters have indicated peak wind speeds are challenging to forecast, particularly in the cool season months of October - April. In Phase I of this task, the Applied Meteorology Unit (AMU) developed a tool to help the 45 WS forecast non-convective winds at KSC/CCAFS for the 24-hour period of 0800 to 0800 local time. The tool was delivered as a Microsoft Excel graphical user interface (GUI). The GUI displayed the forecast of peak wind speed, 5-minute average wind speed at the time of the peak wind, timing of the peak wind and probability the peak speed would meet or exceed 25 kt, 35 kt and 50 kt. For the current task (Phase II ), the 45 WS requested additional observations be used for the creation of the forecast equations by expanding the period of record (POR). Additional parameters were evaluated as predictors, including wind speeds between 500 ft and 3000 ft, static stability classification, Bulk Richardson Number, mixing depth, vertical wind shear, temperature inversion strength and depth and wind direction. Using a verification data set, the AMU compared the performance of the Phase I and II prediction methods. Just as in Phase I, the tool was delivered as a Microsoft Excel GUI. The 45 WS requested the tool also be available in the Meteorological Interactive Data Display System (MIDDS). The AMU first expanded the POR by two years by adding tower observations, surface observations and CCAFS (XMR) soundings for the cool season months of March 2007 to April 2009. The POR was expanded again by six years, from October 1996 to April 2002, by interpolating 1000-ft sounding data to 100-ft increments. The Phase II developmental data set included observations for the cool season months of October 1996 to February 2007. The AMU calculated 68 candidate predictors from the XMR soundings, to include 19 stability parameters, 48 wind speed parameters and one wind shear parameter. Each day in the data set was stratified by synoptic weather pattern, low-level wind direction, precipitation and Richardson Number, for a total of 60 stratification methods. Linear regression equations, using the 68 predictors and 60 stratification methods, were created for the tool's three forecast parameters: the highest peak wind speed of the day (PWSD), 5-minute average speed at the same time (A WSD), and timing of the PWSD. For PWSD and A WSD, 30 Phase II methods were selected for evaluation in the verification data set. For timing of the PWSD, 12 Phase\I methods were selected for evaluation. The verification data set contained observations for the cool season months of March 2007 to April 2009. The data set was used to compare the Phase I and II forecast methods to climatology, model forecast winds and wind advisories issued by the 45 WS. The model forecast winds were derived from the 0000 and 1200 UTC runs of the 12-km North American Mesoscale (MesoNAM) model. The forecast methods that performed the best in the verification data set were selected for the Phase II version of the tool. For PWSD and A WSD, linear regression equations based on MesoNAM forecasts performed significantly better than the Phase I and II methods. For timing of the PWSD, none of the methods performed significantly bener than climatology. The AMU then developed the Microsoft Excel and MIDDS GUls. The GUIs display the forecasts for PWSD, AWSD and the probability the PWSD will meet or exceed 25 kt, 35 kt and 50 kt. Since none of the prediction methods for timing of the PWSD performed significantly better thanlimatology, the tool no longer displays this predictand. The Excel and MIDDS GUIs display forecasts for Day-I to Day-3 and Day-I to Day-5, respectively. The Excel GUI uses MesoNAM forecasts as input, while the MIDDS GUI uses input from the MesoNAM and Global Forecast System model. Based on feedback from the 45 WS, the AMU added the daily average wind speed from 30 ft to 60 ft to the tool, which is one of the parameters in the 24-Hour and Weekly Planning Forecasts issued by the 45 WS. In addition, the AMU expanded the MIDDS GUI to include forecasts out to Day-7.

