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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Trees Outside Forests are an Underestimated Resource in a Country with Low Forest Cover

Trees outside forests (TOF) are an underrepresented resource in forest poor nations. As a result of their frequent omission from national forest resource assessments and a lack of readily available very-high-resolution remotely sensed imagery, TOF status and characterization has until now, been unknown. Here, we assess the capacity of openly available 10 m ESA Sentinel constellation satellite imagery for mapping TOF extent at the national level in Bangladesh. In addition, we estimate canopy height for TOF using a TanDEM-X DEM. We map 2,233,578 ha of TOF in Bangladesh with a mean canopy height of 7.3 m. We map 31 and 53% more TOF than existing estimates of TOF and forest, respectively. We find TOF in Bangladesh is nationally fragmented as a consequence of agricultural activity, yet is capable of maintaining connectedness between remaining stands. Now, TOF accounting is feasible at the national scale using readily available datasets, enabling the mainstream inclusion of TOF in national forest resource assessments for other countries.

Nathan Thomas↗
DOE OSTI2026

SPRUCE Soil Volumetric Water Content in Experimental Plots, Marcell Experimental Forest, Minnesota, 2017-2025

This dataset contains soil volumetric water content (VWC) measurements from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) Experiment. Measurements were made inside SPRUCE experimental plots in the S1 Bog at the US Forest Service Marcell Experimental Forest in northern Minnesota, USA from 2018-2025 (2018-06-14 to 2025-12-31). Observations were made with METER 10HS soil moisture sensors. To reduce bulk density related variability, 10HS sensors were placed inside mesh tubes filled with peat at a standard bulk density. The observations under standard bulk density represent relative differences in water content between hummock and hollow positions, and in response to experimental treatments. Productivity of peatlands, and their keystone species sphagnum, are highly dependent on water availability, which is affected by lateral inputs, precipitation, ground water depth and evapotranspiration. Knowledge of near surface and sphagnum water content is useful to understand peatland function. This dataset contains 8 data files in comma-separate values (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma-separate values (*.csv) format and a user guide in PDF (*.pdf) format.

Warren, Jeffrey [ORNL] (ORCID:0000000206804697)↗
NASA NTRS2010

Mapping Successional Stages in a Wet Tropical Forest Using Landsat ETM+ and Forest Inventory Data

In this study, we test whether an existing classification technique based on the integration of Landsat ETM+ and forest inventory data enables detailed characterization of successional stages in a wet tropical forest site. The specific objectives were: (1) to map forest age classes across the La Selva Biological Station in Costa Rica; and (2) to quantify uncertainties in the proposed approach in relation to field data and existing vegetation maps. Although significant relationships between vegetation height entropy (a surrogate for forest age) and ETM+ data were detected, the classification scheme tested in this study was not suitable for characterizing spatial variation in age at La Selva, as evidenced by the error matrix and the low Kappa coefficient (12.9%). Factors affecting the performance of the classification at this particular study site include the smooth transition in vegetation structure between intermediate and advanced successional stages, and the low sensitivity of NDVI to variations in vertical structure at high biomass levels.

forest structure↗
DOE OSTI2024

Mycorrhizal associations of temperate forest seedlings mediate rhizodeposition, but not soil carbon storage, under elevated nitrogen availability

Abstract Tree‐mycorrhizal associations are associated with patterns in nitrogen (N) availability and soil organic matter storage; however, we still lack a mechanistic understanding of what tree and fungal traits drive these patterns and how they will respond to global changes in soil N availability. To address this knowledge gap, we investigated how arbuscular mycorrhizal (AM)‐ and ectomycorrhizal (EcM)‐associated seedlings alter rhizodeposition in response to increased seedling inorganic N acquisition. We grew four species each of EcM and AM seedlings from forests of the eastern United States in a continuously 13 C‐labeled atmosphere within an environmentally controlled chamber and subjected to three levels of 15 N‐labeled fertilizer. We traced seedling 15 N uptake from, and 13 C‐labeled inputs (net rhizodeposition) into, root‐excluded or ‐included soil over a 5‐month growing season. N uptake by seedlings was positively related to rhizodeposition for EcM‐ but not AM‐associated seedlings in root‐included soils. Despite this contrast in rhizodeposition, there was no difference in soil C storage between mycorrhizal types over the course of the experiment. Instead root‐inclusive soils lost C, while root‐exclusive soils gained C. Our findings suggest that mycorrhizal associations mediate tree belowground C investment in response to inorganic N availability, but these differences do not affect C storage. Continued soil warming and N deposition under global change will increase soil inorganic N availability and our seedling results indicate this could lead to greater belowground C investment by EcM‐associated trees. This potential for less efficient N uptake by EcM‐trees could contribute to AM‐tree success and a shift toward more AM‐dominated temperate forests.

