DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, Lan; Hill, K. W.; Bitter, M.

Here, a high spatial resolution of a few μm is often required for probing small-scale high-energy-density plasmas using high resolution x-ray imaging spectroscopy. This resolution can be achieved by adjusting system magnification to overcome the inherent limitation of the detector pixel size. Laboratory experiments on investigating the relation between spatial resolution and system magnification for a spherical crystal spectrometer are presented. Tungsten Lβ 2 rays from a tungsten-target micro-focus x-ray tube were diffracted by a Ge 440 crystal, which was spherically bent to a radius of 223 mm, and imaged onto an x-ray CCD with 13-μm pixel size. The source-to-crystalmore » (p) and crystal-to-detector (q) distances were varied to produce spatial magnifications ( M = q/p) ranging from 2 to 10. The inferred instrumental spatial width reduces with increasing system magnification M. However, the experimental measurement at each M is larger than the theoretical value of pixel size divided by M. Future work will focus on investigating possible broadening mechanisms that limit the spatial resolution.« less

Hierarchical Spatio-temporal Visual Analysis of Cluster Evolution in Electrocorticography Data

DOE PAGES

Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward; ...

2016-10-02

Here, we present ECoG ClusterFlow, a novel interactive visual analysis tool for the exploration of high-resolution Electrocorticography (ECoG) data. Our system detects and visualizes dynamic high-level structures, such as communities, using the time-varying spatial connectivity network derived from the high-resolution ECoG data. ECoG ClusterFlow provides a multi-scale visualization of the spatio-temporal patterns underlying the time-varying communities using two views: 1) an overview summarizing the evolution of clusters over time and 2) a hierarchical glyph-based technique that uses data aggregation and small multiples techniques to visualize the propagation of clusters in their spatial domain. ECoG ClusterFlow makes it possible 1) tomore » compare the spatio-temporal evolution patterns across various time intervals, 2) to compare the temporal information at varying levels of granularity, and 3) to investigate the evolution of spatial patterns without occluding the spatial context information. Lastly, we present case studies done in collaboration with neuroscientists on our team for both simulated and real epileptic seizure data aimed at evaluating the effectiveness of our approach.« less

Integrating flood modelling in a hydrological catchment model: flow approximations and spatial resolution.

NASA Astrophysics Data System (ADS)

van den Bout, Bastian; Jetten, Victor

2017-04-01

Within hydrological models, flow approximations are commonly used to reduce computation time. The validity of these approximations is strongly determined by flow height, flow velocity, the spatial resolution of the model, and by the manner in which flow routing is implemented. The assumptions of these approximations can furthermore limit emergent behavior, and influence flow behavior under space-time scaling. In this presentation, the validity and performance of the kinematic, diffusive and dynamic flow approximations are investigated for use in a catchment-based flood model. Particularly, the validity during flood events and for varying spatial resolutions is investigated. The OpenLISEM hydrological model is extended to implement these flow approximations and channel flooding based on dynamic flow. The kinematic routing uses a predefined converging flow network, the diffusive and dynamic routing uses a 2D flow solution over a DEM. The channel flow in all cases is a 1D kinematic wave approximation. The flow approximations are used to recreate measured discharge in three catchments of different size in China, Spain and Italy, among which is the hydrograph of the 2003 flood event in the Fella river basin (Italy). Furthermore, spatial resolutions are varied for the flood simulation in order to investigate the influence of spatial resolution on these flow approximations. Results show that the kinematic, diffusive and dynamic flow approximation provide least to highest accuracy, respectively, in recreating measured temporal variation of the discharge. Kinematic flow, which is commonly used in hydrological modelling, substantially over-estimates hydrological connectivity in the simulations with a spatial resolution of below 30 meters. Since spatial resolutions of models have strongly increased over the past decades, usage of routed kinematic flow should be reconsidered. In the case of flood events, spatial modelling of kinematic flow substantially over-estimates hydrological connectivity and flow concentration, leading to significant errors. The combination of diffusive or dynamic overland flow and dynamic channel flooding provides high accuracy in recreating the 2003 Fella river flood event. Finally, flow approximations substantially influenced the predictive potential of the (flash) flood model.

The influence of focal spot blooming on high-contrast spatial resolution in CT imaging.

PubMed

Grimes, Joshua; Duan, Xinhui; Yu, Lifeng; Halaweish, Ahmed F; Haag, Nicole; Leng, Shuai; McCollough, Cynthia

2015-10-01

The objective of this work was to investigate focal spot blooming effects on the spatial resolution of CT images and to evaluate an x-ray tube that uses dynamic focal spot control for minimizing focal spot blooming. The influence of increasing tube current at a fixed tube potential of 80 kV on high-contrast spatial resolution of seven different CT scanner models (scanners A-G), including one scanner that uses dynamic focal spot control to reduce focal spot blooming (scanner A), was evaluated. Spatial resolution was assessed using a wire phantom for the modulation transfer function (MTF) calculation and a copper disc phantom for measuring the slice sensitivity profile (SSP). The impact of varying the tube potential was investigated on two scanner models (scanners A and B) by measuring the MTF and SSP and also by using the resolution bar pattern module of the ACR CT phantom. The phantoms were scanned at 70-150 kV on scanner A and 80-140 kV on scanner B, with tube currents from 100 mA up to the maximum tube current available on each scanner. The images were reconstructed using a slice thickness of 0.6 mm with both smooth and sharp kernels. Additionally, focal spot size at varying tube potentials and currents was directly measured using pinhole and slit camera techniques. Evaluation of the MTF and SSP data from the 7 CT scanner models evaluated demonstrated decreased focal spot blooming for newer scanners, as evidenced by decreasing deviations in MTF and SSP as tube current varied. For scanners A and B, where focal spot blooming effects as a function of tube potential were assessed, the spatial resolution variation in the axial plane was much smaller on scanner A compared to scanner B as tube potential and current changed. On scanner A, the 50% MTF never decreased by more than 2% from the 50% MTF measured at 100 mA. On scanner B, the 50% MTF decreased by as much as 19% from the 50% MTF measured at 100 mA. Assessments of the SSP, the bar patterns in the ACR phantom and the pinhole and slit camera measurements were consistent with the MTF calculations. Focal spot blooming has a noticeable effect on spatial resolution in CT imaging. The focal spot shaping technology of scanner A greatly reduced blooming effects.

Assessing the competing roles of model resolution and meteorological forcing fidelity in hyperresolution simulations of snowpack and streamflow in the southern Rocky Mountains

NASA Astrophysics Data System (ADS)

Gochis, D. J.; Dugger, A. L.; Karsten, L. R.; Barlage, M. J.; Sampson, K. M.; Yu, W.; Pan, L.; McCreight, J. L.; Howard, K.; Busto, J.; Deems, J. S.

2017-12-01

Hydrometeorological processes vary over comparatively short length scales in regions of complex terrain such as the southern Rocky Mountains. Changes in temperature, precipitation, wind and solar radiation can vary significantly across elevation gradients, terrain landform and land cover conditions throughout the region. Capturing such variability in hydrologic models can necessitate the utilization of so-called `hyper-resolution' spatial meshes with effective element spacings of less than 100m. However, it is often difficult to obtain meteorological forcings of high quality in such regions at those resolutions which can result in significant uncertainty in fundamental in hydrologic model inputs. In this study we examine the comparative influences of meteorological forcing data fidelity and spatial resolution on seasonal simulations of snowpack evolution, runoff and streamflow in a set of high mountain watersheds in southern Colorado. We utilize the operational, NOAA National Water Model configuration of the community WRF-Hydro system as a baseline and compare against it, additional model scenarios with differing specifications of meteorological forcing data, with and without topographic downscaling adjustments applied, with and without experimental high resolution radar derived precipitation estimates and with WRF-Hydro configurations of progressively finer spatial resolution. The results suggest significant influence from and importance of meteorological downscaling techniques in controlling spatial distributions of meltout and runoff timing. The use of radar derived precipitation exhibits clear sensitivity on hydrologic simulation skill compared with the use of coarser resolution, background precipitation analyses. Advantages and disadvantages of the utilization of progressively higher resolution model configurations both in terms of computational requirements and model fidelity are also discussed.

Camera system resolution and its influence on digital image correlation

DOE PAGES

Reu, Phillip L.; Sweatt, William; Miller, Timothy; ...

2014-09-21

Digital image correlation (DIC) uses images from a camera and lens system to make quantitative measurements of the shape, displacement, and strain of test objects. This increasingly popular method has had little research on the influence of the imaging system resolution on the DIC results. This paper investigates the entire imaging system and studies how both the camera and lens resolution influence the DIC results as a function of the system Modulation Transfer Function (MTF). It will show that when making spatial resolution decisions (including speckle size) the resolution limiting component should be considered. A consequence of the loss ofmore » spatial resolution is that the DIC uncertainties will be increased. This is demonstrated using both synthetic and experimental images with varying resolution. The loss of image resolution and DIC accuracy can be compensated for by increasing the subset size, or better, by increasing the speckle size. The speckle-size and spatial resolution are now a function of the lens resolution rather than the more typical assumption of the pixel size. The study will demonstrate the tradeoffs associated with limited lens resolution.« less

An evaluation of spatial resolution of a prototype proton CT scanner.

PubMed

Plautz, Tia E; Bashkirov, V; Giacometti, V; Hurley, R F; Johnson, R P; Piersimoni, P; Sadrozinski, H F-W; Schulte, R W; Zatserklyaniy, A

2016-12-01

To evaluate the spatial resolution of proton CT using both a prototype proton CT scanner and Monte Carlo simulations. A custom cylindrical edge phantom containing twelve tissue-equivalent inserts with four different compositions at varying radial displacements from the axis of rotation was developed for measuring the modulation transfer function (MTF) of a prototype proton CT scanner. Two scans of the phantom, centered on the axis of rotation, were obtained with a 200 MeV, low-intensity proton beam: one scan with steps of 4°, and one scan with the phantom continuously rotating. In addition, Monte Carlo simulations of the phantom scan were performed using scanners idealized to various degrees. The data were reconstructed using an iterative projection method with added total variation superiorization based on individual proton histories. Edge spread functions in the radial and azimuthal directions were obtained using the oversampling technique. These were then used to obtain the modulation transfer functions. The spatial resolution was defined by the 10% value of the modulation transfer function (MTF 10% ) in units of line pairs per centimeter (lp/cm). Data from the simulations were used to better understand the contributions of multiple Coulomb scattering in the phantom and the scanner hardware, as well as the effect of discretization of proton location. The radial spatial resolution of the prototype proton CT scanner depends on the total path length, W, of the proton in the phantom, whereas the azimuthal spatial resolution depends both on W and the position, u - , at which the most-likely path uncertainty is evaluated along the path. For protons contributing to radial spatial resolution, W varies with the radial position of the edge, whereas for protons contributing to azimuthal spatial resolution, W is approximately constant. For a pixel size of 0.625 mm, the radial spatial resolution of the image reconstructed from the fully idealized simulation data ranged between 6.31 ± 0.36 lp/cm for W = 197 mm i.e., close to the center of the phantom, and 13.79 ± 0.36 lp/cm for W = 97 mm, near the periphery of the phantom. The azimuthal spatial resolution ranged from 6.99 ± 0.23 lp/cm at u - = 75 mm (near the center) to 11.20 ± 0.26 lp/cm at u - = 20 mm (near the periphery). Multiple Coulomb scattering limits the radial spatial resolution for path lengths greater than approximately 130 mm, and the azimuthal spatial resolution for positions of evaluation greater than approximately 40 mm for W = 199 mm. The radial spatial resolution of the image reconstructed from data from the 4° stepped experimental scan ranged from 5.11 ± 0.61 lp/cm for W = 197 mm to 8.58 ± 0.50 lp/cm for W = 97 mm. In the azimuthal direction, the spatial resolution ranged from 5.37 ± 0.40 lp/cm at u - = 75 mm to 7.27 ± 0.39 lp/cm at u - = 20 mm. The continuous scan achieved the same spatial resolution as that of the stepped scan. Multiple Coulomb scattering in the phantom is the limiting physical factor of the achievable spatial resolution of proton CT; additional loss of spatial resolution in the prototype system is associated with scattering in the proton tracking system and inadequacies of the proton path estimate used in the iterative reconstruction algorithm. Improvement in spatial resolution may be achievable by improving the most likely path estimate by incorporating information about high and low density materials, and by minimizing multiple Coulomb scattering in the proton tracking system.

An evaluation of spatial resolution of a prototype proton CT scanner

PubMed Central

Plautz, Tia E.; Bashkirov, V.; Giacometti, V.; Hurley, R. F.; Piersimoni, P.; Sadrozinski, H. F.-W.; Schulte, R. W.; Zatserklyaniy, A.

2016-01-01

Purpose: To evaluate the spatial resolution of proton CT using both a prototype proton CT scanner and Monte Carlo simulations. Methods: A custom cylindrical edge phantom containing twelve tissue-equivalent inserts with four different compositions at varying radial displacements from the axis of rotation was developed for measuring the modulation transfer function (MTF) of a prototype proton CT scanner. Two scans of the phantom, centered on the axis of rotation, were obtained with a 200 MeV, low-intensity proton beam: one scan with steps of 4°, and one scan with the phantom continuously rotating. In addition, Monte Carlo simulations of the phantom scan were performed using scanners idealized to various degrees. The data were reconstructed using an iterative projection method with added total variation superiorization based on individual proton histories. Edge spread functions in the radial and azimuthal directions were obtained using the oversampling technique. These were then used to obtain the modulation transfer functions. The spatial resolution was defined by the 10% value of the modulation transfer function (MTF10%) in units of line pairs per centimeter (lp/cm). Data from the simulations were used to better understand the contributions of multiple Coulomb scattering in the phantom and the scanner hardware, as well as the effect of discretization of proton location. Results: The radial spatial resolution of the prototype proton CT scanner depends on the total path length, W, of the proton in the phantom, whereas the azimuthal spatial resolution depends both on W and the position, u−, at which the most-likely path uncertainty is evaluated along the path. For protons contributing to radial spatial resolution, W varies with the radial position of the edge, whereas for protons contributing to azimuthal spatial resolution, W is approximately constant. For a pixel size of 0.625 mm, the radial spatial resolution of the image reconstructed from the fully idealized simulation data ranged between 6.31 ± 0.36 lp/cm for W = 197 mm i.e., close to the center of the phantom, and 13.79 ± 0.36 lp/cm for W = 97 mm, near the periphery of the phantom. The azimuthal spatial resolution ranged from 6.99 ± 0.23 lp/cm at u− = 75 mm (near the center) to 11.20 ± 0.26 lp/cm at u− = 20 mm (near the periphery). Multiple Coulomb scattering limits the radial spatial resolution for path lengths greater than approximately 130 mm, and the azimuthal spatial resolution for positions of evaluation greater than approximately 40 mm for W = 199 mm. The radial spatial resolution of the image reconstructed from data from the 4° stepped experimental scan ranged from 5.11 ± 0.61 lp/cm for W = 197 mm to 8.58 ± 0.50 lp/cm for W = 97 mm. In the azimuthal direction, the spatial resolution ranged from 5.37 ± 0.40 lp/cm at u− = 75 mm to 7.27 ± 0.39 lp/cm at u− = 20 mm. The continuous scan achieved the same spatial resolution as that of the stepped scan. Conclusions: Multiple Coulomb scattering in the phantom is the limiting physical factor of the achievable spatial resolution of proton CT; additional loss of spatial resolution in the prototype system is associated with scattering in the proton tracking system and inadequacies of the proton path estimate used in the iterative reconstruction algorithm. Improvement in spatial resolution may be achievable by improving the most likely path estimate by incorporating information about high and low density materials, and by minimizing multiple Coulomb scattering in the proton tracking system. PMID:27908179

Optimizing landslide susceptibility zonation: Effects of DEM spatial resolution and slope unit delineation on logistic regression models

NASA Astrophysics Data System (ADS)

Schlögel, R.; Marchesini, I.; Alvioli, M.; Reichenbach, P.; Rossi, M.; Malet, J.-P.

2018-01-01

We perform landslide susceptibility zonation with slope units using three digital elevation models (DEMs) of varying spatial resolution of the Ubaye Valley (South French Alps). In so doing, we applied a recently developed algorithm automating slope unit delineation, given a number of parameters, in order to optimize simultaneously the partitioning of the terrain and the performance of a logistic regression susceptibility model. The method allowed us to obtain optimal slope units for each available DEM spatial resolution. For each resolution, we studied the susceptibility model performance by analyzing in detail the relevance of the conditioning variables. The analysis is based on landslide morphology data, considering either the whole landslide or only the source area outline as inputs. The procedure allowed us to select the most useful information, in terms of DEM spatial resolution, thematic variables and landslide inventory, in order to obtain the most reliable slope unit-based landslide susceptibility assessment.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, Lan, E-mail: lgao@pppl.gov; Hill, K. W.; Bitter, M.

A high spatial resolution of a few μm is often required for probing small-scale high-energy-density plasmas using high resolution x-ray imaging spectroscopy. This resolution can be achieved by adjusting system magnification to overcome the inherent limitation of the detector pixel size. Laboratory experiments on investigating the relation between spatial resolution and system magnification for a spherical crystal spectrometer are presented. Tungsten Lβ{sub 2} rays from a tungsten-target micro-focus x-ray tube were diffracted by a Ge 440 crystal, which was spherically bent to a radius of 223 mm, and imaged onto an x-ray CCD with 13-μm pixel size. The source-to-crystal (p)more » and crystal-to-detector (q) distances were varied to produce spatial magnifications (M = q/p) ranging from 2 to 10. The inferred instrumental spatial width reduces with increasing system magnification M. However, the experimental measurement at each M is larger than the theoretical value of pixel size divided by M. Future work will focus on investigating possible broadening mechanisms that limit the spatial resolution.« less

Enhancing resolution and contrast in second-harmonic generation microscopy using an advanced maximum likelihood estimation restoration method

NASA Astrophysics Data System (ADS)

Sivaguru, Mayandi; Kabir, Mohammad M.; Gartia, Manas Ranjan; Biggs, David S. C.; Sivaguru, Barghav S.; Sivaguru, Vignesh A.; Berent, Zachary T.; Wagoner Johnson, Amy J.; Fried, Glenn A.; Liu, Gang Logan; Sadayappan, Sakthivel; Toussaint, Kimani C.

2017-02-01

Second-harmonic generation (SHG) microscopy is a label-free imaging technique to study collagenous materials in extracellular matrix environment with high resolution and contrast. However, like many other microscopy techniques, the actual spatial resolution achievable by SHG microscopy is reduced by out-of-focus blur and optical aberrations that degrade particularly the amplitude of the detectable higher spatial frequencies. Being a two-photon scattering process, it is challenging to define a point spread function (PSF) for the SHG imaging modality. As a result, in comparison with other two-photon imaging systems like two-photon fluorescence, it is difficult to apply any PSF-engineering techniques to enhance the experimental spatial resolution closer to the diffraction limit. Here, we present a method to improve the spatial resolution in SHG microscopy using an advanced maximum likelihood estimation (AdvMLE) algorithm to recover the otherwise degraded higher spatial frequencies in an SHG image. Through adaptation and iteration, the AdvMLE algorithm calculates an improved PSF for an SHG image and enhances the spatial resolution by decreasing the full-width-at-halfmaximum (FWHM) by 20%. Similar results are consistently observed for biological tissues with varying SHG sources, such as gold nanoparticles and collagen in porcine feet tendons. By obtaining an experimental transverse spatial resolution of 400 nm, we show that the AdvMLE algorithm brings the practical spatial resolution closer to the theoretical diffraction limit. Our approach is suitable for adaptation in micro-nano CT and MRI imaging, which has the potential to impact diagnosis and treatment of human diseases.

High resolution modelling and observation of wind-driven surface currents in a semi-enclosed estuary

NASA Astrophysics Data System (ADS)

Nash, S.; Hartnett, M.; McKinstry, A.; Ragnoli, E.; Nagle, D.

2012-04-01

Hydrodynamic circulation in estuaries is primarily driven by tides, river inflows and surface winds. While tidal and river data can be quite easily obtained for input to hydrodynamic models, sourcing accurate surface wind data is problematic. Firstly, the wind data used in hydrodynamic models is usually measured on land and can be quite different in magnitude and direction from offshore winds. Secondly, surface winds are spatially-varying but due to a lack of data it is common practice to specify a non-varying wind speed and direction across the full extents of a model domain. These problems can lead to inaccuracies in the surface currents computed by three-dimensional hydrodynamic models. In the present research, a wind forecast model is coupled with a three-dimensional numerical model of Galway Bay, a semi-enclosed estuary on the west coast of Ireland, to investigate the effect of surface wind data resolution on model accuracy. High resolution and low resolution wind fields are specified to the model and the computed surface currents are compared with high resolution surface current measurements obtained from two high frequency SeaSonde-type Coastal Ocean Dynamics Applications Radars (CODAR). The wind forecast models used for the research are Harmonie cy361.3, running on 2.5 and 0.5km spatial grids for the low resolution and high resolution models respectively. The low-resolution model runs over an Irish domain on 540x500 grid points with 60 vertical levels and a 60s timestep and is driven by ECMWF boundary conditions. The nested high-resolution model uses 300x300 grid points on 60 vertical levels and a 12s timestep. EFDC (Environmental Fluid Dynamics Code) is used for the hydrodynamic model. The Galway Bay model has ten vertical layers and is resolved spatially and temporally at 150m and 4 sec respectively. The hydrodynamic model is run for selected hindcast dates when wind fields were highly energetic. Spatially- and temporally-varying wind data is provided by offline coupling with the wind forecast models. Modelled surface currents show good correlation with CODAR observed currents and the resolution of the surface wind data is shown to be important for model accuracy.

Study of spatial resolution of coordinate detectors based on Gas Electron Multipliers

NASA Astrophysics Data System (ADS)

Kudryavtsev, V. N.; Maltsev, T. V.; Shekhtman, L. I.

2017-02-01

Spatial resolution of GEM-based tracking detectors is determined in the simulation and measured in the experiments. The simulation includes GEANT4 implemented transport of high energy electrons with careful accounting of atomic relaxation processes including emission of fluorescent photons and Auger electrons and custom post-processing with accounting of diffusion, gas amplification fluctuations, distribution of signals on readout electrodes, electronics noise and particular algorithm of final coordinate calculation (center of gravity). The simulation demonstrates that the minimum of spatial resolution of about 10 μm can be achieved with a gas mixture of Ar -CO2 (75-25 %) at a strips pitch from 250 μm to 300 μm. At a larger pitch the resolution quickly degrades reaching 80-100 μm at a pitch of 460-500 μm. Spatial resolution of low-material triple-GEM detectors for the DEUTERON facility at the VEPP-3 storage ring is measured at the extracted beam facility of the VEPP-4 M collider. One-coordinate resolution of the DEUTERON detector is measured with electron beam of 500 MeV, 1 GeV and 3.5 GeV energies. The determined value of spatial resolution varies in the range from approximately 35 μm to 50 μm for orthogonal tracks in the experiments.

Characterization of spatial and spectral resolution of a rotating prism chromotomographic hyperspectral imager

NASA Astrophysics Data System (ADS)

Bostick, Randall L.; Perram, Glen P.; Tuttle, Ronald

2009-05-01

The Air Force Institute of Technology (AFIT) has built a rotating prism chromotomographic hyperspectral imager (CTI) with the goal of extending the technology to exploit spatially extended sources with quickly varying (> 10 Hz) phenomenology, such as bomb detonations and muzzle flashes. This technology collects successive frames of 2-D data dispersed at different angles multiplexing spatial and spectral information which can then be used to reconstruct any arbitrary spectral plane(s). In this paper, the design of the AFIT instrument is described and then tested against a spectral target with near point source spatial characteristics to measure spectral and spatial resolution. It will be shown that, in theory, the spectral and spatial resolution in the 3-D spectral image cube is the nearly the same as a simple prism spectrograph with the same design. However, error in the knowledge of the prism linear dispersion at the detector array as a function of wavelength and projection angle will degrade resolution without further corrections. With minimal correction for error and use of a simple shift-and-add reconstruction algorithm, the CTI is able to produce a spatial resolution of about 2 mm in the object plane (234 μrad IFOV) and is limited by chromatic aberration. A spectral resolution of less than 1nm at shorter wavelengths is shown, limited primarily by prism dispersion.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scaduto, DA; Hu, Y-H; Zhao, W

Purpose: Spatial resolution in digital breast tomosynthesis (DBT) is affected by inherent/binned detector resolution, oblique entry of x-rays, and focal spot size/motion; the limited angular range further limits spatial resolution in the depth-direction. While DBT is being widely adopted clinically, imaging performance metrics and quality control protocols have not been standardized. AAPM Task Group 245 on Tomosynthesis Quality Control has been formed to address this deficiency. Methods: Methods of measuring spatial resolution are evaluated using two prototype quality control phantoms for DBT. Spatial resolution in the detector plane is measured in projection and reconstruction domains using edge-spread function (ESF), point-spreadmore » function (PSF) and modulation transfer function (MTF). Spatial resolution in the depth-direction and effective slice thickness are measured in the reconstruction domain using slice sensitivity profile (SSP) and artifact spread function (ASF). An oversampled PSF in the depth-direction is measured using a 50 µm angulated tungsten wire, from which the MTF is computed. Object-dependent PSF is derived and compared with ASF. Sensitivity of these measurements to phantom positioning, imaging conditions and reconstruction algorithms is evaluated. Results are compared from systems of varying acquisition geometry (9–25 projections over 15–60°). Dependence of measurements on feature size is investigated. Results: Measurements of spatial resolution using PSF and LSF are shown to depend on feature size; depth-direction spatial resolution measurements are shown to similarly depend on feature size for ASF, though deconvolution with an object function removes feature size-dependence. A slanted wire may be used to measure oversampled PSFs, from which MTFs may be computed for both in-plane and depth-direction resolution. Conclusion: Spatial resolution measured using PSF is object-independent with sufficiently small object; MTF is object-independent. Depth-direction spatial resolution may be measured directly using MTF or indirectly using ASF or SSP as surrogate measurements. While MTF is object-independent, it is invalid for nonlinear reconstructions.« less

Sensitivity of landscape metrics to changing scale of remote sensing data in spatial pattern analysis: effect, criticality and scaling.

NASA Astrophysics Data System (ADS)

Xu, C.; Zhao, S.; Zhao, B.

2017-12-01

Spatial heterogeneity is scale-dependent, that is, the quantification and representation of spatial pattern vary with the resolution and extent. Overwhelming practices focused on scale effect of landscape metrics, and predicable scaling relationships found among some of them are thought to be the most effective and precise way to quantify multi-scale characteristics. However, previous studies tended to consider a narrow range of scales, and few focused on the critical threshold of scaling function. Here we examine the scalograms of 38 widely-used landscape-level metrics in a more integral spectrum of grain size among 96 landscapes with various extent (i.e. from 25km2 up towards to 221 km2), which sampled randomly from NLCD product. Our goal is to explore the existence of scaling domain and whether the response of metrics to changing resolution would be influenced by spatial extent. Results clearly show the existence of scaling domain for 13 of them (Type II), while the behaviors of other 13 (Type I) exhibit simple scaling functions and the rest (Type III) demonstrate various forms like no obvious change or fluctuation across the integral spectrum of grain size. In addition, an invariant power law scaling relationship was found between critical resolution and spatial extent for metrics falling into Type II, as the critical resolution is proportional to Eρ (ρ is a constant, and E is the extent). All the scaling exponents (ρ) are positive, suggesting that the critical resolutions for these characteristics of landscape structure can be relaxed as the spatial extent expands. This agrees well with empirical perception that coarser grain size might be allowed for spatial data with larger extent. Furthermore, the parameters of scaling functions for metrics falling into Type I and Type II vary with spatial extent, and power law or logarithmic relationships could be identified between them for some metrics. Our finding support the existence of self-organized criticality for a hierarchically-structured landscape. Although the underlying mechanism driving the scaling relationship remains unclear, it could provide guidance toward general principles in spatial pattern analysis and on selecting the proper resolution to avoid the misrepresentation of spatial pattern and profound biases in further ecological progress research.

Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods

NASA Astrophysics Data System (ADS)

Mateo, Cherry May R.; Yamazaki, Dai; Kim, Hyungjun; Champathong, Adisorn; Vaze, Jai; Oki, Taikan

2017-10-01

Global-scale river models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representations of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash-Sutcliffe efficiency coefficients decreased by more than 50 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions at finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings should be universal and may have significant impacts on large- to global-scale simulations, especially in regions where mega deltas exist.These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

Fabrication and characterization of a 0.5-mm lutetium oxyorthosilicate detector array for high-resolution PET applications.

PubMed

Stickel, Jennifer R; Qi, Jinyi; Cherry, Simon R

2007-01-01

With the increasing use of in vivo imaging in mouse models of disease, there are many interesting applications that demand imaging of organs and tissues with submillimeter resolution. Though there are other contributing factors, the spatial resolution in small-animal PET is still largely determined by the detector pixel dimensions. In this work, a pair of lutetium oxyorthosilicate (LSO) arrays with 0.5-mm pixels was coupled to multichannel photomultiplier tubes and evaluated for use as high-resolution PET detectors. Flood histograms demonstrated that most crystals were clearly identifiable. Energy resolution varied from 22% to 38%. The coincidence timing resolution was 1.42-ns full width at half maximum (FWHM). The intrinsic spatial resolution was 0.68-mm FWHM as measured with a 30-gauge needle filled with (18)F. The improvement in spatial resolution in a tomographic setting is demonstrated using images of a line source phantom reconstructed with filtered backprojection and compared with images obtained from 2 dedicated small-animal PET scanners. Finally, a projection image of the mouse foot is shown to demonstrate the application of these 0.5-mm LSO detectors to a biologic task. A pair of highly pixelated LSO detections has been constructed and characterized for use as high-spatial-resolution PET detectors. It appears that small-animal PET systems capable of a FWHM spatial resolution of 600 microm or less are feasible and should be pursued.

Neutron imaging with lithium indium diselenide: Surface properties, spatial resolution, and computed tomography

NASA Astrophysics Data System (ADS)

Lukosi, Eric D.; Herrera, Elan H.; Hamm, Daniel S.; Burger, Arnold; Stowe, Ashley C.

2017-11-01

An array of lithium indium diselenide (LISe) scintillators were investigated for application in neutron imaging. The sensors, varying in thickness and surface roughness, were tested using both reflective and anti-reflective mounting to an aluminum window. The spatial resolution of each LISe scintillator was calculated using the knife-edge test and a modulation transfer function analysis. It was found that the anti-reflective backing case yielded higher spatial resolutions by up to a factor of two over the reflective backing case despite a reduction in measured light yield by an average of 1.97. In most cases, the use of an anti-reflective backing resulted in a higher spatial resolution than the 50 μm-thick ZnS(Cu):6 LiF comparison scintillation screen. The effect of surface roughness was not directly correlated to measured light yield or observed spatial resolution, but weighting the reflective backing case by the random surface roughness revealed that a linear relationship exists between the fractional change (RB/ARB) of the two. Finally, the LISe scintillator array was used in neutron computed tomography to investigate the features of halyomorpha halys with the reflective and anti-reflective backing.

Comparison of alternative spatial resolutions in the application of a spatially distributed biogeochemical model over complex terrain

USGS Publications Warehouse

Turner, D.P.; Dodson, R.; Marks, D.

1996-01-01

Spatially distributed biogeochemical models may be applied over grids at a range of spatial resolutions, however, evaluation of potential errors and loss of information at relatively coarse resolutions is rare. In this study, a georeferenced database at the 1-km spatial resolution was developed to initialize and drive a process-based model (Forest-BGC) of water and carbon balance over a gridded 54976 km2 area covering two river basins in mountainous western Oregon. Corresponding data sets were also prepared at 10-km and 50-km spatial resolutions using commonly employed aggregation schemes. Estimates were made at each grid cell for climate variables including daily solar radiation, air temperature, humidity, and precipitation. The topographic structure, water holding capacity, vegetation type and leaf area index were likewise estimated for initial conditions. The daily time series for the climatic drivers was developed from interpolations of meteorological station data for the water year 1990 (1 October 1989-30 September 1990). Model outputs at the 1-km resolution showed good agreement with observed patterns in runoff and productivity. The ranges for model inputs at the 10-km and 50-km resolutions tended to contract because of the smoothed topography. Estimates for mean evapotranspiration and runoff were relatively insensitive to changing the spatial resolution of the grid whereas estimates of mean annual net primary production varied by 11%. The designation of a vegetation type and leaf area at the 50-km resolution often subsumed significant heterogeneity in vegetation, and this factor accounted for much of the difference in the mean values for the carbon flux variables. Although area wide means for model outputs were generally similar across resolutions, difference maps often revealed large areas of disagreement. Relatively high spatial resolution analyses of biogeochemical cycling are desirable from several perspectives and may be particularly important in the study of the potential impacts of climate change.

Regularization design for high-quality cone-beam CT of intracranial hemorrhage using statistical reconstruction

NASA Astrophysics Data System (ADS)

Dang, H.; Stayman, J. W.; Xu, J.; Sisniega, A.; Zbijewski, W.; Wang, X.; Foos, D. H.; Aygun, N.; Koliatsos, V. E.; Siewerdsen, J. H.

2016-03-01

Intracranial hemorrhage (ICH) is associated with pathologies such as hemorrhagic stroke and traumatic brain injury. Multi-detector CT is the current front-line imaging modality for detecting ICH (fresh blood contrast 40-80 HU, down to 1 mm). Flat-panel detector (FPD) cone-beam CT (CBCT) offers a potential alternative with a smaller scanner footprint, greater portability, and lower cost potentially well suited to deployment at the point of care outside standard diagnostic radiology and emergency room settings. Previous studies have suggested reliable detection of ICH down to 3 mm in CBCT using high-fidelity artifact correction and penalized weighted least-squared (PWLS) image reconstruction with a post-artifact-correction noise model. However, ICH reconstructed by traditional image regularization exhibits nonuniform spatial resolution and noise due to interaction between the statistical weights and regularization, which potentially degrades the detectability of ICH. In this work, we propose three regularization methods designed to overcome these challenges. The first two compute spatially varying certainty for uniform spatial resolution and noise, respectively. The third computes spatially varying regularization strength to achieve uniform "detectability," combining both spatial resolution and noise in a manner analogous to a delta-function detection task. Experiments were conducted on a CBCT test-bench, and image quality was evaluated for simulated ICH in different regions of an anthropomorphic head. The first two methods improved the uniformity in spatial resolution and noise compared to traditional regularization. The third exhibited the highest uniformity in detectability among all methods and best overall image quality. The proposed regularization provides a valuable means to achieve uniform image quality in CBCT of ICH and is being incorporated in a CBCT prototype for ICH imaging.

Modeling the Distribution of African Savanna Elephants in Kruger National Park: AN Application of Multi-Scale GLOBELAND30 Data

NASA Astrophysics Data System (ADS)

Xu, W.; Hays, B.; Fayrer-Hosken, R.; Presotto, A.

2016-06-01

The ability of remote sensing to represent ecologically relevant features at multiple spatial scales makes it a powerful tool for studying wildlife distributions. Species of varying sizes perceive and interact with their environment at differing scales; therefore, it is important to consider the role of spatial resolution of remotely sensed data in the creation of distribution models. The release of the Globeland30 land cover classification in 2014, with its 30 m resolution, presents the opportunity to do precisely that. We created a series of Maximum Entropy distribution models for African savanna elephants (Loxodonta africana) using Globeland30 data analyzed at varying resolutions. We compared these with similarly re-sampled models created from the European Space Agency's Global Land Cover Map (Globcover). These data, in combination with GIS layers of topography and distance to roads, human activity, and water, as well as elephant GPS collar data, were used with MaxEnt software to produce the final distribution models. The AUC (Area Under the Curve) scores indicated that the models created from 600 m data performed better than other spatial resolutions and that the Globeland30 models generally performed better than the Globcover models. Additionally, elevation and distance to rivers seemed to be the most important variables in our models. Our results demonstrate that Globeland30 is a valid alternative to the well-established Globcover for creating wildlife distribution models. It may even be superior for applications which require higher spatial resolution and less nuanced classifications.

Sharpening Ejecta Patterns: Investigating Spectral Fidelity After Controlled Intensity-Hue-Saturation Image Fusion of LROC Images of Fresh Craters

NASA Astrophysics Data System (ADS)

Awumah, A.; Mahanti, P.; Robinson, M. S.

2017-12-01

Image fusion is often used in Earth-based remote sensing applications to merge spatial details from a high-resolution panchromatic (Pan) image with the color information from a lower-resolution multi-spectral (MS) image, resulting in a high-resolution multi-spectral image (HRMS). Previously, the performance of six well-known image fusion methods were compared using Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) and Wide Angle Camera (WAC) images (1). Results showed the Intensity-Hue-Saturation (IHS) method provided the best spatial performance, but deteriorated the spectral content. In general, there was a trade-off between spatial enhancement and spectral fidelity from the fusion process; the more spatial details from the Pan fused with the MS image, the more spectrally distorted the final HRMS. In this work, we control the amount of spatial details fused (from the LROC NAC images to WAC images) using a controlled IHS method (2), to investigate the spatial variation in spectral distortion on fresh crater ejecta. In the controlled IHS method (2), the percentage of the Pan component merged with the MS is varied. The percent of spatial detail from the Pan used is determined by a variable whose value may be varied between 1 (no Pan utilized) to infinity (entire Pan utilized). An HRMS color composite image (red=415nm, green=321/415nm, blue=321/360nm (3)) was used to assess performance (via visual inspection and metric-based evaluations) at each tested value of the control parameter (1 to 10—after which spectral distortion saturates—in 0.01 increments) within three regions: crater interiors, ejecta blankets, and the background material surrounding the craters. Increasing the control parameter introduced increased spatial sharpness and spectral distortion in all regions, but to varying degrees. Crater interiors suffered the most color distortion, while ejecta experienced less color distortion. The controlled IHS method is therefore desirable for resolution-enhancement of fresh crater ejecta; larger values of the control parameter may be used to sharpen MS images of ejecta patterns but with less impact to color distortion than in the uncontrolled IHS fusion process. References: (1) Prasun et. al (2016) ISPRS. (2) Choi, Myungjin (2006) IEEE. (3) Denevi et. al (2014) JGR.

The Effect Of Pixel Size On The Detection Rate Of Early Pulmonary Sarcoidosis In Digital Chest Radiographic Systems

NASA Astrophysics Data System (ADS)

MacMahon, Heber; Vyborny, Carl; Powell, Gregory; Doi, Kunio; Metz, Charles E.

1984-08-01

In digital radiography the pixel size used determines the potential spatial resolution of the system. The need for spatial resolution varies depending on the subject matter imaged. In many areas, including the chest, the minimum spatial resolution requirements have not been determined. Sarcoidosis is a disease which frequently causes subtle interstitial infiltrates in the lungs. As the initial step in an investigation designed to determine the minimum pixel size required in digital chest radiographic systems, we have studied 1 mm pixel digitized images on patients with early pulmonary sarcoidosis. The results of this preliminary study suggest that neither mild interstitial pulmonary infiltrates nor other abnormalities such as pneumothoraces may be detected reliably with 1 mm pixel digital images.

High-Resolution Large Field-of-View FUV Compact Camera

NASA Technical Reports Server (NTRS)

Spann, James F.

2006-01-01

The need for a high resolution camera with a large field of view and capable to image dim emissions in the far-ultraviolet is driven by the widely varying intensities of FUV emissions and spatial/temporal scales of phenomena of interest in the Earth% ionosphere. In this paper, the concept of a camera is presented that is designed to achieve these goals in a lightweight package with sufficient visible light rejection to be useful for dayside and nightside emissions. The camera employs the concept of self-filtering to achieve good spectral resolution tuned to specific wavelengths. The large field of view is sufficient to image the Earth's disk at Geosynchronous altitudes and capable of a spatial resolution of >20 km. The optics and filters are emphasized.

Contrasting landform perception with varied radar illumination geometries and at simulated resolutions of Venera and Magellan

NASA Technical Reports Server (NTRS)

Ford, J. P.; Arvidson, R. E.

1989-01-01

The high sensitivity of imaging radars to slope at moderate to low incidence angles enhances the perception of linear topography on images. It reveals broad spatial patterns that are essential to landform mapping and interpretation. As radar responses are strongly directional, the ability to discriminate linear features on images varies with their orientation. Landforms that appear prominent on images where they are transverse to the illumination may be obscure to indistinguishable on images where they are parallel to it. Landform detection is also influenced by the spatial resolution in radar images. Seasat radar images of the Gran Desierto Dunes complex, Sonora, Mexico; the Appalachian Valley and Ridge Province; and accreted terranes in eastern interior Alaska were processed to simulate both Venera 15 and 16 images (1000 to 3000 km resolution) and image data expected from the Magellan mission (120 to 300 m resolution. The Gran Desierto Dunes are not discernable in the Venera simulation, whereas the higher resolution Magellan simulation shows dominant dune patterns produced from differential erosion of the rocks. The Magellan simulation also shows that fluvial processes have dominated erosion and exposure of the folds.

Influence of spatiotemporally distributed irradiance data input on temperature evolution in parabolic trough solar field simulations

NASA Astrophysics Data System (ADS)

Bubolz, K.; Schenk, H.; Hirsch, T.

2016-05-01

Concentrating solar field operation is affected by shadowing through cloud movement. For line focusing systems the impact of varying irradiance has been studied before by several authors with simulations of relevant thermodynamics assuming spatially homogeneous irradiance or using artificial test signals. While today's simulation capabilities allow more and more a higher spatiotemporal resolution of plant processes there are only few studies on influence of spatially distributed irradiance due to lack of available data. Based on recent work on generating real irradiance maps with high spatial resolution this paper demonstrates their influence on solar field thermodynamics. For a case study an irradiance time series is chosen. One solar field section with several loops and collecting header is modeled for simulation purpose of parabolic trough collectors and oil as heat transfer medium. Assuming homogeneous mass flow distribution among all loops we observe spatially varying temperature characteristics. They are analysed without and with mass flow control and their impact on solar field control design is discussed. Finally, the potential of distributed irradiance data is outlined.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Graesser, Jordan B; Cheriyadat, Anil M; Vatsavai, Raju

The high rate of global urbanization has resulted in a rapid increase in informal settlements, which can be de ned as unplanned, unauthorized, and/or unstructured housing. Techniques for ef ciently mapping these settlement boundaries can bene t various decision making bodies. From a remote sensing perspective, informal settlements share unique spatial characteristics that distinguish them from other types of structures (e.g., industrial, commercial, and formal residential). These spatial characteristics are often captured in high spatial resolution satellite imagery. We analyzed the role of spatial, structural, and contextual features (e.g., GLCM, Histogram of Oriented Gradients, Line Support Regions, Lacunarity) for urbanmore » neighborhood mapping, and computed several low-level image features at multiple scales to characterize local neighborhoods. The decision parameters to classify formal-, informal-, and non-settlement classes were learned under Decision Trees and a supervised classi cation framework. Experiments were conducted on high-resolution satellite imagery from the CitySphere collection, and four different cities (i.e., Caracas, Kabul, Kandahar, and La Paz) with varying spatial characteristics were represented. Overall accuracy ranged from 85% in La Paz, Bolivia, to 92% in Kandahar, Afghanistan. While the disparities between formal and informal neighborhoods varied greatly, many of the image statistics tested proved robust.« less

Matrix recrystallization for MALDI-MS imaging of maize lipids at high-spatial resolution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Duenas, Maria Emilia; Carlucci, Laura; Lee, Young Jin

Matrix recrystallization is optimized and applied to improve lipid ion signals in maize embryos and leaves. A systematic study was performed varying solvent and incubation time. During this study, unexpected side reactions were found when methanol was used as a recrystallization solvent, resulting in the formation of a methyl ester of phosphatidic acid. Furthermore, using an optimum recrystallization condition with isopropanol, there is no apparent delocalization demonstrated with a transmission electron microscopy (TEM) pattern and maize leaf images obtained at 10 μm spatial resolution.

Matrix recrystallization for MALDI-MS imaging of maize lipids at high-spatial resolution

DOE PAGES

Duenas, Maria Emilia; Carlucci, Laura; Lee, Young Jin

2016-06-27

Matrix recrystallization is optimized and applied to improve lipid ion signals in maize embryos and leaves. A systematic study was performed varying solvent and incubation time. During this study, unexpected side reactions were found when methanol was used as a recrystallization solvent, resulting in the formation of a methyl ester of phosphatidic acid. Furthermore, using an optimum recrystallization condition with isopropanol, there is no apparent delocalization demonstrated with a transmission electron microscopy (TEM) pattern and maize leaf images obtained at 10 μm spatial resolution.

Matrix Recrystallization for MALDI-MS Imaging of Maize Lipids at High-Spatial Resolution

NASA Astrophysics Data System (ADS)

Dueñas, Maria Emilia; Carlucci, Laura; Lee, Young Jin

2016-09-01

Matrix recrystallization is optimized and applied to improve lipid ion signals in maize embryos and leaves. A systematic study was performed varying solvent and incubation time. During this study, unexpected side reactions were found when methanol was used as a recrystallization solvent, resulting in the formation of a methyl ester of phosphatidic acid. Using an optimum recrystallization condition with isopropanol, there is no apparent delocalization demonstrated with a transmission electron microscopy (TEM) pattern and maize leaf images obtained at 10 μm spatial resolution.

Matrix Recrystallization for MALDI-MS Imaging of Maize Lipids at High-Spatial Resolution.

PubMed

Dueñas, Maria Emilia; Carlucci, Laura; Lee, Young Jin

2016-09-01

Matrix recrystallization is optimized and applied to improve lipid ion signals in maize embryos and leaves. A systematic study was performed varying solvent and incubation time. During this study, unexpected side reactions were found when methanol was used as a recrystallization solvent, resulting in the formation of a methyl ester of phosphatidic acid. Using an optimum recrystallization condition with isopropanol, there is no apparent delocalization demonstrated with a transmission electron microscopy (TEM) pattern and maize leaf images obtained at 10 μm spatial resolution. Graphical Abstract ᅟ.

Attenuated total reflection-Fourier transform infrared imaging of large areas using inverted prism crystals and combining imaging and mapping.

PubMed

Chan, K L Andrew; Kazarian, Sergei G

2008-10-01

Attenuated total reflection-Fourier transform infrared (ATR-FT-IR) imaging is a very useful tool for capturing chemical images of various materials due to the simple sample preparation and the ability to measure wet samples or samples in an aqueous environment. However, the size of the array detector used for image acquisition is often limited and there is usually a trade off between spatial resolution and the field of view (FOV). The combination of mapping and imaging can be used to acquire images with a larger FOV without sacrificing spatial resolution. Previous attempts have demonstrated this using an infrared microscope and a Germanium hemispherical ATR crystal to achieve images of up to 2.5 mm x 2.5 mm but with varying spatial resolution and depth of penetration across the imaged area. In this paper, we demonstrate a combination of mapping and imaging with a different approach using an external optics housing for large ATR accessories and inverted ATR prisms to achieve ATR-FT-IR images with a large FOV and reasonable spatial resolution. The results have shown that a FOV of 10 mm x 14 mm can be obtained with a spatial resolution of approximately 40-60 microm when using an accessory that gives no magnification. A FOV of 1.3 mm x 1.3 mm can be obtained with spatial resolution of approximately 15-20 microm when using a diamond ATR imaging accessory with 4x magnification. No significant change in image quality such as spatial resolution or depth of penetration has been observed across the whole FOV with this method and the measurement time was approximately 15 minutes for an image consisting of 16 image tiles.

Volumetric CT with sparse detector arrays (and application to Si-strip photon counters).

PubMed

Sisniega, A; Zbijewski, W; Stayman, J W; Xu, J; Taguchi, K; Fredenberg, E; Lundqvist, Mats; Siewerdsen, J H

2016-01-07

Novel x-ray medical imaging sensors, such as photon counting detectors (PCDs) and large area CCD and CMOS cameras can involve irregular and/or sparse sampling of the detector plane. Application of such detectors to CT involves undersampling that is markedly different from the commonly considered case of sparse angular sampling. This work investigates volumetric sampling in CT systems incorporating sparsely sampled detectors with axial and helical scan orbits and evaluates performance of model-based image reconstruction (MBIR) with spatially varying regularization in mitigating artifacts due to sparse detector sampling. Volumetric metrics of sampling density and uniformity were introduced. Penalized-likelihood MBIR with a spatially varying penalty that homogenized resolution by accounting for variations in local sampling density (i.e. detector gaps) was evaluated. The proposed methodology was tested in simulations and on an imaging bench based on a Si-strip PCD (total area 5 cm  ×  25 cm) consisting of an arrangement of line sensors separated by gaps of up to 2.5 mm. The bench was equipped with translation/rotation stages allowing a variety of scanning trajectories, ranging from a simple axial acquisition to helical scans with variable pitch. Statistical (spherical clutter) and anthropomorphic (hand) phantoms were considered. Image quality was compared to that obtained with a conventional uniform penalty in terms of structural similarity index (SSIM), image uniformity, spatial resolution, contrast, and noise. Scan trajectories with intermediate helical width (~10 mm longitudinal distance per 360° rotation) demonstrated optimal tradeoff between the average sampling density and the homogeneity of sampling throughout the volume. For a scan trajectory with 10.8 mm helical width, the spatially varying penalty resulted in significant visual reduction of sampling artifacts, confirmed by a 10% reduction in minimum SSIM (from 0.88 to 0.8) and a 40% reduction in the dispersion of SSIM in the volume compared to the constant penalty (both penalties applied at optimal regularization strength). Images of the spherical clutter and wrist phantoms confirmed the advantages of the spatially varying penalty, showing a 25% improvement in image uniformity and 1.8  ×  higher CNR (at matched spatial resolution) compared to the constant penalty. The studies elucidate the relationship between sampling in the detector plane, acquisition orbit, sampling of the reconstructed volume, and the resulting image quality. They also demonstrate the benefit of spatially varying regularization in MBIR for scenarios with irregular sampling patterns. Such findings are important and integral to the incorporation of a sparsely sampled Si-strip PCD in CT imaging.

Volumetric CT with sparse detector arrays (and application to Si-strip photon counters)

NASA Astrophysics Data System (ADS)

Sisniega, A.; Zbijewski, W.; Stayman, J. W.; Xu, J.; Taguchi, K.; Fredenberg, E.; Lundqvist, Mats; Siewerdsen, J. H.

2016-01-01

Novel x-ray medical imaging sensors, such as photon counting detectors (PCDs) and large area CCD and CMOS cameras can involve irregular and/or sparse sampling of the detector plane. Application of such detectors to CT involves undersampling that is markedly different from the commonly considered case of sparse angular sampling. This work investigates volumetric sampling in CT systems incorporating sparsely sampled detectors with axial and helical scan orbits and evaluates performance of model-based image reconstruction (MBIR) with spatially varying regularization in mitigating artifacts due to sparse detector sampling. Volumetric metrics of sampling density and uniformity were introduced. Penalized-likelihood MBIR with a spatially varying penalty that homogenized resolution by accounting for variations in local sampling density (i.e. detector gaps) was evaluated. The proposed methodology was tested in simulations and on an imaging bench based on a Si-strip PCD (total area 5 cm  ×  25 cm) consisting of an arrangement of line sensors separated by gaps of up to 2.5 mm. The bench was equipped with translation/rotation stages allowing a variety of scanning trajectories, ranging from a simple axial acquisition to helical scans with variable pitch. Statistical (spherical clutter) and anthropomorphic (hand) phantoms were considered. Image quality was compared to that obtained with a conventional uniform penalty in terms of structural similarity index (SSIM), image uniformity, spatial resolution, contrast, and noise. Scan trajectories with intermediate helical width (~10 mm longitudinal distance per 360° rotation) demonstrated optimal tradeoff between the average sampling density and the homogeneity of sampling throughout the volume. For a scan trajectory with 10.8 mm helical width, the spatially varying penalty resulted in significant visual reduction of sampling artifacts, confirmed by a 10% reduction in minimum SSIM (from 0.88 to 0.8) and a 40% reduction in the dispersion of SSIM in the volume compared to the constant penalty (both penalties applied at optimal regularization strength). Images of the spherical clutter and wrist phantoms confirmed the advantages of the spatially varying penalty, showing a 25% improvement in image uniformity and 1.8  ×  higher CNR (at matched spatial resolution) compared to the constant penalty. The studies elucidate the relationship between sampling in the detector plane, acquisition orbit, sampling of the reconstructed volume, and the resulting image quality. They also demonstrate the benefit of spatially varying regularization in MBIR for scenarios with irregular sampling patterns. Such findings are important and integral to the incorporation of a sparsely sampled Si-strip PCD in CT imaging.

Volumetric CT with sparse detector arrays (and application to Si-strip photon counters)

PubMed Central

Sisniega, A; Zbijewski, W; Stayman, J W; Xu, J; Taguchi, K; Fredenberg, E; Lundqvist, Mats; Siewerdsen, J H

2016-01-01

Novel x-ray medical imaging sensors, such as photon counting detectors (PCDs) and large area CCD and CMOS cameras can involve irregular and/or sparse sampling of the detector plane. Application of such detectors to CT involves undersampling that is markedly different from the commonly considered case of sparse angular sampling. This work investigates volumetric sampling in CT systems incorporating sparsely sampled detectors with axial and helical scan orbits and evaluates performance of model-based image reconstruction (MBIR) with spatially varying regularization in mitigating artifacts due to sparse detector sampling. Volumetric metrics of sampling density and uniformity were introduced. Penalized-likelihood MBIR with a spatially varying penalty that homogenized resolution by accounting for variations in local sampling density (i.e. detector gaps) was evaluated. The proposed methodology was tested in simulations and on an imaging bench based on a Si-strip PCD (total area 5 cm × 25 cm) consisting of an arrangement of line sensors separated by gaps of up to 2.5 mm. The bench was equipped with translation/rotation stages allowing a variety of scanning trajectories, ranging from a simple axial acquisition to helical scans with variable pitch. Statistical (spherical clutter) and anthropomorphic (hand) phantoms were considered. Image quality was compared to that obtained with a conventional uniform penalty in terms of structural similarity index (SSIM), image uniformity, spatial resolution, contrast, and noise. Scan trajectories with intermediate helical width (~10 mm longitudinal distance per 360° rotation) demonstrated optimal tradeoff between the average sampling density and the homogeneity of sampling throughout the volume. For a scan trajectory with 10.8 mm helical width, the spatially varying penalty resulted in significant visual reduction of sampling artifacts, confirmed by a 10% reduction in minimum SSIM (from 0.88 to 0.8) and a 40% reduction in the dispersion of SSIM in the volume compared to the constant penalty (both penalties applied at optimal regularization strength). Images of the spherical clutter and wrist phantoms confirmed the advantages of the spatially varying penalty, showing a 25% improvement in image uniformity and 1.8 × higher CNR (at matched spatial resolution) compared to the constant penalty. The studies elucidate the relationship between sampling in the detector plane, acquisition orbit, sampling of the reconstructed volume, and the resulting image quality. They also demonstrate the benefit of spatially varying regularization in MBIR for scenarios with irregular sampling patterns. Such findings are important and integral to the incorporation of a sparsely sampled Si-strip PCD in CT imaging. PMID:26611740

Evaluating the Impact of Spatial Resolution of Landsat Predictors on the Accuracy of Biomass Models for Large-area Estimation Across the Eastern USA

NASA Astrophysics Data System (ADS)

Deo, R. K.; Domke, G. M.; Russell, M.; Woodall, C. W.

2017-12-01

Landsat data have been widely used to support strategic forest inventory and management decisions despite the limited success of passive optical remote sensing for accurate estimation of aboveground biomass (AGB). The archive of publicly available Landsat data, available at 30-m spatial resolutions since 1984, has been a valuable resource for cost-effective large-area estimation of AGB to inform national requirements such as for the US national greenhouse gas inventory (NGHGI). In addition, other optical satellite data such as MODIS imagery of wider spatial coverage and higher temporal resolution are enriching the domain of spatial predictors for regional scale mapping of AGB. Because NGHGIs require national scale AGB information and there are tradeoffs in the prediction accuracy versus operational efficiency of Landsat, this study evaluated the impact of various resolutions of Landsat predictors on the accuracy of regional AGB models across three different sites in the eastern USA: Maine, Pennsylvania-New Jersey, and South Carolina. We used recent national forest inventory (NFI) data with numerous Landsat-derived predictors at ten different spatial resolutions ranging from 30 to 1000 m to understand the optimal spatial resolution of the optical data for enhanced spatial inventory of AGB for NGHGI reporting. Ten generic spatial models at different spatial resolutions were developed for all sites and large-area estimates were evaluated (i) at the county-level against the independent designed-based estimates via the US NFI Evalidator tool and (ii) within a large number of strips ( 1 km wide) predicted via LiDAR metrics at a high spatial resolution. The county-level estimates by the Evalidator and Landsat models were statistically equivalent and produced coefficients of determination (R2) above 0.85 that varied with sites and resolution of predictors. The mean and standard deviation of county-level estimates followed increasing and decreasing trends, respectively, with models of decreasing resolutions. The Landsat-based total AGB estimates within the strips against the total AGB obtained using LiDAR metrics did not differ significantly and were within ±15 Mg/ha for each of the sites. We conclude that the optical satellite data at resolutions up to 1000 m provide acceptable accuracy for the US' NGHGI.