Barrett, Joe H., III↗

NASA NTRS2009

NASA Tech Briefs, November 2009

Topics covered include: Cryogenic Chamber for Servo-Hydraulic Materials Testing; Apparatus Measures Thermal Conductance Through a Thin Sample from Cryogenic to Room Temperature; Rover Attitude and Pointing System Simulation Testbed; Desktop Application Program to Simulate Cargo-Air-Drop Tests; Multimodal Friction Ignition Tester; Small-Bolt Torque-Tension Tester; Integrated Spacesuit Audio System Enhances Speech Quality and Reduces Noise; Hardware Implementation of a Bilateral Subtraction Filter; Simple Optoelectronic Feedback in Microwave Oscillators; Small X-Band Oscillator Antennas; Free-Space Optical Interconnect Employing VCSEL Diodes; Discrete Fourier Transform Analysis in a Complex Vector Space; Miniature Scroll Pumps Fabricated by LIGA; Self-Assembling, Flexible, Pre-Ceramic Composite Preforms; Flight-speed Integral Image Analysis Toolkit; Work Coordination Engine; Multi-Mission Automated Task Invocation Subsystem; Autonomously Calibrating a Quadrupole Mass Spectrometer; Determining Spacecraft Reaction Wheel Friction Parameters; Composite Silica Aerogels Opacified with Titania; Multiplexed Colorimetric Solid-Phase Extraction; Detecting Airborne Mercury by Use of Polymer/Carbon Films; Lattice-Matched Semiconductor Layers on Single Crystalline Sapphire Substrate; Pressure-Energized Seal Rings to Better Withstand Flows; Rollerjaw Rock Crusher; Microwave Sterilization and Depyrogenation System; Quantifying Therapeutic and Diagnostic Efficacy in 2D Microvascular Images; NiF2/NaF:CaF2/Ca Solid-State High-Temperature Battery Cells; Critical Coupling Between Optical Fibers and WGM Resonators; Microwave Temperature Profiler Mounted in a Standard Airborne Research Canister; Alternative Determination of Density of the Titan Atmosphere; Solar Rejection Filter for Large Telescopes; Automated CFD for Generation of Airfoil Performance Tables; Progressive Classification Using Support Vector Machines; Active Learning with Irrelevant Examples; A Data Matrix Method for Improving the Quantification of Element Percentages of SEM/EDX Analysis; Deployable Shroud for the International X-Ray Observatory; Improved Model of a Mercury Ring Damper; Optoelectronic pH Meter: Further Details; X-38 Advanced Sublimator; and Solar Simulator Represents the Mars Surface Solar Environment.

Source record↗

NASA NTRS2017

The Earth Observing System (EOS)

The Earth Observing System is a US National Aeronautics and Space Administration (NASA) program consisting of a science segment, a data system, and a space segment made up of a series of polar-orbiting and mid-inclination satellites for long-term monitoring of the Earth as an integrated system, including observations of the land surface, biosphere, atmosphere, cryosphere, and oceans. Initially conceived in the mid-late 1980s, it was implemented as a series of large "flagship" missions and smaller focused satellites, often in partnership with instruments and sometimes spacecraft from other nations. In 1984 NASA formed several instrument panels to develop concepts for “facility instruments” that would provide comprehensive support to the scientific and applications’ communities, each with a supporting science team competitively selected via peer-review. An Announcement of Opportunity was released in 1988 and proposals were solicited for three types of proposals: (i) instrument investigations that would include the provision of instrumentation for flight on a polar platform, including non-Earth science payloads requiring polar orbits (PI instruments), (ii) research facility instrument team member and team leader investigations for facility instruments, and (iii) interdisciplinary science investigations to provide data analysis and modeling, preparing to use data acquired from the space platforms. The initial selections made in 1989 included support for 24 instrument investigations, 6 research facility instrument investigations, and 28 interdisciplinary investigations. Although considerable changes were made over the years in the structure and orbital configuration of the various instruments and platforms, a total of 10 different missions were eventually flown, as shown in Fig. 1. These included three multiinstrument flagship platforms known as Terra (launched in 1999), Aqua (launched in 2002), and Aura (launched in 2004), where the Terra mission emphasis was primarily on land processes, Aqua on the hydrological cycle, and Aura on atmospheric chemistry. In addition to these flagship missions the EOS missions included Landsat 7 (land cover classification and change), QuikScat (wind speed and direction over the oceans), Jason-1 (ocean surface topography and sea level), ACRIMSAT (total solar irradiance (TSI)), SAGE III (stratospheric aerosol and ozone levels), ICESat (ice, cloud, and land elevation), and SORCE (Solar Radiation and Climate Experiment; total and spectral solar irradiance). In addition EOS supported CERES (an Earth radiation budget sensor) and LIS (a lightning sensor), that flew as part of the NASA/JAXA Tropical Rainfall Measuring Mission (1997), and SeaWinds (wind speed and direction), that flew as part of the short-lived ADEOS II (Midori II, 2002) mission of JAXA (Japan Aerospace Exploration Agency). The EOS contributions are too numerous to present in detail in this article, but can be viewed for convenience as a means of obtaining global measurements (with appropriate characteristics) of the 24 variables and variable groups listed in Table 1. This table was created by the EOS community in the late 1990s as a way to succinctly indicate which instruments on the various EOS platforms were expected to contribute to each of the specified variables in primary (bold), secondary (bold italics), or contributing (roman) roles. All of the science data products produced by these space missions are available without charge throughout the world, and are thus highly valued for their many contributions to applications such as air quality, fires, land cover change, and the state of the oceans, as well as for science and monitoring of the state of the Earth system and its changes over time. These and other international satellites have played a crucial role in understanding and documenting global change, including (i) global surface temperature and atmospheric temperature and water vapor profiles, (ii) glacial retreat, (iii) sea ice extent and change, (iv) solar radiation into and out of the Earth-atmosphere system, (v) atmospheric aerosol and cloud properties, (vi) sources and sinks of