Fitch, Amelia A.↗
NASA NTRS1984

Relationship between forest clearing and biophysical factors in tropical environments: Implications for the design of a forest change monitoring approach

The relationship between forest clearing, biophysical factors (e.g, ecological zones, slope gradient, soils), and transportation network in Costa Rica was analyzed. The location of forested areas at four reference datas (1940, 1950, 1961, and 1977) as derived from aerial photography and LANDSAT MSS data was digitilized and entered into a geographically-referenced data base. Ecological zones as protrayed by the Holdridge Life Zone Ecology System, and the location of roads and railways were also digitized from maps of the entire country as input to the data base. Information on slope gradient and soils was digitized from maps of a 21,000 square kilometer area. The total area of forest cleared over four decades are related to biophysical factors was analyzed within the data base and deforestation rates and trends were tabulated. The relatiohship between forest clearing and ecological zone and the influence of topography, sils, and transportation network are presented and discussed.

Sader, S. A.↗
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 NTRS1986

Assessing forest decline in coniferous forests of Vermont using NS-001 Thematic Mapper Simulator data

This study evaluates the potential of measuring/mapping forest decline in spruce-fir forests using airborne NS-001 TMS data. Using field instruments, it was found that ratios of 1.65/1.23 and 1.65/0.83-micron reflectance discriminated between spruce samples of low and high-damage sites. Using TMS data, band ratios were found to be strongly correlated with ground-based measurements of forest damage. Ratio colo-density slice images using these band ratios, and images using 0.56 and 1.65-micron bands with either of these band ratios in a false-color composite, provide accurate means of detecting, quantifying and mapping levels of forest decline.

Vogelmann, J. E.↗
DOE OSTI2025

Light in the dark forest. Part I. An efficient optimal estimator for 3D Lyman-alpha forest power spectrum

The highly anisotropic nature of the Lyman-alpha (Lyα) forest data introduces a complex survey window function that complicates the measurement of the three-dimensional power spectrum ( P 3D ). In this paper, we present the first fully optimal estimator for P 3D , which exactly deconvolves the survey window function and marginalizes contaminated modes that distort the power spectrum. Our approach adapts optimal estimator techniques developed for the 2D cosmic microwave background data to the 3D case. To achieve computational feasibility, we employ the conjugate gradient method and implement the P 3 M formalism to handle large-scale and small-scale operations separately and efficiently. We validate our estimator using Monte Carlo mocks and Gaussian simulations, demonstrating its accuracy and computational efficiency. We confirm that mode marginalization eliminates distortions arising from quasar continuum errors and delivers robust power spectrum estimation, though it also inflates errors at large scales. This first implementation works in the flat-sky case; we discuss the remaining steps needed to generalize it to the curved-sky case. This formalism offers a foundation for the Lyα forest P 3D measurements and a new path toward cosmological constraints from the Lyα forest data.

Lyman alpha forest↗
NASA NTRS1974

Inventory of forest and rangeland and detection of forest stress

The author has identified the following significant results. Disturbances in a forest environment that cause reductions in forest area, timber volume, and timber growth can be detected on ERTS-1 combined color composites. However, detection depends on comparing a conventional aerial photograph taken at some base year with an ERTS-1 image taken in some subsequent year. In a test made on the Atlanta site, 1:63,360 scale aerial photo index sheets made in 1966 were compared with ERTS-1 image 1264-15445 (April 1973). Five factors were found important to detection reliability: (1) the quality of the imagery; (2) the season of the imagery; (3) the size of the disturbed area; (4) the number of years since the disturbances; and (5) the type of cutting treatment. Of 209 disturbances verified on aerial photography, 165 (or approximately 80%) were detected on the ERTS-1 image by one independent interpreter. Improved training and additional experience in using this low resolution imagery should improve detection. Of the two seasons of data studies (fall and early spring), early spring is the best for detecting land use changes. Generally speaking, winter, early spring, and early summer are the best times of year for detecting forest disturbances.

