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NASA NTRS2000

BOREAS Forest Cover Data Layers of the NSA in Raster Format

This data set was processed by BORIS staff from the original vector data of species, crown closure, cutting class, and site classification/subtype into raster files. The original polygon data were received from Linnet Graphics, the distributor of data for MNR. In the case of the species layer, the percentages of species composition were removed. This reduced the amount of information contained in the species layer of the gridded product, but it was necessary in order to make the gridded product easier to use. The original maps were produced from 1:15,840-scale aerial photography collected in 1988 over an area of the BOREAS NSA MSA. The data are stored in binary, image format files and they are available from Oak Ridge National Laboratory. The data files are available on a CD-ROM (see document number 20010000884).

Hall, Forrest G.↗

NASA NTRS1973

Mapping coastal vegetation, land use and environmental impact from ERTS-1

The author has identified the following significant results. Vegetation map overlays at a scale of 1:24,000 compiled by multispectral analysis from NASA aircraft imagery for all of Delaware's wetlands are being used as ground truth for ERTS-1 mapping and by state agencies for wetlands management. Six major vegetation species were discriminated and mapped, including percentages of minor species. Analogue enhancements of wetlands vegetation and dredge-fill operations have been produced using General Electric's GEMS data processing and ERTS-1 false color composites. Digital, thematic land use, and vegetation mapping of entire Delaware Bay area is in progress using Bendix Corporation's Earth Resources Data System and ERTS-1 digital tapes. Statistical evaluation of target-group selection reliability has been completed. Three papers have been published on ERTS-1 coastal vegetation and land use. Local and state officials are participating in the ERTS-1 program as co-investigators.

Klemas, V.↗

NASA NTRS2018

Simulating Forest Dynamics of Lowland Rainforests in Eastern Madagascar

Ecological modeling and forecasting are essential tools for the understanding of complex vegetation dynamics. The parametric demands of some of these models are often lacking or scant for threatened ecosystems, particularly in diverse tropical ecosystems. One such ecosystem and also one of the world's biodiversity hotspots, Madagascar's lowland rainforests, have disappeared at an alarming rate. The processes that drive tree species growth and distribution remain as poorly understood as the species themselves. We investigated the application of the process-based individual-based FORMIND model to successfully simulate a Madagascar lowland rainforest using previously collected multi-year forest inventory plot data. We inspected the model's ability to characterize growth and species abundance distributions over the study site, and then validated the model with an independently collected forest-inventory dataset from another lowland rainforest in eastern Madagascar. Following a comparative analysis using inventory data from the two study sites, we found that FORMIND accurately captures the structure and biomass of the study forest, with r(squared) values of 0.976, 0.895, and 0.995 for 1:1 lines comparing observed and simulated values across all plant functional types for aboveground biomass (tonnes/ha), stem numbers, and basal area (m(squared)/ha), respectively. Further, in validation with a second study forest site, FORMIND also compared well, only slightly over-estimating shade-intermediate species as compared to the study site, and slightly under-representing shade-tolerant species in percentage of total aboveground biomass. As an important application of the FORMIND model, we measured the net ecosystem exchange (NEE, in tons of carbon per hectare per year) for 50 ha of simulated forest over a 1000-year run from bare ground. We found that NEE values ranged between 1 and -1 t Cha(exp -1)year(exp -1), consequently the study forest can be considered as a net neutral or a very slight carbon sink ecosystem, after the initial 130 years of growth. Our study found that FORMIND represents a valuable tool toward simulating forest dynamics in the immensely diverse Madagascar rainforests.

