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At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

DEEPER: An Intergrated Platform for Deeper Roots

Crops with deeper roots would have multiple benefits, including better drought tolerance, reduced requirement for nitrogen fertilizer, and better sequestration of atmospheric CO 2 . DEEPER is an integrated platform of phenomic, genomic, and in silico technologies to generate maize lines with deeper roots. DEEPER is: LEADER (Leaf Elemental Accumulation from Deep Roots) is a breakthrough technology to nondestructively measure rooting depth by using the plant itself as a sensor. LEADER uses handheld X-ray Fluorescence spectrometry to quantify foliar accumulation of elements that are differentially distributed in the soil profile. LEADER is nondestructive and is orders of magnitude cheaper, faster, and more precise than any competing assay of rooting depth in the field. LEADER is able to distinguish deep-rooted from shallow-rooted maize lines in the field without the need for costly and noisy soil coring. RootRobot/DIRT3D, to automatically phenotype root architecture in any field, combining RootRobot, a mechatronics platform to excavate, clean, section, and image mature root crowns, with DIRT3D, software to quantify architectural traits in 3D. Anatomics, a high-throughput platform to phenotype root anatomy, combining LAT 2.0, a technology for 3D imaging of root anatomy and composition, with RootScan3D, software to automatically extract 3D anatomical and cell wall composition metrics from LAT 2.0 output. Using this platform we discovered two novel root traits, parenchyma cell wall thickness and multiseriate cortical sclerenchyma, that improve rooting depth and drought tolerance in maize and wheat. OpenSimRoot/Deep, software to simulate root interaction with hard subsoils. Using this platform we discovered novel concepts regarding how to increase crop rooting depth by modulating how individual root axes respond to hard soil. DeepGenes, a toolkit of genes, parent lines, and genomic selection strategies to enable breeding hybrids with deeper roots. We discovered 3 novel root genes that increase rooting depth in maize and wheat. DEEPER discovered novel root phenotypes for deeper rooting, and delivered validated ideotypes for deeper-rooted maize; novel technologies to rapidly assess root depth, root architecture and anatomy in field-grown plants; novel software tools for root modeling and 3D image analysis of root architecture and anatomy; and validated genes and genomic selection models to deploy traits for deeper rooting in maize breeding. Each DEEPER technology is transformative in its own right, and exceeds existing technologies. They are mutually synergistic, deployable for field-grown plants, and are ready for application. The phenotyping and modeling technologies are readily applicable to many crops, and genetic leads in maize may have utility in other grasses. Taken as a whole they represent a transformative platform to develop deeper-rooted crops, with greater drought tolerance, reduced fertilizer requirement, and greater carbon sequestration.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1974

Geologic information from satellite images

Extracting geologic information from ERTS and Skylab/EREP images is best done by a geologist trained in photo-interpretation. The information is at a regional scale, and three basic types are available: rock and soil, geologic structures, and landforms. Discrimination between alluvium and sedimentary or crystalline bedrock, and between units in thick sedimentary sequences is best, primarily because of topographic expression and vegetation differences. Discrimination between crystalline rock types is poor. Folds and fractures are the best displayed geologic features. They are recognizable by topographic expression, drainage patterns, and rock or vegetation tonal patterns. Landforms are easily discriminated by their familiar shapes and patterns. Several examples demonstrate the applicability of satellite images to tectonic analysis and petroleum and mineral exploration.

Lee, K.↗
NASA NTRS1976

Surface and atmosphere parameter maps from earth-orbiting radiometers

Earlier studies have shown that an earth-orbiting electrically scanned microwave radiometer (ESMR) is capable of inferring the extent, concentration, and age of sea ice; the extent, concentration, and thickness of lake ice; rainfall rates over oceans; surface wind speeds over open water; particle size distribution in the deep snow cover of continental ice sheets; and soil moisture content in unvegetated fields. Most other features of the surface of the earth and its atmosphere require multispectral imaging techniques to unscramble the combined contributions of the atmosphere and the surface. Multispectral extraction of surface parameters is analyzed on the basis of a pertinent equation in terms of the observed brightness temperature, the emissivity of the surface which depends on wavelength and various parameters, the sensible temperature of the surface, and the total atmospheric opacity which is also wavelength dependent. Implementation of the multispectral technique is examined. Properties of the surface of the earth and its atmosphere to be determined from a scanning multichannel microwave radiometer are tabulated.

