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DOE OSTI2020

LyaCoLoRe : synthetic datasets for current and future Lyman-α forest BAO surveys

The statistical power of Lyman-α forest Baryon Acoustic Oscillation (BAO) measurements is set to increase significantly in the coming years as new instruments such as the Dark Energy Spectroscopic Instrument deliver progressively more constraining data. Generating mock datasets for such measurements will be important for validating analysis pipelines and evaluating the effects of systematics. With such studies in mind, here we present LyaCoLoRe: a package for producing synthetic Lyman-α forest survey datasets for BAO analyses. LyaCoLoRe transforms initial Gaussian random field skewers into skewers of transmitted flux fraction via a number of fast approximations. In this work we explain the methods of producing mock datasets used in LyaCoLoRe, and then measure correlation functions on a suite of realisations of such data. We demonstrate that we are able to recover the correct BAO signal, as well as large-scale bias parameters similar to literature values. Finally, we briefly describe methods to add further astrophysical effects to our skewers — high column density systems and metal absorbers — which act as potential complications for BAO analyses.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Modelling the impact of quasar redshift errors on the full-shape analysis of correlations in the Lyman-α forest.

In preparation for the first cosmological measurements from the full shape of the Lyman-α (Lyα) forest from DESI, we must carefully model all relevant systematics that might bias our analysis. It was shown in Youles et al. (2022) that random quasar redshift errors produce a smoothing effect on the mean quasar continuum in the Lyα forest region. This, in turn, gives rise to spurious features in the Lyα autocorrelation and its cross-correlation with quasars. Using synthetic data sets based on the DESI survey, we confirm that the impact on BAO measurements is small, but that a bias is introduced to parameters which depend on the full shape of our correlations. We combine a model of this contamination in the cross-correlation (Youles et al. 2022) with a new model we introduce here for the auto-correlation. These are parametrised by 3 parameters, which, when included in a joint fit to both correlation functions, successfully eliminate any impact of redshift errors on our full-shape constraints. We also present a strategy for removing this contamination from real data, by removing ∼0.3% of correlating pairs.

cosmology↗

NASA NTRS1984

Discrete Random Media Techniques for Microwave Modeling of Vegetated Terrain

Microwave remote sensing of agricultural crops and forested regions is studied. Long term goals of the research involve modeling vegetation so that radar signatures can be used to infer the parameters which characterize the vegetation and underlying ground. Vegetation is modeled by discrete scatterers viz, leaves, stems, branches and trunks. These are replaced by glossy dielectric discs and cylinders. Rough surfaces are represented by their mean and spectral characteristics. Average scattered power is then calculated by employing discrete random media methodology such as the distorted Born approximation or transport theory. Both coherent and incoherent multiple scattering techniques are explored. Once direct methods are developed, inversion techniques can be investigated.

Lang, R. H.↗

NASA NTRS1991

Radar modeling of a boreal forest

Microwave modeling, ground truth, and SAR data are used to investigate the characteristics of forest stands. A mixed coniferous forest stand has been modeled at P, L, and C bands. Extensive measurements of ground truth and canopy geometry parameters were performed in a 200-m-square hemlock-dominated forest plot. About 10 percent of the trees were sampled to determine a distribution of diameter at breast height (DBH). Hemlock trees in the forest are modeled by characterizing tree trunks, branches, and needles as randomly oriented lossy dielectric cylinders whose area and orientation distributions are prescribed. The distorted Born approximation is used to compute the backscatter at P, L, and C bands. The theoretical results are found to be lower than the calibrated ground-truth data. The experiment and model results agree quite closely, however, when the ratios of VV to HH and HV to HH are compared.

