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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Granitic terrains viewed remotely by Shuttle infrared radiometry - Some compositional predictions

Ratios of intensities of near-infrared spectral bands, measured in reflectance, quantitatively predict the iron content of granitic rocks. Such data from the 1.60- and 1.05-micron bands of the Shuttle multispectral infrared radiometer have been used to study granitic rocks along orbits crossing Baja California, Mexico, and the Eastern Desert of Egypt. Both regions are arid and relatively to essentially free of vegetation, and there is no indication in the spectra that surface chemical alteration masks the true composition of the unweathered rock. Predicted values of iron are consistent with known compositional types of most of the rocks along the orbital paths. Results demonstrate that the near-infrared method used is a powerful technique to average the variability of these rocks on the scales of meters to kilometers.

Baird, A. K.↗
NASA NTRS1979

Detection and mapping of hydrothermally altered rocks in the vicinity of the comstock lode, Virginia Range, Nevada, using enhanced LANDSAT images

The author has identified the following significant results. LANDSAT images enhanced by the band-ratioing method can be used for reconnaissance alteration mapping in moderately heavily vegetated semiarid terrain as well as in sparsely vegetated to semiarid terrain where the technique was originally developed. Significant vegetation cover in a scene, however, requires the use of MSS ratios 4/5, 4/6, and 6/7 rather than 4/5, 5/6, and 6/7, and requires careful interpretation of the results. Supplemental information suitable to vegetation identification and cover estimates, such as standard LANDSAT false-color composites and low altitude aerial photographs of selected areas is desirable.

Ashley, R. P.↗
NASA NTRS2005

Isolation and Identification of Microorganisms in JSC Mars-1 Simulant Soil

Microorganisms were isolated and identified in samples of JSC Mars-1, a Mars simulant soil. JSC Mars-1 is an altered volcanic ash from a cinder cone south of Mauna Kea, Hawaii. This material was chosen because of its similarity to the Martian soil in physical and chemical composition. The soil was obtained by excavating 40 cm deep in a vegetated area to prevent contamination. In previous studies, bacteria from this soil has been isolated by culturing on different types of media, including minimal media, and using biochemical techniques for identification. Isolation by culturing is successful only for a small percentage of the population. As a result, molecular techniques are being employed to identify microorganisms directly from the soil without culturing. In this study, bacteria were identified by purifying and sequencing the DNA encoding the 16s ribosomal RNA (16s rDNA). This gene is well conserved in species and demonstrates species specificity. In addition, biofilm formation, an indicator of microbial life, was studied with this soil. Biofilms are microbial communities consisting of microbes and exopolysaccharides secreted by them. This is a protective way of life for the microbes as they are more resistant to environmental pressures.

Mendez, Claudia↗
NASA NTRS2014

Detecting Change in Urban Areas at Continental Scales with MODIS Data

Urbanization is one of the most important components of global environmental change, yet most of what we know about urban areas is at the local scale. Remote sensing of urban expansion across large areas provides information on the spatial and temporal patterns of growth that are essential for understanding differences in socioeconomic and political factors that spur different forms of development, as well the social, environmental, and climatic impacts that result. However, mapping urban expansion globally is challenging: urban areas have a small footprint compared to other land cover types, their features are small, they are heterogeneous in both material composition and configuration, and the form and rates of new development are often highly variable across locations. Here we demonstrate a methodology for monitoring urban land expansion at continental to global scales using Moderate Resolution Imaging Spectroradiometer (MODIS) data. The new method focuses on resolving the spectral and temporal ambiguities between urban/non-urban land and stable/changed areas by: (1) spatially constraining the study extent to known locations of urban land; (2) integrating multitemporal data from multiple satellite data sources to classify c. 2010 urban extent; and (3) mapping newly built areas (2000-2010) within the 2010 urban land extent using a multi-temporal composite change detection approach based on MODIS 250 m annual maximum enhanced vegetation index (EVI). We test the method in 15 countries in East-Southeast Asia experiencing different rates and manifestations of urban expansion. A two-tiered accuracy assessment shows that the approach characterizes urban change across a variety of socioeconomic/political and ecological/climatic conditions with good accuracy (70-91% overall accuracy by country, 69-89% by biome). The 250 m EVI data not only improve the classification results, but are capable of distinguishing between change and no-change areas in urban areas. Over 80% of the error in the change detection can be related to definitional issues or error propagation, rather than algorithm error. As such, these methods hold great potential for routine monitoring of urban change, as well as for providing a consistent and up-to-date dataset on urban extent and expansion for a rapidly evolving region.