Gloersen, P.↗
NASA NTRS1977

Utilization of remote sensing observations in hydrologic models

Most of the remote sensing related work in hydrologic modeling has centered on modifying existing models to take advantage of the capabilities of new sensor techniques. There has been enough success with this approach to insure that remote sensing is a powerful tool in modeling the watershed processes. Unfortunately, many of the models in use were designed without recognizing the growth of remote sensing technology. Thus, their parameters were selected to be map or field crew definable. It is believed that the real benefits will come through the evolution of new models having new parameters that are developed specifically to take advantage of our capabilities in remote sensing. The ability to define hydrologically active areas could have a significant impact. The ability to define soil moisture and the evolution of new techniques to estimate evoportransportation could significantly modify our approach to hydrologic modeling. Still, without a major educational effort to develop an understanding of the techniques used to extract parameter estimates from remote sensing data, the potential offered by this new technology will not be achieved.

Ragan, R. M.↗
NASA NTRS2004

Reflectance and Thermal Infrared Spectroscopy of Mars: Relationship Between ISM and TES for Compositional Determinations

Reflectance spectroscopy has demonstrated that high albedo surfaces on Mars contain heavily altered materials with some component of hematite, poorly crystalline ferric oxides, and an undefined silicate matrix. The spectral properties of many low albedo regions indicate crystalline basalts containing both low and high calcium pyroxene, a mineralogy consistent with the basaltic SNC meteorites. The Thermal Emission Spectrometer (TES) experiment on the Mars Geochemical Surveyor has acquired critical new data relevant to surface composition and mineralogy, but in a wavelength region that is complementary to reflectance spectroscopy. The essence of the completed research was to analyze TES data in the context of reflectance data obtained by the French ISM imaging spectrometer experiment in 1989. This approach increased our understanding of the complementary nature of these wavelength regions for mineralogic determinations using actual observations of the martian surface. The research effort focused on three regions of scientific importance: Syrtis Major-Isidis Basin, Oxia Palus-Arabia, and Valles Marineris. In each region distinct spatial variations related to reflectance, and in derived mineralogic information and interpreted compositional units were analyzed. In addition, specific science questions related to the composition of volcanics and crustal evolution, soil compositions and pedogenic processes, and the relationship between pristine lithologies and weathering provided an overall science-driven framework for the work. The detailed work plan involved colocation of TES and ISM data, extraction of reflectance and emissivity spectra from areas of known reflectance variability, and quantitative analysis using factor analysis and statistical techniques to determine the degree of correspondence between these different wavelength regions. Identified coherent variations in TES spectroscopy were assessed against known atmospheric effects to validate that the variations are due to surface properties. With this new understanding of reflectance and emission spectroscopy, mineralogic interpretations were derived and applied to the science objectives of the three regions.

Boyce, Joseph↗
NASA NTRS2016

Watershed-Scale Modeling of Land-Use and Altered Environment Impacts on Aquatic Weed Growth in the Delta

The California Sacramento-San Joaquin River Delta is the hub for California's water supply, conveying water from Northern to Southern California agriculture and communities while supporting important ecosystem services, agriculture, and communities in the Delta. Changes in climate, long-term drought, and water quality have all been suspected as playing role in the dramatic expansion of invasive aquatic plants and their impact on ecosystems of the San Francisco Bay / California Delta complex. NASA Ames Research Center, USDA-Agricultural Research Service, the State of California, UC Davis, and local governments have partnered under a USDA sponsored project (DRAAWP) to develop science-based, adaptive-management strategies for invasive aquatic plants in Sacramento-San Joaquin Delta. Critical to developing management strategies is to understand how the Delta is affected by both the magnitude of fluctuations in land-use and climate / drought induced altered environments and how the plants respond to these altered environments. We utilize the Soil Water Assessment Tool (SWAT), a watershed-scale model developed to quantify the impact of land management practices in large and complex watersheds on water quality, as the backbone for a customized Delta model - Delta-SWAT. The model uses land-use, soils, elevation, and hydrologic routing to characterize pesticide and nutrient transport from the Sacramento and San Joaquin rivers watersheds and loading into the Delta. Land-use within the Delta, as well as water extraction to supply those functions, and the resulting return of water to Delta waterways are included in Delta-SWAT. Hydrologic transport within the Delta has required significant attention to address the lack of elevation driven transport processes. Delta-SWAT water quality trend estimates are compared with water quality monitoring conducted throughout the Delta. Aquatic plant response to water quality and other environmental factors is carried out using a customized model component. Plant response to the range of water quality factors, response times, and altered temperature and light regimes of the Delta have required gap-filling studies to provide model parameters. Delta-SWAT provides a tool for evaluating temporal and spatial effects of land-use and altered environments in the Delta and contributing watersheds on aquatic weed growth. Using Delta-SWAT for simulation modeling allows evaluation of historic and current conditions as well as consideration potential climate change and management practice outcomes. Delta-SWAT adds to the scientific understanding of dynamics in the Delta and enhances development of science-informed, management strategies and practices.