ICESat↗

NASA NTRS2020

Defining Handling Qualities of Unmanned Aerial Systems: Phase II Final Report

Unmanned Air Systems (UAS) are no longer coming, they are here, and operators from first responders to Google and Amazon are demanding access to the National Airspace System (NAS) for a wide variety of missions. This includes a proliferation of small UAS or sUAS that will operate beyond line of sight at altitudes of 500 ft and below. A myriad of issues continues to slow the development of verification, validation, and certification methods that will enable the safe introduction of UAS to the NAS. These issues include the lack of both a consensus in UAS categorization process and quantitative certification requirements, including the definition of handling qualities. Because of the wide variety of UAS types (fixed wing, rotary wing from traditional helicopters to multirotor configurations, ducted fans, airships, etc.) and vehicle size from micro vehicles to the Global Hawk with a wing span similar to that of a Boeing 737, there cannot be a one-size-fits-all set of requirements. To address these issues, Systems Technology Inc. (STI) has developed the UAS Handling Qualities Assessment (UAS-HQ) process and corresponding draft specification that will guide UAS stakeholders through a systematic evaluation process. The work described herein builds on the existing, highly successful, military rotorcraft handling qualities specifications that features a mission-oriented approach, a concept that originated at STI. The vehicle is first identified by a simple weight-based classification and then the associated vehicle mission task elements are considered. These missions have specific tasks inclusive to them that then dictate the criteria and demonstration maneuvers necessary to evaluate the UAS handling qualities. An assessment of both modeled responses and flight test data can then be conducted to examine the predicted versus actual handling qualities and, if required, design modifications can then be made. Mr. David Klyde, Vice President and Technical Director, Engineering Services, served as Principal Investigator, while Dr. Natalia Alexandrov served as the NASA LaRC technical representative. In the Phase II program, STI was joined by David Mitchell of Mitchell Aerospace Research and the University of Minnesota. Mr. Mitchell led the draft specification development effort, while the University of Minnesota UAV Lab conducted sUAS flight tests under the direction of Dr. Peter Seiler.

Klyde, David H.↗

NASA NTRSDate not supplied

Transcribing Air Traffic Control System Command Center Planning Telecons Using Cloud-Based Automatic Speech Recognition

This paper addresses the challenge of using Automatic Speech Recognition (ASR) technology to transcribe regular teleconferences that happen between FAA Air Traffic Control System Command Center (ATCSCC) planners, stakeholders and air users. These planning teleconferences (aka telecons or planning webinars) are an integral part of managing air traffic in the U.S. National Airspace System (NAS). In particular, the meetings facilitate the creation and modification of various traffic management initiatives (TMIs), that are used to regulate the flow of air traffic. This is typically a human intensive process, requiring specialists to listen to the entire meeting audio (10-20 minutes duration) and inferring the state of the NAS (e.g., weather phenomenon) that was discussed. It would be advantageous to have digital transcripts of the audio and have useful information (e.g., related to TMIs) automatically extracted from the transcripts. In this regard, we are exploring the adoption of state-of-the-art speech to text and Natural Language Processing (NLP) tools that will achieve our objective of digitizing the webinar audio. Unfortunately, the highly technical phraseology present in the audio and limited data availability for model building make ASR difficult. To overcome this challenge, we have taken the critical first step in creating a human transcription dataset from ~20 hours of speech in the ATCSCC audio with the help of subject matter experts. A novelty of our work is the creation of a ground truth transcription dataset for ATCSCC teleconference webinars, which is particularly important for Aviation domain-specific NLP tasks. Using Microsoft Speech Studio, a cloud-based ASR platform, we have fine-tuned the English pre-trained ASR models (available in speech studio) and achieved an average word error rate (WER) of 6.81%. The baseline ASR also provides a digital version of each planning webinar, making it accessible and text-searchable for future references. Additionally, the transcriptions can serve as a bridge between raw audio data and a range of text-based NLP tasks, such as named entity recognition (NER) and intent classification, potentially enhancing the digital footprint of the webinars and other connected data sources. Our work has several potential applications. Firstly, the transcriptions can be analyzed to understand the complex decision process of creating, implementing and modifying TMIs and may also contribute to TMI prediction services. Secondly, our dataset and model can be used to develop more accurate ASR systems for aviation-specific language, which can bring about digital communication in the aviation industry (and aid current “voice only” communications, which are inherently error-prone). Lastly, the transcriptions themselves can be used as a valuable resource for training other NLP models.

