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DOE OSTI2026

Populus_trichocarpa_Breeding_Population_SNPs

These data are from the manuscript “Application of Genomic Prediction in a Populus trichocarpa Breeding Program”, by Brian J. Stanton, David Macaya-Sanz, Chanaka Roshan Abeyratne, David Kainer, Kathy Haiby, Austin Himes, Carlos Gantz, Gerald A. Tuskan, and Stephen P. DiFazio. The data are based on genome resequencing to approximately 10X depth on two collections of Populus trichocarpa trees from Oregon, Washington, California, and British Columbia. The first collection consists of 293 genets collected by Poplar Innovations LLC for a breeding program. The second collection consists of 961 trees collected for the purpose of genome-wide association studies. These genets were sequenced using short, paired-end Illumina sequence reads (Chhetri et al. 2019). Reads were aligned to the P. trichocarpa ′Stettler-14′ reference (Hofmeister et al. 2020), with minor modifications to correct mis-assemblies (Zhou et al. 2020), and variants were called as per methods described in (Abeyratne et al. 2023). Identified variants were filtered using GATK’s VariantFiltration tool (DePristo et al. 2011), with filter expression flag set to “AF < 0.01 || AF > 0.99 || QD < 10.0 || ExcessHet > 20.0 || FS > 10.0 || MQ < 58.0”. SNPs with severe departures from Hardy−Weinberg expectations (exact-test p< 0.01) were also removed using vcftools --hwe flag (Danecek et al. 2011), resulting in 15,627,211 bi-allelic SNPs. The data included here consist of 141,903 high quality bi-allelic genome-wide SNPs obtained by further filtering the original SNP dataset using vcftools with flags --maf 0.05, --max-maf 0.95, --max-missing 0.95, --min-meanDP 10.75, --max-meanDP 43.00, --thin 2000. Collectively, these filtering parameters removed SNPs with 1) a minor allele frequency ≤ 0.05; 2) proportion of missing data for individual loci exceeding 5%; 3) sequencing depth more than 2X mean-depth or less than 0.5X mean-depth; or 4) a distance of

09 BIOMASS FUELS↗

DOE OSTI2020

Performance Criteria for Capture and/or Immobilization Technologies (Revision 1)

