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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Synoptic System for Capturing Ecosystem Control Points Across Terrestrial‐Aquatic Interfaces

Interconnected landscape features such as terrestrial‐aquatic interfaces play an outsized role in biogeochemical cycles as ecosystem control points, but it is notoriously challenging to characterize these. Here, we document a synoptic sensor network design that is (a) flexible to accommodate diverse ecosystem interfaces and gradients, (b) adaptable to monitoring and modeling needs of small and large projects alike, (c) standardized for intercomparability across sites and field experiments, and (d) adequately replicated to capture heterogeneity of each parameter monitored. This real‐time monitoring of surface water, groundwater, soil, and vegetation supports configuration and evaluation of models that span upland, wetland, open water strata, and transitions between them. We established the network at seven sites along the Chesapeake Bay and Lake Erie coastlines, including large‐scale flood manipulation experiments in both regions. A central design element is “one data logger program to rule them all”—a collection of sensor‐specific modules deployed on 40 loggers controlling ∼2,000 sensors, with the goal of streamlining maintenance, debugging, and reproducible data processing. The network generates ∼6 M observations per month, capturing system dynamics at the broad spatial and fine temporal scales needed to initialize and benchmark models; measurement frequency can be modified remotely to capture events. This network design has also revealed behaviors not represented in Earth system models, such as transient groundwater oxygen pulses. Completely documented and open source, this standardized, flexible, and efficient sensor network design can reduce barriers to understanding environmental changes and ecosystem responses across systems and scales.

Ward, Nicholas D. [Pacific Northwest National Labo↗
NASA NTRS1997

Surface Energy Heat Fluxes Using Remotely Sensed Parameters

Realistic estimates of surface energy heat fluxes are needed for the study of water and energy interactions between the land and atmosphere. The primary objective of this work is to study the estimation of surface heat energy fluxes using remote sensing derived parameters under different spatial and temporal conditions. Surface energy fluxes and remote sensing derived data from two sources were analyzed. First, we used surface heat flux, remote sensing, and ancillary data from the International Satellite Land Surface Climatology Project (ISLSCP), mapped at a 1 deg. x 1 deg. grid. Second, we used NOAA AVHRR (1 km), weather station, and ancillary data to derive estimates of surface latent and sensible heat energy fluxes over a 100 sq kilometers area for three test sites: 1) First ISLSCP Field Experiment (FIFE) grassland site, Konza Prairie, Kansas; 2) Howland, Maine Forest Ecosystem Dynamics Site; and 3) Walnut Gulch, scrubland site, surrounding Tombstone, Arizona. Satellite derived estimates of land surface temperature, surface albedo, and spectral vegetation index are used in selected models to provide estimates of surface heat fluxes. Analysis of results from the 1 deg. x 1 deg. grid for North America indicated there were similar, overall correlations between sensible and latent heat energy fluxes versus remotely sensed vegetation index and ground temperature during dry and wet year conditions. However, there were significant differences in correlations between years when stratified by land cover class. Analysis of 100 km x 100 km data (1 km resolution) indicated partitioning the areas in to primary versus secondary cover, with the secondary cover comprising less than 5% of the area, significantly improved surface heat energy flux estimates.

Toll, David L.↗
NASA NTRS1985

Microwave Dielectric and Propagation Properties of Vegetation Canopies

A vegetation canopy is a highly inhomogeneous medium at microwave frequencies, and because the scattering elements (leaves, stalks, fruits, and branches) have a nonuniform distribution in orientation, the canopy is likely to exhibit nonisotropic attenuation properties. In some canopies, the stalk may contain the overwhelming majority of the plant's biomass, which suggests that an incident radar wave would be differentially attenuated by the canopy depending on the direction of the incident electric field relative to the stalks' orientation. The propagation properties of a vegetation canopy play a central role in modeling both the backscattering behavior observed by an imaging radar and the emission observed by a radiometer. These propagation properties are in turn governed by the dielectric properties and the size, shape, and slope distributions of the scatteres. In spite of the critical need for canopy propagation models and experimental data, very few investigations had been conducted (prior to this study) to determine the extinction properties of vegetation canopies, either by constituent type (leaves, stalks, etc.) or as a whole.