Urban areas↗
DOE OSTI2024

Sustainable co-production of plant lipids and cellulosic sugars from transgenic energycane at an industrially relevant scale: A proof of concept for alternative feedstocks

Development of sustainable and scalable technologies to convert lignocellulosic biomass to biofuels is critical to achieving carbon neutrality. The potential of transgenic bioenergy crops as a renewable source of sugars and lipids has been demonstrated at bench-scale. However, scaling up these processes is important for holistic analysis. Here proof-of-concept for chemical-free hydrothermal pretreatment of transgenic energycane-oilcane line L13 at an industrially relevant scale to recover vegetative lipids along with cellulosic sugars is presented. Here, pilot-scale processing of 97 kg of transgenic energycane-oilcane L13 stems and high solids pretreatment of bagasse enhanced the recovery of cellulosic glucose and xylose by 5-fold as compared to untreated bagasse and helped in the enrichment of vegetative lipids in the biomass residues which allowed its recovery at the end of the bioprocess. Palmitic and oleic acids were the predominant fatty acids (FAs) extracted from stems and leaves. The processing did not affect lipid composition. The efficiency of lipid recovery from untreated biomass was 75.9% which improved to 88.7% upon pretreatment. The vegetative tissues of transgenic energycane-oilcane L13 contained 0.42 metric tons/hectare of lipids. Processing vegetative tissues yielded 0.38 metric tons/hectare of lipids. This approaches an oil yield similar to soybean (global average 0.44 metric tons/hectare) and is almost twice as high as the oil yield from sugarcane engineered to hyperaccumulate lipids (0.20 metric tons/hectare). The study suggests that further optimization by state-of-the-art metabolic engineering and biomass processing can establish transgenic bioenergy crops for commercial drop-in fuel production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Data for Sustainable Co-Production of Plant Lipids and Cellulosic Sugars from Transgenic Energycane at an Industrially Relevant Scale: A Proof of Concept for Alternative Feedstocks

Development of sustainable and scalable technologies to convert lignocellulosic biomass to biofuels is critical to achieving carbon neutrality. The potential of transgenic bioenergy crops as a renewable source of sugars and lipids has been demonstrated at bench-scale. However, scaling up these processes is important for holistic analysis. Here proof-of-concept for chemical-free hydrothermal pretreatment of transgenic energycane-oilcane line L13 at an industrially relevant scale to recover vegetative lipids along with cellulosic sugars is presented. Pilot-scale processing of 97 kg of transgenic energycane-oilcane L13 stems and high solids pretreatment of bagasse enhanced the recovery of cellulosic glucose and xylose by 5-fold as compared to untreated bagasse and helped in the enrichment of vegetative lipids in the biomass residues which allowed its recovery at the end of the bioprocess. Palmitic and oleic acids were the predominant fatty acids (FAs) extracted from stems and leaves. The processing did not affect lipid composition. The efficiency of lipid recovery from untreated biomass was 75.9% which improved to 88.7% upon pretreatment. The vegetative tissues of transgenic energycane-oilcane L13 contained 0.42 metric tons/hectare of lipids. Processing vegetative tissues yielded 0.38 metric tons/hectare of lipids. This approaches an oil yield similar to soybean (global average 0.44 metric tons/hectare) and is almost twice as high as the oil yield from sugarcane engineered to hyperaccumulate lipids (0.20 metric tons/hectare). The study suggests that further optimization by state-of-the-art metabolic engineering and biomass processing can establish transgenic bioenergy crops for commercial drop-in fuel production.

Biomass Analytics↗
DOE OSTI2023

Forest reorganisation effects on fuel moisture content can exceed changes due to climate warming in wet temperate forests