The capture and subsequent immobilization of regulated volatile radionuclides from the off-gas streams of a used nuclear fuel (UNF) reprocessing facility has been a topic of substantial research interest for the US Department of Energy and its international counterparts. Removal of specific radionuclides from the plant effluent streams before discharge to the environment is required to meet regulations set forth by the US Environmental Protection Agency. Upon removal, the radionuclides, as well as associated sorbents that cannot be regenerated in a cost-effective manner, are destined for conversion to a waste form. Research in separation and capture methodologies has included a wide range of technology types, and studies of waste forms are correspondingly diverse. In considering the future development and implementation of both sorbents and waste forms, it is necessary to identify benchmark measures of performance to objectively evaluate each sorbent system or waste form. Sets of performance criteria and associated metrics have been developed for sorbent and waste form evaluation. These criteria address physical, radiological, and chemical characteristics, technical practicality, technical maturity, cost, and, for sorbents, system performance. The criteria and metrics appear to be robust and should be applicable despite the eventual waste classification (as either high- or low-level waste). They are flexible enough to address both aqueous reprocessing and electrochemical reprocessing of UNF. These criteria sets can serve as tools to evaluate performance at multiple stages within the development process, and in this revision (Revision 1) they have been used to assess technologies relating to krypton/xenon separations and iodine capture from off-gas streams arising from UNF reprocessing. Assessment of krypton/xenon separations using engineered forms of two zeolite minerals (silver mordenite and hydrogen mordenite in a polyacrylonitrile-based binder [AgZ-PAN/HZ-PAN]) found that the zeolite-based separation is relatively advanced in its development, but several key issues require resolution. First, desorption processes for both krypton and xenon require refinement to provide an understanding of the product purity that can be achieved. Second, adsorption rate data is needed in order to calculate the bed depth required for effective separation. Finally, it is strongly recommended that a technical review of krypton/xenon separation by AgZ-PAN/HZ-PAN be performed to synergize available data and assess the cost savings and operational benefits that may be realized from implementation of this technology. Assessment of metal organic frameworks (MOFs) for their use in the separation of krypton/xenon found that the ideal separation would be performed using a single-column system with a MOF selective for krypton over xenon. A robust research effort should work to identify a krypton-selective MOF designed to operate at temperatures of approximately 0°C or higher, which could be preferred over cryogenic krypton/xenon capture for used fuel reprocessing off-gas streams. In the case of the CaSDB-MOF (the most well-understood xenon sorbent to date), two issues are judged of high importance. First, xenon breakthrough capacity for the CaSDB-MOF in prototypical conditions should be determined. Preliminary research indicates that breakthrough may be near immediate, presenting a substantial obstacle in separative system design. Second, development of desorption methodology should be performed to determine regeneration time, energy requirements, and the product stream composition. Silver-based sorbents (AgZ and AgAero) for use in iodine capture from the dissolver off-gas were evaluated against the established criteria. These sorbents are significantly better understood for this application as a result of research efforts over the past decade. The potential implementation of AgAero at a large scale is hindered by its physical degradation by components of the dissolver off-gas stream. Less is known about the adsorption of iodine by these sorbents from other off-gas streams in the plant. Initial experimental efforts have been closely coordinated in an effort to understand organic iodine (such as would be found in the vessel off-gas) adsorption by AgZ and AgAero. Future work should expand this experimental program, and analysis of other reprocessing facility off-gas streams such as the vitrification off-gas stream should be conducted to better understand other potential applications for iodine sorbents. A review of iodine waste form development shows that this area is diverse and that multiple promising waste forms have been identified for the immobilization of radioactive iodine. Efforts related to the direct conversion of iodine sorbents (including AgZ and AgAero) should be continued because of the advantages of direct conversion in a waste management strategy and other sorbents should continue to be advanced as merited.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1998

RXTE Observation of Cygnus X-1 Spectral Analysis

We present the results of the analysis of the broad-band spectrum of Cygnus X-1 from 3.0 to 200 keV, using data from a 10 ksec observation by the Rossi X-ray Timing Explorer. Although the spectrum can be well described phenomenologically by an exponentially cut-off power law (photon index Gamma = 1.45+0.01 -0.02 , e-folding energy e(sub f) = 162+9 -8 keV, plus a deviation from a power law that formally can be modeled as a thermal blackbody, with temperature kT(sub BB) = 1.2 +0.0 -0.1 keV), the inclusion of a reflection component does not improve the fit. As a physical description of this system, we apply the accretion disc corona (ADC) models. A slab-geometry ADC model is unable to describe the data. However, a spherical corona, with a total optical depth tau- = 1.6 + or - 0.1 and an average temperature kTc = 87 + or - 5 keV, surrounded by an exterior cold disc, does provide a good description of the data (X red (exp 2) = 1.55). These models deviate from the data bv up to 7% in the 5-10 keV range. However, considering how successfully the spherical corona reproduces the 10-200 keV data, such "photon-starved" coronal geometries seem very promising for explaining the accretion processes of Cygnus X-1.

Dove, J. B.↗

DOE OSTI2022

Short GRB Host Galaxies. I. Photometric and Spectroscopic Catalogs, Host Associations, and Galactocentric Offsets

