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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Tropical Surface Temperature Response to Vegetation Cover Changes and the Role of Drylands

Vegetation cover creates competing effects on land surface temperature: it typically cools through enhancing energy dissipation and warms via decreasing surface albedo. Global vegetation has been previously found to overall net cool land surfaces with cooling contributions from temperate and tropical vegetation and warming contributions from boreal vegetation. Recent studies suggest dryland vegetation across the tropics strongly contributes to this global net cooling feedback. However, observation-based vegetation-temperature interaction studies have been limited in the tropics, especially in their widespread drylands. Theoretical considerations also call into question the ability of dryland vegetation to strongly cool the surface under low water availability. Here, we use satellite observations to investigate how tropical vegetation cover influences the surface energy balance. We find that while increased vegetation cover would impart net cooling feedbacks across the tropics, net vegetal cooling effects are subdued in drylands. Using observations, we determine that dryland plants have less ability to cool the surface due to their cooling pathways being reduced by aridity, overall less efficient dissipation of turbulent energy, and their tendency to strongly increase solar radiation absorption. As a result, while proportional greening across the tropics would create an overall biophysical cooling feedback, dryland tropical vegetation reduces the overall tropical surface cooling magnitude by at least 14%, instead of enhancing cooling as suggested by previous global studies.

Vegetation↗
NASA NTRS2022

Tropical Surface Temperature Response to Vegetation Cover Changes and the Role of Drylands

Vegetation cover creates competing effects on land surface temperature: it typically cools through enhancing energy dissipation and warms via decreasing surface albedo. Global vegetation has been previously found to overall net cool land surfaces with cooling contributions from temperate and tropical vegetation and warming contributions from boreal vegetation. Recent studies suggest dryland vegetation across the tropics strongly contributes to this global net cooling feedback. However, observation-based vegetation-temperature interaction studies have been limited in the tropics, especially in their widespread drylands. Theoretical considerations also call into question the ability of dryland vegetation to strongly cool the surface under low water availability. Here, we use satellite observations to investigate how tropical vegetation cover influences the surface energy balance. We find that while increased vegetation cover would impart net cooling feedbacks across the tropics, net vegetal cooling effects are subdued in drylands. Using observations, we determine that dryland plants have less ability to cool the surface due to their cooling pathways being reduced by aridity, overall less efficient dissipation of turbulent energy, and their tendency to strongly increase solar radiation absorption. As a result, while proportional greening across the tropics would create an overall biophysical cooling feedback, dryland tropical vegetation reduces the overall tropical surface cooling magnitude by at least 14%, instead of enhancing cooling as suggested by previous global studies.

Biophysical Feedbacks↗
DOE OSTI2025

PAVC: The foundation for a Pan-Arctic Vegetation Cover database

Field-measured Arctic vegetation cover data is essential for creating accurate, high-quality vegetation structure and composition maps. Extrapolating field data into high-resolution cover maps provides detailed, function-specific information for use in Earth System Models, vegetation classifications, and monitoring vegetation change over time and space. However, field campaigns that collect plant cover vary substantially in scope, method, and purpose, which makes them difficult to unify across data stores, and they are often not designed to meet remote sensing needs. In this work, we synthesized and harmonized field-based fractional cover data from various data stores to create a high-quality, consistent repository schema for remote sensing-based vegetation cover mapping applications. We developed a reproducible workflow for synthesizing visual estimate and point-intercept fractional cover data. The resultant Pan-Arctic Vegetation Cover (PAVC) database contains synthesized fractional cover at both the species and plant functional type levels. The latter includes absolute foliar cover for deciduous shrubs and trees, evergreen shrubs and trees, forbs, graminoids, lichen, bryophytes, and “other” vegetation, as well as absolute cover for litter and top cover for water and bare ground.