Abstract The distributions of vegetation and fire activity are changing rapidly in response to climate warming. In many regions, climate effects on dead fuel moisture content (FMC) are expected to increase future wildfire activity. However, forest FMC is largely driven by microclimate conditions, which are moderated from open weather by vegetation canopies. As shifts in vegetation increase under climate warming, the extent to which future fire activity will be driven by climate directly or associated vegetation shifts remains unresolved. Here, we present a study aimed at quantifying the relative magnitudes of (i) direct climate warming, and (ii) vegetation change, on FMC. Field sites to evaluate these effects were established in a natural laboratory of altered forest states to mature wet temperate forest in south‐eastern Australia. FMC was estimated using a process‐based model and 48 years of reconstructed climate data. Canopy effects on microclimate were captured by transferring inputs from climate to microclimate using models parameterised with field observations. To evaluate the relative magnitude of climate and vegetation effects, we calculated the maximum difference in mean annual FMC across annual climate replicates and compared this to FMC differences across reorganising forest sites. Our results show vegetation effects on FMC can exceed those related to expected climate change. Changes to forest structure and composition increased (+15.7%) and decreased (−12.3%) mean annual FMC, with a larger negative effect when forest cover was completely removed (−18.5%). In contrast, the largest climate effect on FMC was −6.6% across 48‐years of data. Our study demonstrates that the magnitude of vegetation effects on FMC can exceed expected climate change effects. Models of future fire activity that do not account for changing vegetation effects on microclimate are omitting a key biophysical control on FMC and therefore may not be accurately predicting future fire activity.

Brown, Tegan P.↗
DOE OSTI2024

Long-term drought promotes invasive species by reducing wildfire severity

Anthropogenic climate change has increased the frequency of drought, wildfire, and invasions of non-native species. Although high-severity fires linked to drought can inhibit recovery of native vegetation in forested ecosystems, it remains unclear how drought impacts the recovery of other plant communities following wildfire. We leveraged an existing rainfall manipulation experiment to test the hypothesis that reduced precipitation, fuel load, and fire severity convert plant community composition from native shrubs to invasive grasses in a Southern California coastal sage scrub system. We measured community composition before and after the 2020 Silverado wildfire in plots with three rainfall treatments. Drought reduced fuel load and vegetation cover, which reduced fire severity. Native shrubs had greater prefire cover in added water plots compared to reduced water plots. Native cover was lower and invasive cover was higher in postfire reduced water plots compared to postfire added and ambient water plots. Our results demonstrate the importance of fuel load on fire severity and plant community composition on an ecosystem scale. Management should focus on reducing fire frequency and removing invasive species to maintain the resilience of coastal sage scrub communities facing drought. In these communities, controlled burns are not recommended as they promote invasive plants.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2008

A VARI-Based Relative Greenness from MODIS Data for Computing the Fire Potential Index

The Fire Potential Index (FPI) relies on relative greenness (RG) estimates from remote sensing data. The Normalized Difference Vegetation index (NDVI), derived from NOAA Advanced Very High Resolution Radiometer (AVHRR) imagery is currently used to calculate RG operationally. Here we evaluated an alternate measure of RG using the Visible Atmospheric Resistant Index (VARI) derived from Moderate Resolution Imaging Spectrometer (MODIS) data. VARI was chosen because it has previously been shown to have the strongest relationship with Live Fuel Moisture (LFM) out of a wide selection of MODIS-derived indices in southern California shrublands. To compare MODIS-based NDVI-FPI and VARI-FPI, RG was calculated from a 6-year time series of MODIS composites and validated against in-situ observations of LFM as a surrogate for vegetation greenness. RG from both indices was then compared in terms of its performance for computing the FPI using historical wildfire data. Computed RG values were regressed against ground-sampled LFM at 14 sites within Los Angeles County. The results indicate the VARI-based RG consistently shows a stronger relationship with observed LFM than NDVI-based RG. With an average R2 of 0.727 compared to a value of only 0.622 for NDVI-RG, VARI-RG showed stronger relationships at 13 out of 14 sites. Based on these results, daily FPI maps were computed for the years 2001 through 2005 using both NDVI-RG and VARI-RG. These were then validated against 12,490 fire detections from the MODIS active fire product using logistic regression. Deviance of the logistic regression model was 408.8 for NDVI-FPI and 176.2 for VARI-FPI. The c-index was found to be 0.69 and 0.78, respectively. The results show that VARI-FP outperforms NDVI-FPI in distinguishing between fire and no-fire events for historical wildfire data in southern California for the given time period.

Schneider, P.↗
NASA NTRS1984

Thematic Mapper simulator research for forest resource mapping in the Clearwater National Forest, Idaho

Per-pixel maximum likelihood digital classification and photo interpretation of Thematic Mapper Simulator (TMS) composited images for a managed conifer forest were used to evaluate both land cover and forest structure characteristics. TMS channels 4, 7, 5 and 3, which were found to be optimal for forest vegetation analysis, used the full range of the Thematic Mapper's spectral capability. Photo interpretation results indicate that a false color composite from TMS channels 4, 7, and 2 provided the highest accuracies; the combination of improved spatial, spectral and radiometric resolution of the Thematic Mapper yielded greater sensitivity to forest structural characteristics.

