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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2014

The Near Earth Object Scout Spacecraft: A Low Cost Approach to in-situ Characterization of the NEO Population

In this paper we describe a micro/nano satellite spacecraft and a supporting mission profile and architecture designed to enable preliminary in-situ characterization of a significant number of Near Earth Objects (NEOs) at reasonable cost. The spacecraft will be referred to as the NEO Scout. NEO Scout spacecraft are to be placed in GTO, GEO, or cis-lunar space as secondary payloads on launch vehicles headed for GTO or beyond and will begin their mission after deployment from the launcher. A distinguishing key feature of the NEO scout system is to design the mission timeline and spacecraft to rendezvous with and land on the target NEOs during close approach to the Earth-Moon system using low-thrust/high- impulse propulsion systems. Mission feasibility and preliminary design analysis are presented along with detailed trajectory calculations. The use of micro/nano satellites in low-cost interplanetary exploration is attracting increasing attention and is the subject of several annual workshops and published design studies (1-4). The NEO population consists of those asteroids and short period comets orbiting the Sun with a perihelion of 1.3 astronomical units or less (5-8). As of July 30, 2013 10065 Near-Earth objects have been discovered. The spin rate, mass, density, surface physical (especially mechanical) properties, composition, and mineralogy of the vast majority of these objects are highly uncertain and the limited available telescopic remote sensing data imply a very diverse population (5-8). In-situ measurements by robotic spacecraft are urgently needed to provide the characterization data needed to support hardware and mission design for more ambitious human and robotic NEO operations. Large numbers of NEOs move into close proximity with the Earth-Moon system every year (9). The JPL Near-Earth Object Human Space Flight Accessible Targets Study (NHATS) (10) has produced detailed mission profile and delta V requirements for various NEO missions ranging from 30 to 420 days in duration and assuming chemical propulsion. Similar studies have been reported assuming high power electric propulsion for manned NEO rendezvous missions (11). The delta V requirement breakdown and mission profile data from references 10 and 11 are used as a basis for sizing the NEO Scout spacecraft and for conducting preliminary feasibility assessments using the Tsiokolvsky rocket equation, a (worst-case) delta V requirement of 10 km/sec, and a maximum spacecraft dry mass of 20 kg. Using chemical propellant for a 10 km/sec delta V drives spacecraft wet mass well above 300 kg so that chemical propulsion is a non-starter for the proposed mission profile and spacecraft wet mass limits. In contrast, a solar electric propulsion system needs only 8 kg of Xe propellant to accelerate the spacecraft to 10 km/sec in 163 days with 0.02 N of thrust and 500 W of power from1.6 sq m of 29% efficient solar panels. In a second example, accelerating a 4 kg payload to 7 km/sec over 180 days requires about 6.7 kg of propellant and 1.2 kg of solar panels (12 kg total spacecraft wet mass).

Koontz, Steven L.↗
NASA NTRS2003

Land Use and Land Cover Change, Urban Heat Island Phenomenon, and Health Implications: A Remote Sensing Approach

Land use and land cover maps of Atlanta Metropolitan Area in Georgia were produced from Landsat MSS and TM images for 1973,1979,1983,1987,1992, and 1997, spanning a period of 25 years. Dramatic changes in land use and land cover have occurred with loss of forest and cropland to urban use. In particular, low-density urban use, which includes largely residential use, has increased by over 119% between 1973 and 1997. These land use and land cover changes have drastically altered the land surface characteristics. An analysis of Landsat images revealed an increase in surface temperature and a decline in NDVI from 1973 to 1997. These changes have forced the development of a significant urban heat island effect and an increase in ground level ozone production to such an extent, that Atlanta has violated EPA's ozone level standard in recent years. The urban heat island initiated precipitation events that were identified between 1996 and 2000 tended to occur near high-density urban areas but outside the I-285 loop that traverses around the Central Business District, i.e. not in the inner city area, but some in close proximity to the highways. The health implications were investigated by comparing the spatial patterns of volatile organic compounds (VOC) and nitrogen oxides (NOx) emissions, the two ingredients that form ozone by reacting with sunlight, with those of rates of cardiovascular and chronic lower respiratory diseases. A clear core-periphery pattern was revealed for both VOC and NOx emissions, but the spatial pattern was more random in the cases of rates of cardiovascular and chronic lower respiratory diseases. Clearly, factors other than ozone pollution were involved in explaining the rates of these diseases. Further research is therefore needed to understand the health geography and its relationship to land use and land cover change as well as urban heat island effect. This paper illustrates the usefulness of a remote sensing approach for this purpose.

