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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 NTRS1999

Estimating Vegetation Parameters from Interferometric and Polarimetric Radar Using Physical Scattering Models

Radar data from vegetated land surfaces depend on many structural and compositional parameters describing the terrain. Because early, noninterferometric radar systems usually constituted an insufficient observation set from which to estimate parameters of the terrain, statistical regression techniques were used which incorporated some level of apriori knowledge or field measurements. With the advent of radar interferometry and polarimetric interferometry, potentially at multiple baselines, the observation set is now approaching that required to quantitatively estimate the parameters describing a vegetated land surface. Quantitative estimation entails formulating a physical scattering model relating the radar observations to the vegetation and surface parameters on which they depend. This paper describes the physics of candidate scattering models, and shows how the models determine the estimable parameter set. It also indicates the measurement accuracy of parameters such as vegetation height, height-to-base-of-live-crown, and surface topography with multibaseline polarimetric interferometry.

Treuhaft, Robert N.↗
NASA NTRS1992

The application of a geometric optical canopy reflectance model to semiarid shrub vegetation

Estimates are obtained of the average plant size and density of shrub vegetation on the basis of SPOT High Resolution Visible Multispectral imagery from Chihuahuan desert areas, using the Li and Strahler (1985) model. The aggregated predictions for a number of stands within a class were accurate to within one or two standard errors of the observed average value. Accuracy was highest for those classes of vegetation where the nonrandom scrub pattern was characterized for the class on the basis of the average coefficient of the determination of density.

Franklin, Janet↗
DOE OSTI2024

Integrating NDVI-Based Within-Wetland Vegetation Classification in a Land Surface Model Improves Methane Emission Estimations

Earth system models (ESMs) are a common tool for estimating local and global greenhouse gas emissions under current and projected future conditions. Efforts are underway to expand the representation of wetlands in the Energy Exascale Earth System Model (E3SM) Land Model (ELM) by resolving the simultaneous contributions to greenhouse gas fluxes from multiple, different, sub-grid-scale patch-types, representing different eco-hydrological patches within a wetland. However, for this effort to be effective, it should be coupled with the detection and mapping of within-wetland eco-hydrological patches in real-world wetlands, providing models with corresponding information about vegetation cover. In this short communication, we describe the application of a recently developed NDVI-based method for within-wetland vegetation classification on a coastal wetland in Louisiana and the use of the resulting yearly vegetation cover as input for ELM simulations. Processed Harmonized Landsat and Sentinel-2 (HLS) datasets were used to drive the sub-grid composition of simulated wetland vegetation each year, thus tracking the spatial heterogeneity of wetlands at sufficient spatial and temporal resolutions and providing necessary input for improving the estimation of methane emissions from wetlands. Our results show that including NDVI-based classification in an ELM reduced the uncertainty in predicted methane flux by decreasing the model’s RMSE when compared to Eddy Covariance measurements, while a minimal bias was introduced due to the resampling technique involved in processing HLS data. Our study shows promising results in integrating the remote sensing-based classification of within-wetland vegetation cover into earth system models, while improving their performances toward more accurate predictions of important greenhouse gas emissions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

A Corrected Formulation of the Multilayer Model (MLM) for Inferring Gaseous Dry Deposition to Vegetated Surfaces

The Multilayer Model (MLM) has been used for many years to infer dry deposition fluxes from measured trace species concentrations and standard meteorological measurements for national networks in the U.S., including the U.S. Environmental Protection Agency's Clean Air Status and Trends Network (CASTNet). MLM utilizes a resistance analogy to calculate deposition velocities appropriate for whole vegetative canopies, while employing a multilayer integration to account for vertically varying meteorology, canopy morphology and radiative transfer within the canopy. However, the MLM formulation, as it was originally presented and as it has been subsequently employed, contains a non-physical representation related to the leaf-level quasi-laminar boundary layer resistance that affects the calculation of the total canopy resistance. In this note, the non-physical representation of the canopy resistance as originally formulated in MLM is discussed and a revised, physically consistent, formulation is suggested as a replacement. The revised canopy resistance formulation reduces estimates of HNO3 deposition velocities by as much as 38% during mid-day as compared to values generated by the original formulation. Inferred deposition velocities for SO2 and O3 are not significantly altered by the change in formulation (less than 3%). Inferred deposition loadings of oxidized and total nitrogen from CASTNet data may be reduced by 10-20% and 5-10%, respectively, for the Eastern U. S. when employing the revised formulation of MLM as compared to the original formulation.