Brass, J. A.↗
NASA NTRS1974

Environmental studies of Iceland with ERTS-1 imagery

Imagery from the ERTS-1 satellite can be used to study geological and geophysical phenomena which are important in relation to Iceland's natural resources. Multispectral scanner (MSS) imagery can be used to map areas of altered ground, intense thermal emission, fallout from volcanic eruptions, lava flows, volcanic geomorphology, erosion or build-up of land, snow cover, the areal extent of glaciers and ice caps, etc. At least five distinct vegetation types and barren areas can be mapped using MSS false-color composites. Stereoscopic coverage of iceland by side-lapping ERTS imagery permits precise analysis of various natural phenomena.

Williams, R. S., Jr.↗
NASA NTRS1990

Imaging spectroscopy of the terrestrial environment; Proceedings of the Meeting, Orlando, FL, Apr. 16, 17, 1990

Topics presented include the evolution of the Airborne Visible/Infrared Imaging Spectrometer flight and ground data processing system, direct mineral identification with Geoscan Mk II Advanced Multispectral Scanner, a new approach to imaging spectroscopy, and a linear-wedge spectrometer. Also presented are the effects of moisture content and chemical composition on the near-infrared spectra of forest foliage, change detection in vegetation using 1989 AVIRIS data, and the inversion of high-spectral-resolution data.

Vane, Gregg↗
NASA NTRS1993

Analysis of hyper-spectral AVIRIS image data over a mixed-conifer forest in Maine

An introduction to some of the potential uses of hyperspectral data for ecosystem analysis is presented. The examples given are derived from a digital dataset acquired over a sub-boreal forest in central Maine in 1990 by the NASA-JPL Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) instrument gathers data from 400 to 2500 nm in 224 channels at bandwidths of approximately 10 nm. As a preview to the uses of the hyperspectral data, several products from this dataset were extracted. They range from the traditional false color composite made from simulated Thematic Mapper bands and the well known normalized difference vegetation index to much more exotic products such as fractions of vegetation, soil and shade based on linear spectral mixing models and estimates of the leaf water content at the landscape level derived using spectrum-matching techniques. Our research and that of many others indicates that the hyperspectral datasets carry much important information which is only beginning to be understood. This analysis gives an initial indication of the utility of hyperspectral data. Much work still remains to be done in algorithm development and in understanding the physics behind the complex information signal carried in the hyperspectral datasets. This work must be carried out to provide the fullest science support for high spectral resolution data to be acquired by many of the instruments to be launched as part of the Earth Observing System program in the mid-1990's.

Lawrence, William T.↗
NASA NTRS1991

Representation of vegetation by continental data sets derived from NOAA-AVHRR data

Images of the normalized difference vegetation index (NDVI) are examined with specific attention given to the effect of spatial scales on the understanding of surface phenomena. A scale variance analysis is conducted on NDVI annual and seasonal images of Africa taken from 1987 NOAA-AVHRR data at spatial scales ranging from 8-512 km. The scales at which spatial variation takes place are determined and the relative magnitude of the variations are considered. Substantial differences are demonstrated, notably an increase in spatial variation with coarsening spatial resolution. Different responses in scale variance as a function of spatial resolution are noted in an analysis of maximum value composites for February and September; the difference is most marked in areas with very seasonal vegetation. The spatial variation at different scales is attributed to different factors, and methods involving the averaging of areas of transition and surface heterogeneity can oversimplify surface conditions. The spatial characteristics and the temporal variability of areas should be considered to accurately apply satellite data to global models.