Ecosystem↗
DOE OSTI2025

A unified ensemble soil moisture dataset across the continental United States

Abstract A unified ensemble soil moisture (SM) package has been developed over the Continental United States (CONUS). The data package includes 19 products from land surface models, remote sensing, reanalysis, and machine learning models. All datasets are unified to a 0.25-degree and monthly spatiotemporal resolution, providing a comprehensive view of surface SM dynamics. The statistical analysis of the datasets leverages the Koppen-Geiger Climate Classification to explore surface SM’s spatiotemporal variabilities. The extracted SM characteristics highlight distinct patterns, with the western CONUS showing larger coefficient of variation values and the eastern CONUS exhibiting higher SM values. Remote sensing datasets tend to be drier, while reanalysis products present wetter conditions. In-situ SM observations serve as the basis for wavelet power spectrum analyses to explain discrepancies in temporal scales across datasets facilitating daily SM records. This study provides a comprehensive soil moisture data package and an analysis framework that can be used for Earth system model evaluations and uncertainty quantification, quantifying drought impacts and land–atmosphere interactions and making recommendations for drought response planning.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1995

Chelation And Extraction Of Metals For GC-MS Analysis

Chelation followed by supercritical-fluid extraction enables mass-spectrometric analysis. When fully developed, method implemented in field-portable apparatus for detection and quantification of metals in various matrices without need for elaborate preparation of samples. Used to analyze soil samples for toxic metals.

Sinha, Mahadeva P.↗
NASA NTRS2011

RESOLVE: Regolith and Environment Science and Oxygen and Lunar Volatile Extraction

Regolith & Environment Science and Oxygen & Lunar Volatile Extraction (RESOLVE) is an internationally developed payload that is intended to prospect for resources on other planetary bodies. RESOLVE is a miniature drilling and chemistry plant packaged onto a medium-sized rover to collect and analyze soil for volatile components such as water or hydrogen that could be used in human exploration efforts.

Quinn, Jacqueline↗
NASA NTRS1999

Leaf Optical Properties in Higher Plants: Linking Spectral Characteristics with Plant Stress

A number of studies have addressed responses of leaf spectral reflectance, transmittance, or absorptance to physiological stress. Stressors included dehydration, ozone, herbicides, disease, insufficient mycorrhizae and N fertilization, flooding and insects. Species included conifers, grasses, and broadleaved trees. Increased reflectance with maximum responses near 700 nm wavelength occurred in all cases. Varying the chlorophyll content in leaves or pigment extracts can simulate this effect. Thus, common optical responses to stress result from decreases in leaf chlorophyll contents or the capacity of chloroplasts to absorb light. Leaf optic can be quite sensitive to any stressor that alters soil-plant-atmosphere processes.

Carter, Gregory A.↗
NASA NTRS1992

Availability of hydrogen for lunar base activities

Hydrogen will be needed on a lunar base to make water for consumables, to provide fuel, and to serve as a reducing agent in the extraction of oxygen from lunar minerals. This study was undertaken in order to learn more about the abundance and distribution of solar-wind-implanted hydrogen. Hydrogen was found in all samples studied, with concentrations, varying widely depending on soil maturity, grain size, and mineral composition. Seven cores returned from the Moon were studied. Although hydrogen was implanted in the upper surface layer of the regolith, it was found throughout the cores due to micrometeorite reworking of the soil.