Chauhan, Narinder S.↗

NASA NTRS1991

Remote sensing of earth terrain

In remote sensing, the encountered geophysical media such as agricultural canopy, forest, snow, or ice are inhomogeneous and contain scatters in a random manner. Furthermore, weather conditions such as fog, mist, or snow cover can intervene the electromagnetic observation of the remotely sensed media. In the modelling of such media accounting for the weather effects, a multi-layer random medium model has been developed. The scattering effects of the random media are described by three-dimensional correlation functions with variances and correlation lengths corresponding to the fluctuation strengths and the physical geometry of the inhomogeneities, respectively. With proper consideration of the dyadic Green's function and its singularities, the strong fluctuation theory is used to calculate the effective permittivities which account for the modification of the wave speed and attenuation in the presence of the scatters. The distorted Born approximation is then applied to obtain the correlations of the scattered fields. From the correlation of the scattered field, calculated is the complete set of scattering coefficients for polarimetric radar observation or brightness temperature in passive radiometer applications. In the remote sensing of terrestrial ecosystems, the development of microwave remote sensing technology and the potential of SAR to measure vegetation structure and biomass have increased effort to conduct experimental and theoretical researches on the interactions between microwave and vegetation canopies. The overall objective is to develop inversion algorithms to retrieve biophysical parameters from radar data. In this perspective, theoretical models and experimental data are methodically interconnected in the following manner: Due to the complexity of the interactions involved, all theoretical models have limited domains of validity; the proposed solution is to use theoretical models, which is validated by experiments, to establish the region in which the radar response is most sensitive to the parameters of interest; theoretically simulated data will be used to generate simple invertible models over the region. For applications to the remote sensing of sea ice, the developed theoretical models need to be tested with experimental measurements. With measured ground truth such as ice thickness, temperature, salinity, and structure, input parameters to the theoretical models can be obtained to calculate the polarimetric scattering coefficients for radars or brightness temperature for radiometers and then compare theoretical results with experimental data. Validated models will play an important role in the interpretation and classification of ice in monitoring global ice cover from space borne remote sensors in the future. We present an inversion algorithm based on a recently developed inversion method referred to as the Renormalized Source-Type Integral Equation approach. The objective of this method is to overcome some of the limitations and difficulties of the iterative Born technique. It recasts the inversion, which is nonlinear in nature, in terms of the solution of a set of linear equations; however, the final inversion equation is still nonlinear. The derived inversion equation is an exact equation which sums up the iterative Neuman (or Born) series in a closed form and, thus, is a valid representation even in the case when the Born series diverges; hence, the name Renormalized Source-Type Integral Equation Approach.

Yueh, Herng-Aung↗

NASA NTRS1992

Basic studies in microwave remote sensing

Scattering models were developed in support of microwave remote sensing of earth terrains with particular emphasis on model applications to airborne Synthetic Aperture Radar measurements of forest. Practically useful surface scattering models based on a solution of a pair of integral equations including multiple scattering effects were developed. Comparisons of these models with controlled scattering measurements from statistically known random surfaces indicate that they are valid over a wide range of frequencies. Scattering models treating a forest environment as a two and three layered media were also developed. Extensive testing and comparisons were carried out with the two layered model. Further studies with the three layered model are being carried out. A volume scattering model valid for dense media such as a snow layer was also developed that shows the appropriate trend dependence with the volume fraction of scatterers.

Fung, Adrian K.↗

NASA NTRS2012

Interpretation of Variations in Modis-Measured Greenness Levels of Amazon Forests During 2000 to 2009

This work investigates variations in satellite-measured greenness of Amazon forests using ten years of NASA Moderate Resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) data. Corruption of optical remote sensing data with clouds and aerosols is prevalent in this region; filtering corrupted data causes spatial sampling constraints, as well as reducing the record length, which introduces large biases in estimates of greenness anomalies. The EVI data, analyzed in multiple ways and taking into account EVI accuracy, consistently show a pattern of negligible changes in the greenness levels of forests both in the area affected by drought in 2005 and outside it. Small random patches of anomalous greening and browning-especially prominent in 2009-appear in all ten years, irrespective of contemporaneous variations in precipitation, but with no persistence over time. The fact that over 90% of the EVI anomalies are insignificantly small-within the envelope of error (95% confidence interval) in EVI-warrants cautious interpretation of these results: there were no changes in the greenness of these forests, or if there were changes, the EVI data failed to capture these either because the constituent reflectances were saturated or the moderate resolution precluded viewing small-scale variations. This suggests a need for more accurate and spatially resolved synoptic views from satellite data and corroborating comprehensive ground sampling to understand the greenness dynamics of these forests.