Steckler, Morgan R. [Oak Ridge National Laboratory↗
DOE OSTI2025

The Pan-Arctic Vegetation Cover (PAVC) database v1.1

The Pan-Arctic Vegetation Cover (PAVC) database contains synthesized field-data observations of vegetation cover from 978 Arctic Alaska plots with observations from 2010 to 2021. The cover datasets contain plot data at both the plant functional type (PFT) and species-level resolution, with standardized PFT definitions and species names. We synthesized publicly available point-intercept and visual estimate plots from the Arctic Vegetation Archive of Alaska, the Alaska Vegetation Plots Database, the North Slope Science Catalog, and the National Ecological Observatory Network; as well as previously unpublished data from the Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic).Users will find four synthesized datasets, 4 associated data descriptor (dd) files, and 1 metadata file in the PAVC database:synthesized_species_fcover.csv contains fractional cover (fcover) for unique accepted species names, where names include vegetation identified at the family, genus, species, subspecies, and variety levels, as well as general functional types across all 5 data sources. The synthesized_species_fcover_dd.csv accompanies this dataset with header information.synthesized_pft_fcover.csv contains fcover for the following PFTs: non-vascular plants with lichen and bryophyte subcategories, trees with deciduous and evergreen subcategories, shrubs with deciduous and evergreen subcategories, graminoids (grasses), and forbs (herbaceous flowering plants) measured as total cover. Litter and “other” cover are also included as total cover. Additional “types” include water and bare ground, which were measured as top cover. The synthesized_pft_fcover_dd.csv accompanies this dataset with header information.species_pft_checklist.csv is a lookup table containing the translation from a dataset species name to an accepted species name and to a PFT. This table can be used to clarify our species to PFT adjudications, and to aid users in assigning their own PFTs. Any issues found in this checklist should be reported in the Issues tab of our github.survey_unit_information.csv contains auxiliary information about the plots synthesized in this database. It contains useful information for filtering plots of interest based on temporal, geospatial, and contextual information about the plot surveys.flmd.csv contains metadata information about each file in the database.This research was performed as a part of the NGEE Arctic project. The NGEE Arctic project was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Variations in Bedrock and Vegetation Cover Modulate Subsurface Water Flow Dynamics of a Mountainous Hillslope

Abstract Predicting the hydrological response of watersheds to climate disturbances requires a detailed understanding of the processes connecting hillslopes and streams. Using a network of soil moisture and temperature sensors, electrical resistivity tomography monitoring, and a weather station we assess the above and below‐ground processes driving the hydrological response of a hillslope during snowmelt and summer monsoon. The transect covers bedrock and vegetation gradients, with a steep upper part characterized by shallow bedrock, and gentle lower part underlain by colluvium. The main vegetation cover is conifers on the upper, and grass and veratrum on the lower part. Combined with a simplified hydrological model, we show that the thin soil layer of the steep slope acts as a preferential flow path, leading to mostly shallow lateral flow, interrupted by vertical flow, mostly at tree locations, and likely facilitated by flow along fractures and roots. Vertical flow and upstream‐driven groundwater dynamics are prevailing at the colluvium, presenting a very different hydrological behavior compared to the upper part. These results show that subsurface structure and features have a strong control on the hydrological response of a hillslope and that those can create considerably varying hydrological dynamics across small spatial scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Increasing evapotranspiration decouples the positive correlation between vegetation cover and warming in the Tibetan plateau

Plant growth generally responds positively to an increase in ambient temperature. Hence, most Earth system models project a continuous increase in vegetation cover in the future due to elevated temperatures. Over the last 40 years, a considerable warming trend has affected the alpine ecosystem across the Tibetan Plateau. However, we found vegetation growth in the moderately vegetated areas of the plateau were negatively related to the warming temperatures, thus resulting in a significant degradation of the vegetative cover (LAI: slope = -0.0026 per year, p < 0.05). The underlying mechanisms that caused the decoupling of the relationship between vegetation growth and warming in the region were elaborated with the analysis of water and energy variables in the ecosystem. Results indicate that high temperatures stimulated evapotranspiration and increased the water consumption of the ecosystem (with an influence coefficient of 0.34) in these degrading areas, significantly reducing water availability (with an influence coefficient of -0.68) and limiting vegetation growth. Moreover, the negative warming effect on vegetation was only observed in the moderately vegetated areas, as evapotranspiration there predominantly occupied a larger proportion of available water (compared to the wet and highly vegetated areas) and resulted in a greater increase in total water consumption in a warmer condition (compared to dry areas with lower levels of vegetation cover). These findings highlight the risk of vegetation degradation in semi-arid areas, with the degree of vulnerability depending on the level of vegetation cover. Furthermore, results demonstrate the central role of evapotranspiration in regulating water stress intensity on vegetation under elevated temperatures.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1973