Forest Productivity↗

NASA NTRSDate not supplied

Investigation of Prophage Regions of Bacterial Strains Isolated from the International Space Station (ISS)

Space flight agencies are planning missions back to the Moon and to Mars. When sending humans into space, it is impossible to separate them from microorganisms, either in their associated microbiome or in the spacecraft environment, which are modified through the movement of genetic material. Bacteriophages, small viruses that invade and replicate within bacterial cells, play a central role in the genetic composition and evolution of microorganisms. Lysogenic bacteriophages can insert themselves into the DNA of their bacterial hosts, forming prophage regions, which can also transfer genes from previous hosts. Thus, we aimed to identify and classify all prophages from twelve bacterial species cultured from the International Space Station (ISS) from 2017 to 2018. We determined representative bacterial strains for each species, whose genomes were analyzed to identify prophage regions. Complete prophages were identified through database searches and the number of prophage regions were compared to terrestrial analogs. Additionally, prophage region and genome sizes were compared for each species, identifying the percentage of bacteriophage DNA in each genome. We determined that the prophage-susceptible bacterial species isolated from the ISS had a higher number of prophage regions when compared to terrestrial analogs, as well as having a larger percentage of their genomes made up of prophage material. Of the eighteen complete prophages identified, 72.2% were of family Siphoviridae and 27.8% were of family Myoviridae. Only one of the prophages had a BLAST similarity over 80%, suggesting that the remainder of prophages are novel species. These results imply that there is a higher rate of prophage transduction and lysogeny during spaceflight, and that the prophages present are novel.

Phage↗

NASA NTRS2011

Small-Scale Dissipation in Binary-Species Transitional Mixing Layers

Motivated by large eddy simulation (LES) modeling of supercritical turbulent flows, transitional states of databases obtained from direct numerical simulations (DNS) of binary-species supercritical temporal mixing layers were examined to understand the subgrid-scale dissipation, and its variation with filter size. Examination of the DSN-scale domain- averaged dissipation confirms previous findings that, out of the three modes of viscous, temperature and species-mass dissipation, the species-mass dissipation is the main contributor to the total dissipation. The results revealed that the percentage of species-mass by total dissipation is nearly invariant across species systems and initial conditions. This dominance of the species-mass dissipation is due to high-density-gradient magnitude (HDGM) regions populating the flow under the supercritical conditions of the simulations; such regions have also been observed in fully turbulent supercritical flows. The domain average being the result of both the local values and the extent of the HDGM regions, the expectations were that the response to filtering would vary with these flow characteristics. All filtering here is performed in the dissipation range of the Kolmogorov spectrum, at filter sizes from 4 to 16 times the DNS grid spacing. The small-scale (subgrid scale, SGS) dissipation was found by subtracting the filtered-field dissipation from the DNS-field dissipation. In contrast to the DNS dissipation, the SGS dissipation is not necessarily positive; negative values indicate backscatter. Backscatter was shown to be spatially widespread in all modes of dissipation and in the total dissipation (25 to 60 percent of the domain). The maximum magnitude of the negative subgrid- scale dissipation was as much as 17 percent of the maximum positive subgrid- scale dissipation, indicating that, not only is backscatter spatially widespread in these flows, but it is considerable in magnitude and cannot be ignored for the purposes of LES modeling. The Smagorinsky model, for example, is unsuited for modeling SGS fluxes in the LES because it cannot render backscatter. With increased filter size, there is only a modest decrease in the spatial extent of backscatter. The implication is that even at large LES grid spacing, the issue of backscatter and related SGS-flux modeling decisions are unavoidable. As a fraction of the total dissipation, the small-scale dissipation is between 10 and 30 percent of the total dissipation for a filter size that is four times the DNS grid spacing, with all OH cases bunched at 10 percent, and the HN cases spanning 24 30 percent. A scale similarity was found in that the domain-average proportion of each small-scale dissipation mode, with respect to the total small-scale dissipation, is very similar to equivalent results at the DNS scale. With increasing filter size, the proportion of the small-scale dissipation in the dissipation increases substantially, although not quite proportionally. When the filter size increases by four-fold, 52 percent for all OH runs, and 70 percent for HN runs, of the dissipation is contained in the subgrid-scale portion with virtually no dependence on the initial conditions of the DNS. The indications from the dissipation analysis are that modeling efforts in LES of thermodynamically supercritical flows should be focused primarily on mass-flux effects, with temperature and viscous effects being secondary. The analysis also reveals a physical justification for scale-similarity type models, although the suitability of these will need to be confirmed in a posteriori studies.

