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At least 199 records · Page 11

Spatially-Explicit Monitoring of Crop Photosynthetic Capacity Through the Use of Space-Based Chlorophyll Fluorescence Data

Plant functional traits such as photosynthetic capacity are critical parameters for terrestrial biosphere models. However, their spatial and temporal characteristics are still poorly represented. In this study, we used satellite observations of sun-induced fluorescence (SIF) to estimate top-of-canopy photosynthetic capacity (maximum carboxylation rate, V(sub cmax) at a reference temperature of 25 deg C) for crops, which was in turn utilized to simulate regional gross primary production (GPP). We first estimate the key parameter, V(sub cmax), in the widely-used FvCB photosynthesis model using field measurements of CO2 and water fluxes during 2007-2012 at seven crop eddy covariance flux sites over the US Corn Belt. The results showed that satellite far-red SIF retrievals have a stronger link to V(sub cmax) at the seasonal scale (R(squared)=0.70 for C4 and R(squared)=0.63 for C3 crop) as compared with widely-used vegetation indices. We calibrate an empirical model linking V(sub cmax) with SIF that was used to estimate spatially and temporally varying crop V(sub cmax) for the US Corn Belt region. The resulting V(sub cmax) maps are used together with meteorological data from MERRA reanalysis data and vegetation structural parameters derived from the satellite- based spectral reflectance data to constrain the Soil-Canopy Observation of Photosynthesis and Energy (SCOPE) balance model in order to estimate regional crop GPP. Our results show a substantial improvement in the seasonal and spatial patterns of cropland GPP when compared with crop yield inventory data. The evaluation with tall tower atmospheric CO2 measurements further supports our estimation of spatiotemporal V(sub cmax) from space-borne SIF. Considering that SIF has a direct link to photosynthetic activity, our findings highlight the potential to infer regional V(sub cmax) using remotely sensed SIF data and to use this information for a better quantification of regional cropland carbon cycles.

Drought↗

Enabling Communities in the Use and Application of NASA's Earth Science Data and Information Products: Interactive Webinars that Work

The vast active archives of NASA's Earth science data reflect the agency's ongoing commitment to producing the highest quality data, services and tools intended for a myriad of science and application uses worldwide. These data span the whole of Earth science domains, and most have direct uses in societal applications. As many internet-based tools mature they enable NASA to increase the availability to and, most importantly, the uses of these disparate data types. This poster/paper highlights one particularly effective tool the NASA Earth Science Data and Information System (ESDIS) Project is utilizing to increase our user communities' understanding of these data, services and tools and their varied uses. Webinars, or video-based, on-line, interactive discussions and presentations have become a staple for exchanging information via the internet. The NASA ESDIS Project is using this platform to create a rich, highly-available, source of cutting-edge insights into the uses of Earth science data and applications. As evidence, we present a representative sample of the webinar offerings created by ESDIS beginning in 2013.

Lindsay, Francis E.↗

Post senescent grass canopy remote sensing

Analysis of in situ collected spectral reflectance data from a dormant or senescent grass canopy showed a direct relationship existed between spectral reflectance and biomass for the 0.50-0.80 micron spectral region. The data, collected four weeks after the end of the growing season, indicated that post senescent remote sensing of grass canopy biomass is possible and helps to elucidate the spectral contribution of recently dead vegetation in mixed live/dead canopy situations.

Tucker, C. J.↗

The vertical profile of radar reflectivity of convective cells: A strong indicator of storm intensity and lightning probability?

Reflectivity data from Doppler radars are used to construct vertical profiles of radar reflectivity (VPRR) of convective cells in mesoscale convective systems (MCSs) in three different environmental regimes. The National Center for Atmospheric Research CP-3 and CP-4 radars are used to calculate median VPRR for MCSs in the Oklahoma-Kansas Preliminary Regional Experiment for STORM-Central in 1985. The National Oceanic and Atmospheric Administration-Tropical Ocean Global Atmosphere radar in Darwin, Australia, is used to calculate VPRR for MCSs observed both in oceanic, monsoon regimes and in continental, break period regimes during the wet seasons of 1987/88 and 1988/89. The midlatitude and tropical continental VPRRs both exhibit maximum reflectivity somewhat above the surface and have a gradual decrease in reflectivity with height above the freezing level. In sharp contrast, the tropical oceanic profile has a maximum reflectivity at the lowest level and a very rapid decrease in reflectivity with height beginning just above the freezing level. The tropical oceanic profile in the Darwin area is almost the same shape as that for two other tropical oceanic regimes, leading to the conclustion that it is characteristic. The absolute values of reflectivity in the 0 to 20 C range are compared with values in the literature thought to represent a threshold for rapid storm electrification leading to lightning, about 40 dBZ at -10 C. The large negative vertical gradient of reflectivity in this temperature range for oceanic storms is hypothesized to be a direct result of the characteristically weaker vertical velocities observed in MCSs over tropical oceans. It is proposed, as a necessary condition for rapid electrification, that a convective cell must have its updraft speed exceed some threshold value. Based upon field program data, a tentative estimate for the magnitude of this threshold is 6-7 m/s for mean speed and 10-12 m/s for peak speed.