MODIS↗

NASA NTRS1970

The use of space and high altitude aerial photography to classify forest land and to detect forest disturbances

In October 1969, an investigation was begun near Atlanta, Georgia, to explore the possibilities of developing predictors for forest land and stand condition classifications using space photography. It has been found that forest area can be predicted with reasonable accuracy on space photographs using ocular techniques. Infrared color film is the best single multiband sensor for this purpose. Using the Apollo 9 infrared color photographs taken in March 1969 photointerpreters were able to predict forest area for small units consistently within 5 to 10 percent of ground truth. Approximately 5,000 density data points were recorded for 14 scan lines selected at random from five study blocks. The mean densities and standard deviations were computed for 13 separate land use classes. The results indicate that forest area cannot be separated from other land uses with a high degree of accuracy using optical film density alone. If, however, densities derived by introducing red, green, and blue cutoff filters in the optical system of the microdensitometer are combined with their differences and their ratios in regression analysis techniques, there is a good possibility of discriminating forest from all other classes.

Aldrich, R. C.↗

NASA NTRS2013

Forest Structure Characterization Using JPL's UAVSAR Multi-Baseline Polarimetric SAR Interferometry and Tomography

This paper concerns forest remote sensing using JPL's multi-baseline polarimetric interferometric UAVSAR data. It presents exemplary results and analyzes the possibilities and limitations of using SAR Tomography and Polarimetric SAR Interferometry (PolInSAR) techniques for the estimation of forest structure. Performance and error indicators for the applicability and reliability of the used multi-baseline (MB) multi-temporal (MT) PolInSAR random volume over ground (RVoG) model are discussed. Experimental results are presented based on JPL's L-band repeat-pass polarimetric interferometric UAVSAR data over temperate and tropical forest biomes in the Harvard Forest, Massachusetts, and in the La Amistad Park, Panama and Costa Rica. The results are partially compared with ground field measurements and with air-borne LVIS lidar data.

UAVSAR (Uninhabited Aerial Vehicle SAR)↗

NASA NTRS2013

Forest Structure Characterization Using Jpl's UAVSAR Multi-Baseline Polarimetric SAR Interferometry and Tomography

remote sensing↗

DOE OSTI2023

Combining field and remote sensing data to estimate forest canopy damage and recovery following tropical cyclones across tropical regions

Abstract As tropical forests cycle the most water and carbon, it is crucial to understand the short- and long-term effects of intensifying cyclones on these ecosystems. Soil nutrient status has been shown to moderate forest cyclone responses using field litterfall measurements, but litterfall is one of the multiple cyclone impact metrtics, which may or may not be correlated with one another or with site nutrients. We used remotely sensed vegetation indices to quantify immediate damage and two-year recovery for 42 cases across nine tropical forests in Hawaii, Puerto Rico, Mexico, Australia, and Taiwan affected by 12 cyclones between 2004 and 2017. We tested whether changes in leaf area index (LAI) and enhanced vegetation index (EVI) correlated with changes in litterfall observations and how changes varied with total soil phosphorus (P) concentrations across regions. We compared cyclone-induced changes and recovery of LAI and EVI to litterfall observations compiled in a pantropical meta-analysis. We found large variation in changes in LAI and EVI across forests, with the greatest reductions in LAI (−77%) and EVI (−77%) in Mexico (Jalisco) and Puerto Rico, respectively. LAI ( r = −0.52) and EVI ( r = −0.60) changes correlated with those in litterfall across cases. Post-cyclone data showed recovery of LAI by four months, EVI by two months, and litterfall by ten months. We detected larger changes in LAI and EVI in forests with higher soil P, but these relationships were not significant when accounting for cyclone and site as random effects. Principal component analyses indicated a regional clustering of cases related to their contrasting cyclone regimes, with the frequency and intensity of cyclone events negatively correlated. Overall, remote sensing observations complement but do not substitute for ground observations that reveal cyclone damage and post-cyclone recovery in tropical forests, and soil phosphorus moderates some but not all metrics of stability in response to cyclones.

Bloom, Dellena E. (ORCID:0000000205981747)↗

NASA NTRS1992

Radiative transfer theory for polarimetric remote sensing of pine forest

The radiative transfer theory is applied to interpret polarimetric radar backscatter from pine forest with clustered vegetation structures. The scattering function of each cluster is calculated by incorporating the phase interference of scattered fields from each component. The resulting phase matrix is used in the radiative transfer equations to evaluate the polarimetric backscattering coefficients from random medium layers embedded with vegetation clusters. Upon including multiscale structures (trunks, primary and secondary branches, and needles), polarimetric radar responses from pine forest for different frequencies and looking angles are interpreted and simulated. Preliminary results are shown to be in good agreement with the measured backscattering coefficients at the Landes maritime pine forest during the MAESTRO-1 experiment.