Stephen S. B. Clarke↗

NASA NTRS2009

The Urban Environmental Monitoring/100 Cities Project: Legacy of the First Phase and Next Steps

The Urban Environmental Monitoring (UEM) project, now known as the 100 Cities Project, at Arizona State University (ASU) is a baseline effort to collect and analyze remotely sensed data for 100 urban centers worldwide. Our overarching goal is to use remote sensing technology to better understand the consequences of rapid urbanization through advanced biophysical measurements, classification methods, and modeling, which can then be used to inform public policy and planning. Urbanization represents one of the most significant alterations that humankind has made to the surface of the earth. In the early 20th century, there were less than 20 cities in the world with populations exceeding 1 million; today, there are more than 400. The consequences of urbanization include the transformation of land surfaces from undisturbed natural environments to land that supports different forms of human activity, including agriculture, residential, commercial, industrial, and infrastructure such as roads and other types of transportation. Each of these land transformations has impacted, to varying degrees, the local climatology, hydrology, geology, and biota that predate human settlement. It is essential that we document, to the best of our ability, the nature of land transformations and the consequences to the existing environment. The focus in the UEM project since its inception has been on rapid urbanization. Rapid urbanization is occurring in hundreds of cities worldwide as population increases and people migrate from rural communities to urban centers in search of employment and a better quality of life. The unintended consequences of rapid urbanization have the potential to cause serious harm to the environment, to human life, and to the resulting built environment because rapid development constrains and rushes decision making. Such rapid decision making can result in poor planning, ineffective policies, and decisions that harm the environment and the quality of human life. Slower, more thought-out, decision making could result in more favorable outcomes. The harm to the environment includes poor air quality, soil erosion, polluted rivers and aquifers, and loss of wildlife habitat. Human life is then threatened because of increased potential for disease spreading, human conflict, environmental hazards, and diminished quality of life. The built environment is potentially threatened when cities are built in areas that can be impacted by events such as hurricanes, tsunamis, earthquakes, fires, and landslides. Our goals include assessing the threat of such events on cities and the people living there.

Stefanov, William L.↗

NASA NTRS2006

Characterization of Days Based On Analysis of National Airspace System Performance Metrics

Days of operations in the National Airspace System can be described in term of traffic demand, runway conditions, equipment outages, and surface and enroute weather conditions. These causes manifest themselves in terms of departure delays, arrival delays, enroute delays and traffic flow management delays, Traffic flow management initiatives such as, ground stops, ground delay programs, miles-in-trail restrictions, rerouting and airborne holding are imposed to balance the air traffic demand with respect to the available capacity, In order to maintain operational efficiency of the National Airspace System, the Federal Aviation Administration (FAA) maintains delay sad other statistics in the Air Traffic Operations Network (OPSNET) and the Aviation System Performance Metrics (ASPM) databases. OPSNET data includes reportable delays of fifteen minutes ox more experienced by Instrument Flight Rule (IFR) flights. Numbers of aircraft affected by departure delays, enroute delays, arrival delays and traffic flow delays are recorded in the OPSNET data. ASPM data consist of number of actual departures, number of canceled departures, percentage of on time departures, percentage of on time gate arrivals, taxi-out delays. taxi-in delays, gate delays, arrival delays and block delays. Surface conditions at the major U.S. airports are classified in terms of Instrument Meteorological Condition (IMC) and Visual Meteorological Condition (VMC) as a function of the time of the day in the ASPM data. The main objective of this paper is to use OPSNET and ASPM data to classify the days in the datasets into few distinct groups, where each group is separated from the other groups in terms of a distance metric. The motivations for classifying the days are two-fold, 1) to enable selection of days of traffic with particular operational characteristics for concept evaluation using system-wide simulation systems such as the National Aeronautics and Space Administration's Airspace Concepts Evaluation Tool (ACES) and 2) to enable evaluation of a given day with respect to the characteristics of the classified groups. The first part of the paper is devoted to the analysis of major trends seen in the OPSNET and ASPM data. The second part of the paper is devoted to describing features or measures derived from the OPSNET and ASPM data that are suitable for characterizing days, and the classification algorithm used for grouping the days. Finally, the method for evaluating the characteristics of a given day with respect to the properties of the groups is described.