Justice, C. O.↗
DOE OSTI2024

NEON AOP Survey of Upper East River CO Watersheds: Waveform LiDAR Binary Data

The waveform Light Detection and Ranging (LiDAR) data in this package were generated through a National Ecological Observatory Network Airborne Observation Platform (NEON AOP) acquisition over watersheds of interest surrounding Crested Butte, Colorado. The remote sensing imagery acquired by the NEON AOP supports an interdisciplinary project on hydrology, biogeochemistry, and ecosystem functioning in a snow-dominated headwater environment. These waveform LiDAR data enable spatially continuous estimation of vegetation structure parameters to facilitate analyses of the major environmental drivers of structural and compositional variability. The package contains 97 compressed file archives in 7-zip (.7z) format, each corresponding to one acquisition flightpath. Within each .7z archive is a set of constituent files describing properties of the LiDAR waveforms, such as return intensity, geolocation, outgoing pulse and other behavior of the sensor and signals. Once downloaded, the files must first be unzipped using the widely distributed command-line software utility 7z, using the command '7z x \[filename\].7z \[target_directory\]'. All files within the .7z archives can be opened in IDL, MatLab, or the open-source R statistical computing environment. Further details about the data package are in the attached user guide (neon_aop_crbu_waveformlidar_userguide.pdf). This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2026

Microbial community data from throughfall exclusion experiment: Metadata, SI, community composition, LefSe, and FunGuilR data tables from PARCHED Panama tropical forest soils, 2024-2025

Soil contains more carbon (C) than terrestrial vegetation and the atmosphere combined, with some of the largest terrestrial C stocks in tropical rainforests. Soil microbes decompose organic matter, playing a vital role in the storage or loss of soil C. With climate change, drought conditions are predicted to increase in many tropical regions, including both chronic drying and extended drought, potentially influencing these processes. This project explored the effects of chronic and seasonal drying on soil microbial communities across four distinct tropical forests in a long-term drying experiment. We investigated the effects of a chronic drying manipulation on soil microbial community abundance and variation across different forests and seasons. We also compared findings with previously published data from these forests after short-term drying. This project used soils from a long-term drying experiment established in 2018 across four seasonal lowland forests in Panama. Soils were collected from 0 – 10 cm depths during three seasonal periods in control and drying plots in 2024 and 2025 from a total of 32 plots (n = 4 per forest per treatment). The forests varied in baseline rainfall and soil fertility. We calculated alpha and beta diversity indices and compared taxonomic community composition. We found significant biogeographic variation in microbial diversity and taxonomy, with significant differences across the forests and significant effects of the drying treatment. Metadata and sample IDs are within Metadata_16S.csv and Metadata_ITS.csv. Relative abundance tables of every sample at every season are shown in the Excel workbooks 16S Relative Abundance.xlsx and ITS Relative Abundance.xlsx. They are then also shown in CSV files by each taxonomic level. Linear discriminant analysis effect size (LefSe) tables are shown for the full 16S and ITS datasets (n = 96), subsets for every site at every season (n = 8), and then for the forests with each plot merged by season (n = 8). FunGuildR data table of ITS data is uploaded.

Bacteria↗
DOE OSTI2025

Evaluating sulfurization as a blue carbon sink in a southern California salt marsh

Blue carbon ecosystems such as seagrass meadows, mangrove forests, and salt marshes are important carbon sinks that can store carbon for millennia. Recently, organic matter sulfurization and pyritization have been proposed as mechanisms of net carbon storage in blue carbon ecosystems. At our study site, organic sulfur that is resistant to acid hydrolysis (protokerogen) is an order of magnitude less abundant than pyrite sulfur, suggesting a dominance of pyritization over sulfurization. The C/N ratios and carbon isotope compositions suggest that nearly half of total organic carbon and ≥ 80% of protokerogen is composed of marsh plant material. Sediment protokerogen appears to be sulfurized based on its low δ 34 S values (− 10‰), abundance of disulfides, and higher S/C ratio (~ 1.0%) relative to potential biogenic sulfur sources. However, the interpretation of protokerogen δ 34 S values is complicated by the wide range in sulfur isotope compositions of marsh plants. Evidence for sulfurization occurs within the shallowest sediments across different vegetation zones, yielding consistent products, while pyritization appears to be more sensitive to alterations in sediment redox conditions. Based on organic sulfur and pyrite content, sulfurization may be a more spatially consistent process than pyritization, with implications for carbon storage. The relative abundance of pyrite and protokerogen organic sulfur indicates that pyritization is favored at our study site, but this is likely to vary across the spectrum of blue carbon ecosystems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1974

Management of natural resources through automatic cartographic inventory

The author has identified the following significant results. Significant correspondence codes relating ERTS imagery to ground truth from vegetation and geology maps have been established. The use of color equidensity and color composite methods for selecting zones of equal densitometric value on ERTS imagery was perfected. Primary interest of temporal color composite is stressed. A chain of transfer operations from ERTS imagery to the automatic mapping of natural resources was developed.

Rey, P. A.↗