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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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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

[Sources of Methane in the Boreal Region]

In determining the global methane budget the sources of methane must be balanced with the sinks and atmospheric inventory. The approximate contribution of the different methane sources to the budget has been establish showing the major terrestrial inputs as rice, wetlands, bogs, fens, and tundra. Measurements and modeling of production in these sources suggest that temperature, water table height and saturation along with substratum composition are important in controlling methane production and emission. The isotopic budget of 13 C and D/H in methane can be used as a tool to clarify the global budget. This approach has achieved success at constraining the inputs. Studies using the isotopic approach place constraints on global methane production from different sources. Also, the relation between the two biogenic production pathways, acetate fermentation and CO2 reduction, and the effect of substratum composition can be made using isotope measurements shows the relation between the different biogenic, thermogenic and anthropogenic sources of methane as a function of the carbon and hydrogen isotope values for each source and the atmosphere, tropospheric composition. Methane emissions from ponds and fens are a significant source in the methane budget of the boreal region. An initial study in 1993 and 1994 on the isotopic composition of this methane source and the isotopic composition in relation to oxidation of methane at the sediment surface of the ponds or fen was conducted as part of our BOREAS project. The isotopic composition of methane emitted by saturated anoxic sediment is dependent on the sediment composition and geochemistry, but will be influenced by in situ oxidation, in part, a function of rooted plant activity. The influence of oxidation mediated by rooted plant activities on the isotopic composition of methane is not well known and will depend on the plant type, sediment temperature, and numerous other variables. Information on this isotopic composition is important in both understanding the bio-geochemistry of the system and also in determining the regional and global inputs for the methane isotope budget. In determining the destruction of methane for balancing the atmospheric methane budget soil oxidation must be considered.

Source record↗
NASA NTRS2010

Evaluation and Application of Remotely Sensed Soil Moisture Products

Whereas in-situ measurements of soil moisture are very accurate, achieving accurate regional soil moisture estimates derived solely from point measurements is difficult because of the dependence upon the density of the gauge network and the proper upkeep of these instruments, which can be costly. Microwave remote sensing is the only technology capable of providing timely direct measurements of regional soil moisture in areas that are lacking in-situ networks. Soil moisture remote sensing technology is well established has been successfully applied in many fashions to Earth Science applications. Since the microwave emission from the soil surface has such a high dependency upon the moisture content within the soil, we can take advantage of this relationship and combined with physically-based models of the land surface, derive accurate regional estimates of the soil column water content from the microwave brightness temperature observed from satellite-based remote sensing instruments. However, there still remain many questions regarding the most efficient methodology for evaluating and applying satellite-based soil moisture estimates. As discussed below, we to use satellite-based estimates of soil moisture dynamics to improve the predictive capability of an optimized hydrologic model giving more accurate root-zone soil moisture estimates.

Bolten, J.↗
NASA NTRS2019

An Experimental Investigation of a Wing-Fuselage Junction Model in the NASA Langley 14- by 22-Foot Subsonic Tunnel

Current turbulence models, such as those employed in Reynolds-averaged Navier-Stokes CFD, are unable to reliably predict the onset and extent of the three-dimensional separated flow that typically occurs in wing-fuselage junctions. To critically assess, as well as to improve upon, existing turbulence models, experimental validation-quality flow-field data in the junction region is needed. In this report, we present an overview of experimental measurements on a wing-fuselage junction model that addresses this need. The experimental measurements were performed in the NASA Langley 14- by 22-Foot Subsonic Tunnel. The model was a full-span wing-fuselage body that was configured with truncated DLR-F6 wings, both with and without leading-edge extensions at the wing root. The model was tested at a fixed chord Reynolds number of 2.4 million, and angles-of-attack ranging from -10 degrees to +10 degrees were considered. Flow-field measurements were performed with a pair of miniature laser Doppler velocimetry (LDV) probes that were housed inside the model and attached to three-axis traverse systems. One LDV probe was used to measure the separated flow field in the trailing-edge junction region. The other LDV probe was alternately used to measure the flow field in the leading-edge region of the wing and to measure the incoming fuselage boundary layer well upstream of the leading edge. Both LDV probes provided measurements from which all three mean velocity components, all six independent components of the Reynolds-stress tensor, and all ten independent components of the velocity triple products were calculated. In addition to the flow-field measurements, static and dynamic pressures were measured at selected locations on the wings and fuselage of the model, infrared imaging was used to characterize boundary-layer transition, oil-flow visualization was used to visualize the separated flow in the leading- and trailing-edge regions of the wing, and unsteady shear stress was measured at limited locations using capacitive shear-stress sensors. Sample results from the measurement techniques employed during the test are presented and discussed.