Heller, R. C.↗
NASA NTRS1974

Forest and land inventory using ERTS imagery and aerial photography in the boreal forest region of Alberta, Canada

Satellite imagery and small-scale (1:120,000) infrared ektachrome aerial photography for the development of improved forest and land inventory techniques in the boreal forest region are presented to demonstrate spectral signatures and their application. The forest is predominately mixed, stands of white spruce and poplar, with some pure stands of black spruce, pine and large areas of poorly drained land with peat and sedge type muskegs. This work is part of coordinated program to evaluate ERTS imagery by the Canadian Forestry Service.

Kirby, C. L.↗
NASA NTRS1974

Evaluation of ERTS-1 data for inventory of forest and rangeland and detection of forest stress

The author has identified the following significant results. Results of photointerpretation indicated that ERTS is a good classifier of forest and nonforest lands (90 to 95 percent accurate). Photointerpreters could make this separation as accurately as signature analysis of the computer compatible tapes. Further breakdowns of cover types at each site could not be accurately classified by interpreters (60 percent) or computer analysts (74 percent). Exceptions were water, wet meadow, and coniferous stands. At no time could the large bark beetle infestations (many over 300 meters in size) be detected on ERTS images. The ERTS wavebands are too broad to distinguish the yellow, yellow-red, and red colors of the dying pine foliage from healthy green-yellow foliage. Forest disturbances could be detected on ERTS color composites about 90 percent of the time when compared with six-year-old photo index mosaics. ERTS enlargements (1:125,000 scale, preferably color prints) would be useful to forest managers of large ownerships over 5,000 hectares (12,500 acres) for broad area planning. Black-and-white enlargements can be used effectively as aerial navigation aids for precision aerial photography where maps are old or not available.

Heller, R. C.↗
NASA NTRS1983

A correlation analysis of percent canopy closure versus TMS spectral response for selected forest sites in the San Juan National Forest, Colorado

The correlation of canopy closure with the signal response of individual thematic mapper simulator (TMS) bands for selected forest sites in the San Juan National Forest, Colorado was investigated. Ground truth consisted of a photointerpreted determination of percent canopy closure of 0 to 100 percent for 32 sites. The sites selected were situated on plateaus at an elevation of approximately 3 km with slope or = 10 percent. The predominant tree species were ponderosa pine and aspen. The mean TMS response per band per site was calculated from data acquired by aircraft during mid-September, 1981. A correlation analysis of TMS response vs. canopy closure resulted in the following correlation coefficients for bands 1 through 7, respectively: -0.757, -0.663, -0.666, -0.088, -0.797, -0.763. Two model regressions were applied to the TMS data set to create a map of predicted percent forest canopy closure for the study area. Results indicated percent predictive accuracies of 71, 74, and 57 for percent canopy closure classes of 0-25, 25-75, and 75-100, respectively.

Butera, M. K.↗
NASA NTRS1990

Emission of nitric oxide (NO) from tropical forest soils and exchange of NO between the forest canopy and atmospheric boundary layers

Emissions of NO from soils in the Amazon rain forest were measured at 66 locations using an enclosure technique, and continuous vertical profiles of NO and O3 were measured between the ground and 41-m altitude. Fluxes of NO averaged 8.9 (+ or - 1.5) x 10 to the 9th molecules/sq cm per sec from the dominant (yellow clay) soils of the region, with larger fluxes observed from adjacent white sand soils. Fluxes from clay soils were lower by more than a factor of 5 than fluxes observed during the dry season at a nearby site. Low soil emission rates were reflected in lower concentrations of NO at the top of the forest canopy in the wet season, only 30-50 parts per trillion by volume during the daytime. The measured fluxes are consistent with chemical mass balances for NO within the forest canopy, calculated from the NO and O3 profiles taken at night, and with observations of NO between 150 and 5000 m altitude. Measurements of NO emission rates from soil plots fertilized using NaNO3, NH4Cl, or sucrose indicated that a reductive pathway (denitrification) may have been primarily responsible for production of the NO released by both clay and sand soils.