Hsu, C. C.↗

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 NTRS2016

Ground-Level Digital Terrain Model (DTM) Construction from Tandem-X InSAR Data and Worldview Stereo-Photogrammetric Images

The ground-level digital elevation model (DEM) or digital terrain model (DTM) information are invaluable for environmental modeling, such as water dynamics in forests, canopy height, forest biomass, carbon estimation, etc. We propose to extract the DTM over forested areas from the combination of interferometric complex coherence from single-pass TanDEM-X (TDX) data at HH polarization and Digital Surface Model (DSM) derived from high-resolution WorldView (WV) image pair by means of random volume over ground (RVoG) model. The RVoG model is a widely and successfully used model for polarimetric SAR interferometry (Pol-InSAR) technique for vertical forest structure parameter retrieval [1][2][3][4]. The ground-level DEM have been obtained by complex volume decorrelation in the RVoG model with the DSM using stereo-photogrammetric technique. Finally, the airborne lidar data were used to validate the ground-level DEM and forest canopy height results.

Lee, Seung-Kuk↗

NASA NTRS2008

Validation of a Remote Sensing Based Index of Forest Disturbance Using Streamwater Nitrogen Data

Vegetation disturbances are known to alter the functioning of forested ecosystems by contributing to export ('leakage') of dissolved nitrogen (N), typically nitrate-N, from watersheds that can contribute to acidification of acid-sensitive streams, leaching of base cations, and eutrophication of downstream receiving waters. Yet, at a landscape scale, direct evaluation of how disturbance is linked to spatial variability in N leakage is complicated by the fact that disturbances operate at different spatial scales, over different timescales, and at different intensities. In this paper we explore whether data from synoptic streamwater surveys conducted in an Appalachian oak-dominated forested river basin in western MD (USA) can be used to test and validate a scalable, synthetic, and integrative forest disturbance index (FDI) derived from Landsat imagery. In particular, we found support for the hypothesis that the interannual variation in spring baseflow total dissolved nitrogen (TDN) and nitrate-N concentrations measured at 35 randomly selected stream stations varied as a linear function of the change in FDI computed for the corresponding set of subwatersheds. Our results demonstrate that the combined effects of forest disturbances can be detected using synoptic water quality data. It appears that careful timing of the synoptic baseflow sampling under comparable phenological and hydrometeorological conditions increased our ability to identify a forest disturbance signal.

Eshleman, Keith N.↗

NASA NTRS1992

A microwave scattering model for layered vegetation

A microwave scattering model was developed for layered vegetation based on an iterative solution of the radiative transfer equation up to the second order to account for multiple scattering within the canopy and between the ground and the canopy. The model is designed to operate over a wide frequency range for both deciduous and coniferous forest and to account for the branch size distribution, leaf orientation distribution, and branch orientation distribution for each size. The canopy is modeled as a two-layered medium above a rough interface. The upper layer is the crown containing leaves, stems, and branches. The lower layer is the trunk region modeled as randomly positioned cylinders with a preferred orientation distribution above an irregular soil surface. Comparisons of this model with measurements from deciduous and coniferous forests show good agreements at several frequencies for both like and cross polarizations. Major features of the model needed to realize the agreement include allowance for: (1) branch size distribution, (2) second-order effects, and (3) tree component models valid over a wide range of frequencies.