Scaling effects on spring phenology detections from MODIS data at multiple spatial resolutions over the contiguous United States

NASA Astrophysics Data System (ADS)

Peng, Dailiang; Zhang, Xiaoyang; Zhang, Bing; Liu, Liangyun; Liu, Xinjie; Huete, Alfredo R.; Huang, Wenjiang; Wang, Siyuan; Luo, Shezhou; Zhang, Xiao; Zhang, Helin

2017-10-01

Land surface phenology (LSP) has been widely retrieved from satellite data at multiple spatial resolutions, but the spatial scaling effects on LSP detection are poorly understood. In this study, we collected enhanced vegetation index (EVI, 250 m) from collection 6 MOD13Q1 product over the contiguous United States (CONUS) in 2007 and 2008, and generated a set of multiple spatial resolution EVI data by resampling 250 m to 2 × 250 m and 3 × 250 m, 4 × 250 m, …, 35 × 250 m. These EVI time series were then used to detect the start of spring season (SOS) at various spatial resolutions. Further the SOS variation across scales was examined at each coarse resolution grid (35 × 250 m ≈ 8 km, refer to as reference grid) and ecoregion. Finally, the SOS scaling effects were associated with landscape fragment, proportion of primary land cover type, and spatial variability of seasonal greenness variation within each reference grid. The results revealed the influences of satellite spatial resolutions on SOS retrievals and the related impact factors. Specifically, SOS significantly varied lineally or logarithmically across scales although the relationship could be either positive or negative. The overall SOS values averaged from spatial resolutions between 250 m and 35 × 250 m at large ecosystem regions were generally similar with a difference less than 5 days, while the SOS values within the reference grid could differ greatly in some local areas. Moreover, the standard deviation of SOS across scales in the reference grid was less than 5 days in more than 70% of area over the CONUS, which was smaller in northeastern than in southern and western regions. The SOS scaling effect was significantly associated with heterogeneity of vegetation properties characterized using land landscape fragment, proportion of primary land cover type, and spatial variability of seasonal greenness variation, but the latter was the most important impact factor.

High Resolution PET Imaging Probe for the Detection, Molecular Characterization and Treatment Monitoring of Prostate Cancer

DTIC Science & Technology

2012-07-01

Jitter results from electronic noise and from the fact that the shape of the detector signal used for timing can vary considerably depending on the...photomultiplier technology, several “probe” detectors were developed. It was predicted, and subsequently shown, that probes having good position...high spatial resolution for prostate imaging. Practical proof-of-concept detectors with good depth-of-interactions resolution have been developed and

Evaluating the influence of spatial resolution of Landsat predictors on the accuracy of biomass models for large-area estimation across the eastern USA

NASA Astrophysics Data System (ADS)

Deo, Ram K.; Domke, Grant M.; Russell, Matthew B.; Woodall, Christopher W.; Andersen, Hans-Erik

2018-05-01

Aboveground biomass (AGB) estimates for regional-scale forest planning have become cost-effective with the free access to satellite data from sensors such as Landsat and MODIS. However, the accuracy of AGB predictions based on passive optical data depends on spatial resolution and spatial extent of target area as fine resolution (small pixels) data are associated with smaller coverage and longer repeat cycles compared to coarse resolution data. This study evaluated various spatial resolutions of Landsat-derived predictors on the accuracy of regional AGB models at three different sites in the eastern USA: Maine, Pennsylvania-New Jersey, and South Carolina. We combined national forest inventory data with Landsat-derived predictors at spatial resolutions ranging from 30–1000 m to understand the optimal spatial resolution of optical data for large-area (regional) AGB estimation. Ten generic models were developed using the data collected in 2014, 2015 and 2016, and the predictions were evaluated (i) at the county-level against the estimates of the USFS Forest Inventory and Analysis Program which relied on EVALIDator tool and national forest inventory data from the 2009–2013 cycle and (ii) within a large number of strips (~1 km wide) predicted via LiDAR metrics at 30 m spatial resolution. The county-level estimates by the EVALIDator and Landsat models were highly related (R 2 > 0.66), although the R 2 varied significantly across sites and resolution of predictors. The mean and standard deviation of county-level estimates followed increasing and decreasing trends, respectively, with models of coarser resolution. The Landsat-based total AGB estimates were larger than the LiDAR-based total estimates within the strips, however the mean of AGB predictions by LiDAR were mostly within one-standard deviations of the mean predictions obtained from the Landsat-based model at any of the resolutions. We conclude that satellite data at resolutions up to 1000 m provide acceptable accuracy for continental scale analysis of AGB.

Land use change detection based on multi-date imagery from different satellite sensor systems

NASA Technical Reports Server (NTRS)

Stow, Douglas A.; Collins, Doretta; Mckinsey, David

1990-01-01

An empirical study is conducted to assess the accuracy of land use change detection using satellite image data acquired ten years apart by sensors with differing spatial resolutions. The primary goals of the investigation were to (1) compare standard change detection methods applied to image data of varying spatial resolution, (2) assess whether to transform the raster grid of the higher resolution image data to that of the lower resolution raster grid or vice versa in the registration process, (3) determine if Landsat/Thermatic Mapper or SPOT/High Resolution Visible multispectral data provide more accurate detection of land use changes when registered to historical Landsat/MSS data. It is concluded that image ratioing of multisensor, multidate satellite data produced higher change detection accuracies than did principal components analysis, and that it is useful as a land use change enhancement method.

Differential Deposition Technique for Figure Corrections in Grazing Incidence X-ray Optics

NASA Technical Reports Server (NTRS)

Kilaru, Kiranmayee; Ramsey, Brian D.; Gubarev, Mikhail

2009-01-01

A differential deposition technique is being developed to correct the low- and mid-spatial-frequency deviations in the axial figure profile of Wolter type grazing incidence X-ray optics. These deviations arise due to various factors in the fabrication process and they degrade the performance of the optics by limiting the achievable angular resolution. In the differential deposition technique, material of varying thickness is selectively deposited along the length of the optic to minimize these deviations, thereby improving the overall figure. High resolution focusing optics being developed at MSFC for small animal radionuclide imaging are being coated to test the differential deposition technique. The required spatial resolution for these optics is 100 m. This base resolution is achievable with the regular electroform-nickel-replication fabrication technique used at MSFC. However, by improving the figure quality of the optics through differential deposition, we aim at significantly improving the resolution beyond this value.

Status of the Geostationary Spectrograph (GeoSpec) for Earth and Atmospheric Science Applications

NASA Technical Reports Server (NTRS)

Janz, Scott; Hilsenrath, Ernest; Mount, G.; Brune, W.; Heath, D.

2004-01-01

GeoSpec will support future satellite mission concepts in the Atmospheric Sciences and in Land and Ocean Sciences by providing time-resolved measurements of both chemically linked atmospheric trace gas concentrations of important molecules such as O3, NO2, CH2O and SO2 and at the same time coastal and ocean pollution events, tidal effects, and the origin and evolution of aerosol plumes. The instrument design concept in development is a dual spectrograph covering the WMS wavelength region of 310-500 nm and the VIS/NIR wavelength region of 480-900 nm coupled to all reflective telescope and high sensitivity PIN/CMOS area detector. The goal of the project is to demonstrate a system capable of making moderate spatial resolution (750 meters at nadir) hyperspectral measurements (0.6 to 1.2 nm resolution) from a geostationary orbit. This would enable studies of time-varying pollution and coastal change processes with a temporal resolution of 5 minutes on a regional scale to 1 hour on a continental scale. Other spatial resolutions can be supported by varying the focal length of the input telescope. Scientific rationale and instrument design and status will be presented.

Comparison of NDVI fields obtained from different remote sensors

NASA Astrophysics Data System (ADS)

Escribano Rodriguez, Juan; Alonso, Carmelo; Tarquis, Ana Maria; Benito, Rosa Maria; Hernandez Díaz-Ambrona, Carlos

2013-04-01

Satellite image data have become an important source of information for monitoring vegetation and mapping land cover at several scales. Beside this, the distribution and phenology of vegetation is largely associated with climate, terrain characteristics and human activity. Various vegetation indices have been developed for qualitative and quantitative assessment of vegetation using remote spectral measurements. In particular, sensors with spectral bands in the red (RED) and near-infrared (NIR) lend themselves well to vegetation monitoring and based on them [(NIR - RED) / (NIR + RED)] Normalized Difference Vegetation Index (NDVI) has been widespread used. Given that the characteristics of spectral bands in RED and NIR vary distinctly from sensor to sensor, NDVI values based on data from different instruments will not be directly comparable. The spatial resolution also varies significantly between sensors, as well as within a given scene in the case of wide-angle and oblique sensors. As a result, NDVI values will vary according to combinations of the heterogeneity and scale of terrestrial surfaces and pixel footprint sizes. Therefore, the question arises as to the impact of differences in spectral and spatial resolutions on vegetation indices like the NDVI and their interpretation as a drought index. During 2012 three locations (at Salamanca, Granada and Córdoba) were selected and a periodic pasture monitoring and botanic composition were achieved. Daily precipitation, temperature and monthly soil water content were measurement as well as fresh and dry pasture weight. At the same time, remote sensing images were capture by DEIMOS-1 and MODIS of the chosen places. DEIMOS-1 is based on the concept Microsat-100 from Surrey. It is conceived for obtaining Earth images with a good enough resolution to study the terrestrial vegetation cover (20x20 m), although with a great range of visual field (600 km) in order to obtain those images with high temporal resolution and at a reduced cost. By contranst, MODIS images present a much lower spatial resolution (500x500 m). The aim of this study is to establish a comparison between two different sensors in their NDVI values at different spatial resolutions. Acknowledgements. This work was partially supported by ENESA under project P10 0220C-823. Funding provided by Spanish Ministerio de Ciencia e Innovación (MICINN) through project no. MTM2009-14621 and i-MATH No. CSD2006-00032 is greatly appreciated.

Soccer Offside Judgments in Laypersons with Different Types of Static Displays

PubMed Central

Wühr, Peter; Fasold, Frowin; Memmert, Daniel

2015-01-01

Four experiments investigated offside decisions in laypersons with different types of static displays. Previous research neglected this group although the majority of assistant referees in soccer games at the amateur level are laypersons. The aims of our research were (a) to investigate the spatial resolution in laypersons’ perception of offside situations, (b) to search for biases in laypersons’ offside judgments, and (c) to develop useful displays for future research. The displays showed the moment when a midfielder passes the ball to a forward moving in the vicinity of a defender. We varied the spatial location of the forward around the defender in eleven steps and participants made their offside decision by pressing a key. Across experiments, displays varied in abstractness (simple shapes, clipart figures, photographs). There were two major findings. Firstly, both accuracy and speed of offside judgments deteriorated when the spatial distance between forward and defender decreased, approaching guessing rate at the smallest distances. Secondly, participants showed a consistent bias in favor of the non-offside response, in contrast to most studies on professional assistant referees. In sum, the results highlight the limited spatial resolution of the visual system and underscore the role of response bias in offside-judgment tasks. PMID:26252653

Evaluation and Validation of Aboveground Techniques for Coating Condition Assessment

DOT National Transportation Integrated Search

2006-02-28

The overall objective was to determine the accuracy, resolution, and limitations of equipment typically used for modern aboveground ECDA work with respect to locating holidays and disbondments with commonly used coatings with varying spatial relation...

Spectral characteristics of background error covariance and multiscale data assimilation

DOE PAGES

Li, Zhijin; Cheng, Xiaoping; Gustafson, Jr., William I.; ...

2016-05-17

The steady increase of the spatial resolutions of numerical atmospheric and oceanic circulation models has occurred over the past decades. Horizontal grid spacing down to the order of 1 km is now often used to resolve cloud systems in the atmosphere and sub-mesoscale circulation systems in the ocean. These fine resolution models encompass a wide range of temporal and spatial scales, across which dynamical and statistical properties vary. In particular, dynamic flow systems at small scales can be spatially localized and temporarily intermittent. Difficulties of current data assimilation algorithms for such fine resolution models are numerically and theoretically examined. Ourmore » analysis shows that the background error correlation length scale is larger than 75 km for streamfunctions and is larger than 25 km for water vapor mixing ratios, even for a 2-km resolution model. A theoretical analysis suggests that such correlation length scales prevent the currently used data assimilation schemes from constraining spatial scales smaller than 150 km for streamfunctions and 50 km for water vapor mixing ratios. Moreover, our results highlight the need to fundamentally modify currently used data assimilation algorithms for assimilating high-resolution observations into the aforementioned fine resolution models. Lastly, within the framework of four-dimensional variational data assimilation, a multiscale methodology based on scale decomposition is suggested and challenges are discussed.« less

A space-time multiscale modelling of Earth's gravity field variations

NASA Astrophysics Data System (ADS)

Wang, Shuo; Panet, Isabelle; Ramillien, Guillaume; Guilloux, Frédéric

2017-04-01

The mass distribution within the Earth varies over a wide range of spatial and temporal scales, generating variations in the Earth's gravity field in space and time. These variations are monitored by satellites as the GRACE mission, with a 400 km spatial resolution and 10 days to 1 month temporal resolution. They are expressed in the form of gravity field models, often with a fixed spatial or temporal resolution. The analysis of these models allows us to study the mass transfers within the Earth system. Here, we have developed space-time multi-scale models of the gravity field, in order to optimize the estimation of gravity signals resulting from local processes at different spatial and temporal scales, and to adapt the time resolution of the model to its spatial resolution according to the satellites sampling. For that, we first build a 4D wavelet family combining spatial Poisson wavelets with temporal Haar wavelets. Then, we set-up a regularized inversion of inter-satellites gravity potential differences in a bayesian framework, to estimate the model parameters. To build the prior, we develop a spectral analysis, localized in time and space, of geophysical models of mass transport and associated gravity variations. Finally, we test our approach to the reconstruction of space-time variations of the gravity field due to hydrology. We first consider a global distribution of observations along the orbit, from a simplified synthetic hydrology signal comprising only annual variations at large spatial scales. Then, we consider a regional distribution of observations in Africa, and a larger number of spatial and temporal scales. We test the influence of an imperfect prior and discuss our results.

Synthesis and Photochromic Properties of Configurationally Varied Azobenzene Glycosides

PubMed Central

Chandrasekaran, Vijayanand; Johannes, Eugen; Kobarg, Hauke; Sönnichsen, Frank D; Lindhorst, Thisbe K

2014-01-01

Spatial orientation of carbohydrates is a meaningful parameter in carbohydrate recognition processes. To vary orientation of sugars with temporal and spatial resolution, photosensitive glycoconjugates with favorable photochromic properties appear to be opportune. Here, a series of azobenzene glycosides were synthesized, employing glycoside synthesis and Mills reaction, to allow “switching” of carbohydrate orientation by reversible E/Z isomerization of the azobenzene N=N double bond. Their photochromic properties were tested and effects of azobenzene substitution as well as the effect of anomeric configuration and the orientation of the sugars 2-hydroxy group were evaluated. PMID:25050228

Applications of Fractal Analytical Techniques in the Estimation of Operational Scale

NASA Technical Reports Server (NTRS)

Emerson, Charles W.; Quattrochi, Dale A.

2000-01-01

The observational scale and the resolution of remotely sensed imagery are essential considerations in the interpretation process. Many atmospheric, hydrologic, and other natural and human-influenced spatial phenomena are inherently scale dependent and are governed by different physical processes at different spatial domains. This spatial and operational heterogeneity constrains the ability to compare interpretations of phenomena and processes observed in higher spatial resolution imagery to similar interpretations obtained from lower resolution imagery. This is a particularly acute problem, since longterm global change investigations will require high spatial resolution Earth Observing System (EOS), Landsat 7, or commercial satellite data to be combined with lower resolution imagery from older sensors such as Landsat TM and MSS. Fractal analysis is a useful technique for identifying the effects of scale changes on remotely sensed imagery. The fractal dimension of an image is a non-integer value between two and three which indicates the degree of complexity in the texture and shapes depicted in the image. A true fractal surface exhibits self-similarity, a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution, and the slope of the fractal dimension-resolution relationship would be zero. Most geographical phenomena, however, are not self-similar at all scales, but they can be modeled by a stochastic fractal in which the scaling properties of the image exhibit patterns that can be described by statistics such as area-perimeter ratios and autocovariances. Stochastic fractal sets relax the self-similarity assumption and measure many scales and resolutions to represent the varying form of a phenomenon as the pixel size is increased in a convolution process. We have observed that for images of homogeneous land covers, the fractal dimension varies linearly with changes in resolution or pixel size over the range of past, current, and planned space-borne sensors. This relationship differs significantly in images of agricultural, urban, and forest land covers, with urban areas retaining the same level of complexity, forested areas growing smoother, and agricultural areas growing more complex as small pixels are aggregated into larger, mixed pixels. Images of scenes having a mixture of land covers have fractal dimensions that exhibit a non-linear, complex relationship to pixel size. Measuring the fractal dimension of a difference image derived from two images of the same area obtained on different dates showed that the fractal dimension increased steadily, then exhibited a sharp decrease at increasing levels of pixel aggregation. This breakpoint of the fractal dimension/resolution plot is related to the spatial domain or operational scale of the phenomenon exhibiting the predominant visible difference between the two images (in this case, mountain snow cover). The degree to which an image departs from a theoretical ideal fractal surface provides clues as to how much information is altered or lost in the processes of rescaling and rectification. The measured fractal dimension of complex, composite land covers such as urban areas also provides a useful textural index that can assist image classification of complex scenes.

Superresolution parallel magnetic resonance imaging: Application to functional and spectroscopic imaging

PubMed Central

Otazo, Ricardo; Lin, Fa-Hsuan; Wiggins, Graham; Jordan, Ramiro; Sodickson, Daniel; Posse, Stefan

2009-01-01

Standard parallel magnetic resonance imaging (MRI) techniques suffer from residual aliasing artifacts when the coil sensitivities vary within the image voxel. In this work, a parallel MRI approach known as Superresolution SENSE (SURE-SENSE) is presented in which acceleration is performed by acquiring only the central region of k-space instead of increasing the sampling distance over the complete k-space matrix and reconstruction is explicitly based on intra-voxel coil sensitivity variation. In SURE-SENSE, parallel MRI reconstruction is formulated as a superresolution imaging problem where a collection of low resolution images acquired with multiple receiver coils are combined into a single image with higher spatial resolution using coil sensitivities acquired with high spatial resolution. The effective acceleration of conventional gradient encoding is given by the gain in spatial resolution, which is dictated by the degree of variation of the different coil sensitivity profiles within the low resolution image voxel. Since SURE-SENSE is an ill-posed inverse problem, Tikhonov regularization is employed to control noise amplification. Unlike standard SENSE, for which acceleration is constrained to the phase-encoding dimension/s, SURE-SENSE allows acceleration along all encoding directions — for example, two-dimensional acceleration of a 2D echo-planar acquisition. SURE-SENSE is particularly suitable for low spatial resolution imaging modalities such as spectroscopic imaging and functional imaging with high temporal resolution. Application to echo-planar functional and spectroscopic imaging in human brain is presented using two-dimensional acceleration with a 32-channel receiver coil. PMID:19341804

Third version of vendor-specific model-based iterativereconstruction (Veo 3.0): evaluation of CT image quality in the abdomen using new noise reduction presets and varied slice optimization.

PubMed

Telesmanich, Morgan E; Jensen, Corey T; Enriquez, Jose L; Wagner-Bartak, Nicolaus A; Liu, Xinming; Le, Ott; Wei, Wei; Chandler, Adam G; Tamm, Eric P

2017-08-01

To qualitatively and quantitatively compare abdominal CT images reconstructed with a newversion of model-based iterative reconstruction (Veo 3.0; GE Healthcare Waukesha, WI) utilizing varied presetsof resolution preference, noise reduction and slice optimization. This retrospective study was approved by our Institutional Review Board and was Health Insurance Portability and Accountability Act compliant. The raw datafrom 30 consecutive patients who had undergone CT abdomen scanning were used to reconstructfour clinical presets of 3.75mm axial images using Veo 3.0: 5% resolution preference (RP05n), 5%noise reduction (NR05) and 40% noise reduction (NR40) with new 3.75mm "sliceoptimization," as well as one set using RP05 with conventional 0.625mm "slice optimization" (RP05c). The images were reviewed by two independent readers in a blinded, randomized manner using a 5-point Likert scale as well as a 5-point comparative scale. Multiple two-dimensional circular regions of interest were defined for noise and contrast-to-noise ratio measurements. Line profiles were drawn across the 7 lp cm -1 bar pattern of the Catphan 600 phantom for evaluation of spatial resolution. The NR05 image set was ranked as the best series in overall image quality (mean difference inrank 0.48, 95% CI [0.081-0.88], p = 0.01) and with specific reference to liver evaluation (meandifference 0.46, 95% CI [0.030-0.89], p = 0.03), when compared with the secondbest series ineach category. RP05n was ranked as the best for bone evaluation. NR40 was ranked assignificantly inferior across all assessed categories. Although the NR05 and RP05c image setshad nearly the same contrast-to-noise ratio and spatial resolution, NR05 was generally preferred. Image noise and spatial resolution increased along a spectrum with RP05n the highest and NR40the lowest. Compared to RP05n, the average noise was 21.01% lower for NR05, 26.88%lower for RP05c and 50.86% lower for NR40. Veo 3.0 clinical presets allow for selection of image noise and spatial resolution balance; for contrast-enhanced CT evaluation of the abdomen, the 5% noise reduction preset with 3.75 mm slice optimization (NR05) was generally ranked superior qualitatively and, relative to other series, was in the middle of the spectrum with reference to image noise and spatial resolution. Advances in knowledge: To our knowledge, this is the first study of Veo 3.0 noise reduction presets and varied slice optimization. This study provides insight into the behaviour of slice optimization and documents the degree of noise reduction and spatial resolution changes that users can expect across various Veo 3.0 clinical presets. These results provide important parameters to guide preset selection for both clinical and research purposes.

Dual Double-Wedge Pseudo-Depolarizer with Anamorphic PSF

NASA Technical Reports Server (NTRS)

Hill, Peter; Thompson, Patrick

2012-01-01

A polarized scene, which may occur at oblique illumination angles, creates a radiometric signal that varies as a function of viewing angle. One common optical component that is used to minimize such an effect is a polarization scrambler or depolarizer. As part of the CLARREO mission, the SOLARIS instrument project at Goddard Space Flight Center has developed a new class of polarization scramblers using a dual double-wedge pseudo-depolarizer that produces an anamorphic point spread function (PSF). The SOLARIS instrument uses two Wollaston type scramblers in series, each with a distinct wedge angle, to image a pseudo-depolarized scene that is free of eigenstates. Since each wedge is distinct, the scrambler is able to produce an anamorphic PSF that maintains high spatial resolution in one dimension by sacrificing the spatial resolution in the other dimension. This scrambler geometry is ideal for 1-D imagers, such as pushbroom slit spectrometers, which require high spectral resolution, high spatial resolution, and low sensitivity to polarized light. Moreover, the geometry is applicable to a wide range of scientific instruments that require both high SNR (signal-to-noise ratio) and low sensitivity to polarized scenes

A distance-driven deconvolution method for CT image-resolution improvement

NASA Astrophysics Data System (ADS)

Han, Seokmin; Choi, Kihwan; Yoo, Sang Wook; Yi, Jonghyon

2016-12-01

The purpose of this research is to achieve high spatial resolution in CT (computed tomography) images without hardware modification. The main idea is to consider geometry optics model, which can provide the approximate blurring PSF (point spread function) kernel, which varies according to the distance from the X-ray tube to each point. The FOV (field of view) is divided into several band regions based on the distance from the X-ray source, and each region is deconvolved with a different deconvolution kernel. As the number of subbands increases, the overshoot of the MTF (modulation transfer function) curve increases first. After that, the overshoot begins to decrease while still showing a larger MTF than the normal FBP (filtered backprojection). The case of five subbands seems to show balanced performance between MTF boost and overshoot minimization. It can be seen that, as the number of subbands increases, the noise (STD) can be seen to show a tendency to decrease. The results shows that spatial resolution in CT images can be improved without using high-resolution detectors or focal spot wobbling. The proposed algorithm shows promising results in improving spatial resolution while avoiding excessive noise boost.

Estimating Carbon Storage and Sequestration by Urban Trees at Multiple Spatial Resolutions

NASA Astrophysics Data System (ADS)

Wu, J.; Tran, A.; Liao, A.

2010-12-01

Urban forests are an important component of urban-suburban environments. Urban trees provide not only a full range of social and psychological benefits to city dwellers, but also valuable ecosystem services to communities, such as removing atmospheric carbon dioxide, improving air quality, and reducing storm water runoff. There is an urgent need for developing strategic conservation plans for environmentally sustainable urban-suburban development based on the scientific understanding of the extent and function of urban forests. However, several challenges remain to accurately quantify various environmental benefits provided by urban trees, among which is to deal with the effect of changing spatial resolution and/or scale. In this study, we intended to examine the uncertainties of carbon storage and sequestration associated with the tree canopy coverage of different spatial resolutions. Multi-source satellite imagery data were acquired for the City of Fullerton, located in Orange County of California. The tree canopy coverage of the study area was classified at three spatial resolutions, ranging from 30 m (Landsat-5 Thematic Mapper), 15 m (Advanced Spaceborne Thermal Emission and Reflection Radiometer), to 2.5 m (QuickBird). We calculated the amount of carbon stored in the trees represented on the individual tree coverage maps and the annual carbon taken up by the trees with a model (i.e., CITYgreen) developed by the U.S. Forest Service. The results indicate that urban trees account for significant proportions of land cover in the study area even with the low spatial resolution data. The estimated carbon fixation benefits vary greatly depending on the details of land use and land cover classification. The extrapolation of estimation from the fine-resolution stand-level to the low-resolution landscape-scale will likely not preserve reasonable accuracy.

Area-to-point regression kriging for pan-sharpening

NASA Astrophysics Data System (ADS)

Wang, Qunming; Shi, Wenzhong; Atkinson, Peter M.

2016-04-01

Pan-sharpening is a technique to combine the fine spatial resolution panchromatic (PAN) band with the coarse spatial resolution multispectral bands of the same satellite to create a fine spatial resolution multispectral image. In this paper, area-to-point regression kriging (ATPRK) is proposed for pan-sharpening. ATPRK considers the PAN band as the covariate. Moreover, ATPRK is extended with a local approach, called adaptive ATPRK (AATPRK), which fits a regression model using a local, non-stationary scheme such that the regression coefficients change across the image. The two geostatistical approaches, ATPRK and AATPRK, were compared to the 13 state-of-the-art pan-sharpening approaches summarized in Vivone et al. (2015) in experiments on three separate datasets. ATPRK and AATPRK produced more accurate pan-sharpened images than the 13 benchmark algorithms in all three experiments. Unlike the benchmark algorithms, the two geostatistical solutions precisely preserved the spectral properties of the original coarse data. Furthermore, ATPRK can be enhanced by a local scheme in AATRPK, in cases where the residuals from a global regression model are such that their spatial character varies locally.

Scaling properties of Arctic sea ice deformation in high-resolution viscous-plastic sea ice models and satellite observations

NASA Astrophysics Data System (ADS)

Hutter, Nils; Losch, Martin; Menemenlis, Dimitris

2017-04-01

Sea ice models with the traditional viscous-plastic (VP) rheology and very high grid resolution can resolve leads and deformation rates that are localised along Linear Kinematic Features (LKF). In a 1-km pan-Arctic sea ice-ocean simulation, the small scale sea-ice deformations in the Central Arctic are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS). A new coupled scaling analysis for data on Eulerian grids determines the spatial and the temporal scaling as well as the coupling between temporal and spatial scales. The spatial scaling of the modelled sea ice deformation implies multi-fractality. The spatial scaling is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling and its coupling to temporal scales with satellite observations and models with the modern elasto-brittle rheology challenges previous results with VP models at coarse resolution where no such scaling was found. The temporal scaling analysis, however, shows that the VP model does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.

Downscaling remotely sensed imagery using area-to-point cokriging and multiple-point geostatistical simulation

NASA Astrophysics Data System (ADS)

Tang, Yunwei; Atkinson, Peter M.; Zhang, Jingxiong

2015-03-01

A cross-scale data integration method was developed and tested based on the theory of geostatistics and multiple-point geostatistics (MPG). The goal was to downscale remotely sensed images while retaining spatial structure by integrating images at different spatial resolutions. During the process of downscaling, a rich spatial correlation model in the form of a training image was incorporated to facilitate reproduction of similar local patterns in the simulated images. Area-to-point cokriging (ATPCK) was used as locally varying mean (LVM) (i.e., soft data) to deal with the change of support problem (COSP) for cross-scale integration, which MPG cannot achieve alone. Several pairs of spectral bands of remotely sensed images were tested for integration within different cross-scale case studies. The experiment shows that MPG can restore the spatial structure of the image at a fine spatial resolution given the training image and conditioning data. The super-resolution image can be predicted using the proposed method, which cannot be realised using most data integration methods. The results show that ATPCK-MPG approach can achieve greater accuracy than methods which do not account for the change of support issue.

Assessing the resolution-dependent utility of tomograms for geostatistics

USGS Publications Warehouse

Day-Lewis, F. D.; Lane, J.W.

2004-01-01

Geophysical tomograms are used increasingly as auxiliary data for geostatistical modeling of aquifer and reservoir properties. The correlation between tomographic estimates and hydrogeologic properties is commonly based on laboratory measurements, co-located measurements at boreholes, or petrophysical models. The inferred correlation is assumed uniform throughout the interwell region; however, tomographic resolution varies spatially due to acquisition geometry, regularization, data error, and the physics underlying the geophysical measurements. Blurring and inversion artifacts are expected in regions traversed by few or only low-angle raypaths. In the context of radar traveltime tomography, we derive analytical models for (1) the variance of tomographic estimates, (2) the spatially variable correlation with a hydrologic parameter of interest, and (3) the spatial covariance of tomographic estimates. Synthetic examples demonstrate that tomograms of qualitative value may have limited utility for geostatistics; moreover, the imprint of regularization may preclude inference of meaningful spatial statistics from tomograms.

Slitless Solar Spectroscopy

NASA Technical Reports Server (NTRS)

Davila, Joseph M.; Jones, Sahela

2011-01-01

Spectrographs have traditionally suffered from the inability to obtain line intensities, widths, and Doppler shifts over large spatial regions of the Sun quickly because of the narrow instantaneous field of view. This has limited the spectroscopic analysis of rapidly varying solar features like, flares, CME eruptions, coronal jets, and reconnection regions. Imagers have provided high time resolution images of the full Sun with limited spectral resolution. In this paper we present recent advances in deconvolving spectrally dispersed images obtained through broad slits. We use this new theoretical formulation to examine the effectiveness of various potential observing scenarios, spatial and spectral resolutions, signal to noise ratio, and other instrument characteristics. This information will lay the foundation for a new generation of spectral imagers optimized for slitless spectral operation, while retaining the ability to obtain spectral information in transient solar events.

Time-Optimized High-Resolution Readout-Segmented Diffusion Tensor Imaging

PubMed Central

Reishofer, Gernot; Koschutnig, Karl; Langkammer, Christian; Porter, David; Jehna, Margit; Enzinger, Christian; Keeling, Stephen; Ebner, Franz

2013-01-01

Readout-segmented echo planar imaging with 2D navigator-based reacquisition is an uprising technique enabling the sampling of high-resolution diffusion images with reduced susceptibility artifacts. However, low signal from the small voxels and long scan times hamper the clinical applicability. Therefore, we introduce a regularization algorithm based on total variation that is applied directly on the entire diffusion tensor. The spatially varying regularization parameter is determined automatically dependent on spatial variations in signal-to-noise ratio thus, avoiding over- or under-regularization. Information about the noise distribution in the diffusion tensor is extracted from the diffusion weighted images by means of complex independent component analysis. Moreover, the combination of those features enables processing of the diffusion data absolutely user independent. Tractography from in vivo data and from a software phantom demonstrate the advantage of the spatially varying regularization compared to un-regularized data with respect to parameters relevant for fiber-tracking such as Mean Fiber Length, Track Count, Volume and Voxel Count. Specifically, for in vivo data findings suggest that tractography results from the regularized diffusion tensor based on one measurement (16 min) generates results comparable to the un-regularized data with three averages (48 min). This significant reduction in scan time renders high resolution (1×1×2.5 mm3) diffusion tensor imaging of the entire brain applicable in a clinical context. PMID:24019951

The effects of spatial sampling choices on MR temperature measurements.

PubMed

Todd, Nick; Vyas, Urvi; de Bever, Josh; Payne, Allison; Parker, Dennis L

2011-02-01

The purpose of this article is to quantify the effects that spatial sampling parameters have on the accuracy of magnetic resonance temperature measurements during high intensity focused ultrasound treatments. Spatial resolution and position of the sampling grid were considered using experimental and simulated data for two different types of high intensity focused ultrasound heating trajectories (a single point and a 4-mm circle) with maximum measured temperature and thermal dose volume as the metrics. It is demonstrated that measurement accuracy is related to the curvature of the temperature distribution, where regions with larger spatial second derivatives require higher resolution. The location of the sampling grid relative temperature distribution has a significant effect on the measured values. When imaging at 1.0 × 1.0 × 3.0 mm(3) resolution, the measured values for maximum temperature and volume dosed to 240 cumulative equivalent minutes (CEM) or greater varied by 17% and 33%, respectively, for the single-point heating case, and by 5% and 18%, respectively, for the 4-mm circle heating case. Accurate measurement of the maximum temperature required imaging at 1.0 × 1.0 × 3.0 mm(3) resolution for the single-point heating case and 2.0 × 2.0 × 5.0 mm(3) resolution for the 4-mm circle heating case. Copyright © 2010 Wiley-Liss, Inc.

Influence of Scale Effect and Model Performance in Downscaling ASTER Land Surface Temperatures to a Very High Spatial Resolution in an Agricultural Area

NASA Astrophysics Data System (ADS)

Zhou, J.; Li, G.; Liu, S.; Zhan, W.; Zhang, X.

2015-12-01

At present land surface temperatures (LSTs) can be generated from thermal infrared remote sensing with spatial resolutions from ~100 m to tens of kilometers. However, LSTs with high spatial resolution, e.g. tens of meters, are still lack. The purpose of LST downscaling is to generate LSTs with finer spatial resolutions than their native spatial resolutions. The statistical linear or nonlinear regression models are most frequently used for LST downscaling. The basic assumption of these models is the scale-invariant relationships between LST and its descriptors, which is questioned but rare researches have been reported. In addition, few researches can be found for downscaling satellite LST or TIR data to a high spatial resolution, i.e. better than 100 m or even finer. The lack of LST with high spatial resolution cannot satisfy the requirements of applications such as evapotranspiration mapping at the field scale. By selecting a dynamically developing agricultural oasis as the study area, the aim of this study is to downscale the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) LSTs to 15 m, to satisfy the requirement of evapotranspiration mapping at the field scale. Twelve ASTER images from May to September in 2012, covering the entire growth stage of maize, were selected. Four statistical models were evaluated, including one global model, one piecewise model, and two local models. The influence from scale effect in downscaling LST was quantified. The downscaled LSTs are evaluated from accuracy and image quality. Results demonstrate that the influence from scale effect varies according to models and the maize growth stage. Significant influence about -4 K to 6 K existed at the early stage and weaker influence existed in the middle stage. When compared with the ground measured LSTs, the downscaled LSTs resulted from the global and local models yielded higher accuracies and better image qualities than the local models. In addition to the vegetation indices, the surface albedo is an important descriptor for downscaling LST through explaining its spatial variation induced by soil moisture.

Spatial variations of the Sr I 4607 Å scattering polarization peak

NASA Astrophysics Data System (ADS)

Bianda, M.; Berdyugina, S.; Gisler, D.; Ramelli, R.; Belluzzi, L.; Carlin, E. S.; Stenflo, J. O.; Berkefeld, T.

2018-06-01

Context. The scattering polarization signal observed in the photospheric Sr I 4607 Å line is expected to vary at granular spatial scales. This variation can be due to changes in the magnetic field intensity and orientation (Hanle effect), but also to spatial and temporal variations in the plasma properties. Measuring the spatial variation of such polarization signal would allow us to study the properties of the magnetic fields at subgranular scales, but observations are challenging since both high spatial resolution and high spectropolarimetric sensitivity are required. Aims: We aim to provide observational evidence of the polarization peak spatial variations, and to analyze the correlation they might have with granulation. Methods: Observations conjugating high spatial resolution and high spectropolarimetric precision were performed with the Zurich IMaging POLarimeter, ZIMPOL, at the GREGOR solar telescope, taking advantage of the adaptive optics system and the newly installed image derotator. Results: Spatial variations of the scattering polarization in the Sr I 4607 Å line are clearly observed. The spatial scale of these variations is comparable with the granular size. Small correlations between the polarization signal amplitude and the continuum intensity indicate that the polarization is higher at the center of granules than in the intergranular lanes.

Snow depth spatial structure from hillslope to basin scale

NASA Astrophysics Data System (ADS)

Deems, J. S.

2017-12-01

Knowledge of spatial patterns of snow accumulation is required for understanding the hydrology, climatology, and ecology of mountain regions. Spatial structure in snow accumulation patterns changes with the scale of observation, a feature that has been characterized using fractal dimensions calculated from lidar-derived snow depth maps: fractal scaling structure at short length scales, with a `scale break' transition to more stochastic patterns at longer separation distances. Previous work has shown that this fractal structure of snow depth distributions differs between sites with different vegetation and terrain characteristics. Forested areas showed a transition to a nearly random spatial distribution at a much shorter lag distance than do unforested sites, enabling a statistical characterization. Alpine areas, however, showed strong spatial structure for a much wider scale range, and were the source of the dominant spatial pattern observable over a wider area. These spatial structure characteristics suggest that the choice of measurement or model resolution (satellite sensor, DEM, field survey point spacing, etc.) will strongly affect the estimates of snow volume or mass, as well as the magnitude of spatial variability. These prior efforts used data sets that were high resolution ( 1 m laser point spacing) but of limited extent ( 1 km2), constraining detection of scale features such as fractal dimension or scale breaks to areas of relatively similar characteristics and to lag distances of under 500 m. New datasets available from the NASA JPL Airborne Snow Observatory (ASO) provide similar resolution but over large areas, enabling assessment of snow spatial structure across an entire watershed, or in similar vegetation or physiography but in different parts of the basin. Additionally, the multi-year ASO time series allows an investigation into the temporal stability of these scale characteristics, within a single snow season and between seasons of strongly varying accumulation totals and patterns. This presentation will explore initial results from this study, using data from the Tuolumne River Basin in California, USA. Fractal scaling characteristics derived from ASO lidar snow depth measurements are examined at the basin scale, as well as in varying topographic and forest cover environments.

Next Generation Snow Cover Mapping: Can Future Hyperspectral Satellite Spectrometer Systems Improve Subpixel Snow-covered Area and Grain Size in the Sierra Nevada?

NASA Astrophysics Data System (ADS)

Hill, R.; Calvin, W. M.; Harpold, A.

2017-12-01

Mountain snow storage is the dominant source of water for humans and ecosystems in western North America. Consequently, the spatial distribution of snow-covered area is fundamental to both hydrological, ecological, and climate models. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were collected along the entire Sierra Nevada mountain range extending from north of Lake Tahoe to south of Mt. Whitney during the 2015 and 2016 snow-covered season. The AVIRIS dataset used in this experiment consists of 224 contiguous spectral channels with wavelengths ranging 400-2500 nanometers at a 15-meter spatial pixel size. Data from the Sierras were acquired on four days: 2/24/15 during a very low snow year, 3/24/16 near maximum snow accumulation, and 5/12/16 and 5/18/16 during snow ablation and snow loss. Building on previous retrieval of subpixel snow-covered area algorithms that take into account varying grain size we present a model that analyzes multiple endmembers of varying snow grain size, vegetation, rock, and soil in segmented regions along the Sierra Nevada to determine snow-cover spatial extent, snow sub-pixel fraction, and approximate grain size. In addition, varying simulated models of the data will compare and contrast the retrieval of current snow products such as MODIS Snow-Covered Area and Grain Size (MODSCAG) and the Airborne Space Observatory (ASO). Specifically, does lower spatial resolution (MODIS), broader resolution bandwidth (MODIS), and limited spectral resolution (ASO) affect snow-cover area and grain size approximations? The implications of our findings will help refine snow mapping products for planned hyperspectral satellite spectrometer systems such as EnMAP (slated to launch in 2019), HISUI (planned for inclusion on the International Space Station in 2018), and HyspIRI (currently under consideration).

Study of the central part of Mare Moscoviense by combining near-infrared spectrometer, SIR-2 and Hyper Spectral Imager (HySI) data onboard Chandrayaan-1

NASA Astrophysics Data System (ADS)

Upendra Bhatt, Megha; Mall, Urs; Bugiolacchi, Roberto; Bhattacharya, Satadru

2010-05-01

The impact basins on lunar surface act as a window into the lunar interior and allow investigations of the composition of lower crust and upper mantle. Mare Moscoviense is one of the oldest impact basins on the far side of the Moon. We report on our preliminary analysis conducted in the central region of Mare Moscoviense using the near-infrared spectrometer, SIR-2 data in combination with the Hyperspectral Imager (HySI) data from the Chandrayaan-1 mission. SIR-2 is a compact, monolithic grating type point spectrometer which collected data with high spatial resolution (~200 m) and spectral resolution (6 nm) at wavelengths between 0.93 to 2.41 µm. The Indian HySI instrument mapped the lunar surface in the spectral range of 0.42 to 0.96 µm in 64 contiguous bands with a spectral bandwidth ~20 nm and spatial resolution of 80 m. We will explain the method of combining the response of SIR-2 and HySI to get a complete spectral coverage from 0.42-2.40 µm with high spatial and spectral resolution. We compare average reflectance spectra for spatially, spectrally and compositionally varying areas with the published literature.

Vegetation Greenness and Its Drivers across Ice-free Greenland

NASA Astrophysics Data System (ADS)

Pedersen, S. H.; Liston, G. E.; Tamstorf, M. P.; Schmidt, N. M.

2017-12-01

The coastal and mountain areas surrounding the Greenland Ice Sheet cover one-fifth of Greenland. This ice-free area spans more than 20 degrees latitude and includes high-, low-, and sub-Arctic climate zones and the terrain varies from sea level to 3700 m elevation. Hence, this area contains a wide range of vegetation growing conditions associated with precipitation, temperature, and incoming solar radiation found across these latitudinal, elevational, and coast-inland gradients. In this study, we mapped the spatial distribution of vegetation at 300-m spatial resolution across ice-free Greenland using the annual maximum vegetation greenness (MaxNDVI) and the timing of MaxNDVI derived from daily Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance data from 2000-2015. Further, we investigated the drivers of the annual MaxNDVI and its timing across the diverse vegetation growing conditions in Greenland using modeled climatic variables, including snow quantity and timing, at the same temporal and spatial resolutions. The annual average MaxNDVI varied between 0.3 and 0.5 in North Greenland, and 0.6 and 0.9 in South Greenland. The timing of MaxNDVI differed more than two weeks between North and South Greenland. The potential growing season, e.g., the period with no snow on the ground, was as short as one month in North Greenland (mainly August), and four to five times longer in South Greenland (typically starting in mid-May). The snow-free date varied with elevation, from valley bottoms to the mountain tops, having the same range that existed from South to North Greenland. Our results show that MaxNDVI and its timing are significantly driven by the timing of snow-free ground and the amount of meltwater available from the snowpack during spring snowmelt.

Fast Time-Varying Volume Rendering Using Time-Space Partition (TSP) Tree

NASA Technical Reports Server (NTRS)

Shen, Han-Wei; Chiang, Ling-Jen; Ma, Kwan-Liu

1999-01-01

We present a new, algorithm for rapid rendering of time-varying volumes. A new hierarchical data structure that is capable of capturing both the temporal and the spatial coherence is proposed. Conventional hierarchical data structures such as octrees are effective in characterizing the homogeneity of the field values existing in the spatial domain. However, when treating time merely as another dimension for a time-varying field, difficulties frequently arise due to the discrepancy between the field's spatial and temporal resolutions. In addition, treating spatial and temporal dimensions equally often prevents the possibility of detecting the coherence that is unique in the temporal domain. Using the proposed data structure, our algorithm can meet the following goals. First, both spatial and temporal coherence are identified and exploited for accelerating the rendering process. Second, our algorithm allows the user to supply the desired error tolerances at run time for the purpose of image-quality/rendering-speed trade-off. Third, the amount of data that are required to be loaded into main memory is reduced, and thus the I/O overhead is minimized. This low I/O overhead makes our algorithm suitable for out-of-core applications.

Temporally resolved proton radiography of rapidly varying electric and magnetic fields in laser-driven capacitor coil targets

NASA Astrophysics Data System (ADS)

Morace, A.; Santos, J. J.; Bailly-Grandvaux, M.; Ehret, M.; Alpinaniz, J.; Brabetz, C.; Schaumann, G.; Volpe, L.

2017-02-01

Understanding the dynamics of rapidly varying electromagnetic fields in intense short pulse laser plasma interactions is of key importance to understand the mechanisms at the basis of a wide variety of physical processes, from high energy density physics and fusion science to the development of ultrafast laser plasma devices to control laser-generated particle beams. Target normal sheath accelerated (TNSA) proton radiography represents an ideal tool to diagnose ultrafast electromagnetic phenomena, providing 2D spatially and temporally resolved radiographs with temporal resolution varying from 2-3 ps to few tens of ps. In this work we introduce the proton radiography technique and its application to diagnose the spatial and temporal evolution of electromagnetic fields in laser-driven capacitor coil targets.

Retinal specialization through spatially varying cell densities and opsin coexpression in cichlid fish.

PubMed

Dalton, Brian E; de Busserolles, Fanny; Marshall, N Justin; Carleton, Karen L

2017-01-15

The distinct behaviours of animals and the varied habitats in which animals live place different requirements on their visual systems. A trade-off exists between resolution and sensitivity, with these properties varying across the retina. Spectral sensitivity, which affects both achromatic and chromatic (colour) vision, also varies across the retina, though the function of this inhomogeneity is less clear. We previously demonstrated spatially varying spectral sensitivity of double cones in the cichlid fish Metriaclima zebra owing to coexpression of different opsins. Here, we map the distributions of ganglion cells and cone cells and quantify opsin coexpression in single cones to show these also vary across the retina. We identify an area centralis with peak acuity and infrequent coexpression, which may be suited for tasks such as foraging and detecting male signals. The peripheral retina has reduced ganglion cell densities and increased opsin coexpression. Modeling of cichlid visual tasks indicates that coexpression might hinder colour discrimination of foraging targets and some fish colours. But, coexpression might improve contrast detection of dark objects against bright backgrounds, which might be useful for detecting predators or zooplankton. This suggests a trade-off between acuity and colour discrimination in the central retina versus lower resolution but more sensitive contrast detection in the peripheral retina. Significant variation in the pattern of coexpression among individuals, however, raises interesting questions about the selective forces at work. © 2017. Published by The Company of Biologists Ltd.

Mate choice in the eye and ear of the beholder? Female multimodal sensory configuration influences her preferences.

PubMed

Ronald, Kelly L; Fernández-Juricic, Esteban; Lucas, Jeffrey R

2018-05-16

A common assumption in sexual selection studies is that receivers decode signal information similarly. However, receivers may vary in how they rank signallers if signal perception varies with an individual's sensory configuration. Furthermore, receivers may vary in their weighting of different elements of multimodal signals based on their sensory configuration. This could lead to complex levels of selection on signalling traits. We tested whether multimodal sensory configuration could affect preferences for multimodal signals. We used brown-headed cowbird ( Molothrus ater ) females to examine how auditory sensitivity and auditory filters, which influence auditory spectral and temporal resolution, affect song preferences, and how visual spatial resolution and visual temporal resolution, which influence resolution of a moving visual signal, affect visual display preferences. Our results show that multimodal sensory configuration significantly affects preferences for male displays: females with better auditory temporal resolution preferred songs that were shorter, with lower Wiener entropy, and higher frequency; and females with better visual temporal resolution preferred males with less intense visual displays. Our findings provide new insights into mate-choice decisions and receiver signal processing. Furthermore, our results challenge a long-standing assumption in animal communication which can affect how we address honest signalling, assortative mating and sensory drive. © 2018 The Author(s).

Prevalence of pure versus mixed snow cover pixels across spatial resolutions in alpine environments: implications for binary and fractional remote sensing approaches

USGS Publications Warehouse

Selkowitz, David J.; Forster, Richard; Caldwell, Megan K.

2014-01-01

Remote sensing of snow-covered area (SCA) can be binary (indicating the presence/absence of snow cover at each pixel) or fractional (indicating the fraction of each pixel covered by snow). Fractional SCA mapping provides more information than binary SCA, but is more difficult to implement and may not be feasible with all types of remote sensing data. The utility of fractional SCA mapping relative to binary SCA mapping varies with the intended application as well as by spatial resolution, temporal resolution and period of interest, and climate. We quantified the frequency of occurrence of partially snow-covered (mixed) pixels at spatial resolutions between 1 m and 500 m over five dates at two study areas in the western U.S., using 0.5 m binary SCA maps derived from high spatial resolution imagery aggregated to fractional SCA at coarser spatial resolutions. In addition, we used in situ monitoring to estimate the frequency of partially snow-covered conditions for the period September 2013–August 2014 at 10 60-m grid cell footprints at two study areas with continental snow climates. Results from the image analysis indicate that at 40 m, slightly above the nominal spatial resolution of Landsat, mixed pixels accounted for 25%–93% of total pixels, while at 500 m, the nominal spatial resolution of MODIS bands used for snow cover mapping, mixed pixels accounted for 67%–100% of total pixels. Mixed pixels occurred more commonly at the continental snow climate site than at the maritime snow climate site. The in situ data indicate that some snow cover was present between 186 and 303 days, and partial snow cover conditions occurred on 10%–98% of days with snow cover. Four sites remained partially snow-free throughout most of the winter and spring, while six sites were entirely snow covered throughout most or all of the winter and spring. Within 60 m grid cells, the late spring/summer transition from snow-covered to snow-free conditions lasted 17–56 days and averaged 37 days. Our results suggest that mixed snow-covered snow-free pixels are common at the spatial resolutions imaged by both the Landsat and MODIS sensors. This highlights the additional information available from fractional SCA products and suggests fractional SCA can provide a major advantage for hydrological and climatological monitoring and modeling, particularly when accurate representation of the spatial distribution of snow cover is critical.

Peripheral resolution and contrast sensitivity: Effects of stimulus drift.

PubMed

Venkataraman, Abinaya Priya; Lewis, Peter; Unsbo, Peter; Lundström, Linda

2017-04-01

Optimal temporal modulation of the stimulus can improve foveal contrast sensitivity. This study evaluates the characteristics of the peripheral spatiotemporal contrast sensitivity function in normal-sighted subjects. The purpose is to identify a temporal modulation that can potentially improve the remaining peripheral visual function in subjects with central visual field loss. High contrast resolution cut-off for grating stimuli with four temporal frequencies (0, 5, 10 and 15Hz drift) was first evaluated in the 10° nasal visual field. Resolution contrast sensitivity for all temporal frequencies was then measured at four spatial frequencies between 0.5 cycles per degree (cpd) and the measured stationary cut-off. All measurements were performed with eccentric optical correction. Similar to foveal vision, peripheral contrast sensitivity is highest for a combination of low spatial frequency and 5-10Hz drift. At higher spatial frequencies, there was a decrease in contrast sensitivity with 15Hz drift. Despite this decrease, the resolution cut-off did not vary largely between the different temporal frequencies tested. Additional measurements of contrast sensitivity at 0.5 cpd and resolution cut-off for stationary (0Hz) and 7.5Hz stimuli performed at 10, 15, 20 and 25° in the nasal visual field also showed the same characteristics across eccentricities. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

High temporal resolution aerosol retrieval using Geostationary Ocean Color Imager: application and initial validation

NASA Astrophysics Data System (ADS)

Zhang, Yuhuan; Li, Zhengqiang; Zhang, Ying; Hou, Weizhen; Xu, Hua; Chen, Cheng; Ma, Yan

2014-01-01

The Geostationary Ocean Color Imager (GOCI) provides multispectral imagery of the East Asia region hourly from 9:00 to 16:00 local time (GMT+9) and collects multispectral imagery at eight spectral channels (412, 443, 490, 555, 660, 680, 745, and 865 nm) with a spatial resolution of 500 m. Thus, this technology brings significant advantages to high temporal resolution environmental monitoring. We present the retrieval of aerosol optical depth (AOD) in northern China based on GOCI data. Cross-calibration was performed against Moderate Resolution Imaging Spectrometer (MODIS) data in order to correct the land calibration bias of the GOCI sensor. AOD retrievals were then accomplished using a look-up table (LUT) strategy with assumptions of a quickly varying aerosol and a slowly varying surface with time. The AOD retrieval algorithm calculates AOD by minimizing the surface reflectance variations of a series of observations in a short period of time, such as several days. The monitoring of hourly AOD variations was implemented, and the retrieved AOD agreed well with AErosol RObotic NETwork (AERONET) ground-based measurements with a good R2 of approximately 0.74 at validation sites at the cities of Beijing and Xianghe, although intercept bias may be high in specific cases. The comparisons with MODIS products also show a good agreement in AOD spatial distribution. This work suggests that GOCI imagery can provide high temporal resolution monitoring of atmospheric aerosols over land, which is of great interest in climate change studies and environmental monitoring.

Spatiotemporal Pixelization to Increase the Recognition Score of Characters for Retinal Prostheses

PubMed Central

Kim, Hyun Seok; Park, Kwang Suk

2017-01-01

Most of the retinal prostheses use a head-fixed camera and a video processing unit. Some studies proposed various image processing methods to improve visual perception for patients. However, previous studies only focused on using spatial information. The present study proposes a spatiotemporal pixelization method mimicking fixational eye movements to generate stimulation images for artificial retina arrays by combining spatial and temporal information. Input images were sampled with a resolution that was four times higher than the number of pixel arrays. We subsampled this image and generated four different phosphene images. We then evaluated the recognition scores of characters by sequentially presenting phosphene images with varying pixel array sizes (6 × 6, 8 × 8 and 10 × 10) and stimulus frame rates (10 Hz, 15 Hz, 20 Hz, 30 Hz, and 60 Hz). The proposed method showed the highest recognition score at a stimulus frame rate of approximately 20 Hz. The method also significantly improved the recognition score for complex characters. This method provides a new way to increase practical resolution over restricted spatial resolution by merging the higher resolution image into high-frame time slots. PMID:29073735

Comparison of radar and gauge precipitation data in watershed models across varying spatial and temporal scales

EPA Science Inventory

Precipitation is a key control on watershed hydrologic modelling output, with errors in rainfall propagating through subsequent stages of water quantity and quality analysis. Most watershed models incorporate precipitation data from rain gauges; higher-resolution data sources are...

Multisource Imaging of Seasonal Dynamics in Land Surface Phenology Using Harmonized Landsat and Sentinel-2 Data

NASA Astrophysics Data System (ADS)

Melaas, E. K.; Graesser, J.; Friedl, M. A.

2017-12-01

Land surface phenology, including the timing of phenophase transitions and the entire seasonal cycle of surface reflectance and vegetation indices, is important for a myriad of applications including monitoring the response of terrestrial ecosystems to climate variability and extreme events, and land cover mapping. While methods to monitor and map phenology from coarse spatial resolution instruments such as MODIS are now relatively mature, the spatial resolution of these instruments is inadequate where vegetation properties, land use, and land cover vary at spatial scales of tens of meters. To address this need, algorithms to map phenology at moderate spatial resolution (30 m) using data from Landsat have recently been developed. However, the 16-day repeat cycle of Landsat presents significant challenges in regions where changes are rapid or where cloud cover reduces the frequency of clear-sky views. The European Space Agency's Sentinel-2 satellites, which are designed to provide moderate spatial resolution data at 5-day revisit frequency near the equator and 3 day revisit frequency in the mid-latitudes, will alleviate this constraint in many parts of the world. Here, we use harmonized time series of data from Sentinel-2A and Landsat OLI (HLS) to quantify the timing of land surface phenology metrics across a sample of deciduous forest and grassland-dominated sites, and then compare these estimates with co-located in situ observations. The resulting phenology maps demonstrate the improved information related to landscape-scale features that can be estimated from HLS data relative to comparable metrics from coarse spatial resolution instruments. For example, our results based on HLS data reveal spatial patterns in phenological metrics related to topographic and land cover controls that are not resolved in MODIS data, and show good agreement with transition dates observed from in situ measurements. Our results also show systematic bias toward earlier timing of spring, which is caused by inadequate density of observations that will be mitigated once data from Sentinel-2B are available. Overall, our results highlight the potential for using moderate spatial resolution data from Landsat and Sentinel-2 for developing operational phenology algorithms and products in support of the science community.

Combined effects of levels of protection and environmental variables at different spatial resolutions on fish assemblages in a marine protected area.