Bustin, Roberta↗
NASA NTRS1992

Use of AVIRIS data to the definition of optimised specifications for land applications with future spaceborne imaging spectrometers

Recent experience with airborne imaging spectrometers demonstrated the advantages of narrow band sensors over broad band scanners for characterizing the nature, extent, and physical status of typical land surfaces. Information on key spectral features associated with various land surfaces can be obtained from the data of such instruments, which can be used to simulate spaceborne imaging spectrometer data and to assess their information content if comprehensive underpinning is provided by ground data. The collection of such information was an issue of airborne imaging spectrometer campaigns like the NASA MAC-Europe 1991. Airborne and ground data obtained from different test sites in Europe are utilized for a comparative analysis of the spectral signatures of various land surfaces (vegetation, bare soils and rocks, and mixed soil/rock-vegetation) as seen from different imaging spectrometers like Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), GERIS 63 band scanner, and CASI. The following items are discussed: (1) the significance of different spectral regions within the wavelength interval between 0.4 m and 2.5 m for the differentiation of different land units; (2) recommendations on the optimum band selection and band-widths to be used for the application of future satellite-based imaging spectrometers for land applications; (3) the boundaries for the detection of plant features in mixed-soil plant spectra and the influence of different soil properties on the mixture of the spectra; (4) recommendations on the optimum spatial resolution and recording dates for the discrimination of spectral features of various surface types; and (5) evaluation of different data compressing techniques for the optimum extraction of spectral information from imaging spectrometry data.

Bodechtel, J.↗
NASA NTRS2009

The Evolution and Development of the Lunar Regolith and Implications for Lunar Surface Operations and Construction

The lunar regolith consists of about 90% submillimeter particles traditionally termed lunar soil. The remainder consists of larger particles ranging up to boulder size rocks. At the lower size end, soil particles in the 10s of nanometer sizes are present in all soil samples. Lunar regolith overlies bedrock which consists of either lava flows in mare regions or impact-produced megaregolith in highland regions. Lunar regolith has been produced over billions of years by a combination of breaking and communition of bedrock by meteorite bombardment coupled with a variety of complex space weathering processes including solar wind implantation, solar flare and cosmic ray bombardment with attendant radiation damage, melting, vaporization, and vapor condensation driven by impact, and gardening and turnover of the resultant soil. Lunar regolith is poorly sorted compared to most terrestrial soils, and has interesting engineering properties including strong grain adhesion, over-compacted soil density, an abundance of agglutinates with sharp corners, and a variety of properties related to soil maturity. The NASA program has supported a variety of engineering test research projects, the production of bricks by solar or microwave sintering, the production of concrete, the in situ sintering and glazing of regolith by microwave, and the extraction of useful resources such as oxygen, hydrogen, iron, aluminum, silicon and other products. Future requirements for a lunar surface base or outpost will include construction of protective berms, construction of paved roadways, construction of shelters, movement and emplacement of regolith for radiation shielding and thermal control, and extraction of useful products. One early need is for light weight but powerful digging, trenching, and regolith-moving equipment.

McKay, David↗
NASA NTRS2013

Using Giovanni in Investigating the Links between Environmental Processes and Drought in Northern sub-Saharan Africa

The northern sub-Saharan African (NSSA) region, bounded on the north and south by the Sahara and the Equator, respectively, and stretching East-West across Africa, is very vulnerable because of the highly active environmental and meteorological processes associated with its unique location and human activities that adversely impact the regional water cycle. Over the years, this region has suffered frequent severe droughts that have caused tremendous hardship and loss of life to millions of its inhabitants due to the rapid depletion of the regional water resources, as exemplified by the dramatic drying of Lake Chad. On the other hand, the NSSA region shows one of the highest biomass-burning rates per unit land area among all regions of the world. Because of the high concentration and frequency of fires in this region, with the associated abundance of heat release and gaseous and particulate smoke emissions, biomass-burning activity is believed to be one of the drivers of the regional carbon and energy cycles, with serious implications for the water cycle. An interdisciplinary research effort funded by NASA is presently being focused on the NSSA region, to better understand possible connections between the intense biomass burning observed from satellite year after year across the region and the water cycle, through associated changes in land-cover, surface albedo, emissions, atmospheric processes, precipitation, soil moisture, surface evaporation and runoff, and groundwater recharge. A combination of remote sensing and modeling approaches is being utilized to investigate these multiple processes to clarify possible links between them. However, by using Giovanni, we are able to extract and jointly analyze some of the important relevant parameters to obtain a first insight into their relationships. In this presentation, we will discuss these preliminary results as well as the path toward improved understanding of the interrelationships and feedbacks between the water cycle components and the environmental change dynamics due to biomass burning and related processes in the NSSA region.

water resources↗
NASA NTRS1977

Radioactivities in returned lunar materials

Results from a carbon-14 study in size fractions of lunar soil are reported. The 10 to 30 micrometers and 74 to 124 micrometers size fraction results were supplemented by 30 to 37 micrometers results that are given in this report. The gases from the less than 10 micrometers fraction were extracted and purified and carbon-14 counting is now in progress. Meteorites were also studied using carbon-14, with emphasis directed to those recently discovered in the Antarctic.