Kegerise, Michael A.↗
NASA NTRS2020

What Can We Learn from One Billion Ground System Log Messages?

Shortage of log-based data in a ground system they have traditionally been the under achievers in a satellite ground system. This is due to several factors: Once log messages scroll out of view on the TTC event console window they are soon forgotten. Application and system log files are scattered across directories within a system, across a multitude of servers, and across one or more databases making access cumbersome. Typical tools to perform log file content searching are generally crude and typically only employed as part of trouble-shooting exercises.As we move towards satellite constellations and fleets and add even more status information, the number of messages keeps growing. One mission now estimates that they could generate 3,000,000 messages per day 1 billion per year - for the life of their mission. What to do with those 1 billion messages? That is the challenge. With the recent technological advances in the management of large data sets, text-based processing, and data analytics, there are now capabilities that we can provide to the ground system engineers and satellite operators to address what we postulate are missed opportunities. Advanced real-time log analysis can allow us to be less reactionary in favor of being more proactive. Analytics goals include the ability to: Identify root cause of unexpected events, failures or error conditions enabled by correlating disparate data. Detect security breaches attempts before they are successful. Help admins ensure IT resources continue running optimally. Identify trends and patterns that may indicate impending failures or error conditions for valuable assets before they happen. Compare satellites in a fleet or constellation in terms of number of alarms, number of command sent to them, etc.. Answer questions like "Are the operations support needs increasing over the past year?" or "Have we seen this combination of alarm conditions before?" But really, once the tools are readily available the users will start realizing what can be done with their new powers. In this presentation we will show the results of analyzing millions of actual mission operations log messages, how the results can be displayed to the user, and how new products now available as open source can be applied to the challenges of large scale time-tagged text-based mission operations messages. Flight operations team members believe that this is a powerful new option for how they assess overall system and space asset health. Technical descriptions of the design, tools, and storage will be provided. One billion messages? Bring'em on!

Orsborne, Sharon↗
NASA NTRS1988

Cultural systems for growing potatoes in space

Higher plants are being evaluated for life support to provide needed food, oxygen and water as well as removal of carbon dioxide from the atmosphere. The successful utilization of plants in space will require the development of not only highly productive growing systems but also highly efficient bioregenerative systems. It will be necessary to recycle all inedible plant parts and all human wastes so that the entire complement of elemental compounds can be reused. Potatoes have been proposed as one of the desirable crops because they are 1) extremely productive, yielding more than 100 metric tons per hectare from field plantings, 2) the edible tubers are high in digestible starch (70%) and protein (10%) on a dry weight basis, 3) up to 80% of the total plant production is in tubers and thus edible, 4) the plants are easily propagated either from tubers or from tissue culture plantlets, 5) the tubers can be utilized with a minimum of processing, and 6) potatoes can be prepared in a variety of different forms for the human diet (Tibbitts et al., 1982). However potatoes have a growth pattern that complicates the development of growing the plants in controlled systems. Tubers are borne on underground stems that are botanically termed 'rhizomes', but in common usage termed 'stolons'. The stolons must be maintained in a dark, moist area with sufficient provision for enlargement of tubers. Stems rapidly terminate in flowers forcing extensive branching and spreading of plants so that individual plants will cover 0.2 m2 or more area. Thus the growing system must be developed to provide an area that is darkened for tuber and root growth and of sufficient size for plant spread. A system developed for growing potatoes, or any plants, in space will have certain requirements that must be met to make them a useful part of a life support system. The system must 1) be constructed of materials, and involve media, that can be reused for many successive cycles of plant growth, 2) involve a minimum quantity of media, 3) contain media that is essentially inert and not oxidize or degrade with use, 4) utilize a recirculating nutrient solution to permit regulation of pH and nutrient concentrations, and 5) be capable of complete automation of all planting, maintenance and harvesting procedures.