PubMed

Claudet, Joachim; García-Charton, José Antonio; Lenfant, Philippe

2011-02-01

The links between species-environment relations and species' responses to protection are unclear, but the objectives of marine protected areas (MPAs) are most likely to be achieved when those relations are known and inform MPA design. The components of a species' habitat vary with the spatial resolution of the area considered. We characterized areas at two resolutions: 250 m(2) (transect) and approximately 30,000 m(2) (seascape). We considered three categories of environmental variables: substrate type, bottom complexity, and depth. We sought to determine at which resolution habitat characteristics were a better predictor of abundance and species composition of fishes and whether the relations with environmental variables at either resolution affected species' responses to protection. Habitat features accounted for a larger proportion of spatial variation in species composition and abundances than differences in protection status. This spatial variation was explained best by habitat characteristics at the seascape level than at the transect level. Species' responses to protected areas were specific to particular seascape characteristics, primarily depth, and bottom complexity. Our method may be useful for prioritizing marine areas for protection, designing MPAs, and monitoring their effectiveness. It identified areas that provided natural shelter, areas acting as buffer zones, and areas where fish species were most responsive to protection. The identification of such areas is necessary for cost-effective establishment and monitoring of MPAs. ©2010 Society for Conservation Biology.

Vegetation cover in relation to socioeconomic factors in a tropical city assessed from sub-meter resolution imagery.

PubMed

Martinuzzi, Sebastián; Ramos-González, Olga M; Muñoz-Erickson, Tischa A; Locke, Dexter H; Lugo, Ariel E; Radeloff, Volker C

2018-04-01

Fine-scale information about urban vegetation and social-ecological relationships is crucial to inform both urban planning and ecological research, and high spatial resolution imagery is a valuable tool for assessing urban areas. However, urban ecology and remote sensing have largely focused on cities in temperate zones. Our goal was to characterize urban vegetation cover with sub-meter (<1 m) resolution aerial imagery, and identify social-ecological relationships of urban vegetation patterns in a tropical city, the San Juan Metropolitan Area, Puerto Rico. Our specific objectives were to (1) map vegetation cover using sub-meter spatial resolution (0.3-m) imagery, (2) quantify the amount of residential and non-residential vegetation, and (3) investigate the relationship between patterns of urban vegetation vs. socioeconomic and environmental factors. We found that 61% of the San Juan Metropolitan Area was green and that our combination of high spatial resolution imagery and object-based classification was highly successful for extracting vegetation cover in a moist tropical city (97% accuracy). In addition, simple spatial pattern analysis allowed us to separate residential from non-residential vegetation with 76% accuracy, and patterns of residential and non-residential vegetation varied greatly across the city. Both socioeconomic (e.g., population density, building age, detached homes) and environmental variables (e.g., topography) were important in explaining variations in vegetation cover in our spatial regression models. However, important socioeconomic drivers found in cities in temperate zones, such as income and home value, were not important in San Juan. Climatic and cultural differences between tropical and temperate cities may result in different social-ecological relationships. Our study provides novel information for local land use planners, highlights the value of high spatial resolution remote sensing data to advance ecological research and urban planning in tropical cities, and emphasizes the need for more studies in tropical cities. © 2017 by the Ecological Society of America.

Influence of Gridded Standoff Measurement Resolution on Numerical Bathymetric Inversion

NASA Astrophysics Data System (ADS)

Hesser, T.; Farthing, M. W.; Brodie, K.

2016-02-01

The bathymetry from the surfzone to the shoreline incurs frequent, active movement due to wave energy interacting with the seafloor. Methodologies to measure bathymetry range from point-source in-situ instruments, vessel-mounted single-beam or multi-beam sonar surveys, airborne bathymetric lidar, as well as inversion techniques from standoff measurements of wave processes from video or radar imagery. Each type of measurement has unique sources of error and spatial and temporal resolution and availability. Numerical bathymetry estimation frameworks can use these disparate data types in combination with model-based inversion techniques to produce a "best-estimate of bathymetry" at a given time. Understanding how the sources of error and varying spatial or temporal resolution of each data type affect the end result is critical for determining best practices and in turn increase the accuracy of bathymetry estimation techniques. In this work, we consider an initial step in the development of a complete framework for estimating bathymetry in the nearshore by focusing on gridded standoff measurements and in-situ point observations in model-based inversion at the U.S. Army Corps of Engineers Field Research Facility in Duck, NC. The standoff measurement methods return wave parameters computed using linear wave theory from the direct measurements. These gridded datasets can range in temporal and spatial resolution that do not match the desired model parameters and therefore could lead to a reduction in the accuracy of these methods. Specifically, we investigate the affect of numerical resolution on the accuracy of an Ensemble Kalman Filter bathymetric inversion technique in relation to the spatial and temporal resolution of the gridded standoff measurements. The accuracies of the bathymetric estimates are compared with both high-resolution Real Time Kinematic (RTK) single-beam surveys as well as alternative direct in-situ measurements using sonic altimeters.

Remotely Sensed High-Resolution Global Cloud Dynamics for Predicting Ecosystem and Biodiversity Distributions.

PubMed

Wilson, Adam M; Jetz, Walter

2016-03-01

Cloud cover can influence numerous important ecological processes, including reproduction, growth, survival, and behavior, yet our assessment of its importance at the appropriate spatial scales has remained remarkably limited. If captured over a large extent yet at sufficiently fine spatial grain, cloud cover dynamics may provide key information for delineating a variety of habitat types and predicting species distributions. Here, we develop new near-global, fine-grain (≈1 km) monthly cloud frequencies from 15 y of twice-daily Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images that expose spatiotemporal cloud cover dynamics of previously undocumented global complexity. We demonstrate that cloud cover varies strongly in its geographic heterogeneity and that the direct, observation-based nature of cloud-derived metrics can improve predictions of habitats, ecosystem, and species distributions with reduced spatial autocorrelation compared to commonly used interpolated climate data. These findings support the fundamental role of remote sensing as an effective lens through which to understand and globally monitor the fine-grain spatial variability of key biodiversity and ecosystem properties.

AgroEcoSystem-Watershed (AgES-W) model delineation and scaling

USDA-ARS?s Scientific Manuscript database

Water movement and storage within an agricultural watershed can be simulated at different spatial resolutions of land areas or hydrological response units (HRUs). Interactions between HRUs in space and time vary with the HRU sizes, such that natural scaling relationships are confounded with the simu...

Spatially-Resolved Observations of Giant Stars with SPHERE

NASA Astrophysics Data System (ADS)

Khouri, Theo

2018-04-01

SPHERE on the VLT is an extreme adaptive optics instrument that produces images with unprecedented angular resolution at visible and near-infrared wavelengths. Its primary goal is imaging, low-resolution spectroscopic, and polarimetric characterization of extra-solar planetary systems. Nonetheless, the high spatial resolution and the instrument design optimized for observations in a narrow field of view around bright targets make SPHERE the perfect instrument for obtaining spatially-resolved images of close-by giant, evolved stars. This is particularly true at the shortest wavelengths available with SPHERE, where the angular resolution is best (> 20 mas) and these stars appear larger (< 70 mas). In this talk, I will review how SPHERE has been used to study the surfaces and extended atmospheres of evolved stars and how these observations advance our understanding of the stellar pulsations and convective motions that shape these stars. Moreover, I will present recent results from a monitoring campaign of the star R Doradus using SPHERE with observations taken at twelve epochs over eight months that reveal features on the stellar disc varying on timescales of a few weeks. Finally, I will present quasi-simultaneous observations with SPHERE and ALMA that spatially resolve the stellar discs of two asymptotic giant branch stars, Mira and R Doradus, and discuss what such multi-wavelength observation campaigns can teach us about the processes that shape evolved stars.

Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model.

PubMed

Shafer, Sarah L; Bartlein, Patrick J; Gray, Elizabeth M; Pelltier, Richard T

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0-58.0°N latitude by 136.6-103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070-2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.

Cosmic Ray Neutron Sensing in Complex Systems

NASA Astrophysics Data System (ADS)

Piussi, L. M.; Tomelleri, E.; Tonon, G.; Bertoldi, G.; Mejia Aguilar, A.; Monsorno, R.; Zebisch, M.

2017-12-01

Soil moisture is a key variable in environmental monitoring and modelling: being located at the soil-atmosphere boundary, it is a driving force for water, energy and carbon fluxes. Nevertheless its importance, soil moisture observations lack of long time-series at high acquisition frequency in spatial meso-scale resolutions: traditional measurements deliver either long time series with high measurement frequency at spatial point scale or large scale and low frequency acquisitions. The Cosmic Ray Neutron Sensing (CRNS) technique fills this gap because it supplies information from a footprint of 240m of diameter and 15 to 83 cm of depth at a temporal resolution varying between 15 minutes and 24 hours. In addition, being a passive sensing technique, it is non-invasive. For these reasons, CRNS is gaining more and more attention from the scientific community. Nevertheless, the application of this technique in complex systems is still an open issue: where different Hydrogen pools are present and where their distributions vary appreciably with space and time, the traditional calibration method shows some limits. In order to obtain a better understanding of the data and to compare them with remote sensing products and spatially distributed traditional measurements (i.e. Wireless Sensors Network), the complexity of the surrounding environment has to be taken into account. In the current work we assessed the effects of spatial-temporal variability of soil moisture within the footprint, in a steep, heterogeneous mountain grassland area. Measurement were performed with a Cosmic Ray Neutron Probe (CRNP) and a mobile Wireless Sensors Network. We performed an in-deep sensitivity analysis of the effects of varying distributions of soil moisture on the calibration of the CRNP and our preliminary results show how the footprint shape varies depending on these dynamics. The results are then compared with remote sensing data (Sentinel 1 and 2). The current work is an assessment of different calibration procedures and their effect on the measurement outcome. We found that the response of the CRNP follows quite well the punctual measurement performed by a TDR installed on the site, but discrepancies could be explained by using the Wireless Sensors Network to perform a spatially weighted calibration and to introduce temporal dynamics.

High resolution telescope and spectrograph observations of solar fine structure in the 1600 A region

NASA Technical Reports Server (NTRS)

Cook, J. W.; Brueckner, G. E.; Bartoe, J.-D. F.

1983-01-01

High spatial resolution spectroheliograms of the 1600 A region obtained during the HRTS rocket flight of 1978 February 13 are presented. The morphology, fine structure, and temporal behavior of emission bright points (BPs) in active and quiet regions are illustrated. In quiet regions, network elements persist as morphological units, although individual BPs may vary in intensity while usually lasting the flight duration. In cell centers, the BPs are highly variable on a 1 minute time scale. BPs in plages remain more constant in brightness over the observing sequence. BPs cover less than 4 percent of the quiet surface. The lifetime and degree of packing of BPs vary with the local strength of the magnetic field.

Extended-range high-resolution dynamical downscaling over a continental-scale spatial domain with atmospheric and surface nudging

NASA Astrophysics Data System (ADS)

Husain, S. Z.; Separovic, L.; Yu, W.; Fernig, D.

2014-12-01

Extended-range high-resolution mesoscale simulations with limited-area atmospheric models when applied to downscale regional analysis fields over large spatial domains can provide valuable information for many applications including the weather-dependent renewable energy industry. Long-term simulations over a continental-scale spatial domain, however, require mechanisms to control the large-scale deviations in the high-resolution simulated fields from the coarse-resolution driving fields. As enforcement of the lateral boundary conditions is insufficient to restrict such deviations, large scales in the simulated high-resolution meteorological fields are therefore spectrally nudged toward the driving fields. Different spectral nudging approaches, including the appropriate nudging length scales as well as the vertical profiles and temporal relaxations for nudging, have been investigated to propose an optimal nudging strategy. Impacts of time-varying nudging and generation of hourly analysis estimates are explored to circumvent problems arising from the coarse temporal resolution of the regional analysis fields. Although controlling the evolution of the atmospheric large scales generally improves the outputs of high-resolution mesoscale simulations within the surface layer, the prognostically evolving surface fields can nevertheless deviate from their expected values leading to significant inaccuracies in the predicted surface layer meteorology. A forcing strategy based on grid nudging of the different surface fields, including surface temperature, soil moisture, and snow conditions, toward their expected values obtained from a high-resolution offline surface scheme is therefore proposed to limit any considerable deviation. Finally, wind speed and temperature at wind turbine hub height predicted by different spectrally nudged extended-range simulations are compared against observations to demonstrate possible improvements achievable using higher spatiotemporal resolution.

Longitudinal spatial coherence gated high-resolution tomography and quantitative phase microscopy of biological cells and tissues with uniform illumination

NASA Astrophysics Data System (ADS)

Mehta, Dalip Singh; Ahmad, Azeem; Dubey, Vishesh; Singh, Veena; Butola, Ankit; Mohanty, Tonmoy; Nandi, Sreyankar

2018-02-01

We report longitudinal spatial coherence (LSC) gated high-resolution tomography and quantitative phase microscopy of biological cells and tissues with uniform illumination using laser as a light source. To accomplish this a pseudo thermal light source was synthesized by passing laser beams through an optical system, which is basically a speckle reduction system with combined effect of spatial, temporal, angular and polarisation diversity. The longitudinal spatial coherence length of such light was significantly reduced by synthesizing a pseudo thermal source with the combined effect of spatial, angular and temporal diversity. This results in a low spatially coherent (i.e., broad angular frequency spectrum) light source with narrow temporal frequency spectrum. Light from such a pseudo thermal light source was passed through an interference microscope with varying magnification, such as, 10X and 50X. The interference microscope was used for full-field OCT imaging of multilayer objects and topography of industrial objects. Experimental results of optical sectioning of multilayer biological objects with high axial-resolution less than 10μm was achieved which is comparable to broadband white light source. The synthesized light source with reduced speckles having uniform illumination on the sample, which can be very useful for fluorescence microscopy as well as quantitative phase microscopy with less phase noise. The present system does not require any dispersion compensation optical system for biological samples as a highly monochromatic light source is used.

First characterization of a digital SiPM based time-of-flight PET detector with 1 mm spatial resolution

NASA Astrophysics Data System (ADS)

Seifert, Stefan; van der Lei, Gerben; van Dam, Herman T.; Schaart, Dennis R.

2013-05-01

Monolithic scintillator detectors can offer a combination of spatial resolution, energy resolution, timing performance, depth-of-interaction information, and detection efficiency that make this type of detector a promising candidate for application in clinical, time-of-flight (TOF) positron emission tomography (PET). In such detectors the scintillation light is distributed over a relatively large number of photosensor pixels and the light intensity per pixel can be relatively low. Therefore, monolithic scintillator detectors are expected to benefit from the low readout noise offered by a novel photosensor called the digital silicon photomultiplier (dSiPM). Here, we present a first experimental characterization of a TOF PET detector comprising a 24 × 24 × 10 mm3 LSO:Ce,0.2%Ca scintillator read out by a dSiPM array (DPC-6400-44-22) developed by Philips Digital Photon Counting. A spatial resolution of ˜1 mm full-width-at-half-maximum (FWHM) averaged over the entire crystal was obtained (varying from just below 1 mm FWHM in the detector center to ˜1.2 mm FWHM close to the edges). Furthermore, the bias in the position estimation at the crystal edges that is typically found in monolithic scintillators is well below 1 mm even in the corners of the crystal.

Impact of temporal upscaling and chemical transport model horizontal resolution on reducing ozone exposure misclassification

NASA Astrophysics Data System (ADS)

Xu, Yadong; Serre, Marc L.; Reyes, Jeanette M.; Vizuete, William

2017-10-01

We have developed a Bayesian Maximum Entropy (BME) framework that integrates observations from a surface monitoring network and predictions from a Chemical Transport Model (CTM) to create improved exposure estimates that can be resolved into any spatial and temporal resolution. The flexibility of the framework allows for input of data in any choice of time scales and CTM predictions of any spatial resolution with varying associated degrees of estimation error and cost in terms of implementation and computation. This study quantifies the impact on exposure estimation error due to these choices by first comparing estimations errors when BME relied on ozone concentration data either as an hourly average, the daily maximum 8-h average (DM8A), or the daily 24-h average (D24A). Our analysis found that the use of DM8A and D24A data, although less computationally intensive, reduced estimation error more when compared to the use of hourly data. This was primarily due to the poorer CTM model performance in the hourly average predicted ozone. Our second analysis compared spatial variability and estimation errors when BME relied on CTM predictions with a grid cell resolution of 12 × 12 km2 versus a coarser resolution of 36 × 36 km2. Our analysis found that integrating the finer grid resolution CTM predictions not only reduced estimation error, but also increased the spatial variability in daily ozone estimates by 5 times. This improvement was due to the improved spatial gradients and model performance found in the finer resolved CTM simulation. The integration of observational and model predictions that is permitted in a BME framework continues to be a powerful approach for improving exposure estimates of ambient air pollution. The results of this analysis demonstrate the importance of also understanding model performance variability and its implications on exposure error.

SU-E-T-96: Energy Dependence of the New GafChromic- EBT3 Film's Dose Response-Curve.

PubMed

Chiu-Tsao, S; Massillon-Jl, G; Domingo-Muñoz, I; Chan, M

2012-06-01

To study and compare the dose response curves of the new GafChromic EBT3 film for megavoltage and kilovoltage x-ray beams, with different spatial resolution. Two sets of EBT3 films (lot#A101711-02) were exposed to each x-ray beam (6MV, 15MV and 50kV) at 8 dose values (50-3200cGy). The megavoltage beams were calibrated per AAPM TG-51 protocol while the kilovoltage beam was calibrated following the TG-61 using an ionization chamber calibrated at NIST. Each film piece was scanned three consecutive times in the center of Epson 10000XL flatbed scanner in transmission mode, landscape orientation, 48-bit color at two separate spatial resolutions of 75 and 300 dpi. The data were analyzed using ImageJ and, for each scanned image, a region of interest (ROI) of 2×2cm 2 at the field center was selected to obtain the mean pixel value with its standard deviation in the ROI. For each energy, dose value and spatial resolution, the average netOD and its associated uncertainty were determined. The Student's t-test was performed to evaluate the statistical differences between the netOD/dose values of the three energy modalities, with different color channels and spatial resolutions. The dose response curves for the three energy modalities were compared in three color channels with 75 and 300dpi. Weak energy dependence was found. For doses above 100cGy, no statistical differences were observed between 6 and 15MV beams, regardless of spatial resolution. However, statistical differences were observed between 50kV and the megavoltage beams. The degree of energy dependence (from MV to 50kV) was found to be function of color channel, dose level and spatial resolution. The dose response curves for GafChromic EBT3 films were found to be weakly dependent on the energy of the photon beams from 6MV to 50kV. The degree of energy dependence varies with color channel, dose and spatial resolution. GafChromic EBT3 films were supplied by Ashland Corp. This work was partially supported by DGAPA-UNAM grant IN102610 and Conacyt Mexico grant 127409. © 2012 American Association of Physicists in Medicine.

Establishing resolution-improved NMR spectroscopy in high magnetic fields with unknown spatiotemporal variations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Zhiyong; Cai, Shuhui; Zheng, Zhenyao

A half-century quest for higher magnetic fields has been an integral part of the progress undergone in the Nuclear Magnetic Resonance (NMR) study of materials’ structure and dynamics. Because 2D NMR relies on systematic changes in coherences’ phases as a function of an encoding time varied over a series of independent experiments, it generally cannot be applied in temporally unstable fields. This precludes most NMR methods from being used to characterize samples situated in hybrid or resistive magnets that are capable of achieving extremely high magnetic field strength. Recently, “ultrafast” NMR has been developed into an effective and widely applicablemore » methodology enabling the acquisition of a multidimensional NMR spectrum in a single scan; it can therefore be used to partially mitigate the effects of temporally varying magnetic fields. Nevertheless, the strong interference of fluctuating fields with the spatial encoding of ultrafast NMR still severely restricts measurement sensitivity and resolution. Here, we introduce a strategy for obtaining high resolution NMR spectra that exploits the immunity of intermolecular zero-quantum coherences (iZQCs) to field instabilities and inhomogeneities. The spatial encoding of iZQCs is combined with a J-modulated detection scheme that removes the influence of arbitrary field inhomogeneities during acquisition. This new method can acquire high-resolution one-dimensional NMR spectra in large inhomogeneous and fluctuating fields, and it is tested with fields experimentally modeled to mimic those of resistive and resistive-superconducting hybrid magnets.« less

The Partition of Multi-Resolution LOD Based on Qtm

NASA Astrophysics Data System (ADS)

Hou, M.-L.; Xing, H.-Q.; Zhao, X.-S.; Chen, J.

2011-08-01

The partition hierarch of Quaternary Triangular Mesh (QTM) determine the accuracy of spatial analysis and application based on QTM. In order to resolve the problem that the partition hierarch of QTM is limited by the level of the computer hardware, the new method that Multi- Resolution LOD (Level of Details) based on QTM will be discussed in this paper. This method can make the resolution of the cells varying with the viewpoint position by partitioning the cells of QTM, selecting the particular area according to the viewpoint; dealing with the cracks caused by different subdivisions, it satisfies the request of unlimited partition in part.

Extrapolating active layer thickness measurements across Arctic polygonal terrain using LiDAR and NDVI data sets.

PubMed

Gangodagamage, Chandana; Rowland, Joel C; Hubbard, Susan S; Brumby, Steven P; Liljedahl, Anna K; Wainwright, Haruko; Wilson, Cathy J; Altmann, Garrett L; Dafflon, Baptiste; Peterson, John; Ulrich, Craig; Tweedie, Craig E; Wullschleger, Stan D

2014-08-01

Landscape attributes that vary with microtopography, such as active layer thickness ( ALT ), are labor intensive and difficult to document effectively through in situ methods at kilometer spatial extents, thus rendering remotely sensed methods desirable. Spatially explicit estimates of ALT can provide critically needed data for parameterization, initialization, and evaluation of Arctic terrestrial models. In this work, we demonstrate a new approach using high-resolution remotely sensed data for estimating centimeter-scale ALT in a 5 km 2 area of ice-wedge polygon terrain in Barrow, Alaska. We use a simple regression-based, machine learning data-fusion algorithm that uses topographic and spectral metrics derived from multisensor data (LiDAR and WorldView-2) to estimate ALT (2 m spatial resolution) across the study area. Comparison of the ALT estimates with ground-based measurements, indicates the accuracy (r 2  = 0.76, RMSE ±4.4 cm) of the approach. While it is generally accepted that broad climatic variability associated with increasing air temperature will govern the regional averages of ALT , consistent with prior studies, our findings using high-resolution LiDAR and WorldView-2 data, show that smaller-scale variability in ALT is controlled by local eco-hydro-geomorphic factors. This work demonstrates a path forward for mapping ALT at high spatial resolution and across sufficiently large regions for improved understanding and predictions of coupled dynamics among permafrost, hydrology, and land-surface processes from readily available remote sensing data.

Scaling of surface energy fluxes using remotely sensed data

NASA Astrophysics Data System (ADS)

French, Andrew Nichols

Accurate estimates of evapotranspiration (ET) across multiple terrains would greatly ease challenges faced by hydrologists, climate modelers, and agronomists as they attempt to apply theoretical models to real-world situations. One ET estimation approach uses an energy balance model to interpret a combination of meteorological observations taken at the surface and data captured by remote sensors. However, results of this approach have not been accurate because of poor understanding of the relationship between surface energy flux and land cover heterogeneity, combined with limits in available resolution of remote sensors. The purpose of this study was to determine how land cover and image resolution affect ET estimates. Using remotely sensed data collected over El Reno, Oklahoma, during four days in June and July 1997, scale effects on the estimation of spatially distributed ET were investigated. Instantaneous estimates of latent and sensible heat flux were calculated using a two-source surface energy balance model driven by thermal infrared, visible-near infrared, and meteorological data. The heat flux estimates were verified by comparison to independent eddy-covariance observations. Outcomes of observations taken at coarser resolutions were simulated by aggregating remote sensor data and estimated surface energy balance components from the finest sensor resolution (12 meter) to hypothetical resolutions as coarse as one kilometer. Estimated surface energy flux components were found to be significantly dependent on observation scale. For example, average evaporative fraction varied from 0.79, using 12-m resolution data, to 0.93, using 1-km resolution data. Resolution effects upon flux estimates were related to a measure of landscape heterogeneity known as operational scale, reflecting the size of dominant landscape features. Energy flux estimates based on data at resolutions less than 100 m and much greater than 400 m showed a scale-dependent bias. But estimates derived from data taken at about 400-m resolution (the operational scale at El Reno) were susceptible to large error due to mixing of surface types. The El Reno experiments show that accurate instantaneous estimates of ET require precise image alignment and image resolutions finer than landscape operational scale. These findings are valuable for the design of sensors and experiments to quantify spatially-varying hydrologic processes.

Ultrafast scanning probe microscopy

DOEpatents

Weiss, S.; Chemla, D.S.; Ogletree, D.F.; Botkin, D.

1995-05-16

An ultrafast scanning probe microscopy method is described for achieving subpicosecond-temporal resolution and submicron-spatial resolution of an observation sample. In one embodiment of the present claimed invention, a single short optical pulse is generated and is split into first and second pulses. One of the pulses is delayed using variable time delay means. The first pulse is then directed at an observation sample located proximate to the probe of a scanning probe microscope. The scanning probe microscope produces probe-sample signals indicative of the response of the probe to characteristics of the sample. The second pulse is used to modulate the probe of the scanning probe microscope. The time delay between the first and second pulses is then varied. The probe-sample response signal is recorded at each of the various time delays created between the first and second pulses. The probe-sample response signal is then plotted as a function of time delay to produce a cross-correlation of the probe sample response. In so doing, the present invention provides simultaneous subpicosecond-temporal resolution and submicron-spatial resolution of the sample. 6 Figs.

qSR: a quantitative super-resolution analysis tool reveals the cell-cycle dependent organization of RNA Polymerase I in live human cells.

PubMed

Andrews, J O; Conway, W; Cho, W -K; Narayanan, A; Spille, J -H; Jayanth, N; Inoue, T; Mullen, S; Thaler, J; Cissé, I I

2018-05-09

We present qSR, an analytical tool for the quantitative analysis of single molecule based super-resolution data. The software is created as an open-source platform integrating multiple algorithms for rigorous spatial and temporal characterizations of protein clusters in super-resolution data of living cells. First, we illustrate qSR using a sample live cell data of RNA Polymerase II (Pol II) as an example of highly dynamic sub-diffractive clusters. Then we utilize qSR to investigate the organization and dynamics of endogenous RNA Polymerase I (Pol I) in live human cells, throughout the cell cycle. Our analysis reveals a previously uncharacterized transient clustering of Pol I. Both stable and transient populations of Pol I clusters co-exist in individual living cells, and their relative fraction vary during cell cycle, in a manner correlating with global gene expression. Thus, qSR serves to facilitate the study of protein organization and dynamics with very high spatial and temporal resolutions directly in live cell.

Ultrafast scanning probe microscopy

DOEpatents

Weiss, Shimon; Chemla, Daniel S.; Ogletree, D. Frank; Botkin, David

1995-01-01

An ultrafast scanning probe microscopy method for achieving subpicosecond-temporal resolution and submicron-spatial resolution of an observation sample. In one embodiment of the present claimed invention, a single short optical pulse is generated and is split into first and second pulses. One of the pulses is delayed using variable time delay means. The first pulse is then directed at an observation sample located proximate to the probe of a scanning probe microscope. The scanning probe microscope produces probe-sample signals indicative of the response of the probe to characteristics of the sample. The second pulse is used to modulate the probe of the scanning probe microscope. The time delay between the first and second pulses is then varied. The probe-sample response signal is recorded at each of the various time delays created between the first and second pulses. The probe-sample response signal is then plotted as a function of time delay to produce a cross-correlation of the probe sample response. In so doing, the present invention provides simultaneous subpicosecond-temporal resolution and submicron-spatial resolution of the sample.

Scaling Properties of Arctic Sea Ice Deformation in a High‐Resolution Viscous‐Plastic Sea Ice Model and in Satellite Observations

PubMed Central

Losch, Martin; Menemenlis, Dimitris

2018-01-01

Abstract Sea ice models with the traditional viscous‐plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan‐Arctic sea ice‐ocean simulation, the small‐scale sea ice deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled sea ice deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of sea ice deformation that is observed in satellite data. PMID:29576996

Remotely Sensed High-Resolution Global Cloud Dynamics for Predicting Ecosystem and Biodiversity Distributions

PubMed Central

Wilson, Adam M.; Jetz, Walter

2016-01-01

Cloud cover can influence numerous important ecological processes, including reproduction, growth, survival, and behavior, yet our assessment of its importance at the appropriate spatial scales has remained remarkably limited. If captured over a large extent yet at sufficiently fine spatial grain, cloud cover dynamics may provide key information for delineating a variety of habitat types and predicting species distributions. Here, we develop new near-global, fine-grain (≈1 km) monthly cloud frequencies from 15 y of twice-daily Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images that expose spatiotemporal cloud cover dynamics of previously undocumented global complexity. We demonstrate that cloud cover varies strongly in its geographic heterogeneity and that the direct, observation-based nature of cloud-derived metrics can improve predictions of habitats, ecosystem, and species distributions with reduced spatial autocorrelation compared to commonly used interpolated climate data. These findings support the fundamental role of remote sensing as an effective lens through which to understand and globally monitor the fine-grain spatial variability of key biodiversity and ecosystem properties. PMID:27031693

Scaling Properties of Arctic Sea Ice Deformation in a High-Resolution Viscous-Plastic Sea Ice Model and in Satellite Observations

NASA Astrophysics Data System (ADS)

Hutter, Nils; Losch, Martin; Menemenlis, Dimitris

2018-01-01

Sea ice models with the traditional viscous-plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan-Arctic sea ice-ocean simulation, the small-scale sea ice deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled sea ice deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.

Scaling Properties of Arctic Sea Ice Deformation in a High-Resolution Viscous-Plastic Sea Ice Model and in Satellite Observations.

PubMed

Hutter, Nils; Losch, Martin; Menemenlis, Dimitris

2018-01-01

Sea ice models with the traditional viscous-plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan-Arctic sea ice-ocean simulation, the small-scale sea ice deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled sea ice deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.

Spatial downscaling of soil prediction models based on weighted generalized additive models in smallholder farm settings.

PubMed

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D

2017-09-11

Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.

A Review of Hybrid Fiber-Optic Distributed Simultaneous Vibration and Temperature Sensing Technology and Its Geophysical Applications

PubMed Central

2017-01-01

Distributed sensing systems can transform an optical fiber cable into an array of sensors, allowing users to detect and monitor multiple physical parameters such as temperature, vibration and strain with fine spatial and temporal resolution over a long distance. Fiber-optic distributed acoustic sensing (DAS) and distributed temperature sensing (DTS) systems have been developed for various applications with varied spatial resolution, and spectral and sensing range. Rayleigh scattering-based phase optical time domain reflectometry (OTDR) for vibration and Raman/Brillouin scattering-based OTDR for temperature and strain measurements have been developed over the past two decades. The key challenge has been to find a methodology that would enable the physical parameters to be determined at any point along the sensing fiber with high sensitivity and spatial resolution, yet within acceptable frequency range for dynamic vibration, and temperature detection. There are many applications, especially in geophysical and mining engineering where simultaneous measurements of vibration and temperature are essential. In this article, recent developments of different hybrid systems for simultaneous vibration, temperature and strain measurements are analyzed based on their operation principles and performance. Then, challenges and limitations of the systems are highlighted for geophysical applications. PMID:29104259

High spatiotemporal resolution monitoring of hydrological function across degraded peatlands in the south west UK.

NASA Astrophysics Data System (ADS)

Ashe, Josie; Luscombe, David; Grand-Clement, Emilie; Gatis, Naomi; Anderson, Karen; Brazier, Richard

2014-05-01

The Exmoor/Dartmoor Mires Project is a peatland restoration programme focused on the geoclimatically marginal blanket bogs of South West England. In order to better understand the hydrological functioning of degraded/restored peatlands and support land management decisions across these uplands, this study is providing robust spatially distributed, hydrological monitoring at a high temporal resolution and in near real time. This paper presents the conceptual framework and experimental design for three hydrological monitoring arrays situated in headwater catchments dominated by eroding and drained blanket peatland. Over 250 individual measurements are collected at a high temporal resolution (15 minute time-step) via sensors integrated within a remote telemetry system. These are sent directly to a dedicated server over VHF and GPRS mobile networks. Sensors arrays are distributed at varying spatial scales throughout the studied catchments and record multiple parameters including: water table depth, channel flow, temperature, conductivity and pH measurements. A full suite of meteorological sensors and ten spatially distributed automatic flow based water samplers are also connected to the telemetry system and controlled remotely. This paper will highlight the challenges and solutions to obtaining these data in exceptionally remote and harsh field conditions over long (multi annual) temporal scales.

A Review of Hybrid Fiber-Optic Distributed Simultaneous Vibration and Temperature Sensing Technology and Its Geophysical Applications.

PubMed

Miah, Khalid; Potter, David K

2017-11-01

Distributed sensing systems can transform an optical fiber cable into an array of sensors, allowing users to detect and monitor multiple physical parameters such as temperature, vibration and strain with fine spatial and temporal resolution over a long distance. Fiber-optic distributed acoustic sensing (DAS) and distributed temperature sensing (DTS) systems have been developed for various applications with varied spatial resolution, and spectral and sensing range. Rayleigh scattering-based phase optical time domain reflectometry (OTDR) for vibration and Raman/Brillouin scattering-based OTDR for temperature and strain measurements have been developed over the past two decades. The key challenge has been to find a methodology that would enable the physical parameters to be determined at any point along the sensing fiber with high sensitivity and spatial resolution, yet within acceptable frequency range for dynamic vibration, and temperature detection. There are many applications, especially in geophysical and mining engineering where simultaneous measurements of vibration and temperature are essential. In this article, recent developments of different hybrid systems for simultaneous vibration, temperature and strain measurements are analyzed based on their operation principles and performance. Then, challenges and limitations of the systems are highlighted for geophysical applications.

NDVI, scale invariance and the modifiable areal unit problem: An assessment of vegetation in the Adelaide Parklands

USGS Publications Warehouse

Nouri, Hamideh; Anderson, Sharolyn; Sutton, Paul; Beecham, Simon; Nagler, Pamela L.; Jarchow, Christopher J.; Roberts, Dar A.

2017-01-01

This research addresses the question as to whether or not the Normalised Difference Vegetation Index (NDVI) is scale invariant (i.e. constant over spatial aggregation) for pure pixels of urban vegetation. It has been long recognized that there are issues related to the modifiable areal unit problem (MAUP) pertaining to indices such as NDVI and images at varying spatial resolutions. These issues are relevant to using NDVI values in spatial analyses. We compare two different methods of calculation of a mean NDVI: 1) using pixel values of NDVI within feature/object boundaries and 2) first calculating the mean red and mean near-infrared across all feature pixels and then calculating NDVI. We explore the nature and magnitude of these differences for images taken from two sensors, a 1.24 m resolution WorldView-3 and a 0.1 m resolution digital aerial image. We apply these methods over an urban park located in the Adelaide Parklands of South Australia. We demonstrate that the MAUP is not an issue for calculation of NDVI within a sensor for pure urban vegetation pixels. This may prove useful for future rule-based monitoring of the ecosystem functioning of green infrastructure.

Fluorescence microscopy.

PubMed

Sanderson, Michael J; Smith, Ian; Parker, Ian; Bootman, Martin D

2014-10-01

Fluorescence microscopy is a major tool with which to monitor cell physiology. Although the concepts of fluorescence and its optical separation using filters remain similar, microscope design varies with the aim of increasing image contrast and spatial resolution. The basics of wide-field microscopy are outlined to emphasize the selection, advantages, and correct use of laser scanning confocal microscopy, two-photon microscopy, scanning disk confocal microscopy, total internal reflection, and super-resolution microscopy. In addition, the principles of how these microscopes form images are reviewed to appreciate their capabilities, limitations, and constraints for operation. © 2014 Cold Spring Harbor Laboratory Press.

Fluorescence Microscopy

PubMed Central

Sanderson, Michael J.; Smith, Ian; Parker, Ian; Bootman, Martin D.

2016-01-01

Fluorescence microscopy is a major tool with which to monitor cell physiology. Although the concepts of fluorescence and its optical separation using filters remain similar, microscope design varies with the aim of increasing image contrast and spatial resolution. The basics of wide-field microscopy are outlined to emphasize the selection, advantages, and correct use of laser scanning confocal microscopy, two-photon microscopy, scanning disk confocal microscopy, total internal reflection, and super-resolution microscopy. In addition, the principles of how these microscopes form images are reviewed to appreciate their capabilities, limitations, and constraints for operation. PMID:25275114

CT-based attenuation correction and resolution compensation for I-123 IMP brain SPECT normal database: a multicenter phantom study.

PubMed

Inui, Yoshitaka; Ichihara, Takashi; Uno, Masaki; Ishiguro, Masanobu; Ito, Kengo; Kato, Katsuhiko; Sakuma, Hajime; Okazawa, Hidehiko; Toyama, Hiroshi

2018-06-01

Statistical image analysis of brain SPECT images has improved diagnostic accuracy for brain disorders. However, the results of statistical analysis vary depending on the institution even when they use a common normal database (NDB), due to different intrinsic spatial resolutions or correction methods. The present study aimed to evaluate the correction of spatial resolution differences between equipment and examine the differences in skull bone attenuation to construct a common NDB for use in multicenter settings. The proposed acquisition and processing protocols were those routinely used at each participating center with additional triple energy window (TEW) scatter correction (SC) and computed tomography (CT) based attenuation correction (CTAC). A multicenter phantom study was conducted on six imaging systems in five centers, with either single photon emission computed tomography (SPECT) or SPECT/CT, and two brain phantoms. The gray/white matter I-123 activity ratio in the brain phantoms was 4, and they were enclosed in either an artificial adult male skull, 1300 Hounsfield units (HU), a female skull, 850 HU, or an acrylic cover. The cut-off frequency of the Butterworth filters was adjusted so that the spatial resolution was unified to a 17.9 mm full width at half maximum (FWHM), that of the lowest resolution system. The gray-to-white matter count ratios were measured from SPECT images and compared with the actual activity ratio. In addition, mean, standard deviation and coefficient of variation images were calculated after normalization and anatomical standardization to evaluate the variability of the NDB. The gray-to-white matter count ratio error without SC and attenuation correction (AC) was significantly larger for higher bone densities (p < 0.05). The count ratio error with TEW and CTAC was approximately 5% regardless of bone density. After adjustment of the spatial resolution in the SPECT images, the variability of the NDB decreased and was comparable to that of the NDB without correction. The proposed protocol showed potential for constructing an appropriate common NDB from SPECT images with SC, AC and spatial resolution compensation.

High Resolution Insights into Snow Distribution Provided by Drone Photogrammetry

NASA Astrophysics Data System (ADS)

Redpath, T.; Sirguey, P. J.; Cullen, N. J.; Fitzsimons, S.

2017-12-01

Dynamic in time and space, New Zealand's seasonal snow is largely confined to remote alpine areas, complicating ongoing in situ measurement and characterisation. Improved understanding and modeling of the seasonal snowpack requires fine scale resolution of snow distribution and spatial variability. The potential of remotely piloted aircraft system (RPAS) photogrammetry to resolve spatial and temporal variability of snow depth and water equivalent in a New Zealand alpine catchment is assessed in the Pisa Range, Central Otago. This approach yielded orthophotomosaics and digital surface models (DSM) at 0.05 and 0.15 m spatial resolution, respectively. An autumn reference DSM allowed mapping of winter (02/08/2016) and spring (10/09/2016) snow depth at 0.15 m spatial resolution, via DSM differencing. The consistency and accuracy of the RPAS-derived surface was assessed by comparison of snow-free regions of the spring and autumn DSMs, while accuracy of RPAS retrieved snow depth was assessed with 86 in situ snow probe measurements. Results show a mean vertical residual of 0.024 m between DSMs acquired in autumn and spring. This residual approximated a Laplace distribution, reflecting the influence of large outliers on the small overall bias. Propagation of errors associated with successive DSMs saw snow depth mapped with an accuracy of ± 0.09 m (95% c.l.). Comparing RPAS and in situ snow depth measurements revealed the influence of geo-location uncertainty and interactions between vegetation and the snowpack on snow depth uncertainty and bias. Semi-variogram analysis revealed that the RPAS outperformed systematic in situ measurements in resolving fine scale spatial variability. Despite limitations accompanying RPAS photogrammetry, this study demonstrates a repeatable means of accurately mapping snow depth for an entire, yet relatively small, hydrological basin ( 0.5 km2), at high resolution. Resolving snowpack features associated with re-distribution and preferential accumulation and ablation, snow depth maps provide geostatistically robust insights into seasonal snow processes, with unprecedented detail. Such data may enhance understanding of physical processes controlling spatial and temporal distribution of seasonal snow, and their relative importance at varying spatial and temporal scales.

Species classification using Unmanned Aerial Vehicle (UAV)-acquired high spatial resolution imagery in a heterogeneous grassland

NASA Astrophysics Data System (ADS)

Lu, Bing; He, Yuhong

2017-06-01

Investigating spatio-temporal variations of species composition in grassland is an essential step in evaluating grassland health conditions, understanding the evolutionary processes of the local ecosystem, and developing grassland management strategies. Space-borne remote sensing images (e.g., MODIS, Landsat, and Quickbird) with spatial resolutions varying from less than 1 m to 500 m have been widely applied for vegetation species classification at spatial scales from community to regional levels. However, the spatial resolutions of these images are not fine enough to investigate grassland species composition, since grass species are generally small in size and highly mixed, and vegetation cover is greatly heterogeneous. Unmanned Aerial Vehicle (UAV) as an emerging remote sensing platform offers a unique ability to acquire imagery at very high spatial resolution (centimetres). Compared to satellites or airplanes, UAVs can be deployed quickly and repeatedly, and are less limited by weather conditions, facilitating advantageous temporal studies. In this study, we utilize an octocopter, on which we mounted a modified digital camera (with near-infrared (NIR), green, and blue bands), to investigate species composition in a tall grassland in Ontario, Canada. Seven flight missions were conducted during the growing season (April to December) in 2015 to detect seasonal variations, and four of them were selected in this study to investigate the spatio-temporal variations of species composition. To quantitatively compare images acquired at different times, we establish a processing flow of UAV-acquired imagery, focusing on imagery quality evaluation and radiometric correction. The corrected imagery is then applied to an object-based species classification. Maps of species distribution are subsequently used for a spatio-temporal change analysis. Results indicate that UAV-acquired imagery is an incomparable data source for studying fine-scale grassland species composition, owing to its high spatial resolution. The overall accuracy is around 85% for images acquired at different times. Species composition is spatially attributed by topographical features and soil moisture conditions. Spatio-temporal variation of species composition implies the growing process and succession of different species, which is critical for understanding the evolutionary features of grassland ecosystems. Strengths and challenges of applying UAV-acquired imagery for vegetation studies are summarized at the end.

A compact large-format streak tube for imaging lidar

NASA Astrophysics Data System (ADS)

Hui, Dandan; Luo, Duan; Tian, Liping; Lu, Yu; Chen, Ping; Wang, Junfeng; Sai, Xiaofeng; Wen, Wenlong; Wang, Xing; Xin, Liwei; Zhao, Wei; Tian, Jinshou

2018-04-01

The streak tubes with a large effective photocathode area, large effective phosphor screen area, and high photocathode radiant sensitivity are essential for improving the field of view, depth of field, and detectable range of the multiple-slit streak tube imaging lidar. In this paper, a high spatial resolution, large photocathode area, and compact meshless streak tube with a spherically curved cathode and screen is designed and tested. Its spatial resolution reaches 20 lp/mm over the entire Φ28 mm photocathode working area, and the simulated physical temporal resolution is better than 30 ps. The temporal distortion in our large-format streak tube, which is shown to be a non-negligible factor, has a minimum value as the radius of curvature of the photocathode varies. Furthermore, the photocathode radiant sensitivity and radiant power gain reach 41 mA/W and 18.4 at the wavelength of 550 nm, respectively. Most importantly, the external dimensions of our streak tube are no more than Φ60 mm × 110 mm.

A New Columnar CsI(Tl) Scintillator for iQID detectors

PubMed Central

Han, Ling; Miller, Brian W.; Barber, H. Bradford; Nagarkar, Vivek V.; Furenlid, Lars R.

2015-01-01

A 1650 μm thick columnar CsI(Tl) scintillator for upgrading iQID detectors, which is a high-resolution photon-counting gamma-ray and x-ray detector recently developed at the Center for Gamma-Ray Imaging (CGRI), has been studied in terms of sensitivity, spatial resolution and depth-of-interaction effects. To facilitate these studies, a new frame-parsing algorithm for processing raw event data is also proposed that has more degrees of freedom in data processing and can discriminate against a special kind of noise present in some low-cost intensifiers. The results show that in comparison with a 450 μm-thickness columnar CsI(Tl) scintillator, the 1650 μm thick CsI(Tl) scintillator provides more than twice the sensitivity at the expense of some spatial resolution degradation. The depth-of-interaction study also shows that event size and amplitude vary with scintillator thickness, which can assist in future detector simulations and 3D-interaction-position estimation. PMID:26146444

A New Columnar CsI(Tl) Scintillator for iQID detectors.

PubMed

Han, Ling; Miller, Brian W; Barber, H Bradford; Nagarkar, Vivek V; Furenlid, Lars R

2014-09-12

A 1650 μm thick columnar CsI(Tl) scintillator for upgrading iQID detectors, which is a high-resolution photon-counting gamma-ray and x-ray detector recently developed at the Center for Gamma-Ray Imaging (CGRI), has been studied in terms of sensitivity, spatial resolution and depth-of-interaction effects. To facilitate these studies, a new frame-parsing algorithm for processing raw event data is also proposed that has more degrees of freedom in data processing and can discriminate against a special kind of noise present in some low-cost intensifiers. The results show that in comparison with a 450 μm-thickness columnar CsI(Tl) scintillator, the 1650 μm thick CsI(Tl) scintillator provides more than twice the sensitivity at the expense of some spatial resolution degradation. The depth-of-interaction study also shows that event size and amplitude vary with scintillator thickness, which can assist in future detector simulations and 3D-interaction-position estimation.

Investigation of carbonates in the Sutter's Mill meteorite grains with hyperspectral infrared imaging micro-spectroscopy

NASA Astrophysics Data System (ADS)

Yesiltas, Mehmet

2018-04-01

Synchrotron-based high spatial resolution hyperspectral infrared imaging technique provides thousands of infrared spectra with high resolution, thus allowing us to acquire detailed spatial maps of chemical molecular structures for many grains in short times. Utilizing this technique, thousands of infrared spectra were analyzed at once instead of inspecting each spectrum separately. Sutter's Mill meteorite is a unique carbonaceous type meteorite with highly heterogeneous chemical composition. Multiple grains from the Sutter's Mill meteorite have been studied using this technique and the presence of both hydrous and anhydrous silicate minerals have been observed. It is observed that the carbonate mineralogy varies from simple to more complex carbonates even within a few microns in the meteorite grains. These variations, the type and distribution of calcite-like vs. dolomite-like carbonates are presented by means of hyperspectral FTIR imaging spectroscopy with high resolution. Various scenarios for the formation of different carbonate compositions in the Sutter's Mill parent body are discussed.

Simulation of semi-arid hydrological processes at different spatial resolutions using the AgroEcoSystem-Watershed (AgES-W) model

NASA Astrophysics Data System (ADS)

Green, T. R.; Erksine, R. H.; David, O.; Ascough, J. C., II; Kipka, H.; Lloyd, W. J.; McMaster, G. S.

2015-12-01

Water movement and storage within a watershed may be simulated at different spatial resolutions of land areas or hydrological response units (HRUs). Here, effects of HRU size on simulated soil water and surface runoff are tested using the AgroEcoSystem-Watershed (AgES-W) model with three different resolutions of HRUs. We studied a 56-ha agricultural watershed in northern Colorado, USA farmed primarily under a wheat-fallow rotation. The delineation algorithm was based upon topography (surface flow paths), land use (crop management strips and native grass), and mapped soil units (three types), which produced HRUs that follow the land use and soil boundaries. AgES-W model parameters that control surface and subsurface hydrology were calibrated using simulated daily soil moisture at different landscape positions and depths where soil moisture was measured hourly and averaged up to daily values. Parameter sets were both uniform and spatially variable with depth and across the watershed (5 different calibration approaches). Although forward simulations were computationally efficient (less than 1 minute each), each calibration required thousands of model runs. Execution of such large jobs was facilitated by using the Object Modeling System with the Cloud Services Innovation Platform to manage four virtual machines on a commercial web service configured with a total of 64 computational cores and 120 GB of memory. Results show how spatially distributed and averaged soil moisture and runoff at the outlet vary with different HRU delineations. The results will help guide HRU delineation, spatial resolution and parameter estimation methods for improved hydrological simulations in this and other semi-arid agricultural watersheds.

Comparison of multi-arm VRX CT scanners through computer models

NASA Astrophysics Data System (ADS)

Rendon, David A.; DiBianca, Frank A.; Keyes, Gary S.

2007-03-01

Variable Resolution X-ray (VRX) CT scanners allow imaging of different sized anatomy at the same level of detail using the same device. This is achieved by tilting the x-ray detectors so that the projected size of the detecting elements is varied producing reconstructions of smaller fields of view with higher spatial resolution.1 The detector can be divided in two or more separate segments, called arms, which can be placed at different angles, allowing some flexibility for the scanner design. In particular, several arms can be set at different angles creating a target region of considerably higher resolution that can be used to track the evolution of a previously diagnosed condition, while keeping the patient completely inside the field of view (FOV).2 This work presents newly-developed computer models of single-slice VRX scanners that allow us to study and compare different configurations (that is, various types of detectors arranged in any number of arms arranged in different geometries) in terms of spatial and contrast resolution. In particular, we are interested in comparing the performance of various geometric configurations that would otherwise be considered equivalent (using the same equipment, imaging FOVs of the same sizes, and having a similar overall scanner size). For this, a VRX simulator was developed, along with mathematical phantoms for spatial resolution and contrast analysis. These tools were used to compare scanner configurations that can be reproduced with materials presently available in our lab.

GATE simulation of a new design of pinhole SPECT system for small animal brain imaging

NASA Astrophysics Data System (ADS)

Uzun Ozsahin, D.; Bläckberg, L.; El Fakhri, G.; Sabet, H.

2017-01-01

Small animal SPECT imaging has gained an increased interest over the past decade since it is an excellent tool for developing new drugs and tracers. Therefore, there is a huge effort on the development of cost-effective SPECT detectors with high capabilities. The aim of this study is to simulate the performance characteristics of new designs for a cost effective, stationary SPECT system dedicated to small animal imaging with a focus on mice brain. The conceptual design of this SPECT system platform, Stationary Small Animal SSA-SPECT, is to use many pixelated CsI:TI detector modules with 0.4 mm × 0.4 mm pixels in order to achieve excellent intrinsic detector resolution where each module is backed by a single pinhole collimator with 0.3 mm hole diameter. In this work, we present the simulation results of four variations of the SSA-SPECT platform where the number of detector modules and FOV size is varied while keeping the detector size and collimator hole size constant. Using the NEMA NU-4 protocol, we performed spatial resolution, sensitivity, image quality simulations followed by a Derenzo-like phantom evaluation. The results suggest that all four SSA-SPECT systems can provide better than 0.063% system sensitivity and < 1.5 mm FWHM spatial resolution without resolution recovery or other correction techniques. Specifically, SSA-SPECT-1 showed a system sensitivity of 0.09% in combination with 1.1 mm FWHM spatial resolution.

Statistical analysis of corn yields responding to climate variability at various spatio-temporal resolutions

NASA Astrophysics Data System (ADS)

Jiang, H.; Lin, T.

2017-12-01

Rain-fed corn production systems are subject to sub-seasonal variations of precipitation and temperature during the growing season. As each growth phase has varied inherent physiological process, plants necessitate different optimal environmental conditions during each phase. However, this temporal heterogeneity towards climate variability alongside the lifecycle of crops is often simplified and fixed as constant responses in large scale statistical modeling analysis. To capture the time-variant growing requirements in large scale statistical analysis, we develop and compare statistical models at various spatial and temporal resolutions to quantify the relationship between corn yield and weather factors for 12 corn belt states from 1981 to 2016. The study compares three spatial resolutions (county, agricultural district, and state scale) and three temporal resolutions (crop growth phase, monthly, and growing season) to characterize the effects of spatial and temporal variability. Our results show that the agricultural district model together with growth phase resolution can explain 52% variations of corn yield caused by temperature and precipitation variability. It provides a practical model structure balancing the overfitting problem in county specific model and weak explanation power in state specific model. In US corn belt, precipitation has positive impact on corn yield in growing season except for vegetative stage while extreme heat attains highest sensitivity from silking to dough phase. The results show the northern counties in corn belt area are less interfered by extreme heat but are more vulnerable to water deficiency.

Digital polarization holography advancing geometrical phase optics.

PubMed

De Sio, Luciano; Roberts, David E; Liao, Zhi; Nersisyan, Sarik; Uskova, Olena; Wickboldt, Lloyd; Tabiryan, Nelson; Steeves, Diane M; Kimball, Brian R

2016-08-08

Geometrical phase or the fourth generation (4G) optics enables realization of optical components (lenses, prisms, gratings, spiral phase plates, etc.) by patterning the optical axis orientation in the plane of thin anisotropic films. Such components exhibit near 100% diffraction efficiency over a broadband of wavelengths. The films are obtained by coating liquid crystalline (LC) materials over substrates with patterned alignment conditions. Photo-anisotropic materials are used for producing desired alignment conditions at the substrate surface. We present and discuss here an opportunity of producing the widest variety of "free-form" 4G optical components with arbitrary spatial patterns of the optical anisotropy axis orientation with the aid of a digital spatial light polarization converter (DSLPC). The DSLPC is based on a reflective, high resolution spatial light modulator (SLM) combined with an "ad hoc" optical setup. The most attractive feature of the use of a DSLPC for photoalignment of nanometer thin photo-anisotropic coatings is that the orientation of the alignment layer, and therefore of the fabricated LC or LC polymer (LCP) components can be specified on a pixel-by-pixel basis with high spatial resolution. By varying the optical magnification or de-magnification the spatial resolution of the photoaligned layer can be adjusted to an optimum for each application. With a simple "click" it is possible to record different optical components as well as arbitrary patterns ranging from lenses to invisible labels and other transparent labels that reveal different images depending on the side from which they are viewed.

In-operando synchronous time-multiplexed O K-edge x-ray absorption spectromicroscopy of functioning tantalum oxide memristors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, Suhas; Department of Electrical Engineering, Stanford University, Stanford, California 94305; Graves, Catherine E.

2015-07-21

Memristors are receiving keen interest because of their potential varied applications and promising large-scale information storage capabilities. Tantalum oxide is a memristive material that has shown promise for high-performance nonvolatile computer memory. The microphysics has been elusive because of the small scale and subtle physical changes that accompany conductance switching. In this study, we probed the atomic composition, local chemistry, and electronic structure of functioning tantalum oxide memristors through spatially mapped O K-edge x-ray absorption. We developed a time-multiplexed spectromicroscopy technique to enhance the weak and possibly localized oxide modifications with spatial and spectral resolutions of <30 nm and 70 meV, respectively.more » During the initial stages of conductance switching of a micrometer sized crosspoint device, the spectral changes were uniform within the spatial resolution of our technique. When the device was further driven with millions of high voltage-pulse cycles, we observed lateral motion and separation of ∼100 nm-scale agglomerates of both oxygen interstitials and vacancies. We also demonstrate a unique capability of this technique by identifying the relaxation behavior in the material during electrical stimuli by identifying electric field driven changes with varying pulse widths. In addition, we show that changes to the material can be localized to a spatial region by modifying its topography or uniformity, as against spatially uniform changes observed here during memristive switching. The goal of this report is to introduce the capability of time-multiplexed x-ray spectromicroscopy in studying weak-signal transitions in inhomogeneous media through the example of the operation and temporal evolution of a memristor.« less

The spatial sensitivity of the spectral diversity-biodiversity relationship: an experimental test in a prairie grassland.

PubMed

Wang, Ran; Gamon, John A; Cavender-Bares, Jeannine; Townsend, Philip A; Zygielbaum, Arthur I

2018-03-01

Remote sensing has been used to detect plant biodiversity in a range of ecosystems based on the varying spectral properties of different species or functional groups. However, the most appropriate spatial resolution necessary to detect diversity remains unclear. At coarse resolution, differences among spectral patterns may be too weak to detect. In contrast, at fine resolution, redundant information may be introduced. To explore the effect of spatial resolution, we studied the scale dependence of spectral diversity in a prairie ecosystem experiment at Cedar Creek Ecosystem Science Reserve, Minnesota, USA. Our study involved a scaling exercise comparing synthetic pixels resampled from high-resolution images within manipulated diversity treatments. Hyperspectral data were collected using several instruments on both ground and airborne platforms. We used the coefficient of variation (CV) of spectral reflectance in space as the indicator of spectral diversity and then compared CV at different scales ranging from 1 mm 2 to 1 m 2 to conventional biodiversity metrics, including species richness, Shannon's index, Simpson's index, phylogenetic species variation, and phylogenetic species evenness. In this study, higher species richness plots generally had higher CV. CV showed higher correlations with Shannon's index and Simpson's index than did species richness alone, indicating evenness contributed to the spectral diversity. Correlations with species richness and Simpson's index were generally higher than with phylogenetic species variation and evenness measured at comparable spatial scales, indicating weaker relationships between spectral diversity and phylogenetic diversity metrics than with species diversity metrics. High resolution imaging spectrometer data (1 mm 2 pixels) showed the highest sensitivity to diversity level. With decreasing spatial resolution, the difference in CV between diversity levels decreased and greatly reduced the optical detectability of biodiversity. The optimal pixel size for distinguishing α diversity in these prairie plots appeared to be around 1 mm to 10 cm, a spatial scale similar to the size of an individual herbaceous plant. These results indicate a strong scale-dependence of the spectral diversity-biodiversity relationships, with spectral diversity best able to detect a combination of species richness and evenness, and more weakly detecting phylogenetic diversity. These findings can be used to guide airborne studies of biodiversity and develop more effective large-scale biodiversity sampling methods. ©2018 The Authors Ecological Applications published by Wiley Periodicals, Inc. on behalf of Ecological Society of America.