Zipser, Edward J.↗

BOREAS TE-4 Gas Exchange Data from Boreal Tree Species

The BOREAS TE-4 team collected steady-state gas exchange and reflectance data from several species in the BOREAS SSA during 1994 and in the NSA during 1996. Measurements of light, CO2, temperature, and humidity response curves were made by the BOREAS TE-4 team during the summers of 1994 and 1996 using intact attached leaves of boreal forest species located in the BOREAS SSA and NSA. These measurements were conducted to calibrate models used to predict photosynthesis, stomatal conductance, and leaf respiration. The 1994 and 1996 data can be used to construct plots of response functions or for parameterizing models. Parameter values are suitable for application in SiB2 (Sellers et al., 1996) or the leaf model of Collatz et al. (1991), and programs can be obtained from the investigators. The data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗

Characterization of Venera 15/16 Geologic Units from Pioneer Venus Reflectivity and Roughness Data

Geologic units have been defined for the surface of Venus from Venera 15/16 image data. A characterization of these geologic units is carried out using information on surface properties derived from Pioneer Venus (PV) reflectivity and rms slope data. The geologic context provided by Venera 15/16 units allows additional, more specific interpretations of surface radar properties to be made. Characterization of Venera units results in the definition of four groups of Venera units: (1) smooth rocky units, 2) rough rocky units, (3) rough high dielectric units, and (4) diffusely scattering units. On the basis of correlations of surface morphology to spatial and statistical distributions in rms slope and reflectivity data, we test models for the origin of the surface properties of some units. We conclude that plains and tectonic units can be contrasted in terms of the average roughness of the surface and that tectonic deformation appears to roughen the surface at 0.5- to 10-m and 5- to 50-cm scales. This tectonic weathering process appears to dominate the erosional regime of Venus. Unlike Earth or Mars, production and transport of soils dominates only a small portion (less than or equal to 5%) of the surface. Some of the Venera units display distinctive spatial and statistical distributions of PV radar data. In particular, apparent low reflectivity in the tesserae appears to be caused by small (5-50 cm) rock fragments on the surface which cause diffuse scattering at Pioneer Venus wavelengths. Analysis of models for the formation of these fragments suggests that they are due to the pervasive deformation undergone by the tesserae. Finally, aspects of this study have been used to extend results of Venera image data analysis southward of 30 deg. N lat, resulting in it prediction of the distribution of tessera. Such results can aid in Magellan investigations.

Bindschadler, D. L.↗

Autocorrelation and Multifractal Detrended Fluctuation Analyses Reveal Superdiffusive Mass Transport in Solvent-Filled Nanoporous Media

Fluorescence fluctuation spectroscopy experiments were conducted to better understand the complex mass transport dynamics of organic molecules in liquid-filled nanoporous media. Anodic aluminum oxide (AAO) membranes incorporating 10 and 20 nm diameter cylindrical pores were employed as model materials. Nile red (NR) dye was used as a fluorescent tracer. The dye was dissolved separately in ethanol and toluene at a concentration of 20 nM and used to fill the membrane nanopores. Confocal fluorescence microscopy was employed to capture photon intensity time series data reflecting apparent diffusion of the dye within the pores. Autocorrelation of these data revealed that NR diffusion within the membranes occurred over a broad range of time scales. The autocorrelation decays were fit to a model for one-dimensional diffusion incorporating both fast and slow components having apparent diffusion coefficients, D f and D s , differing by a factor of ∼100. The fast mechanism was attributed to hindered bulk-like diffusion in the central pore cavity, while slow diffusion likely involved absorption of the dye to the pore surfaces. Unfortunately, important evidence of diffusion anomalies is lost in the broad autocorrelation decays obtained. The method of multifractal detrended fluctuation analysis (MF-DFA) was applied to the same data as a means to overcome this limitation. MF-DFA revealed that time series acquired from within the nanopores were multifractal and exhibited evidence of anomalous superdiffusion, likely resulting from the participation of a desorption-mediated diffusion mechanism. Monte Carlo simulations of time series modeling desorption-mediated diffusion in cylindrical nanopores provided support for this assignment. Here, the new knowledge gained affords an improved understanding of hydrocarbon dynamics within nanoporous oil and gas shales.