We present a comprehensive optical and near-infrared census of the fields of 90 short gamma-ray bursts (GRBs) discovered in 2005–2021, constituting all short GRBs for which host galaxy associations are feasible (≈60% of the total Swift short GRB population). We contribute 274 new multi-band imaging observations across 58 distinct GRBs and 26 spectra of their host galaxies. Supplemented by literature and archival survey data, the catalog contains 542 photometric and 42 spectroscopic data sets. The photometric catalog reaches 3σ depths of ≳24–27 mag and ≳23–26 mag for the optical and near-infrared bands, respectively. We identify host galaxies for 84 bursts, in which the most robust associations make up 56% (50/90) of events, while only a small fraction, 6.7%, have inconclusive host associations. Based on new spectroscopy, we determine 18 host spectroscopic redshifts with a range of z ≈ 0.15–1.5 and find that ≈23%–41% of Swift short GRBs originate from z > 1. We also present the galactocentric offset catalog for 84 short GRBs. Taking into account the large range of individual measurement uncertainties, we find a median of projected offset of ≈7.7 kpc, for which the bursts with the most robust associations have a smaller median of ≈4.8 kpc. Our catalog captures more high-redshift and low-luminosity hosts, and more highly offset bursts than previously found, thereby diversifying the population of known short GRB hosts and properties. In terms of locations and host luminosities, the populations of short GRBs with and without detectable extended emission are statistically indistinguishable. This suggests that they arise from the same progenitors, or from multiple progenitors, which form and evolve in similar environments. All of the data products are available on the Broadband Repository for Investigating Gamma-Ray Burst Host Traits website.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1975

Extremal inversion of lunar travel time data

The tau method, developed by Bessonova et al. (1974), of inversion of travel times is applied to lunar P-wave travel time data to find limits on the velocity structure of the moon. Tau is the singular solution to the Clairaut equation. Models with low-velocity zones, with low-velocity zones at differing depths, and without low-velocity zones, were found to be consistent with data and within the determined limits. Models with and without a discontinuity at about 25-km depth have been found which agree with all travel time data to within two standard deviations. In other words, the existence of the discontinuity and its size and location have not been uniquely resolved. Models with low-velocity channels are also possible.

Burkhard, N.↗

NASA NTRS2017

Answering the Call for Model-Relevant Observations of Aerosols and Clouds

Redemann, J.↗

NASA NTRS2017

Use of A-Train Aerosol Observations to Constrain Direct Aerosol Radiative Effects (DARE) Comparisons with Aerocom Models and Uncertainty Assessments

We describe a technique for combining multiple A-Train aerosol data sets, namely MODIS spectral AOD (aerosol optical depth), OMI AAOD (absorption aerosol optical depth) and CALIOP aerosol backscatter retrievals (hereafter referred to as MOC retrievals) to estimate full spectral sets of aerosol radiative properties, and ultimately to calculate the 3-D distribution of direct aerosol radiative effects (DARE). We present MOC results using almost two years of data collected in 2007 and 2008, and show comparisons of the aerosol radiative property estimates to collocated AERONET retrievals. Use of the MODIS Collection 6 AOD data derived with the dark target and deep blue algorithms has extended the coverage of the MOC retrievals towards higher latitudes. The MOC aerosol retrievals agree better with AERONET in terms of the single scattering albedo (ssa) at 441 nm than ssa calculated from OMI and MODIS data alone, indicating that CALIOP aerosol backscatter data contains information on aerosol absorption. We compare the spatio-temporal distribution of the MOC retrievals and MOC-based calculations of seasonal clear-sky DARE to values derived from four models that participated in the Phase II AeroCom model intercomparison initiative. Overall, the MOC-based calculations of clear-sky DARE at TOA over land are smaller (less negative) than previous model or observational estimates due to the inclusion of more absorbing aerosol retrievals over brighter surfaces, not previously available for observationally-based estimates of DARE. MOC-based DARE estimates at the surface over land and total (land and ocean) DARE estimates at TOA are in between previous model and observational results. Comparisons of seasonal aerosol property to AeroCom Phase II results show generally good agreement best agreement with forcing results at TOA is found with GMI-MerraV3. We discuss sampling issues that affect the comparisons and the major challenges in extending our clear-sky DARE results to all-sky conditions. We present estimates of clear-sky and all-sky DARE and show uncertainties that stem from the assumptions in the spatial extrapolation and accuracy of aerosol and cloud properties, in the diurnal evolution of these properties, and in the radiative transfer calculations.