Robustness of movement models: can models bridge the gap between temporal scales of data sets and behavioural processes?

PubMed

Schlägel, Ulrike E; Lewis, Mark A

2016-12-01

Discrete-time random walks and their extensions are common tools for analyzing animal movement data. In these analyses, resolution of temporal discretization is a critical feature. Ideally, a model both mirrors the relevant temporal scale of the biological process of interest and matches the data sampling rate. Challenges arise when resolution of data is too coarse due to technological constraints, or when we wish to extrapolate results or compare results obtained from data with different resolutions. Drawing loosely on the concept of robustness in statistics, we propose a rigorous mathematical framework for studying movement models' robustness against changes in temporal resolution. In this framework, we define varying levels of robustness as formal model properties, focusing on random walk models with spatially-explicit component. With the new framework, we can investigate whether models can validly be applied to data across varying temporal resolutions and how we can account for these different resolutions in statistical inference results. We apply the new framework to movement-based resource selection models, demonstrating both analytical and numerical calculations, as well as a Monte Carlo simulation approach. While exact robustness is rare, the concept of approximate robustness provides a promising new direction for analyzing movement models.

Projected future vegetation changes for the northwest United States and southwest Canada at a fine spatial resolution using a dynamic global vegetation model.

USGS Publications Warehouse

Shafer, Sarah; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Plautz, Tia E.; Johnson, R. P.; Sadrozinski, H. F.-W.

Purpose: To characterize the modulation transfer function (MTF) of the pre-clinical (phase II) head scanner developed for proton computed tomography (pCT) by the pCT collaboration. To evaluate the spatial resolution achievable by this system. Methods: Our phase II proton CT scanner prototype consists of two silicon telescopes that track individual protons upstream and downstream from a phantom, and a 5-stage scintillation detector that measures a combination of the residual energy and range of the proton. Residual energy is converted to water equivalent path length (WEPL) of the protons in the scanned object. The set of WEPL values and associated pathsmore » of protons passing through the object over a 360° angular scan is processed by an iterative parallelizable reconstruction algorithm that runs on GP-GPU hardware. A custom edge phantom composed of water-equivalent polymer and tissue-equivalent material inserts was constructed. The phantom was first simulated in Geant4 and then built to perform experimental beam tests with 200 MeV protons at the Northwestern Medicine Chicago Proton Center. The oversampling method was used to construct radial and azimuthal edge spread functions and modulation transfer functions. The spatial resolution was defined by the 10% point of the modulation transfer function in units of lp/cm. Results: The spatial resolution of the image was found to be strongly correlated with the radial position of the insert but independent of the relative stopping power of the insert. The spatial resolution varies between roughly 4 and 6 lp/cm in both the the radial and azimuthal directions depending on the radial displacement of the edge. Conclusion: The amount of image degradation due to our detector system is small compared with the effects of multiple Coulomb scattering, pixelation of the image and the reconstruction algorithm. Improvements in reconstruction will be made in order to achieve the theoretical limits of spatial resolution.« less

Estimating Temperature Retrieval Accuracy Associated With Thermal Band Spatial Resolution Requirements for Center Pivot Irrigation Monitoring and Management

NASA Technical Reports Server (NTRS)

Ryan, Robert E.; Irons, James; Spruce, Joseph P.; Underwood, Lauren W.; Pagnutti, Mary

2006-01-01

This study explores the use of synthetic thermal center pivot irrigation scenes to estimate temperature retrieval accuracy for thermal remote sensed data, such as data acquired from current and proposed Landsat-like thermal systems. Center pivot irrigation is a common practice in the western United States and in other parts of the world where water resources are scarce. Wide-area ET (evapotranspiration) estimates and reliable water management decisions depend on accurate temperature information retrieval from remotely sensed data. Spatial resolution, sensor noise, and the temperature step between a field and its surrounding area impose limits on the ability to retrieve temperature information. Spatial resolution is an interrelationship between GSD (ground sample distance) and a measure of image sharpness, such as edge response or edge slope. Edge response and edge slope are intuitive, and direct measures of spatial resolution are easier to visualize and estimate than the more common Modulation Transfer Function or Point Spread Function. For these reasons, recent data specifications, such as those for the LDCM (Landsat Data Continuity Mission), have used GSD and edge response to specify spatial resolution. For this study, we have defined a 400-800 m diameter center pivot irrigation area with a large 25 K temperature step associated with a 300 K well-watered field surrounded by an infinite 325 K dry area. In this context, we defined the benchmark problem as an easily modeled, highly common stressing case. By parametrically varying GSD (30-240 m) and edge slope, we determined the number of pixels and field area fraction that meet a given temperature accuracy estimate for 400-m, 600-m, and 800-m diameter field sizes. Results of this project will help assess the utility of proposed specifications for the LDCM and other future thermal remote sensing missions and for water resource management.

A 50-m forest cover map in Southeast Asia from ALOS/PALSAR and its application on forest fragmentation assessment.

PubMed

Dong, Jinwei; Xiao, Xiangming; Sheldon, Sage; Biradar, Chandrashekhar; Zhang, Geli; Duong, Nguyen Dinh; Hazarika, Manzul; Wikantika, Ketut; Takeuhci, Wataru; Moore, Berrien

2014-01-01

Southeast Asia experienced higher rates of deforestation than other continents in the 1990s and still was a hotspot of forest change in the 2000s. Biodiversity conservation planning and accurate estimation of forest carbon fluxes and pools need more accurate information about forest area, spatial distribution and fragmentation. However, the recent forest maps of Southeast Asia were generated from optical images at spatial resolutions of several hundreds of meters, and they do not capture well the exceptionally complex and dynamic environments in Southeast Asia. The forest area estimates from those maps vary substantially, ranging from 1.73×10(6) km(2) (GlobCover) to 2.69×10(6) km(2) (MCD12Q1) in 2009; and their uncertainty is constrained by frequent cloud cover and coarse spatial resolution. Recently, cloud-free imagery from the Phased Array Type L-band Synthetic Aperture Radar (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) became available. We used the PALSAR 50-m orthorectified mosaic imagery in 2009 to generate a forest cover map of Southeast Asia at 50-m spatial resolution. The validation, using ground-reference data collected from the Geo-Referenced Field Photo Library and high-resolution images in Google Earth, showed that our forest map has a reasonably high accuracy (producer's accuracy 86% and user's accuracy 93%). The PALSAR-based forest area estimates in 2009 are significantly correlated with those from GlobCover and MCD12Q1 at national and subnational scales but differ in some regions at the pixel scale due to different spatial resolutions, forest definitions, and algorithms. The resultant 50-m forest map was used to quantify forest fragmentation and it revealed substantial details of forest fragmentation. This new 50-m map of tropical forests could serve as a baseline map for forest resource inventory, deforestation monitoring, reducing emissions from deforestation and forest degradation (REDD+) implementation, and biodiversity.

A 50-m Forest Cover Map in Southeast Asia from ALOS/PALSAR and Its Application on Forest Fragmentation Assessment

PubMed Central

Dong, Jinwei; Xiao, Xiangming; Sheldon, Sage; Biradar, Chandrashekhar; Zhang, Geli; Dinh Duong, Nguyen; Hazarika, Manzul; Wikantika, Ketut; Takeuhci, Wataru; Moore, Berrien

2014-01-01

Southeast Asia experienced higher rates of deforestation than other continents in the 1990s and still was a hotspot of forest change in the 2000s. Biodiversity conservation planning and accurate estimation of forest carbon fluxes and pools need more accurate information about forest area, spatial distribution and fragmentation. However, the recent forest maps of Southeast Asia were generated from optical images at spatial resolutions of several hundreds of meters, and they do not capture well the exceptionally complex and dynamic environments in Southeast Asia. The forest area estimates from those maps vary substantially, ranging from 1.73×106 km2 (GlobCover) to 2.69×106 km2 (MCD12Q1) in 2009; and their uncertainty is constrained by frequent cloud cover and coarse spatial resolution. Recently, cloud-free imagery from the Phased Array Type L-band Synthetic Aperture Radar (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) became available. We used the PALSAR 50-m orthorectified mosaic imagery in 2009 to generate a forest cover map of Southeast Asia at 50-m spatial resolution. The validation, using ground-reference data collected from the Geo-Referenced Field Photo Library and high-resolution images in Google Earth, showed that our forest map has a reasonably high accuracy (producer's accuracy 86% and user's accuracy 93%). The PALSAR-based forest area estimates in 2009 are significantly correlated with those from GlobCover and MCD12Q1 at national and subnational scales but differ in some regions at the pixel scale due to different spatial resolutions, forest definitions, and algorithms. The resultant 50-m forest map was used to quantify forest fragmentation and it revealed substantial details of forest fragmentation. This new 50-m map of tropical forests could serve as a baseline map for forest resource inventory, deforestation monitoring, reducing emissions from deforestation and forest degradation (REDD+) implementation, and biodiversity. PMID:24465714

Nanoscale magnetic imaging with a single nitrogen-vacancy center in diamond

NASA Astrophysics Data System (ADS)

Hong, Sungkun

Magnetic imaging has been playing central roles not only in fundamental sciences but also in engineering and industry. Their numerous applications can be found in various areas, ranging from chemical analysis and biomedical imaging to magnetic data storage technology. An outstanding problem is to develop new magnetic imaging techniques with improved spatial resolutions down to nanoscale, while maintaining their magnetic sensitivities. For instance, if detecting individual electron or nuclear spins with nanomter spatial resolution is possible, it would allow for direct imaging of chemical structures of complex molecules, which then could bring termendous impacts on biological sciences. While realization of such nanoscale magnetic imaging still remains challenging, nitrogen-vacancy (NV) defects in diamond have recently considered as promising magnetic field sensors, as their electron spins show exceptionally long coherence even at room temperature. This thesis presents experimental progress in realizing a nanoscale magnetic imaging apparatus with a single nitrogen-vacancy (NV) color center diamond. We first fabricated diamond nanopillar devices hosting single NV centers at their ends, and incorporated them to a custom-built atomic force microscope (AFM). Our devices showed unprecedented combination of magnetic field sensitivity and spatial resolution for scanning NV systems. We then used these devices to magnetically image a single isolated electronic spin with nanometer resolution, for the first time under ambient condition. We also extended our study to improve and generalize the application of the scanning NV magnetometer we developed. We first introduced magnetic field gradients from a strongly magnetized tip, and demonstrated that the spatial resolution can be further improved by spectrally distinguishing identical spins at different locations. In addition, we developed a method to synchronize the periodic motion of an AFM tip and pulsed microwave sequences controlling an NV spin. This scheme enabled employment of 'AC magnetic field sensing scheme' in imaging samples with static and spatially varying magnetizations.

Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model

PubMed Central

Shafer, Sarah L.; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas. PMID:26488750

Differential Deposition for Surface Figure Corrections in Grazing Incidence X-Ray Optics

NASA Technical Reports Server (NTRS)

Ramsey, Brian D.; Kilaru, Kiranmayee; Atkins, Carolyn; Gubarev, Mikhail V.; Broadway, David M.

2015-01-01

Differential deposition corrects the low- and mid- spatial-frequency deviations in the axial figure of Wolter-type grazing incidence X-ray optics. Figure deviations is one of the major contributors to the achievable angular resolution. Minimizing figure errors can significantly improve the imaging quality of X-ray optics. Material of varying thickness is selectively deposited, using DC magnetron sputtering, along the length of optic to minimize figure deviations. Custom vacuum chambers are built that can incorporate full-shell and segmented Xray optics. Metrology data of preliminary corrections on a single meridian of full-shell x-ray optics show an improvement of mid-spatial frequencies from 6.7 to 1.8 arc secs HPD. Efforts are in progress to correct a full-shell and segmented optics and to verify angular-resolution improvement with X-ray testing.

Fast, Accurate and Shift-Varying Line Projections for Iterative Reconstruction Using the GPU

PubMed Central

Pratx, Guillem; Chinn, Garry; Olcott, Peter D.; Levin, Craig S.

2013-01-01

List-mode processing provides an efficient way to deal with sparse projections in iterative image reconstruction for emission tomography. An issue often reported is the tremendous amount of computation required by such algorithm. Each recorded event requires several back- and forward line projections. We investigated the use of the programmable graphics processing unit (GPU) to accelerate the line-projection operations and implement fully-3D list-mode ordered-subsets expectation-maximization for positron emission tomography (PET). We designed a reconstruction approach that incorporates resolution kernels, which model the spatially-varying physical processes associated with photon emission, transport and detection. Our development is particularly suitable for applications where the projection data is sparse, such as high-resolution, dynamic, and time-of-flight PET reconstruction. The GPU approach runs more than 50 times faster than an equivalent CPU implementation while image quality and accuracy are virtually identical. This paper describes in details how the GPU can be used to accelerate the line projection operations, even when the lines-of-response have arbitrary endpoint locations and shift-varying resolution kernels are used. A quantitative evaluation is included to validate the correctness of this new approach. PMID:19244015

Comparison of fractal dimensions based on segmented NDVI fields obtained from different remote sensors.

NASA Astrophysics Data System (ADS)

Alonso, C.; Benito, R. M.; Tarquis, A. M.

2012-04-01

Satellite image data have become an important source of information for monitoring vegetation and mapping land cover at several scales. Beside this, the distribution and phenology of vegetation is largely associated with climate, terrain characteristics and human activity. Various vegetation indices have been developed for qualitative and quantitative assessment of vegetation using remote spectral measurements. In particular, sensors with spectral bands in the red (RED) and near-infrared (NIR) lend themselves well to vegetation monitoring and based on them [(NIR - RED) / (NIR + RED)] Normalized Difference Vegetation Index (NDVI) has been widespread used. Given that the characteristics of spectral bands in RED and NIR vary distinctly from sensor to sensor, NDVI values based on data from different instruments will not be directly comparable. The spatial resolution also varies significantly between sensors, as well as within a given scene in the case of wide-angle and oblique sensors. As a result, NDVI values will vary according to combinations of the heterogeneity and scale of terrestrial surfaces and pixel footprint sizes. Therefore, the question arises as to the impact of differences in spectral and spatial resolutions on vegetation indices like the NDVI. The aim of this study is to establish a comparison between two different sensors in their NDVI values at different spatial resolutions. Scaling analysis and modeling techniques are increasingly understood to be the result of nonlinear dynamic mechanisms repeating scale after scale from large to small scales leading to non-classical resolution dependencies. In the remote sensing framework the main characteristic of sensors images is the high local variability in their values. This variability is a consequence of the increase in spatial and radiometric resolution that implies an increase in complexity that it is necessary to characterize. Fractal and multifractal techniques has been proven to be useful to extract such complexities from remote sensing images and will applied in this study to see the scaling behavior for each sensor in generalized fractal dimensions. The studied area is located in the provinces of Caceres and Salamanca (east of Iberia Peninsula) with an extension of 32 x 32 km2. The altitude in the area varies from 1,560 to 320 m, comprising natural vegetation in the mountain area (forest and bushes) and agricultural crops in the valleys. Scaling analysis were applied to Landsat-5 and MODIS TERRA to the normalized derived vegetation index (NDVI) on the same region with one day of difference, 13 and 12 of July 2003 respectively. From these images the area of interest was selected obtaining 1024 x 1024 pixels for Landsat image and 128 x 128 pixels for MODIS image. This implies that the resolution for MODIS is 250x250 m. and for Landsat is 30x30 m. From the reflectance data obtained from NIR and RED bands, NDVI was calculated for each image focusing this study on 0.2 to 0.5 ranges of values. Once that both NDVI fields were obtained several fractal dimensions were estimated in each one segmenting the values in 0.20-0.25, 0.25-0.30 and so on to rich 0.45-0.50. In all the scaling analysis the scale size length was expressed in meters, and not in pixels, to make the comparison between both sensors possible. Results are discussed. Acknowledgements This work has been supported by the Spanish MEC under Projects No. AGL2010-21501/AGR, MTM2009-14621 and i-MATH No. CSD2006-00032

Mass Fluxes of Ice and Oxygen Across the Entire Lid of Lake Vostok from Observations of Englacial Radiowave Attenuation

NASA Astrophysics Data System (ADS)

Winebrenner, D. P.; Kintner, P. M. S.; MacGregor, J. A.

2017-12-01

Over deep Antarctic subglacial lakes, spatially varying ice thickness and the pressure-dependent melting point of ice result in areas of melting and accretion at the ice-water interface, i.e., the lake lid. These ice mass fluxes drive lake circulation and, because basal Antarctic ice contains air-clathrate, affect the input of oxygen to the lake, with implications for subglacial life. Inferences of melting and accretion from radar-layer tracking and geodesy are limited in spatial coverage and resolution. Here we develop a new method to estimate rates of accretion, melting, and the resulting oxygen input at a lake lid, using airborne radar data over Lake Vostok together with ice-temperature and chemistry data from the Vostok ice core. Because the lake lid is a coherent reflector of known reflectivity (at our radar frequency), we can infer depth-averaged radiowave attenuation in the ice, with spatial resolution 1 km along flight lines. Spatial variation in attenuation depends mostly on variation in ice temperature near the lid, which in turn varies strongly with ice mass flux at the lid. We model ice temperature versus depth with ice mass flux as a parameter, thus linking that flux to (observed) depth-averaged attenuation. The resulting map of melt- and accretion-rates independently reproduces features known from earlier studies, but now covers the entire lid. We find that accretion is dominant when integrated over the lid, with an ice imbalance of 0.05 to 0.07 km3 a-1, which is robust against uncertainties.

An integrated and highly sensitive ultrafast acoustoelectric imaging system for biomedical applications

NASA Astrophysics Data System (ADS)

Berthon, Beatrice; Dansette, Pierre-Marc; Tanter, Mickaël; Pernot, Mathieu; Provost, Jean

2017-07-01

Direct imaging of the electrical activation of the heart is crucial to better understand and diagnose diseases linked to arrhythmias. This work presents an ultrafast acoustoelectric imaging (UAI) system for direct and non-invasive ultrafast mapping of propagating current densities using the acoustoelectric effect. Acoustoelectric imaging is based on the acoustoelectric effect, the modulation of the medium’s electrical impedance by a propagating ultrasonic wave. UAI triggers this effect with plane wave emissions to image current densities. An ultrasound research platform was fitted with electrodes connected to high common-mode rejection ratio amplifiers and sampled by up to 128 independent channels. The sequences developed allow for both real-time display of acoustoelectric maps and long ultrafast acquisition with fast off-line processing. The system was evaluated by injecting controlled currents into a saline pool via copper wire electrodes. Sensitivity to low current and low acoustic pressure were measured independently. Contrast and spatial resolution were measured for varying numbers of plane waves and compared to line per line acoustoelectric imaging with focused beams at equivalent peak pressure. Temporal resolution was assessed by measuring time-varying current densities associated with sinusoidal currents. Complex intensity distributions were also imaged in 3D. Electrical current densities were detected for injected currents as low as 0.56 mA. UAI outperformed conventional focused acoustoelectric imaging in terms of contrast and spatial resolution when using 3 and 13 plane waves or more, respectively. Neighboring sinusoidal currents with opposed phases were accurately imaged and separated. Time-varying currents were mapped and their frequency accurately measured for imaging frame rates up to 500 Hz. Finally, a 3D image of a complex intensity distribution was obtained. The results demonstrated the high sensitivity of the UAI system proposed. The plane wave based approach provides a highly flexible trade-off between frame rate, resolution and contrast. In conclusion, the UAI system shows promise for non-invasive, direct and accurate real-time imaging of electrical activation in vivo.

Mapping lightscapes: spatial patterning of artificial lighting in an urban landscape.

PubMed

Hale, James D; Davies, Gemma; Fairbrass, Alison J; Matthews, Thomas J; Rogers, Christopher D F; Sadler, Jon P

2013-01-01

Artificial lighting is strongly associated with urbanisation and is increasing in its extent, brightness and spectral range. Changes in urban lighting have both positive and negative effects on city performance, yet little is known about how its character and magnitude vary across the urban landscape. A major barrier to related research, planning and governance has been the lack of lighting data at the city extent, particularly at a fine spatial resolution. Our aims were therefore to capture such data using aerial night photography and to undertake a case study of urban lighting. We present the finest scale multi-spectral lighting dataset available for an entire city and explore how lighting metrics vary with built density and land-use. We found positive relationships between artificial lighting indicators and built density at coarse spatial scales, whilst at a local level lighting varied with land-use. Manufacturing and housing are the primary land-use zones responsible for the city's brightly lit areas, yet manufacturing sites are relatively rare within the city. Our data suggests that efforts to address light pollution should broaden their focus from residential street lighting to include security lighting within manufacturing areas.

Mapping Lightscapes: Spatial Patterning of Artificial Lighting in an Urban Landscape

PubMed Central

Hale, James D.; Davies, Gemma; Fairbrass, Alison J.; Matthews, Thomas J.; Rogers, Christopher D. F.; Sadler, Jon P.

2013-01-01

Artificial lighting is strongly associated with urbanisation and is increasing in its extent, brightness and spectral range. Changes in urban lighting have both positive and negative effects on city performance, yet little is known about how its character and magnitude vary across the urban landscape. A major barrier to related research, planning and governance has been the lack of lighting data at the city extent, particularly at a fine spatial resolution. Our aims were therefore to capture such data using aerial night photography and to undertake a case study of urban lighting. We present the finest scale multi-spectral lighting dataset available for an entire city and explore how lighting metrics vary with built density and land-use. We found positive relationships between artificial lighting indicators and built density at coarse spatial scales, whilst at a local level lighting varied with land-use. Manufacturing and housing are the primary land-use zones responsible for the city’s brightly lit areas, yet manufacturing sites are relatively rare within the city. Our data suggests that efforts to address light pollution should broaden their focus from residential street lighting to include security lighting within manufacturing areas. PMID:23671566

Distributed Temperature Sensing of hyporheic flux patterns in varied space and time around beaver dams

NASA Astrophysics Data System (ADS)

Briggs, M.; Lautz, L. K.; McKenzie, J. M.

2010-12-01

Small dams enhance hyporheic interaction by creating punctuated head differentials along streams, thereby affecting redox conditions and nutrient cycling in the streambed. As beaver populations return, they create dams that alter hyporheic flowpaths locally, an effect which may integrate at the reach scale to produce a net hydrological and ecological functional change. Streambed heterogeneity around beaver dams combines with varied morphology, head differentials and stream velocities to create patterns of hyporheic seepage flux that vary in both space and time. Heat has been used as a groundwater tracer for many years, but it’s dependence on spatially disperse point measurements has only recently been resolved by the development of Distributed Temperature Sensing (DTS) fiber-optic technology. Modified applications of DTS include wrapping the fiber around a mandrel to increase spatial resolution dramatically. Wrapped configurations can be installed vertically in the streambed to provide data for heat transport modeling of vertical hyporheic flux. The vertically continuous dataset generated with DTS may be more informative regarding subsurface heterogeneity than more commonly used spatially discrete thermocouples. We installed a total of nine wrapped DTS rods with 1.4 cm vertical spatial resolution above two beaver dams in Cherry Creek, a tributary of the Little Popo Agie River in Lander, Wyoming, USA. Data was collected over 20 min periods in dual-ended mode continuously for one month (10-Jul to 10-Aug 2010) during baseflow recession, as discharge dropped from 384 Ls-1 to 211 Ls-1. The temperature rods were installed to at least 0.75 m depth within bed sediments at varied distances upstream of the dams in diverse stream morphological units, which ranged from gravel bars to clay lined pools. Diurnal fluctuations in stream temperature were generally between 4.5 and 5.5 oC in amplitude, imparting a strong potential signal for propagation into the bed due to advective hyporheic flux. In many locations monthly temperature standard deviations at the 10 cm depth were larger than that of the overlying stream water, indicating direct heating of the streambed by solar radiation was an important process, even in that high velocity system. The high-resolution temperature records revealed local heterogeneity in the streambed at each rod and indicated the largest hyporheic flux was within gravel bars close to the dams. The smallest flux was through a gravel bar farther upstream of the dam, and through the deepest portions of pools closer to the dam. High flux regions had monthly temperature standard deviations close to that of the stream (1.5 oC) at shallow depths, while shallow sediments in pools had much more muted temperature oscillations. At 0.5 m depth, all rods had similar, smaller temperature standard deviations, ranging from 0.64-0.80 oC. The extensive and spatially continuous data set generated using DTS allowed us to determine hyporheic flux patterns for virtually any depth and time along the high-resolution temperature rods, a crucial step for understanding transient patterns in biogeochemical processing around beaver dams.

Low-Cost Sensor Units for Measuring Urban Air Quality

NASA Astrophysics Data System (ADS)

Popoola, O. A.; Mead, M.; Stewart, G.; Hodgson, T.; McLoed, M.; Baldovi, J.; Landshoff, P.; Hayes, M.; Calleja, M.; Jones, R.

2010-12-01

Measurements of selected key air quality gases (CO, NO & NO2) have been made with a range of miniature low-cost sensors based on electrochemical gas sensing technology incorporating GPS and GPRS for position and communication respectively. Two types of simple to operate sensors units have been designed to be deployed in relatively large numbers. Mobile handheld sensor units designed for operation by members of the public have been deployed on numerous occasions including in Cambridge, London and Valencia. Static sensor units have also been designed for long-term autonomous deployment on existing street furniture. A study was recently completed in which 45 sensor units were deployed in the Cambridge area for a period of 3 months. Results from these studies indicate that air quality varies widely both spatially and temporally. The widely varying concentrations found suggest that the urban environment cannot be fully understood using limited static site (AURN) networks and that a higher resolution, more dispersed network is required to better define air quality in the urban environment. The results also suggest that higher spatial and temporal resolution measurements could improve knowledge of the levels of individual exposure in the urban environment.

Enhancing Spatial Resolution of Remotely Sensed Imagery Using Deep Learning

NASA Astrophysics Data System (ADS)

Beck, J. M.; Bridges, S.; Collins, C.; Rushing, J.; Graves, S. J.

2017-12-01

Researchers at the Information Technology and Systems Center at the University of Alabama in Huntsville are using Deep Learning with Convolutional Neural Networks (CNNs) to develop a method for enhancing the spatial resolutions of moderate resolution (10-60m) multispectral satellite imagery. This enhancement will effectively match the resolutions of imagery from multiple sensors to provide increased global temporal-spatial coverage for a variety of Earth science products. Our research is centered on using Deep Learning for automatically generating transformations for increasing the spatial resolution of remotely sensed images with different spatial, spectral, and temporal resolutions. One of the most important steps in using images from multiple sensors is to transform the different image layers into the same spatial resolution, preferably the highest spatial resolution, without compromising the spectral information. Recent advances in Deep Learning have shown that CNNs can be used to effectively and efficiently upscale or enhance the spatial resolution of multispectral images with the use of an auxiliary data source such as a high spatial resolution panchromatic image. In contrast, we are using both the spatial and spectral details inherent in low spatial resolution multispectral images for image enhancement without the use of a panchromatic image. This presentation will discuss how this technology will benefit many Earth Science applications that use remotely sensed images with moderate spatial resolutions.

Mapping regional distribution of a single tree species: Whitebark pine in the Greater Yellowstone Ecosystem

USGS Publications Warehouse

Landenburger, L.; Lawrence, R.L.; Podruzny, S.; Schwartz, C.C.

2008-01-01

Moderate resolution satellite imagery traditionally has been thought to be inadequate for mapping vegetation at the species level. This has made comprehensive mapping of regional distributions of sensitive species, such as whitebark pine, either impractical or extremely time consuming. We sought to determine whether using a combination of moderate resolution satellite imagery (Landsat Enhanced Thematic Mapper Plus), extensive stand data collected by land management agencies for other purposes, and modern statistical classification techniques (boosted classification trees) could result in successful mapping of whitebark pine. Overall classification accuracies exceeded 90%, with similar individual class accuracies. Accuracies on a localized basis varied based on elevation. Accuracies also varied among administrative units, although we were not able to determine whether these differences related to inherent spatial variations or differences in the quality of available reference data.

Geostatistical uncertainty of assessing air quality using high-spatial-resolution lichen data: A health study in the urban area of Sines, Portugal.

PubMed

Ribeiro, Manuel C; Pinho, P; Branquinho, C; Llop, Esteve; Pereira, Maria J

2016-08-15

In most studies correlating health outcomes with air pollution, personal exposure assignments are based on measurements collected at air-quality monitoring stations not coinciding with health data locations. In such cases, interpolators are needed to predict air quality in unsampled locations and to assign personal exposures. Moreover, a measure of the spatial uncertainty of exposures should be incorporated, especially in urban areas where concentrations vary at short distances due to changes in land use and pollution intensity. These studies are limited by the lack of literature comparing exposure uncertainty derived from distinct spatial interpolators. Here, we addressed these issues with two interpolation methods: regression Kriging (RK) and ordinary Kriging (OK). These methods were used to generate air-quality simulations with a geostatistical algorithm. For each method, the geostatistical uncertainty was drawn from generalized linear model (GLM) analysis. We analyzed the association between air quality and birth weight. Personal health data (n=227) and exposure data were collected in Sines (Portugal) during 2007-2010. Because air-quality monitoring stations in the city do not offer high-spatial-resolution measurements (n=1), we used lichen data as an ecological indicator of air quality (n=83). We found no significant difference in the fit of GLMs with any of the geostatistical methods. With RK, however, the models tended to fit better more often and worse less often. Moreover, the geostatistical uncertainty results showed a marginally higher mean and precision with RK. Combined with lichen data and land-use data of high spatial resolution, RK is a more effective geostatistical method for relating health outcomes with air quality in urban areas. This is particularly important in small cities, which generally do not have expensive air-quality monitoring stations with high spatial resolution. Further, alternative ways of linking human activities with their environment are needed to improve human well-being. Copyright © 2016 Elsevier B.V. All rights reserved.

Using High Spatial Resolution Satellite Imagery to Map Forest Burn Severity Across Spatial Scales in a Pine Barrens Ecosystem

NASA Technical Reports Server (NTRS)

Meng, Ran; Wu, Jin; Schwager, Kathy L.; Zhao, Feng; Dennison, Philip E.; Cook, Bruce D.; Brewster, Kristen; Green, Timothy M.; Serbin, Shawn P.

2017-01-01

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (less than or equal to 5 m) from very-high-resolution (VHR) data. We assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severity was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal - pre- and post-fire event - WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). This work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the less than 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.

Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meng, Ran; Wu, Jin; Schwager, Kathy L.

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (≤ 5 m) from very-high-resolution (VHR) data. Here we assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severitymore » was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal — pre- and post-fire event — WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). Lastly, this work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the < 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.« less

Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem

DOE PAGES

Meng, Ran; Wu, Jin; Schwager, Kathy L.; ...

2017-01-21

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (≤ 5 m) from very-high-resolution (VHR) data. Here we assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severitymore » was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal — pre- and post-fire event — WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). Lastly, this work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the < 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.« less

High-speed, random-access fluorescence microscopy: I. High-resolution optical recording with voltage-sensitive dyes and ion indicators.

PubMed

Bullen, A; Patel, S S; Saggau, P

1997-07-01

The design and implementation of a high-speed, random-access, laser-scanning fluorescence microscope configured to record fast physiological signals from small neuronal structures with high spatiotemporal resolution is presented. The laser-scanning capability of this nonimaging microscope is provided by two orthogonal acousto-optic deflectors under computer control. Each scanning point can be randomly accessed and has a positioning time of 3-5 microseconds. Sampling time is also computer-controlled and can be varied to maximize the signal-to-noise ratio. Acquisition rates up to 200k samples/s at 16-bit digitizing resolution are possible. The spatial resolution of this instrument is determined by the minimal spot size at the level of the preparation (i.e., 2-7 microns). Scanning points are selected interactively from a reference image collected with differential interference contrast optics and a video camera. Frame rates up to 5 kHz are easily attainable. Intrinsic variations in laser light intensity and scanning spot brightness are overcome by an on-line signal-processing scheme. Representative records obtained with this instrument by using voltage-sensitive dyes and calcium indicators demonstrate the ability to make fast, high-fidelity measurements of membrane potential and intracellular calcium at high spatial resolution (2 microns) without any temporal averaging.

Comparison of Different EO Sensors for Mapping Tree Species- A Case Study in Southwest Germany

NASA Astrophysics Data System (ADS)

Enßle, Fabian; Kattenborn, Teja; Koch, Barbara

2014-11-01

The variety of different remote sensing sensors and thus the types of data specifications which are available is increasing continuously. Especially the differences in geometric, radiometric and temporal resolutions of different platforms affect their ability for the mapping of forests. These differences hinder the comparability and application of uniform methods of different remotely sensed data across the same region of interest. The quality and quantity of retrieved forest parameters is directly dependent on the data source, and therefore the objective of this project is to analyse the relationship between the data source and its derived parameters. A comparison of different optical EO-data (e.g. spatial resolution and spectral resolution of specific bands) will help to define the optimum data sets to produce a reproducible method to provide additional inputs to the Dragon cooperative project, specifically to method development for woody biomass estimation and biodiversity assessment services. This poster presents the first results on tree species mapping in a mixed temperate forest by satellite imagery taken from four different sensors. Tree species addressed in this pilot study are Scots pine (Pinus sylvestris), sessile oak (Quercus petraea) and red oak (Quercus rubra). The spatial resolution varies from 2m to 30m and the spectral resolutions range from 8bands up to 155bands.

Comparison of Different EO Sensors for Mapping Tree Species- A Case Study in Southwest Germany

NASA Astrophysics Data System (ADS)

Enβle, Fabian; Kattenborn, Teja; Koch, Barbara

2014-11-01

The variety of different remote sensing sensors and thus the types of data specifications which are available is increasing continuously. Especially the differences in geometric, radiometric and temporal resolutions of different platforms affect their ability for the mapping of forests. These differences hinder the comparability and application of uniform methods of different remotely sensed data across the same region of interest. The quality and quantity of retrieved forest parameters is directly dependent on the data source, and therefore the objective of this project is to analyse the relationship between the data source and its derived parameters. A comparison of different optical EO-data (e.g. spatial resolution and spectral resolution of specific bands) will help to define the optimum data sets to produce a reproducible method to provide additional inputs to the Dragon cooperative project, specifically to method development for woody biomass estimation and biodiversity assessment services. This poster presents the first results on tree species mapping in a mixed temperate forest by satellite imagery taken from four different sensors. Tree species addressed in this pilot study are: Scots pine (Pinus sylvestris), sessile oak (Quercus petraea) and red oak (Quercus rubra). The spatial resolution varies from 2m to 30m and the spectral resolutions range from 8bands up to 155bands.

High-speed, random-access fluorescence microscopy: I. High-resolution optical recording with voltage-sensitive dyes and ion indicators.

PubMed Central

Bullen, A; Patel, S S; Saggau, P

1997-01-01

The design and implementation of a high-speed, random-access, laser-scanning fluorescence microscope configured to record fast physiological signals from small neuronal structures with high spatiotemporal resolution is presented. The laser-scanning capability of this nonimaging microscope is provided by two orthogonal acousto-optic deflectors under computer control. Each scanning point can be randomly accessed and has a positioning time of 3-5 microseconds. Sampling time is also computer-controlled and can be varied to maximize the signal-to-noise ratio. Acquisition rates up to 200k samples/s at 16-bit digitizing resolution are possible. The spatial resolution of this instrument is determined by the minimal spot size at the level of the preparation (i.e., 2-7 microns). Scanning points are selected interactively from a reference image collected with differential interference contrast optics and a video camera. Frame rates up to 5 kHz are easily attainable. Intrinsic variations in laser light intensity and scanning spot brightness are overcome by an on-line signal-processing scheme. Representative records obtained with this instrument by using voltage-sensitive dyes and calcium indicators demonstrate the ability to make fast, high-fidelity measurements of membrane potential and intracellular calcium at high spatial resolution (2 microns) without any temporal averaging. Images FIGURE 6 PMID:9199810

Integrated sensor with frame memory and programmable resolution for light adaptive imaging

NASA Technical Reports Server (NTRS)

Zhou, Zhimin (Inventor); Fossum, Eric R. (Inventor); Pain, Bedabrata (Inventor)

2004-01-01

An image sensor operable to vary the output spatial resolution according to a received light level while maintaining a desired signal-to-noise ratio. Signals from neighboring pixels in a pixel patch with an adjustable size are added to increase both the image brightness and signal-to-noise ratio. One embodiment comprises a sensor array for receiving input signals, a frame memory array for temporarily storing a full frame, and an array of self-calibration column integrators for uniform column-parallel signal summation. The column integrators are capable of substantially canceling fixed pattern noise.

A new global 1-km dataset of percentage tree cover derived from remote sensing

USGS Publications Warehouse

DeFries, R.S.; Hansen, M.C.; Townshend, J.R.G.; Janetos, A.C.; Loveland, Thomas R.

2000-01-01

Accurate assessment of the spatial extent of forest cover is a crucial requirement for quantifying the sources and sinks of carbon from the terrestrial biosphere. In the more immediate context of the United Nations Framework Convention on Climate Change, implementation of the Kyoto Protocol calls for estimates of carbon stocks for a baseline year as well as for subsequent years. Data sources from country level statistics and other ground-based information are based on varying definitions of 'forest' and are consequently problematic for obtaining spatially and temporally consistent carbon stock estimates. By combining two datasets previously derived from the Advanced Very High Resolution Radiometer (AVHRR) at 1 km spatial resolution, we have generated a prototype global map depicting percentage tree cover and associated proportions of trees with different leaf longevity (evergreen and deciduous) and leaf type (broadleaf and needleleaf). The product is intended for use in terrestrial carbon cycle models, in conjunction with other spatial datasets such as climate and soil type, to obtain more consistent and reliable estimates of carbon stocks. The percentage tree cover dataset is available through the Global Land Cover Facility at the University of Maryland at http://glcf.umiacs.umd.edu.

The estimation of probable maximum precipitation: the case of Catalonia.

PubMed

Casas, M Carmen; Rodríguez, Raül; Nieto, Raquel; Redaño, Angel

2008-12-01

A brief overview of the different techniques used to estimate the probable maximum precipitation (PMP) is presented. As a particular case, the 1-day PMP over Catalonia has been calculated and mapped with a high spatial resolution. For this purpose, the annual maximum daily rainfall series from 145 pluviometric stations of the Instituto Nacional de Meteorología (Spanish Weather Service) in Catalonia have been analyzed. In order to obtain values of PMP, an enveloping frequency factor curve based on the actual rainfall data of stations in the region has been developed. This enveloping curve has been used to estimate 1-day PMP values of all the 145 stations. Applying the Cressman method, the spatial analysis of these values has been achieved. Monthly precipitation climatological data, obtained from the application of Geographic Information Systems techniques, have been used as the initial field for the analysis. The 1-day PMP at 1 km(2) spatial resolution over Catalonia has been objectively determined, varying from 200 to 550 mm. Structures with wavelength longer than approximately 35 km can be identified and, despite their general concordance, the obtained 1-day PMP spatial distribution shows remarkable differences compared to the annual mean precipitation arrangement over Catalonia.

Mapping wood density globally using remote sensing and climatological data

NASA Astrophysics Data System (ADS)

Moreno, A.; Camps-Valls, G.; Carvalhais, N.; Kattge, J.; Robinson, N.; Reichstein, M.; Allred, B. W.; Running, S. W.

2017-12-01

Wood density (WD) is defined as the oven-dry mass divided by fresh volume, varies between individuals, and describes the carbon investment per unit volume of stem. WD has been proven to be a key functional trait in carbon cycle research and correlates with numerous morphological, mechanical, physiological, and ecological properties. In spite of the utility and importance of this trait, there is a lack of an operational framework to spatialize plant WD measurements at a global scale. In this work, we present a consistent modular processing chain to derive global maps (500 m) of WD using modern machine learning techniques along with optical remote sensing data (MODIS/Landsat) and climate data using the Google Earth Engine platform. The developed approach uses a hierarchical Bayesian approach to fill in gaps in the plant measured WD data set to maximize its global representativeness. WD plant species are then aggregated to Plant Functional Types (PFT). The spatial abundance of PFT at 500 m spatial resolution (MODIS) is calculated using a high resolution (30 m) PFT map developed using Landsat data. Based on these PFT abundances, representative WD values are estimated for each MODIS pixel with nearby measured data. Finally, random forests are used to globally estimate WD from these MODIS pixels using remote sensing and climate. The validation and assessment of the applied methods indicate that the model explains more than 72% of the spatial variance of the calculated community aggregated WD estimates with virtually unbiased estimates and low RMSE (<15%). The maps thus offer new opportunities to study and analyze the global patterns of variation of WD at an unprecedented spatial coverage and spatial resolution.

Spatial Representativeness of PM2.5 Concentrations Obtained Using Observations From Network Stations

NASA Astrophysics Data System (ADS)

Shi, Xiaoqin; Zhao, Chuanfeng; Jiang, Jonathan H.; Wang, Chunying; Yang, Xin; Yung, Yuk L.

2018-03-01

Haze has been a focused air pollution phenomenon in China, and its characterization is highly desired. Aerosol properties obtained from a single station are frequently used to represent the haze condition over a large domain, such as tens of kilometers, which could result in high uncertainties due to their spatial variation. Using a high-resolution network observation over an urban city in North China from November 2015 to February 2016, this study examines the spatial representativeness of ground station observations of particulate matter with diameters less than 2.5 μm (PM2.5). We developed a new method to determine the representative area of PM2.5 measurements from limited stations. The key idea is to determine the PM2.5 spatial representative area using its spatial variability and temporal correlation. We also determine stations with large representative area using two grid networks with different resolutions. Based on the high spatial resolution measurements, the representative area of PM2.5 at one station can be determined from the grids with high correlations and small differences of PM2.5. The representative area for a single station in the study period ranges from 0.25 to 16.25 km2 but is less than 3 km2 for more than half of the stations. The representative area varies with locations, and observation at 10 optimal stations would have a good representativeness of those obtained from 169 stations for the 4 month time scale studied. Both evaluations with an empirical orthogonal function analysis and with independent data set corroborate the validity of the results found in this study.

Fine Particulate Matter Predictions Using High Resolution Aerosol Optical Depth (AOD) Retrievals

NASA Technical Reports Server (NTRS)

Chudnovsky, Alexandra A.; Koutrakis, Petros; Kloog, Itai; Melly, Steven; Nordio, Francesco; Lyapustin, Alexei; Wang, Jujie; Schwartz, Joel

2014-01-01

To date, spatial-temporal patterns of particulate matter (PM) within urban areas have primarily been examined using models. On the other hand, satellites extend spatial coverage but their spatial resolution is too coarse. In order to address this issue, here we report on spatial variability in PM levels derived from high 1 km resolution AOD product of Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm developed for MODIS satellite. We apply day-specific calibrations of AOD data to predict PM(sub 2.5) concentrations within the New England area of the United States. To improve the accuracy of our model, land use and meteorological variables were incorporated. We used inverse probability weighting (IPW) to account for nonrandom missingness of AOD and nested regions within days to capture spatial variation. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance among others. Out-of-sample "ten-fold" cross-validation was used to quantify the accuracy of model predictions. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations, with out-of- sample R(sub 2) of 0.89. Furthermore, our study shows that the model captures the pollution levels along highways and many urban locations thereby extending our ability to investigate the spatial patterns of urban air quality, such as examining exposures in areas with high traffic. Our results also show high accuracy within the cities of Boston and New Haven thereby indicating that MAIAC data can be used to examine intra-urban exposure contrasts in PM(sub 2.5) levels.

Effects of spatial resolution ratio in image fusion

USGS Publications Warehouse

Ling, Y.; Ehlers, M.; Usery, E.L.; Madden, M.

2008-01-01

In image fusion, the spatial resolution ratio can be defined as the ratio between the spatial resolution of the high-resolution panchromatic image and that of the low-resolution multispectral image. This paper attempts to assess the effects of the spatial resolution ratio of the input images on the quality of the fused image. Experimental results indicate that a spatial resolution ratio of 1:10 or higher is desired for optimal multisensor image fusion provided the input panchromatic image is not downsampled to a coarser resolution. Due to the synthetic pixels generated from resampling, the quality of the fused image decreases as the spatial resolution ratio decreases (e.g. from 1:10 to 1:30). However, even with a spatial resolution ratio as small as 1:30, the quality of the fused image is still better than the original multispectral image alone for feature interpretation. In cases where the spatial resolution ratio is too small (e.g. 1:30), to obtain better spectral integrity of the fused image, one may downsample the input high-resolution panchromatic image to a slightly lower resolution before fusing it with the multispectral image.

Digital Astronaut Photography: A Discovery Dataset for Archaeology

NASA Technical Reports Server (NTRS)

Stefanov, William L.

2010-01-01

Astronaut photography acquired from the International Space Station (ISS) using commercial off-the-shelf cameras offers a freely-accessible source for high to very high resolution (4-20 m/pixel) visible-wavelength digital data of Earth. Since ISS Expedition 1 in 2000, over 373,000 images of the Earth-Moon system (including land surface, ocean, atmospheric, and lunar images) have been added to the Gateway to Astronaut Photography of Earth online database (http://eol.jsc.nasa.gov ). Handheld astronaut photographs vary in look angle, time of acquisition, solar illumination, and spatial resolution. These attributes of digital astronaut photography result from a unique combination of ISS orbital dynamics, mission operations, camera systems, and the individual skills of the astronaut. The variable nature of astronaut photography makes the dataset uniquely useful for archaeological applications in comparison with more traditional nadir-viewing multispectral datasets acquired from unmanned orbital platforms. For example, surface features such as trenches, walls, ruins, urban patterns, and vegetation clearing and regrowth patterns may be accentuated by low sun angles and oblique viewing conditions (Fig. 1). High spatial resolution digital astronaut photographs can also be used with sophisticated land cover classification and spatial analysis approaches like Object Based Image Analysis, increasing the potential for use in archaeological characterization of landscapes and specific sites.

Analyzing Variability in Landscape Nutrient Loading Using Spatially-Explicit Maps in the Great Lakes Basin

NASA Astrophysics Data System (ADS)

Hamlin, Q. F.; Kendall, A. D.; Martin, S. L.; Whitenack, H. D.; Roush, J. A.; Hannah, B. A.; Hyndman, D. W.

2017-12-01

Excessive loading of nitrogen and phosphorous to the landscape has caused biologically and economically damaging eutrophication and harmful algal blooms in the Great Lakes Basin (GLB) and across the world. We mapped source-specific loads of nitrogen and phosphorous to the landscape using broadly available data across the GLB. SENSMap (Spatially Explicit Nutrient Source Map) is a 30m resolution snapshot of nutrient loads ca. 2010. We use these maps to study variable nutrient loading and provide this information to watershed managers through NOAA's GLB Tipping Points Planner. SENSMap individually maps nutrient point sources and six non-point sources: 1) atmospheric deposition, 2) septic tanks, 3) non-agricultural chemical fertilizer, 4) agricultural chemical fertilizer, 5) manure, and 6) nitrogen fixation from legumes. To model source-specific loads at high resolution, SENSMap synthesizes a wide range of remotely sensed, surveyed, and tabular data. Using these spatially explicit nutrient loading maps, we can better calibrate local land use-based water quality models and provide insight to watershed managers on how to focus nutrient reduction strategies. Here we examine differences in dominant nutrient sources across the GLB, and how those sources vary by land use. SENSMap's high resolution, source-specific approach offers a different lens to understand nutrient loading than traditional semi-distributed or land use based models.

High spatial resolution with zoomable saw-tooth refractive lenses?

NASA Astrophysics Data System (ADS)

Jark, Werner

2011-09-01

Refractive x-ray lenses can be assembled from two opposing saw-tooth structures, when they are inclined with respect to each other and almost touch at one end. An incident plane wave will then traverse a varying number of triangular prisms, which direct the beam towards the optical axis and focus it. Optically speaking the plane wave traverses a parabolic lens profile, which is approximated by trapezoidal segments. The parabolic profile will focus ideally, when a lens can be discussed in the "thin lens" approximation. Now the saw-tooth refractive lens is found to be too "thick". The residual aberrations limit the focusing capability to just submicrometer focusing, significantly above the limit in diffraction limited focusing. It is shown that the aberrations can be removed by introducing a variation into the originally constant saw-tooth angle. After this modification the lens can be operated in the diffraction limited regime. Spot sizes even below 0.1 micrometer are then feasible. This performance in terms of spatial resolution is found to be limited to focusing to microspots and is not available, when the saw-tooth refractive lens is used in an imaging setup. In this case the spatial resolution deteriorates rapidly with increasing off axis distance of the object to be imaged.

NDVI, scale invariance and the modifiable areal unit problem: An assessment of vegetation in the Adelaide Parklands.

PubMed

Nouri, Hamideh; Anderson, Sharolyn; Sutton, Paul; Beecham, Simon; Nagler, Pamela; Jarchow, Christopher J; Roberts, Dar A

2017-04-15

This research addresses the question as to whether or not the Normalised Difference Vegetation Index (NDVI) is scale invariant (i.e. constant over spatial aggregation) for pure pixels of urban vegetation. It has been long recognized that there are issues related to the modifiable areal unit problem (MAUP) pertaining to indices such as NDVI and images at varying spatial resolutions. These issues are relevant to using NDVI values in spatial analyses. We compare two different methods of calculation of a mean NDVI: 1) using pixel values of NDVI within feature/object boundaries and 2) first calculating the mean red and mean near-infrared across all feature pixels and then calculating NDVI. We explore the nature and magnitude of these differences for images taken from two sensors, a 1.24m resolution WorldView-3 and a 0.1m resolution digital aerial image. We apply these methods over an urban park located in the Adelaide Parklands of South Australia. We demonstrate that the MAUP is not an issue for calculation of NDVI within a sensor for pure urban vegetation pixels. This may prove useful for future rule-based monitoring of the ecosystem functioning of green infrastructure. Copyright © 2017 Elsevier B.V. All rights reserved.

Linking innovative measurement technologies (ConMon and Dataflow© systems) for high-resolution temporal and spatial dissolved oxygen criteria assessment.

PubMed

O'Leary, C A; Perry, E; Bayard, A; Wainger, L; Boynton, W R

2015-10-01

One consequence of nutrient-induced eutrophication in shallow estuarine waters is the occurrence of hypoxia and anoxia that has serious impacts on biota, habitats, and biogeochemical cycles of important elements. Because of the important role of dissolved oxygen (DO) on these ecosystem features, a variety of DO criteria have been established as indicators of system condition. However, DO dynamics are complex and vary on time scales ranging from diel to decadal and spatial scales from meters to multiple kilometers. Because of these complexities, determining DO criteria attainment or failure remains difficult. We propose a method for linking two common measurement technologies for shallow water DO criteria assessment using a Chesapeake Bay tributary as a test case. Dataflow© is a spatially intensive (30-60-m collection intervals) system used to map surface water conditions at the whole estuary scale, and ConMon is a high-frequency (15-min collection intervals) fixed station approach. The former technology is effective with spatial descriptions but poor regarding temporal resolution, while the latter provides excellent temporal but very limited spatial resolution. Our methodology for combining the strengths of these measurement technologies involved a sequence of steps. First, a statistical model of surface water DO dynamics, based on temporally intense ConMon data, was developed. The results of this model were used to calculate daily DO minimum concentrations. Second, this model was then inserted into Dataflow©-generated spatial maps of DO conditions and used to adjust measured DO concentrations to daily minimum concentrations. This information was used to assess DO criteria compliance at the full tributary scale. Model results indicated that it is vital to consider the short-term time scale DO criteria across both space and time concurrently. Large fluctuations in DO occurred within a 24-h time period, and DO dynamics varied across the length and width of the tributary. The overall result provided a more detailed and realistic characterization of the shallow water DO minimum conditions that have the potential to be extended to other tributaries and regions. Broader applications of this model include instantaneous DO criteria assessment, utilizing this model in combination with aerial remote sensing, and developing DO amplitude as an indicator of impaired water bodies.

Improvement in the accuracy of back trajectories using WRF to identify pollen sources in southern Iberian Peninsula.

PubMed

Hernández-Ceballos, M A; Skjøth, C A; García-Mozo, H; Bolívar, J P; Galán, C

2014-12-01

Airborne pollen transport at micro-, meso-gamma and meso-beta scales must be studied by atmospheric models, having special relevance in complex terrain. In these cases, the accuracy of these models is mainly determined by the spatial resolution of the underlying meteorological dataset. This work examines how meteorological datasets determine the results obtained from atmospheric transport models used to describe pollen transport in the atmosphere. We investigate the effect of the spatial resolution when computing backward trajectories with the HYSPLIT model. We have used meteorological datasets from the WRF model with 27, 9 and 3 km resolutions and from the GDAS files with 1° resolution. This work allows characterizing atmospheric transport of Olea pollen in a region with complex flows. The results show that the complex terrain affects the trajectories and this effect varies with the different meteorological datasets. Overall, the change from GDAS to WRF-ARW inputs improves the analyses with the HYSPLIT model, thereby increasing the understanding the pollen episode. The results indicate that a spatial resolution of at least 9 km is needed to simulate atmospheric flows that are considerable affected by the relief of the landscape. The results suggest that the appropriate meteorological files should be considered when atmospheric models are used to characterize the atmospheric transport of pollen on micro-, meso-gamma and meso-beta scales. Furthermore, at these scales, the results are believed to be generally applicable for related areas such as the description of atmospheric transport of radionuclides or in the definition of nuclear-radioactivity emergency preparedness.

Improvement in the accuracy of back trajectories using WRF to identify pollen sources in southern Iberian Peninsula

NASA Astrophysics Data System (ADS)

Hernández-Ceballos, M. A.; Skjøth, C. A.; García-Mozo, H.; Bolívar, J. P.; Galán, C.

2014-12-01

Airborne pollen transport at micro-, meso-gamma and meso-beta scales must be studied by atmospheric models, having special relevance in complex terrain. In these cases, the accuracy of these models is mainly determined by the spatial resolution of the underlying meteorological dataset. This work examines how meteorological datasets determine the results obtained from atmospheric transport models used to describe pollen transport in the atmosphere. We investigate the effect of the spatial resolution when computing backward trajectories with the HYSPLIT model. We have used meteorological datasets from the WRF model with 27, 9 and 3 km resolutions and from the GDAS files with 1 ° resolution. This work allows characterizing atmospheric transport of Olea pollen in a region with complex flows. The results show that the complex terrain affects the trajectories and this effect varies with the different meteorological datasets. Overall, the change from GDAS to WRF-ARW inputs improves the analyses with the HYSPLIT model, thereby increasing the understanding the pollen episode. The results indicate that a spatial resolution of at least 9 km is needed to simulate atmospheric flows that are considerable affected by the relief of the landscape. The results suggest that the appropriate meteorological files should be considered when atmospheric models are used to characterize the atmospheric transport of pollen on micro-, meso-gamma and meso-beta scales. Furthermore, at these scales, the results are believed to be generally applicable for related areas such as the description of atmospheric transport of radionuclides or in the definition of nuclear-radioactivity emergency preparedness.

Black hole mass measurement using molecular gas kinematics: what ALMA can do

NASA Astrophysics Data System (ADS)

Yoon, Ilsang

2017-04-01

We study the limits of the spatial and velocity resolution of radio interferometry to infer the mass of supermassive black holes (SMBHs) in galactic centres using the kinematics of circum-nuclear molecular gas, by considering the shapes of the galaxy surface brightness profile, signal-to-noise ratios (S/Ns) of the position-velocity diagram (PVD) and systematic errors due to the spatial and velocity structure of the molecular gas. We argue that for fixed galaxy stellar mass and SMBH mass, the spatial and velocity scales that need to be resolved increase and decrease, respectively, with decreasing Sérsic index of the galaxy surface brightness profile. We validate our arguments using simulated PVDs for varying beam size and velocity channel width. Furthermore, we consider the systematic effects on the inference of the SMBH mass by simulating PVDs including the spatial and velocity structure of the molecular gas, which demonstrates that their impacts are not significant for a PVD with good S/N unless the spatial and velocity scale associated with the systematic effects are comparable to or larger than the angular resolution and velocity channel width of the PVD from pure circular motion. Also, we caution that a bias in a galaxy surface brightness profile owing to the poor resolution of a galaxy photometric image can largely bias the SMBH mass by an order of magnitude. This study shows the promise and the limits of ALMA observations for measuring SMBH mass using molecular gas kinematics and provides a useful technical justification for an ALMA proposal with the science goal of measuring SMBH mass.