Chatterji, Gano B.↗

NASA NTRSDate not supplied

An Impedance-Based Complexity Metric for Unmanned Aircraft System Traffic Scenario Classification

This paper introduces an impedance-based metric to capture the complexity of a given unmanned aircraft system traffic scenario. The metric accounts for both the number of aircraft and the traffic flow pattern. The work presented here extends an earlier approach that introduced another scenario complexity metric based on the number of potential conflicts weighted by the conflict resolution cost associated. Complexity measurements for randomly-generated scenarios were produced through high-fidelity fast-time simulations and treated as baseline. Then the impedance based metric was evaluated, for the same scenarios, without the need for an actual flight simulation and a conflict resolution method. The results show that the impedance-based metric has a strong correlation to the baseline data and performs marginally better than the weighted conflict-based complexity metric introduced in the earlier work. The metric computation generates impedance maps which are useful for identifying high complexity regions in a scenario, where flight plan changes might be necessitated. This metric can therefore be used, in conjunction with other complexity metrics, to inform adequate traffic management strategies and classify a traffic scenario as acceptable, unacceptable or acceptable with changes made to flight plans that pass through the high complexity regions. The metric can also be used as a guidance metric for strategic conflict management methods.

Complexity↗

NASA NTRS1998

Teaching Soil Science in Primary and Secondary Schools

Earth's thin layer of soil is a fragile resource, made up of minerals, organic materials, air, water, and billions of living organisms. Soils plays a variety of critical roles that sustain life on Earth. If we think about soil, we tend to see it first as the source of most of the food we eat and the fibers we use, such as wood and cotton. Few students realize that soils also provide the key ingredients to many of the medicines (including antibiotics), cosmetics, and dyes that we use. Fewer still understand the importance of soils in integrating, controlling, and regulating the movement of air, water, materials, and energy between the hydrosphere, lithosphere, atmosphere, and biosphere. Because soil sustains life, it offers both a context and a natural laboratory for investigating these interactions. The enclosed poster, which integrates soil profiles with typical landscapes in which soils form, can also help students explore the interrelationships of Earth systems and gain an understanding of our soil resources. The poster, produced jointly by the American Geological Institute and the Soil Science Society of America, aims to increase awareness of the importance of soil, as does the GLOBE (Global Learning and Observations To Benefit the Environment) Program. Vice President Al Gore instituted the GLOBE Program on Earth Day of 1993 to increase environmental awareness of individuals throughout the world, contribute to a better scientific understanding of the Earth, and help all students reach higher levels of achievement in science and mathematics. GLOBE functions as a partnership between scientists, students, and teachers in which scientists design protocols for specific measurements they need for their research that can be performed by K-12 students. Teachers are trained in the GLOBE protocols and teach them to their students. Students make the measurements, enter data via the Internet to a central data archive, and the data becomes available to scientists and the general community. Students benefit by having a "hands-on"experience in science, math, and technology, using their local environment as a learning laboratory, as well as contact with scientists and other students around the world. Soil investigations have become an essential component of GLOBE. The protocols that have been developed so far within the GLOBE program include GPS Location, Atmosphere/Climate, Soil Characterization, Soil Moisture and Temperature, Land Cover/Biometry, Hydrology, and Satellite Image Classification. For the GLOBE Soil Characterization Protocol, students explore the physical. chemical, and morphological properties of the soil at their study site. They are asked to dig a pit or use an auger to about 1 meter at at least 2 sites.