Karam, Mostafa A.↗

NASA NTRS1995

The Local Ly(alpha) Forest: Association of Clouds with Superclusters and Voids

The Goddard High Resolution Spectrograph aboard the Hubble Space Telescope was used with the G160M grating to obtain high-resolution (6.2 A) spectra of three very bright active galactic nuclei located behind voids in the nearby distribution of bright galaxies (i.e., CfA and Arecibo redshift survey regions). A total of eight definite (greater than or equal to 4 sigma) Ly(alpha) absorption lines were discovered ranging in equivalent width from 26 to 240 mA at Galactocentric velocities 1740-7740 km/s. Of these eight systems, we locate seven in supercluster structures and one, in the sight line of Mrk 501 at 7740 km/s, in a void. In addition, one of two tentative (3-4 sigma) Ly(alpha) absorption lines are found in voids. Thus, the voids are not entirely devoid of matter, and not all Ly(alpha) clouds are associated with galaxies. Also, since the path lengths through voids and superclusters probed by our observations thus far are nearly equal, there is some statistical evidence that the Ly(alpha) clouds avoid the voids. The nearest galaxy neighbors to these absorbing clouds are 0.45-5.9 Mpc away, too far to be physically associated by most models. The lower equivalent width absorption lines (W(sub lambda) less than or equal to 100 mA) are consistent with random locations with respect to galaxies and may be truly intergalactic, similar to the bulk of the Ly(alpha) forest seen at high z. These results on local Ly(alpha) clouds are in full agreement with those found by Morris et al. (1993) for the 3C 273 sight line but are different from the results for higher equivalent width systems where closer cloud-galaxy associations were found by Lanzetta et al. (1994). Pencil-beam optical and 21 cm radio line observations of the area of sky surrounding Mrk 501 fail to find faint galaxies near the velocities of the Ly(alpha) clouds in that sight line. Specifically, for the 'void absorption' system at 7740 km/s, we find no galaxy at comparable redshift to the absorber within 100 h(sub 75)(sup -1) kpc (H(sub 0) = 75 h(sub 75) km/s Mpc(sup -1)) with an absolute magnitude of B less than or equal to - 16 and no object with H I mass greater than or equal to 7 x 10(exp 8) h(sub 75)(sup -2) M(solar) within 500 h(sub 75)(sup -1) kpc. Thus, neither a faint optical galaxy nor a gas-rich, optically dim or low surface brightness galaxy is present close to this absorber.

Stocke, John T.↗

DOE OSTI2024

Differential Organic Carbon Mineralization Responses to Soil Moisture in Three Different Soil Orders Under Mixed Forested System: Supporting Data

This data contains data from 90-day long incubation study which aimed to look at the soil moisture-texture relationship on soil organic carbon (SOC) cycling. Soils were collected from three distinct soil textures from mixed forests in 2017: sandy (Georgia, 2017-05-01), loamy (Missouri, 2017-06-14) and clayey (Texas, December 2017) were incubated at different soil moisture levels (air-dried, 25% water holding capacity (WHC), 50% WHC, 100% WHC and 175% WHC) at room temperature for a period of 90 days. Files contain microbial respiration, active and slow SOC pools, and their respective mineralization rates, extractable organic carbon (C), and C-acquiring extracellular enzymes. Findings from these data were used in Singh et al. (2021). This study aimed to examine the interactive effect of soil moisture and texture on SOC mineralization. Soil samples of three distinct textures (sandy, loamy, and clayey) were collected from mixed forests of Georgia, Missouri, and Texas, respectively. Soil cores of 5 cm diameter were collected from numerous random locations at each site from 0-15 cm depth after scraping the litter layer and mixed thoroughly to obtain a composite sample per site. Three additional soil cores were collected to determine the WHC using pressure plate extractors. Soil samples were composited, and triplicate soil samples were incubated in mason jars for a period of 90 days at room temperature under different moisture regimes: air dried, 25% WHC, 50% WHC, at WHC and 100% saturation. Soil respiration was measured weekly, and destructive sampling was conducted at 1, 15, 60, and 90 days to determine extractable organic C, C acquiring enzyme activity, and active and slow SOC pools with their respective mineralization rates. The C acquiring enzyme activity was the total activity of α-glucosidase, β-glucosidase, cellobiohydrolase, and β-xylosidase enzymes. Gas samples for microbial respiration measurements were collected from headspace of incubation jars through the sampling ports on the lids and then analyzed using a Shimadzu Gas Chromatograph (GC-2014). Prior to sampling, the vials were evacuated. Blank correction was also done by collecting gas samples from empty incubation jars. Double pool exponential decay model was used in SigmaPlot to determine the active and slow SOC pools and their mineralization rates (Farrar et al., 2012; Jagadamma et al., 2014). The C-acquiring extracellular enzymes were measured using the microplate method by German et al., (2011). Microbial community structure was determined using the phospholipid fatty acid (PLFA) and neutral lipid fatty acid (NLFA) analyses (Buyer and Sasser, 2012). This dataset has seven data files provided in comma-separate (*.csv) format. Additional metadata are provided: seven data dictionaries and a file-level metadata file in comma separate (*.csv) format and a user guide in PDF (*.pdf) format.

Carbon acquiring enzyme activity↗