vegetated surfaces↗
NASA NTRS1992

Geometric-optical bidirectional reflectance modeling of the discrete crown vegetation canopy - Effect of crown shape and mutual shadowing

Many natural vegetation covers can be regarded as assemblages of plant crowns, on a background, which interact with light as discrete objects. On this basis, geometric optics furnish an approach to the modeling of vegetation canopies that captures the most important features of such growths' bidirectional measurements. Attention is presently given to models which approximate these phenomena and relate the size, shape, and count density of plant crowns to viewing and illumination positions and to crown-background reflectance contrasts.

Li, Xiaowen↗
NASA NTRS2010

Irrigation Requirement Estimation Using Vegetation Indices and Inverse Biophysical Modeling

We explore an inverse biophysical modeling process forced by satellite and climatological data to quantify irrigation requirements in semi-arid agricultural areas. We constrain the carbon and water cycles modeled under both equilibrium, balance between vegetation and climate, and non-equilibrium, water added through irrigation. We postulate that the degree to which irrigated dry lands vary from equilibrium climate conditions is related to the amount of irrigation. The amount of water required over and above precipitation is considered as an irrigation requirement. For July, results show that spray irrigation resulted in an additional amount of water of 1.3 mm per occurrence with a frequency of 24.6 hours. In contrast, the drip irrigation required only 0.6 mm every 45.6 hours or 46% of that simulated by the spray irrigation. The modeled estimates account for 87% of the total reported irrigation water use, when soil salinity is not important and 66% in saline lands.

Bounoua, Lahouari↗
NASA NTRS2010

Quantifying the Negative Feedback of Vegetation to Greenhouse Warming: A Modeling Approach

Several climate models indicate that in a 2 x CO2 environment, temperature and precipitation would increase and runoff would increase faster than precipitation. These models, however, did not allow the vegetation to increase its leaf density as a response to the physiological effects of increased CO2 and consequent changes in climate. Other assessments included these interactions but did not account for the vegetation down-regulation to reduce plant's photosynthetic activity and as such resulted in a weak vegetation negative response. When we combine these interactions in climate simulations with 2 x CO2, the associated increase in precipitation contributes primarily to increase evapotranspiration rather than surface runoff, consistent with observations, and results in an additional cooling effect not fully accounted for in previous simulations with elevated CO2. By accelerating the water cycle, this feedback slows but does not alleviate the projected warming, reducing the land surface warming by 0.6 C. Compared to previous studies, these results imply that long term negative feedback from CO2-induced increases in vegetation density could reduce temperature following a stabilization of CO2 concentration.

Bounous, L.↗
NASA NTRS1984

Measuring and Modeling of the Dielectric Properties and Attenuation of Vegetation

The dielectric properties and attenuation of vegetation was measured and modeled. The purpose was to: (1) measure the microwave dielectric properties of vegetation material as a function of moisture content and microwave frequency; (2) develop dielectric mixing models for the vegetation-water mixture; (3) develop a model for the loss factor of a vegetation canopy; (4) relate the results of (1) and (2) to (3); and (5) test the model in (3) against direct canopy transmission measurements.