Bakwin, Peter S.↗
NASA NTRS1995

Determining coniferous forest cover and forest fragmentation with NOAA-9 advanced very high resolution radiometer data

NOAA-9 satellite data from the Advanced Very High Resolution Radiometer (AVHRR) were used in conjunction with Landsat Multispectral Scanner (MSS) data to determine the proportion of closed canopy conifer forest cover in the Cascade Range of Oregon. A closed canopy conifer map, as determined from the MSS, was registered with AVHRR pixels. Regression was used to relate closed canopy conifer forest cover to AVHRR spectral data. A two-variable (band) regression model accounted for more variance in conifer cover than the Normalized Difference Vegetation Index (NDVI). The spectral signatures of various conifer successional stages were also examined. A map of Oregon was produced showing the proportion of closed canopy conifer cover for each AVHRR pixel. The AVHRR was responsive to both the percentage of closed canopy conifer cover and the successional stage in these temperate coniferous forests in this experiment.

Ripple, William J.↗
NASA NTRS1994

Radon 222 tracing of soil and forest canopy trace gas exchange in an open canopy boreal forest

A set of continuous, high-resolution atmospheric radon (Rn-222) concentration time series and radon soil flux measurements were acquired during the summer of 1990 at a micrometeorological tower site 13 km northwest of Schefferville, Quebec, Canada. The tower was located in a dry upland, open-canopy lichen-spruce woodland. For the period July 23 to August 1, 1990, the mean radon soil flux was 41.1 +/- 4.8 Bq m(exp -2)/h. Radon surface flux from the two end-member forest floor cover types (lichen mat and bare soil) were 38.8 +/- 5.1 and 61.8 +/- 15.6 Bq m(exp -2)/h, respectively. Average total forest canopy resistances computed using a simple 'flux box' model for radon exchange between the forest canopy and the overlying atmosphere range from 0.47 +/- 0.24 s cm(exp -1) to 2.65 +/- 1.61 cm(exp -1) for daytime hours (0900-1700 LT) and from 3.44 +/- 0.91 s cm(exp -1) to 10.55 +/- 7.16 s cm(exp -1) for nighttime hours (2000-0600) for the period July 23 to August 6, 1990. Continuous radon profiling of canopy atmospheres is a suitable approach for determining rates of biosphere/atmosphere trace gas exchange for remote field sites where daily equipment maintenance is not possible. where daily equipment maintenance is not possible.

Ussler, William, III↗
DOE OSTI2026

Quantifying mean, variability, and uncertainty in indoor radon exposure in Pennsylvania using random forest and quantile regression forest models

Radon is a naturally occurring radioactive gas that poses a serious health risk as the primary cause of lung cancer in non-smokers. Despite the well-known adverse association with health outcomes, current radon exposure assessments are limited to county-level or average-level estimates, which fail to capture regional variability. This study uses Machine Learning models, including Random Forest (RF) and Quantile Regression Forest (QRF), to estimate the indoor radon concentrations at the ZCTA (Zip code tabulation area)-level and characterize uncertainties in model estimates. Incorporating geological, meteorological, and building-specific data, the models aim to improve radon risk assessment by capturing mean exposure, variability, and extreme concentration levels. Processed radon test data (n = 718,111) were analyzed using average, variability, and quantile prediction methods. Models that estimate the average radon exposure at the ZCTA-level can yield promising model-fit results, but they do not capture the underlying variability of indoor radon exposure within a ZCTA. We utilize volatility analyses to identify characteristics indicative of high variability of indoor radon exposure. We also show that a QRF model can be used to estimate upper quantiles of residential radon exposure, thereby uncovering localized areas of elevated exposure that were not apparent in mean estimates. The results highlighted the need for a deep characterization of exposure risk and show that regions with moderate average exposure levels could still harbor extreme outliers with implications for evaluating health risks. Utilizing multiple radon exposure models allows for a deeper characterization of radon risk within a geographic area and can better identify high-risk areas. The results from this study provide a foundation for developing mitigation strategies and examining associations between radon exposure and health outcomes at fine scales. Future research should extend the geographic scope and incorporate additional environmental risk factors to establish a comprehensive framework for risk assessment.

Lee, Heechan [ORNL]↗