Levine, Elissa R.↗

NASA NTRS1993

Comparative magnetic and thermoanalytical study of two enstatite chondrites: Adhi Kot and Atlanta

With allowance for the discussion of classification of enstatite chondrites and their relation to aubrites, the obtained magnetic and thermoanalytical data is submitted to be considered as additive arguments. Our study covered the Adhi Kot (EH4) and Atlanta (EL6). meteorites belonging to two distinct groups of enstatite chondrites. Applying AF demagnetization the intensity of natural remanent magnetization (NRM) was measured and the mean magnetic susceptibility of the samples was determined. The differential thermal (DTA) and thermogravimetric (TG) curves were obtained for meteorites under study. For measurements of the intensity of NRM, a superconducting cryomagnetometer SQUID (2 G Enterprise, USA), while magnetic susceptibility Kappabridge KLY-2 (Czechoslovakia) were used. The abbreviated magnetic data sheets are given. The values 786 x 10(exp -4)A/mkg and 196.1 x 10(exp -4)A/mkg were obtained as NRM intensities for Atlanta and Adhi Kot respectively, while 17.4 x 10(exp -6) SIu/kg and 43.4 x 10(exp -6) SIu/kg for their susceptibilities. Both meteorites proved to be strongly magnetized. The demagnetization down to 3.2 percent of NMR was received for Atlanta at AF field intensity of 250 Oe. For Adhi Kot at this level rested 13.2 percent of NRM intensity, this sample being demagnetized without change of direction till 750 Oe field. The demagnetization curves are similar to those obtained for Abee (EL4) chondrite by Sugiura and Strangway. Against Abee the Adhi Kot exhibited a little bit steeper downfall, and in both cases dominate one component of magnetization. The DTA and TG curves were obtained with Rigaku-Denki thermoanalytical instrument. The DTA curves exhibit striking similarity in their shape and relatively close temperature values for various features. The same is valid for TG curves. The higher values for TG for Adhi Kot express its higher content of oxydable (Fe, Ni) whose oxidation in air is reached at 1000-1200 C.

Krol, Elizabeth↗

NASA NTRSDate not supplied

Assessing Alaskan boreal forest landcover affected by climate-wildfire interactions from ground truth surveys and NASA airborne remote sensing

Alaska’s boreal forest is facing unprecedented challenges under rapid climate warming (increasingly severe fires, droughts, pest/disease outbreaks) that may destabilize its function as a global carbon sink. Forests near Fairbanks may be especially vulnerable, impacting air quality and ecosystem services. We combined GT (ground truthing) with Airborne Visible InfraRed Imaging Spectrometer (AVIRIS-NG) images collected by the NASA Arctic-Boreal Vulnerability Experiment (ABoVE) program (2017-2019) to assess landcover change at five recently burned sites (2001-2019) of different fire severities and moisture regimes within 30 miles of Fairbanks. GT included tree seedling counts, understory % cover and >50% leaf canopy color assessment. 36 circular plots (1/30 ha radius) including 6 moderate to severely burned plots were selected across sites. 31 additional sites including 12 burned sites were geotagged in photos. AVIRIS images were processed from 29 spectral bands selected to identify changes in chlorophyll and water content. Images were segmented into natural boundaries (polygons) using ENVI 5.5 software. A spectral library of 8 AVIRIS bands with high between-class/low within-class variation was used in two random forest models to predict vegetation classes (model 1: 12 classes, model 2: 14 classes) in each AVIRIS scene, using 20% of the data as training data. Model 2 classified 20% more polygons overall, but only 42% of GT/geotagged polygons were correctly classified by both models. More forest sites were correctly classified (63%) than open vegetation (32%) or post-fire sites (46%). 50% of aspen forest and post-fire polygons were misclassified as shrubland. GT revealed that post-fire plots supported 134,000 (± 48,000) tree seedlings and saplings ha-1 (0.2 - 4 m height, 64% deciduous) versus 2500 (± 2100) shrubs ha-1 (1-6 m height). > 50% canopy browning was observed in conifer forest (8 plots) with no signs of insect infestation. Canopy herbivory > 50% (leaf miner, leaf beetle) and moose herbivory of tree bark was seen across aspen sites. Our study suggests: 1) low canopy vegetation presents challenges for improved landcover classification, and 2) aspen forest should be differentiated in vegetation maps which would aid in tracking herbivory.

Alaska↗