NASA Discipline Number 61-10↗
NASA NTRSDate not supplied

Plant Water Management in Microgravity

The NASA Plant Water Management (PWM) technology demonstrations aboard ISS apply recent advances in microgravity capillary fluidics research towards the mundane yet problematic challenges of simply watering plants in space. Plant growth in a low-g environment is often hampered by inadequate aeration and over-saturation of the root zone. The present effort aims to exploit the passive capillary forces of poorly wetting liquids (i.e., contaminated water) within unique system geometries that effectively replace the role of gravity in providing sufficient aeration and hydration for simulated plants. Several flight demonstrations have been completed on ISS, including soil and hydroponic models in single and parallel channel networks. Two future demonstrations are still in work and plan to further develop the system to handle sustained plant growth with additional sensors to monitor the growth environment. The results to date demonstrate proof-of-concept, system stability, limits of operation, and more, for simulated plant models. Eventually, real plants will be incorporated into these systems and tested on orbit. The implications are discussed in relation to plant growth facilities for further near-term microgravity plant science research as well as for automated food production for long duration human exploration missions.

microgravity↗
NASA NTRS2016

A Quasi-Global Approach to Improve Day-Time Satellite Surface Soil Moisture Anomalies through the Land Surface Temperature Input

Passive microwave observations from various spaceborne sensors have been linked to the soil moisture of the Earth's surface layer. A new generation of passive microwave sensors are dedicated to retrieving this variable and make observations in the single theoretically optimal L-band frequency (1-2 GHz). Previous generations of passive microwave sensors made observations in a range of higher frequencies, allowing for simultaneous estimation of additional variables required for solving the radiative transfer equation. One of these additional variables is land surface temperature, which plays a unique role in the radiative transfer equation and has an influence on the final quality of retrieved soil moisture anomalies. This study presents an optimization procedure for soil moisture retrievals through a quasi-global precipitation-based verification technique, the so-called Rvalue metric. Various land surface temperature scenarios were evaluated in which biases were added to an existing linear regression, specifically focusing on improving the skills to capture the temporal variability of soil moisture. We focus on the relative quality of the day-time (01:30 pm) observations from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), as these are theoretically most challenging due to the thermal equilibrium theory, and existing studies indicate that larger improvements are possible for these observations compared to their night-time (01:30 am) equivalent. Soil moisture data used in this study were retrieved through the Land Parameter Retrieval Model (LPRM), and in line with theory, both satellite paths show a unique and distinct degradation as a function of vegetation density. Both the ascending (01:30 pm) and descending (01:30 am) paths of the publicly available and widely used AMSR-E LPRM soil moisture products were used for benchmarking purposes. Several scenarios were employed in which the land surface temperature input for the radiative transfer was varied by imposing a bias on an existing regression. These scenarios were evaluated through the Rvalue technique, resulting in optimal bias values on top of this regression. In a next step, these optimal bias values were incorporated in order to re-calibrate the existing linear regression, resulting in a quasi-global uniform LST relation for day-time observations. In a final step, day-time soil moisture retrievals using the re-calibrated land surface temperature relation were again validated through the Rvalue technique. Results indicate an average increasing Rvalue of 16.5%, which indicates a better performance obtained through the re-calibration. This number was confirmed through an independent Triple Collocation verification over the same domain, demonstrating an average root mean square error reduction of 15.3%. Furthermore, a comparison against an extensive in situ database (679 stations) also indicates a generally higher quality for the re-calibrated dataset. Besides the improved day-time dataset, this study furthermore provides insights on the relative quality of soil moisture retrieved from AMSR-E's day- and night-time observations.