Ulaby, F. T.↗
DOE OSTI2020

Recoveries of Oil and Hydrolyzed Sugars from Corn Germ Meal by Hydrothermal Pretreatment: A Model Feedstock for Lipid-Producing Energy Crops

Vegetable oil is extracted from oil rich seeds, such as soybeans. Genetic engineering of green plants to accumulate oil in vegetative tissue is a future source of oil that promises increased land productivity and the use of marginal lands. However, the low concentration of lipids in current engineered plant biomass samples makes the oil extraction process challenging and expensive. In this study, liquid hot water (LHW) pretreatment was investigated to enhance oil recovery from the solids and increase enzymatic hydrolysis efficiency of such feedstocks. Corn germ meal was chosen as a model feedstock representing lipid-producing energy crops. Germ meal was pretreated at 160 and 180 °C for 10 and 15 min at 20% w/w solids loading. Enzymatic hydrolysis on the pretreated solid was performed. After pretreatment, the oil concentration increased by 2.2 to 4.2 fold. The most severe pretreatment condition of LHW, at 180 °C for 15 min, gave the maximum oil concentration (9.7%, w/w), the highest triacylglycerol (TAG) content of the extracted oil (71.6%), and the highest conversions of glucose and xylose (99.0% and 32.8%, respectively). This study demonstrates that the optimal pretreatment condition for corn germ meal is 180 °C LHW for 15 min. Pretreatment improves lipids recovery from oil bearing biomass with little or no effect on the lipid profile.

09 BIOMASS FUELS↗
DOE OSTI2025

ELM model simulations of Plum Island Ecosystems LTER low marsh site 2018-2020

Model simulations using the Department of Energy's Energy Exascale Earth System Model (E3SM) land model (ELM) with improved capabilities to represent vegetation response to salinity and inundation. The simulations were conducted for a tidal salt marsh at Plum Island Ecosystems Long Term Ecological Research (LTER) site near Rowley, Massachusetts, USA; the site is a low marsh dominated by Spartina alterniflora. The model was forced with site-specific meteorology, salinity and tidal cycles from 2018-2020. Four sets of model simulations are included and described below:1. Parameterization of the salinity response function. These simulations tested different combinations of values for optimal salinity and salinity tolerance.2. Model evaluation. This comparison conducted simulations using the default model, the salinity function only, the submergence function only, and both the salinity and submergence functions. 3. Salinity scenarios. These simulations used the 2018 salinity input data varied by -5 to +10 ppt salinity.4. Water level scenarios. These simulations used the tide height varied by -10 to +50 cm. These simulations were used to demonstrate how the salinity and submergence functions better represent carbon uptake by tidal salt marshes.The data package includes netCDF files used as forcing files for tide height and salinity, one for each year 2018-2020 at observed salinity concentrations, and an additional three forcing files in which salinity concentrations were varied 5 ppt lower, 5 ppt higher, and 10 ppt higher than the measured 2018 time series. Also included are python scripts for creating forcing files, plain text parameter and command files for running simulations, model outputs in netCDF format, and python scripts for visualizing outputs. Code for the modified E3SM model is archived in Sulman et al 2023 at doi:10.15485/1991625. More detail about files is provided in the README.md file.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Simulated retrieval of land surface parameters using multichannel satellite microwave radiometry

The current global change research emphasis on understanding water and energy fluxes at the land-atmosphere interface provided renewed interest in using passive microwave satellite data for land studies. Radiative transfer models of microwave emission and scattering in the soil-vegetation-atmosphere column, though still in the process of development, can be used to estimate the accuracies with which land surface parameters can be derived from satellite data. These parameters include surface soil moisture, surface temperature, vegetation water content, and atmospheric water content. A microwave radiative transfer model is used to develop linear and nonlinear versions of a multichannel retrieval algorithm to simulate retrievals of the surface and atmospheric parameters. These simulations include the effect of additive noise, and examine the effects of nonlinearities in the radiative transfer models. However, effects of spatial heterogeneity are not considered. Satellite data to which the retrieval algorithms may be applied include the SSMR and SSM/I, and in future will include the Multifrequency Imaging Microwave Radiometer (MIMR) to be launched as part of the Earth Observing System (EOS). The Scanning Multichannel Microwave Radiometer (SMMR) on the Nimbus-7 satellite provided data from 1978 to 1987 at five microwave frequencies between 6.6 and 37 GHz. The series of Special Sensor Microwave/Imager (SSM/I) instruments launched on the DMSP satellites provide data from 1987 to the present at four frequencies between 19.35 and 8.5 GHz. Spatial resolutions of the data range from approximately 12 to 120 km depending on the frequency. Examples using data from these sensors are shown to indicate the results of applying retrieval algorithms based on model simulations to real data.