aerosol↗

DOE OSTI2021

HAIMOS Ensemble Forecasts for Intra-day and Day- Ahead GHI, DNI and Ramps

The objective of this research is to develop a hybrid physics-based/data-driven forecast model to improve direct normal and global horizontal irradiance (DNI and GHI) prediction for horizons ranging from 1 to 72 hours. Project objectives also address key gaps in state-of-the-art solar forecasting: accurate probabilistic solar forecasts and the forecasting of large irradiance ramps (ramp onset and magnitude). The proposed model ensembles Numerical Weather Prediction (NWP) forecasts, determinist physics-based algorithms, and new-generation cloud cover products (high-resolution rapid refresh satellite images and Large Eddy Simulations). The result is the Hybrid Adaptive Input Model Objective Selection (HAIMOS) ensemble model. HAIMOS blends state of the art machine learning methodologies with physics-based models for cloud cover and cloud optical depth forecasts. The technical activities followed a two-pronged strategy. First, the preprocessing of data, the selection of inputs to the nonlinear approximators, the type of approximator and objective functions, and post-processing ensembling techniques included in HAIMOS were all optimized adaptively to find the best model for a specific goal (reduce DNI/GHI forecast error, improve the prediction of ramp onset, etc.). Second, a large effort was put in improving cloud identification and the forecast of cloud cover and cloud optical depth. To this end, new-generation cloud parametrization products were developed in this work. These include improved algorithms to assist in cloud identification, cloud classification and cloud parametrization from satellite images – three key factors in the accuracy of 1 to 6-hours irradiance forecasts and prediction of ramp onset. Furthermore, we also included cloud information extracted from high resolution rapid refresh satellite images (GOES-16) and Large Eddy Simulations (LES). LES was used to model the atmosphere in detail over locations of interest and produce cloud optical depth forecasts. Once these data streams were validated, they were used as input data to the HAIMOS forecast. The model was developed using data from several climatologically distinct locations with potential for high solar penetration. In the last year of the project, we conducted a validation campaign according to the guidelines stipulated by the Topic Area 1 project as described in the FOA. This effort brings, for the first time, proven machine-learning methodologies for generating state-of-the-art solar forecasts interweaved with detailed physics-based models for cloud detection, and cloud optical depth forecasts. HAIMOS will generate accurate irradiance probabilistic forecast to assist in reducing solar generation prediction error. Globally optimized solar forecast models are more likely to impact solar energy stakeholders. The goal of this project was to increase the state-of-the-art forecast skill from their present values of 10 to 35%. At the end of the project, we achieved between 30% and 50% forecast skill across a wide range of horizons for both GHI and DNI.

14 SOLAR ENERGY↗

NASA NTRS2022

TESS Revisits WASP-12: Updated Orbital Decay Rate and Constraints on Atmospheric Variability

After observing WASP-12 in the second year of the primary mission, the Transiting Exoplanet Survey Satellite (TESS) revisited the system in late 2021 during its extended mission. In this paper, we incorporate the new TESS photometry into a reanalysis of the transits, secondary eclipses, and phase curve. We also present a new Ks-band occultation observation of WASP-12b obtained with the Palomar/Wide-field Infrared Camera instrument. The latest TESS photometry spans three consecutive months, quadrupling the total length of the TESS WASP-12 light curve and extending the overall time baseline by almost two years. Based on the full set of available transit and occultation timings, we find that the orbital period is shrinking at a rate of −29.81 ± 0.94 ms yr−1. The additional data also increase the measurement precision of the transit depth, orbital parameters, and phase-curve amplitudes. We obtain a secondary eclipse depth of 466 ± 35 ppm, a 2σ upper limit on the nightside brightness of 70 ppm, and a marginal 6°.2 ± 2°.8 eastward offset between the dayside hotspot and the substellar point. The voluminous TESS data set allows us to assess the level of atmospheric variability on timescales of days, months, and years. We do not detect any statistically significant modulations in the secondary eclipse depth or day–night brightness contrast. Likewise, our measured Ks-band occultation depth of 2810 ± 390 ppm is consistent with most ∼2.2 μm observations in the literature.