Lo, C. P.↗
NASA NTRS1973

Laser radar studies: A study of the feasibility of remote measurement of atmospheric density and turbidity by means of rotational Raman scattering of laser light

A remote sensing technique is described which utilizes elastic scattering and rotational Raman scattering of laser light in the atmosphere to obtain soundings of turbidity, transmissivity and density. A scheme is devised whereby, through selective weighting of the rotational Raman lines, the effect of atmospheric temperature structure may be eliminated. The close spectral proximity of the elastic and Raman-scattered signals, combined with the fact that the Raman scattering is quite weak, produces special requirements for the spectroscopic and light-gathering components of a rotational Raman laser radar system. These requirements are investigated. A computation of typical signal-to-noise ratios is made. It is shown that daytime signal-to-noise ratios greater than 10 db are to be expected for observation heights of 5 km and below. For nighttime work, 10 db signal-to-noise ratios are achievable to altitudes as high as 15 km.

Reiss, N.↗
NASA NTRS1990

Jet Propulsion Laboratory/Kennedy Space Center telerobotic inspection and manipulation demonstration

The goal of this effort is to demonstrate telerobotic inspection and mainpulation of space shuttle payloads in the presence of substantial communications time delays between the operator station and the robotic work space. The processing of space shuttle payloads provides a variety of tasks which are typical of both space shuttle ground operations and Space Station in-flight operations, and communications time delays are inevitable in space operations where the operator station will be light-seconds away from the telerobot. With this demonstration we hope to show the efficacy and safety of robotic technology for ground and space operations. Our approach is to develop an experimental telerobotic system with the remote sensing, actuation and reflex portions located at KSC in Florida, while the operator control station will be located at Jet Propulsion Laboratory (JPL) in California. The JPL portion of the system includes a high-level operator interface, intelligent spatial planning and machine vision, while the KSC portion includes the robot arm, end effectors, cameras and proximity sensors, and the necessary control and communications computers and software. The communications between JPL and KSC are over a limited-bandwidth network channel (19200 baud) with unpredictable and unrepeatable time delays. In FY89 we integrated a basic version of the robotic, communications, and computer hardware, and we developed the software to perform an operator-supervised inspection of a PAM-D satellite upper stage rocket motor and its shuttle support cradle. The demonstration, though severely limited by the bulk of the available computer arm, showed the potential of telerobotics for inspection tasks. In the future, we plan to develop additional capabilities which will allow manipulation tasks to be performed, including removal of dust covers and lens caps, insertion of connectors and batteries, and installation of payload objects.

Wilcox, Brian↗
NASA NTRS1978

Smart Sensors for Smart Hands

Proximity, force-torque, touch and slippage sensors developed or applied by the JPL Teleoperator Project for remote manipulator control are described, including sensor data handling by computers for display and control. Examples are quoted showing the significance of these sensors for manual or computer control of manipulators. An interesting example is a proximity sensor system implemented for a four-claw JSC end effector and tested at the Shuttle Manipulator Training Facility of JSC. New sensing concepts aimed at simplifying the implementation of 'Smart Sensors for Smart Hands' in the space environment are discussed.