Njoku, Eni G.↗
NASA NTRS2018

Polarization Decomposition and Temperature Bias Resolution for SMAP Passive Soil Moisture Retrieval Using Time Series Brightness Temperature Observations

In passive microwave remote sensing of soil moisture, the tau-omega (τ-ω) model has often been used to provide soil moisture estimates at a spatial scale representative of the satellite footprint dimensions. For modeling simplicity, model parameters such as the single scattering albedo (ω) and vegetation opacity (τ) that go into the geophysical inversion process are often assumed to be independent of polarizations. Although this absence of polarization dependence can often be justified in special cases as in low-frequency remote sensing or under dense vegetation conditions, it is not a robust assumption in general. Additional model parameterization errors arising from this assumption are possible, leading to degradation in soil moisture estimation accuracy. In this paper, we propose a time series approach to try to resolve the polarization dependence of several τ-ω model parameters as well as the temperature bias arising from the ancillary temperature data. The Version 4 of the Soil Moisture Active Passive (SMAP) Level 1B brightness temperature time series observations were used to illustrate the mechanics of this approach, with an emphasis on a comparison between resulting satellite soil moisture retrievals and in situ data collected at several core validation sites. It was found that this time series approach resulted in significant reduction of the dry bias exhibited in the current SMAP passive soil moisture data products, while retaining the same performance in other metrics of the current baseline passive soil moisture retrieval algorithm.

time series↗
NASA NTRS2012

Roles of Urban Tree Canopy and Buildings in Urban Heat Island Effects: Parameterization and Preliminary Results

Urban heat island (UHI) effects can strengthen heat waves and air pollution episodes. In this study, the dampening impact of urban trees on the UHI during an extreme heat wave in the Washington, D.C., and Baltimore, Maryland, metropolitan area is examined by incorporating trees, soil, and grass into the coupled Weather Research and Forecasting model and an urban canopy model (WRF-UCM). By parameterizing the effects of these natural surfaces alongside roadways and buildings, the modified WRF-UCM is used to investigate how urban trees, soil, and grass dampen the UHI. The modified model was run with 50% tree cover over urban roads and a 10% decrease in the width of urban streets to make space for soil and grass alongside the roads and buildings. Results show that, averaged over all urban areas, the added vegetation decreases surface air temperature in urban street canyons by 4.1 K and road-surface and building-wall temperatures by 15.4 and 8.9 K, respectively, as a result of tree shading and evapotranspiration. These temperature changes propagate downwind and alter the temperature gradient associated with the Chesapeake Bay breeze and, therefore, alter the strength of the bay breeze. The impact of building height on the UHI shows that decreasing commercial building heights by 8 m and residential building heights by 2.5 m results in up to 0.4-K higher daytime surface and near-surface air temperatures because of less building shading and up to 1.2-K lower nighttime temperatures because of less longwave radiative trapping in urban street canyons.

urban vegetation↗
NASA NTRS2010

Evaluating the Impact of Vegetation Cover and Atmospheric Characteristics on the Estimation of Snow Water Equivalent from Spaceborne Microwave Radiometry

