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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Mapping Forest Disturbance Intensity in North and South Carolina Using Annual Landsat Observations and Field Inventory Data

Disturbance and regrowth are vital processes in determining the roles of forest ecosystem in the carbon and biogeochemical cycles. Using time series observations, the vegetation change tracker (VCT) algorithm was designed to map the location, timing, and spectral magnitudes of forest disturbance events. While these spectral disturbance magnitudes are indicative of physical changes in tree cover or biomass, their quantitative relationships have yet to be established. This study focuses on estimating disturbance intensity as measured by percent basal area removal using spectral indices from the VCT algorithm over North and South Carolina. Repeat measurements on Forest Service Forest Inventory Analysis (FIA) ground plots, which provide changes in basal area between multiple dates at precise locations, are used for training and validation of the model. The overall R2 between predicted disturbance intensity and reference data is 0.66, and cross-validation prediction uncertainty is 14% in North Carolina. Possible causes of this uncertainty could be site heterogeneity and the temporal offset between ground measurements and satellite observations. Results show the area of stand clearing disturbances remains relatively stable around 1143 km2 yr−1 in North and South Carolina throughout the period of observations (1985–2015). The average amount of forest area affected by partial disturbance is much higher at 3287 km2 yr−1. The area of partial disturbances has strong inter-annual variability with a high value of 6000 km2 in 2007 and a low value of 1919 km2 in 2013.

Xin Tao↗
NASA NTRS2021

Mapping Global Forest Age from Forest Inventories, Biomass and Climate Data

Forest age can determine the capacity of a forest to uptake carbon from the atmosphere. However, a lack of global diagnostics that reflect the forest stage and associated disturbance regimes hampers the quantification of age-related differences in forest carbon dynamics. This study provides a new global distribution of forest age circa 2010, estimated using a machine learning approach trained with more than 40 000 plots using forest inventory, biomass and climate data. First, an evaluation against the plot-level measurements of forest age reveals that the data-driven method has a relatively good predictive capacity of classifying old-growth vs. non-old-growth (precision = 0.81 and 0.99 for old-growth and non-old-growth, respectively) forests and estimating corresponding forest age estimates (NSE = 0.6 – Nash–Sutcliffe efficiency – and RMSE = 50 years – root-mean-square error). However, there are systematic biases of overestimation in young- and underestimation in old-forest stands, respectively. Globally, we find a large variability in forest age with the old-growth forests in the tropical regions of Amazon and Congo, young forests in China, and intermediate stands in Europe. Furthermore, we find that the regions with high rates of deforestation or forest degradation (e.g. the arc of deforestation in the Amazon) are composed mainly of younger stands. Assessment of forest age in the climate space shows that the old forests are either in cold and dry regions or warm and wet regions, while young–intermediate forests span a large climatic gradient. Finally, comparing the presented forest age estimates with a series of regional products reveals differences rooted in different approaches and different in situ observations and global-scale products. Despite showing robustness in cross-validation results, additional methodological insights on further developments should as much as possible harmonize data across the different approaches. The forest age dataset presented here provides additional insights into the global distribution of forest age to better understand the global dynamics in the forest water and carbon cycles. The forest age datasets are openly available at https://doi.org/10.17871/ForestAgeBGI.2021 (Besnard et al., 2021).

Simon Besnard↗
NASA NTRS2016

The Habitability of Proxima Centauri b: I. Irradiation, Rotation and Volatile Inventory From Formation to the Present

Proxima b is a planet with a minimum mass of 1.3 M(sub ⨁) orbiting within the habitable zone (HZ) of Proxima Centauri, a very low-mass, active star and the Sun’s closest neighbor. Here we investigate a number of factors related to the potential habitability of Proxima b and its ability to maintain liquid water on its surface. We set the stage by estimating the current high-energy irradiance of the planet and show that the planet currently receives 30 times more extreme-UV radiation than Earth and 250 times more X-rays. We compute the time evolution of the star’s spectrum, which is essential for modeling the flux received over Proxima b’s lifetime. We also show that Proxima b’s obliquity is likely null, and its spin is either synchronous or in a 3:2 spin-orbit resonance, depending on the planet’s eccentricity and level of triaxiality. Next, we consider the evolution of Proxima b’s water inventory. We use our spectral energy distribution to compute the hydrogen loss from the planet with an improved energy-limited escape formalism. Despite the high level of stellar activity, we find that Proxima b is likely to have lost less than an Earth ocean’s worth of hydrogen (EO(sub H)) before it reached the HZ 100–200 Myr after its formation. The largest uncertainty in our work is the initial water budget, which is not constrained by planet formation models. We conclude that Proxima b is a viable candidate habitable planet.

Proxima Cen↗
NASA NTRS1970

Experimental applications of multispectral data to natural resource inventory and survey

The feasibility of using multispectral, color, color infrared, thermal infrared imagery and related ground data to recognize, identify, determine and monitor the status of mineral ore and metals stockpiles is studied. An attempt was made to identify valid, unique spectral signatures of such materials for possible use under a wide variety of environmental circumstances. Research emphasis was upon the analysis of the multiband imagery from the various film-filter combinations, using density analysis techniques.

Mallon, H. J.↗
NASA NTRS1971

Remote sensing for mined area reclamation: Application inventory

Applications of aerial remote sensing to coal mined area reclamation are documented, and information concerning available data banks for coal producing areas in the east and midwest is given. A summary of mined area information requirements to which remote sensing methods might contribute is included.

Source record↗
NASA NTRS1971

An inventory of aeronautical ground research facilities. Volume 4: Engineering flight simulation facilities

The general purpose capabilities of government and industry in the area of real time engineering flight simulation are discussed. The information covers computer equipment, visual systems, crew stations, and motion systems, along with brief statements of facility capabilities. Facility construction and typical operational costs are included where available. The facilities provide for economical and safe solutions to vehicle design, performance, control, and flying qualities problems of manned and unmanned flight systems.

Pirrello, C. J.↗