Bejczy, A. K.↗
NASA NTRS2018

Advances in Hyperspectral Image Classification Methods for Vegetation and Agricultural Cropland Studies

Hyperspectral data are becoming more widely available via sensors on airborne and unmanned aerial vehicle (UAV) platforms, as well as proximal platforms. While space-based hyperspectral data continue to be limited in availability, multiple spaceborne Earth-observing missions on traditional platforms are scheduled for launch, and companies are experimenting with small satellites for constellations to observe the Earth, as well as for planetary missions. Land cover mapping via classification is one of the most important applications of hyperspectral remote sensing and will increase in significance as time series of imagery are more readily available. However, while the narrow bands of hyperspectral data provide new opportunities for chemistry-based modeling and mapping, challenges remain. Hyperspectral data are high dimensional, and many bands are highly correlated or irrelevant for a given classification problem. For supervised classification methods, the quantity of training data is typically limited relative to the dimension of the input space. The resulting Hughes phenomenon, often referred to as the curse of dimensionality, increases potential for unstable parameter estimates, overfitting, and poor generalization of classifiers. This is particularly problematic for parametric approaches such as Gaussian maximum likelihood–based classifiers that have been the backbone of pixel-based multispectral classification methods. This issue has motivated investigation of alternatives, including regularization of the class covariance matrices, ensembles of weak classifiers, development of feature selection and extraction methods, adoption of nonparametric classifiers, and exploration of methods to exploit unlabeled samples via semi-supervised and active learning. Data sets are also quite large, motivating computationally efficient algorithms and implementations. This chapter provides an overview of the recent advances in classification methods for mapping vegetation using hyperspectral data. Three data sets that are used in the hyperspectral classification literature (e.g., Botswana Hyperion satellite data and AVIRIS airborne data over both Kennedy Space Center and Indian Pines) are described in Section 3.2 and used to illustrate methods described in the chapter. An additional high-resolution hyperspectral data set acquired by a SpecTIR sensor on an airborne platform over the Indian Pines area is included to exemplify the use of new deep learning approaches, and a multiplatform example of airborne hyperspectral data is provided to demonstrate transfer learning in hyperspectral image classification. Classical approaches for supervised and unsupervised feature selection and extraction are reviewed in Section 3.3. In particular, nonlinearities exhibited in hyperspectral imagery have motivated development of nonlinear feature extraction methods in manifold learning, which are outlined in Section 3.3.1.4. Spatial context is also important in classification of both natural vegetation with complex textural patterns and large agricultural fields with significant local variability within fields. Approaches to exploit spatial features at both the pixel level (e.g., co-occurrence–based texture and extended morphological attribute profiles [EMAPs]) and integration of segmentation approaches (e.g., HSeg) are discussed in this context in Section 3.3.2. Recently, classification methods that leverage nonparametric methods originating in the machine learning community have grown in popularity. An overview of both widely used and newly emerging approaches, including support vector machines (SVMs), Gaussian mixture models, and deep learning based on convolutional neural networks is provided in Section 3.4. Strategies to exploit unlabeled samples, including active learning and metric learning, which combine feature extraction and augmentation of the pool of training samples in an active learning framework, are outlined in Section 3.5. Integration of image segmentation with classification to accommodate spatial coherence typically observed in vegetation is also explored, including as an integrated active learning system. Exploitation of multisensor strategies for augmenting the pool of training samples is investigated via a transfer learning framework in Section 3.5.1.2. Finally, we look to the future, considering opportunities soon to be provided by new paradigms, as hyperspectral sensing is becoming common at multiple scales from ground-based and airborne autonomous vehicles to manned aircraft and space-based platforms.