Ian Wong↗

NASA NTRS2014

Application of spectral analysis techniques in the intercomparison of aerosol data: Part III. Using combined PCA to compare spatiotemporal variability of MODIS, MISR, and OMI aerosol optical depth

Explore the source record for details and available documents.

Jing Li↗

DOE OSTI2022

Root system architecture and environmental flux analysis in mature crops using 3D root mesocosms

Current methods of root sampling typically only obtain small or incomplete sections of root systems and do not capture their true complexity. To facilitate the visualization and analysis of full-sized plant root systems in 3-dimensions, we developed customized mesocosm growth containers. While highly scalable, the design presented here uses an internal volume of 45 ft 3 (1.27 m 3 ), suitable for large crop and bioenergy grass root systems to grow largely unconstrained. Furthermore, they allow for the excavation and preservation of 3-dimensional root system architecture (RSA), and facilitate the collection of time-resolved subterranean environmental data. Sensor arrays monitoring matric potential, temperature and CO 2 levels are buried in a grid formation at various depths to assess environmental fluxes at regular intervals. Methods of 3D data visualization of fluxes were developed to allow for comparison with root system architectural traits. Following harvest, the recovered root system can be digitally reconstructed in 3D through photogrammetry, which is an inexpensive method requiring only an appropriate studio space and a digital camera. We developed a pipeline to extract features from the 3D point clouds, or from derived skeletons that include point cloud voxel number as a proxy for biomass, total root system length, volume, depth, convex hull volume and solidity as a function of depth. Ground-truthing these features with biomass measurements from manually dissected root systems showed a high correlation. We evaluated switchgrass, maize, and sorghum root systems to highlight the capability for species wide comparisons. We focused on two switchgrass ecotypes, upland (VS16) and lowland (WBC3), in identical environments to demonstrate widely different root system architectures that may be indicative of core differences in their rhizoeconomic foraging strategies. Finally, we imposed a strong physiological water stress and manipulated the growth medium to demonstrate whole root system plasticity in response to environmental stimuli. Hence, these new “3D Root Mesocosms” and accompanying computational analysis provides a new paradigm for study of mature crop systems and the environmental fluxes that shape them.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2002

Hawaii Ocean Mixing Experiment: Program Summary

It is becoming apparent that insufficient mixing occurs in the pelagic ocean to maintain the large scale thermohaline circulation. Observed mixing rates fall a factor of ten short of classical indices such as Munk's "Abyssal Recipe." The growing suspicion is that most of the mixing in the sea occurs near topography. Exciting recent observations by Polzin et al., among others, fuel this speculation. If topographic mixing is indeed important, it must be acknowledged that its geographic distribution, both laterally and vertically, is presently unknown. The vertical distribution of mixing plays a critical role in the Stommel Arons model of the ocean interior circulation. In recent numerical studies, Samelson demonstrates the extreme sensitivity of flow in the abyssal ocean to the spatial distribution of mixing. We propose to study the topographic mixing problem through an integrated program of modeling and observation. We focus on tidally forced mixing as the global energetics of this process have received (and are receiving) considerable study. Also, the well defined frequency of the forcing and the unique geometry of tidal scattering serve to focus the experiment design. The Hawaiian Ridge is selected as a study site. Strong interaction between the barotropic tide and the Ridge is known to take place. The goals of the Hawaiian Ocean Mixing Experiment (HOME) are to quantify the rate of tidal energy loss to mixing at the Ridge and to identify the mechanisms by which energy is lost and mixing generated. We are challenged to develop a sufficiently comprehensive picture that results can be generalized from Hawaii to the global ocean. To achieve these goals, investigators from five institutions have designed HOME, a program of historic data analysis, modeling and field observation. The Analysis and Modeling efforts support the design of the field experiments. As the program progresses, a global model of the barotropic (depth independent) tide, and two models of the baroclinic (depth varying) tide, all validated with near-Ridge data, will be applied, to reveal the mechanisms of tidal energy conversion along the Ridge, and allow spatial and temporal integration of the rate of conversion. Field experiments include a survey to identify "hot spots" of enhanced mixing and barotropic to baroclinic conversion, a Nearfield study identifying the dominant mechanisms responsible for topographic mixing, and a Farfield program which quantifies the barotropic energy flux convergence at the Ridge and the flux divergence associated with low mode baroclinic waves radiation. The difference is a measure of the tidal power available for mixing at the Ridge. Field work is planned from years 2000 through 2002, with analysis and modeling efforts extending through early 2006. If successful, HOME will yield an understanding of the dominant topographic mixing processes applicable throughout the global ocean. It will advance understanding of two central problems in ocean science, the maintenance of the abyssal stratification, and the dissipation of the tides. HOME data will be used to improve the parameterization of dissipation in models which presently assimilate TOPEX-POSEIDON observations. The improved understanding of the dynamics and spatial distribution of mixing processes will benefit future long-term programs such as CLIVAR.