Bellan, Josette↗

NASA NTRS1973

Iterative techniques to estimate signature vectors for mixture processing of multispectral data

Two methods for obtaining the required spectral signatures for a particular mixture model are considered. For the model considered, the spectral signatures become signature vectors. The first method is based upon determination of the signature vectors in such a way that a measure of the inconsistency between the mixture model and the observed data is minimized. The second method is based upon determination of the signature vectors in such a way that the estimated mean percentage coverage of individual species matches apriori or ground truth estimates. The two methods proposed are applied to actual multispectral data in order to verify the concepts presented.

Salvato, P., Jr.↗

NASA NTRS2016

Spaceborne Remote Sensing of Aerosol Type: Global Distribution, Model Evaluation and Translation into Chemical Speciation

It is essential to evaluate and refine aerosol classification methods applied to passive satellite remote sensing. We have developed an aerosol classification algorithm (called Specified Clustering and Mahalanobis Classification, SCMC) that assigns an aerosol type to multi-parameter retrievals by spaceborne, airborne or ground-based passive remote sensing instruments [1]. The aerosol types identified by our scheme are pure dust, polluted dust, urban-industrialdeveloped economy, urban-industrialdeveloping economy, dark biomass smoke, light biomass smoke and pure marine. We apply the SCMC method to inversions from the ground-based AErosol RObotic NETwork (AERONET [2]) and retrievals from the space-borne Polarization and Directionality of Earths Reflectances instrument (POLDER, [3]). The POLDER retrievals that we use differ from the standard POLDER retrievals [4] as they make full use of multi-angle, multispectral polarimetric data [5]. We analyze agreement in the aerosol types inferred from both AERONET and POLDER and evaluate GEOS-Chem [6] simulations over the globe. Finally, we use in-situ observations from the SEAC4RS airborne field experiment to bridge the gap between remote sensing-inferred qualitative SCMC aerosol types and their corresponding quantitative chemical speciation. We apply the SCMC method to airborne in-situ observations from the NASA Langley Aerosol Research Group Experiment (LARGE, [7]) and the Differential Aerosol Sizing and Hygroscopicity Spectrometer Probe (DASH-SP, [8]) instruments; we then relate each coarsely defined SCMC type to a sum of percentage of individual aerosol species, using in-situ observations from the Particle Analysis by Laser Mass Spectrometry (PALMS, [9]), the Soluble Acidic Gases and Aerosol (SAGA, [10]), and the High - Resolution Time - of - Flight Aerosol Mass Spectrometer (HR ToF AMS, [11]).

airborne↗

NASA NTRS2007

Characterization of Forested Landscapes From Remotely Sensed Data Using Fractals and Spatial Autocorrelation

The characterization of forested areas is frequently required in resource management practice. Passive remotely sensed data, which are much more accessible and cost effective than are active data, have rarely, if ever, been used to characterize forest structure directly, but rather they usually focus on the estimation of indirect measurement of biomass or canopy coverage. In this study, some spatial analysis techniques are presented that might be employed with Landsat TM data to analyze forest structure characteristics. A case study is presented wherein fractal dimensions, along with a simple spatial autocorrelation technique (Moran s I), were related to stand density parameters of the Oakmulgee National Forest located in the southeastern United States (Alabama). The results of the case study presented herein have shown that as the percentage of smaller diameter trees becomes greater, and particularly if it exceeds 50%, then the canopy image obtained from Landsat TM data becomes sufficiently homogeneous so that the spatial indices reach their lower limits and thus are no longer determinative. It also appears, at least for the Oakmulgee forest, that the relationships between the spatial indices and forest class percentages within the boundaries can reasonably be considered linear. The linear relationship is much more pronounced in the sawtimber and saplings cases than in samples dominated by medium sized trees (poletimber). In addition, it also appears that, at least for the Oakmulgee forest, the relationships between the spatial indices and forest species groups (Hardwood and Softwood) percentages can reasonably be considered linear. The linear relationship is more pronounced in the forest species groups cases than in the forest classes cases. These results appear to indicate that both fractal dimensions and spatial autocorrelation indices hold promise as means of estimating forest stand characteristics from remotely sensed images. However, additional work is needed to confirm that the boundaries identified for Oakmulgee forest and the linear nature of the relationship between image complexity indices and forest characteristics are generally evident in other forests. In addition, the effects of other parameters such ,as topographic relief and image distortion due to sun angle and cloud cover, for example, need to be examined.