Diffusion↗

Autonomous Tuning and Charge-State Detection of Gate-Defined Quantum Dots

Defining quantum dots in semiconductor-based heterostructures is an essential step in initializing solid-state qubits. With growing device complexity and increasing number of functional devices required for measurements, a manual approach to finding suitable gate voltages to confine electrons electrostatically is impractical. Here, we implement a two-stage device characterization and dot-tuning process, which first determines whether devices are functional and then attempts to tune the functional devices to the single or double quantum-dot regime. We show that automating well-established manual-tuning procedures and replacing the experimenter’s decisions by supervised machine learning is sufficient to tune double quantum dots in multiple devices without premeasured input or manual intervention. The quality of measurement results and charge states are assessed by four binary classifiers trained with experimental data, reflecting real device behavior. We compare and optimize eight models and different data preprocessing techniques for each of the classifiers to achieve reliable autonomous tuning, an essential step towards scalable quantum systems in quantum-dot-based qubit architectures.

Darulova, J↗

Leaf structural and chemical traits, and vegetation temperature and height, Seward Peninsula, Alaska, 2019.

Leaf nitrogen and carbon content, leaf water content (LWC) and leaf mass per area (LMA) of leaves, and vegetation height and temperatures sampled from locations on the Teller MM 27, Kougarok MM 64 and Kougarok MM 80 NGEE Arctic sites, Seward Peninsula, Alaska. These data were collected in support of ongoing NASA ABoVE AVIRIS data synthesis work. Samples were collected in July 2019 from 24 species. This data package includes leaf sample information and vegetation trait data (*.csv). Metadata files include data descriptions (_dd.csv) for tabular data and a key to species symbols used in data files. All included files are listed and described in NGA210_flmd.csv. See data package NGA212 "Full spectrum 350-2500 nm leaf and canopy spectral reflectance, Seward Peninsula, Alaska, 2019" for linked spectral reflectance data. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), 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↗

Soil spectra contributions to grass canopy spectral reflectance

The soil or background spectra contribution to grass canopy spectral reflectance for the 0.35 to 0.80 micron region was investigated using in situ collected spectral reflectance data. Regression analysis was used to estimate accurately the unexposed soil spectral reflectance and to quantify maxima and minima for soil-green vegetation reflection contrasts.

Tucker, C. J.↗

Real Time HABs Mapping Using NASA Glenn Hyperspectral Imager

The hyperspectral imaging system (HSI) developed by the NASA Glenn Research Center was used from 2015- 2017 to collect high spatial resolution data over Lake Erie and the Ohio River. Paired with a vicarious correction approach implemented by the Michigan Tech Research Institute, radiance data collected by the HSI system can be converted to high quality reflectance data which can be used to generate near-real time (within 24 hours) products for the monitoring of harmful algal blooms using existing algorithms. The vicarious correction method relies on imaging a spectrally constant target to normalize HSI data for atmospheric and instrument calibration signals. A large asphalt parking lot near the Western Basin of Lake Erie was spectrally characterized and was determined to be a suitable correction target. Due to the HSI deployment aboard an aircraft, it is able to provide unique insights into water quality conditions not offered by space-based solutions. Aircraft can operate under cloud cover and flight paths can be chosen and changed on-demand, allowing for far more flexibility than space-based platforms. The HSI is also able to collect data at a high spatial resolution (~1 m), allowing for the monitoring of small water bodies, the ability to detect small patches of surface scum, and the capability to monitor the proximity of blooms to targets of interest such as water intakes. With this new rapid turnaround time, airborne data can serve as a complementary monitoring tool to existing satellite platforms, targeting critical areas and responding to bloom events on-demand.

Reid W Sawtell↗

Real Time HABs Mapping Using NASA Glenn Hyperspectral Imager

The hyperspectral imaging system (HSI) developed by the NASA Glenn Research Center was used from 2015- 2017 to collect high spatial resolution data over Lake Erie and the Ohio River. Paired with a vicarious correction approach implemented by the Michigan Tech Research Institute, radiance data collected by the HSI system can be converted to high quality reflectance data which can be used to generate near-real time (within 24 hours) products for the monitoring of harmful algal blooms using existing algorithms. The vicarious correction method relies on imaging a spectrally constant target to normalize HSI data for atmospheric and instrument calibration signals. A large asphalt parking lot near the Western Basin of Lake Erie was spectrally characterized and was determined to be a suitable correction target. Due to the HSI deployment aboard an aircraft, it is able to provide unique insights into water quality conditions not offered by space-based solutions. Aircraft can operate under cloud cover and flight paths can be chosen and changed on-demand, allowing for far more flexibility than space-based platforms. The HSI is also able to collect data at a high spatial resolution (~1 m), allowing for the monitoring of small water bodies, the ability to detect small patches of surface scum, and the capability to monitor the proximity of blooms to targets of interest such as water intakes. With this new rapid turnaround time, airborne data can serve as a complementary monitoring tool to existing satellite platforms, targeting critical areas and responding to bloom events on-demand.