Ray, Richard D.↗

DOE OSTI2024

Soil carbon, nitrogen, and ice content data (2014-2018) at Happy Valley and Sagwon Hills in Northern Alaska, United States

This dataset contains three data files from soil data collected by sampling soil cores and pits across a toposequence on two hillslopes in permafrost affected soils in Northern Alaska, USA. Soil cores and profiles were excavated to 3m or until auger refusal. Samples were collected by genetic soil horizons for laboratory analysis and organized into complete soil profiles ordered depth. Soil carbon, nitrogen, and ice stocks (stocks_by_core.csv) were calculated from the core dataset . Data for mean values by depth increments (20,50,100,150,200 cm) of total soc, total nitrogen, bulk density, and ice content were determined and made available in this dataset (soc-tn-bd-ice-slab_tables.csv). Stocks by site are included in a separate file (stocks_by_site.csv). Each of these three files also has an associated data dictionary file (stocks_by_core_dd.csv, soc-tn-bd-ice-slab_tables_dd.csv, stocks_by_site_dd.csv). Finally, an FLMD file is also included (FLMD_Happy_Valley_Sagwon.csv).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1999

Correlations Between Topex Altimeter and Temperature Profile Data in the Equatorial Pacific

Observations of sea-surface heights from satellite altimeters have been a major contributor to monitoring the evolution of the recent major El Nino event. Assimilating altimeter data directly into numerical models only takes advantage of the surface signature provided by the data. However, that surface signature is usually indicative of processes occurring at depth, especially in the equatorial Pacific. In order for assimilation schemes to make maximum use of surface data, it is helpful to have knowledge of how to best extend that data in the vertical to account for that variability. Toward that end, the vertical correlation structure between satellite-observed sea-surface heights and in situ temperature measurements is examined using TOPEX altimeter and TOGA TAO profile data for the period 1993-1998. This time period includes several states of the tropical Pacific, including a perturbed state from 1993-1994, a quiescent state encompassing 1995-1996, and the major ENSO event of 1997-1998. Analyses for each of these periods, as well as the total period will be presented. In addition to analyses at specific depth levels, analyses for particular density surfaces will also be presented.

Adamec, David↗

DOE OSTI2022

Fast decay of classification error in variational quantum circuits

Variational quantum circuits (VQCs) have shown great potential in near-term applications. However, the discriminative power of a VQC, in connection to its circuit architecture and depth, is not understood. To unleash the genuine discriminative power of a VQC, we propose a VQC system with the optimal classical post-processing—maximum-likelihood estimation on measuring all VQC output qubits. Via extensive numerical simulations, we find that the error of VQC quantum data classification typically decays exponentially with the circuit depth, when the VQC architecture is extensive—the number of gates does not shrink with the circuit depth. This fast error suppression ends at the saturation towards the ultimate Helstrom limit of quantum state discrimination. On the other hand, non-extensive VQCs such as quantum convolutional neural networks are sub-optimal and fail to achieve the Helstrom limit, demonstrating a trade-off between ansatz complexity and classification performance in general. To achieve the best performance for a given VQC, the optimal classical post-processing is crucial even for a binary classification problem. To simplify VQCs for near-term implementations, we find that utilizing the symmetry of the input properly can improve the performance, while oversimplification can lead to degradation.