Fireman, E. L.↗
NASA NTRS1986

1985 International Geoscience and Remote Sensing Symposium (IGARSS '85), University of Massachusetts, Amherst, October 7-9, 1985, Proceedings

Papers are presented on an EM subsurface radar based on the transient field radiated by a wire antenna; the microwave dielectric, structural, and salinity properties of simulated sea ice; the extraction of sea-ice data from satellite SAR imagery, and the probing of thick vegetation canopies with a field microwave scatterometer. Also discussed are the bidirectional reflectance modeling of a conifer forest canopy, a microwave dielectric model for aggregated soils, and the estimation of soil hydraulic parameters with passive microwave data.

Carver, K. R.↗
NASA NTRS2004

Alternative Approaches to Land Initialization for Seasonal Precipitation and Temperature Forecasts

The seasonal prediction system of the NASA Global Modeling and Assimilation Office is used to generate ensembles of summer forecasts utilizing realistic soil moisture initialization. To derive the realistic land states, we drive offline the system's land model with realistic meteorological forcing over the period 1979-1993 (in cooperation with the Global Land Data Assimilation System project at GSFC) and then extract the state variables' values on the chosen forecast start dates. A parallel series of forecast ensembles is performed with a random (though climatologically consistent) set of land initial conditions; by comparing the two sets of ensembles, we can isolate the impact of land initialization on forecast skill from that of the imposed SSTs. The base initialization experiment is supplemented with several forecast ensembles that use alternative initialization techniques. One ensemble addresses the impact of minimizing climate drift in the system through the scaling of the initial conditions, and another is designed to isolate the importance of the precipitation signal from that of all other signals in the antecedent offline forcing. A third ensemble includes a more realistic initialization of the atmosphere along with the land initialization. The impact of each variation on forecast skill is quantified.

Koster, Randal↗
NASA NTRSDate not supplied

Algorithmic Classification of Raman Spectra Biosignatures: Improving Life Detection Confidence

“Agnostic” biosignatures – indicators of life (or the absence of life), independent of a particular biochemistry – are increasingly considered a high standard for life detection. The Ladder of Life Detection (2018) called for investigating how combinations of independent and different potential biosignatures affect confidence. To address this gap, statistical classification of elemental abundances, isotopic fractionation, and reflectance spectroscopy (VNIR) has been implemented. Raman spectroscopy, highly desirable due to its wide availability, has the potential to improve this predictive power. This work implemented biosignature classification algorithms on Raman data alone, in preparation for combination with the other data types. Raman spectroscopy data was collected from published databases and papers as part of a manually curated dataset of “indicative” and “non-indicative of life” samples. These currently include 61 non-indicative samples (meteorites, magnetite); 3 indicative living samples (bacteria); 20 indicative non-living samples (chalk, bone); and 12 indicative mixed (with non-indicative material) samples (soil, microbial mats). Laboratory work is ongoing to characterize additional samples, particularly a greater breadth of mixed systems. Spectra were interpolated, filtered with the Savitzsky-Golay filter, and de-noised. For a preliminary examination, agnostic features were manually extracted including mean intensity, number of peaks, and mean peak width. Different peak prominences and filtering polynomials were used to refine features. Classification algorithms were implemented: k-nearest neighbors (KNN), logistic regression (LR), linear support vector machines (SVM), random forest (RF), Gaussian naïve bayes (GNB). Lastly, Monte Carlo simulations on 1,000 50%-train-test-splits were used to validate classification performance and feature significance. The preliminary feature set achieved its highest AUC of 0.52 with LR, with no strongly discriminatory features. Work to improve feature extraction, such as through deep learning with back propagation, is planned. In future work, the Raman data will be combined with the other data types, and potentially new data types such as enantiomeric excess. This project was partially supported through the NASA Ames Project EXcellence (APEX) incubator program.

Astrobiology↗