Monitoring vegetation cover on mine dumps with ERTS-1 imagery: Some initial results

ERTS-1 imagery is being used in an attempt to differentiate between mine dumps having varying degrees of vegetative cover. At this stage it is clear that the various mine dumps can be located and identified. Differences in vegetative cover can be seen and measured. Patterns of vegetative growth, some characteristic to particular dumps, can also be seen. It is therefore tentatively concluded that mine dumps can be differentiated with respect to their vegetative cover on the imagery received to date. Subsequent imagery showing seasonal variations should facilitate this program.

Gilbertson, B. P.↗
NASA NTRS1984

Calculations of radar backscattering coefficient of vegetation-covered soils

The present investigation has the objective to develop a simple 'user's' model for simulating the measured radar backscattering coefficients from vegetation-covered fields in conjunction with the data obtained by Jackson et al. (1980, 1982). The theoretical work reported by Fung and Eom (1981) provides the basis for the model. Certain modifications are related to a consideration of the effect of a vegetation canopy. The first part of the model is concerned with a description of scatter from rough bare soil, while the second part takes into account the effect of a vegetation cover. It is shown that the measured angular distribution of the backscattering coefficient of vegetation-covered fields can be satisfactory reproduced by using the developed model.

Mo, T.↗
NASA NTRS1999

Quantifying BRDF Effects in Comparing Landsat-7 and AVIRIS Near-Simultaneous Acquisitions for Studies of High Plains Vegetation Cover

Approximately 100,000 sq. km of the High Plains of the central United States are covered by sand dunes and sand sheets deposited during the Holocene. Soil-dating evidence shows that there were at least four periods of dune reactivation during major droughts in the last 10,000 years. The dunes in this region are anchored by vegetation. We have undertaken a study of land-use change in the High Plains from 1985 to the present using Landsat 5 TM and Landsat 7 ETM+ images to map variation in vegetation cover during wet and dry years. Mapping vegetation cover of less than 20% is important in modeling potential surface reactivation since at this level the vegetation no longer sufficiently shields sandy surfaces from movement by wind. Landsat TM data have both the spatial resolution and temporal coverage to facilitate vegetation cover analysis for model development and verification. However, there is still the question of how accurate TM data are for the measurement of both growing and senescent vegetation in and and semi-arid regions. AVIRIS provides both high spectral resolution as well as high signal-to-noise ratio and can be used to test the accuracy of Landsat TM and ETM+ data. We have analyzed data from AVIRIS flown nearly concurrently with a Landsat 7 overpass. The comparison between an AVIRIS image swath of 11 km width subtending a 30 deg. angle and the same area covered by a 0.8 deg. angle from Landsat required accounting for the BRDF. A normalization technique using the ratio of the reflectances from registered AVIRIS and Landsat data proved superior to the techniques of column averaging on AVIRIS data alone published previously by Kennedy et al. This technique can be applied to aircraft data covering a wider swath angle than AVIRIS to develop BRDF responses for a wide variety of surfaces more efficiently than from ground measurements.