soil moisture↗
NASA NTRS2017

Biomass Retrieval from L-Band Polarimetric UAVSAR Backscatter and PRISM Stereo Imagery

The forest above-ground biomass (AGB) and spatial distribution of vegetation elements have profound effects on the productivity and biodiversity of terrestrial ecosystems. In this paper, we evaluated biomass estimation from L-band Synthetic Aperture Radar (SAR) data acquired by National Aeronautics and Space Administration (NASA) Uninhabited Aerial Vehicle SAR (UAVSAR) and the improvement of accuracy by adding canopy height information derived from stereo imagery acquired by Japan Aerospace Exploration Agency (JAXA) Panchromatic Remote Sensing Instrument for Stereo Mapping (PRISM) on-board the Advanced Land Observing Satellite (ALOS). Various models for prediction of forest biomass from UAVSAR data were investigated at pixel sizes of 1/4 ha (50 m x 50 m) and 1 ha. The variance inflation factor (VIF) was calculated for each of the explanatory variables in multivariable regression models to assess the multi-collinearity between explanatory variables. In addition, the t-and p-values were used to interpret the significance of the coefficients of each explanatory variables. The R(exp. 2), Root Mean Square Error (RMSE), bias and Akaike information criterion (AIC), and leave-one-out cross-validation (LOOCV) and bootstrapping were used to validate models. At 1/4-ha scale, the R(exp. 2) and RMSE of biomass estimation from a model using a single track of polarimetric UAVSAR data were 0.59 and 52.08 Mg/ha. With canopy height from PRISM as additional independent variable, R(exp. 2) increased to 0.76 and RMSE decreased to 39.74 Mg/ha (28.24%). At 1-ha scale, the RMSE of biomass estimation based on UAVSAR data of a single track was 39.42 Mg/ha with a R(exp. 2) of 0.77. With the canopy height from PRISM, R(exp. 2) increased to 0.86 and RMSE decreased to 29.47 Mg/ha (20.18%). The models using UAVSAR data alone underestimated biomass at levels above approximately 150 Mg/ha showing the saturation phenomenon. Adding canopy height from PRISM stereo imagery significantly improved the biomass estimation and elevated the saturation level in estimating biomass. Combined use of UAVSAR data acquired from opposite directions (odd and even tracks) slightly improved the biomass estimation.Combined use of UAVSAR data acquired from opposite directions (odd and even tracks) slightly improved the biomass estimation at 1/4-ha scale, R(exp. 2) increased from 0.59 to 0.66 and RMSE reduced from 52.08 to 48.57 Mg/ha. Averaging multiple acquisitions of UAVSAR data from the same look azimuth direction did not improve biomass estimation. A biomass map derived from NASA's LVIS (Laser Vegetation Imaging System) wave-form data was used as a reference for evaluation of the biomass maps from these models. The study has also shown that the errors decreased when deciduous, evergreen, and mixed forests were modeled separately but the improvement was not significant

Zhang, Zhiyu↗
NASA NTRS2012

Cloud Droplet Size and Liquid Water Path Retrievals From Zenith Radiance Measurements: Examples From the Atmospheric Radiation Measurement Program and the Aerosol Robotic Network