Reid W Sawtell↗

The Influence of Aqueous Dispersivity on Transport of Radiological Material at LANL MDA G - 20450

Aqueous dispersivity is a phenomenon by which a solute moving in groundwater mixes with water that does not contain the solute and becomes diluted. Solutes take paths of varying lengths through pore networks or experience slower velocities due to interactions with pore walls. Aqueous dispersivity leads to breakthrough curves with earlier arrival than expected in purely advective systems and persistent 'tails,' or late-arriving, dilute concentrations of the solute. Dispersivity can be longitudinal (in the direction of flow) or transverse (orthogonal to flow). LANL has disposed of radioactive material at Material Disposal Area (MDA) G since the late 1950's. Most of the disposed materials at MDA G are low-level waste (LLW), but other types of radioactive wastes are disposed or stored at the site. For example, there is a collection of remote-handled transuranic waste (RH-TRU) waste in 33 shafts, which were intended to be stored retrievably. Aqueous-phase radionuclides included in models of contaminant transport at MDA G are subject to dispersive processes in porous media of the vadose zone and saturated zone. To model dispersivity at MDA G probabilistically, we created site-specific distributions of aqueous dispersivity. First, we performed a comprehensive review of peer-reviewed publications, reports from other performance assessments of MDA G, and documentation from sites that were considered similar based on expert opinion, such as Yucca Mountain. Data were included from a wide range of sources, so that distributions developed based on the data reflect the current state of knowledge in properties of the subsurface environment. Data were grouped based on value type (e.g., determined via experiment or used in a different model), rock type, zone type (saturated or unsaturated), and site, and were weighted in the distributions according to their relevance to the site and zone type. We combined Monte Carlo simulation and bootstrapping techniques to produce approximate distributions of mean aqueous dispersivity. Distributions of dispersivity for saturated and unsaturated zone transport are differentiated by data weight and the length scales over which transport occurs. We find that underestimating or disregarding transverse dispersivity may lead to overstating simulated well capture in the saturated zone at MDA G. Neglecting transverse dispersivity is a common assumption due in part to use of one-dimensional transport models that do not consider solute spreading orthogonal to flow. Also, we find that variability in longitudinal dispersivity is associated with substantial travel time alterations in the MDA G unsaturated zone and in simulated contaminant breakthrough times at a downstream observation plane in the MDA G saturated zone. Finally, at large scales (>1000 m), a linear trend between the dispersivity coefficient and length over which transport occurs may overestimate the dispersivity coefficient. Future modeling work with application to solute spreading could include interacting advective and diffusive zones in the highly fractured basalt below MDA G. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Use of LANDSAT data to define soil boundaries in Carroll County, Missouri

Bands 4, 5 and 7 false color composite photographs were prepared using data from LANDSAT scenes acquired during April 1977 and April 1981 on computer compatible tapes, and these color composites were compared with band 7 black and white photographs prepared for the entire county. Delineations of soil boundaries at the soil association level were achieved using LANDSAT spectral reflectance data and slope maps for a portion of Carroll County, Missouri. Forty two spectral reflectance classes from April 1977 LANDSAT data were overlaid on digitized slope maps of nine USGS 7.5 minute series topographic quadrangle slope maps to achieve boundary delineations of the soil associations.

Davidson, S. E.↗

Spectral estimation of green leaf area index of oats

Green leaf area index (LAI) is a measure of vegetative growth and development and is frequently used as an input parameter in yield estimation and evapotranspiration models. Extensive destructive sampling is usually required to achieve accurate estimates of green LAI in natural situations. In this investigation, a statistical modeling approach was used to predict the green LAI of oats from bidirectional reflectance data collected with multiband radiometers. Stepwise multiple regression models based on two sets of spectral reflectance factors accounted for 73 percent and 65 percent of the variance in green LAI of oats. Exponential models of spectral data transformations of greenness, normalized difference, and near-infrared/red ratio accounted for more of the variance in green LAI than the multiple regression models.