F Ulaby↗
DOE OSTI2025

Demography, dynamics and data: building confidence for simulating changes in the world's forests

Vegetation demographic models (VDMs) are advanced tools for simulating forest responses to climate and land-use changes, and are essential for projecting carbon cycling and large-scale forest management strategies. Despite their increasing incorporation into Earth System Models, VDMs differ in their demographic assumptions, with no prior quantitative comparison of their performance. We benchmarked nine VDMs against observational data from boreal, temperate and tropical sites, assessing their accuracy in predicting tree growth, carbon turnover, biomass stocks and size distributions. Models were simulated under consistent climate conditions with postdisturbance recovery monitored for at least 420 yr. Postdisturbance carbon recovery trajectories showed significant variability while remaining within observational ranges. Initial regrowth rates varied substantially (0.03-0.60, 0.18-0.70 and 0.35-1.10 kgCm-2 yr-1 for boreal, temperate and tropical sites, respectively), influenced by each model's initial forest state. Models captured mature forest carbon content but showed compensating effects between overestimated growth and underestimated mortality rates. This first multi-model benchmarking identifies growth and mortality rates as critical calibration targets and highlights the need to refine postdisturbance establishment conditions for model development. We outline specific benchmarking variables needed to improve predictions of forest responses to environmental change.

demographic vegetation model benchmarking↗
NASA NTRS1987

Inversion of canopy reflectance models for estimation of vegetation parameters

One of the keys to successful remote sensing of vegetation is to be able to estimate important agronomic parameters like leaf area index (LAI) and biomass (BM) from the bidirectional canopy reflectance (CR) data obtained by a space-shuttle or satellite borne sensor. One approach for such an estimation is through inversion of CR models which relate these parameters to CR. The feasibility of this approach was shown. The overall objective of the research carried out was to address heretofore uninvestigated but important fundamental issues, develop the inversion technique further, and delineate its strengths and limitations.

Goel, Narendra S.↗
NASA NTRS1999

Simple Forest Canopy Thermal Exitance Model

We describe a model to calculate brightness temperature and surface energy balance for a forest canopy system. The model is an extension of an earlier vegetation only model by inclusion of a simple soil layer. The root mean square error in brightness temperature for a dense forest canopy was 2.5 C. Surface energy balance predictions were also in good agreement. The corresponding root mean square errors for net radiation, latent, and sensible heat were 38.9, 30.7, and 41.4 W/sq m respectively.

Smith J. A.↗
NASA NTRS2020

Twenty‐First Century Drought Projections in the CMIP6 Forcing Scenarios

There is strong evidence climate change will increase drought risk and severity, but these conclusions depend on the regions, seasons, and drought metrics being considered. We analyze changes in drought across the hydrologic cycle (precipitation, soil moisture, and runoff) in projections from Phase Six of the Coupled Model Intercomparison Project (CMIP6). The multi‐model ensemble shows robust drying in the mean state across many regions and metrics by the end of the 21st century, even following the more aggressive mitigation pathways (SSP1‐2.6 and SSP2‐4.5). Regional hotspots with strong drying include western North America, Central America, Europe and the Mediterranean, the Amazon, southern Africa, China, Southeast Asia, and Australia. Compared to SSP3‐7.0 and SSP5‐8.5, however, the severity of drying in the lower warming scenarios is substantially reduced and further precipitation declines in many regions are avoided. Along with drying in the mean state, the risk of the historically most extreme drought events also increases with warming, by 200–300% in some regions. Soil moisture and runoff drying in CMIP6 is more robust, spatially extensive, and severe than precipitation, indicating an important role for other temperature‐sensitive drought processes, including evapotranspiration and snow. Given the similarity in drought responses between CMIP5 and CMIP6, we speculate both generations of models are subject to similar uncertainties, including vegetation processes, model representations of precipitation, and the degree to which model responses to warming are consistent with observations. These topics should be further explored to evaluate whether CMIP6 models offer reasons to have increased confidence in drought projections.

drought↗
NASA NTRS2017

Temporal Consistency Between Gross Primary Production and Solar-Induced Chlorophyll Fluorescence in the Ten Most Populous Megacity Areas over Years