Compensation for Blur Requires Increase in Field of View and Viewing Time

PubMed Central

Kwon, MiYoung; Liu, Rong; Chien, Lillian

2016-01-01

Spatial resolution is an important factor for human pattern recognition. In particular, low resolution (blur) is a defining characteristic of low vision. Here, we examined spatial (field of view) and temporal (stimulus duration) requirements for blurry object recognition. The spatial resolution of an image such as letter or face, was manipulated with a low-pass filter. In experiment 1, studying spatial requirement, observers viewed a fixed-size object through a window of varying sizes, which was repositioned until object identification (moving window paradigm). Field of view requirement, quantified as the number of “views” (window repositions) for correct recognition, was obtained for three blur levels, including no blur. In experiment 2, studying temporal requirement, we determined threshold viewing time, the stimulus duration yielding criterion recognition accuracy, at six blur levels, including no blur. For letter and face recognition, we found blur significantly increased the number of views, suggesting a larger field of view is required to recognize blurry objects. We also found blur significantly increased threshold viewing time, suggesting longer temporal integration is necessary to recognize blurry objects. The temporal integration reflects the tradeoff between stimulus intensity and time. While humans excel at recognizing blurry objects, our findings suggest compensating for blur requires increased field of view and viewing time. The need for larger spatial and longer temporal integration for recognizing blurry objects may further challenge object recognition in low vision. Thus, interactions between blur and field of view should be considered for developing low vision rehabilitation or assistive aids. PMID:27622710

Complex Greenland outlet glacier flow captured

PubMed Central

Aschwanden, Andy; Fahnestock, Mark A.; Truffer, Martin

2016-01-01

The Greenland Ice Sheet is losing mass at an accelerating rate due to increased surface melt and flow acceleration in outlet glaciers. Quantifying future dynamic contributions to sea level requires accurate portrayal of outlet glaciers in ice sheet simulations, but to date poor knowledge of subglacial topography and limited model resolution have prevented reproduction of complex spatial patterns of outlet flow. Here we combine a high-resolution ice-sheet model coupled to uniformly applied models of subglacial hydrology and basal sliding, and a new subglacial topography data set to simulate the flow of the Greenland Ice Sheet. Flow patterns of many outlet glaciers are well captured, illustrating fundamental commonalities in outlet glacier flow and highlighting the importance of efforts to map subglacial topography. Success in reproducing present day flow patterns shows the potential for prognostic modelling of ice sheets without the need for spatially varying parameters with uncertain time evolution. PMID:26830316

Spatial Soliton Interactions for Photonic Switching. Part I

DTIC Science & Technology

2000-03-07

technique , a fully vectorial, first-order nonlinear wave equation that consistently includes terms two -orders beyond the slowly-varying amplitude , slowly...by using two tunable mode-locked Er-doped fiber lasers ," in Conference on Optical Fiber Communications, OSA Technical Digest Series, vol. 4, 1994...instead, based on optical logic gates. In addition, optical logic could be used for contention resolution, real-time encryption /decryption, and other

Wood density and anatomical properties in suppressed-growth trees : comparison of two methods

Treesearch

David W. Vahey; J. Y. Zhu; C. Tim Scott

2007-01-01

Interest in the commercial value of small-diameter timber has led to testing core samples with SilviScan to characterize density and transverse fiber dimensions. Data showed that latewood density and tracheid diameter in suppressed-growth material can vary spatially on a scale comparable to the 50-_m resolution of the instrument used in our testing. An optical imaging...

Satellite remote sensing of landscape freeze/thaw state dynamics for complex Topography and Fire Disturbance Areas Using multi-sensor radar and SRTM digital elevation models

NASA Technical Reports Server (NTRS)

Podest, Erika; McDonald, Kyle; Kimball, John; Randerson, James

2003-01-01

We characterize differences in radar-derived freeze/thaw state, examining transitions over complex terrain and landscape disturbance regimes. In areas of complex terrain, we explore freezekhaw dynamics related to elevation, slope aspect and varying landcover. In the burned regions, we explore the timing of seasonal freeze/thaw transition as related to the recovering landscape, relative to that of a nearby control site. We apply in situ biophysical measurements, including flux tower measurements to validate and interpret the remotely sensed parameters. A multi-scale analysis is performed relating high-resolution SAR backscatter and moderate resolution scatterometer measurements to assess trade-offs in spatial and temporal resolution in the remotely sensed fields.

Comparing long-term geomorphic model outcomes with sediment archives highlights the need for high-resolution Holocene land cover reconstructions

NASA Astrophysics Data System (ADS)

De Brue, Hanne; Verstraeten, Gert

2013-04-01

During the last decade, several global land cover reconstructions have been produced that enable to quantify human impact on the landscape since the introduction of agriculture. Application of these land cover maps in geomorphic models potentially allows to estimate the anthropogenic impact on sediment fluxes and thus to reconstruct changes in landscape morphology through time. However, current land cover reconstructions face some drawbacks. First of all, their low spatial resolution (i.e. 5 arc-minutes at best) questions their use in geomorphic models, as sub-catchment vegetation patterns play an important role in sediment dynamics. Existing global land cover reconstructions also do not differentiate the typology of human impact (cropland, grazing land, disturbed forests), although the susceptibility of different anthropogenic land uses towards erosion varies greatly. Finally, the various land cover reconstructions differ significantly regarding the estimated intensity of human impact for the preindustrial period. In this study, we assessed the performance of a spatially distributed erosion and sediment redistribution model that operates at high resolution (100 m) to the quality and spatial resolution of input land cover maps. This was done through a comparison of two sets of model runs. Firstly, low-resolution land cover (expressed as percentage of non-natural vegetation) maps were resampled to a spatial resolution of 100 m without differentiation of non-natural vegetation types. For the second set of model runs, estimated non-natural vegetation was differentiated in areas of cropland and grassland, and spatially allocated to a high-resolution grid (100 m) using a logistic model that relates contemporary land cover classes to slope, soil characteristics, landforms and distance to rivers. For both land cover maps, different scenarios for the ratio between cropland and grassland were simulated. Analyses were performed for several time periods throughout the Holocene, for the Scheldt River Basin (19,000 km2) in Belgium and northern France. Results indicate that low-resolution land cover information, regardless of the considered cropland/grassland ratio, leads to largely overestimated sediment fluxes when compared to field-based sediment budgets. Allocation of land cover to a higher spatial resolution yields far better results. Variations in model outcomes are related to differences in landscape connectivity between allocated and non-allocated land cover. These results point towards the need for higher-resolution land cover maps that incorporate the patchiness of vegetation at relevant scales regarding geomorphic processes. Also, model results with allocated and non-allocated land cover maps differ greatly for different cropland/grassland ratios. This indicates that there is not only a need for land cover reconstructions at high spatial resolution, but also that differentiation between cropland and grassland is essential for accurate geomorphic modeling. Further improvements in land cover reconstructions are thus needed before reliable quantitative estimates of anthropogenic impact on soil profiles and sediment redistribution can be simulated at continental scales. Detailed historic sediment budgets can provide an important tool not only for validating but also for reconstructing land cover histories.

Performance evaluation of spatial compounding in the presence of aberration and adaptive imaging

NASA Astrophysics Data System (ADS)

Dahl, Jeremy J.; Guenther, Drake; Trahey, Gregg E.

2003-05-01

Spatial compounding has been used for years to reduce speckle in ultrasonic images and to resolve anatomical features hidden behind the grainy appearance of speckle. Adaptive imaging restores image contrast and resolution by compensating for beamforming errors caused by tissue-induced phase errors. Spatial compounding represents a form of incoherent imaging, whereas adaptive imaging attempts to maintain a coherent, diffraction-limited aperture in the presence of aberration. Using a Siemens Antares scanner, we acquired single channel RF data on a commercially available 1-D probe. Individual channel RF data was acquired on a cyst phantom in the presence of a near field electronic phase screen. Simulated data was also acquired for both a 1-D and a custom built 8x96, 1.75-D probe (Tetrad Corp.). The data was compounded using a receive spatial compounding algorithm; a widely used algorithm because it takes advantage of parallel beamforming to avoid reductions in frame rate. Phase correction was also performed by using a least mean squares algorithm to estimate the arrival time errors. We present simulation and experimental data comparing the performance of spatial compounding to phase correction in contrast and resolution tasks. We evaluate spatial compounding and phase correction, and combinations of the two methods, under varying aperture sizes, aperture overlaps, and aberrator strength to examine the optimum configuration and conditions in which spatial compounding will provide a similar or better result than adaptive imaging. We find that, in general, phase correction is hindered at high aberration strengths and spatial frequencies, whereas spatial compounding is helped by these aberrators.

A Mach-Zender digital holographic microscope with sub-micrometer resolution for imaging and tracking of marine micro-organisms

NASA Astrophysics Data System (ADS)

Kühn, Jonas; Niraula, Bimochan; Liewer, Kurt; Kent Wallace, J.; Serabyn, Eugene; Graff, Emilio; Lindensmith, Christian; Nadeau, Jay L.

2014-12-01

Digital holographic microscopy is an ideal tool for investigation of microbial motility. However, most designs do not exhibit sufficient spatial resolution for imaging bacteria. In this study we present an off-axis Mach-Zehnder design of a holographic microscope with spatial resolution of better than 800 nm and the ability to resolve bacterial samples at varying densities over a 380 μm × 380 μm × 600 μm three-dimensional field of view. Larger organisms, such as protozoa, can be resolved in detail, including cilia and flagella. The instrument design and performance are presented, including images and tracks of bacterial and protozoal mixed samples and pure cultures of six selected species. Organisms as small as 1 μm (bacterial spores) and as large as 60 μm (Paramecium bursaria) may be resolved and tracked without changes in the instrument configuration. Finally, we present a dilution series investigating the maximum cell density that can be imaged, a type of analysis that has not been presented in previous holographic microscopy studies.

Quantitative imaging of single-shot liquid distributions in sprays using broadband flash x-ray radiography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Halls, B. R.; Roy, S.; Gord, J. R.

Flash x-ray radiography is used to capture quantitative, two-dimensional line-of-sight averaged, single-shot liquid distribution measurements in impinging jet sprays. The accuracy of utilizing broadband x-ray radiation from compact flash tube sources is investigated for a range of conditions by comparing the data with radiographic high-speed measurements from a narrowband, high-intensity synchrotron x-ray facility at the Advanced Photon Source (APS) of Argonne National Laboratory. The path length of the liquid jets is varied to evaluate the effects of energy dependent x-ray attenuation, also known as spectral beam hardening. The spatial liquid distributions from flash x-ray and synchrotron-based radiography are compared, alongmore » with spectral characteristics using Taylor’s hypothesis. The results indicate that quantitative, single-shot imaging of liquid distributions can be achieved using broadband x-ray sources with nanosecond temporal resolution. Practical considerations for optimizing the imaging system performance are discussed, including the coupled effects of x-ray bandwidth, contrast, sensitivity, spatial resolution, temporal resolution, and spectral beam hardening.« less

Digital micromirror device-based laser-illumination Fourier ptychographic microscopy

PubMed Central

Kuang, Cuifang; Ma, Ye; Zhou, Renjie; Lee, Justin; Barbastathis, George; Dasari, Ramachandra R.; Yaqoob, Zahid; So, Peter T. C.

2015-01-01

We report a novel approach to Fourier ptychographic microscopy (FPM) by using a digital micromirror device (DMD) and a coherent laser source (532 nm) for generating spatially modulated sample illumination. Previously demonstrated FPM systems are all based on partially-coherent illumination, which offers limited throughput due to insufficient brightness. Our FPM employs a high power coherent laser source to enable shot-noise limited high-speed imaging. For the first time, a digital micromirror device (DMD), imaged onto the back focal plane of the illumination objective, is used to generate spatially modulated sample illumination field for ptychography. By coding the on/off states of the micromirrors, the illumination plane wave angle can be varied at speeds more than 4 kHz. A set of intensity images, resulting from different oblique illuminations, are used to numerically reconstruct one high-resolution image without obvious laser speckle. Experiments were conducted using a USAF resolution target and a fiber sample, demonstrating high-resolution imaging capability of our system. We envision that our approach, if combined with a coded-aperture compressive-sensing algorithm, will further improve the imaging speed in DMD-based FPM systems. PMID:26480361

Digital micromirror device-based laser-illumination Fourier ptychographic microscopy.

PubMed

Kuang, Cuifang; Ma, Ye; Zhou, Renjie; Lee, Justin; Barbastathis, George; Dasari, Ramachandra R; Yaqoob, Zahid; So, Peter T C

2015-10-19

We report a novel approach to Fourier ptychographic microscopy (FPM) by using a digital micromirror device (DMD) and a coherent laser source (532 nm) for generating spatially modulated sample illumination. Previously demonstrated FPM systems are all based on partially-coherent illumination, which offers limited throughput due to insufficient brightness. Our FPM employs a high power coherent laser source to enable shot-noise limited high-speed imaging. For the first time, a digital micromirror device (DMD), imaged onto the back focal plane of the illumination objective, is used to generate spatially modulated sample illumination field for ptychography. By coding the on/off states of the micromirrors, the illumination plane wave angle can be varied at speeds more than 4 kHz. A set of intensity images, resulting from different oblique illuminations, are used to numerically reconstruct one high-resolution image without obvious laser speckle. Experiments were conducted using a USAF resolution target and a fiber sample, demonstrating high-resolution imaging capability of our system. We envision that our approach, if combined with a coded-aperture compressive-sensing algorithm, will further improve the imaging speed in DMD-based FPM systems.

The Role of Nonlinear Gradients in Parallel Imaging: A k-Space Based Analysis.

PubMed

Galiana, Gigi; Stockmann, Jason P; Tam, Leo; Peters, Dana; Tagare, Hemant; Constable, R Todd

2012-09-01

Sequences that encode the spatial information of an object using nonlinear gradient fields are a new frontier in MRI, with potential to provide lower peripheral nerve stimulation, windowed fields of view, tailored spatially-varying resolution, curved slices that mirror physiological geometry, and, most importantly, very fast parallel imaging with multichannel coils. The acceleration for multichannel images is generally explained by the fact that curvilinear gradient isocontours better complement the azimuthal spatial encoding provided by typical receiver arrays. However, the details of this complementarity have been more difficult to specify. We present a simple and intuitive framework for describing the mechanics of image formation with nonlinear gradients, and we use this framework to review some the main classes of nonlinear encoding schemes.

MOS Circuitry Would Detect Low-Energy Charged Particles

NASA Technical Reports Server (NTRS)

Sinha, Mahadeva; Wadsworth, Mark

2003-01-01

Metal oxide semiconductor (MOS) circuits for measuring spatially varying intensities of beams of low-energy charged particles have been developed. These circuits are intended especially for use in measuring fluxes of ions with spatial resolution along the focal planes of mass spectrometers. Unlike prior mass spectrometer focal-plane detectors, these MOS circuits would not be based on ion-induced generation of electrons, and photons; instead, they would be based on direct detection of the electric charges of the ions. Hence, there would be no need for microchannel plates (for ion-to-electron conversion), phosphors (for electron-to-photon conversion), and photodetectors (for final detection) -- components that degrade spatial resolution and contribute to complexity and size. The developmental circuits are based on linear arrays of charge-coupled devices (CCDs) with associated readout circuitry (see figure). They resemble linear CCD photodetector arrays, except that instead of a photodetector, each pixel contains a capacitive charge sensor. The capacitor in each sensor comprises two electrodes (typically made of aluminum) separated by a layer of insulating material. The exposed electrode captures ions and accumulates their electric charges during signal-integration periods.

Perceptual Real-Time 2D-to-3D Conversion Using Cue Fusion.

PubMed

Leimkuhler, Thomas; Kellnhofer, Petr; Ritschel, Tobias; Myszkowski, Karol; Seidel, Hans-Peter

2018-06-01

We propose a system to infer binocular disparity from a monocular video stream in real-time. Different from classic reconstruction of physical depth in computer vision, we compute perceptually plausible disparity, that is numerically inaccurate, but results in a very similar overall depth impression with plausible overall layout, sharp edges, fine details and agreement between luminance and disparity. We use several simple monocular cues to estimate disparity maps and confidence maps of low spatial and temporal resolution in real-time. These are complemented by spatially-varying, appearance-dependent and class-specific disparity prior maps, learned from example stereo images. Scene classification selects this prior at runtime. Fusion of prior and cues is done by means of robust MAP inference on a dense spatio-temporal conditional random field with high spatial and temporal resolution. Using normal distributions allows this in constant-time, parallel per-pixel work. We compare our approach to previous 2D-to-3D conversion systems in terms of different metrics, as well as a user study and validate our notion of perceptually plausible disparity.

Inspecting Friction Stir Welding using Electromagnetic Probes

NASA Technical Reports Server (NTRS)

Kinchen, David G.

2004-01-01

A report describes the use of advanced electromagnetic probes to measure the dimensions, the spatial distribution of electrical conductivity, and related other properties of friction stir welds (FSWs) between parts made of the same or different aluminum alloy(s). The probes are of the type described in in another Tech Brief. To recapitulate: A probe of this type is essentially an eddy-current probe that includes a primary (driver) winding that meanders and multiple secondary (sensing) windings that meander along the primary winding. Electrical conductivity is commonly used as a measure of heat treatment and tempering of aluminum alloys, but prior to the development of these probes, the inadequate sensitivity and limited accuracy of electrical-conductivity probes precluded such use on FSWs between different aluminum alloys, and the resolution of those probes was inadequate for measurement of FSW dimensions with positions and metallurgical properties. In contrast, the present probes afford adequate accuracy and spatial resolution for the purposes of measuring the dimensions of FSW welds and correlating spatially varying electrical conductivities with metallurgical properties, including surface defects.

Monte Carlo design of optimal wire mesh collimator for breast tumor imaging process

NASA Astrophysics Data System (ADS)

Saad, W. H. M.; Roslan, R. E.; Mahdi, M. A.; Choong, W.-S.; Saion, E.; Saripan, M. I.

2011-08-01

This paper presents the modeling of breast tumor imaging process using wire mesh collimator gamma camera. Previous studies showed that the wire mesh collimator has a potential to improve the sensitivity of the tumor detection. In this paper, we extend our research significantly, to find an optimal configuration of the wire mesh collimator specifically for semi-compressed breast tumor detection, by looking into four major factors: weight, sensitivity, spatial resolution and tumor contrast. The numbers of layers in the wire mesh collimator is varied to optimize the collimator design. The statistical variations of the results are studied by simulating multiple realizations for each experiment using different starting random numbers. All the simulation environments are modeled using Monte Carlo N-Particle Code (MCNP). The quality of the detection is measured directly by comparing the sensitivity, spatial resolution and tumor contrast of the images produced by the wire mesh collimator and benchmarked that with a standard multihole collimator. The proposed optimal configuration of the wire mesh collimator is optimized by selecting the number of layers in wire mesh collimator, where the tumor contrast shows a relatively comparable value to the multihole collimator, when it is tested with uniformly semi-compressed breast phantom. The wire mesh collimator showed higher number of sensitivity because of its loose arrangement while the spatial resolution of wire mesh collimator does not shows much different compared to the multihole collimator. With a relatively good tumor contrast and spatial resolution, and increased in sensitivity, a new proposed wire mesh collimator gives a significant improvement in the wire mesh collimator design for breast cancer imaging process. The proposed collimator configuration is reduced to 44.09% from the total multihole collimator weight.

Resolving vorticity-driven lateral fire spread using the WRF-Fire coupled atmosphere-fire numerical model

NASA Astrophysics Data System (ADS)

Simpson, C. C.; Sharples, J. J.; Evans, J. P.

2014-05-01

Fire channelling is a form of dynamic fire behaviour, during which a wildland fire spreads rapidly across a steep lee-facing slope in a direction transverse to the background winds, and is often accompanied by a downwind extension of the active flaming region and extreme pyro-convection. Recent work using the WRF-Fire coupled atmosphere-fire model has demonstrated that fire channelling can be characterised as vorticity-driven lateral fire spread (VDLS). In this study, 16 simulations are conducted using WRF-Fire to examine the sensitivity of resolving VDLS to spatial resolution and atmosphere-fire coupling within the WRF-Fire model framework. The horizontal grid spacing is varied between 25 and 90 m, and the two-way atmosphere-fire coupling is either enabled or disabled. At high spatial resolution, the atmosphere-fire coupling increases the peak uphill and lateral spread rate by a factor of up to 2.7 and 9.5. The enhancement of the uphill and lateral spread rate diminishes at coarser spatial resolution, and VDLS is not modelled for a horizontal grid spacing of 90 m. The laterally spreading fire fronts become the dominant contributors of the extreme pyro-convection. The resolved fire-induced vortices responsible for driving the lateral spread in the coupled simulations have non-zero vorticity along each unit vector direction, and develop due to an interaction between the background winds and vertical return circulations generated at the flank of the fire front as part of the pyro-convective updraft. The results presented in this study demonstrate that both high spatial resolution and two-way atmosphere-fire coupling are required to reproduce VDLS within the current WRF-Fire model framework.

Fire Impacts on Mixed Pine-oak Forests Assessed with High Spatial Resolution Imagery, Imaging Spectroscopy, and LiDAR

NASA Astrophysics Data System (ADS)

Meng, R.; Wu, J.; Zhao, F. R.; Kathy, S. L.; Dennison, P. E.; Cook, B.; Hanavan, R. P.; Serbin, S.

2016-12-01

As a primary disturbance agent, fire significantly influences forest ecosystems, including the modification or resetting of vegetation composition and structure, which can then significantly impact landscape-scale plant function and carbon stocks. Most ecological processes associated with fire effects (e.g. tree damage, mortality, and vegetation recovery) display fine-scale, species specific responses but can also vary spatially within the boundary of the perturbation. For example, both oak and pine species are fire-adapted, but fire can still induce changes in composition, structure, and dominance in a mixed pine-oak forest, mainly because of their varying degrees of fire adaption. Evidence of post-fire shifts in dominance between oak and pine species has been documented in mixed pine-oak forests, but these processes have been poorly investigated in a spatially explicit manner. In addition, traditional field-based means of quantifying the response of partially damaged trees across space and time is logistically challenging. Here we show how combining high resolution satellite imagery (i.e. Worldview-2,WV-2) and airborne imaging spectroscopy and LiDAR (i.e. NASA Goddard's Lidar, Hyperspectral and Thermal airborne imager, G-LiHT) can be effectively used to remotely quantify spatial and temporal patterns of vegetation recovery following a top-killing fire that occurred in 2012 within mixed pine-oak forests in the Long Island Central Pine Barrens Region, New York. We explore the following questions: 1) what are the impacts of fire on species composition, dominance, plant health, and vertical structure; 2) what are the recovery trajectories of forest biomass, structure, and spectral properties for three years following the fire; and 3) to what extent can fire impacts be captured and characterized by multi-sensor remote sensing techniques from active and passive optical remote sensing.

Surface water classification and monitoring using polarimetric synthetic aperture radar

NASA Astrophysics Data System (ADS)

Irwin, Katherine Elizabeth

Surface water classification using synthetic aperture radar (SAR) is an established practice for monitoring flood hazards due to the high temporal and spatial resolution it provides. Surface water change is a dynamic process that varies both spatially and temporally, and can occur on various scales resulting in significant impacts on affected areas. Small-scale flooding hazards, caused by beaver dam failure, is an example of surface water change, which can impact nearby infrastructure and ecosystems. Assessing these hazards is essential to transportation and infrastructure maintenance. With current satellite missions operating in multiple polarizations, spatio-temporal resolutions, and frequencies, a comprehensive comparison between SAR products for surface water monitoring is necessary. In this thesis, surface water extent models derived from high resolution single-polarization TerraSAR-X (TSX) data, medium resolution dual-polarization TSX data and low resolution quad-polarization RADARSAT-2 (RS-2) data are compared. There exists a compromise between acquiring SAR data with a high resolution or high information content. Multi-polarization data provides additional phase and intensity information, which makes it possible to better classify areas of flooded vegetation and wetlands. These locations are often where fluctuations in surface water occur and are essential for understanding dynamic underlying processes. However, often multi-polarized data is acquired at a low resolution, which cannot image these zones effectively. High spatial resolution, single-polarization TSX data provides the best model of open water. However, these single-polarization observations have limited information content and are affected by shadow and layover errors. This often hinders the classification of other land cover types. The dual-polarization TSX data allows for the classification of flooded vegetation, but classification is less accurate compared to the quad-polarization RS-2 data. The RS-2 data allows for the discrimination of open water, marshes/fields and forested areas. However, the RS-2 data is less applicable to small scale surface water monitoring (e.g. beaver dam failure), due to its low spatial resolution. By understanding the strengths and weaknesses of available SAR technology, an appropriate product can be chosen for a specific target application involving surface water change. This research benefits the eventual development of a space-based monitoring strategy over longer periods.

The influence of channel bed disturbance on benthic Chlorophyll a: A high resolution perspective

NASA Astrophysics Data System (ADS)

Katz, Scott B.; Segura, Catalina; Warren, Dana R.

2018-03-01

This study explores how spatial dynamics and frequency of bed mobility events in a headwater stream affect the spatial and temporal variability in stream benthic algal abundance and ultimately the resilience of benthic algae to stream scouring events of different magnitudes. We characterized spatial variability in sediment transport for nine separate flow events (0.1-1.7 of bankfull flow), coupling high resolution (< 0.1 m2) two-dimensional shear stress values with detailed measurements of the channel substrate. The stream bed was categorized into regions of high and low disturbance based on potential mobility of different grain sizes. High resolution (< 0.25 m2), in situ measurements of benthic Chlorophyll-a concentrations (Chl-a) were taken on 18 sampling dates before and after high flow events in regions of the streambed with contrasting disturbance to understand how benthic algal communities respond to sediment transport disturbance through space and time. According to the modeling results, the percentage of the channel likely to be disturbed varied greatly across the different flows and considered grain sizes between 7.7 and 70.4% for the lowest and highest flow events respectively. Mean shear stress in the channel bed across all sampling dates explained 49% of the variance in Chl-a. Over the 18 sampling dates - encompassing post-disturbance impacts and subsequent recovery - Chl-a differed between disturbance level categories defined based on the relative movement of the median grain size on 14 occasions. However, low disturbance locations were not always associated with higher Chl-a. The algal Chl-a biomass at any given time was a function of the stage of algal recovery following a high flow event and the magnitude of the disturbance itself - impacting algal loss during the event. Resistance of the algal communities to bed disturbance and resilience to recovery following a flow event varied spatially. Areas with low shear stress were less susceptible to scour during moderate disturbance events but were slower to recover when scour occurred. In contrast, high shear stress areas responded rapidly to flood events with rapid declines, but also recovered more quickly and appeared to have high potential for maximum accrual within our study reach. Ultimately, timing along with the inverse relationship between resiliency and disturbance frequency highlights the complexity of these processes and the importance of studying the interactions between geomorphic and ecological processes with high resolution across spatial and temporal scales.

ICESat laser altimetry over small mountain glaciers

NASA Astrophysics Data System (ADS)

Treichler, Désirée; Kääb, Andreas

2016-09-01

Using sparsely glaciated southern Norway as a case study, we assess the potential and limitations of ICESat laser altimetry for analysing regional glacier elevation change in rough mountain terrain. Differences between ICESat GLAS elevations and reference elevation data are plotted over time to derive a glacier surface elevation trend for the ICESat acquisition period 2003-2008. We find spatially varying biases between ICESat and three tested digital elevation models (DEMs): the Norwegian national DEM, SRTM DEM, and a high-resolution lidar DEM. For regional glacier elevation change, the spatial inconsistency of reference DEMs - a result of spatio-temporal merging - has the potential to significantly affect or dilute trends. Elevation uncertainties of all three tested DEMs exceed ICESat elevation uncertainty by an order of magnitude, and are thus limiting the accuracy of the method, rather than ICESat uncertainty. ICESat matches glacier size distribution of the study area well and measures small ice patches not commonly monitored in situ. The sample is large enough for spatial and thematic subsetting. Vertical offsets to ICESat elevations vary for different glaciers in southern Norway due to spatially inconsistent reference DEM age. We introduce a per-glacier correction that removes these spatially varying offsets, and considerably increases trend significance. Only after application of this correction do individual campaigns fit observed in situ glacier mass balance. Our correction also has the potential to improve glacier trend significance for other causes of spatially varying vertical offsets, for instance due to radar penetration into ice and snow for the SRTM DEM or as a consequence of mosaicking and merging that is common for national or global DEMs. After correction of reference elevation bias, we find that ICESat provides a robust and realistic estimate of a moderately negative glacier mass balance of around -0.36 ± 0.07 m ice per year. This regional estimate agrees well with the heterogeneous but overall negative in situ glacier mass balance observed in the area.

Analysing child mortality in Nigeria with geoadditive discrete-time survival models.

PubMed

Adebayo, Samson B; Fahrmeir, Ludwig

2005-03-15

Child mortality reflects a country's level of socio-economic development and quality of life. In developing countries, mortality rates are not only influenced by socio-economic, demographic and health variables but they also vary considerably across regions and districts. In this paper, we analysed child mortality in Nigeria with flexible geoadditive discrete-time survival models. This class of models allows us to measure small-area district-specific spatial effects simultaneously with possibly non-linear or time-varying effects of other factors. Inference is fully Bayesian and uses computationally efficient Markov chain Monte Carlo (MCMC) simulation techniques. The application is based on the 1999 Nigeria Demographic and Health Survey. Our method assesses effects at a high level of temporal and spatial resolution not available with traditional parametric models, and the results provide some evidence on how to reduce child mortality by improving socio-economic and public health conditions. Copyright (c) 2004 John Wiley & Sons, Ltd.

From puddles to planet: modeling approaches to vector-borne diseases at varying resolution and scale.

PubMed

Eckhoff, Philip A; Bever, Caitlin A; Gerardin, Jaline; Wenger, Edward A; Smith, David L

2015-08-01

Since the original Ross-Macdonald formulations of vector-borne disease transmission, there has been a broad proliferation of mathematical models of vector-borne disease, but many of these models retain most to all of the simplifying assumptions of the original formulations. Recently, there has been a new expansion of mathematical frameworks that contain explicit representations of the vector life cycle including aquatic stages, multiple vector species, host heterogeneity in biting rate, realistic vector feeding behavior, and spatial heterogeneity. In particular, there are now multiple frameworks for spatially explicit dynamics with movements of vector, host, or both. These frameworks are flexible and powerful, but require additional data to take advantage of these features. For a given question posed, utilizing a range of models with varying complexity and assumptions can provide a deeper understanding of the answers derived from models. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Area-based tests for association between spatial patterns

NASA Astrophysics Data System (ADS)

Maruca, Susan L.; Jacquez, Geoffrey M.

Edge effects pervade natural systems, and the processes that determine spatial heterogeneity (e.g. physical, geochemical, biological, ecological factors) occur on diverse spatial scales. Hence, tests for association between spatial patterns should be unbiased by edge effects and be based on null spatial models that incorporate the spatial heterogeneity characteristic of real-world systems. This paper develops probabilistic pattern association tests that are appropriate when edge effects are present, polygon size is heterogeneous, and the number of polygons varies from one classification to another. The tests are based on the amount of overlap between polygons in each of two partitions. Unweighted and area-weighted versions of the statistics are developed and verified using scenarios representing both polygon overlap and avoidance at different spatial scales and for different distributions of polygon sizes. These statistics were applied to Soda Butte Creek, Wyoming, to determine whether stream microhabitats, such as riffles, pools and glides, can be identified remotely using high spatial resolution hyperspectral imagery. These new ``spatially explicit'' techniques provide information and insights that cannot be obtained from the spectral information alone.

The Substructure of the Solar Corona Observed in the Hi-C Telescope

NASA Technical Reports Server (NTRS)

Winebarger, A.; Cirtain, J.; Golub, L.; DeLuca, E.; Savage, S.; Alexander, C.; Schuler, T.

2014-01-01

In the summer of 2012, the High-resolution Coronal Imager (Hi-C) flew aboard a NASA sounding rocket and collected the highest spatial resolution images ever obtained of the solar corona. One of the goals of the Hi-C flight was to characterize the substructure of the solar corona. We therefore calculate how the intensity scales from a low-resolution (AIA) pixels to high-resolution (Hi-C) pixels for both the dynamic events and "background" emission (meaning, the steady emission over the 5 minutes of data acquisition time). We find there is no evidence of substructure in the background corona; the intensity scales smoothly from low-resolution to high-resolution Hi-C pixels. In transient events, however, the intensity observed with Hi-C is, on average, 2.6 times larger than observed with AIA. This increase in intensity suggests that AIA is not resolving these events. This result suggests a finely structured dynamic corona embedded in a smoothly varying background.

Discovery of Finely Structured Dynamic Solar Corona Observed in the Hi-C Telescope

NASA Technical Reports Server (NTRS)

Winebarger, A.; Cirtain, J.; Golub, L.; DeLuca, E.; Savage, S.; Alexander, C.; Schuler, T.

2014-01-01

In the summer of 2012, the High-resolution Coronal Imager (Hi-C) flew aboard a NASA sounding rocket and collected the highest spatial resolution images ever obtained of the solar corona. One of the goals of the Hi-C flight was to characterize the substructure of the solar corona. We therefore examine how the intensity scales from AIA resolution to Hi-C resolution. For each low-resolution pixel, we calculate the standard deviation in the contributing high-resolution pixel intensities and compare that to the expected standard deviation calculated from the noise. If these numbers are approximately equal, the corona can be assumed to be smoothly varying, i.e. have no evidence of substructure in the Hi-C image to within Hi-C's ability to measure it given its throughput and readout noise. A standard deviation much larger than the noise value indicates the presence of substructure. We calculate these values for each low-resolution pixel for each frame of the Hi-C data. On average, 70 percent of the pixels in each Hi-C image show no evidence of substructure. The locations where substructure is prevalent is in the moss regions and in regions of sheared magnetic field. We also find that the level of substructure varies significantly over the roughly 160 s of the Hi-C data analyzed here. This result indicates that the finely structured corona is concentrated in regions of heating and is highly time dependent.

DISCOVERY OF FINELY STRUCTURED DYNAMIC SOLAR CORONA OBSERVED IN THE Hi-C TELESCOPE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Winebarger, Amy R.; Cirtain, Jonathan; Savage, Sabrina

In the Summer of 2012, the High-resolution Coronal Imager (Hi-C) flew on board a NASA sounding rocket and collected the highest spatial resolution images ever obtained of the solar corona. One of the goals of the Hi-C flight was to characterize the substructure of the solar corona. We therefore examine how the intensity scales from AIA resolution to Hi-C resolution. For each low-resolution pixel, we calculate the standard deviation in the contributing high-resolution pixel intensities and compare that to the expected standard deviation calculated from the noise. If these numbers are approximately equal, the corona can be assumed to bemore » smoothly varying, i.e., have no evidence of substructure in the Hi-C image to within Hi-C's ability to measure it given its throughput and readout noise. A standard deviation much larger than the noise value indicates the presence of substructure. We calculate these values for each low-resolution pixel for each frame of the Hi-C data. On average, 70% of the pixels in each Hi-C image show no evidence of substructure. The locations where substructure is prevalent is in the moss regions and in regions of sheared magnetic field. We also find that the level of substructure varies significantly over the roughly 160 s of the Hi-C data analyzed here. This result indicates that the finely structured corona is concentrated in regions of heating and is highly time dependent.« less

Phenological monitoring of Acadia National Park using Landsat, MODIS and VIIRS observations and fused data

NASA Astrophysics Data System (ADS)

Liu, Y.; McDonough MacKenzie, C.; Primack, R.; Zhang, X.; Schaaf, C.; Sun, Q.; Wang, Z.

2015-12-01

Monitoring phenology with remotely sensed data has become standard practice in large-plot agriculture but remains an area of research in complex terrain. Landsat data (30m) provides a more appropriate spatial resolution to describe such regions but may only capture a few cloud-free images over a growing period. Daily data from the MODerate resolution Imaging Spectroradiometer(MODIS) and Visible Infrared Imaging Radiometer Suite(VIIRS) offer better temporal acquisitions but at coarse spatial resolutions of 250m to 1km. Thus fused data sets are being employed to provide the temporal and spatial resolutions necessary to accurately monitor vegetation phenology. This study focused on Acadia National Park, Maine, attempts to compare green-up from remote sensing and ground observations over varying topography. Three north-south field transects were established in 2013 on parallel mountains. Along these transects, researchers record the leaf out and flowering phenology for thirty plant species biweekly. These in situ spring phenological observations are compared with the dates detected by Landsat 7, Landsat 8, MODIS, and VIIRS observations, both separately and as fused data, to explore the ability of remotely sensed data to capture the subtle variations due to elevation. Daily Nadir BRDF Adjusted Reflectances(NBAR) from MODIS and VIIRS are fused with Landsat imagery to simulate 30m daily data via the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model(ESTARFM) algorithm. Piecewise logistic functions are fit to the time series to establish spring leaf-out dates. Acadia National Park, a region frequently affected by coastal clouds, is a particularly useful study area as it falls in a Landsat overlap region and thus offers the possibility of acquiring as many as 4 Landsat observations in a 16 day period. With the recent launch of Sentinel 2A, the community will have routine access to such high spatial and temporal data for phenological monitoring.

A 3D Finite Element Model with Improved Spatial Resolution to Investigate the Effect of Varying Viscosity on Antarctica

NASA Astrophysics Data System (ADS)

Blank, B.; van der Wal, W.; Pappa, F.; Ebbing, J.

2017-12-01

B. Blank1, H. Hu1, W. van der Wal1, F Pappa2, J. Ebbing21Delft University of Technology 2Christian-Albrechts-University of KielSince the beginning of the 2000's time-variable gravity data from GRACE has proved to be an effective method for mapping ice mass loss in Antarctica. However, Glacial Isostatic Adjustment (GIA) models are required to correct for GIA induced mass changes. While most GIA models have adopted an Earth model that only varies radially in parameters, it has long been clear that the Earth structure also varies with longitude and latitude. For this study a new global 3D GIA model has been developed within the finite element software package ABAQUS, which can be modified to operate on a spatial resolution down to 50 km locally. The model is being benchmarked against normal model models for surface loading. It will be used to investigate the effects of a 3D varying lithosphere and upper asthenosphere in Antarctica. Viscosity which will be computed from temperature estimates with laboratory based flow laws. A new 3D temperature map of the Antarctic lithosphere has been developed within ESA's GOCE+ project based on seismic data as well as on GOCE and GRACE inferred gravity gradients. Output from the GIA model with this new temperature estimates will be compared to that of 1D viscosity profiles and other recent 3D viscosity models based on seismic data. From these side to side comparisons we want to investigate the influence of the viscosity map on uplift rates and horizontal movement. Finally the results can be compared to GPS measurement to investigate the validity of all models.

Acoustic Sensing of Ocean Turbulence

DTIC Science & Technology

1991-12-01

quantities and of fast varying quantities, requiring high spatial resolution, fast response sensors and stable observation platforms. A classical approach to...with this type of sensor . Moum et.al. [Ref.l0] performed upper ocean observations with this instrument where they were able to 60 characterize the fine...platform orientation using the 3 axis accelerometer as tiltmeters . E. NON-ACOUSTIC DATA The non-acoustic channels on the CDV package are: 3 component

Advanced image processing approach for ET estimation with remote sensing data of varying spectral, spatial and temporal resolutions

Treesearch

Sudhanshu Panda; Devendra Amatya; Young Kim; Ge Sun

2016-01-01

Evapotranspiration (ET) is one of the most important hydrologic parameters for vegetation growth, carbon sequestration, and other associated biodiversity study and analysis. Plant stomatal conductance, leaf area index, canopy temperature, soil moisture, and wind speed values generally correlate well with ET. It is difficult to estimate these hydrologic parameters of...

The Effect of Spatial and Spectral Resolution in Determining NDVI

NASA Astrophysics Data System (ADS)

Boelman, N. T.

2003-12-01

We explore the impact that varying spatial and spectral resolutions of several sensors (a field portable spectroradiometer, Landsat, MODIS and AVHRR) has in determining the average Normalized Difference Vegetation Index (NDVI) at Imnavait Creek, a small arctic tundra watershed located on the north slope of Alaska. We found that at the field-of-views (FOVs) of less than 20 m2 that were sampled, the average NDVI value for this watershed is 0.65, compared to 0.77 at FOVs equal to and greater than 20 m2. In addition, we found that at FOVs less than 20 m2, the average NDVI value calculated according to each of Landsat, MODIS and AVHRR band definitions (controlled by spectral resolution) was similar. However, at FOVs equal to and greater than 20 m2, the average NDVI value calculated according to AVHRR's broad-band definitions was significantly and consistently higher than that from both Landsat and MODIS's narrow-band NDVI values. We speculate that these differences in NDVI exist because high leaf-area-index vegetation communities associated with watertracks are commonly spaced between 10 and 20 m apart in arctic tundra landscapes and are often only included when spectral sampling is conducted at FOVs greater than tens of square meters. These results suggest that both spatial resolution alone and its interaction with spectral resolution have to be considered when interpreting commonly used global-scale NDVI datasets. This is because traditionally, the fundamental relationships established between NDVI and ecosystem parameters, such as CO2 fluxes, aboveground biomass and net primary productivity, have been established at scales less than 20 m2. Other ecosystems, such as landscapes with isolated tree islands in boreal forest-tundra ecotones, may exhibit similar scaling patterns that need to be considered when interpreting global-scale NDVI datasets.

Isotopic Recorders of Pollution in Heterogeneous Urban Areas

NASA Astrophysics Data System (ADS)

Pataki, D. E.; Cobley, L.; Smith, R. M.; Ehleringer, J. R.; Chritz, K.

2017-12-01

A significant difficulty in quantifying urban pollution lies in the extreme spatial and temporal heterogeneity of cities. Dense sources of both point and non-point source pollution as well as the dynamic role of human activities, which vary over very short time scales and small spatial scales, complicate efforts to establish long-term urban monitoring networks that are relevant at neighborhood, municipal, and regional scales. Fortunately, the natural abundance of isotopes of carbon, nitrogen, and other elements provides a wealth of information about the sources and fate of urban atmospheric pollution. In particular, soils and plant material integrate pollution sources and cycling over space and time, and have the potential to provide long-term records of pollution dynamics that extend back before atmospheric monitoring data are available. Similarly, sampling organic material at high spatial resolution can provide "isoscapes" that shed light on the spatial heterogeneity of pollutants in different urban parcels and neighborhoods, along roads of varying traffic density, and across neighborhoods of varying affluence and sociodemographic composition. We have compiled numerous datasets of the isotopic composition of urban organic matter that illustrate the potential for isotopic monitoring of urban areas as a means of understanding hot spots and hot moments in urban atmospheric biogeochemistry. Findings to date already reveal the critical role of affluence, economic activity, demographic change, and land management practices in influencing urban pollution sources and sinks, and suggest an important role of stable isotope and radioisotope measurements in urban atmospheric and biogeochemical monitoring.

Integrated photoacoustic, ultrasound and fluorescence platform for diagnostic medical imaging-proof of concept study with a tissue mimicking phantom.

PubMed

James, Joseph; Murukeshan, Vadakke Matham; Woh, Lye Sun

2014-07-01

The structural and molecular heterogeneities of biological tissues demand the interrogation of the samples with multiple energy sources and provide visualization capabilities at varying spatial resolution and depth scales for obtaining complementary diagnostic information. A novel multi-modal imaging approach that uses optical and acoustic energies to perform photoacoustic, ultrasound and fluorescence imaging at multiple resolution scales from the tissue surface and depth is proposed in this paper. The system comprises of two distinct forms of hardware level integration so as to have an integrated imaging system under a single instrumentation set-up. The experimental studies show that the system is capable of mapping high resolution fluorescence signatures from the surface, optical absorption and acoustic heterogeneities along the depth (>2cm) of the tissue at multi-scale resolution (<1µm to <0.5mm).

Mapping Cortical Laminar Structure in the 3D BigBrain.

PubMed

Wagstyl, Konrad; Lepage, Claude; Bludau, Sebastian; Zilles, Karl; Fletcher, Paul C; Amunts, Katrin; Evans, Alan C

2018-07-01

Histological sections offer high spatial resolution to examine laminar architecture of the human cerebral cortex; however, they are restricted by being 2D, hence only regions with sufficiently optimal cutting planes can be analyzed. Conversely, noninvasive neuroimaging approaches are whole brain but have relatively low resolution. Consequently, correct 3D cross-cortical patterns of laminar architecture have never been mapped in histological sections. We developed an automated technique to identify and analyze laminar structure within the high-resolution 3D histological BigBrain. We extracted white matter and pial surfaces, from which we derived histologically verified surfaces at the layer I/II boundary and within layer IV. Layer IV depth was strongly predicted by cortical curvature but varied between areas. This fully automated 3D laminar analysis is an important requirement for bridging high-resolution 2D cytoarchitecture and in vivo 3D neuroimaging. It lays the foundation for in-depth, whole-brain analyses of cortical layering.

High spatial correspondence at a columnar level between activation and resting state fMRI signals and local field potentials.

PubMed

Shi, Zhaoyue; Wu, Ruiqi; Yang, Pai-Feng; Wang, Feng; Wu, Tung-Lin; Mishra, Arabinda; Chen, Li Min; Gore, John C

2017-05-16

Although blood oxygenation level-dependent (BOLD) fMRI has been widely used to map brain responses to external stimuli and to delineate functional circuits at rest, the extent to which BOLD signals correlate spatially with underlying neuronal activity, the spatial relationships between stimulus-evoked BOLD activations and local correlations of BOLD signals in a resting state, and whether these spatial relationships vary across functionally distinct cortical areas are not known. To address these critical questions, we directly compared the spatial extents of stimulated activations and the local profiles of intervoxel resting state correlations for both high-resolution BOLD at 9.4 T and local field potentials (LFPs), using 98-channel microelectrode arrays, in functionally distinct primary somatosensory areas 3b and 1 in nonhuman primates. Anatomic images of LFP and BOLD were coregistered within 0.10 mm accuracy. We found that the point spread functions (PSFs) of BOLD and LFP responses were comparable in the stimulus condition, and both estimates of activations were slightly more spatially constrained than local correlations at rest. The magnitudes of stimulus responses in area 3b were stronger than those in area 1 and extended in a medial to lateral direction. In addition, the reproducibility and stability of stimulus-evoked activation locations within and across both modalities were robust. Our work suggests that the intrinsic resolution of BOLD is not a limiting feature in practice and approaches the intrinsic precision achievable by multielectrode electrophysiology.

High spatial correspondence at a columnar level between activation and resting state fMRI signals and local field potentials

PubMed Central

Shi, Zhaoyue; Wu, Ruiqi; Yang, Pai-Feng; Wang, Feng; Wu, Tung-Lin; Mishra, Arabinda; Chen, Li Min; Gore, John C.

2017-01-01

Although blood oxygenation level-dependent (BOLD) fMRI has been widely used to map brain responses to external stimuli and to delineate functional circuits at rest, the extent to which BOLD signals correlate spatially with underlying neuronal activity, the spatial relationships between stimulus-evoked BOLD activations and local correlations of BOLD signals in a resting state, and whether these spatial relationships vary across functionally distinct cortical areas are not known. To address these critical questions, we directly compared the spatial extents of stimulated activations and the local profiles of intervoxel resting state correlations for both high-resolution BOLD at 9.4 T and local field potentials (LFPs), using 98-channel microelectrode arrays, in functionally distinct primary somatosensory areas 3b and 1 in nonhuman primates. Anatomic images of LFP and BOLD were coregistered within 0.10 mm accuracy. We found that the point spread functions (PSFs) of BOLD and LFP responses were comparable in the stimulus condition, and both estimates of activations were slightly more spatially constrained than local correlations at rest. The magnitudes of stimulus responses in area 3b were stronger than those in area 1 and extended in a medial to lateral direction. In addition, the reproducibility and stability of stimulus-evoked activation locations within and across both modalities were robust. Our work suggests that the intrinsic resolution of BOLD is not a limiting feature in practice and approaches the intrinsic precision achievable by multielectrode electrophysiology. PMID:28461461

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations

PubMed Central

Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T.; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P.; Rötter, Reimund P.; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

2016-01-01

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations. PMID:27055028

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations.

PubMed

Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P; Rötter, Reimund P; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

2016-01-01

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

ALMA Maps of Dust and Warm Dense Gas Emission in the Starburst Galaxy IC 5179

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao Yinghe; Lu, Nanyao; Xu, C. Kevin

We present our high-resolution (0.″15 × 0.″13, ∼34 pc) observations of the CO (6−5) line emission, which probes the warm and dense molecular gas, and the 434 μ m dust continuum emission in the nuclear region of the starburst galaxy IC 5179, conducted with the Atacama Large Millimeter Array (ALMA). The CO (6−5) emission is spatially distributed in filamentary structures with many dense cores and shows a velocity field that is characteristic of a circumnuclear rotating gas disk, with 90% of the rotation speed arising within a radius of ≲150 pc. At the scale of our spatial resolution, the COmore » (6−5) and dust emission peaks do not always coincide, with their surface brightness ratio varying by a factor of ∼10. This result suggests that their excitation mechanisms are likely different, as further evidenced by the southwest to northeast spatial gradient of both CO-to-dust continuum ratio and Pa- α equivalent width. Within the nuclear region (radius ∼ 300 pc) and with a resolution of ∼34 pc, the CO line flux (dust flux density) detected in our ALMA observations is 180 ± 18 Jy km s{sup −1} (71 ± 7 mJy), which accounts for 22% (2.4%) of the total value measured by Herschel .« less

Recent applications of hyperspectral imaging in microbiology.

PubMed

Gowen, Aoife A; Feng, Yaoze; Gaston, Edurne; Valdramidis, Vasilis

2015-05-01

Hyperspectral chemical imaging (HSI) is a broad term encompassing spatially resolved spectral data obtained through a variety of modalities (e.g. Raman scattering, Fourier transform infrared microscopy, fluorescence and near-infrared chemical imaging). It goes beyond the capabilities of conventional imaging and spectroscopy by obtaining spatially resolved spectra from objects at spatial resolutions varying from the level of single cells up to macroscopic objects (e.g. foods). In tandem with recent developments in instrumentation and sampling protocols, applications of HSI in microbiology have increased rapidly. This article gives a brief overview of the fundamentals of HSI and a comprehensive review of applications of HSI in microbiology over the past 10 years. Technical challenges and future perspectives for these techniques are also discussed. Copyright © 2015 Elsevier B.V. All rights reserved.

Effect of Downscaled Forcings and Soil Texture Properties on Hyperresolution Hydrologic Simulations in a Regional Basin in Northwest Mexico

NASA Astrophysics Data System (ADS)

Ko, A.; Mascaro, G.; Vivoni, E. R.

2017-12-01

Hyper-resolution (< 1 km) hydrological modeling is expected to support a range of studies related to the terrestrial water cycle. A critical need for increasing the utility of hyper-resolution modeling is the availability of meteorological forcings and land surface characteristics at high spatial resolution. Unfortunately, in many areas these datasets are only available at coarse (> 10 km) scales. In this study, we address some of the challenges by applying a parallel version of the Triangulated Irregular Network (TIN)-based Real Time Integrated Basin Simulator (tRIBS) to the Rio Sonora Basin (RSB) in northwest Mexico. The RSB is a large, semiarid watershed ( 21,000 km2) characterized by complex topography and a strong seasonality in vegetation conditions, due to the North American monsoon. We conducted simulations at an average spatial resolution of 88 m over a decadal (2004-2013) period using spatially-distributed forcings from remotely-sensed and reanalysis products. Meteorological forcings were derived from the North American Land Data Assimilation System (NLDAS) at the original resolution of 12 km and were downscaled at 1 km with techniques accounting for terrain effects. Two grids of soil properties were created from different sources, including: (i) CONABIO (Comisión Nacional para el Conocimiento y Uso de la Biodiversidad) at 6 km resolution; and (ii) ISRIC (International Soil Reference Information Centre) at 250 m. Time-varying vegetation parameters were derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) composite products. The model was first calibrated and validated through distributed soil moisture data from a network of 20 soil moisture stations during the monsoon season. Next, hydrologic simulations were conducted with five different combinations of coarse and downscaled forcings and soil properties. Outputs in the different configurations were then compared with independent observations of soil moisture, and with estimates of land surface temperature (1 km, daily) and evapotranspiration (1 km, monthly) from MODIS. This study is expected to support the community involved in hyper-resolution hydrologic modeling by identifying the crucial factors that, if available at higher resolution, lead to the largest improvement of the simulation prognostic capability.

Aspects of spatial and temporal aggregation in estimating regional carbon dioxide fluxes from temperate forest soils

NASA Technical Reports Server (NTRS)

Kicklighter, David W.; Melillo, Jerry M.; Peterjohn, William T.; Rastetter, Edward B.; Mcguire, A. David; Steudler, Paul A.; Aber, John D.

1994-01-01

We examine the influence of aggregation errors on developing estimates of regional soil-CO2 flux from temperate forests. We find daily soil-CO2 fluxes to be more sensitive to changes in soil temperatures (Q(sub 10) = 3.08) than air temperatures (Q(sub 10) = 1.99). The direct use of mean monthly air temperatures with a daily flux model underestimates regional fluxes by approximately 4%. Temporal aggregation error varies with spatial resolution. Overall, our calibrated modeling approach reduces spatial aggregation error by 9.3% and temporal aggregation error by 15.5%. After minimizing spatial and temporal aggregation errors, mature temperate forest soils are estimated to contribute 12.9 Pg C/yr to the atmosphere as carbon dioxide. Georeferenced model estimates agree well with annual soil-CO2 fluxes measured during chamber studies in mature temperate forest stands around the globe.

Bridging the Past with Today's Microwave Remote Sensing: A Case Study of Long Term Inundation Patterns in Two River Deltas

NASA Astrophysics Data System (ADS)

McDonald, K. C.; Jensen, K.; Schroeder, R.; Tessler, Z. D.

2016-12-01

Surface inundation extent and its predictability vary tremendously across the globe. This dynamic is being and has been captured by three general categories of satellite imagery: a) low-spatial-resolution microwave sensors with global coverage and a long record of observations (e.g., SSM/I), b) optical sensors with high spatial and temporal resolution and global coverage as well, but with cloud contamination (e.g. MODIS), and also c) less frequently in ``snapshot'' form by high-resolution synthetic aperture radar (SAR) sensors. We explore the ability to bridge techniques that can exploit the higher spatial resolution of more recent data products back in time with the help of the temporal evolution of lower resolution products. We present a study of long term (20+ yrs) inundation patterns in two river deltas: (1) the Mekong, and (2) the Ganges-Brahmaputra. This research utilizes baseline observations from the Surface Water Microwave Product Series (SWAMPS), an inundation area fraction product derived at 25km scale from active and passive microwave instruments (ERS, QuikSCAT, ASCAT, and SSM/I) that spans from Jan 1992 to the present. Every hydrological basin has unique characteristics - such as its topography, land cover / land use, and spatio-temporal variability - thus, a downscaling algorithm needs to take into account these idiosyncrasies. We merge SWAMPS with topographical information derived from 30m SRTM DEM, river networks from USGS HydroSHEDS, and train a downscaling algorithm to learn from two sets of classified SAR data: (1) L-band imaging radar from ALOS PALSAR, 2007-2010, and (2) more recent C-band imagery from the Sentinel-1 mission (2014 to present). We present an accuracy assessment of retrospective downscaled flood extent with Landsat imagery and address potential sources of biases. With a higher spatial resolution of past flooding extent, we can improve our understanding of how delta surface hydrology has responded to climate events and human activities. This is important both in the short-term for accurate flood prediction, as well as on longer-term planning horizons.

How Cities Breathe: Ground-Referenced, Airborne Hyperspectral Imaging Precursor Measurements To Space-Based Monitoring

NASA Technical Reports Server (NTRS)

Leifer, Ira; Tratt, David; Quattrochi, Dale; Bovensmann, Heinrich; Gerilowski, Konstantin; Buchwitz, Michael; Burrows, John

2013-01-01

Methane's (CH4) large global warming potential (Shindell et al., 2012) and likely increasing future emissions due to global warming feedbacks emphasize its importance to anthropogenic greenhouse warming (IPCC, 2007). Furthermore, CH4 regulation has far greater near-term climate change mitigation potential versus carbon dioxide CO2, the other major anthropogenic Greenhouse Gas (GHG) (Shindell et al., 2009). Uncertainties in CH4 budgets arise from the poor state of knowledge of CH4 sources - in part from a lack of sufficiently accurate assessments of the temporal and spatial emissions and controlling factors of highly variable anthropogenic and natural CH4 surface fluxes (IPCC, 2007) and the lack of global-scale (satellite) data at sufficiently high spatial resolution to resolve sources. Many important methane (and other trace gases) sources arise from urban and mega-urban landscapes where anthropogenic activities are centered - most of humanity lives in urban areas. Studying these complex landscape tapestries is challenged by a wide and varied range of activities at small spatial scale, and difficulty in obtaining up-to-date landuse data in the developed world - a key desire of policy makers towards development of effective regulations. In the developing world, challenges are multiplied with additional political access challenges. As high spatial resolution satellite and airborne data has become available, activity mapping applications have blossomed - i.e., Google maps; however, tap a minute fraction of remote sensing capabilities due to limited (three band) spectral information. Next generation approaches that incorporate high spatial resolution hyperspectral and ultraspectral data will allow detangling of the highly heterogeneous usage megacity patterns by providing diagnostic identification of chemical composition from solids (refs) to gases (refs). To properly enable these next generation technologies for megacity include atmospheric radiative transfer modeling the complex and often aerosol laden, humid, urban microclimates, atmospheric transport and profile monitoring, spatial resolution, temporal cycles (diurnal and seasonal which involve interactions with the surrounding environment diurnal and seasonal cycles) and representative measurement approaches given traffic realities. Promising approaches incorporate contemporaneous airborne remote sensing and in situ measurements, nocturnal surface surveys, with ground station measurement

Use of Visible Satellite Imagery to Determine Velocity in Tidal Rivers

NASA Astrophysics Data System (ADS)

Mied, R. P.; Donato, T. F.; Chen, W.