Best, R. G.↗

Estimation of Crop Gross Primary Production (GPP): I. Impact of MODIS Observation Footprint and Impact of Vegetation BRDF Characteristics

Accurate estimation of gross primary production (GPP) is essential for carbon cycle and climate change studies. Three AmeriFlux crop sites of maize and soybean were selected for this study. Two of the sites were irrigated and the other one was rainfed. The normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), the green band chlorophyll index (CIgreen), and the green band wide dynamic range vegetation index (WDRVIgreen) were computed from the moderate resolution imaging spectroradiometer (MODIS) surface reflectance data. We examined the impacts of the MODIS observation footprint and the vegetation bidirectional reflectance distribution function (BRDF) on crop daily GPP estimation with the four spectral vegetation indices (VIs - NDVI, EVI, WDRVIgreen and CIgreen) where GPP was predicted with two linear models, with and without offset: GPP = a × VI × PAR and GPP = a × VI × PAR + b. Model performance was evaluated with coefficient of determination (R2), root mean square error (RMSE), and coefficient of variation (CV). The MODIS data were filtered into four categories and four experiments were conducted to assess the impacts. The first experiment included all observations. The second experiment only included observations with view zenith angle (VZA) ≤ 35◦ to constrain growth of the footprint size,which achieved a better grid cell match with the agricultural fields. The third experiment included only forward scatter observations with VZA ≤ 35◦. The fourth experiment included only backscatter observations with VZA ≤ 35◦. Overall, the EVI yielded the most consistently strong relationships to daily GPP under all examined conditions. The model GPP = a × VI × PAR + b had better performance than the model GPP = a × VI × PAR, and the offset was significant for most cases. Better performance was obtained for the irrigated field than its counterpart rainfed field. Comparison of experiment 2 vs. experiment 1 was used to examine the observation footprint impact whereas comparison of experiment 4 vs. experiment 3 was used to examine the BRDF impact. Changes in R2, RMSE,CV and changes in model coefficients "a" and "b" (experiment 2 vs. experiment 1; and experiment 4 vs. experiment 3) were indicators of the impacts. The second experiment produced better performance than the first experiment, increasing R2 (↑0.13) and reducing RMSE (↓0.68 g C m−2 d−1) and CV (↓9%). For each VI, the slope of GPP = a × VI × PAR in the second experiment for each crop type changed little while the slope and intercept of GPP = a × VI × PAR + b varied field by field. The CIgreen was least affected by the MODIS observation footprint in estimating crop daily GPP (R2, ↑0.08; RMSE, ↓0.42 g C m−2 d−1; and CV, ↓7%). Footprint most affected the NDVI (R2, ↑0.15; CV, ↓10%) and the EVI (RMSE, ↓0.84 g C m−2 d−1). The vegetation BRDF impact also caused variation of model performance and change of model coefficients. Significantly different slopes were obtained for forward vs. backscatter observations, especially for the CIgreen and the NDVI. Both the footprint impact and the BRDF impact varied with crop types, irrigation options, model options and VI options.

Chlorophyll↗

Venus global radar reflectivity and correlations with elevation

A geological analysis of the global radar reflectivity data for Venus is presented. The statistical and map pattern distribution of the radar reflectivity rho is first analyzed in the context of the porosity structure of the surface. Rho is then correlated with elevation in order to examine the degree of topographic control on material properties which could depend on PT-sensitive chemical weathering phenomena. Comparison of the rms slope alpha and rho correlations with elevation demonstrates that there are distinct topographic zones defined on the basis of the rho and alpha trends. Finally, hierarchical clustering analysis is applied to the global rho, alpha, and 100-km baseline regional slope data sets in order to define radar property-related subregions.

Garvin, J. B.↗

Comparison of methods for calibrating AVIRIS data to ground reflectance

We are comparing three basic methods of calibrating AVIRIS data to ground reflectance: (1) atmospheric radiative transfer models with the solar flux can be used to calibrate AVIRIS radiance data (Specific methods include the University of Colorado CSES ARP and ATREM algorithms); (2) Robert Green's modified MODTRAN and AVIRIS radiance model (This method is similar to 1 but differs in that the solar radiance is bypassed, so any errors in the solar flux are canceled, too); and (3) ground calibration using known sites in the AVIRIS scene. We are using 1992AVIRIS data over Cuprite, Nevada, and Blackhawk Island, Wisconsin, as our test scenes. Both these sites have extensive field measurements. The Cuprite site had a very clear atmosphere, thus path radiance was dominated by Rayleigh scattering with little or no flux beyond 1 micron. The Blackhawk site has more aerosols, with significant path radiance flux beyond 2 micron.

Clark, Roger N.↗