Al-Hamdan, Mohammad Z.↗

NASA NTRS1979

A model of the Venus atmosphere from radio, radar, and occultation observations

A model is presented of the atmosphere and surface of Venus which best fits in the least-squares sense the available radio-brightness, radar cross-section, radio interferometric, and Mariner 5 and 10 radio occultation observations. The determinations of the radius of the planet obtained by others from radar time-delay measurements are included in the data set. The values of the adjusted parameters are: molar fraction of CO2 = 95 plus or minus 3%; fraction of combined nitrogen and argon = 5 plus or minus 3%; total atmospheric opacity at a wavelength of 1 cm = 19.4 plus or minus 1.3; mean radius of the surface = 6050.7 plus or minus 0.8 km; mean dielectric constant of the surface = 4.1 plus or minus 0.2, and percentage of total opacity due to chemical species other than CO2 = 45 plus or minus 12. The model temperature and pressure at the mean surface are 755 K and 91.4 atm, respectively.

Muhleman, D. O.↗

NASA NTRS2021

Residual Temperature Bias Effects in Stratospheric Species Distributions from LIMS

The Nimbus 7 Limb Infrared Monitor of theStratosphere (LIMS) instrument operated from 25 Octo-ber 1978 through 28 May 1979. Its version 6 (V6) profileswere processed and archived in 2002. We present severaldiagnostic examples of the quality of the V6 stratospheric species distributions based on their level 3 zonal Fourier co-efficient products. In particular, we show that there are smalldifferences in the ascending (A) minus descending (D) or-bital temperature–pressure orT(p) profiles (theirA−Dval-ues) that affect (A−D) species values. SystematicA−Dbi-ases inT(p) can arise from small radiance biases and/or fromviewing anomalies along orbits. There can also be (A−D)differences inT(p) due to not resolving and correcting forall of the atmospheric temperature gradient along LIMS tan-gent view-paths. An error inT(p) affects species retrievalsthrough (1) the Planck blackbody function in forward calcu-lations of limb radiance that are part of the iterative retrievalalgorithm of LIMS, and (2) the registration of the measuredLIMS species radiance profiles in pressure altitude, mainlyfor the lower stratosphere. There are clearA−Ddifferencesfor ozone, H2O, and HNO3but not for NO2. Percentage differences are larger in the lower stratosphere for ozone andH2O because those species are optically thick. We evaluateV6 ozone profile biases in the upper stratosphere with the aid of comparisons against a monthly climatology of UV–ozone soundings from rocketsondes. We also provide resultsof time series analyses of V6 ozone, H2O, and potential vor-ticity for the middle stratosphere to show that their average(A+D) V6 level 3 products provide a clear picture of the evolution of those tracers during Northern Hemisphere win-ter. We recommend that researchers use the average V6 level3 product for their science studies of stratospheric ozone andH2O, while keeping in mind that there are uncorrected non-local thermodynamic equilibrium effects in daytime ozone inthe lower mesosphere and in daytime H2O in the uppermoststratosphere. We also point out that the present-day Soundingof the Atmosphere using Broadband Emission Radiometry(SABER) experiment provides measurements and retrievalsof temperature and ozone that are nearly free of anomalousdiurnal variations and of effects from gradients at low and middle latitudes.

Ellis Remsberg↗

NASA NTRS2021

Synthesizing Disparate LiDAR and Satellite Datasets through Deep Learning to Generate Wall-to-Wall Regional Inventories for the Complex, Mixed-Species Forests of the Eastern United States