2006-05-01

In the open ocean and on the continental shelf, current velocities have traditionally been calculated remotely using the Maximum Correlation Coefficient (MCC) technique to track features between sequential sea surface temperature image scenes. These images are obtained from NOAA polar orbiters having an effective ground pixel size of 1.47 km. In contrast to this relatively large distance, spatial scales over which current velocities can vary in rivers and estuaries are hundreds of meters; associated temporal scales vary from tens of minutes to hours. Traditional in-situ measurements can be instructive in determining some aspects of the flow, but truly synoptic overviews are possible only with remote sensing, provided high-resolution imagery is available. With the advent of a constellation of moderate- to high-resolution imaging systems (e.g., Landsat, ASTER, SPOT, Quickbird, Ikonos, and Orbview-3) it is now available to extend current estimations to these areas. For instance, Landsat-7 and ASTER produce imagery with spatial resolutions on the order of 30 m or less and within 30 min of each other. This is sufficient to spatially resolve a wide variety of surface features, and to maintain feature integrity over time for tracking purposes. We apply this approach to a portion of the tidal Potomac River by using pairs of co-registered, sequential, multi-spectral Landsat-7 and ASTER images. The final data used in the analysis set contain three spectral bands (green, red, and near-infrared), and have a ground pixel spacing (GSD) of 30m. The time step between each Landsat-7 and ASTER pair is approximately 29 minutes. Two image sets are used in the present study, one occurring on 5 October 2001 and the other on 2 April 2003. We show current maps derived from both image pairs an discuss the results in the light of model and

Multi-image acquisition-based distance sensor using agile laser spot beam.

PubMed

Riza, Nabeel A; Amin, M Junaid

2014-09-01

We present a novel laser-based distance measurement technique that uses multiple-image-based spatial processing to enable distance measurements. Compared with the first-generation distance sensor using spatial processing, the modified sensor is no longer hindered by the classic Rayleigh axial resolution limit for the propagating laser beam at its minimum beam waist location. The proposed high-resolution distance sensor design uses an electronically controlled variable focus lens (ECVFL) in combination with an optical imaging device, such as a charged-coupled device (CCD), to produce and capture different laser spot size images on a target with these beam spot sizes different from the minimal spot size possible at this target distance. By exploiting the unique relationship of the target located spot sizes with the varying ECVFL focal length for each target distance, the proposed distance sensor can compute the target distance with a distance measurement resolution better than the axial resolution via the Rayleigh resolution criterion. Using a 30 mW 633 nm He-Ne laser coupled with an electromagnetically actuated liquid ECVFL, along with a 20 cm focal length bias lens, and using five spot images captured per target position by a CCD-based Nikon camera, a proof-of-concept proposed distance sensor is successfully implemented in the laboratory over target ranges from 10 to 100 cm with a demonstrated sub-cm axial resolution, which is better than the axial Rayleigh resolution limit at these target distances. Applications for the proposed potentially cost-effective distance sensor are diverse and include industrial inspection and measurement and 3D object shape mapping and imaging.

Robust video super-resolution with registration efficiency adaptation

NASA Astrophysics Data System (ADS)

Zhang, Xinfeng; Xiong, Ruiqin; Ma, Siwei; Zhang, Li; Gao, Wen

2010-07-01

Super-Resolution (SR) is a technique to construct a high-resolution (HR) frame by fusing a group of low-resolution (LR) frames describing the same scene. The effectiveness of the conventional super-resolution techniques, when applied on video sequences, strongly relies on the efficiency of motion alignment achieved by image registration. Unfortunately, such efficiency is limited by the motion complexity in the video and the capability of adopted motion model. In image regions with severe registration errors, annoying artifacts usually appear in the produced super-resolution video. This paper proposes a robust video super-resolution technique that adapts itself to the spatially-varying registration efficiency. The reliability of each reference pixel is measured by the corresponding registration error and incorporated into the optimization objective function of SR reconstruction. This makes the SR reconstruction highly immune to the registration errors, as outliers with higher registration errors are assigned lower weights in the objective function. In particular, we carefully design a mechanism to assign weights according to registration errors. The proposed superresolution scheme has been tested with various video sequences and experimental results clearly demonstrate the effectiveness of the proposed method.

Three-Dimensional Orientation of Anisotropic Plasmonic Aggregates at Intracellular Nuclear Indentation Sites by Integrated Light Sheet Super-Resolution Microscopy.

PubMed

Chakkarapani, Suresh Kumar; Sun, Yucheng; Lee, Seungah; Fang, Ning; Kang, Seong Ho

2018-05-22

Three-dimensional (3D) orientations of individual anisotropic plasmonic nanoparticles in aggregates were observed in real time by integrated light sheet super-resolution microscopy ( iLSRM). Asymmetric light scattering of a gold nanorod (AuNR) was used to trigger signals based on the polarizer angle. Controlled photoswitching was achieved by turning the polarizer and obtaining a series of images at different polarization directions. 3D subdiffraction-limited super-resolution images were obtained by superlocalization of scattering signals as a function of the anisotropic optical properties of AuNRs. Varying the polarizer angle allowed resolution of the orientation of individual AuNRs. 3D images of individual nanoparticles were resolved in aggregated regions, resulting in as low as 64 nm axial resolution and 28 nm spatial resolution. The proposed imaging setup and localization approach demonstrates a convenient method for imaging under a noisy environment where the majority of scattering noise comes from cellular components. This integrated 3D iLSRM and localization technique was shown to be reliable and useful in the field of 3D nonfluorescence super-resolution imaging.

Modeling winter precipitation over the Juneau Icefield, Alaska, using a linear model of orographic precipitation

NASA Astrophysics Data System (ADS)

Roth, Aurora; Hock, Regine; Schuler, Thomas V.; Bieniek, Peter A.; Pelto, Mauri; Aschwanden, Andy

2018-03-01

Assessing and modeling precipitation in mountainous areas remains a major challenge in glacier mass balance modeling. Observations are typically scarce and reanalysis data and similar climate products are too coarse to accurately capture orographic effects. Here we use the linear theory of orographic precipitation model (LT model) to downscale winter precipitation from a regional climate model over the Juneau Icefield, one of the largest ice masses in North America (>4000 km2), for the period 1979-2013. The LT model is physically-based yet computationally efficient, combining airflow dynamics and simple cloud microphysics. The resulting 1 km resolution precipitation fields show substantially reduced precipitation on the northeastern portion of the icefield compared to the southwestern side, a pattern that is not well captured in the coarse resolution (20 km) WRF data. Net snow accumulation derived from the LT model precipitation agrees well with point observations across the icefield. To investigate the robustness of the LT model results, we perform a series of sensitivity experiments varying hydrometeor fall speeds, the horizontal resolution of the underlying grid, and the source of the meteorological forcing data. The resulting normalized spatial precipitation pattern is similar for all sensitivity experiments, but local precipitation amounts vary strongly, with greatest sensitivity to variations in snow fall speed. Results indicate that the LT model has great potential to provide improved spatial patterns of winter precipitation for glacier mass balance modeling purposes in complex terrain, but ground observations are necessary to constrain model parameters to match total amounts.

Simulating effects of brain atrophy in longitudinal PET imaging with an anthropomorphic brain phantom

NASA Astrophysics Data System (ADS)

Jonasson, L. S.; Axelsson, J.; Riklund, K.; Boraxbekk, C. J.

2017-07-01

In longitudinal positron emission tomography (PET), the presence of volumetric changes over time can lead to an overestimation or underestimation of the true changes in the quantified PET signal due to the partial volume effect (PVE) introduced by the limited spatial resolution of existing PET cameras and reconstruction algorithms. Here, a 3D-printed anthropomorphic brain phantom with attachable striata in three sizes was designed to enable controlled volumetric changes. Using a method to eliminate the non-radioactive plastic wall, and manipulating BP levels by adding different number of events from list-mode acquisitions, we investigated the artificial volume dependence of BP due to PVE, and potential bias arising from varying BP. Comparing multiple reconstruction algorithms we found that a high-resolution ordered-subsets maximization algorithm with spatially variant point-spread function resolution modeling provided the most accurate data. For striatum, the BP changed by 0.08% for every 1% volume change, but for smaller volumes such as the posterior caudate the artificial change in BP was as high as 0.7% per 1% volume change. A simple gross correction for striatal volume is unsatisfactory, as the amplitude of the PVE on the BP differs depending on where in the striatum the change occurred. Therefore, to correctly interpret age-related longitudinal changes in the BP, we must account for volumetric changes also within a structure, rather than across the whole volume. The present 3D-printing technology, combined with the wall removal method, can be implemented to gain knowledge about the predictable bias introduced by the PVE differences in uptake regions of varying shape.

Restoring the spatial resolution of refocus images on 4D light field

NASA Astrophysics Data System (ADS)

Lim, JaeGuyn; Park, ByungKwan; Kang, JooYoung; Lee, SeongDeok

2010-01-01

This paper presents the method for generating a refocus image with restored spatial resolution on a plenoptic camera, which functions controlling the depth of field after capturing one image unlike a traditional camera. It is generally known that the camera captures 4D light field (angular and spatial information of light) within a limited 2D sensor and results in reducing 2D spatial resolution due to inevitable 2D angular data. That's the reason why a refocus image is composed of a low spatial resolution compared with 2D sensor. However, it has recently been known that angular data contain sub-pixel spatial information such that the spatial resolution of 4D light field can be increased. We exploit the fact for improving the spatial resolution of a refocus image. We have experimentally scrutinized that the spatial information is different according to the depth of objects from a camera. So, from the selection of refocused regions (corresponding depth), we use corresponding pre-estimated sub-pixel spatial information for reconstructing spatial resolution of the regions. Meanwhile other regions maintain out-of-focus. Our experimental results show the effect of this proposed method compared to existing method.

Tight-frame based iterative image reconstruction for spectral breast CT

PubMed Central

Zhao, Bo; Gao, Hao; Ding, Huanjun; Molloi, Sabee

2013-01-01

Purpose: To investigate tight-frame based iterative reconstruction (TFIR) technique for spectral breast computed tomography (CT) using fewer projections while achieving greater image quality. Methods: The experimental data were acquired with a fan-beam breast CT system based on a cadmium zinc telluride photon-counting detector. The images were reconstructed with a varying number of projections using the TFIR and filtered backprojection (FBP) techniques. The image quality between these two techniques was evaluated. The image's spatial resolution was evaluated using a high-resolution phantom, and the contrast to noise ratio (CNR) was evaluated using a postmortem breast sample. The postmortem breast samples were decomposed into water, lipid, and protein contents based on images reconstructed from TFIR with 204 projections and FBP with 614 projections. The volumetric fractions of water, lipid, and protein from the image-based measurements in both TFIR and FBP were compared to the chemical analysis. Results: The spatial resolution and CNR were comparable for the images reconstructed by TFIR with 204 projections and FBP with 614 projections. Both reconstruction techniques provided accurate quantification of water, lipid, and protein composition of the breast tissue when compared with data from the reference standard chemical analysis. Conclusions: Accurate breast tissue decomposition can be done with three fold fewer projection images by the TFIR technique without any reduction in image spatial resolution and CNR. This can result in a two-third reduction of the patient dose in a multislit and multislice spiral CT system in addition to the reduced scanning time in this system. PMID:23464320

Evaluation of downscaled, gridded climate data for the conterminous United States

USGS Publications Warehouse

Robert J. Behnke,; Stephen J. Vavrus,; Andrew Allstadt,; Thomas P. Albright,; Thogmartin, Wayne E.; Volker C. Radeloff,

2016-01-01

Weather and climate affect many ecological processes, making spatially continuous yet fine-resolution weather data desirable for ecological research and predictions. Numerous downscaled weather data sets exist, but little attempt has been made to evaluate them systematically. Here we address this shortcoming by focusing on four major questions: (1) How accurate are downscaled, gridded climate data sets in terms of temperature and precipitation estimates?, (2) Are there significant regional differences in accuracy among data sets?, (3) How accurate are their mean values compared with extremes?, and (4) Does their accuracy depend on spatial resolution? We compared eight widely used downscaled data sets that provide gridded daily weather data for recent decades across the United States. We found considerable differences among data sets and between downscaled and weather station data. Temperature is represented more accurately than precipitation, and climate averages are more accurate than weather extremes. The data set exhibiting the best agreement with station data varies among ecoregions. Surprisingly, the accuracy of the data sets does not depend on spatial resolution. Although some inherent differences among data sets and weather station data are to be expected, our findings highlight how much different interpolation methods affect downscaled weather data, even for local comparisons with nearby weather stations located inside a grid cell. More broadly, our results highlight the need for careful consideration among different available data sets in terms of which variables they describe best, where they perform best, and their resolution, when selecting a downscaled weather data set for a given ecological application.

Phenomapping of rangelands in South Africa using time series of RapidEye data

NASA Astrophysics Data System (ADS)

Parplies, André; Dubovyk, Olena; Tewes, Andreas; Mund, Jan-Peter; Schellberg, Jürgen

2016-12-01

Phenomapping is an approach which allows the derivation of spatial patterns of vegetation phenology and rangeland productivity based on time series of vegetation indices. In our study, we propose a new spatial mapping approach which combines phenometrics derived from high resolution (HR) satellite time series with spatial logistic regression modeling to discriminate land management systems in rangelands. From the RapidEye time series for selected rangelands in South Africa, we calculated bi-weekly noise reduced Normalized Difference Vegetation Index (NDVI) images. For the growing season of 2011⿿2012, we further derived principal phenology metrics such as start, end and length of growing season and related phenological variables such as amplitude, left derivative and small integral of the NDVI curve. We then mapped these phenometrics across two different tenure systems, communal and commercial, at the very detailed spatial resolution of 5 m. The result of a binary logistic regression (BLR) has shown that the amplitude and the left derivative of the NDVI curve were statistically significant. These indicators are useful to discriminate commercial from communal rangeland systems. We conclude that phenomapping combined with spatial modeling is a powerful tool that allows efficient aggregation of phenology and productivity metrics for spatially explicit analysis of the relationships of crop phenology with site conditions and management. This approach has particular potential for disaggregated and patchy environments such as in farming systems in semi-arid South Africa, where phenology varies considerably among and within years. Further, we see a strong perspective for phenomapping to support spatially explicit modelling of vegetation.

Accuracy of stream habitat interpolations across spatial scales

USGS Publications Warehouse

Sheehan, Kenneth R.; Welsh, Stuart A.

2013-01-01

Stream habitat data are often collected across spatial scales because relationships among habitat, species occurrence, and management plans are linked at multiple spatial scales. Unfortunately, scale is often a factor limiting insight gained from spatial analysis of stream habitat data. Considerable cost is often expended to collect data at several spatial scales to provide accurate evaluation of spatial relationships in streams. To address utility of single scale set of stream habitat data used at varying scales, we examined the influence that data scaling had on accuracy of natural neighbor predictions of depth, flow, and benthic substrate. To achieve this goal, we measured two streams at gridded resolution of 0.33 × 0.33 meter cell size over a combined area of 934 m2 to create a baseline for natural neighbor interpolated maps at 12 incremental scales ranging from a raster cell size of 0.11 m2 to 16 m2 . Analysis of predictive maps showed a logarithmic linear decay pattern in RMSE values in interpolation accuracy for variables as resolution of data used to interpolate study areas became coarser. Proportional accuracy of interpolated models (r2 ) decreased, but it was maintained up to 78% as interpolation scale moved from 0.11 m2 to 16 m2 . Results indicated that accuracy retention was suitable for assessment and management purposes at various scales different from the data collection scale. Our study is relevant to spatial modeling, fish habitat assessment, and stream habitat management because it highlights the potential of using a single dataset to fulfill analysis needs rather than investing considerable cost to develop several scaled datasets.

Analysis of Trace Siderophile Elements at High Spatial Resolution Using Laser Ablation ICP-MS

NASA Astrophysics Data System (ADS)

Campbell, A. J.; Humayun, M.

2006-05-01

Laser ablation inductively coupled plasma mass spectometry is an increasingly important method of performing spatially resolved trace element analyses. Over the last several years we have applied this technique to measure siderophile element distributions at the ppm level in a variety of natural and synthetic samples, especially metallic phases in meteorites and experimental run products intended for trace element partitioning studies. These samples frequently require trace element analyses to be made at a finer spatial resolution (25 microns or better) than is frequently attained using LA-ICP-MS. In this presentation we review analytical protocols that were developed to optimize the LA-ICP-MS measurements for high spatial resolution. Particular attention is paid to the trade-offs involving sensitivity, ablation pit depth and diameter, background levels, and number of elements measured. To maximize signal/background ratios and avoid difficulties associated with ablating to depths greater than the ablation pit diameter, measurement involved integration of rapidly varying, transient but well-behaved signals. The abundances of platinum group elements and other siderophile elements in ferrous metals were calibrated against well-characterized standards, including iron meteorites and NIST certified steels. The calibrations can be set against the known abundance of an independently determined element, but normalization to 100 percent can also be employed, and was more useful in many circumstances. Evaluation of uncertainties incorporated counting statistics as well as a measure of instrumental uncertainty, determined by replicate analyses of the standards. These methods have led to a number of insights into the formation and chemical processing of metal in the early solar system.

Ultrasound line-by-line scanning method of spatial-temporal active cavitation mapping for high-intensity focused ultrasound.

PubMed

Ding, Ting; Zhang, Siyuan; Fu, Quanyou; Xu, Zhian; Wan, Mingxi

2014-01-01

This paper presented an ultrasound line-by-line scanning method of spatial-temporal active cavitation mapping applicable in a liquid or liquid filled tissue cavities exposed by high-intensity focused ultrasound (HIFU). Scattered signals from cavitation bubbles were obtained in a scan line immediately after one HIFU exposure, and then there was a waiting time of 2 s long enough to make the liquid back to the original state. As this pattern extended, an image was built up by sequentially measuring a series of such lines. The acquisition of the beamformed radiofrequency (RF) signals for a scan line was synchronized with HIFU exposure. The duration of HIFU exposure, as well as the delay of the interrogating pulse relative to the moment while HIFU was turned off, could vary from microseconds to seconds. The feasibility of this method was demonstrated in tap-water and a tap-water filled cavity in the tissue-mimicking gelatin-agar phantom as capable of observing temporal evolutions of cavitation bubble cloud with temporal resolution of several microseconds, lateral and axial resolution of 0.50 mm and 0.29 mm respectively. The dissolution process of cavitation bubble cloud and spatial distribution affected by cavitation previously generated were also investigated. Although the application is limited by the requirement for a gassy fluid (e.g. tap water, etc.) that allows replenishment of nuclei between HIFU exposures, the technique may be a useful tool in spatial-temporal cavitation mapping for HIFU with high precision and resolution, providing a reference for clinical therapy. Copyright © 2013 Elsevier B.V. All rights reserved.

High Spatial Resolution Commercial Satellite Imaging Product Characterization

NASA Technical Reports Server (NTRS)

Ryan, Robert E.; Pagnutti, Mary; Blonski, Slawomir; Ross, Kenton W.; Stnaley, Thomas

2005-01-01

NASA Stennis Space Center's Remote Sensing group has been characterizing privately owned high spatial resolution multispectral imaging systems, such as IKONOS, QuickBird, and OrbView-3. Natural and man made targets were used for spatial resolution, radiometric, and geopositional characterizations. Higher spatial resolution also presents significant adjacency effects for accurate reliable radiometry.

The impact of high-resolution topography on landslide characterization using DInSAR

NASA Astrophysics Data System (ADS)

Tiampo, K. F.; Barba, M.; Jacquemart, M. F.; Willis, M. J.; González, P. J.; McKee, C.; Samsonov, S. V.; Feng, W.

2017-12-01

Differential interferometric synthetic aperture radar (DInSAR) can measure surface deformation at the centimeter level and, as a result, has been used to investigate a wide variety of natural hazards since the 1990s. In general, short spatial and temporal baselines are selected to reduce decorrelation and the effect of incorrect removal of the topographic component in differential interferograms. The nearly global coverage of the Shuttle Radar Topography Mission (SRTM) digital elevation models (DEMs) significantly simplified and improved the modelling and removal of topography for differential interferometric applications. However, DEMs are produced today at much finer resolutions, although with varying availability and cost. SRTM DEMs are freely available at 30 m resolution world-wide and 10 m resolution in the US. The TanDEM-X mission has produced a worldwide DEM at 12 m, although it is not generally free of cost. Light Detection and Ranging (LiDAR) DEMs can provide better than 1m resolution, but are expensive to produce over limited extents. Finally, DEMs from optical data can be produced from Digital Globe satellite images over larger regions at resolutions of less than 1 m, subject to various restrictions. It can be shown that the coherence quality of a DInSAR image is directly related to the DEM resolution, improving recovery of the differential phase by significantly reducing the geometric decorrelation, and that the number of recovered pixels significantly increases with higher resolutions, particularly in steep topography. In this work we quantify that improvement for varying resolutions, from 1 to 30 m, and slopes and investigate its effect on the characterization of landslides in different regions and with a variety of surface conditions, including Greenland, Alaska, California, and the Canary Islands.

Resolution Enhancement of Hyperion Hyperspectral Data using Ikonos Multispectral Data

DTIC Science & Technology

2007-09-01

spatial - resolution hyperspectral image to produce a sharpened product. The result is a product that has the spectral properties of the ...multispectral sensors. In this work, we examine the benefits of combining data from high- spatial - resolution , low- spectral - resolution spectral imaging...sensors with data obtained from high- spectral - resolution , low- spatial - resolution spectral imaging sensors.

Spatial statistical analysis of tree deaths using airborne digital imagery

NASA Astrophysics Data System (ADS)

Chang, Ya-Mei; Baddeley, Adrian; Wallace, Jeremy; Canci, Michael

2013-04-01

High resolution digital airborne imagery offers unprecedented opportunities for observation and monitoring of vegetation, providing the potential to identify, locate and track individual vegetation objects over time. Analytical tools are required to quantify relevant information. In this paper, locations of trees over a large area of native woodland vegetation were identified using morphological image analysis techniques. Methods of spatial point process statistics were then applied to estimate the spatially-varying tree death risk, and to show that it is significantly non-uniform. [Tree deaths over the area were detected in our previous work (Wallace et al., 2008).] The study area is a major source of ground water for the city of Perth, and the work was motivated by the need to understand and quantify vegetation changes in the context of water extraction and drying climate. The influence of hydrological variables on tree death risk was investigated using spatial statistics (graphical exploratory methods, spatial point pattern modelling and diagnostics).

Applications of the line-of-response probability density function resolution model in PET list mode reconstruction.

PubMed

Jian, Y; Yao, R; Mulnix, T; Jin, X; Carson, R E

2015-01-07

Resolution degradation in PET image reconstruction can be caused by inaccurate modeling of the physical factors in the acquisition process. Resolution modeling (RM) is a common technique that takes into account the resolution degrading factors in the system matrix. Our previous work has introduced a probability density function (PDF) method of deriving the resolution kernels from Monte Carlo simulation and parameterizing the LORs to reduce the number of kernels needed for image reconstruction. In addition, LOR-PDF allows different PDFs to be applied to LORs from different crystal layer pairs of the HRRT. In this study, a thorough test was performed with this new model (LOR-PDF) applied to two PET scanners-the HRRT and Focus-220. A more uniform resolution distribution was observed in point source reconstructions by replacing the spatially-invariant kernels with the spatially-variant LOR-PDF. Specifically, from the center to the edge of radial field of view (FOV) of the HRRT, the measured in-plane FWHMs of point sources in a warm background varied slightly from 1.7 mm to 1.9 mm in LOR-PDF reconstructions. In Minihot and contrast phantom reconstructions, LOR-PDF resulted in up to 9% higher contrast at any given noise level than image-space resolution model. LOR-PDF also has the advantage in performing crystal-layer-dependent resolution modeling. The contrast improvement by using LOR-PDF was verified statistically by replicate reconstructions. In addition, [(11)C]AFM rats imaged on the HRRT and [(11)C]PHNO rats imaged on the Focus-220 were utilized to demonstrated the advantage of the new model. Higher contrast between high-uptake regions of only a few millimeter diameter and the background was observed in LOR-PDF reconstruction than in other methods.

Applications of the line-of-response probability density function resolution model in PET list mode reconstruction

PubMed Central

Jian, Y; Yao, R; Mulnix, T; Jin, X; Carson, R E

2016-01-01

Resolution degradation in PET image reconstruction can be caused by inaccurate modeling of the physical factors in the acquisition process. Resolution modeling (RM) is a common technique that takes into account the resolution degrading factors in the system matrix. Our previous work has introduced a probability density function (PDF) method of deriving the resolution kernels from Monte Carlo simulation and parameterizing the LORs to reduce the number of kernels needed for image reconstruction. In addition, LOR-PDF allows different PDFs to be applied to LORs from different crystal layer pairs of the HRRT. In this study, a thorough test was performed with this new model (LOR-PDF) applied to two PET scanners - the HRRT and Focus-220. A more uniform resolution distribution was observed in point source reconstructions by replacing the spatially-invariant kernels with the spatially-variant LOR-PDF. Specifically, from the center to the edge of radial field of view (FOV) of the HRRT, the measured in-plane FWHMs of point sources in a warm background varied slightly from 1.7 mm to 1.9 mm in LOR-PDF reconstructions. In Minihot and contrast phantom reconstructions, LOR-PDF resulted in up to 9% higher contrast at any given noise level than image-space resolution model. LOR-PDF also has the advantage in performing crystal-layer-dependent resolution modeling. The contrast improvement by using LOR-PDF was verified statistically by replicate reconstructions. In addition, [11C]AFM rats imaged on the HRRT and [11C]PHNO rats imaged on the Focus-220 were utilized to demonstrated the advantage of the new model. Higher contrast between high-uptake regions of only a few millimeter diameter and the background was observed in LOR-PDF reconstruction than in other methods. PMID:25490063

Using Rose’s metal alloy as a pinhole collimator material in preclinical small-animal imaging: A Monte Carlo evaluation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peterson, Mikael, E-mail: Mikael.Peterson@med.lu.se; Strand, Sven-Erik; Ljungberg, Michael

Purpose: Pinhole collimation is the most common method of high-resolution preclinical single photon emission computed tomography imaging. The collimators are usually constructed from dense materials with high atomic numbers, such as gold and platinum, which are expensive and not always flexible in the fabrication step. In this work, the authors have investigated the properties of a fusible alloy called Rose’s metal and its potential in pinhole preclinical imaging. When compared to current standard pinhole materials such as gold and platinum, Rose’s metal has a lower density and a relatively low effective atomic number. However, it is inexpensive, has a lowmore » melting point, and does not contract when solidifying. Once cast, the piece can be machined with high precision. The aim of this study was to evaluate the imaging properties for Rose’s metal and compare them with those of standard materials. Methods: After validating their Monte Carlo code by comparing its results with published data and the results from analytical calculations, they investigated different pinhole geometries by varying the collimator material, acceptance angle, aperture diameter, and photon incident angle. The penetration-to-scatter and penetration-to-total component ratios, sensitivity, and the spatial resolution were determined for gold, tungsten, and Rose’s metal for two radionuclides, {sup 99}Tc{sup m} and {sup 125}I. Results: The Rose’s metal pinhole-imaging simulations show higher penetration/total and scatter/total ratios. For example, the penetration/total is 50% for gold and 75% for Rose’s metal when simulating {sup 99}Tc{sup m} with a 0.3 mm aperture diameter and a 60° acceptance angle. However, the degradation in spatial resolution remained below 10% relative to the spatial resolution for gold for acceptance angles below 40° and aperture diameters larger than 0.5 mm. Conclusions: Extra penetration and scatter associated with Rose’s metal contribute to degradation in the spatial resolution, but this degradation is not always substantial. The most important factor besides the collimator material was the acceptance angle. This should be kept to a minimum to prevent unnecessary scatter and penetration. For {sup 125}I, the difference in spatial resolution between gold and Rose’s metal is very small, 2.2% in the worst-case scenario. Based on these results, the authors conclude that Rose’s metal is an alternative to standard materials not only for low-energy photon imaging but also for medium-energy applications that require low-cost, flexible pinhole configurations and designs, and that can tolerate a degraded spatial resolution.« less

A new high resolution permafrost map of Iceland from Earth Observation data

NASA Astrophysics Data System (ADS)

Barnie, Talfan; Conway, Susan; Balme, Matt; Graham, Alastair

2017-04-01

High resolution maps of permafrost are required for ongoing monitoring of environmental change and the resulting hazards to ecosystems, people and infrastructure. However, permafrost maps are difficult to construct - direct observations require maintaining networks of sensors and boreholes in harsh environments and are thus limited in extent in space and time, and indirect observations require models or assumptions relating the measurements (e.g. weather station air temperature, basal snow temperature) to ground temperature. Operationally produced Land Surface Temperature maps from Earth Observation data can be used to make spatially contiguous estimates of mean annual skin temperature, which has been used a proxy for the presence of permafrost. However these maps are subject to biases due to (i) selective sampling during the day due to limited satellite overpass times, (ii) selective sampling over the year due to seasonally varying cloud cover, (iii) selective sampling of LST only during clearsky conditions, (iv) errors in cloud masking (v) errors in temperature emissivity separation (vi) smoothing over spatial variability. In this study we attempt to compensate for some of these problems using a bayesian modelling approach and high resolution topography-based downscaling.

Photoinduced force microscopy: A technique for hyperspectral nanochemical mapping

NASA Astrophysics Data System (ADS)

Murdick, Ryan A.; Morrison, William; Nowak, Derek; Albrecht, Thomas R.; Jahng, Junghoon; Park, Sung

2017-08-01

Advances in nanotechnology have intensified the need for tools that can characterize newly synthesized nanomaterials. A variety of techniques has recently been shown which combines atomic force microscopy (AFM) with optical illumination including tip-enhanced Raman spectroscopy (TERS), scattering-type scanning near-field optical microscopy (sSNOM), and photothermal induced resonance microscopy (PTIR). To varying degrees, these existing techniques enable optical spectroscopy with the nanoscale spatial resolution inherent to AFM, thereby providing nanochemical interrogation of a specimen. Here we discuss photoinduced force microscopy (PiFM), a recently developed technique for nanoscale optical spectroscopy that exploits image forces acting between an AFM tip and sample to detect wavelength-dependent polarization within the sample to generate absorption spectra. This approach enables ∼10 nm spatial resolution with spectra that show correlation with macroscopic optical absorption spectra. Unlike other techniques, PiFM achieves this high resolution with virtually no constraints on sample or substrate properties. The applicability of PiFM to a variety of archetypal systems is reported here, highlighting the potential of PiFM as a useful tool for a wide variety of industrial and academic investigations, including semiconducting nanoparticles, nanocellulose, block copolymers, and low dimensional systems, as well as chemical and morphological mixing at interfaces.

Retrieved Products from Simulated Hyperspectral Observations of a Hurricane

NASA Technical Reports Server (NTRS)

Susskind, Joel; Kouvaris, Louis; Iredell, Lena; Blaisdell, John

2015-01-01

Demonstrate via Observing System Simulation Experiments (OSSEs) the potential utility of flying high spatial resolution AIRS class IR sounders on future LEO and GEO missions.The study simulates and analyzes radiances for 3 sounders with AIRS spectral and radiometric properties on different orbits with different spatial resolutions: 1) Control run 13 kilometers AIRS spatial resolution at nadir on LEO in Aqua orbit; 2) 2 kilometer spatial resolution LEO sounder at nadir ARIES; 3) 5 kilometers spatial resolution sounder on a GEO orbit, radiances simulated every 72 minutes.

Measurement of temperature and density fluctuations in turbulence using an ultraviolet laser

NASA Technical Reports Server (NTRS)

Massey, G. A.

1984-01-01

Noninvasive measurement of density and temperature fluctuations in turbulent air flow was examined. The approach used fluorescence of oxygen molecules which are selectively excited by a tunable vacuum ultraviolet laser beam. The strength of the fluorescence signal and its dependence on laser wavelength vary with the density and temperature of the air in the laser beam. Because fluorescence can be detected at 90 degrees from the beam propagation direction, spatial resolution in three dimensions, rather than path-integrated measurements can be achieved. With spatial resolutions of the order of a millimeter and at supersonic air velocities it is necessary to perform each measurement in a time of the order of a microsecond; this is possible by by using laser pulses of ten nanosecond duration. In this method atmospheric O2 is excited by the emission of a tunable ArF excimer laser, and the fluorescence, which spans the 210 to 420 range, is detected by an ultraviolet phototube.

The Marshall Grazing Incidence X-ray Spectrometer

NASA Astrophysics Data System (ADS)

Kobayashi, Ken; Winebarger, Amy R.; Savage, Sabrina; Champey, Patrick; Cheimets, Peter N.; Hertz, Edward; Bruccoleri, Alexander R.; Golub, Leon; Ramsey, Brian; Ranganathan, Jaganathan; Marquez, Vanessa; Allured, Ryan; Parker, Theodore; Heilmann, Ralf K.; Schattenburg, Mark L.

2017-08-01

The Marshall Grazing Incidence X-ray Spectrometer (MaGIXS) is a NASA sounding rocket instrument designed to obtain spatially resolved soft X-ray spectra of the solar atmosphere in the 6-24 Å (0.5-2.0 keV) range. The instrument consists of a single shell Wolter Type-I telescope, a slit, and a spectrometer comprising a matched pair of grazing incidence parabolic mirrors and a planar varied-line space diffraction grating. The instrument is designed to achieve a 50 mÅ spectral resolution and 5 arcsecond spatial resolution along a +/-4-arcminute long slit, and launch is planned for 2019. We report on the status and our approaches for fabrication and alignment for this novel optical system. The telescope and spectrometer mirrors are replicated nickel shells, and are currently being fabricated at the NASA Marshall Space Flight Center. The diffraction grating is currently under development by the Massachusetts Institute of Technology (MIT); because of the strong line spacing variation across the grating, it will be fabricated through e-beam lithography.

Image construction from the IRAS survey and data fusion

NASA Technical Reports Server (NTRS)

Bontekoe, Tj. R.

1990-01-01

The IRAS survey data can be used successfully to produce images of extended objects. The major difficulty, viz. non-uniform sampling, different response functions for each detector, and varying signal-to-noise levels for each detector for each scan, were resolved. The results of three different image construction techniques are compared: co-addition, constrained least squares, and maximum entropy. The maximum entropy result is superior. An image of the galaxy M51 with an average spatial resolution of 45 arc seconds, is presented using 60 micron survey data. This exceeds the telescope diffraction limit of 1 minute of arc, at this wavelength. Data fusion is a proposed method for combining data from different instruments, with different spatial resolutions, at different wavelengths. Direct estimates of the physical parameters, temperature, density and composition, can be made from the data without prior images (re-)construction. An increase in the accuracy of these parameters is expected as the result of this more systematic approach.

Study of Electric Explosion of Flat Micron-Thick Foils at Current Densities of (5-50)×108 A/cm2

NASA Astrophysics Data System (ADS)

Shelkovenko, T. A.; Pikuz, S. A.; Tilikin, I. N.; Mingaleev, A. R.; Atoyan, L.; Hammer, D. A.

2018-02-01

Electric explosions of flat Al, Ti, Ni, Cu, and Ta foils with thicknesses of 1-16 μm, widths of 1-8 mm, and lengths of 5-11 mm were studied experimentally on the BIN, XP, and COBRA high-current generators at currents of 40-1000 kA and current densities of (5-50) × 108 A/cm2. The images of the exploded foils were taken at different angles to the foil surface by using point projection radiography with an X-pinch hot spot as the radiation source, the spatial resolution and exposure time being 3 μm and 50 ps, respectively, as well by the laser probing method with a spatial resolution of 20 μm and an exposure time of 180 ps. In the course of foil explosion, rapidly expanding objects resembling the core and corona of an exploded wire were observed. It is shown that the core of the exploded foil has a complicated time-varying structure.

Integrating stations from the North America Gravity Database into a local GPS-based land gravity survey

USGS Publications Warehouse

Shoberg, Thomas G.; Stoddard, Paul R.

2013-01-01

The ability to augment local gravity surveys with additional gravity stations from easily accessible national databases can greatly increase the areal coverage and spatial resolution of a survey. It is, however, necessary to integrate such data seamlessly with the local survey. One challenge to overcome in integrating data from national databases is that these data are typically of unknown quality. This study presents a procedure for the evaluation and seamless integration of gravity data of unknown quality from a national database with data from a local Global Positioning System (GPS)-based survey. The starting components include the latitude, longitude, elevation and observed gravity at each station location. Interpolated surfaces of the complete Bouguer anomaly are used as a means of quality control and comparison. The result is an integrated dataset of varying quality with many stations having GPS accuracy and other reliable stations of unknown origin, yielding a wider coverage and greater spatial resolution than either survey alone.

Monitoring mangrove forests after aquaculture abandonment using time series of very high spatial resolution satellite images: A case study from the Perancak estuary, Bali, Indonesia.

PubMed

Proisy, Christophe; Viennois, Gaëlle; Sidik, Frida; Andayani, Ariani; Enright, James Anthony; Guitet, Stéphane; Gusmawati, Niken; Lemonnier, Hugues; Muthusankar, Gowrappan; Olagoke, Adewole; Prosperi, Juliana; Rahmania, Rinny; Ricout, Anaïs; Soulard, Benoit; Suhardjono

2018-06-01

Revegetation of abandoned aquaculture regions should be a priority for any integrated coastal zone management (ICZM). This paper examines the potential of a matchless time series of 20 very high spatial resolution (VHSR) optical satellite images acquired for mapping trends in the evolution of mangrove forests from 2001 to 2015 in an estuary fragmented into aquaculture ponds. Evolution of mangrove extent was quantified through robust multitemporal analysis based on supervised image classification. Results indicated that mangroves are expanding inside and outside ponds and over pond dykes. However, the yearly expansion rate of vegetation cover greatly varied between replanted ponds. Ground truthing showed that only Rhizophora species had been planted, whereas natural mangroves consist of Avicennia and Sonneratia species. In addition, the dense Rhizophora plantations present very low regeneration capabilities compared with natural mangroves. Time series of VHSR images provide comprehensive and intuitive level of information for the support of ICZM. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Study of Feature Extraction Using Divergence Analysis of Texture Features

NASA Technical Reports Server (NTRS)

Hallada, W. A.; Bly, B. G.; Boyd, R. K.; Cox, S.

1982-01-01

An empirical study of texture analysis for feature extraction and classification of high spatial resolution remotely sensed imagery (10 meters) is presented in terms of specific land cover types. The principal method examined is the use of spatial gray tone dependence (SGTD). The SGTD method reduces the gray levels within a moving window into a two-dimensional spatial gray tone dependence matrix which can be interpreted as a probability matrix of gray tone pairs. Haralick et al (1973) used a number of information theory measures to extract texture features from these matrices, including angular second moment (inertia), correlation, entropy, homogeneity, and energy. The derivation of the SGTD matrix is a function of: (1) the number of gray tones in an image; (2) the angle along which the frequency of SGTD is calculated; (3) the size of the moving window; and (4) the distance between gray tone pairs. The first three parameters were varied and tested on a 10 meter resolution panchromatic image of Maryville, Tennessee using the five SGTD measures. A transformed divergence measure was used to determine the statistical separability between four land cover categories forest, new residential, old residential, and industrial for each variation in texture parameters.

Visibility of wavelet quantization noise

NASA Technical Reports Server (NTRS)

Watson, A. B.; Yang, G. Y.; Solomon, J. A.; Villasenor, J.

1997-01-01

The discrete wavelet transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression. Measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band of coefficients results in an artifact that we call DWT uniform quantization noise; it is the sum of a lattice of random amplitude basis functions of the corresponding DWT synthesis filter. We measured visual detection thresholds for samples of DWT uniform quantization noise in Y, Cb, and Cr color channels. The spatial frequency of a wavelet is r 2-lambda, where r is display visual resolution in pixels/degree, and lambda is the wavelet level. Thresholds increase rapidly with wavelet spatial frequency. Thresholds also increase from Y to Cr to Cb, and with orientation from lowpass to horizontal/vertical to diagonal. We construct a mathematical model for DWT noise detection thresholds that is a function of level, orientation, and display visual resolution. This allows calculation of a "perceptually lossless" quantization matrix for which all errors are in theory below the visual threshold. The model may also be used as the basis for adaptive quantization schemes.

MODIS 3 Km Aerosol Product: Applications over Land in an Urban/suburban Region

NASA Technical Reports Server (NTRS)

Munchak, L. A.; Levy, R. C.; Mattoo, S.; Remer, L. A.; Holben, B. N.; Schafer, J. S.; Hostetler, C. A.; Ferrare, R. A.

2013-01-01

MODerate resolution Imaging Spectroradiometer (MODIS) instruments aboard the Terra and Aqua satellites have provided a rich dataset of aerosol information at a 10 km spatial scale. Although originally intended for climate applications, the air quality community quickly became interested in using the MODIS aerosol data. However, 10 km resolution is not sufficient to resolve local scale aerosol features. With this in mind, MODIS Collection 6 is including a global aerosol product with a 3 km resolution. Here, we evaluate the 3 km product over the Baltimore/Washington D.C., USA, corridor during the summer of 2011, by comparing with spatially dense data collected as part of the DISCOVER-AQ campaign these data were measured by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and a network of 44 sun photometers (SP) spaced approximately 10 km apart. The HSRL instrument shows that AOD can vary by up to 0.2 within a single 10 km MODIS pixel, meaning that higher resolution satellite retrievals may help to characterize aerosol spatial distributions in this region. Different techniques for validating a high-resolution aerosol product against SP measurements are considered. Although the 10 km product is more statistically reliable than the 3 km product, the 3 km product still performs acceptably, with more than two-thirds of MODIS/SP collocations falling within the expected error envelope with high correlation (R > 0.90). The 3 km product can better resolve aerosol gradients and retrieve closer to clouds and shorelines than the 10 km product, but tends to show more significant noise especially in urban areas. This urban degradation is quantified using ancillary land cover data. Overall, we show that the MODIS 3 km product adds new information to the existing set of satellite derived aerosol products and validates well over the region, but due to noise and problems in urban areas, should be treated with some degree of caution.

Impact of Urbanization on Spatial Variability of Rainfall-A case study of Mumbai city with WRF Model

NASA Astrophysics Data System (ADS)

Mathew, M.; Paul, S.; Devanand, A.; Ghosh, S.

2015-12-01

Urban precipitation enhancement has been identified over many cities in India by previous studies conducted. Anthropogenic effects such as change in land cover from hilly forest areas to flat topography with solid concrete infrastructures has certain effect on the local weather, the same way the greenhouse gas has on climate change. Urbanization could alter the large scale forcings to such an extent that it may bring about temporal and spatial changes in the urban weather. The present study investigate the physical processes involved in urban forcings, such as the effect of sudden increase in wind velocity travelling through the channel space in between the dense array of buildings, which give rise to turbulence and air mass instability in urban boundary layer and in return alters the rainfall distribution as well as rainfall initiation. A numerical model study is conducted over Mumbai metropolitan city which lies on the west coast of India, to assess the effect of urban morphology on the increase in number of extreme rainfall events in specific locations. An attempt has been made to simulate twenty extreme rainfall events that occurred over the summer monsoon period of the year 2014 using high resolution WRF-ARW (Weather Research and Forecasting-Advanced Research WRF) model to assess the urban land cover mechanisms that influences precipitation variability over this spatially varying urbanized region. The result is tested against simulations with altered land use. The correlation of precipitation with spatial variability of land use is found using a detailed urban land use classification. The initial and boundary conditions for running the model were obtained from the global model ECMWF(European Centre for Medium Range Weather Forecast) reanalysis data having a horizontal resolution of 0.75 °x 0.75°. The high resolution simulations show significant spatial variability in the accumulated rainfall, within a few kilometers itself. Understanding the spatial variability of precipitation will help in the planning and management of the built environment more efficiently.

Detector motion method to increase spatial resolution in photon-counting detectors

NASA Astrophysics Data System (ADS)

Lee, Daehee; Park, Kyeongjin; Lim, Kyung Taek; Cho, Gyuseong

2017-03-01

Medical imaging requires high spatial resolution of an image to identify fine lesions. Photon-counting detectors in medical imaging have recently been rapidly replacing energy-integrating detectors due to the former`s high spatial resolution, high efficiency and low noise. Spatial resolution in a photon counting image is determined by the pixel size. Therefore, the smaller the pixel size, the higher the spatial resolution that can be obtained in an image. However, detector redesigning is required to reduce pixel size, and an expensive fine process is required to integrate a signal processing unit with reduced pixel size. Furthermore, as the pixel size decreases, charge sharing severely deteriorates spatial resolution. To increase spatial resolution, we propose a detector motion method using a large pixel detector that is less affected by charge sharing. To verify the proposed method, we utilized a UNO-XRI photon-counting detector (1-mm CdTe, Timepix chip) at the maximum X-ray tube voltage of 80 kVp. A similar spatial resolution of a 55- μm-pixel image was achieved by application of the proposed method to a 110- μm-pixel detector with a higher signal-to-noise ratio. The proposed method could be a way to increase spatial resolution without a pixel redesign when pixels severely suffer from charge sharing as pixel size is reduced.

The Effect of Remote Sensor Spatial Resolution in Monitoring U.S. Army Training Maneuver Sites

DTIC Science & Technology

1990-12-01

THE EFFECT OF REMOTE SENSOR SPATIAL RESOLUTION IN MONITORING U.S. ARMY...Multispectral Scanner with 6.5 meter spatial resolution provided the most effective digital data set for enhancing tank trails. However, this Airborne Scanner...primary objective of this research was to determine the capabilities and limitations of remote sensor systems having different spatial resolutions to

Chiral Domain Structure in Superfluid 3He-A Studied by Magnetic Resonance Imaging

NASA Astrophysics Data System (ADS)

Kasai, J.; Okamoto, Y.; Nishioka, K.; Takagi, T.; Sasaki, Y.

2018-05-01

The existence of a spatially varying texture in superfluid 3He is a direct manifestation of the complex macroscopic wave function. The real space shape of the texture, namely, a macroscopic wave function, has been studied extensively with the help of theoretical modeling but has never been directly observed experimentally with spatial resolution. We have succeeded in visualizing the texture by a specialized magnetic resonance imaging. With this new technology, we have discovered that the macroscopic chiral domains, of which sizes are as large as 1 mm, and corresponding chiral domain walls exist rather stably in 3He - A film at temperatures far below the transition temperature.

The effects of transient attention on spatial resolution and the size of the attentional cue.

PubMed

Yeshurun, Yaffa; Carrasco, Marisa

2008-01-01

It has been shown that transient attention enhances spatial resolution, but is the effect of transient attention on spatial resolution modulated by the size of the attentional cue? Would a gradual increase in the size of the cue lead to a gradual decrement in spatial resolution? To test these hypotheses, we used a texture segmentation task in which performance depends on spatial resolution, and systematically manipulated the size of the attentional cue: A bar of different lengths (Experiment 1) or a frame of different sizes (Experiments 2-3) indicated the target region in a texture segmentation display. Observers indicated whether a target patch region (oriented line elements in a background of an orthogonal orientation), appearing at a range of eccentricities, was present in the first or the second interval. We replicated the attentional enhancement of spatial resolution found with small cues; attention improved performance at peripheral locations but impaired performance at central locations. However, there was no evidence of gradual resolution decrement with large cues. Transient attention enhanced spatial resolution at the attended location when it was attracted to that location by a small cue but did not affect resolution when it was attracted by a large cue. These results indicate that transient attention cannot adapt its operation on spatial resolution on the basis of the size of the attentional cue.

Selecting a spatial resolution for estimation of per-field green leaf area index

NASA Technical Reports Server (NTRS)

Curran, Paul J.; Williamson, H. Dawn

1988-01-01

For any application of multispectral scanner (MSS) data, a user is faced with a number of choices concerning the characteristics of the data; one of these is their spatial resolution. A pilot study was undertaken to determine the spatial resolution that would be optimal for the per-field estimation of green leaf area index (GLAI) in grassland. By reference to empirically-derived data from three areas of grassland, the suitable spatial resolution was hypothesized to lie in the lower portion of a 2-18 m range. To estimate per-field GLAI, airborne MSS data were collected at spatial resolutions of 2 m, 5 m and 10 m. The highest accuracies of per-field GLAI estimation were achieved using MSS data with spatial resolutions of 2 m and 5 m.

Spatial Metadata for Global Change Investigations Using Remote Sensing

NASA Technical Reports Server (NTRS)

Emerson, Charles W.; Quattrochi, Dale A.; Lam, Nina Siu-Ngan; Arnold, James E. (Technical Monitor)

2002-01-01

Satellite and aircraft-borne remote sensors have gathered petabytes of data over the past 30+ years. These images are an important resource for establishing cause and effect relationships between human-induced land cover changes and alterations in climate and other biophysical patterns at local to global scales. However, the spatial, temporal, and spectral characteristics of these datasets vary, thus complicating long-term studies involving several types of imagery. As the geographical and temporal coverage, the spectral and spatial resolution, and the number of individual sensors increase, the sheer volume and complexity of available data sets will complicate management and use of the rapidly growing archive of earth imagery. Mining this vast data resource for images that provide the necessary information for climate change studies becomes more difficult as more sensors are launched and more imagery is obtained.

On the use of adaptive multiresolution method with time-varying tolerance for compressible fluid flows

NASA Astrophysics Data System (ADS)

Soni, V.; Hadjadj, A.; Roussel, O.

2017-12-01

In this paper, a fully adaptive multiresolution (MR) finite difference scheme with a time-varying tolerance is developed to study compressible fluid flows containing shock waves in interaction with solid obstacles. To ensure adequate resolution near rigid bodies, the MR algorithm is combined with an immersed boundary method based on a direct-forcing approach in which the solid object is represented by a continuous solid-volume fraction. The resulting algorithm forms an efficient tool capable of solving linear and nonlinear waves on arbitrary geometries. Through a one-dimensional scalar wave equation, the accuracy of the MR computation is, as expected, seen to decrease in time when using a constant MR tolerance considering the accumulation of error. To overcome this problem, a variable tolerance formulation is proposed, which is assessed through a new quality criterion, to ensure a time-convergence solution for a suitable quality resolution. The newly developed algorithm coupled with high-resolution spatial and temporal approximations is successfully applied to shock-bluff body and shock-diffraction problems solving Euler and Navier-Stokes equations. Results show excellent agreement with the available numerical and experimental data, thereby demonstrating the efficiency and the performance of the proposed method.

Endogenous synchronous fluorescence spectroscopy (SFS) of basal cell carcinoma-initial study

NASA Astrophysics Data System (ADS)

Borisova, E.; Zhelyazkova, Al.; Keremedchiev, M.; Penkov, N.; Semyachkina-Glushkovskaya, O.; Avramov, L.

2016-01-01

The human skin is a complex, multilayered and inhomogeneous organ with spatially varying optical properties. Analysis of cutaneous fluorescence spectra could be a very complicated task; therefore researchers apply complex mathematical tools for data evaluation, or try to find some specific approaches, that would simplify the spectral analysis. Synchronous fluorescence spectroscopy (SFS) allows improving the spectral resolution, which could be useful for the biological tissue fluorescence characterization and could increase the tumour detection diagnostic accuracy.

Forest Classification Accuracy as Influenced by Multispectral Scanner Spatial Resolution. [Sam Houston National Forest, Texas

NASA Technical Reports Server (NTRS)

Nalepka, R. F. (Principal Investigator); Sadowski, F. E.; Sarno, J. E.

1976-01-01

The author has identified the following significant results. A supervised classification within two separate ground areas of the Sam Houston National Forest was carried out for two sq meters spatial resolution MSS data. Data were progressively coarsened to simulate five additional cases of spatial resolution ranging up to 64 sq meters. Similar processing and analysis of all spatial resolutions enabled evaluations of the effect of spatial resolution on classification accuracy for various levels of detail and the effects on area proportion estimation for very general forest features. For very coarse resolutions, a subset of spectral channels which simulated the proposed thematic mapper channels was used to study classification accuracy.

Infrared-temperature variability in a large agricultural field. [Dunnigan, California

NASA Technical Reports Server (NTRS)

Millard, J. P.; Goettelman, R. C.; Leroy, M. L. (Principal Investigator)

1980-01-01

The combined effect of water carved gullies, varying soil color, moisture state of the soil and crop, nonuniform phenology, and bare spots was measured for commercially grown barley planted on varying terrain. For all but the most rugged terrain, over 80% of the area within 4, 16, 65, and 259 ha cells was at temperatures within 3 C of the mean cell temperature. The result of using relatively small, 4 ha instantaneous field of views for remote sensing applications is that either the worst or the best of conditions is often observed. There appears to be no great advantage in utilizing a small instantaneous field of view instead of a large one for remote sensing of crop canopy temperatures. The two alternatives for design purposes are then either a very high spatial resolution, of the order of a meter or so, where the field is very accurately temperature mapped, or a low resolution, where the actual size seems to make little difference.

High resolution exposure modelling of heat and air pollution and the impact on mortality.

PubMed

Willers, Saskia M; Jonker, Marcel F; Klok, Lisette; Keuken, Menno P; Odink, Jennie; van den Elshout, Sef; Sabel, Clive E; Mackenbach, Johan P; Burdorf, Alex

2016-01-01

Elevated temperature and air pollution have been associated with increased mortality. Exposure to heat and air pollution, as well as the density of vulnerable groups varies within cities. The objective was to investigate the extent of neighbourhood differences in mortality risk due to heat and air pollution in a city with a temperate maritime climate. A case-crossover design was used to study associations between heat, air pollution and mortality. Different thermal indicators and air pollutants (PM10, NO2, O3) were reconstructed at high spatial resolution to improve exposure classification. Daily exposures were linked to individual mortality cases over a 15year period. Significant interaction between maximum air temperature (Tamax) and PM10 was observed. During "summer smog" days (Tamax>25°C and PM10>50μg/m(3)), the mortality risk at lag 2 was 7% higher compared to the reference (Tamax 15°C and PM10 15μg/m(3)). Persons above age 85 living alone were at highest risk. We found significant synergistic effects of high temperatures and air pollution on mortality. Single living elderly were the most vulnerable group. Due to spatial differences in temperature and air pollution, mortality risks varied substantially between neighbourhoods, with a difference up to 7%. Copyright © 2016 Elsevier Ltd. All rights reserved.

Biogeochemistry and Spatial Distribution of the Microbial-Mineral Interface Using I2LD-FTMS

NASA Astrophysics Data System (ADS)

Scott, J. R.; Kauffman, M. E.; Kauffman, M. E.; Tremblay, P. L.

2001-12-01

Previous studies indicate that biogeochemistry can vary within individual mineral specimens in contact with microorganisms. These same studies have shown that microcosms containing a mixture of minerals simulating a heterogeneous geologic matrix do not yield the same results as the naturally occurring rock. Therefore, it is of utmost importance to develop analytical tools that can provide spatially correlative biogeochemical data of the microbial-mineral interface within naturally occurring geologic matrices. Imaging internal laser desorption Fourier transform mass spectrometry (I2LD-FTMS) can provide elemental and molecular information of the microbial-mineral interface at a spatial resolution limited only by the optical diffraction limit of the final focusing lens (down to 2 μ m). Additionally, the I2LD-FTMS used in this study has exceptional reproducibility, which can provide successive mapping sequences for depth-profiling studies. Basalt core samples, taken from the Snake River Plain Aquifer in southeastern Idaho, were mapped prior to, and after, exposure to a bacterial culture. The bacteria-basalt interface spectra were collected using the I2LD-FTMS at the INEEL. Mass spectra were recorded over a mass-to-charge range of 30-2500 Da with an average peak resolution of 15,000 using 10 μ m spots. Two-dimensional maps were constructed depicting the spatial distribution of the minerals within the basalt as well as the spatial distribution of the bacteria on the basalt surface. This represents the first reported application of I2LD-FTMS in the field of biogeochemistry.

Spatial variations in shear stress in a 3-D bifurcation model at low Reynolds numbers.

PubMed

Rouhanizadeh, Mahsa; Lin, Tiantian C; Arcas, Diego; Hwang, Juliana; Hsiai, Tzung K

2005-10-01

Real-time wall shear stress is difficult to monitor precisely because it varies in space and time. Microelectromechanical systems sensor provides high spatial resolution to resolve variations in shear stress in a 3-D bifurcation model for small-scaled hemodynamics. At low Reynolds numbers from 1.34 to 6.7 skin friction coefficients (C(f)) varied circumferentially by a factor of two or more within the bifurcation. At a Reynolds number of 6.7, the C(f) value at the lateral wall of the bifurcation along the 270 degree plane was 7.1, corresponding to a shear stress value of 0.0061 dyn/cm(2). Along the 180 degree plane, C(f) was 13 or 0.0079 dyn/cm(2), and at the medial wall along the 90 degree plane, C(f) was 10.3 or 0.0091 dyn/cm(2). The experimental skin friction coefficients correlated with values derived from the Navier-Stokes solutions.

High Resolution Mesoscale Weather Data Improvement to Spatial Effects for Dose-Rate Contour Plot Predictions

DTIC Science & Technology

2007-03-01

time. This is a very powerful tool in determining fine spatial resolution , as boundary conditions are not only updated at every timestep, but the ...HIGH RESOLUTION MESOSCALE WEATHER DATA IMPROVEMENT TO SPATIAL EFFECTS FOR DOSE-RATE CONTOUR PLOT PREDICTIONS THESIS Christopher P...11 1 HIGH RESOLUTION MESOSCALE WEATHER DATA IMPROVEMENT TO SPATIAL EFFECTS FOR DOSE-RATE CONTOUR PLOT

External and middle ear sound pressure distribution and acoustic coupling to the tympanic membrane

PubMed Central

Bergevin, Christopher; Olson, Elizabeth S.