The ground-based Atmospheric Radiation Measurement Program (ARM) and NASA Aerosol Robotic Network (AERONET) routinely monitor clouds using zenith radiances at visible and near-infrared wavelengths. Using the transmittance calculated from such measurements, we have developed a new retrieval method for cloud effective droplet size and conducted extensive tests for non-precipitating liquid water clouds. The underlying principle is to combine a water-absorbing wavelength (i.e. 1640 nm) with a nonwater-absorbing wavelength for acquiring information on cloud droplet size and optical depth. For simulated stratocumulus clouds with liquid water path less than 300 g/sq m and horizontal resolution of 201m, the retrieval method underestimates the mean effective radius by 0.8 m, with a root-mean-squared error of 1.7 m and a relative deviation of 13 %. For actual observations with a liquid water path less than 450 gm.2 at the ARM Oklahoma site during 2007-2008, our 1.5 min-averaged retrievals are generally larger by around 1 m than those from combined ground-based cloud radar and microwave radiometer at a 5min temporal resolution. We also compared our retrievals to those from combined shortwave flux and microwave observations for relatively homogeneous clouds, showing that the bias between these two retrieval sets is negligible, but the error of 2.6 m and the relative deviation of 22% are larger than those found in our simulation case. Finally, the transmittance-based cloud effective droplet radii agree to better than 11% with satellite observations and have a negative bias of 1 m. Overall, the retrieval method provides reasonable cloud effective radius estimates, which can enhance the cloud products of both ARM and AERONET.

Chiu, J. C.↗
NASA NTRSDate not supplied

Changes in Plants Developed from Imbibed Seeds Irradiated by Simulated Solar Particle Events

One of the major concerns for long-term exploration missions beyond the Earth’s magnetosphere is radiation risk primarily from solar particle events (SPEs) and galactic cosmic rays (GCRs). With the goal of manned Mars exploration, the production of fresh food during long duration space missions may provide nutritional supplementation and benefit astronauts’ behavioral health. However, the effects of space radiation on plants and plant propagules have not been sufficiently investigated and characterized. In this study, we evaluated the effect of simulated GCRs on dry seeds of mizuna mustard, ‘Outredgeous’ red romaine lettuce, and ‘Red Robin’ dwarf tomato. Seeds were exposed to various doses of simulated GCRs (0, 40, and 80 cGy), either acutely or at a low dose rate (LDR), using the NASA Space Radiation Laboratory (NSRL) facility at Brookhaven National Lab (BNL). Control and irradiated seeds were planted and maintained under space-vehicle relevant controlled environment conditions. Plant/fruit morphometrics and edible fresh mass were measured. In addition, nutrient analyses were performed for both mizuna and ripe tomatoe fruit. Seedlings from irradiated seeds (both 40 cGy and 80 cGy) showed significant changes in cotyledon development, but not in root length or morphology. Interestingly, significant changes in vitamin content were found in mizuna grown from 80 cGy (LDR) irradiated seeds. In addition, 80 cGy (LDR) simulated GCRs significantly affected lettuce and tomato seed quality, delayed tomato fruiting, and reduced the total yield of tomato. Generally, compared to 80 cGy, 40 cGy (LDR) of simulated GCRs displayed some impacts to the seeds and seedlings, but to a much lesser degree. (This study was supported by NASA Human Research Program.)

J.T. Richards↗
NASA NTRS2021

Validation of SMAP L2 passive-only soil moisture products using upscaled in situ measurements collected in Twente, the Netherlands

The Twente region in the east of the Netherlands has a network with twenty soil monitoring stations that has been utilized for validation of the Soil Moisture Active/Passive (SMAP) passive-only soil moisture products. Over the period from April 2015 until December 2018, seven stations covered by the SMAP reference pixels 15 have fairly complete data records. Spatially distributed soil moisture simulations with the Dutch national hydrological model have been utilized for the development of upscaling functions to translate the spatial mean of point measurements to the domain of the SMAP reference pixels. The native and upscaled spatial soil moisture means computed using the in-situ measurements have been adopted as references to assess the performance of the SMAP i) Single Channel Algorithm at Horizontal Polarization (SCA-H), ii) Single Channel Algorithm at Vertical Polarization (SCA-V), and iii) Dual Channel Algorithm (DCA) soil moisture estimates. In the case of the Twente network it was found that the SCA-V soil moisture retrieved SMAP observations collected in the afternoon had the best agreement with the native spatial mean leading to an unbiased Root Mean Squared Error (uRMSE) of 0.059 m3 m-3, whereas for the upscaled in-situ references primarily larger biases were found. These error levels are larger than the mission’s target accuracy of 0.04 m3 m-3, which can be attributed to large over- and underestimation errors (>0.08 m3 m-3) in particular at the end of dry spells and during freezing, respectively. The strong vertical dielectric gradients associated with rapid soil freezing and wetting causes the disparity in soil depth characterized by SMAP and in situ that leads to the large mismatches. Once filtered for frozen conditions and antecedent rainfall the uRMSE improves to 0.043 m3 m-3.