Pasolli, Edoardo↗
NASA NTRS2015

Neutron Spectrometer Prospecting in the Mojave Volatiles Project Analog Field Test

We know that volatiles are sequestered at the poles of the Moon. While we have evidence of water ice and a number of other compounds based on remote sensing, the detailed distribution, and physical and chemical form are largely unknown. Additional orbital studies of lunar polar volatiles may yield further insights, but the most important next step is to use landed assets to fully characterize the volatile composition and distribution at scales of tens to hundreds of meters. To achieve this range of scales, mobility is needed. Because of the proximity of the Moon, near real-time operation of the surface assets is possible, with an associated reduction in risk and cost. This concept of operations is very different from that of rovers on Mars, and new operational approaches are required to carry out such real-time robotic exploration. The Mojave Volatiles Project (MVP) was a Moon-Mars Analog Mission Activities (MMAMA) program project aimed at (1) determining effective approaches to operating a real-time but short-duration lunar surface robotic mission, and (2) performing prospecting science in a natural setting, as a test of these approaches. Here we describe some results from the first such test, carried out in the Mojave Desert between 16 and 24 October, 2014. The test site was an alluvial fan just E of the Soda Mountains, SW of Baker, California. This site contains desert pavements, ranging from the late Pleistocene to early-Holocene in age. These pavements are undergoing dissection by the ongoing development of washes. A principal objective was to determine the hydration state of different types of desert pavement and bare ground features. The mobility element of the test was provided by the KREX-2 rover, designed and operated by the Intelligent Robotics Group at NASA Ames Research Center. The rover-borne neutron spectrometer measured the neutron albedo at both thermal and epithermal energies. Assuming uniform geochemistry and material bulk density, hydrogen as either hydroxyl/water in mineral assemblages or as moisture will significantly enhance the return of thermalized neutrons. However, in the Mojave test setting there is little uniformity, especially in bulk material density. We find that lighter toned materials (immature pavements, bar and swale, and wash materials) have lower thermal neutron flux, while mature, darker pavements with the greatest desert varnish development have higher neutron fluxes. Preliminary analysis of samples from the various terrain types in the test area indicates a prevailing moisture content of 2-3 wt% H2O. However, soil mineralogy suggests that the welldeveloped Av1 soil horizon beneath the topmost dark pavement clast layer contains the highest clay content. Structural water (including hydroxyl) in these clays may explain the enhanced neutron albedo over dark pavements. On the other hand, surface and subsurface bulk density can also play a role in neutron albedo - lower density of materials found in washes, for example, can result in a reduction in neutron flux. Analysis is ongoing.

rover-borne neutron spectrometer↗
NASA NTRS1999

Park Smart

The Parking Garage Automation System (PGAS) is based on a technology developed by a NASA-sponsored project called Robot sensorSkin(TM). Merritt Systems, Inc., of Orlando, Florida, teamed up with NASA to improve robots working with critical flight hardware at Kennedy Space Center in Florida. The system, containing smart sensor modules and flexible printed circuit board skin, help robots to steer clear of obstacles using a proximity sensing system. Advancements in the sensor designs are being applied to various commercial applications, including the PGAS. The system includes a smartSensor(TM) network installed around and within public parking garages to autonomously guide motorists to open facilities, and once within, to free parking spaces. The sensors use non-invasive reflective-ultrasonic technology for high accuracy, high reliability, and low maintenance. The system is remotely programmable: it can be tuned to site-specific requirements, has variable range capability, and allows remote configuration, monitoring, and diagnostics. The sensors are immune to interference from metallic construction materials, such as rebar and steel beams. Inside the garage, smart routing signs mounted overhead or on poles in front of each row of parking spots guide the motorist precisely to free spaces.

Source record↗
NASA NTRS2016

Characterization of Lunar Farside Plains

The Moon contains broad and isolated areas of plains that have been recognized as mare, cryptomare, impact ejecta, or impact melt. These deposits have been extensively studied on the lunar nearside by remote sensing via telescopes and numerous spacecraft, and in some cases, in situ robotically and by astronauts. Only recently have the deposits on the entire farside been able to be observed and evaluated to the same degree. There are spatially extensive plains deposits located throughout the lunar farside highlands whose formation has remained ambiguous. Many of the plains deposits in the lunar farside highlands display higher albedos than mare materials. Some deposits are located in close proximity to relatively younger impact craters suggesting that plains could be composed of cryptomare or ejecta materials. Some deposits are within the range in which ejecta from large basin-forming events (e.g., SPA and Orientale) likely distributed large amounts of ejecta across the surface. Here we are conducting a series of observations and models in order to resolve the nature and origin of lunar farside plains deposits. Understanding these plains is important for understanding the volcanic and impact histories of the lunar farside, and is important for future mapping and thermal modeling studies.