Zhang, Bingzhi↗

DOE OSTI2023

2016 Floodplain Geochemistry from the East River Watershed, Colorado

This dataset includes groundwater geochemistry data from floodplain piezometers collected as a part of the Watershed Function Scientific Focus Area (SFA) located in the Upper Colorado River Basin. The data were collected in order to investigate the role of hyporheic exchange and other river corridor processes on riverine export of solutes. Floodplain piezometers installed in several meanders (Meander C, Meander D, and Meander O) in the vicinity of the Pumphouse were sampled at several dates in 2016. Data includes in-field measurements (pH, electrical conductivity, oxidation reduction potential, dissolved oxygen, dissolved Fe(II), dissolved sulfide, and groundwater level) along with laboratory measurements (dissolved inorganic carbon, dissolved organic carbon, metals and major cations). Five files are included in this dataset, including: sample locations and depths in a csv file (metadata.csv), aqueous geochemistry data in a csv file, analytical detection limits in a csv file, a file-level metadata (flmd.csv) file, and a data dictionary (dd.csv) file. Data that was below the detection limit is reported as one half of the detection limit and missing data is listed as "-9999".

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1977

Comparing soil boundaries delineated by digital analysis of multispectral scanner data from high and low spatial resolution systems

The author has identified the following significant results. Computer-aided analysis techniques used with aircraft MSS data showed that the spatial resolution was sufficient to recognize each soil mapping unit of the test site. Some difficulties occurred where different soil series were intricately mixed, and this mixture showed as a separate spectral mapping unit, or where the difference between two soils depended on the depth of silty surface material. Analysis of LANDSAT data with computer-aided techniques showed that it was not possible to find spectrally homogeneous soil features of the seven soil series on the 40 ha test site on the digital display or on a picture print map. Cluster techniques could be used on an extended test area to group spectrally similar data points into cluster classes.

Kristof, S. J.↗

NASA NTRS2010

Modeling Fire Severity in Black Spruce Stands in the Alaskan Boreal Forest Using Spectral and Non-Spectral Geospatial Data

Biomass burning in the Alaskan interior is already a major disturbance and source of carbon emissions, and is likely to increase in response to the warming and drying predicted for the future climate. In addition to quantifying changes to the spatial and temporal patterns of burned areas, observing variations in severity is the key to studying the impact of changes to the fire regime on carbon cycling, energy budgets, and post-fire succession. Remote sensing indices of fire severity have not consistently been well-correlated with in situ observations of important severity characteristics in Alaskan black spruce stands, including depth of burning of the surface organic layer. The incorporation of ancillary data such as in situ observations and GIS layers with spectral data from Landsat TM/ETM+ greatly improved efforts to map the reduction of the organic layer in burned black spruce stands. Using a regression tree approach, the R2 of the organic layer depth reduction models was 0.60 and 0.55 (pb0.01) for relative and absolute depth reduction, respectively. All of the independent variables used by the regression tree to estimate burn depth can be obtained independently of field observations. Implementation of a gradient boosting algorithm improved the R2 to 0.80 and 0.79 (pb0.01) for absolute and relative organic layer depth reduction, respectively. Independent variables used in the regression tree model of burn depth included topographic position, remote sensing indices related to soil and vegetation characteristics, timing of the fire event, and meteorological data. Post-fire organic layer depth characteristics are determined for a large (N200,000 ha) fire to identify areas that are potentially vulnerable to a shift in post-fire succession. This application showed that 12% of this fire event experienced fire severe enough to support a change in post-fire succession. We conclude that non-parametric models and ancillary data are useful in the modeling of the surface organic layer fire depth. Because quantitative differences in post-fire surface characteristics do not directly influence spectral properties, these modeling techniques provide better information than the use of remote sensing data alone.

Barrett, K.↗