Rogier van der Velde↗
NASA NTRS1997

A Comparison of Pressure Measurements Between a Full-Scale and a 1/16-Scale F/A-18 Twin Tail During Buffet

In 1993, tail buffet tests were performed on a full-scale, production model F/A-18 in the 80-by-120 Foot Wind Tunnel at NASA Ames Research Center. Steady and unsteady pressures were recorded on both sides of the starboard vertical tail for an angle of attack range of 20 to 40 degrees and at a sideslip range of -16 to 16 degrees at freestream velocities up to 100 knots (Mach 0.15, Reynolds number 1.23 x 10(exp 7)). The aircraft was equipped with removable leading edge extension (LEX) fences that are used in flight to reduce tail buffet loads. In 1995, tail buffet tests were performed on a 1/6-scale F-18 A/B model in the Transonic Dynamics Tunnel (TDT) at NASA Langley Research Center. Steady and unsteady pressures were recorded on both sides of both vertical tails for an angle-of-attack range of 7 to 37 degrees at freestream velocities up to 65 knots (Mach 0.10). Comparisons of steady and unsteady pressures and root bending moments are presented for these wind-tunnel models for selected test cases. Representative pressure and root bending moment power spectra are also discussed, as are selected pressure cross-spectral densities.

Moses, Robert W.↗
NASA NTRS2021

Seasonal Bias in Global Ocean Color Observations

In this study we identify a seasonal bias in the ocean color satellite derived remote sensing reflectances (Rrs(λ); sr-1) at the ocean color validation site, MOBY (Marine Optical BuoY). The seasonal bias in Rrs(λ) is present to varying degrees in all ocean color satellites examined, including VIIRS (Visible Infrared Imaging Radiometer Suite), SeaWiFS (Sea-viewing Wide Field-of-view Sensor), and MODIS (Moderate Resolution Imaging Spectrometer). The relative bias in Rrs has spectral dependence. Products derived from Rrs(λ) are affected by the bias to varying degrees, with particulate backscattering varying up to 50% over a year, chlorophyll varying up to 25% over a year, and absorption from phytoplankton or dissolved material varying by up to 15%. The propagation of Rrs(λ) bias into derived products is broadly confirmed on regional and global scales using Argo floats and data from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) instrument aboard the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder) satellite. The artifactual seasonality in ocean color is prominent in areas of low biomass (i.e., subtropical gyres) and is not easily discerned in areas of high biomass. While we have eliminated several candidates that could cause the biases in Rrs(λ), there are still outstanding questions regarding potential contributions from atmospheric corrections. Specifically, we provide evidence that the aquatic bidirectional reflectance distribution function may in part cause the observed seasonal bias, but this does not preclude an additional effect of the aerosol estimation. Our investigation highlights the contributions that atmospheric correction schemes can make in introducing biases in Rrs (λ) and we recommend more simulations to discern these influence Rrs (λ) biases. Community efforts are needed to find the root cause of the seasonal bias because all past, present, and future data are or will be affected until a solution is implemented.

satellite ocean color↗
NASA NTRS1996

A Comparison of Pressure Measurements Between a Full-Scale and a 1/6-Scale F/A-18 Twin Tail During Buffet