Moon↗
NASA NTRS2022

An Evaluation of the Liquid Cloud Droplet Effective Radius Derived from MODIS, Airborne Remote Sensing, and in Situ Measurements from CAMP2Ex

The cloud drop effective radius (Re) of the drop size distribution derived from passive satellite sensors is a key variable used in climate research. Validation of these satellite products has often taken place under stratiform cloud conditions that favor the assumption of cloud horizontal homogeneity used by the retrieval techniques. However, many studies have noted concerns with respect to significant biases in retrieved Re arising from cloud heterogeneity, for example, in cumulus cloud fields. Here, we examine data collected during the 2019 “Cloud, Aerosol and Monsoon Processes Philippines Experiment” (CAMP2Ex), which, in part, targeted the objective of providing the first detailed evaluation of Re retrieved across multiple platforms and techniques in a cumulus and congestus cloud region. Our evaluation consists of cross-comparisons of Re between the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra satellite, the Research Scanning Polarimeter (RSP) onboard the NASA P-3 aircraft, and in situ measurements from both the NASA P-3 and Learjet aircraft that are all taken in close spatiotemporal proximity to the same cloud fields. A particular advantage of our approach lies in the capability of the RSP to retrieve Re using a bi-spectral MODIS approach and a polarimetric approach, which allows for the evaluation of bi-spectral and polarimetric Re retrievals from an airborne perspective using the same samples. Averaged over all P-3 flight segments examined here for warm clouds, the RSP polarimetric method, the in situ method, and the bias-adjusted MODIS method of Fu et al. (2019) show a comparable median (mean ± standard deviation) for the Re samples of 9.6 (10.2 ± 4.0) µm, 11.0 (13.6 ± 11.3) µm, and 10.4 (10.8 ± 3.8) µm, respectively. These values are far lower than the values of 15.1 (16.2 ± 5.5) µm and 17.2 (17.7 ± 5.7) µm from the bi-spectral retrievals of RSP and MODIS, respectively. Similar results are observed when Re is segregated by cloud-top height and in detailed case studies. The clouds sampled during CAMP2Ex consist of mostly small (mean transect length ∼ 1.4 km) and low clouds (mean cloud-top height ∼ 1 km), which had more numerous small clouds than the trade wind cumuli sampled in past field campaigns such as Rain in Shallow Cumulus over the Ocean (RICO) and the Indian Ocean Experiment (INDOEX). The overestimates of Re from the RSP bi-spectral technique compared with the polarimetric technique increased as cloud size and cloud optical depth decreased. Drizzle, cloud-top bumpiness, and solar zenith angle, however, are not closely correlated with the overestimate of bi-spectral Re. For shallow clouds that dominated the liquid cloud cover for the CAMP2Ex region and period, we show that 3-D radiative transfer and cloud heterogeneity, particularly for the optically thin and small clouds, appear to be the leading cause of the large positive biases in bi-spectral retrievals. Because this bias varies with the underlying structure of the cloud field, caution continues to be warranted in studies that use bi-spectral Re retrievals in cumulus cloud fields.