2014-01-01

Sound energy is conveyed to the inner ear by the diaphanous, cone-shaped tympanic membrane (TM). The TM moves in a complex manner and transmits sound signals to the inner ear with high fidelity, pressure gain, and a short delay. Miniaturized sensors allowing high spatial resolution in small spaces and sensitivity to high frequencies were used to explore how pressure drives the TM. Salient findings are: (1) A substantial pressure drop exists across the TM, and varies in frequency from ∼10 to 30 dB. It thus appears reasonable to approximate the drive to the TM as being defined solely by the pressure in the ear canal (EC) close to the TM. (2) Within the middle ear cavity (MEC), spatial variations in sound pressure could vary by more than 20 dB, and the MEC pressure at certain locations/frequencies was as large as in the EC. (3) Spatial variations in pressure along the TM surface on the EC-side were typically less than 5 dB up to 50 kHz. Larger surface variations were observed on the MEC-side. PMID:24606269

Sensitivity of Offshore Surface Fluxes and Sea Breezes to the Spatial Distribution of Sea-Surface Temperature

NASA Astrophysics Data System (ADS)

Lombardo, Kelly; Sinsky, Eric; Edson, James; Whitney, Michael M.; Jia, Yan

2018-03-01

A series of numerical sensitivity experiments is performed to quantify the impact of sea-surface temperature (SST) distribution on offshore surface fluxes and simulated sea-breeze dynamics. The SST simulations of two mid-latitude sea-breeze events over coastal New England are performed using a spatially-uniform SST, as well as spatially-varying SST datasets of 32- and 1-km horizontal resolutions. Offshore surface heat and buoyancy fluxes vary in response to the SST distribution. Local sea-breeze circulations are relatively insensitive, with minimal differences in vertical structure and propagation speed among the experiments. The largest thermal perturbations are confined to the lowest 10% of the sea-breeze column due to the relatively high stability of the mid-Atlantic marine atmospheric boundary layer (ABL) suppressing vertical mixing, resulting in the depth of the marine layer remaining unchanged. Minimal impacts on the column-averaged virtual potential temperature and sea-breeze depth translates to small changes in sea-breeze propagation speed. This indicates that the use of datasets with a fine-scale SST may not produce more accurate sea-breeze simulations in highly stable marine ABL regimes, though may prove more beneficial in less stable sub-tropical environments.

Impact of the spatial resolution of satellite remote sensing sensors in the quantification of total suspended sediment concentration: A case study in turbid waters of Northern Western Australia.

PubMed

Dorji, Passang; Fearns, Peter

2017-01-01

The impact of anthropogenic activities on coastal waters is a cause of concern because such activities add to the total suspended sediment (TSS) budget of the coastal waters, which have negative impacts on the coastal ecosystem. Satellite remote sensing provides a powerful tool in monitoring TSS concentration at high spatiotemporal resolution, but coastal managers should be mindful that the satellite-derived TSS concentrations are dependent on the satellite sensor's radiometric properties, atmospheric correction approaches, the spatial resolution and the limitations of specific TSS algorithms. In this study, we investigated the impact of different spatial resolutions of satellite sensor on the quantification of TSS concentration in coastal waters of northern Western Australia. We quantified the TSS product derived from MODerate resolution Imaging Spectroradiometer (MODIS)-Aqua, Landsat-8 Operational Land Image (OLI), and WorldView-2 (WV2) at native spatial resolutions of 250 m, 30 m and 2 m respectively and coarser spatial resolution (resampled up to 5 km) to quantify the impact of spatial resolution on the derived TSS product in different turbidity conditions. The results from the study show that in the waters of high turbidity and high spatial variability, the high spatial resolution WV2 sensor reported TSS concentration as high as 160 mg L-1 while the low spatial resolution MODIS-Aqua reported a maximum TSS concentration of 23.6 mg L-1. Degrading the spatial resolution of each satellite sensor for highly spatially variable turbid waters led to variability in the TSS concentrations of 114.46%, 304.68% and 38.2% for WV2, Landsat-8 OLI and MODIS-Aqua respectively. The implications of this work are particularly relevant in the situation of compliance monitoring where operations may be required to restrict TSS concentrations to a pre-defined limit.

Impact of the spatial resolution of satellite remote sensing sensors in the quantification of total suspended sediment concentration: A case study in turbid waters of Northern Western Australia

PubMed Central

Fearns, Peter

2017-01-01

The impact of anthropogenic activities on coastal waters is a cause of concern because such activities add to the total suspended sediment (TSS) budget of the coastal waters, which have negative impacts on the coastal ecosystem. Satellite remote sensing provides a powerful tool in monitoring TSS concentration at high spatiotemporal resolution, but coastal managers should be mindful that the satellite-derived TSS concentrations are dependent on the satellite sensor’s radiometric properties, atmospheric correction approaches, the spatial resolution and the limitations of specific TSS algorithms. In this study, we investigated the impact of different spatial resolutions of satellite sensor on the quantification of TSS concentration in coastal waters of northern Western Australia. We quantified the TSS product derived from MODerate resolution Imaging Spectroradiometer (MODIS)-Aqua, Landsat-8 Operational Land Image (OLI), and WorldView-2 (WV2) at native spatial resolutions of 250 m, 30 m and 2 m respectively and coarser spatial resolution (resampled up to 5 km) to quantify the impact of spatial resolution on the derived TSS product in different turbidity conditions. The results from the study show that in the waters of high turbidity and high spatial variability, the high spatial resolution WV2 sensor reported TSS concentration as high as 160 mg L-1 while the low spatial resolution MODIS-Aqua reported a maximum TSS concentration of 23.6 mg L-1. Degrading the spatial resolution of each satellite sensor for highly spatially variable turbid waters led to variability in the TSS concentrations of 114.46%, 304.68% and 38.2% for WV2, Landsat-8 OLI and MODIS-Aqua respectively. The implications of this work are particularly relevant in the situation of compliance monitoring where operations may be required to restrict TSS concentrations to a pre-defined limit. PMID:28380059

Attention Modifies Spatial Resolution According to Task Demands.

PubMed

Barbot, Antoine; Carrasco, Marisa

2017-03-01

How does visual attention affect spatial resolution? In texture-segmentation tasks, exogenous (involuntary) attention automatically increases resolution at the attended location, which improves performance where resolution is too low (at the periphery) but impairs performance where resolution is already too high (at central locations). Conversely, endogenous (voluntary) attention improves performance at all eccentricities, which suggests a more flexible mechanism. Here, using selective adaptation to spatial frequency, we investigated the mechanism by which endogenous attention benefits performance in resolution tasks. Participants detected a texture target that could appear at several eccentricities. Adapting to high or low spatial frequencies selectively affected performance in a manner consistent with changes in resolution. Moreover, adapting to high, but not low, frequencies mitigated the attentional benefit at central locations where resolution was too high; this shows that attention can improve performance by decreasing resolution. Altogether, our results indicate that endogenous attention benefits performance by modulating the contribution of high-frequency information in order to flexibly adjust spatial resolution according to task demands.

Attention Modifies Spatial Resolution According to Task Demands

PubMed Central

Barbot, Antoine; Carrasco, Marisa

2017-01-01

How does visual attention affect spatial resolution? In texture-segmentation tasks, exogenous (involuntary) attention automatically increases resolution at the attended location, which improves performance where resolution is too low (at the periphery) but impairs performance where resolution is already too high (at central locations). Conversely, endogenous (voluntary) attention improves performance at all eccentricities, which suggests a more flexible mechanism. Here, using selective adaptation to spatial frequency, we investigated the mechanism by which endogenous attention benefits performance in resolution tasks. Participants detected a texture target that could appear at several eccentricities. Adapting to high or low spatial frequencies selectively affected performance in a manner consistent with changes in resolution. Moreover, adapting to high, but not low, frequencies mitigated the attentional benefit at central locations where resolution was too high; this shows that attention can improve performance by decreasing resolution. Altogether, our results indicate that endogenous attention benefits performance by modulating the contribution of high-frequency information in order to flexibly adjust spatial resolution according to task demands. PMID:28118103

On the effects of scale for ecosystem services mapping

USGS Publications Warehouse

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J.; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability.

On the Effects of Scale for Ecosystem Services Mapping

PubMed Central

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J.; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability. PMID:25549256

Least-squares model-based halftoning

NASA Astrophysics Data System (ADS)

Pappas, Thrasyvoulos N.; Neuhoff, David L.

1992-08-01

A least-squares model-based approach to digital halftoning is proposed. It exploits both a printer model and a model for visual perception. It attempts to produce an 'optimal' halftoned reproduction, by minimizing the squared error between the response of the cascade of the printer and visual models to the binary image and the response of the visual model to the original gray-scale image. Conventional methods, such as clustered ordered dither, use the properties of the eye only implicitly, and resist printer distortions at the expense of spatial and gray-scale resolution. In previous work we showed that our printer model can be used to modify error diffusion to account for printer distortions. The modified error diffusion algorithm has better spatial and gray-scale resolution than conventional techniques, but produces some well known artifacts and asymmetries because it does not make use of an explicit eye model. Least-squares model-based halftoning uses explicit eye models and relies on printer models that predict distortions and exploit them to increase, rather than decrease, both spatial and gray-scale resolution. We have shown that the one-dimensional least-squares problem, in which each row or column of the image is halftoned independently, can be implemented with the Viterbi's algorithm. Unfortunately, no closed form solution can be found in two dimensions. The two-dimensional least squares solution is obtained by iterative techniques. Experiments show that least-squares model-based halftoning produces more gray levels and better spatial resolution than conventional techniques. We also show that the least- squares approach eliminates the problems associated with error diffusion. Model-based halftoning can be especially useful in transmission of high quality documents using high fidelity gray-scale image encoders. As we have shown, in such cases halftoning can be performed at the receiver, just before printing. Apart from coding efficiency, this approach permits the halftoner to be tuned to the individual printer, whose characteristics may vary considerably from those of other printers, for example, write-black vs. write-white laser printers.

A Next-Generation Hard X-Ray Nanoprobe Beamline for In Situ Studies of Energy Materials and Devices

NASA Astrophysics Data System (ADS)

Maser, Jörg; Lai, Barry; Buonassisi, Tonio; Cai, Zhonghou; Chen, Si; Finney, Lydia; Gleber, Sophie-Charlotte; Jacobsen, Chris; Preissner, Curt; Roehrig, Chris; Rose, Volker; Shu, Deming; Vine, David; Vogt, Stefan

2014-01-01

The Advanced Photon Source is developing a suite of new X-ray beamlines to study materials and devices across many length scales and under real conditions. One of the flagship beamlines of the APS upgrade is the In Situ Nanoprobe (ISN) beamline, which will provide in situ and operando characterization of advanced energy materials and devices under varying temperatures, gas ambients, and applied fields, at previously unavailable spatial resolution and throughput. Examples of materials systems include inorganic and organic photovoltaic systems, advanced battery systems, fuel cell components, nanoelectronic devices, advanced building materials and other scientifically and technologically relevant systems. To characterize these systems at very high spatial resolution and trace sensitivity, the ISN will use both nanofocusing mirrors and diffractive optics to achieve spots sizes as small as 20 nm. Nanofocusing mirrors in Kirkpatrick-Baez geometry will provide several orders of magnitude increase in photon flux at a spatial resolution of 50 nm. Diffractive optics such as zone plates and/or multilayer Laue lenses will provide a highest spatial resolution of 20 nm. Coherent diffraction methods will be used to study even small specimen features with sub-10 nm relevant length scale. A high-throughput data acquisition system will be employed to significantly increase operations efficiency and usability of the instrument. The ISN will provide full spectroscopy capabilities to study the chemical state of most materials in the periodic table, and enable X-ray fluorescence tomography. In situ electrical characterization will enable operando studies of energy and electronic devices such as photovoltaic systems and batteries. We describe the optical concept for the ISN beamline, the technical design, and the approach for enabling a broad variety of in situ studies. We furthermore discuss the application of hard X-ray microscopy to study defects in multi-crystalline solar cells, one of the lines of inquiries for which the ISN is being developed.

On the effects of scale for ecosystem services mapping.

PubMed

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability.

Stochastic Analysis and Probabilistic Downscaling of Soil Moisture

NASA Astrophysics Data System (ADS)

Deshon, J. P.; Niemann, J. D.; Green, T. R.; Jones, A. S.

2017-12-01

Soil moisture is a key variable for rainfall-runoff response estimation, ecological and biogeochemical flux estimation, and biodiversity characterization, each of which is useful for watershed condition assessment. These applications require not only accurate, fine-resolution soil-moisture estimates but also confidence limits on those estimates and soil-moisture patterns that exhibit realistic statistical properties (e.g., variance and spatial correlation structure). The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution (9-40 km) soil moisture from satellite remote sensing or land-surface models to produce fine-resolution (10-30 m) estimates. The model was designed to produce accurate deterministic soil-moisture estimates at multiple points, but the resulting patterns do not reproduce the variance or spatial correlation of observed soil-moisture patterns. The primary objective of this research is to generalize the EMT+VS model to produce a probability density function (pdf) for soil moisture at each fine-resolution location and time. Each pdf has a mean that is equal to the deterministic soil-moisture estimate, and the pdf can be used to quantify the uncertainty in the soil-moisture estimates and to simulate soil-moisture patterns. Different versions of the generalized model are hypothesized based on how uncertainty enters the model, whether the uncertainty is additive or multiplicative, and which distributions describe the uncertainty. These versions are then tested by application to four catchments with detailed soil-moisture observations (Tarrawarra, Satellite Station, Cache la Poudre, and Nerrigundah). The performance of the generalized models is evaluated by comparing the statistical properties of the simulated soil-moisture patterns to those of the observations and the deterministic EMT+VS model. The versions of the generalized EMT+VS model with normally distributed stochastic components produce soil-moisture patterns with more realistic statistical properties than the deterministic model. Additionally, the results suggest that the variance and spatial correlation of the stochastic soil-moisture variations do not vary consistently with the spatial-average soil moisture.

Effects of spatial resolution

NASA Technical Reports Server (NTRS)

Abrams, M.

1982-01-01

Studies of the effects of spatial resolution on extraction of geologic information are woefully lacking but spatial resolution effects can be examined as they influence two general categories: detection of spatial features per se; and the effects of IFOV on the definition of spectral signatures and on general mapping abilities.

Spatial, Temporal and Spectral Satellite Image Fusion via Sparse Representation

NASA Astrophysics Data System (ADS)

Song, Huihui

Remote sensing provides good measurements for monitoring and further analyzing the climate change, dynamics of ecosystem, and human activities in global or regional scales. Over the past two decades, the number of launched satellite sensors has been increasing with the development of aerospace technologies and the growing requirements on remote sensing data in a vast amount of application fields. However, a key technological challenge confronting these sensors is that they tradeoff between spatial resolution and other properties, including temporal resolution, spectral resolution, swath width, etc., due to the limitations of hardware technology and budget constraints. To increase the spatial resolution of data with other good properties, one possible cost-effective solution is to explore data integration methods that can fuse multi-resolution data from multiple sensors, thereby enhancing the application capabilities of available remote sensing data. In this thesis, we propose to fuse the spatial resolution with temporal resolution and spectral resolution, respectively, based on sparse representation theory. Taking the study case of Landsat ETM+ (with spatial resolution of 30m and temporal resolution of 16 days) and MODIS (with spatial resolution of 250m ~ 1km and daily temporal resolution) reflectance, we propose two spatial-temporal fusion methods to combine the fine spatial information of Landsat image and the daily temporal resolution of MODIS image. Motivated by that the images from these two sensors are comparable on corresponding bands, we propose to link their spatial information on available Landsat- MODIS image pair (captured on prior date) and then predict the Landsat image from the MODIS counterpart on prediction date. To well-learn the spatial details from the prior images, we use a redundant dictionary to extract the basic representation atoms for both Landsat and MODIS images based on sparse representation. Under the scenario of two prior Landsat-MODIS image pairs, we build the corresponding relationship between the difference images of MODIS and ETM+ by training a low- and high-resolution dictionary pair from the given prior image pairs. In the second scenario, i.e., only one Landsat- MODIS image pair being available, we directly correlate MODIS and ETM+ data through an image degradation model. Then, the fusion stage is achieved by super-resolving the MODIS image combining the high-pass modulation in a two-layer fusion framework. Remarkably, the proposed spatial-temporal fusion methods form a unified framework for blending remote sensing images with phenology change or land-cover-type change. Based on the proposed spatial-temporal fusion models, we propose to monitor the land use/land cover changes in Shenzhen, China. As a fast-growing city, Shenzhen faces the problem of detecting the rapid changes for both rational city planning and sustainable development. However, the cloudy and rainy weather in region Shenzhen located makes the capturing circle of high-quality satellite images longer than their normal revisit periods. Spatial-temporal fusion methods are capable to tackle this problem by improving the spatial resolution of images with coarse spatial resolution but frequent temporal coverage, thereby making the detection of rapid changes possible. On two Landsat-MODIS datasets with annual and monthly changes, respectively, we apply the proposed spatial-temporal fusion methods to the task of multiple change detection. Afterward, we propose a novel spatial and spectral fusion method for satellite multispectral and hyperspectral (or high-spectral) images based on dictionary-pair learning and sparse non-negative matrix factorization. By combining the spectral information from hyperspectral image, which is characterized by low spatial resolution but high spectral resolution and abbreviated as LSHS, and the spatial information from multispectral image, which is featured by high spatial resolution but low spectral resolution and abbreviated as HSLS, this method aims to generate the fused data with both high spatial and high spectral resolutions. Motivated by the observation that each hyperspectral pixel can be represented by a linear combination of a few endmembers, this method first extracts the spectral bases of LSHS and HSLS images by making full use of the rich spectral information in LSHS data. The spectral bases of these two categories data then formulate a dictionary-pair due to their correspondence in representing each pixel spectra of LSHS data and HSLS data, respectively. Subsequently, the LSHS image is spatially unmixed by representing the HSLS image with respect to the corresponding learned dictionary to derive its representation coefficients. Combining the spectral bases of LSHS data and the representation coefficients of HSLS data, we finally derive the fused data characterized by the spectral resolution of LSHS data and the spatial resolution of HSLS data.

Enhancing image contrast of carbon nanotubes on cellular background using helium ion microscope by varying helium ion fluence.

PubMed

Dykas, M M; Poddar, K; Yoong, S L; Viswanathan, V; Mathew, S; Patra, A; Saha, S; Pastorin, G; Venkatesan, T

2018-01-01

Carbon nanotubes (CNTs) have become an important nano entity for biomedical applications. Conventional methods of their imaging, often cannot be applied in biological samples due to an inadequate spatial resolution or poor contrast between the CNTs and the biological sample. Here we report a unique and effective detection method, which uses differences in conductivities of carbon nanotubes and HeLa cells. The technique involves the use of a helium ion microscope to image the sample with the surface charging artefacts created by the He + and neutralised by electron flood gun. This enables us to obtain a few nanometre resolution images of CNTs in HeLa Cells with high contrast, which was achieved by tailoring the He + fluence. Charging artefacts can be efficiently removed for conductive CNTs by a low amount of electrons, the fluence of which is not adequate to discharge the cell surface, resulting in high image contrast. Thus, this technique enables rapid detection of any conducting nano structures on insulating cellular background even in large fields of view and fine spatial resolution. The technique demonstrated has wider applications for researchers seeking enhanced contrast and high-resolution imaging of any conducting entity in a biological matrix - a commonly encountered issue of importance in drug delivery, tissue engineering and toxicological studies. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.

Plasma bubble monitoring by TEC map and 630 nm airglow image

NASA Astrophysics Data System (ADS)

Takahashi, H.; Wrasse, C. M.; Otsuka, Y.; Ivo, A.; Gomes, V.; Paulino, I.; Medeiros, A. F.; Denardini, C. M.; Sant'Anna, N.; Shiokawa, K.

2015-08-01

Equatorial ionosphere plasma bubbles over the South American continent were successfully observed by mapping the total electron content (TECMAP) using data provided by ground-based GNSS receiver networks. The TECMAP could cover almost all of the continent within ~4000 km distance in longitude and latitude, monitoring TEC variability continuously with a time resolution of 10 min. Simultaneous observations of OI 630 nm all-sky image at Cachoeira Paulista (22.7°S, 45.0°W) and Cariri (7.4°S, 36.5°W) were used to compare the bubble structures. The spatial resolution of the TECMAP varied from 50 km to 1000 km, depending on the density of the observation sites. On the other hand, optical imaging has a spatial resolution better than 15 km, depicting the fine structure of the bubbles but covering a limited area (~1600 km diameter). TECMAP has an advantage in its spatial coverage and the continuous monitoring (day and night) form. The initial phase of plasma depletion in the post-sunset equatorial ionization anomaly (PS-EIA) trough region, followed by development of plasma bubbles in the crest region, could be monitored in a progressive way over the magnetic equator. In December 2013 to January 2014, periodically spaced bubble structures were frequently observed. The longitudinal spacing between the bubbles was around 600-800 km depending on the day. The periodic form of plasma bubbles may suggest a seeding process related to the solar terminator passage in the ionosphere.

ALMA Maps of Dust and Warm Dense Gas Emission in the Starburst Galaxy IC 5179

NASA Astrophysics Data System (ADS)

Zhao, Yinghe; Lu, Nanyao; Díaz-Santos, Tanio; Xu, C. Kevin; Gao, Yu; Charmandaris, Vassilis; van der Werf, Paul; Zhang, Zhi-Yu; Cao, Chen

2017-08-01

We present our high-resolution (0.″15 × 0.″13, ˜34 pc) observations of the CO (6-5) line emission, which probes the warm and dense molecular gas, and the 434 μm dust continuum emission in the nuclear region of the starburst galaxy IC 5179, conducted with the Atacama Large Millimeter Array (ALMA). The CO (6-5) emission is spatially distributed in filamentary structures with many dense cores and shows a velocity field that is characteristic of a circumnuclear rotating gas disk, with 90% of the rotation speed arising within a radius of ≲150 pc. At the scale of our spatial resolution, the CO (6-5) and dust emission peaks do not always coincide, with their surface brightness ratio varying by a factor of ˜10. This result suggests that their excitation mechanisms are likely different, as further evidenced by the southwest to northeast spatial gradient of both CO-to-dust continuum ratio and Pa-α equivalent width. Within the nuclear region (radius ˜ 300 pc) and with a resolution of ˜34 pc, the CO line flux (dust flux density) detected in our ALMA observations is 180 ± 18 Jy km s-1 (71 ± 7 mJy), which accounts for 22% (2.4%) of the total value measured by Herschel. The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities, Inc.

The sea urchin Diadema africanum uses low resolution vision to find shelter and deter enemies.

PubMed

Kirwan, John D; Bok, Michael J; Smolka, Jochen; Foster, James J; Hernández, José Carlos; Nilsson, Dan-Eric

2018-05-08

Many sea urchins can detect light on their body surface and some species are reported to possess image-resolving vision. Here we measure the spatial resolution of vision in the long-spined sea urchin Diadema africanum , using two different visual responses: a taxis towards dark objects and an alarm response of spine-pointing towards looming stimuli. For the taxis response we used visual stimuli, which were isoluminant to the background, to discriminate spatial vision from phototaxis. Individual animals were placed in the centre of a cylindrical arena under bright down-welling light, with stimuli of varying angular width placed on the arena wall at pseudorandom directions from the centre. We tracked the direction of movement of individual animals in relation to the stimuli to determine whether the animals oriented towards the stimulus. We found that D. africanum responds by taxis towards isoluminant stimuli with a spatial resolution in the range 29°-69°. This corresponds to a theoretical acceptance angle of 38°-89°, assuming a contrast threshold of 10%. The visual acuity of the alarm response of D. africanum was tested by exposing animals to different sized dark looming and appearing stimuli on a monitor. We found that D. africanum displays a spine-pointing response to appearing black circles of 13°-25° angular width, corresponding to an acceptance angle of 60°-116°, assuming the same contrast threshold as above. © 2018. Published by The Company of Biologists Ltd.

Results of the spatial resolution simulation for multispectral data (resolution brochures)

NASA Technical Reports Server (NTRS)

1982-01-01

The variable information content of Earth Resource products at different levels of spatial resolution and in different spectral bands is addressed. A low-cost brochure that scientists and laymen could use to visualize the effects of increasing the spatial resolution of multispectral scanner images was produced.

Spatial patterns of native freshwater mussels in the Upper Mississippi River

USGS Publications Warehouse

Ries, Patricia R.; DeJager, Nathan R.; Zigler, Steven J.; Newton, Teresa

2016-01-01

Multiple physical and biological factors structure freshwater mussel communities in large rivers, and their distributions have been described as clumped or patchy. However, few surveys of mussel populations have been conducted over areas large enough and at resolutions fine enough to quantify spatial patterns in their distribution. We used global and local indicators of spatial autocorrelation (i.e., Moran’s I) to quantify spatial patterns of adult and juvenile (≤5 y of age) freshwater mussels across multiple scales based on survey data from 4 reaches (navigation pools 3, 5, 6, and 18) of the Upper Mississippi River, USA. Native mussel densities were sampled at a resolution of ∼300 m and across distances ranging from 21 to 37 km, making these some of the most spatially extensive surveys conducted in a large river. Patch density and the degree and scale of patchiness varied by river reach, age group, and the scale of analysis. In all 4 pools, some patches of adults overlapped patches of juveniles, suggesting spatial and temporal persistence of adequate habitat. In pools 3 and 5, patches of juveniles were found where there were few adults, suggesting recent emergence of positive structuring mechanisms. Last, in pools 3, 5, and 6, some patches of adults were found where there were few juveniles, suggesting that negative structuring mechanisms may have replaced positive ones, leading to a lack of localized recruitment. Our results suggest that: 1) the detection of patches of freshwater mussels requires a multiscaled approach, 2) insights into the spatial and temporal dynamics of structuring mechanisms can be gained by conducting independent analyses of adults and juveniles, and 3) maps of patch distributions can be used to guide restoration and management actions and identify areas where mussels are most likely to influence ecosystem function.

High-Resolution Synchrotron Radiation Imaging of Trace Metal Elemental Concentrations in Porites Coral

NASA Astrophysics Data System (ADS)

Cirino, M.; Dunbar, R. B.; Tangri, N.; Mehta, A.

2014-12-01

We investigated the use of synchrotron radiation for elemental imaging within the skeleton of a Porites coral from American Samoa to explore the fine-scale structure of strontium to calcium (Sr/Ca) variability. The use of a synchrotron for coral paleoclimate analysis is relatively new. The method provides a high resolution, two-dimensional elemental map of a coral surface. The aragonitic skeleton of Porites sp. colonies has been widely used for paleoclimate reconstruction as the oxygen isotope ratio (δ18O) signal varies with both sea surface temperature (SST) and sea surface salinity (SSS). Sr/Ca has been used in previous studies in conjunction with δ18O to deconvolve SST from SSS, as Sr/Ca in the coral skeleton varies with SST, but not SSS. However, recent studies suggest that in some cases Sr/Ca variability in coral does not reliably reflect changes in SST. We sought to address this puzzle by investigating Sr/Ca variability in Porites corals at a very fine spatial scale while also demonstrating the suitability of the synchrotron as a coral analysis tool. We also considered Sr/Ca variability as it pertains to the coral's structural elements. The Stanford Linear Accelerator Center synchrotron station generates collimated x-rays in the energy range of 4500-45000 eV with beam diameters as small as 20 μm. Synchrotron imaging allows faster and higher-resolution Sr/Ca analysis than does inductively coupled plasma mass spectrometry (ICP-MS). It also is capable of mapping spatial distributions of many elements, which aids in the development of a multiproxy approach to paleoclimate reconstruction. Imaging and analysis of the Porites coral using synchrotron radiation revealed an intricate sub-seasonal Sr/Ca signal, possibly correlating to a sub-monthly resolution. This signal, which seems unrelated to SST, dominates the annual signal.

Quantifying discharge uncertainty from remotely sensed precipitation data products in Puerto Rico

NASA Astrophysics Data System (ADS)

Weerasinghe, H.; Raoufi, R.; Yoon, Y.; Beighley, E., II; Alshawabkeh, A.

2014-12-01

Preterm birth is a serious health issue in the United States that contributes to over one-third of all infant deaths. Puerto Rico being one of the hot spots, preliminary research found that the high preterm birth rate can be associated with exposure to some contaminants in water used on daily basis. Puerto Rico has more than 200 contaminated sites including 16 active Superfund sites. Risk of exposure to contaminants is aggravated by unlined landfills lying over the karst regions, highly mobile and dynamic nature of the karst aquifers, and direct contact with surface water through sinkholes and springs. Much of the population in the island is getting water from natural springs or artesian wells that are connected with many of these potentially contaminated karst aquifers. Mobility of contaminants through surface water flows and reservoirs are largely known and are highly correlated with the variations in hydrologic events and conditions. In this study, we quantify the spatial and temporal distribution of Puerto Rico's surface water stores and fluxes to better understand potential impacts on the distribution of groundwater contamination. To quantify and characterize Puerto Rico's surface waters, hydrologic modeling, remote sensing and field measurements are combined. Streamflow measurements are available from 27 U.S. Geological Survey (USGS) gauging stations with drainage areas ranging from 2 to 510 km2. Hillslope River Routing (HRR) model is used to simulate hourly streamflow from watersheds larger than 1 km2 that discharge to ocean. HRR model simulates vertical water balance, lateral surface and subsurface runoff and river discharge. The model consists of 4418 sub-catchments with a mean model unit area (i.e., sub-catchment) of 1.8 km2. Using gauged streamflow measurements for validation, we first assess model results for simulated discharge using three precipitation products: TRMM-3B42 (3 hour temporal resolution, 0.25 degree spatial resolution); NWS stage-III radar rainfall (~ 5 min temporal resolution and 4 km spatial resolution); and gauge measurements from 37 rainfall stations for the period 2000-2012. We then explore methods for combining each product to improve overall model performance. Effects of varied spatial and temporal rainfall resolutions on simulated discharge are also investigated.

Testing a high resolution CO2 and CO emission inventory against atmospheric observations in Salt Lake City, Utah for policy applications

NASA Astrophysics Data System (ADS)

Mendoza, D. L.; Lin, J. C.; Mitchell, L.; Gurney, K. R.; Patarasuk, R.; Mallia, D. V.; Fasoli, B.; Bares, R.; Catharine, D.; O'Keeffe, D.; Song, Y.; Huang, J.; Horel, J.; Crosman, E.; Hoch, S.; Ehleringer, J. R.

2016-12-01

We address the need for robust highly-resolved emissions and trace gas concentration data required for planning purposes and policy development aimed at managing pollutant sources. Adverse health effects resulting from urban pollution exposure are the result of proximity to emission sources and atmospheric mixing, necessitating models with high spatial and temporal resolution. As urban emission sources co-emit carbon dioxide (CO2) and criteria air pollutants (CAPs), efforts to reduce specific pollutants would synergistically reduce others. We present a contemporary (2010-2015) emissions inventory and modeled CO2 and carbon monoxide (CO) concentrations for Salt Lake County, Utah. We compare emissions transported by a dispersion model against stationary measurement data and present a systematic quantification of uncertainties. The emissions inventory for CO2 is based on the Hestia emissions data inventory that resolves emissions at hourly, building and road-link resolutions, as well as on an hourly gridded scale. The emissions were scaled using annual Energy Information Administration (EIA) fuel consumption data. We derived a CO emissions inventory using methods similar to Hestia, downscaling total county emissions from the 2011 Environmental Protection Agency's (EPA) National Emissions Inventory (NEI). The gridded CO emissions were compared against the Hestia CO2 gridded data to characterize spatial similarities and differences between them. Correlations were calculated at multiple scales of aggregation. The Stochastic Time-Inverted Lagrangian Trasport (STILT) dispersion model was used to transport emissions and estimate pollutant concentrations at an hourly resolution. Modeled results were compared against stationary measurements in the Salt Lake County area. This comparison highlights spatial locations and hours of high variability and uncertainty. Sensitivity to biological fluxes as well as to specific economic sectors was tested by varying their contributions to modeled concentrations and calibrating their emissions.

Estimating Evaporative Fraction From Readily Obtainable Variables in Mangrove Forests of the Everglades, U.S.A.

NASA Technical Reports Server (NTRS)

Yagci, Ali Levent; Santanello, Joseph A.; Jones, John; Barr, Jordan

2017-01-01

A remote-sensing-based model to estimate evaporative fraction (EF) the ratio of latent heat (LE; energy equivalent of evapotranspiration -ET-) to total available energy from easily obtainable remotely-sensed and meteorological parameters is presented. This research specifically addresses the shortcomings of existing ET retrieval methods such as calibration requirements of extensive accurate in situ micro-meteorological and flux tower observations, or of a large set of coarse-resolution or model-derived input datasets. The trapezoid model is capable of generating spatially varying EF maps from standard products such as land surface temperature [T(sub s)] normalized difference vegetation index (NDVI)and daily maximum air temperature [T(sub a)]. The 2009 model results were validated at an eddy-covariance tower (Fluxnet ID: US-Skr) in the Everglades using T(sub s) and NDVI products from Landsat as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. Results indicate that the model accuracy is within the range of instrument uncertainty, and is dependent on the spatial resolution and selection of end-members (i.e. wet/dry edge). The most accurate results were achieved with the T(sub s) from Landsat relative to the T(sub s) from the MODIS flown on the Terra and Aqua platforms due to the fine spatial resolution of Landsat (30 m). The bias, mean absolute percentage error and root mean square percentage error were as low as 2.9% (3.0%), 9.8% (13.3%), and 12.1% (16.1%) for Landsat-based (MODIS-based) EF estimates, respectively. Overall, this methodology shows promise for bridging the gap between temporally limited ET estimates at Landsat scales and more complex and difficult to constrain global ET remote-sensing models.

Estimating evaporative fraction from readily obtainable variables in mangrove forests of the Everglades, U.S.A.

USGS Publications Warehouse

Yagci, Ali Levent; Santanello, Joseph A.; Jones, John W.; Barr, Jordan G.

2017-01-01

A remote-sensing-based model to estimate evaporative fraction (EF) – the ratio of latent heat (LE; energy equivalent of evapotranspiration –ET–) to total available energy – from easily obtainable remotely-sensed and meteorological parameters is presented. This research specifically addresses the shortcomings of existing ET retrieval methods such as calibration requirements of extensive accurate in situ micrometeorological and flux tower observations or of a large set of coarse-resolution or model-derived input datasets. The trapezoid model is capable of generating spatially varying EF maps from standard products such as land surface temperature (Ts) normalized difference vegetation index (NDVI) and daily maximum air temperature (Ta). The 2009 model results were validated at an eddy-covariance tower (Fluxnet ID: US-Skr) in the Everglades using Ts and NDVI products from Landsat as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. Results indicate that the model accuracy is within the range of instrument uncertainty, and is dependent on the spatial resolution and selection of end-members (i.e. wet/dry edge). The most accurate results were achieved with the Ts from Landsat relative to the Ts from the MODIS flown on the Terra and Aqua platforms due to the fine spatial resolution of Landsat (30 m). The bias, mean absolute percentage error and root mean square percentage error were as low as 2.9% (3.0%), 9.8% (13.3%), and 12.1% (16.1%) for Landsat-based (MODIS-based) EF estimates, respectively. Overall, this methodology shows promise for bridging the gap between temporally limited ET estimates at Landsat scales and more complex and difficult to constrain global ET remote-sensing models.

Longitudinal thermal heterogeneity in rivers and refugia for coldwater species: Effects of scale and climate change

USGS Publications Warehouse

Fullerton, A.H.; Torgersen, Christian E.; Lawer, J.J.; Steel, E. A.; Ebersole, J.L.; Lee, S.Y.

2018-01-01

Climate-change driven increases in water temperature pose challenges for aquatic organisms. Predictions of impacts typically do not account for fine-grained spatiotemporal thermal patterns in rivers. Patches of cooler water could serve as refuges for anadromous species like salmon that migrate during summer. We used high-resolution remotely sensed water temperature data to characterize summer thermal heterogeneity patterns for 11,308 km of second–seventh-order rivers throughout the Pacific Northwest and northern California (USA). We evaluated (1) water temperature patterns at different spatial resolutions, (2) the frequency, size, and spacing of cool thermal patches suitable for Pacific salmon (i.e., contiguous stretches ≥ 0.25 km, ≤ 15 °C and ≥ 2 °C, aooler than adjacent water), and (3) potential influences of climate change on availability of cool patches. Thermal heterogeneity was nonlinearly related to the spatial resolution of water temperature data, and heterogeneity at fine resolution (< 1 km) would have been difficult to quantify without spatially continuous data. Cool patches were generally > 2.7 and < 13.0 km long, and spacing among patches was generally > 5.7 and < 49.4 km. Thermal heterogeneity varied among rivers, some of which had long uninterrupted stretches of warm water ≥ 20 °C, and others had many smaller cool patches. Our models predicted little change in future thermal heterogeneity among rivers, but within-river patterns sometimes changed markedly compared to contemporary patterns. These results can inform long-term monitoring programs as well as near-term climate-adaptation strategies.

Efficient Probabilistic Forecasting for High-Resolution Models through Clustered-State Data Assimilation

NASA Astrophysics Data System (ADS)

Hamidi, A.; Grossberg, M.; Khanbilvardi, R.

2016-12-01

Flood response in an urban area is the product of interactions of spatially and temporally varying rainfall and infrastructures. In urban areas, however, the complex sub-surface networks of tunnels, waste and storm water drainage systems are often inaccessible, pose challenges for modeling and prediction of the drainage infrastructure performance. The increased availability of open data in cities is an emerging information asset for a better understanding of the dynamics of urban water drainage infrastructure. This includes crowd sourced data and community reporting. A well-known source of this type of data is the non-emergency hotline "311" which is available in many US cities, and may contain information pertaining to the performance of physical facilities, condition of the environment, or residents' experience, comfort and well-being. In this study, seven years of New York City 311 (NYC311) call during 2010-2016 is employed, as an alternative approach for identifying the areas of the city most prone to sewer back up flooding. These zones are compared with the hydrologic analysis of runoff flooding zones to provide a predictive model for the City. The proposed methodology is an example of urban system phenomenology using crowd sourced, open data. A novel algorithm for calculating the spatial distribution of flooding complaints across NYC's five boroughs is presented in this study. In this approach, the features that represent reporting bias are separated from those that relate to actual infrastructure system performance. The sewer backup results are assessed with the spatial distribution of runoff in NYC during 2010-2016. With advances in radar technologies, a high spatial-temporal resolution data set for precipitation is available for most of the United States that can be implemented in hydrologic analysis of dense urban environments. High resolution gridded Stage IV radar rainfall data along with the high resolution spatially distributed land cover data are employed to investigate the urban pluvial flooding. The monthly results of excess runoff are compared with the sewer backup in NYC to build a predictive model of flood zones according to the 311 phone calls.

Image sharpening for mixed spatial and spectral resolution satellite systems

NASA Technical Reports Server (NTRS)

Hallada, W. A.; Cox, S.

1983-01-01

Two methods of image sharpening (reconstruction) are compared. The first, a spatial filtering technique, extrapolates edge information from a high spatial resolution panchromatic band at 10 meters and adds it to the low spatial resolution narrow spectral bands. The second method, a color normalizing technique, is based on the ability to separate image hue and brightness components in spectral data. Using both techniques, multispectral images are sharpened from 30, 50, 70, and 90 meter resolutions. Error rates are calculated for the two methods and all sharpened resolutions. The results indicate that the color normalizing method is superior to the spatial filtering technique.

Porous media flux sensitivity to pore-scale geostatistics: A bottom-up approach

NASA Astrophysics Data System (ADS)

Di Palma, P. R.; Guyennon, N.; Heße, F.; Romano, E.

2017-04-01

Macroscopic properties of flow through porous media can be directly computed by solving the Navier-Stokes equations at the scales related to the actual flow processes, while considering the porous structures in an explicit way. The aim of this paper is to investigate the effects of the pore-scale spatial distribution on seepage velocity through numerical simulations of 3D fluid flow performed by the lattice Boltzmann method. To this end, we generate multiple random Gaussian fields whose spatial correlation follows an assigned semi-variogram function. The Exponential and Gaussian semi-variograms are chosen as extreme-cases of correlation for short distances and statistical properties of the resulting porous media (indicator field) are described using the Matèrn covariance model, with characteristic lengths of spatial autocorrelation (pore size) varying from 2% to 13% of the linear domain. To consider the sensitivity of the modeling results to the geostatistical representativeness of the domain as well as to the adopted resolution, porous media have been generated repetitively with re-initialized random seeds and three different resolutions have been tested for each resulting realization. The main difference among results is observed between the two adopted semi-variograms, indicating that the roughness (short distances autocorrelation) is the property mainly affecting the flux. However, computed seepage velocities show additionally a wide variability (about three orders of magnitude) for each semi-variogram model in relation to the assigned correlation length, corresponding to pore sizes. The spatial resolution affects more the results for short correlation lengths (i.e., small pore sizes), resulting in an increasing underestimation of the seepage velocity with the decreasing correlation length. On the other hand, results show an increasing uncertainty as the correlation length approaches the domain size.

Assessing the applicability of WRF optimal parameters under the different precipitation simulations in the Greater Beijing Area

NASA Astrophysics Data System (ADS)

Di, Zhenhua; Duan, Qingyun; Wang, Chen; Ye, Aizhong; Miao, Chiyuan; Gong, Wei

2018-03-01

Forecasting skills of the complex weather and climate models have been improved by tuning the sensitive parameters that exert the greatest impact on simulated results based on more effective optimization methods. However, whether the optimal parameter values are still work when the model simulation conditions vary, which is a scientific problem deserving of study. In this study, a highly-effective optimization method, adaptive surrogate model-based optimization (ASMO), was firstly used to tune nine sensitive parameters from four physical parameterization schemes of the Weather Research and Forecasting (WRF) model to obtain better summer precipitation forecasting over the Greater Beijing Area in China. Then, to assess the applicability of the optimal parameter values, simulation results from the WRF model with default and optimal parameter values were compared across precipitation events, boundary conditions, spatial scales, and physical processes in the Greater Beijing Area. The summer precipitation events from 6 years were used to calibrate and evaluate the optimal parameter values of WRF model. Three boundary data and two spatial resolutions were adopted to evaluate the superiority of the calibrated optimal parameters to default parameters under the WRF simulations with different boundary conditions and spatial resolutions, respectively. Physical interpretations of the optimal parameters indicating how to improve precipitation simulation results were also examined. All the results showed that the optimal parameters obtained by ASMO are superior to the default parameters for WRF simulations for predicting summer precipitation in the Greater Beijing Area because the optimal parameters are not constrained by specific precipitation events, boundary conditions, and spatial resolutions. The optimal values of the nine parameters were determined from 127 parameter samples using the ASMO method, which showed that the ASMO method is very highly-efficient for optimizing WRF model parameters.

Spatial Resolution Requirements for Accurate Identification of Drivers of Atrial Fibrillation

PubMed Central

Roney, Caroline H.; Cantwell, Chris D.; Bayer, Jason D.; Qureshi, Norman A.; Lim, Phang Boon; Tweedy, Jennifer H.; Kanagaratnam, Prapa; Vigmond, Edward J.; Ng, Fu Siong

2017-01-01

Background— Recent studies have demonstrated conflicting mechanisms underlying atrial fibrillation (AF), with the spatial resolution of data often cited as a potential reason for the disagreement. The purpose of this study was to investigate whether the variation in spatial resolution of mapping may lead to misinterpretation of the underlying mechanism in persistent AF. Methods and Results— Simulations of rotors and focal sources were performed to estimate the minimum number of recording points required to correctly identify the underlying AF mechanism. The effects of different data types (action potentials and unipolar or bipolar electrograms) and rotor stability on resolution requirements were investigated. We also determined the ability of clinically used endocardial catheters to identify AF mechanisms using clinically recorded and simulated data. The spatial resolution required for correct identification of rotors and focal sources is a linear function of spatial wavelength (the distance between wavefronts) of the arrhythmia. Rotor localization errors are larger for electrogram data than for action potential data. Stationary rotors are more reliably identified compared with meandering trajectories, for any given spatial resolution. All clinical high-resolution multipolar catheters are of sufficient resolution to accurately detect and track rotors when placed over the rotor core although the low-resolution basket catheter is prone to false detections and may incorrectly identify rotors that are not present. Conclusions— The spatial resolution of AF data can significantly affect the interpretation of the underlying AF mechanism. Therefore, the interpretation of human AF data must be taken in the context of the spatial resolution of the recordings. PMID:28500175

High-Resolution Mesoscale Simulations of the 6-7 May 2000 Missouri Flash Flood: Impact of Model Initialization and Land Surface Treatment

NASA Technical Reports Server (NTRS)

Baker, R. David; Wang, Yansen; Tao, Wei-Kuo; Wetzel, Peter; Belcher, Larry R.

2004-01-01

High-resolution mesoscale model simulations of the 6-7 May 2000 Missouri flash flood event were performed to test the impact of model initialization and land surface treatment on timing, intensity, and location of extreme precipitation. In this flash flood event, a mesoscale convective system (MCS) produced over 340 mm of rain in roughly 9 hours in some locations. Two different types of model initialization were employed: 1) NCEP global reanalysis with 2.5-degree grid spacing and 12-hour temporal resolution, and 2) Eta reanalysis with 40- km grid spacing and $hour temporal resolution. In addition, two different land surface treatments were considered. A simple land scheme. (SLAB) keeps soil moisture fixed at initial values throughout the simulation, while a more sophisticated land model (PLACE) allows for r interactive feedback. Simulations with high-resolution Eta model initialization show considerable improvement in the intensity of precipitation due to the presence in the initialization of a residual mesoscale convective vortex (hlCV) from a previous MCS. Simulations with the PLACE land model show improved location of heavy precipitation. Since soil moisture can vary over time in the PLACE model, surface energy fluxes exhibit strong spatial gradients. These surface energy flux gradients help produce a strong low-level jet (LLJ) in the correct location. The LLJ then interacts with the cold outflow boundary of the MCS to produce new convective cells. The simulation with both high-resolution model initialization and time-varying soil moisture test reproduces the intensity and location of observed rainfall.

Validation of a Fast-Response Urban Micrometeorological Model to Assess the Performance of Urban Heat Island Mitigation Strategies

NASA Astrophysics Data System (ADS)

Nadeau, D.; Girard, P.; Overby, M.; Pardyjak, E.; Stoll, R., II; Willemsen, P.; Bailey, B.; Parlange, M. B.

2015-12-01

Urban heat islands (UHI) are a real threat in many cities worldwide and mitigation measures have become a central component of urban planning strategies. Even within a city, causes of UHI vary from one neighborhood to another, mostly due the spatial variability in surface thermal properties, building geometry, anthropogenic heat flux releases and vegetation cover. As a result, the performance of UHI mitigation measures also varies in space. Hence, there is a need to develop a tool to quantify the efficiency of UHI mitigation measures at the neighborhood scale. The objective of this ongoing study is to validate the fast-response micrometeorological model QUIC EnvSim (QES). This model can provide all information required for UHI studies with a fine spatial resolution (up to 0.5m) and short computation time. QES combines QUIC, a CFD-based wind solver and dispersion model, and EnvSim, composed of a radiation model, a land-surface model and a turbulent transport model. Here, high-resolution (1 m) simulations are run over a subset of the École Polytechnique Fédérale de Lausanne (EPFL) campus including complex buildings, various surfaces properties and vegetation. For nearly five months in 2006-07, a dense network of meteorological observations (92 weather stations over 0.1 km2) was deployed over the campus and these unique data are used here as a validation dataset. We present validation results for different test cases (e.g., sunny vs cloudy days, different incoming wind speeds and directions) and explore the effect of a few UHI mitigation strategies on the spatial distribution of near-surface air temperatures. Preliminary results suggest that QES may be a valuable tool in decision-making regarding adaptation of urban planning to UHI.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kirtley, John R., E-mail: jkirtley@stanford.edu; Rosenberg, Aaron J.; Palmstrom, Johanna C.

Superconducting QUantum Interference Device (SQUID) microscopy has excellent magnetic field sensitivity, but suffers from modest spatial resolution when compared with other scanning probes. This spatial resolution is determined by both the size of the field sensitive area and the spacing between this area and the sample surface. In this paper we describe scanning SQUID susceptometers that achieve sub-micron spatial resolution while retaining a white noise floor flux sensitivity of ≈2μΦ{sub 0}/Hz{sup 1/2}. This high spatial resolution is accomplished by deep sub-micron feature sizes, well shielded pickup loops fabricated using a planarized process, and a deep etch step that minimizes themore » spacing between the sample surface and the SQUID pickup loop. We describe the design, modeling, fabrication, and testing of these sensors. Although sub-micron spatial resolution has been achieved previously in scanning SQUID sensors, our sensors not only achieve high spatial resolution but also have integrated modulation coils for flux feedback, integrated field coils for susceptibility measurements, and batch processing. They are therefore a generally applicable tool for imaging sample magnetization, currents, and susceptibilities with higher spatial resolution than previous susceptometers.« less

Chromatic and Achromatic Spatial Resolution of Local Field Potentials in Awake Cortex

PubMed Central

Jansen, Michael; Li, Xiaobing; Lashgari, Reza; Kremkow, Jens; Bereshpolova, Yulia; Swadlow, Harvey A.; Zaidi, Qasim; Alonso, Jose-Manuel

2015-01-01

Local field potentials (LFPs) have become an important measure of neuronal population activity in the brain and could provide robust signals to guide the implant of visual cortical prosthesis in the future. However, it remains unclear whether LFPs can detect weak cortical responses (e.g., cortical responses to equiluminant color) and whether they have enough visual spatial resolution to distinguish different chromatic and achromatic stimulus patterns. By recording from awake behaving macaques in primary visual cortex, here we demonstrate that LFPs respond robustly to pure chromatic stimuli and exhibit ∼2.5 times lower spatial resolution for chromatic than achromatic stimulus patterns, a value that resembles the ratio of achromatic/chromatic resolution measured with psychophysical experiments in humans. We also show that, although the spatial resolution of LFP decays with visual eccentricity as is also the case for single neurons, LFPs have higher spatial resolution and show weaker response suppression to low spatial frequencies than spiking multiunit activity. These results indicate that LFP recordings are an excellent approach to measure spatial resolution from local populations of neurons in visual cortex including those responsive to color. PMID:25416722

Calculation of the spatial resolution in two-photon absorption spectroscopy applied to plasma diagnosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garcia-Lechuga, M.; Laser Processing Group, Instituto de Óptica “Daza de Valdés,” CSIC, 28006-Madrid; Fuentes, L. M.

2014-10-07

We report a detailed characterization of the spatial resolution provided by two-photon absorption spectroscopy suited for plasma diagnosis via the 1S-2S transition of atomic hydrogen for optogalvanic detection and laser induced fluorescence (LIF). A precise knowledge of the spatial resolution is crucial for a correct interpretation of measurements, if the plasma parameters to be analysed undergo strong spatial variations. The present study is based on a novel approach which provides a reliable and realistic determination of the spatial resolution. Measured irradiance distribution of laser beam waists in the overlap volume, provided by a high resolution UV camera, are employed tomore » resolve coupled rate equations accounting for two-photon excitation, fluorescence decay and ionization. The resulting three-dimensional yield distributions reveal in detail the spatial resolution for optogalvanic and LIF detection and related saturation due to depletion. Two-photon absorption profiles broader than the Fourier transform-limited laser bandwidth are also incorporated in the calculations. The approach allows an accurate analysis of the spatial resolution present in recent and future measurements.« less

[An effective method for improving the imaging spatial resolution of terahertz time domain spectroscopy system].

PubMed

Zhang, Zeng-yan; Ji, Te; Zhu, Zhi-yong; Zhao, Hong-wei; Chen, Min; Xiao, Ti-qiao; Guo, Zhi

2015-01-01

Terahertz radiation is an electromagnetic radiation in the range between millimeter waves and far infrared. Due to its low energy and non-ionizing characters, THz pulse imaging emerges as a novel tool in many fields, such as material, chemical, biological medicine, and food safety. Limited spatial resolution is a significant restricting factor of terahertz imaging technology. Near field imaging method was proposed to improve the spatial resolution of terahertz system. Submillimeter scale's spauial resolution can be achieved if the income source size is smaller than the wawelength of the incoming source and the source is very close to the sample. But many changes were needed to the traditional terahertz time domain spectroscopy system, and it's very complex to analyze sample's physical parameters through the terahertz signal. A method of inserting a pinhole upstream to the sample was first proposed in this article to improve the spatial resolution of traditional terahertz time domain spectroscopy system. The measured spatial resolution of terahertz time domain spectroscopy system by knife edge method can achieve spatial resolution curves. The moving stage distance between 10 % and 90 Yo of the maximum signals respectively was defined as the, spatial resolution of the system. Imaging spatial resolution of traditional terahertz time domain spectroscopy system was improved dramatically after inserted a pinhole with diameter 0. 5 mm, 2 mm upstream to the sample. Experimental results show that the spatial resolution has been improved from 1. 276 mm to 0. 774 mm, with the increment about 39 %. Though this simple method, the spatial resolution of traditional terahertz time domain spectroscopy system was increased from millimeter scale to submillimeter scale. A pinhole with diameter 1 mm on a polyethylene plate was taken as sample, to terahertz imaging study. The traditional terahertz time domain spectroscopy system and pinhole inserted terahertz time domain spectroscopy system were applied in the imaging experiment respectively. The relative THz-power loss imaging of samples were use in this article. This method generally delivers the best signal to noise ratio in loss images, dispersion effects are cancelled. Terahertz imaging results show that the sample's boundary was more distinct after inserting the pinhole in front of, sample. The results also conform that inserting pinhole in front of sample can improve the imaging spatial resolution effectively. The theoretical analyses of the method which improve the spatial resolution by inserting a pinhole in front of sample were given in this article. The analyses also indicate that the smaller the pinhole size, the longer spatial coherence length of the system, the better spatial resolution of the system. At the same time the terahertz signal will be reduced accordingly. All the experimental results and theoretical analyses indicate that the method of inserting a pinhole in front of sample can improve the spatial resolution of traditional terahertz time domain spectroscopy system effectively, and it will further expand the application of terahertz imaging technology.

Synthetic generation of spatially high resolution extreme rainfall in Japan using Monte Carlo simulation with AMeDAS analyzed rainfall data sets

NASA Astrophysics Data System (ADS)

Haruki, W.; Iseri, Y.; Takegawa, S.; Sasaki, O.; Yoshikawa, S.; Kanae, S.

2016-12-01

Natural disasters caused by heavy rainfall occur every year in Japan. Effective countermeasures against such events are important. In 2015, a catastrophic flood occurred in Kinu river basin, which locates in the northern part of Kanto region. The remarkable feature of this flood event was not only in the intensity of rainfall but also in the spatial characteristics of heavy rainfall area. The flood was caused by continuous overlapping of heavy rainfall area over the Kinu river basin, suggesting consideration of spatial extent is quite important to assess impacts of heavy rainfall events. However, the spatial extent of heavy rainfall events cannot be properly measured through rainfall measurement by rain gauges at observation points. On the other hand, rainfall measurements by radar observations provide spatially and temporarily high resolution rainfall data which would be useful to catch the characteristics of heavy rainfall events. For long term effective countermeasure, extreme heavy rainfall scenario considering rainfall area and distribution is required. In this study, a new method for generating extreme heavy rainfall events using Monte Carlo Simulation has been developed in order to produce extreme heavy rainfall scenario. This study used AMeDAS analyzed precipitation data which is high resolution grid precipitation data made by Japan Meteorological Agency. Depth area duration (DAD) analysis has been conducted to extract extreme rainfall events in the past, considering time and spatial scale. In the Monte Carlo Simulation, extreme rainfall event is generated based on events extracted by DAD analysis. Extreme heavy rainfall events are generated in specific region in Japan and the types of generated extreme heavy rainfall events can be changed by varying the parameter. For application of this method, we focused on Kanto region in Japan. As a result, 3000 years rainfall data are generated. 100 -year probable rainfall and return period of flood in Kinu River Basin (2015) are obtained using generated data. We compared 100-year probable rainfall calculated by this method with other traditional method. New developed method enables us to generate extreme rainfall events considering time and spatial scale and produce extreme rainfall scenario.

Analysis of Helimak Plasma Using Movies of Density Contours

NASA Astrophysics Data System (ADS)

Williams, Chad; Gentle, Kenneth; Li, Bo

2013-10-01

Using an array of Langmuir probes we have created two-dimensional contour plot movies showing the arrangement, convection, and time sequence of plasma structures inside of the Texas Helimak, which approximates aspects of the tokamak SOL. These structures are seen to vary with time, magnetic field line pitch, and applied bias voltage. The probes are distributed in two sets of 48 probes arranged in a grid with two centimeter spacing, providing good spatial resolution of these structures. We find that, for negative biases, the plasma moves away from the biased plate in agreement with the simulations. For positive biases, the plasma is found close to the bias plate. Positive biases are seen to induce more radial convection than the negatively biased case. While all structures vary with time, those at lower magnetic field line pitch are seen to vary most dramatically.