In 1993, tail buffet tests were performed on a full-scale, production model F/A-18 in the 80 x 120-foot Wind Tunnel at NASA Ames Research Center. Steady and unsteady pressures were recorded on both sides of the starboard vertical tail for an angle-of-attack range of 20 to 40 degrees and at a sideslip range of -1 6 to 16 degrees at freestream velocities up to 100 knots (Mach 0.15, Reynolds number 1.23 x 10(exp 7). The aircraft was equipped with removable leading edge extension (LEX) fences that are used in flight to reduce tail buffet loads. In 1995, tail buffet tests were performed on a 1/6-scale F-18 A/B model in the Transonic Dynamics Tunnel (TDT) at NASA Langley Research Center. Steady and unsteady pressures were recorded on both sides of both vertical tails for an angle-of-attack range of 7 to 37 degrees at freestream velocities up to 65 knots (Mach 0.10). Comparisons of steady and unsteady pressures and root bending moments are presented for these wind-tunnel models for selected test cases. Representative pressure and root bending moment power spectra are also discussed, as are selected pressure cross-spectral densities.

Moses, Robert W.↗
NASA NTRS2021

Weekly Mapping of Sea Ice Freeboard in the Ross Sea from ICESat-2

NASA’s ICESat-2 has been providing sea ice freeboard measurements across the polar regions since October 2018. In spite of the outstanding spatial resolution and precision of ICESat-2, the spatial sparsity of the data can be a critical issue for sea ice monitoring. This study employs a geostatistical approach (i.e., ordinary kriging) to characterize the spatial autocorrelation of the ICESat-2 freeboard measurements (ATL10) to estimate weekly freeboard variations in 2019 for the entire Ross Sea area, including where ICESat-2 tracks are not directly available. Three variogram models (exponential, Gaussian, and spherical) are compared in this study. According to the cross-validation results, the kriging-estimated freeboards show correlation coefficients of 0.56–0.57, root mean square error (RMSE) of ~0.12 m, and mean absolute error (MAE) of ~0.07 m with the actual ATL10 freeboard measurements. In addition, the estimated errors of the kriging interpolation are low in autumn and high in winter to spring, and low in southern regions and high in northern regions of the Ross Sea. The effective ranges of the variograms are 5–10 km and the results from the three variogram models do not show significant differences with each other. The southwest (SW) sector of the Ross Sea shows low and consistent freeboard over the entire year because of the frequent opening of wide polynya areas generating new ice in this sector. However, the southeast (SE) sector shows large variations in freeboard, which demonstrates the advection of thick multiyear ice from the Amundsen Sea into the Ross Sea. Thus, this kriging-based interpolation of ICESat-2 freeboard can be used in the future to estimate accurate sea ice production over the Ross Sea by incorporating other remote sensing data.

Satellite altimeter↗
NASA NTRS2016

DeepSAT: A Deep Learning Approach to Tree-Cover Delineation in 1-m NAIP Imagery for the Continental United States

High resolution tree cover classification maps are needed to increase the accuracy of current land ecosystem and climate model outputs. Limited studies are in place that demonstrates the state-of-the-art in deriving very high resolution (VHR) tree cover products. In addition, most methods heavily rely on commercial softwares that are difficult to scale given the region of study (e.g. continents to globe). Complexities in present approaches relate to (a) scalability of the algorithm, (b) large image data processing (compute and memory intensive), (c) computational cost, (d) massively parallel architecture, and (e) machine learning automation. In addition, VHR satellite datasets are of the order of terabytes and features extracted from these datasets are of the order of petabytes. In our present study, we have acquired the National Agriculture Imagery Program (NAIP) dataset for the Continental United States at a spatial resolution of 1-m. This data comes as image tiles (a total of quarter million image scenes with ~60 million pixels) and has a total size of ~65 terabytes for a single acquisition. Features extracted from the entire dataset would amount to ~8-10 petabytes. In our proposed approach, we have implemented a novel semi-automated machine learning algorithm rooted on the principles of "deep learning" to delineate the percentage of tree cover. Using the NASA Earth Exchange (NEX) initiative, we have developed an end-to-end architecture by integrating a segmentation module based on Statistical Region Merging, a classification algorithm using Deep Belief Network and a structured prediction algorithm using Conditional Random Fields to integrate the results from the segmentation and classification modules to create per-pixel class labels. The training process is scaled up using the power of GPUs and the prediction is scaled to quarter million NAIP tiles spanning the whole of Continental United States using the NEX HPC supercomputing cluster. An initial pilot over the state of California spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles has produced true positive rates of around 88 percent for fragmented forests and 74 percent for urban tree cover areas, with false positive rates lower than 2 percent for both landscapes.