Cloud microphysics↗
NASA NTRS2017

DART: Recent Advances in Remote Sensing Data Modeling With Atmosphere, Polarization, and Chlorophyll Fluorescence

To better understand the life-essential cycles and processes of our planet and to further develop remote sensing (RS) technology, there is an increasing need for models that simulate the radiative budget (RB) and RS acquisitions of urban and natural landscapes using physical approaches and considering the three-dimensional (3-D) architecture of Earth surfaces. Discrete anisotropic radiative transfer (DART) is one of the most comprehensive physically based 3-D models of Earth-atmosphere radiative transfer, covering the spectral domain from ultraviolet to thermal infrared wavelengths. It simulates the optical 3-DRB and optical signals of proximal, aerial, and satellite imaging spectrometers and laser scanners, for any urban and/or natural landscapes and for any experimental and instrumental configurations. It is freely available for research and teaching activities. In this paper, we briefly introduce DART theory and present recent advances in simulated sensors (LiDAR and cameras with finite field of view) and modeling mechanisms (atmosphere, specular reflectance with polarization and chlorophyll fluorescence). A case study demonstrating a novel application of DART to investigate urban landscapes is also presented.

Gastellu-Etchegorry, Jean-Phil↗
NASA NTRSDate not supplied

Lunar Impact Melt Crystallization Produces Reflectance Spectra Dominated By Clinopyroxene Signatures: Implications for the Origin of Pink Spinel Anorthosite

Magma-wallrock interaction and impact melt crystallization are the two leading hypotheses for the formation of orbitally detected lunar “pink” spinel anorthosite (PSA) [1-3]. Distinguishing among hypotheses is complicated because both require mixing of anorthositic crust and MgO-rich ultramafic components. Models for PSA formation need to account for either the thermodynamic hurdles of crustal assimilation, or the size of impactor and composition of target material needed to generate spinel during crater and basin formation. Determining whether the energy source is endogenic or exogenic is important for understanding the thermal and chemical evolution of the lunar crust. Here we test the impact melt hypothesis by performing controlled cooling experiments on two hypothetical impact melt compositions. The compositions represent mixing of ultramafic magma and anorthositic crust in molar ratios of approximately 50:50 and 25:75. Synthetic crystallized assemblages were prepared for chemical analysis and bidirectional reflectance spectroscopy in the visible to near-infrared wavelengths. All crystallization experiments contained plagioclase, olivine, and clinopyroxene, but trace amounts of spinel were only observed in the 50:50 mix. The experimental spinel is similar to the compositions inferred from remote observations. However, the high-Ca pyroxene in our experimental assemblages (9 – 18 wt.%) resulted in 1 and 2 µm absorption band center positions consistent with synthetic clinopyroxene. The clinopyroxene absorptions are present regardless of specific mineral modes and the presence of either olivine or spinel. These results suggest that impact melt crystallization will produce clinopyroxene-bearing lithologies, the presence of which masks spectral contributions from coexisting spinel and olivine. Assuming that the trace amounts of spinel observed in our experiments could be concentrated and isolated from the mafic silicates by convection or density settling in the impact melt sheet, the spinel-rich areas would still be proximally associated with the remaining silicate-dominated assemblage exhibiting strong clinopyroxene spectral signatures. We conclude that impact melting of the lunar crust can explain rare cases of PSA in association with clinopyroxene. Previous investigations of magma-wallrock interactions [2] demonstrate that small plagioclase-contaminated regions of an ultramafic intrusion can concentrate spinel whereas larger portions of the same intrusion remain relatively uncontaminated and yield olivine and orthopyroxene, consistent with the more common occurrence of PSAs in association with orthopyroxene ±olivine in the remote sensing database (e.g., Moscoviense Basin) [4].

petrology↗
NASA NTRS2008

Eurasian Reindeer Pastoralism in a Changing Climate: Indigenous Knowledge and NASA Remote Sensing