Goetz, A. F. H.↗
NASA NTRS2023

Modeling Global Indices for Estimating Non-Photosynthetic Vegetation Cover

Non-photosynthetic vegetation (NPV) includes plant litter, senesced leaves, and crop residues. NPV plays an essential role in terrestrial ecosystem processes, and is an important indicator of drought severity, ecosystem disturbance, agricultural resilience, and wildfire danger. Current moderate spatial resolution multispectral satellite systems (e.g., Landsat and Sentinel-2) have only a single band in the 2000–2500 nm shortwave infrared “SWIR2” range where non-pigment biochemical constituents of NPV, including cellulose and lignin, have important spectral absorption features. Thus, these current systems have suboptimal capabilities for characterizing NPV cover. This research used simulated spectral mixtures accounting for variability among NPV and soils to evaluate globally-appropriate hyperspectral and multispectral indices for estimation of fractional NPV cover. The Continuum Interpolated NPV Depth Index (CINDI), a weighted ratio index measuring lignocellulose absorption near 2100 nm, was found to produce the lowest error in estimating NPV cover. CINDI was less sensitive to variability in soil spectra and green vegetation cover than competing indices. While CINDI was sensitive to the relative water content of soil and NPV, this sensitivity allowed for correcting error in estimated NPV cover as water content increased. CINDI bands were less capable than Dual Absorption NPV Index (DANI) bands for maintaining continuity with the heritage Landsat SWIR2 band, but combining multiple CINDI bands demonstrated adequate continuity. Three SWIR2 bands with band centers at 2038, 2108, and 2211 nm can provide superior capabilities for future moderate resolution multispectral/superspectral systems targeting NPV monitoring, including the next generation Landsat mission (Landsat Next). These bands and the associated CINDI index provide potential for global NPV monitoring using a constellation of future superspectral sensors and imaging spectrometers, with applications including improving soil management, preventing land degradation, evaluating impacts of drought, mapping ecosystem disturbance, and assessing wildfire danger.

Index optimization↗
NASA NTRS1982

A model for microwave emission from vegetation-covered fields

The measured brightness temperatures over vegetation-covered fields are simulated by a radiative transfer model which treats the vegetation as a uniform canopy with a constant temperature, over a moist soil which emits polarized microwave radiation. The analytic formula for the microwave emission has four parameters: roughness height, polarization mixing factor, effective canopy optical thickness, and single scattering albedo. A good representation has been obtained with the model for both the horizontally and vertically polarized brightness temperatures at 1.4 and 5 GHz frequencies, over fields covered with grass, soybean and corn. A directly proportional relation is found between effective canopy optical thickness and the amount of water present in the vegetation canopy. The effective canopy single scattering albedo depends on vegetation type.

Mo, T.↗
NASA NTRS1981

Radar reflectivity of bare and vegetation-covered soil

Radar sensitivity to soil moisture content has been investigated experimentally for bare and vegetation-covered soil using detailed spectral measurements obtained by a truck-mounted radar spectrometer in the 1-8 GHz band and by airborne scatterometer observations at 1.6, 4.75, and 13.3 GHz. It is shown that radar can provide quantitative information on the soil moisture content of both bare and vegetation-covered soil. The observed soil moisture is in the form of the soil matric potential or a related quantity such as the percent of field capacity. The depth of the monitored layer varies from 1 cm for very wet soil to about 15 cm for very dry soil.

Ulaby, F. T.↗
NASA NTRS1983

Effects of vegetation cover on the microwave radiometric sensitivity to soil moisture

The reduction in sensitivity of the microwave brightness temperature to soil moisture content due to vegetation cover is analyzed using airborne observations made at 1.4 and 5 GHz. The data were acquired during six flights in 1978 over a test site near Colby, Kansas. The test site consisted of bare soil, wheat stubble, and fully mature corn fields. The results for corn indicate that the radiometric sensitivity to soil moisture S decreases in magnitude with increasing frequency and with increasing angle of incidence (relative to nadir). The sensitivity reduction factor, defined in terms of the radiometric sensitivities for bare soil and canopy-covered conditions Y = 1 - Scan/Ss was found to be equal to 0.65 for normal incidence at 1.4 GHz, and increases to 0.89 at 5 GHz. These results confirm previous conclusions that the presence of vegetation cover may pose a serious problem for soil moisture detection with passive microwave sensors.