Imagery↗
NASA NTRS2023

Application of Bioengineering in Space Exploration - Sleep Study System

Bioengineering has spread roots far and wide among the needs of space exploration. The field creates many of paths to generate information from a variety of sources. One such source is the astronauts on the International Space Station (ISS). As of now the investigation is focused on the quality of sleep of crew members during a long duration flight. Our team is investing time into a piece of hardware’s comfort, waste, and operability. The hardware was not originally designed for space; therefore, the device must be modified to function at a optimal level in space. The design not made for space has generated some ailments, such as discomfort and decreased mobility. A function of the internship was to produce designs that would manage the wires to increase mobility and comfort. The wires excess slack was reduced by the part that was designed. The piece was adjustable, so the patient may adjust the system to their comfort and space compatible material was used. This product will help control the direction and length of the wires, thereby aiding in comforting the patient. This multifaceted design may be used in future for all other wire management for wearable biomedical sensor on orbit.

Biomedical↗
NASA NTRS2014

Large Plant Growth Chambers: Flying Soon on a Space Station near You!

The International Space Station (ISS) now has platforms for conducting research on horticultural plant species, and those capabilities continue to grow. The Veggie vegetable production system will be deployed to the ISS in Spring of 2014 to act as an applied research platform with goals of studying food production in space, providing the crew with a source of fresh food, allowing behavioral health and plant microbiology experimentation, and being a source of recreation and enjoyment for the crew. Veggie was conceived, designed, and constructed by Orbital Technologies Corporation (ORBITEC, Madison, WI). Veggie is the largest plant growth chamber that NASA has flown to date, and is capable of growing a wide array of horticultural crops. It was designed for low energy usage, low launch mass and stowage volume, and minimal crew time requirements. The Veggie flight hardware consists of a light cap containing red (630 nanometers), blue, (455 nanometers) and green (530 nanometers) light emitting diodes. Interfacing with the light cap is an extendable bellows baseplate secured to the light cap via magnetic closures and stabilized with extensible flexible arms. The baseplate contains vents allowing air from the ISS cabin to be pulled through the plant growth area by a fan in the light cap. The baseplate holds a Veggie root mat reservoir that will supply water to plant pillows attached via elastic cords. Plant pillows are packages of growth media and seeds that will be sent to ISS dry and installed and hydrated on orbit. Pillows can be constructed in various sizes for different plant types. Watering will be via passive wicking from the root mat to the pillows. Science procedures will include photography or videography, plant thinning, pollination, harvesting, microbial sampling, water sampling, etcetera. Veggie is one of the ISS flight options currently available for research investigations on plants. The Plant Habitat (PH) is being designed and constructed through a NASA-ORBITEC collaboration, and is scheduled to fly on ISS around 2016. This large plant chamber will control light quality, level, and timing, temperature, CO2, relative humidity, and irrigation, while scrubbing ethylene. Additional monitoring capabilities include leaf temperature sensing and root zone moisture and oxygen sensing. The PH light cap will have red (630 nanometers), blue (450 nanometers), green (525 nanometers), far red (730 nanometers) and broad spectrum white light emitting diodes. There will be several internal cameras to monitor and record plant growth and operations.

Space Biology↗