Light detection and ranging (LiDAR) has become a commonly-used tool for generating remotely-sensed forest inventories. However, LiDAR-derived forest inventories have remained uncommon at a regional scale due to varying parameters among LiDAR data acquisitions and the availability of sufficient calibration data. Here, we present a model using a 3-D convolutional neural network (CNN), a form of deep learning capable of scanning a LiDAR point cloud, combined with coincident satellite data (spectral, phenology, and disturbance history). We compared this approach to traditional modeling used for making forest predictions from LiDAR data (height metrics and random forest) and found that the CNN had consistently lower uncertainty. We then applied the CNN to public data over six New England states in the USA, generating maps of 14 forest attributes at a 10 m resolution over 85% of the region. Aboveground biomass estimates produced a root mean square error of 36 Mg ha−1 (44%) and were within the 97.5% confidence of independent county-level estimates for 33 of 38 or 86.8% of the counties examined. CNN predictions for stem density and percentage of conifer attributes were moderately successful, while predictions for detailed species groupings were less successful. The approach shows promise for improving the prediction of forest attributes from regional LiDAR data and for combining disparate LiDAR datasets into a common framework for large-scale estimation.

Elias Ayrey↗

NASA NTRS2000

Natural transfer of viable microbes in space

The possibility and probability of natural transfer of viable microbes from Mars to Earth and Earth to Mars traveling in meteoroids during the first 0.5 Ga and the following 4 Ga are investigated, including: --radiation protection against the galactic cosmic ray nuclei and the solar rays, dose rates as a function of the meteorite's radial column mass (radius x density), combined with dose rates generated by natural radioactivity within the meteorite; and survival curves for some bacterial species using NASA's HZETRN transport code --other factors affecting microbe survival: vacuum; central meteorite temperatures at launch, orbiting, and arrival; pressure and acceleration at launch; spontaneous DNA decay; metal ion migration --mean sizes and numbers of unshocked meteorites ejected and percentage falling on Earth, using current semiempirical results --viable flight times for the microbe species Bacillus subtilis and Deinococcus radiodurans R1 --the approximate fraction of microbes (with properties like the two species studied) viably arriving on Earth out of those ejected from Mars during the period 4 Ga BP to the present time, and during the 700 Ma from 4.5 to 3.8 Ga. Similarly, from Earth to Mars. The conclusion is that if microbes existed or exist on Mars, viable transfer to Earth is not only possible but also highly probable, due to microbes' impressive resistance to the dangers of space transfer and to the dense traffic of billions of martian meteorites which have fallen on Earth since the dawn of our planetary system. Earth-to-Mars transfer is also possible but at a much lower frequency.

Non-NASA Center↗

NASA NTRS1976

A LANDSAT study of ephemeral and perennial rangeland vegetation and soils

The author has identified the following significant results. Several methods of computer processing were applied to LANDSAT data for mapping vegetation characteristics of perennial rangeland in Montana and ephemeral rangeland in Arizona. The choice of optimal processing technique was dependent on prescribed mapping and site condition. Single channel level slicing and ratioing of channels were used for simple enhancement. Predictive models for mapping percent vegetation cover based on data from field spectra and LANDSAT data were generated by multiple linear regression of six unique LANDSAT spectral ratios. Ratio gating logic and maximum likelihood classification were applied successfully to recognize plant communities in Montana. Maximum likelihood classification did little to improve recognition of terrain features when compared to a single channel density slice in sparsely vegetated Arizona. LANDSAT was found to be more sensitive to differences between plant communities based on percentages of vigorous vegetation than to actual physical or spectral differences among plant species.

Bentley, R. G., Jr.↗

NASA NTRS1990

Electrochemical amperometric gas sensors for environmental monitoring and control

Theoretical considerations and experimental results regarding a unique class of vapor sensors are presented, and the sensors are compared to semiconductor-based sensors. The electrochemical sensors are based on nonaquaeous electrolytes, and gas-detection selectivity achieved by applying a known potential to the sensing electrode using a reference electrode and a counter electrode. Results are given regarding the detection of oxygen and carbon dioxide using one cell, the detection of 3-percent carbon dioxide in nitrogen, and the detection of carbon dioxide in air at percentages ranging from 3 to 6. The sensors are found to be effective in the detection of toxic chemical species including CO, NO2, and formaldehyde; the sensors are further found to require minimal power, operate over long periods of time, and function over a wide temperature range.