The gross primary production (GPP) of vegetation in urban areas plays an important role in the study of urban ecology. It is difficult however, to accurately estimate GPP in urban areas, mostly due to the complexity of impervious land surfaces, buildings, vegetation, and management. Recently, we used the Vegetation Photosynthesis Model (VPM), climate data, and satellite images to estimate the GPP of terrestrial ecosystems including urban areas. Here, we report VPM-based GPP (GPPvpm) estimates for the world's ten most populous megacities during 2000-2014. The seasonal dynamics of GPPvpm during 2007-2014 in the ten megacities track well that of the solar-induced chlorophyll fluorescence (SIF) data from GOME-2 at 0.5deg x 0.5deg resolution. Annual GPPvpm during 2000-2014 also shows substantial variation among the ten megacities, and year-to-year trends show increases, no change, and decreases. Urban expansion and vegetation collectively impact GPP variations in these megacities. The results of this study demonstrate the potential of a satellite-based vegetation photosynthesis model for diagnostic studies of GPP and the terrestrial carbon cycle in urban areas.

urban↗
NASA NTRS2013

Hydroclimatic Controls on the Means and Variability of Vegetation Phenology and Carbon Uptake

Long-term, global offline (land-only) simulations with a dynamic vegetation phenology model are used to examine the control of hydroclimate over vegetation-related quantities. First, with a control simulation, the model is shown to capture successfully (though with some bias) key observed relationships between hydroclimate and the spatial and temporal variations of phenological expression. In subsequent simulations, the model shows that: (i) the global spatial variation of seasonal phenological maxima is controlled mostly by hydroclimate, irrespective of distributions in vegetation type, (ii) the occurrence of high interannual moisture-related phenological variability in grassland areas is determined by hydroclimate rather than by the specific properties of grassland, and (iii) hydroclimatic means and variability have a corresponding impact on the spatial and temporal distributions of gross primary productivity (GPP).

GPP↗
NASA NTRS1990

A physical model of the bidirectional reflectance of vegetation canopies. I - Theory. II - Inversion and validation

A new physically based analytical model of the bidirectional reflectance of vegetation canopies is derived. The model expresses the bidirectional reflectance field of a semiinfinite canopy as a combination of functions describing (1) the optical properties of the leaves through their single-scattering albedo and their phase function, (2) the average distribution of leaf orientations, and (3) the architecture of the canopy. The model is validated against laboratory and ground-based measurements in the visible and IR spectral regions, taken over two vegetation covers. The intrinsic optical properties of leaves and the information on the geometrical canopy arrangements in space were obtained using an inversion procedure based on a nonlinear optimization technique. Model predictions of bidirectional reflectances obtained using the inversion procedure compare well with actual observations.

Verstraete, Michel M.↗
NASA NTRS1991

Calculating the bidirectional reflectance of natural vegetation covers using Boolean models and geometric optics

The bidirectional radiance or reflectance of a forest or woodland can be modeled using principles of geometric optics and Boolean models for random sets in a three dimensional space. This model may be defined at two levels, the scene includes four components; sunlight and shadowed canopy, and sunlit and shadowed background. The reflectance of the scene is modeled as the sum of the reflectances of the individual components as weighted by their areal proportions in the field of view. At the leaf level, the canopy envelope is an assemblage of leaves, and thus the reflectance is a function of the areal proportions of sunlit and shadowed leaf, and sunlit and shadowed background. Because the proportions of scene components are dependent upon the directions of irradiance and exitance, the model accounts for the hotspot that is well known in leaf and tree canopies.

Strahler, Alan H.↗
NASA NTRS1999

Physics Based Modeling and Rendering of Vegetation in the Thermal Infrared

We outline a procedure for rendering physically-based thermal infrared images of simple vegetation scenes. Our approach incorporates the biophysical processes that affect the temperature distribution of the elements within a scene. Computer graphics plays a key role in two respects. First, in computing the distribution of scene shaded and sunlit facets and, second, in the final image rendering once the temperatures of all the elements in the scene have been computed. We illustrate our approach for a simple corn scene where the three-dimensional geometry is constructed based on measured morphological attributes of the row crop. Statistical methods are used to construct a representation of the scene in agreement with the measured characteristics. Our results are quite good. The rendered images exhibit realistic behavior in directional properties as a function of view and sun angle. The root-mean-square error in measured versus predicted brightness temperatures for the scene was 2.1 deg C.

Smith, J. A.↗