A radiative transfer model for estimating snow water equivalent (SWE, mm) from satellite-observed brightness temperature (K) at 19 and 37 GHz (respectively, T(sub B(sub, sat,19)) and T(sub B(sub, sat,37)) over partially forested area is presented, as an extension of a previously published model, by considering scattering of radiation within the canopy. For the specific case of dense vegetation covering fractional area f, the model can be written as, SWE = alpha{ A. delta (T(sub B(sub, sat)) + B - C. f}/(l f), where delta T(sub B(sub, sat)), is the difference of T(sub B(sub, sat,19)) and T(sub B(sub, sat,37)), alpha(mm/K) is the slope of SWE vs. brightness temperature difference at 19 and 37 GHz that would be obtained by ignoring the presence of atmosphere, delta(T(sub B)sub g)), for a homogeneous snow cover (which varies with grain size). The parameters A, B, and C, are determined primarily by atmospheric characteristics, and for a likely range of atmospheric conditions appear to be in the range of, respectively, 1.15-1.63, 0.69-2.84 K and 0.59-2.39 K. Ignoring atmospheric correction would introduce bias towards underestimation of SWE (and also, snow cover area and snow depth). Increasing cloud liquid water path (L) has the effect of increasing A, and ignoring this variation of A with L would have the impact of biasing the estimate of SWE (and snow extent). Such biasing is further exacerbated with increasing f, because of the appearance of term (l-f) in the denominator. The impact of ignoring the intercept parameters (B and C) would be noticeable at low values of SWE (appearing as a bias towards underestimation of SWE), which has been determined to be about 6 mm for average environmental conditions. The uncertainty in estimating SWE due to variations in the atmospheric characteristics is likely to be less than 15%, but could be up to 25% for non-vegetated snow-covered areas. Better estimates of SWE (and snow extent) would be obtained by adjusting the parameters of the above model to regional differences in the atmospheric characteristics. The biases in determining SWE arising due to variations in atmospheric conditions and due to changes in fractional forest cover are not independent, since they interact as {A/(l-f)}. The present calculations also show that improvement in determining snow cover area from the microwave data is likely to occur when these data are corrected for atmospheric effects, as demonstrated by a specific case study.

Choudhury, Bhaskar J.↗
NASA NTRS1987

Determination of vegetated fraction of surface from satellite measurements

One input to the ground hydrology component of general circulation models is the fraction of gridbox covered (i.e., shaded) by vegetation. The FV is needed in order to specify the partitioning of evaporation between vegetated and nonvegetated surfaces. Satellite data could provide global and seasonally varying specification of FV. In this work, FV is derived from Landsat data for a site in western Kenya; the accuracy of the estimate is evaluated and then compared to the accuracy requirements of a ground hydrology model. Results show that the accuracy of Landsat estimation of FV is + or - 5 percent and that transpiration, evaporation from bare soil and the seasonality of evapotranspiration are strongly dependent on FV.

Cary, Ernestine↗
NASA NTRS1987

Heat transfer to and from vegetated surfaces - An analytical method for the bulk exchange coefficients

The semianalytical model outlined in a previous study (Massman, 1987) to describe momentum exchange between the atmosphere and vegetated surfaces is extended to include the exchange of heat. The methods employed are based on one-dimensional turbulent diffusivities, and use analytical solutions to the steady-state diffusion equation. The model is used to assess the influence that the canopy foliage structure and density, the wind profile structure within the canopy, and the shelter factor can have upon the inverse surface Stanton number (kB exp -1), as well as to explore the consequences of introducing a scalar displacement height which can be different from the momentum displacement height. In general, the triangular foliage area density function gives results which agree more closely with observations than that for constant foliage area density. The intended application of this work is for parameterizing the bulk aerodynamic resistances for heat and momentum exchange for use within large-scale models of plant-atmosphere exchanges.

Massman, William J.↗
NASA NTRS2020

Acoustic space occupancy: Combining ecoacoustics and lidar to model biodiversity variation and detection bias across heterogeneous landscapes