Venkatasetty, H. V.↗

NASA NTRSDate not supplied

Benefits of Trash-to-Gas Versus Jettison of Waste Via Trash-Lock for Mars Transit

Human exploration missions to Mars pose difficulties due to the significant waste that will be generated during transit, which will need to be carried along or disposed of in some fashion. Waste removal from the spacecraft decreases the spacecraft’s mass as well as the associated logistic items necessary for storing the waste. A mission propellant analysis was performed to highlight the mass benefits that may be accessed via waste removal. The propellant mass savings were determined for different waste removal rates (2.9 – 11.6 kg/day) with the highest removal rate leading to the greatest propellant savings of 7,785 kg for an 850-day round-trip mission. Due to these benefits, two methods for waste reduction were studied for the 850-day Mars mission: Trash-to-Gas (TtG) and physical jettison via a trash-lock. The trash-to-gas methods considered were combustion, steam reforming, and pyrolysis, which convert waste into ventable gases (e.g., CO2, CO, CH4, etc.). Combustion and steam reforming require a co-reactant (O2 and/or H2O). Therefore, additional processing units or integration with the spacecraft’s environmental control and life support system (ECLSS) are required to facilitate recycle of the pertinent species. In contrast, pyrolysis is a purely thermal degradation process, which can operate as a standalone system; however, a lower percentage of waste is gasified with pyrolysis. The study herein compares standalone TtG (e.g., Advanced Organic Waste Gasifier, Plasma Pyrolysis, etc.), integrated TtG-ECLSS (e.g., Orbital Syngas Commodity Augmentation Reactor, Incineration/Gasification, etc.), and physical jettison. Each system’s mass, volume, power, and cooling requirements were compared via an equivalent system mass (ESM) analysis to ascertain potentially promising technologies that can achieve efficient waste removal while minimizing their own spacecraft load. This study highlights the advantages and disadvantages of the different waste management technologies and provides recommendations on the promising technologies based on the ESM metric and propellant mass savings.

Jettison↗

NASA NTRS1972

Remote sensing in Virginia agriculture

An experimental investigation, designed to develop and evaluate multispectral sensing techniques used in sensing agricultural crops, is described. Initial studies were designed to detect plant species and associated diseases, soil variations, and cultural practices under natural environment conditions. In addition, crop varieties, age, spacing, plant height, percentage of ground cover, and plant vigor are determined.

Pettry, D. E.↗

NASA NTRS1996

Proximate composition of CELSS crops grown in NASA's Biomass Production Chamber

Edible biomass from four crops of wheat (Triticum aestivum L.), four crops of lettuce (Lactuca sativa L.), four crops of potato (Solanum tuberosum L.), and three crops of soybean (Glycine max (L.) Merr.) grown in NASA's CELSS Biomass Production Chamber were analyzed for proximate composition. All plants were grown using recirculating nutrient (hydroponic) film culture with pH and electrical conductivity automatically controlled. Temperature and humidity were controlled to near optimal levels for each species and atmospheric carbon dioxide partial pressures were maintained near 100 Pa during the light cycles. Soybean seed contained the highest percentage of protein and fat, potato tubers and wheat seed contained the highest levels of carbohydrate, and lettuce leaves contained the highest level of ash. Analyses showed values close to data published for field-grown plants with several exceptions: In comparison with field-grown plants, wheat seed had higher protein levels; soybean seed had higher ash and crude fiber levels; and potato tubers and lettuce leaves had higher protein and ash levels. The higher ash and protein levels may have been a result of the continuous supply of nutrients (e.g., potassium and nitrogen) to the plants by the recirculating hydroponic culture.

NASA Discipline Life Support Systems↗

NASA NTRS1971

Sleep in the nocturnal primate, Aotus trivirgatus.

Measurement of the cycles of wakefulness and stages of sleep in owl monkeys during 24-hr periods divided into half dark and half light segments. Recordings of electrophysiological activity were used. Reversal of the sequence of light and dark served to test the influence of environmental lighting on the sleep-wakefulness cycles. The sleep patterns of owl monkeys expressed in percentage of rapid eye movement (REM) and nonrapid eye movement (NREM) were compared with those of a closely related New World monkey species, Saimiri Sciureus.

Perachio, A. A.↗