It is intended that Reindeer Mapper/EALAT will be able to provide reindeer herders with an efficient tool for managing the real-time movements and migrations of their herds through enabling improved efficiency in linking different members of the herder settlements or communities and providing real-time local, satellite or other data (e.g., ice melt in lakes and rivers, weather events), thus enabling real time adjustments to herd movements to avoid problems such as changing weather/climate conditions, freeze-thaw "lock-out" problems, or take advantage of availability of better pasturelands along migration routes. The system is being designed to incorporate local data to allow users to bring their own data into the system for analysis in addition to the data provided by the system itself. With the local information of the population, up to date environmental data and habitat characteristics, the system could generate maps depicting important features of interest for reindeer managers. One of the products derived from the planned Reindeer Mapper system will be a web-based graphic display that allows analysts to quickly pinpoint areas of interest such as those with large concentrations of reindeer and provide surrounding environmental information. The system could be automatically updated with near-real-time information such as hourly precipitation and snowfall rate and accumulation, daily surface and air temperatures, and vegetation cover conditions. The system could bring attention to the proximity of human and animal populations as part of the need for control response. A local GIS will bring these many layers together with several supporting models, showing only a straightforward graphic of the real-time situation in the field. Because the system proposed will be operating in the Internet environment, it should be virtually accessible from any network computers and wireless remote access from the field. The International Center for Reindeer Husbandry in Kautokeino, Norway, is providing regional and international coordination of and access to data sets and expertise, and will act as overall clearinghouse for EALAT information.

Maynard, N. G.↗
NASA NTRSDate not supplied

Treating gridded geospatial data as point data to simplify analytics

Gridded geospatial remote sensing (satellite) data has traditionally been stored in file-based multidimensional arrays to preserve the locality of data. Measurements from locations that are physically next to each other on earth remain next to each other in the arrays. Maintaining this locality is useful when running calculations like reprojection, but unnecessary for many other calculations. This talk will go through a real world example of a tool redesign at the Goddard Earth Sciences Data and Information Services Center (GES DISC), showing the advantages of using the data frame model for calculating summary statistics, where measurement proximity is unimportant.

Analysis-ready data↗
NASA NTRS1995

A relational metric, its application to domain analysis, and an example analysis and model of a remote sensing domain

An objective and quantitative method has been developed for deriving models of complex and specialized spheres of activity (domains) from domain-generated verbal data. The method was developed for analysis of interview transcripts, incident reports, and other text documents whose original source is people who are knowledgeable about, and participate in, the domain in question. To test the method, it is applied here to a report describing a remote sensing project within the scope of the Earth Observing System (EOS). The method has the potential to improve the designs of domain-related computer systems and software by quickly providing developers with explicit and objective models of the domain in a form which is useful for design. Results of the analysis include a network model of the domain, and an object-oriented relational analysis report which describes the nodes and relationships in the network model. Other products include a database of relationships in the domain, and an interactive concordance. The analysis method utilizes a newly developed relational metric, a proximity-weighted frequency of co-occurrence. The metric is applied to relations between the most frequently occurring terms (words or multiword entities) in the domain text, and the terms found within the contexts of these terms. Contextual scope is selectable. Because of the discriminating power of the metric, data reduction from the association matrix to the network is simple. In addition to their value for design. the models produced by the method are also useful for understanding the domains themselves. They can, for example, be interpreted as models of presence in the domain.

Mcgreevy, Michael W.↗
NASA NTRS2022

Evaluation of IMERG Satellite Precipitation Over the Land-Coast-Ocean Continuum – Part Ii: Quantification

To understand and manage water systems under a changing climate and meet an increasing demand for water, a quantitative understanding of precipitation is most important in coastal regions. The capabilities of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) V06B product for precipitation quantification are examined over three coastal regions of the United States: the West Coast, the Gulf of Mexico, and the East Coast, all of which are characterized by different topographies and precipitation climatologies. A novel uncertainty analysis of IMERG is proposed that considers environmental and physical parameters such as elevation and distance to the coastline. The IMERG performance is traced back to its components, i.e., passive microwave (PMW), infrared (IR), and morphing-based estimates. The analysis is performed using high-resolution, high-quality Ground Validation Multi-Radar/Multi-Sensor (GV-MRMS) rainfall estimates as ground reference at the native resolution of IMERG of 30 min and 0.1°. IMERG Final (IM-F) quantification performance heavily depends on the respective contribution of PMW, IR, and morph components. IM-F and its components overestimate the contribution of light rainfall (<1 mm h−1) and underestimate the contribution of high rainfall rates (>10 mm h−1) to the total rainfall volume. Strong regional dependencies are highlighted, especially over the West Coast, where the proximity of complex terrain to the coastline challenges precipitation estimates. Other major drivers are the distance from the coastline, elevation, and precipitation types, especially over the land and coast surface types, that highlight the impact of precipitation regimes.