There is global interest in quantifying changing biodiversity in human-modified landscapes. Ecoacoustics may offer a promising pathway for supporting multi-taxa monitoring, but its scalability has been hampered by the sonic complexity of biodiverse ecosystems and the imperfect detectability of animal-generated sounds. The acoustic signature of a habitat, or soundscape, contains information about multiple taxa and may circumvent species identification, but robust statistical technology for characterizing community-level attributes is lacking. Here, we present the Acoustic Space Occupancy Model, a flexible hierarchical framework designed to account for detection artifacts from acoustic surveys in order to model biologically relevant variation in acoustic space use among community assemblages. We illustrate its utility in a biologically and structurally diverse Amazon frontier forest landscape, a valuable test case for modeling biodiversity variation and acoustic attenuation from vegetation density. We use complementary airborne lidar data to capture aspects of 3D forest structure hypothesized to influence community composition and acoustic signal detection. Our novel analytic framework permitted us to model both the assembly and detectability of soundscapes using lidar-derived estimates of forest structure. Our empirical predictions were consistent with physical models of frequency-dependent attenuation, and we estimated that the probability of observing animal activity in the frequency channel most vulnerable to acoustic attenuation varied by over 60%, depending on vegetation density. There were also large differences in the biotic use of acoustic space predicted for intact and degraded forest habitats, with notable differences in the soundscape channels predominantly occupied by insects. This study advances the utility of ecoacoustics by providing a robust modeling framework for addressing detection bias from remote audio surveys while preserving the rich dimensionality of soundscape data, which may be critical for inferring biological patterns pertinent to multiple taxonomic groups in the tropics. Our methodology paves the way for greater integration of remotely sensed observations with high-throughput biodiversity data to help bring routine, multi-taxa monitoring to scale in dynamic and diverse landscapes.

Airborne lidar↗
DOE OSTI2024

Machine Learning Driven Sensitivity Analysis of E3SM Land Model Parameters for Wetland Methane Emissions

Methane (CH 4 ) is globally the second most critical greenhouse gas after carbon dioxide, contributing to 16%–25% of the observed atmospheric warming. Wetlands are the primary natural source of methane emissions globally. However, wetland methane emission estimates from biogeochemistry models contain considerable uncertainty. One of the main sources of this uncertainty arises from the numerous uncertain model parameters within various physical, biological, and chemical processes that influence methane production, oxidation, and transport. Sensitivity Analysis (SA) can help identify critical parameters for methane emission and achieve reduced biases and uncertainties in future projections. This study performs SA for 19 selected parameters responsible for critical biogeochemical processes in the methane module of the Energy Exascale Earth System Model (E3SM) land model (ELM). The impact of these parameters on various CH 4 fluxes is examined at 14 FLUXNET- CH 4 sites with diverse vegetation types. Given the extensive number of model simulations needed for global variance-based SA, we employ a machine learning (ML) algorithm to emulate the complex behavior of ELM methane biogeochemistry. We found that parameters linked to CH 4 production and diffusion generally present the highest sensitivities despite apparent seasonal variation. Comparing simulated emissions from perturbed parameter sets against FLUXNET-CH 4 observations revealed that better performances can be achieved at each site compared to the default parameter values. This presents a scope for further improving simulated emissions using parameter calibration with advanced optimization techniques.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Comparison of ground and satellite based measurements of the fraction of photosynthetically active radiation intercepted by tall-grass prairie

The fraction, of photosynthetically active radiation intercepted by vegetation, F(sub ipar) is an important parameter for modeling the interactions between the land-surface and atmosphere and for estimating vegetation biomass productivity. This study was; therefore, an integral part of FIFE. The specific purpose of this experiment was to find out how well definitive measurements of F(sub ipar) on the ground relate to near-ground and satellite based spectral reflectance measurements. Concurrent measurements of F(sub ipar) and ground, helicopter, and satellite based reflectance measurements were taken at thirteen tall-grass prairie sites within the FIFE experimental area. The sites were subjected to various combinations of burning and grazing managements. The ground and helicopter based reflectance measurements were taken on the same day or few days from the time of the overpass of LANDSAT and SPOT satellites. Ground-based reflectance measurements and sun photometer readings taken at the times of the satellite overpasses were used to correct for atmospheric attenuation. Hand-held radiometer spectral indices were strongly correlated with helicopter and satellite based values (r=0.94 for helicopter, 0.93 for LANDSAT Thematic Mapper, and 0.86 for SPOT). However, the ground, helicopter, and satellite based normalized difference spectral vegetation indices showed low sensitivity to changes in F(sub ipar). Reflectance measurements were only moderately well correlated with measurements of F(sub ipar) (r=0.82 for hand-held radiometer, 0.84 for helicopter measurements, and 0.75 for the LANDSAT Thematic Mapper and SPOT). Improved spectral indices which can compensate for site differences are needed in order to monitor F(sub ipar) more reliably.