Ulaby, F. T.↗
NASA NTRS1995

Thermal remote sensing of surface soil water content with partial vegetation cover for incorporation into climate models

This study outlines a method for the estimation of regional patterns of surface moisture availability (M(sub 0)) and fractional vegetation (Fr) in the presence of spatially variable vegetation cover. The method requires relating variations in satellite-derived (NOAA, Advanced Very High Resolution Radiometer (AVHRR)) surface radiant temperature to a vegetation index (computed from satellite visible and near-infrared data) while coupling this association to an inverse modeling scheme. More than merely furnishing surface soil moisture values, the method constitues a new conceptual and practical approach for combining thermal infrared and vegetation index measurements for incorporating the derived values of M(sub 0) into hydrologic and atmospheric prediction models. Application of the technique is demonstrated for a region in and around the city of Newcastle upon Tyne situated in the northeast of England. A regional estimate of M(sub 0) is derived and is probabbly good for fractional vegetation cover up to 80% before errors in the estimated soil water content become unacceptably large. Moreover, a normalization scheme is suggested from which a nomogram, `universal triangle,' is constructed and is seen to fit the observed data well. The universal triangle also simplifies the inclusion of remotely derived M(sub 0) in hydrology and meteorological models and is perhaps a practicable step toward integrating derived data from satellite measurements in weather forecasting.

Gillies, Robert R.↗
NASA NTRS1986

The SIR-B observations of microwave backscatter dependence on soil moisture, surface roughness, and vegetation covers

An experiment was conducted from an L-band SAR aboard Space Shuttle Challenger in October 1984 to study the microwave backscatter dependence on soil moisture, surface roughness, and vegetation cover. The results based on the analyses of an image obtained at 21-deg incidence angle show a positive correlatlion between scattering coefficient and soil moisture content, with a sensitivity comparable to that derived from the ground radar measurements reported by Ulaby et al. (1978). The surface roughness strongly affects the microwave backscatter. A factor of two change in the standard deviation of surface roughness height gives a corresponding change of about 8 dB in the scattering coefficient. The microwave backscatter also depends on the vegetation types. Under the dry soil conditions, the scattering coefficient is observed to change from about -24 dB for an alfalfa or lettuce field to about -17 dB for a mature corn field. These results suggest that observations with a SAR system of multiple frequencies and polarizations are required to unravel the effects of soil moisture, surface roughness, and vegetation cover.

Wang, J. R.↗
NASA NTRS1983

Calculations of radar backscattering coefficient of vegetation-covered soils

A model for simulating the measured backscattering coefficient of vegetation-covered soil surfaces includes both coherent and incoherent components of the backscattered radar pulses from a rough sil surface. The effect of vegetation canopy scattering is also incorporated into the model by making the radar pulse subject to two-way attenuation and volume scattering when it passes through the vegetation layer. Model results agree well with the measured angular distributions of the radar backscattering coefficient for HH polarization at the 1.6 GHz and 4.75 GHz frequencies over grass-covered fields. It was found that the coherent scattering component is very important at angles near nadir, while the vegetation volume scattering is dominant at incident angles 30 degrees.

Mo, T.↗
NASA NTRS1975

Detection of short-term changes in vegetation cover by use of LANDSAT imagery

The author has identified the following significant results. By using a constant band 6 to band 5 radiance ratio of 1.25, the changing pattern of areas of relatively dense vegetation cover was detected for the semiarid region in the vicinity of Tucson, Arizona. Electronically produced binary thematic masks were used to map areas with dense vegetation. The foliar cover threshold represented by the ratio was not accurately determined but field measurements show that the threshold lies in the range of 10 to 25 percent foliage cover. Montana evergreen forests with constant dense cover were correctly shown to exceed the threshold on all dates. The summer active grassland exceeded the threshold in the summer unless rainfall was insufficient. Desert areas exceeded the threshold during the spring of 1973 following heavy rains; the same areas during the rainless spring of 1974 did not exceed threshold. Irrigated fields, parks, golf courses, and riparian communities were among the habitats most frequently surpassing the threshold.

Turner, R. M.↗