Atmosphere↗
NASA NTRS2017

Atmospheric Form Drag Coefficients Over Arctic Sea Ice Using Remotely Sensed Ice Topography Data, Spring 2009-2015

Sea ice topography significantly impacts turbulent energy/momentum exchange, e.g., atmospheric (wind) drag, over Arctic sea ice. Unfortunately, observational estimates of this contribution to atmospheric drag variability are spatially and temporally limited. Here we present new estimates of the neutral atmospheric form drag coefficient over Arctic sea ice in early spring, using high-resolution Airborne Topographic Mapper elevation data from NASA's Operation IceBridge mission. We utilize a new three-dimensional ice topography data set and combine this with an existing parameterization scheme linking surface feature height and spacing to form drag. To be consistent with previous studies investigating form drag, we compare these results with those produced using a new linear profiling topography data set. The form drag coefficient from surface feature variability shows lower values [less than 0.5-1 × 10(exp. −3)] in the Beaufort/Chukchi Seas, compared with higher values [greater than 0.5-1 ×10(exp. −3)] in the more deformed ice regimes of the Central Arctic (north of Greenland and the Canadian Archipelago), which increase with coastline proximity. The results show moderate interannual variability, including a strong increase in the form drag coefficient from 2013 to 2014/2015 north of the Canadian Archipelago. The form drag coefficient estimates are extrapolated across the Arctic with Advanced Scatterometer satellite radar backscatter data, further highlighting the regional/interannual drag coefficient variability. Finally, we combine the results with existing parameterizations of form drag from floe edges (a function of ice concentration) and skin drag to produce, to our knowledge, the first pan-Arctic estimates of the total neutral atmospheric drag coefficient (in early spring) from 2009 to 2015.

sea ice↗
NASA NTRS2021

Southern Bhutan Ecological Forecasting III: Utilizing NASA Earth Observations to Model Land Cover Change and Elephant Wildlife Corridors in Southern Bhutan

Habitat loss of the endangered Asian elephants (Elephas maximus) accompanied by rapid urbanization has contributed to the rising human-elephant conflict (HEC) crisis in southern Bhutan. This poses a serious threat to the survival of Asian elephants, a keystone wildlife species essential for maintaining Bhutan’s forest ecosystems and rich biodiversity. With expanding urban areas, HECs present challenges to conservation efforts in the region. The team partnered with the Bhutan Foundation, the Bhutan Tiger Center, and Bhutan Ecological Society to help mitigate this issue using remote sensing technology and NASA Earth observations. The team refined Land Use and Land Cover (LULC) maps for 2010–2019 generated in previous terms and elephant corridor maps to include information on human settlements using Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) data. We generated LULC change maps and forecasted the LULC to 2030 using TerrSet Land Change Modeler, providing insights into future elephant habitat suitability in southern Bhutan. The results indicated that built-up areas increased approximately 688.9% from 2010 to 2019 and the forecasted 2030 LULC also predicted an increase in built-up areas compared to 2019. Suitable corridors in Gelephu intersect cultivated and built-up areas, indicating close proximity of elephants to humans and a need to research alternative corridor strategies. The end products from this project will aid partner organizations in decision-making processes in urban planning and future conservation strategies that include the refined placement of biological corridors to aid elephant movement and reduce the risk of HECs.

Thinley Yidzin Wangden↗