Demetriades-Shah, T. H.↗
NASA NTRS1992

Comparison of ground and satellite based measurements of the fraction of photosynthetically active radiation intercepted by tall-grass prairie

The fraction of photosynthetically active radiation intercepted by vegetation, F(sub ipar) is an important parameter for modeling the interactions between the land-surface and atmosphere and for estimating vegetation biomass productivity. This study was, therefore, an integral part of FIFE. The specific purpose of this experiment was to find out how well definitive measurements of F(sub ipar) on the ground relate to near-ground and satellite based spectral reflectance measurements. Concurrent measurements of F(sub ipar) and ground, helicopter, and satellite based reflectance measurements were taken at thirteen tall-grass prairie sites within the FIFE experimental area. The sites were subjected to various combinations of burning and grazing managements. The ground and helicopter based reflectance measurements were taken on the same day or few days from the time of the overpass of LANDSAT and SPOT satellites. Ground-based reflectance measurements and sun photometer readings taken at the times of the satellite overpasses were used to correct for atmospheric attenuation. Hand-held radiometer spectral indices were strongly correlated with helicopter and satellite based values (r = 0.94 for helicopter, 0.93 for LANDSAT Thematic Mapper, and 0.86 for SPOT). However, the ground, helicopter, and satellite based normalized difference spectral vegetation indices showed low sensitivity to changes in F(sub ipar). Reflectance measurements were only moderately well correlated with measurements of F(sub ipar) (r = 0.82 for hand-held radiometer, 0.84 for helicopter measurements, and 0.75 for the LANDSAT Thematic Mapper and SPOT). Improved spectral indices which can compensate for site differences are needed in order to monitor F(sub ipar) more reliably.

Demetriades-Shah, T. H.↗
NASA NTRS1985

Understanding the Radiant Scattering Behavior of Vegetated Scenes

Knowledge of the physics of the scattering behavior of vegetation will ultimately serve the remote sensing and earth science community in many ways. For example, it will provide: (1) insight and guidance in developing new extraction techniques of canopy characteristics, (2) a basis for better interpretation of off-nadir satellite and aircraft data, (3) a basis for defining specifications of future earth observing sensor systems, and (4) a basis for defining important aspects of physical and biological processes of the plant system. The overall objective of the three-year study is to improve our fundamental understanding of the dynamics of directional scattering properties of vegetation canopies through analysis of field data and model simulation data. The specific objectives are to: (1) collect directional reflectance data covering the entire exitance hemisphere for several common vegetation canopies with various geometric structure (both homogeneous and row crop structures), (2) develop a scene radiation model with a general mathematical framework which will treat 3-D variability in heterogeneous scenes and account for 3-D radiant interactions within the scene, (3) conduct validations of the model on collected data sets, and (4) test and expand proposed physical scattering mechanisms involved in reflectance distribution dynamics by analyzing both field and modeling data.

Kimes, D. S.↗
NASA NTRS2002

Investigation of Aerodynamic and Radiometric Land Surface Temperatures

The surface temperature, T(sub s), of a land surface measured by a radiometer, T(sub s,r), and the temperature "felt" by the air, T(sub aero), often differ significantly and are difficult if not impossible to define rigorously. However, recent studies conducted by the principal investigators with several land surface models suggest that this problem can be largely resolved. The main goal of this project was to use model-based and empirical studies to improve understanding and reconcile the difference between T(sub s,r) and T(sub aero), while maintaining consistency within the models and with theory and data. The results from this effort have contributed progress towards the effective use of remotely sensed surface temperature measurements taken from an arbitrary view angle over a partial canopy cover for producing high quality sensible and latent heat flux estimates. In addition, we have developed parameterizations that are designed to improve the representation of the roughness length for heat in climate and mesoscale models. This not only provides improved representation of surface energy balance in such models, but should also facilitate the use of surface temperature measurements for validating or updating the surface temperature produced by SVATs (soil-vegetation-atmosphere schemes) in climate or mesoscale models.

Friedl, Mark↗