Decorrelation Times of Photospheric Fields and Flows

NASA Technical Reports Server (NTRS)

Welsch, B. T.; Kusano, K.; Yamamoto, T. T.; Muglach, K.

2012-01-01

We use autocorrelation to investigate evolution in flow fields inferred by applying Fourier Local Correlation Tracking (FLCT) to a sequence of high-resolution (0.3 "), high-cadence (approx = 2 min) line-of-sight magnetograms of NOAA active region (AR) 10930 recorded by the Narrowband Filter Imager (NFI) of the Solar Optical Telescope (SOT) aboard the Hinode satellite over 12 - 13 December 2006. To baseline the timescales of flow evolution, we also autocorrelated the magnetograms, at several spatial binnings, to characterize the lifetimes of active region magnetic structures versus spatial scale. Autocorrelation of flow maps can be used to optimize tracking parameters, to understand tracking algorithms f susceptibility to noise, and to estimate flow lifetimes. Tracking parameters varied include: time interval Delta t between magnetogram pairs tracked, spatial binning applied to the magnetograms, and windowing parameter sigma used in FLCT. Flow structures vary over a range of spatial and temporal scales (including unresolved scales), so tracked flows represent a local average of the flow over a particular range of space and time. We define flow lifetime to be the flow decorrelation time, tau . For Delta t > tau, tracking results represent the average velocity over one or more flow lifetimes. We analyze lifetimes of flow components, divergences, and curls as functions of magnetic field strength and spatial scale. We find a significant trend of increasing lifetimes of flow components, divergences, and curls with field strength, consistent with Lorentz forces partially governing flows in the active photosphere, as well as strong trends of increasing flow lifetime and decreasing magnitudes with increases in both spatial scale and Delta t.

Terahertz imaging with sub-wavelength resolution by femtosecond laser filament in air

PubMed Central

Zhao, Jiayu; Chu, Wei; Guo, Lanjun; Wang, Zhi; Yang, Jing; Liu, Weiwei; Cheng, Ya; Xu, Zhizhan

2014-01-01

Terahertz (THz) imaging provides cutting edge technique in biology, medical sciences and non-destructive evaluation. However, due to the long wavelength of the THz wave, the obtained resolution of THz imaging is normally a few hundred microns and is much lower than that of the traditional optical imaging. We introduce a sub-wavelength resolution THz imaging technique which uses the THz radiation generated by a femtosecond laser filament in air as the probe. This method is based on the fact that the femtosecond laser filament forms a waveguide for the THz wave in air. The diameter of the THz beam, which propagates inside the filament, varies from 20 μm to 50 μm, which is significantly smaller than the wavelength of the THz wave. Using this highly spatially confined THz beam as the probe, THz imaging with resolution as high as 20 μm (~λ/38 at 0.4 THz) can be realized. PMID:24457525

Aplanatic and quasi-aplanatic diffraction gratings

DOEpatents

Hettrick, M.C.

1987-09-14

A reflection diffraction grating having a series of transverse minute grooves of progressively varying spacing along a concave surface enables use of such gratings for x-ray or longer wavelength imaging of objects. The variable groove spacing establishes aplanatism or substantially uniform magnetification across the optical aperture. The grating may be sued, for example, in x-ray microscopes or telescopes of the imaging type and in x-ray microprobed. Increased spatial resolution and field of view may be realized in x-ray imaging. 5 figs.

Handling Different Spatial Resolutions in Image Fusion by Multivariate Curve Resolution-Alternating Least Squares for Incomplete Image Multisets.

PubMed

Piqueras, Sara; Bedia, Carmen; Beleites, Claudia; Krafft, Christoph; Popp, Jürgen; Maeder, Marcel; Tauler, Romà; de Juan, Anna

2018-06-05

Data fusion of different imaging techniques allows a comprehensive description of chemical and biological systems. Yet, joining images acquired with different spectroscopic platforms is complex because of the different sample orientation and image spatial resolution. Whereas matching sample orientation is often solved by performing suitable affine transformations of rotation, translation, and scaling among images, the main difficulty in image fusion is preserving the spatial detail of the highest spatial resolution image during multitechnique image analysis. In this work, a special variant of the unmixing algorithm Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) for incomplete multisets is proposed to provide a solution for this kind of problem. This algorithm allows analyzing simultaneously images collected with different spectroscopic platforms without losing spatial resolution and ensuring spatial coherence among the images treated. The incomplete multiset structure concatenates images of the two platforms at the lowest spatial resolution with the image acquired with the highest spatial resolution. As a result, the constituents of the sample analyzed are defined by a single set of distribution maps, common to all platforms used and with the highest spatial resolution, and their related extended spectral signatures, covering the signals provided by each of the fused techniques. We demonstrate the potential of the new variant of MCR-ALS for multitechnique analysis on three case studies: (i) a model example of MIR and Raman images of pharmaceutical mixture, (ii) FT-IR and Raman images of palatine tonsil tissue, and (iii) mass spectrometry and Raman images of bean tissue.

Assessing the Resolution Adaptability of the Zhang-McFarlane Cumulus Parameterization With Spatial and Temporal Averaging: RESOLUTION ADAPTABILITY OF ZM SCHEME

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yun, Yuxing; Fan, Jiwen; Xiao, Heng

Realistic modeling of cumulus convection at fine model resolutions (a few to a few tens of km) is problematic since it requires the cumulus scheme to adapt to higher resolution than they were originally designed for (~100 km). To solve this problem, we implement the spatial averaging method proposed in Xiao et al. (2015) and also propose a temporal averaging method for the large-scale convective available potential energy (CAPE) tendency in the Zhang-McFarlane (ZM) cumulus parameterization. The resolution adaptability of the original ZM scheme, the scheme with spatial averaging, and the scheme with both spatial and temporal averaging at 4-32more » km resolution is assessed using the Weather Research and Forecasting (WRF) model, by comparing with Cloud Resolving Model (CRM) results. We find that the original ZM scheme has very poor resolution adaptability, with sub-grid convective transport and precipitation increasing significantly as the resolution increases. The spatial averaging method improves the resolution adaptability of the ZM scheme and better conserves the total transport of moist static energy and total precipitation. With the temporal averaging method, the resolution adaptability of the scheme is further improved, with sub-grid convective precipitation becoming smaller than resolved precipitation for resolution higher than 8 km, which is consistent with the results from the CRM simulation. Both the spatial distribution and time series of precipitation are improved with the spatial and temporal averaging methods. The results may be helpful for developing resolution adaptability for other cumulus parameterizations that are based on quasi-equilibrium assumption.« less

Computational Models of Protein Kinematics and Dynamics: Beyond Simulation

PubMed Central

Gipson, Bryant; Hsu, David; Kavraki, Lydia E.; Latombe, Jean-Claude

2016-01-01

Physics-based simulation represents a powerful method for investigating the time-varying behavior of dynamic protein systems at high spatial and temporal resolution. Such simulations, however, can be prohibitively difficult or lengthy for large proteins or when probing the lower-resolution, long-timescale behaviors of proteins generally. Importantly, not all questions about a protein system require full space and time resolution to produce an informative answer. For instance, by avoiding the simulation of uncorrelated, high-frequency atomic movements, a larger, domain-level picture of protein dynamics can be revealed. The purpose of this review is to highlight the growing body of complementary work that goes beyond simulation. In particular, this review focuses on methods that address kinematics and dynamics, as well as those that address larger organizational questions and can quickly yield useful information about the long-timescale behavior of a protein. PMID:22524225

Achieving high spatial resolution using a microchannel plate detector with an economic and scalable approach

NASA Astrophysics Data System (ADS)

Wiggins, B. B.; deSouza, Z. O.; Vadas, J.; Alexander, A.; Hudan, S.; deSouza, R. T.

2017-11-01

A second generation position-sensitive microchannel plate detector using the induced signal approach has been realized. This detector is presently capable of measuring the incident position of electrons, photons, or ions. To assess the spatial resolution, the masked detector was illuminated by electrons. The initial, measured spatial resolution of 276 μm FWHM was improved by requiring a minimum signal amplitude on the anode and by employing digital signal processing techniques. The resulting measured spatial resolution of 119 μm FWHM corresponds to an intrinsic resolution of 98 μm FWHM when the effect of the finite slit width is de-convoluted. This measurement is a substantial improvement from the last reported spatial resolution of 466 μm FWHM using the induced signal approach. To understand the factors that limit the measured resolution, the performance of the detector is simulated.

Statistical model based iterative reconstruction (MBIR) in clinical CT systems. Part II. Experimental assessment of spatial resolution performance.

PubMed

Li, Ke; Garrett, John; Ge, Yongshuai; Chen, Guang-Hong

2014-07-01

Statistical model based iterative reconstruction (MBIR) methods have been introduced to clinical CT systems and are being used in some clinical diagnostic applications. The purpose of this paper is to experimentally assess the unique spatial resolution characteristics of this nonlinear reconstruction method and identify its potential impact on the detectabilities and the associated radiation dose levels for specific imaging tasks. The thoracic section of a pediatric phantom was repeatedly scanned 50 or 100 times using a 64-slice clinical CT scanner at four different dose levels [CTDIvol =4, 8, 12, 16 (mGy)]. Both filtered backprojection (FBP) and MBIR (Veo(®), GE Healthcare, Waukesha, WI) were used for image reconstruction and results were compared with one another. Eight test objects in the phantom with contrast levels ranging from 13 to 1710 HU were used to assess spatial resolution. The axial spatial resolution was quantified with the point spread function (PSF), while the z resolution was quantified with the slice sensitivity profile. Both were measured locally on the test objects and in the image domain. The dependence of spatial resolution on contrast and dose levels was studied. The study also features a systematic investigation of the potential trade-off between spatial resolution and locally defined noise and their joint impact on the overall image quality, which was quantified by the image domain-based channelized Hotelling observer (CHO) detectability index d'. (1) The axial spatial resolution of MBIR depends on both radiation dose level and image contrast level, whereas it is supposedly independent of these two factors in FBP. The axial spatial resolution of MBIR always improved with an increasing radiation dose level and/or contrast level. (2) The axial spatial resolution of MBIR became equivalent to that of FBP at some transitional contrast level, above which MBIR demonstrated superior spatial resolution than FBP (and vice versa); the value of this transitional contrast highly depended on the dose level. (3) The PSFs of MBIR could be approximated as Gaussian functions with reasonably good accuracy. (4) Thez resolution of MBIR showed similar contrast and dose dependence. (5) Noise standard deviation assessed on the edges of objects demonstrated a trade-off with spatial resolution in MBIR. (5) When both spatial resolution and image noise were considered using the CHO analysis, MBIR led to significant improvement in the overall CT image quality for both high and low contrast detection tasks at both standard and low dose levels. Due to the intrinsic nonlinearity of the MBIR method, many well-known CT spatial resolution and noise properties have been modified. In particular, dose dependence and contrast dependence have been introduced to the spatial resolution of CT images by MBIR. The method has also introduced some novel noise-resolution trade-off not seen in traditional CT images. While the benefits of MBIR regarding the overall image quality, as demonstrated in this work, are significant, the optimal use of this method in clinical practice demands a thorough understanding of its unique physical characteristics.

Characterizing spatial and temporal variability in methane gas-flux dynamics of subtropical wetlands in the Big Cypress National Preserve, Florida

NASA Astrophysics Data System (ADS)

Sirianni, M.; Comas, X.; Shoemaker, B.

2017-12-01

Wetland methane emissions are highly variable both in space and time, and are controlled by changes in certain biogeochemical controls (i.e. organic matter availability; redox potential) and/or other environmental factors (i.e. soil temperature; water level). Consequently, hot spots (areas with disproportionally high emissions) may develop where biogeochemical and environmental conditions are especially conducive for enhancing certain microbial processes such as methanogenesis. The Big Cypress National Preserve is a collection of subtropical wetlands in southwestern Florida, including extensive forested (cypress, pine, hardwood) and sawgrass ecosystems that dry and flood annually in response to rainfall. In addition to rainfall, hydroperiod, fire regime, elevation above mean sea level, dominant vegetation type and underlying geological controls contribute to the development and evolution of organic and calcitic soils found throughout the Preserve. Currently, the U.S. Geological Survey employs eddy covariance methods within the Preserve to quantify carbon and methane exchanges over several spatially extensive vegetation communities. While eddy covariance towers are a convenient tool for measuring gas exchanges at the ecosystem scale, their spatially extensive footprint (hundreds of meters) may mask smaller scale spatial variabilities that may be conducive to the development of hot spots. Similarly, temporal resolution (i.e. sampling effort) at scales smaller that the eddy covariance measurement footprint is important since low resolution data may overlook rapid emission events and the temporal variability of discrete hot spots. In this work, we intend to estimate small-scale contributions of organic and calcitic soils to gas exchanges measured by the eddy covariance towers using a unique combination of ground penetrating radar (GPR), capacitance probes, gas traps, and time-lapse photography. By using an array of methods that vary in spatio-temporal resolution, we hope to better understand the uncertainties associated with measuring wetland methane fluxes across different spatial and temporal scales. Our results have implications for characterizing and refining methane flux estimates in subtropical peat soils that could be used for climate models.

Theoretical evaluation of accuracy in position and size of brain activity obtained by near-infrared topography

NASA Astrophysics Data System (ADS)

Kawaguchi, Hiroshi; Hayashi, Toshiyuki; Kato, Toshinori; Okada, Eiji

2004-06-01

Near-infrared (NIR) topography can obtain a topographical distribution of the activated region in the brain cortex. Near-infrared light is strongly scattered in the head, and the volume of tissue sampled by a source-detector pair on the head surface is broadly distributed in the brain. This scattering effect results in poor resolution and contrast in the topographic image of the brain activity. In this study, a one-dimensional distribution of absorption change in a head model is calculated by mapping and reconstruction methods to evaluate the effect of the image reconstruction algorithm and the interval of measurement points for topographic imaging on the accuracy of the topographic image. The light propagation in the head model is predicted by Monte Carlo simulation to obtain the spatial sensitivity profile for a source-detector pair. The measurement points are one-dimensionally arranged on the surface of the model, and the distance between adjacent measurement points is varied from 4 mm to 28 mm. Small intervals of the measurement points improve the topographic image calculated by both the mapping and reconstruction methods. In the conventional mapping method, the limit of the spatial resolution depends upon the interval of the measurement points and spatial sensitivity profile for source-detector pairs. The reconstruction method has advantages over the mapping method which improve the results of one-dimensional analysis when the interval of measurement points is less than 12 mm. The effect of overlapping of spatial sensitivity profiles indicates that the reconstruction method may be effective to improve the spatial resolution of a two-dimensional reconstruction of topographic image obtained with larger interval of measurement points. Near-infrared topography with the reconstruction method potentially obtains an accurate distribution of absorption change in the brain even if the size of absorption change is less than 10 mm.

Local signaling from a retinal prosthetic in a rodent retinitis pigmentosa model in vivo

NASA Astrophysics Data System (ADS)

Fransen, James W.; Pangeni, Gobinda; Pardue, Machelle T.; McCall, Maureen A.

2014-08-01

Objective. In clinical trials, retinitis pigmentosa patients implanted with a retinal prosthetic device show enhanced spatial vision, including the ability to read large text and navigate. New prosthetics aim to increase spatial resolution by decreasing pixel/electrode size and limiting current spread. To examine spatial resolution of a new prosthetic design, we characterized and compared two photovoltaic array (PVA) designs and their interaction with the retina after subretinal implantation in transgenic S334ter line 3 rats (Tg S334ter-3). Approach. PVAs were implanted subretinally at two stages of degeneration and assessed in vivo using extracellular recordings in the superior colliculus (SC). Several aspects of this interaction were evaluated by varying duration, irradiance and position of a near infrared laser focused on the PVA. These characteristics included: activation threshold, response linearity, SC signal topography and spatial localization. The major design difference between the two PVA designs is the inclusion of local current returns in the newer design. Main results. When tested in vivo, PVA-evoked response thresholds were independent of pixel/electrode size, but differ between the new and old PVA designs. Response thresholds were independent of implantation age and duration (⩽7.5 months). For both prosthesis designs, threshold intensities were within established safety limits. PVA-evoked responses require inner retina synaptic transmission and do not directly activate retinal ganglion cells. The new PVA design evokes local retinal activation, which is not found with the older PVA design that lacks local current returns. Significance. Our study provides in vivo evidence that prosthetics make functional contacts with the inner nuclear layer at several stages of degeneration. The new PVA design enhances local activation within the retina and SC. Together these results predict that the new design can potentially harness the inherent processing within the retina and is likely to produce higher spatial resolution in patients.

Phytoplankton plasticity drives large variability in carbon fixation efficiency

NASA Astrophysics Data System (ADS)

Ayata, Sakina-Dorothée.; Lévy, Marina; Aumont, Olivier; Resplandy, Laure; Tagliabue, Alessandro; Sciandra, Antoine; Bernard, Olivier

2014-12-01

Phytoplankton C:N stoichiometry is highly flexible due to physiological plasticity, which could lead to high variations in carbon fixation efficiency (carbon consumption relative to nitrogen). However, the magnitude, as well as the spatial and temporal scales of variability, remains poorly constrained. We used a high-resolution biogeochemical model resolving various scales from small to high, spatially and temporally, in order to quantify and better understand this variability. We find that phytoplankton C:N ratio is highly variable at all spatial and temporal scales (5-12 molC/molN), from mesoscale to regional scale, and is mainly driven by nitrogen supply. Carbon fixation efficiency varies accordingly at all scales (±30%), with higher values under oligotrophic conditions and lower values under eutrophic conditions. Hence, phytoplankton plasticity may act as a buffer by attenuating carbon sequestration variability. Our results have implications for in situ estimations of C:N ratios and for future predictions under high CO2 world.

An online, energy-resolving beam profile detector for laser-driven proton beams

DOE Office of Scientific and Technical Information (OSTI.GOV)

Metzkes, J.; Rehwald, M.; Obst, L.

In this paper, a scintillator-based online beam profile detector for the characterization of laser-driven proton beams is presented. Using a pixelated matrix with varying absorber thicknesses, the proton beam is spatially resolved in two dimensions and simultaneously energy-resolved. A thin plastic scintillator placed behind the absorber and read out by a CCD camera is used as the active detector material. The spatial detector resolution reaches down to ∼4 mm and the detector can resolve proton beam profiles for up to 9 proton threshold energies. With these detector design parameters, the spatial characteristics of the proton distribution and its cut-off energymore » can be analyzed online and on-shot under vacuum conditions. The paper discusses the detector design, its characterization and calibration at a conventional proton source, as well as the first detector application at a laser-driven proton source.« less

An online, energy-resolving beam profile detector for laser-driven proton beams.

PubMed

Metzkes, J; Zeil, K; Kraft, S D; Karsch, L; Sobiella, M; Rehwald, M; Obst, L; Schlenvoigt, H-P; Schramm, U

2016-08-01

In this paper, a scintillator-based online beam profile detector for the characterization of laser-driven proton beams is presented. Using a pixelated matrix with varying absorber thicknesses, the proton beam is spatially resolved in two dimensions and simultaneously energy-resolved. A thin plastic scintillator placed behind the absorber and read out by a CCD camera is used as the active detector material. The spatial detector resolution reaches down to ∼4 mm and the detector can resolve proton beam profiles for up to 9 proton threshold energies. With these detector design parameters, the spatial characteristics of the proton distribution and its cut-off energy can be analyzed online and on-shot under vacuum conditions. The paper discusses the detector design, its characterization and calibration at a conventional proton source, as well as the first detector application at a laser-driven proton source.

a Spiral-Based Downscaling Method for Generating 30 M Time Series Image Data

NASA Astrophysics Data System (ADS)

Liu, B.; Chen, J.; Xing, H.; Wu, H.; Zhang, J.

2017-09-01

The spatial detail and updating frequency of land cover data are important factors influencing land surface dynamic monitoring applications in high spatial resolution scale. However, the fragmentized patches and seasonal variable of some land cover types (e. g. small crop field, wetland) make it labor-intensive and difficult in the generation of land cover data. Utilizing the high spatial resolution multi-temporal image data is a possible solution. Unfortunately, the spatial and temporal resolution of available remote sensing data like Landsat or MODIS datasets can hardly satisfy the minimum mapping unit and frequency of current land cover mapping / updating at the same time. The generation of high resolution time series may be a compromise to cover the shortage in land cover updating process. One of popular way is to downscale multi-temporal MODIS data with other high spatial resolution auxiliary data like Landsat. But the usual manner of downscaling pixel based on a window may lead to the underdetermined problem in heterogeneous area, result in the uncertainty of some high spatial resolution pixels. Therefore, the downscaled multi-temporal data can hardly reach high spatial resolution as Landsat data. A spiral based method was introduced to downscale low spatial and high temporal resolution image data to high spatial and high temporal resolution image data. By the way of searching the similar pixels around the adjacent region based on the spiral, the pixel set was made up in the adjacent region pixel by pixel. The underdetermined problem is prevented to a large extent from solving the linear system when adopting the pixel set constructed. With the help of ordinary least squares, the method inverted the endmember values of linear system. The high spatial resolution image was reconstructed on the basis of high spatial resolution class map and the endmember values band by band. Then, the high spatial resolution time series was formed with these high spatial resolution images image by image. Simulated experiment and remote sensing image downscaling experiment were conducted. In simulated experiment, the 30 meters class map dataset Globeland30 was adopted to investigate the effect on avoid the underdetermined problem in downscaling procedure and a comparison between spiral and window was conducted. Further, the MODIS NDVI and Landsat image data was adopted to generate the 30m time series NDVI in remote sensing image downscaling experiment. Simulated experiment results showed that the proposed method had a robust performance in downscaling pixel in heterogeneous region and indicated that it was superior to the traditional window-based methods. The high resolution time series generated may be a benefit to the mapping and updating of land cover data.

Towards a high resolution, integrated hydrology model of North America.

NASA Astrophysics Data System (ADS)

Maxwell, R. M.; Condon, L. E.

2015-12-01

Recent studies demonstrate feedbacks between groundwater dynamics, overland flow, land surface and vegetation processes, and atmospheric boundary layer development that significantly affect local and regional climate across a range of climatic conditions. Furthermore, the type and distribution of vegetation cover alters land-atmosphere water and energy fluxes, as well as runoff generation and overland flow processes. These interactions can result in significant feedbacks on local and regional climate. In mountainous regions, recent research has shown that spatial and temporal variability in annual evapotranspiration, and thus water budgets, is strongly dependent on lateral groundwater flow; however, the full effects of these feedbacks across varied terrain (e.g. from plains to mountains) are not well understood. Here, we present a high-resolution, integrated hydrology model that covers much of continental North America and encompasses the Mississippi and Colorado watersheds. The model is run in a fully-transient manner at hourly temporal resolution incorporating fully-coupled land energy states and fluxes with integrated surface and subsurface hydrology. Connections are seen between hydrologic variables (such as water table depth) and land energy fluxes (such as latent heat) and spatial and temporal scaling is shown to span many orders of magnitude. Using these transient simulations as a proof of concept, we present a vision for future integrated simulation capabilities.

The VLITE Post-Processing Pipeline

NASA Astrophysics Data System (ADS)

Richards, Emily E.; Clarke, Tracy; Peters, Wendy; Polisensky, Emil; Kassim, Namir E.

2018-01-01

A post-processing pipeline to adaptively extract and catalog point sources is being developed to enhance the scientific value and accessibility of data products generated by the VLA Low-band Ionosphere and Transient Experiment (VLITE; ) on the Karl G. Jansky Very Large Array (VLA). In contrast to other radio sky surveys, the commensal observing mode of VLITE results in varying depths, sensitivities, and spatial resolutions across the sky based on the configuration of the VLA, location on the sky, and time on source specified by the primary observer for their independent science objectives. Therefore, previously developed tools and methods for generating source catalogs and survey statistics are not always appropriate for VLITE's diverse and growing set of data. A raw catalog of point sources extracted from every VLITE image will be created from source fit parameters stored in a queryable database. Point sources will be measured using the Python Blob Detector and Source Finder software (PyBDSF; Mohan & Rafferty 2015). Sources in the raw catalog will be associated with previous VLITE detections in a resolution- and sensitivity-dependent manner, and cross-matched to other radio sky surveys to aid in the detection of transient and variable sources. Final data products will include separate, tiered point source catalogs grouped by sensitivity limit and spatial resolution.

Multiscale landscape genomic models to detect signatures of selection in the alpine plant Biscutella laevigata.

PubMed

Leempoel, Kevin; Parisod, Christian; Geiser, Céline; Joost, Stéphane

2018-02-01

Plant species are known to adapt locally to their environment, particularly in mountainous areas where conditions can vary drastically over short distances. The climate of such landscapes being largely influenced by topography, using fine-scale models to evaluate environmental heterogeneity may help detecting adaptation to micro-habitats. Here, we applied a multiscale landscape genomic approach to detect evidence of local adaptation in the alpine plant Biscutella laevigata . The two gene pools identified, experiencing limited gene flow along a 1-km ridge, were different in regard to several habitat features derived from a very high resolution (VHR) digital elevation model (DEM). A correlative approach detected signatures of selection along environmental gradients such as altitude, wind exposure, and solar radiation, indicating adaptive pressures likely driven by fine-scale topography. Using a large panel of DEM-derived variables as ecologically relevant proxies, our results highlighted the critical role of spatial resolution. These high-resolution multiscale variables indeed indicate that the robustness of associations between genetic loci and environmental features depends on spatial parameters that are poorly documented. We argue that the scale issue is critical in landscape genomics and that multiscale ecological variables are key to improve our understanding of local adaptation in highly heterogeneous landscapes.

Integrating High-Resolution Datasets to Target Mitigation Efforts for Improving Air Quality and Public Health in Urban Neighborhoods

PubMed Central

Shandas, Vivek; Voelkel, Jackson; Rao, Meenakshi; George, Linda

2016-01-01

Reducing exposure to degraded air quality is essential for building healthy cities. Although air quality and population vary at fine spatial scales, current regulatory and public health frameworks assess human exposures using county- or city-scales. We build on a spatial analysis technique, dasymetric mapping, for allocating urban populations that, together with emerging fine-scale measurements of air pollution, addresses three objectives: (1) evaluate the role of spatial scale in estimating exposure; (2) identify urban communities that are disproportionately burdened by poor air quality; and (3) estimate reduction in mobile sources of pollutants due to local tree-planting efforts using nitrogen dioxide. Our results show a maximum value of 197% difference between cadastrally-informed dasymetric system (CIDS) and standard estimations of population exposure to degraded air quality for small spatial extent analyses, and a lack of substantial difference for large spatial extent analyses. These results provide the foundation for improving policies for managing air quality, and targeting mitigation efforts to address challenges of environmental justice. PMID:27527205

Chromatic and Achromatic Spatial Resolution of Local Field Potentials in Awake Cortex.

PubMed

Jansen, Michael; Li, Xiaobing; Lashgari, Reza; Kremkow, Jens; Bereshpolova, Yulia; Swadlow, Harvey A; Zaidi, Qasim; Alonso, Jose-Manuel

2015-10-01

Local field potentials (LFPs) have become an important measure of neuronal population activity in the brain and could provide robust signals to guide the implant of visual cortical prosthesis in the future. However, it remains unclear whether LFPs can detect weak cortical responses (e.g., cortical responses to equiluminant color) and whether they have enough visual spatial resolution to distinguish different chromatic and achromatic stimulus patterns. By recording from awake behaving macaques in primary visual cortex, here we demonstrate that LFPs respond robustly to pure chromatic stimuli and exhibit ∼2.5 times lower spatial resolution for chromatic than achromatic stimulus patterns, a value that resembles the ratio of achromatic/chromatic resolution measured with psychophysical experiments in humans. We also show that, although the spatial resolution of LFP decays with visual eccentricity as is also the case for single neurons, LFPs have higher spatial resolution and show weaker response suppression to low spatial frequencies than spiking multiunit activity. These results indicate that LFP recordings are an excellent approach to measure spatial resolution from local populations of neurons in visual cortex including those responsive to color. © The Author 2014. Published by Oxford University Press.

The spatial resolution of silicon-based electron detectors in beta-autoradiography.

PubMed

Cabello, Jorge; Wells, Kevin

2010-03-21

Thin tissue autoradiography is an imaging modality where ex-vivo tissue sections are placed in direct contact with autoradiographic film. These tissue sections contain a radiolabelled ligand bound to a specific biomolecule under study. This radioligand emits beta - or beta+ particles ionizing silver halide crystals in the film. High spatial resolution autoradiograms are obtained using low energy radioisotopes, such as (3)H where an intrinsic 0.1-1 microm spatial resolution can be achieved. Several digital alternatives have been presented over the past few years to replace conventional film but their spatial resolution has yet to equal film, although silicon-based imaging technologies have demonstrated higher sensitivity compared to conventional film. It will be shown in this work how pixel size is a critical parameter for achieving high spatial resolution for low energy uncollimated beta imaging. In this work we also examine the confounding factors impeding silicon-based technologies with respect to spatial resolution. The study considers charge diffusion in silicon and detector noise, and this is applied to a range of radioisotopes typically used in autoradiography. Finally an optimal detector geometry to obtain the best possible spatial resolution for a specific technology and a specific radioisotope is suggested.

Recording High Resolution 3D Lagrangian Motions In Marine Dinoflagellates using Digital Holographic Microscopic Cinematography

NASA Astrophysics Data System (ADS)

Sheng, J.; Malkiel, E.; Katz, J.; Place, A. R.; Belas, R.

2006-11-01

Detailed data on swimming behavior and locomotion for dense population of dinoflagellates constitutes a key component to understanding cell migration, cell-cell interactions and predator-prey dynamics, all of which affect algae bloom dynamics. Due to the multi-dimensional nature of flagellated cell motions, spatial-temporal Lagrangian measurements of multiple cells in high concentration are very limited. Here we present detailed data on 3D Lagrangian motions for three marine dinoflagellates: Oxyrrhis marina, Karlodinium veneficum, and Pfiesteria piscicida, using digital holographic microscopic cinematography. The measurements are performed in a 5x5x25mm cuvette with cell densities varying from 50,000 ˜ 90,000 cells/ml. Approximately 200-500 cells are tracked simultaneously for 12s at 60fps in a sample volume of 1x1x5 mm at a spatial resolution of 0.4x0.4x2 μm. We fully resolve the longitudinal flagella (˜200nm) along with the Lagrangian trajectory of each organism. Species dependent swimming behavior are identified and categorized quantitatively by velocities, radii of curvature, and rotations of pitch. Statistics on locomotion, temporal & spatial scales, and diffusion rate show substantial differences between species. The scaling between turning radius and cell dimension can be explained by a distributed stokeslet model for a self-propelled body.

Stream dynamics and chemical transformations control the environmental fate of silver and zinc oxide nanoparticles in a watershed-scale model.

PubMed

Dale, Amy L; Lowry, Gregory V; Casman, Elizabeth A

2015-06-16

Mathematical models are needed to estimate environmental concentrations of engineered nanoparticles (NPs), which enter the environment upon the use and disposal of consumer goods and other products. We present a spatially resolved environmental fate model for the James River Basin, Virginia, that explores the influence of daily variation in streamflow, sediment transport, and stream loads from point and nonpoint sources on water column and sediment concentrations of zinc oxide (ZnO) and silver (Ag) NPs and their reaction byproducts over 20 simulation years. Spatial and temporal variability in sediment transport rates led to high NP transport such that less than 6% of NP-derived metals were retained in the river and sediments. Chemical transformations entirely eliminated ZnO NPs and doubled Zn mobility in the stream relative to Ag. Agricultural runoff accounted for 23% of total metal stream loads from NPs. Average NP-derived metal concentrations in the sediment varied spatially up to 9 orders of magnitude, highlighting the need for high-resolution models. Overall, our results suggest that "first generation" NP risk models have probably misrepresented NP fate in freshwater rivers due to low model resolutions and the simplification of NP chemistry and sediment transport.

Development of a large-area Multigap RPC with adequate spatial resolution for muon tomography

NASA Astrophysics Data System (ADS)

Wang, J.; Wang, Y.; Wang, X.; Zeng, M.; Xie, B.; Han, D.; Lyu, P.; Wang, F.; Li, Y.

2016-11-01

We study the performance of a large-area 2-D Multigap Resistive Plate Chamber (MRPC) designed for muon tomography with high spatial resolution. An efficiency up to 98% and a spatial resolution of around 270 μ m are obtained in cosmic ray and X-ray tests. The performance of the MRPC is also investigated for two working gases: standard gas and pure Freon. The result shows that the MRPC working in pure Freon can provide higher efficiency and better spatial resolution.

Study of electrode pattern design for a CZT-based PET detector.

PubMed

Gu, Y; Levin, C S

2014-06-07

We are developing a 1 mm resolution small animal positron emission tomography (PET) system using 3D positioning cadmium zinc telluride photon detectors comprising 40 mm × 40 mm × 5 mm crystals metalized with a cross-strip electrode pattern with a 1 mm anode strip pitch. We optimized the electrode pattern design for intrinsic sensitivity and spatial, energy and time resolution performance using a test detector comprising cathode and steering electrode strips of varying dimensions. The study found 3 and 5 mm width cathode strips locate charge-shared photon interactions near cathode strip boundaries with equal precision. 3 mm width cathode strips exhibited large time resolution variability as a function of photon interaction location between the anode and cathode planes (~26 to ~127.5 ns full width at half maximum (FWHM) for 0.5 mm and 4.2 mm depths, respectively). 5 mm width cathode strips by contrast exhibited more stable time resolution for the same interaction locations (~34 to ~83 ns FWHM), provided more linear spatial positioning in the direction orthogonal to the electrode planes, and as much as 68.4% improvement in photon sensitivity over the 3 mm wide cathode strips. The results were understood by analyzing the cathode strips' weighting functions, which indicated a stronger 'small pixel' effect in the 3 mm wide cathode strips. Photon sensitivity and anode energy resolution were seen to improve with decreasing steering electrode bias from 0 to -80 V w.r.t. the anode potential. A slight improvement in energy resolution was seen for wider steering electrode strips (400 versus 100 µm) for charge-shared photon interactions. Although this study successfully focused on electrode pattern features for PET performance, the results are generally applicable to semiconductor photon detectors employing cross-trip electrode patterns.

Study of electrode pattern design for a CZT-based PET detector

PubMed Central

Gu, Y; Levin, C S

2014-01-01

We are developing a 1 mm resolution small animal positron emission tomography (PET) system using 3-D positioning Cadmium Zinc Telluride (CZT) photon detectors comprising 40 mm × 40 mm × 5 mm crystals metalized with a cross-strip electrode pattern with a 1 mm anode strip pitch. We optimized the electrode pattern design for intrinsic sensitivity and spatial, energy and time resolution performance using a test detector comprising cathode and steering electrode strips of varying dimensions. The study found 3 mm and 5 mm width cathode strips locate charge-shared photon interactions near cathode strip boundaries with equal precision. 3 mm width cathode strips exhibited large time resolution variability as a function of photon interaction location between the anode and cathode planes (~26 ns to ~127.5 ns FWHM for 0.5 mm and 4.2 mm depths, respectively). 5 mm width cathode strips by contrast exhibited more stable time resolution for the same interaction locations (~34 ns to ~83 ns FWHM), provided more linear spatial positioning in the direction orthogonal to the electrode planes, and as much as 68.4% improvement in photon sensitivity over the 3 mm wide cathode strips. The results were understood by analyzing the cathode strips’ weighting functions, which indicated a stronger “small pixel” effect in the 3 mm wide cathode strips. Photon sensitivity and anode energy resolution were seen to improve with decreasing steering electrode bias from 0 V to −80 V w.r.t the anode potential. A slight improvement in energy resolution was seen for wider steering electrode strips (400 μm vs. 100 μm) for charge-shared photon interactions. Although this study successfully focused on electrode pattern features for PET performance, the results are generally applicable to semiconductor photon detectors employing cross-trip electrode patterns. PMID:24786208

High variability in spatial and temporal size-based trophodynamics of deep-sea fishes from the Mid-Atlantic Ridge elucidated by stable isotopes

NASA Astrophysics Data System (ADS)

Reid, William D. K.; Sweeting, Christopher J.; Wigham, Ben D.; McGill, Rona A. R.; Polunin, Nicholas V. C.

2013-12-01

Demersal fish play an important role in the deep-sea ecosystem by acting as a link to mobile food in the water column, consuming benthic fauna, breaking down large food parcels and dispersing organic matter over large areas. Poor diet resolution from stomach content analysis often impairs the ability to assess differences in inter- and intra-population trophodynamics and therefore understand resource partitioning among deep-sea fishes. Antimora rostrata (predator-scavenger), Coryphaenoides armatus (predator-scavenger), Coryphaenoides brevibarbis (predator) and Halosauropsis macrochir (predator) were collected from 3 stations on the Mid-Atlantic Ridge (MAR) in 2007 and 2009 to investigate trophic ecology using δ13C and δ15N. Variability in lipid-normalised δ13C (δ13Cn) and δ15N was explained by body length in all species but slope and significance of the isotope-length relationships varied both temporally and spatially. δ15N increases with length were observed in A. rostrata at all stations, C. brevibarbis and H. macrochir at one or more stations but were absent in C. armatus. δ13Cn increased with length in A. rostrata but the slope of δ13Cn-length relationships varied spatially and temporally in C. armatus and C. brevibarbis. The co-occurring δ13Cn and δ15N size-based trends in A. rostrata and H. macrochir suggested that size-based trends were a result of increasing trophic position. In C. armatus and C. brevibarbis the isotope-length trends were difficult to distinguish among trophic position increases, shifts in resource use i.e. benthic to pelagic or internal physiology. However, the overall strength, direction and significance of isotope-length trends varied temporally and spatially which suggested varying degrees of overlap in trophic ecology and feeding plasticity among these species.

Estimation of Orbital Neutron Detector Spatial Resolution by Systematic Shifting of Differential Topographic Masks

NASA Technical Reports Server (NTRS)

McClanahan, T. P.; Mitrofanov, I. G.; Boynton, W. V.; Chin, G.; Livengood, T.; Starr, R. D.; Evans, L. G.; Mazarico, E.; Smith, D. E.

2012-01-01

We present a method and preliminary results related to determining the spatial resolution of orbital neutron detectors using epithermal maps and differential topographic masks. Our technique is similar to coded aperture imaging methods for optimizing photonic signals in telescopes [I]. In that approach photon masks with known spatial patterns in a telescope aperature are used to systematically restrict incoming photons which minimizes interference and enhances photon signal to noise. Three orbital neutron detector systems with different stated spatial resolutions are evaluated. The differing spatial resolutions arise due different orbital altitudes and the use of neutron collimation techniques. 1) The uncollimated Lunar Prospector Neutron Spectrometer (LPNS) system has spatial resolution of 45km FWHM from approx. 30km altitude mission phase [2]. The Lunar Rennaissance Orbiter (LRO) Lunar Exploration Neutron Detector (LEND) with two detectors at 50km altitude evaluated here: 2) the collimated 10km FWHM spatial resolution detector CSETN and 3) LEND's collimated Sensor for Epithermal Neutrons (SETN). Thus providing two orbital altitudes to study factors of: uncollimated vs collimated and two average altitudes for their effect on fields-of-view.

Some effects of finite spatial resolution on skin friction measurements in turbulent boundary layers

NASA Technical Reports Server (NTRS)

Westphal, Russell V.

1988-01-01

The effects of finite spatial resolution often cause serious errors in measurements in turbulent boundary layers, with particularly large effects for measurements of fluctuating skin friction and velocities within the sublayer. However, classical analyses of finite spatial resolution effects have generally not accounted for the substantial inhomogeneity and anisotropy of near-wall turbulence. The present study has made use of results from recent computational simulations of wall-bounded turbulent flows to examine spatial resolution effects for measurements made at a wall using both single-sensor probes and those employing two sensing volumes in a V shape. Results are presented to show the effects of finite spatial resolution on a variety of quantitites deduced from the skin friction field.

Examination about the Spatial Representation of PM2.5 Obtained from Limited Stations Using a Network Observation

NASA Astrophysics Data System (ADS)

Shi, X.; Zhao, C.

2017-12-01

Haze aerosol pollution has been a focus issue in China, and its characteristics is highly demanded. With limited observation sites, aerosol properties obtained from a single site is frequently used to represent the haze condition over a large domain, such as tens of kilometers. This could result in high uncertainties in the haze characteristics due to their spatial variation. Using a network observation from November 2015 to February 2016 over an urban city in North China with high spatial resolution, this study examines the spatial representation of ground site observations. A method is first developed to determine the representative area of measurements from limited stations. The key idea of this method is to determine the spatial variability of particulate matter with diameters less than 2.5 μm (PM2.5) concentration using a variance function in 2km x 2km grids. Based on the high spatial resolution (0.5km x 0.5km) measurements of PM2.5, the grids in which PM2.5 have high correlations and weak value differences are determined as the representation area of measurements at these grids. Note that the size representation area is not exactly a circle region. It shows that the size representation are for the study region and study period ranges from 0.25 km2 to 16.25 km2. The representation area varies with locations. For the 20 km x 20 km study region, 10 station observations would have a good representation of the PM2.5 observations obtained from current 169 stations at the four-month time scale.

Evaluating the Value of High Spatial Resolution in National Capacity Expansion Models using ReEDS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krishnan, Venkat; Cole, Wesley

2016-11-14

Power sector capacity expansion models (CEMs) have a broad range of spatial resolutions. This paper uses the Regional Energy Deployment System (ReEDS) model, a long-term national scale electric sector CEM, to evaluate the value of high spatial resolution for CEMs. ReEDS models the United States with 134 load balancing areas (BAs) and captures the variability in existing generation parameters, future technology costs, performance, and resource availability using very high spatial resolution data, especially for wind and solar modeled at 356 resource regions. In this paper we perform planning studies at three different spatial resolutions--native resolution (134 BAs), state-level, and NERCmore » region level--and evaluate how results change under different levels of spatial aggregation in terms of renewable capacity deployment and location, associated transmission builds, and system costs. The results are used to ascertain the value of high geographically resolved models in terms of their impact on relative competitiveness among renewable energy resources.« less

The Analysis of Burrows Recognition Accuracy in XINJIANG'S Pasture Area Based on Uav Visible Images with Different Spatial Resolution

NASA Astrophysics Data System (ADS)

Sun, D.; Zheng, J. H.; Ma, T.; Chen, J. J.; Li, X.

2018-04-01

The rodent disaster is one of the main biological disasters in grassland in northern Xinjiang. The eating and digging behaviors will cause the destruction of ground vegetation, which seriously affected the development of animal husbandry and grassland ecological security. UAV low altitude remote sensing, as an emerging technique with high spatial resolution, can effectively recognize the burrows. However, how to select the appropriate spatial resolution to monitor the calamity of the rodent disaster is the first problem we need to pay attention to. The purpose of this study is to explore the optimal spatial scale on identification of the burrows by evaluating the impact of different spatial resolution for the burrows identification accuracy. In this study, we shoot burrows from different flight heights to obtain visible images of different spatial resolution. Then an object-oriented method is used to identify the caves, and we also evaluate the accuracy of the classification. We found that the highest classification accuracy of holes, the average has reached more than 80 %. At the altitude of 24 m and the spatial resolution of 1cm, the accuracy of the classification is the highest We have created a unique and effective way to identify burrows by using UAVs visible images. We draw the following conclusion: the best spatial resolution of burrows recognition is 1 cm using DJI PHANTOM-3 UAV, and the improvement of spatial resolution does not necessarily lead to the improvement of classification accuracy. This study lays the foundation for future research and can be extended to similar studies elsewhere.

Time Series Analysis for Spatial Node Selection in Environment Monitoring Sensor Networks

PubMed Central

Bhandari, Siddhartha; Jurdak, Raja; Kusy, Branislav

2017-01-01

Wireless sensor networks are widely used in environmental monitoring. The number of sensor nodes to be deployed will vary depending on the desired spatio-temporal resolution. Selecting an optimal number, position and sampling rate for an array of sensor nodes in environmental monitoring is a challenging question. Most of the current solutions are either theoretical or simulation-based where the problems are tackled using random field theory, computational geometry or computer simulations, limiting their specificity to a given sensor deployment. Using an empirical dataset from a mine rehabilitation monitoring sensor network, this work proposes a data-driven approach where co-integrated time series analysis is used to select the number of sensors from a short-term deployment of a larger set of potential node positions. Analyses conducted on temperature time series show 75% of sensors are co-integrated. Using only 25% of the original nodes can generate a complete dataset within a 0.5 °C average error bound. Our data-driven approach to sensor position selection is applicable for spatiotemporal monitoring of spatially correlated environmental parameters to minimize deployment cost without compromising data resolution. PMID:29271880

Study of Electric Explosion of Flat Micron-Thick Foils at Current Densities of (5-50)×10 8A/cm 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shelkovenko, T. A.; Pikuz, S. A.; Tilikin, I. N.

Electric explosions of flat Al, Тi, Ni, Cu, and Та foils with thicknesses of 1-16 μm, widths of 1-8 mm, and lengths of 5-11 mm were studied experimentally on the BIN, XP, and COBRA high-current generators at currents of 40-1000 kA and current densities of (5–50) × 10 8 A/cm 2. The images of the exploded foils were taken at different angles to the foil surface by using point projection radiography with an X-pinch hot spot as the radiation source, the spatial resolution and exposure time being 3 μm and 50 ps, respectively, as well by the laser probing methodmore » with a spatial resolution of 20 μm and an exposure time of 180 ps. In the course of foil explosion, rapidly expanding objects resembling the core and corona of an exploded wire were observed. It is shown that the core of the exploded foil has a complicated time-varying structure.« less

Study of Electric Explosion of Flat Micron-Thick Foils at Current Densities of (5-50)×10 8A/cm 2

DOE PAGES

Shelkovenko, T. A.; Pikuz, S. A.; Tilikin, I. N.; ...

2018-01-01

Electric explosions of flat Al, Тi, Ni, Cu, and Та foils with thicknesses of 1-16 μm, widths of 1-8 mm, and lengths of 5-11 mm were studied experimentally on the BIN, XP, and COBRA high-current generators at currents of 40-1000 kA and current densities of (5–50) × 10 8 A/cm 2. The images of the exploded foils were taken at different angles to the foil surface by using point projection radiography with an X-pinch hot spot as the radiation source, the spatial resolution and exposure time being 3 μm and 50 ps, respectively, as well by the laser probing methodmore » with a spatial resolution of 20 μm and an exposure time of 180 ps. In the course of foil explosion, rapidly expanding objects resembling the core and corona of an exploded wire were observed. It is shown that the core of the exploded foil has a complicated time-varying structure.« less

Investigation of CMOS pixel sensor with 0.18 μm CMOS technology for high-precision tracking detector

NASA Astrophysics Data System (ADS)

Zhang, L.; Fu, M.; Zhang, Y.; Yan, W.; Wang, M.

2017-01-01

The Circular Electron Positron Collider (CEPC) proposed by the Chinese high energy physics community is aiming to measure Higgs particles and their interactions precisely. The tracking detector including Silicon Inner Tracker (SIT) and Forward Tracking Disks (FTD) has driven stringent requirements on sensor technologies in term of spatial resolution, power consumption and readout speed. CMOS Pixel Sensor (CPS) is a promising candidate to approach these requirements. This paper presents the preliminary studies on the sensor optimization for tracking detector to achieve high collection efficiency while keeping necessary spatial resolution. Detailed studies have been performed on the charge collection using a 0.18 μm CMOS image sensor process. This process allows high resistivity epitaxial layer, leading to a significant improvement on the charge collection and therefore improving the radiation tolerance. Together with the simulation results, the first exploratory prototype has bee designed and fabricated. The prototype includes 9 different pixel arrays, which vary in terms of pixel pitch, diode size and geometry. The total area of the prototype amounts to 2 × 7.88 mm2.

Design of 4D x-ray tomography experiments for reconstruction using regularized iterative algorithms

NASA Astrophysics Data System (ADS)

Mohan, K. Aditya

2017-10-01

4D X-ray computed tomography (4D-XCT) is widely used to perform non-destructive characterization of time varying physical processes in various materials. The conventional approach to improving temporal resolution in 4D-XCT involves the development of expensive and complex instrumentation that acquire data faster with reduced noise. It is customary to acquire data with many tomographic views at a high signal to noise ratio. Instead, temporal resolution can be improved using regularized iterative algorithms that are less sensitive to noise and limited views. These algorithms benefit from optimization of other parameters such as the view sampling strategy while improving temporal resolution by reducing the total number of views or the detector exposure time. This paper presents the design principles of 4D-XCT experiments when using regularized iterative algorithms derived using the framework of model-based reconstruction. A strategy for performing 4D-XCT experiments is presented that allows for improving the temporal resolution by progressively reducing the number of views or the detector exposure time. Theoretical analysis of the effect of the data acquisition parameters on the detector signal to noise ratio, spatial reconstruction resolution, and temporal reconstruction resolution is also presented in this paper.

SU-F-I-55: Performance Evaluation of Digital PET/CT: Medical Physics Basis for the Clinical Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, J; Knopp, MV; Miller, M

2016-06-15

Purpose: Replacement of conventional PMT-based detector with next generation digital photon counting (DPC) detector is a technology leap for PET imaging. This study evaluated the performance and characteristics of the DPC system and its stability within a 1 year time window following its installation focusing on the medical physics basis for clinical applications. Methods: A digital PET/CT scanner using 1:1 coupling of 23,040 crystal: detector elements was introduced and became operational at OSU. We tested and evaluated system performance and characteristics using NEMA NU2-2012. System stabilities in timing resolution, energy resolution, detector temperature and humidity (T&H) were monitored over 1-yr.more » Timing, energy and spatial resolution were characterized across clinically relevant count rate range. CQIE uniformity PET and NEMA IEC-Body PET with hot spheres varying with sizes and contrasts were performed. PET reconstructed in standard(4mm), High(2mm) and Ultra-High(1mm) definitions were evaluated. Results: NEMA results showed PET spatial resolution (mm-FWHM) from 4.01&4.14 at 1cm to 5.82&6.17 at 20cm in transverse & axial. 322±3ps timing and 11.0% energy resolution were measured. 5.7kcps/MBq system sensitivity with 24kcps/MBq effective sensitivity was obtained. The peak-NECR was ∼171kcps with the effective peak-NECR >650kcps@50kBq/mL. Scatter fraction was ∼30%, and the maximum trues was >900kcps. NEMA IQ demonstrated hot sphere contrast ranging from ∼62%±2%(10mm) to ∼88%±2%(22mm), cold sphere contrast of ∼86%±2%(28mm) and ∼89%±3%(37mm) and excellent uniformity. Monitoring 1-yr stability, it revealed ∼1% change in timing, ±0.4% change in energy resolution, and <10% variations in T&H. CQIE PET gave <3% SUV variances in axial. 60%–100% recovery coefficients across sphere sizes and contrast levels were achieved. Conclusion: Characteristics and stability of the next generation DPC PET detector system over an 1-yr time window was excellent and better than prior experiences. It demonstrated improved and robust system characteristics and performance in spatial resolution, sensitivity, timing and energy resolution, count rate and image quality. Michael Miller is an employee of Philips Healthcare.« less

Evaluation of appropriate sensor specifications for space based ballistic missile detection

NASA Astrophysics Data System (ADS)

Schweitzer, Caroline; Stein, Karin; Wendelstein, Norbert

2012-10-01

The detection and tracking of ballistic missiles (BMs) during launch or cloud break using satellite based electro-optical (EO) sensors is a promising possibility for pre-instructing early warning and fire control radars. However, the successful detection of a BM is depending on the applied infrared (IR)-channel, as emission and reflection of threat and background vary in different spectral (IR-) bands and for different observation scenarios. In addition, the spatial resolution of the satellite based system also conditions the signal-to-clutter-ratio (SCR) and therefore the predictability of the flight path. Generally available satellite images provide data in spectral bands, which are suitable for remote sensing applications and earth surface observations. However, in the fields of BM early warning, these bands are not of interest making the simulation of background data essential. The paper focuses on the analysis of IR-bands suitable for missile detection by trading off the suppression of background signature against threat signal strength. This comprises a radiometric overview of the background radiation in different spectral bands for different climates and seasons as well as for various cloud types and covers. A brief investigation of the BM signature and its trajectory within a threat scenario is presented. Moreover, the influence on the SCR caused by different observation scenarios and varying spatial resolution are pointed out. The paper also introduces the software used for simulating natural background spectral radiance images, MATISSE ("Advanced Modeling of the Earth for Environment and Scenes Simulation") by ONERA [1].

The effects of spatial population dataset choice on estimates of population at risk of disease

PubMed Central

2011-01-01

Background The spatial modeling of infectious disease distributions and dynamics is increasingly being undertaken for health services planning and disease control monitoring, implementation, and evaluation. Where risks are heterogeneous in space or dependent on person-to-person transmission, spatial data on human population distributions are required to estimate infectious disease risks, burdens, and dynamics. Several different modeled human population distribution datasets are available and widely used, but the disparities among them and the implications for enumerating disease burdens and populations at risk have not been considered systematically. Here, we quantify some of these effects using global estimates of populations at risk (PAR) of P. falciparum malaria as an example. Methods The recent construction of a global map of P. falciparum malaria endemicity enabled the testing of different gridded population datasets for providing estimates of PAR by endemicity class. The estimated population numbers within each class were calculated for each country using four different global gridded human population datasets: GRUMP (~1 km spatial resolution), LandScan (~1 km), UNEP Global Population Databases (~5 km), and GPW3 (~5 km). More detailed assessments of PAR variation and accuracy were conducted for three African countries where census data were available at a higher administrative-unit level than used by any of the four gridded population datasets. Results The estimates of PAR based on the datasets varied by more than 10 million people for some countries, even accounting for the fact that estimates of population totals made by different agencies are used to correct national totals in these datasets and can vary by more than 5% for many low-income countries. In many cases, these variations in PAR estimates comprised more than 10% of the total national population. The detailed country-level assessments suggested that none of the datasets was consistently more accurate than the others in estimating PAR. The sizes of such differences among modeled human populations were related to variations in the methods, input resolution, and date of the census data underlying each dataset. Data quality varied from country to country within the spatial population datasets. Conclusions Detailed, highly spatially resolved human population data are an essential resource for planning health service delivery for disease control, for the spatial modeling of epidemics, and for decision-making processes related to public health. However, our results highlight that for the low-income regions of the world where disease burden is greatest, existing datasets display substantial variations in estimated population distributions, resulting in uncertainty in disease assessments that utilize them. Increased efforts are required to gather contemporary and spatially detailed demographic data to reduce this uncertainty, particularly in Africa, and to develop population distribution modeling methods that match the rigor, sophistication, and ability to handle uncertainty of contemporary disease mapping and spread modeling. In the meantime, studies that utilize a particular spatial population dataset need to acknowledge the uncertainties inherent within them and consider how the methods and data that comprise each will affect conclusions. PMID:21299885

Temporal changes of spatial soil moisture patterns: controlling factors explained with a multidisciplinary approach

NASA Astrophysics Data System (ADS)

Martini, Edoardo; Wollschläger, Ute; Kögler, Simon; Behrens, Thorsten; Dietrich, Peter; Reinstorf, Frido; Schmidt, Karsten; Weiler, Markus; Werban, Ulrike; Zacharias, Steffen

2016-04-01

Characterizing the spatial patterns of soil moisture is critical for hydrological and meteorological models, as soil moisture is a key variable that controls matter and energy fluxes and soil-vegetation-atmosphere exchange processes. Deriving detailed process understanding at the hillslope scale is not trivial, because of the temporal variability of local soil moisture dynamics. Nevertheless, it remains a challenge to provide adequate information on the temporal variability of soil moisture and its controlling factors. Recent advances in wireless sensor technology allow monitoring of soil moisture dynamics with high temporal resolution at varying scales. In addition, mobile geophysical methods such as electromagnetic induction (EMI) have been widely used for mapping soil water content at the field scale with high spatial resolution, as being related to soil apparent electrical conductivity (ECa). The objective of this study was to characterize the spatial and temporal pattern of soil moisture at the hillslope scale and to infer the controlling hydrological processes, integrating well established and innovative sensing techniques, as well as new statistical methods. We combined soil hydrological and pedological expertise with geophysical measurements and methods from digital soil mapping for designing a wireless soil moisture monitoring network. For a hillslope site within the Schäfertal catchment (Central Germany), soil water dynamics were observed during 14 months, and soil ECa was mapped on seven occasions whithin this period of time using an EM38-DD device. Using the Spearman rank correlation coefficient, we described the temporal persistence of a dry and a wet characteristic state of soil moisture as well as the switching mechanisms, inferring the local properties that control the observed spatial patterns and the hydrological processes driving the transitions. Based on this, we evaluated the use of EMI for mapping the spatial pattern of soil moisture under different hydrologic conditions and the factors controlling the temporal variability of the ECa-soil moisture relationship. The approach provided valuable insight into the time-varying contribution of local and nonlocal factors to the characteristic spatial patterns of soil moisture and the transition mechanisms. The spatial organization of soil moisture was controlled by different processes in different soil horizons, and the topsoil's moisture did not mirror processes that take place within the soil profile. Results show that, for the Schäfertal hillslope site which is presumed to be representative for non-intensively managed soils with moderate clay content, local soil properties (e.g., soil texture and porosity) are the major control on the spatial pattern of ECa. In contrast, the ECa-soil moisture relationship is small and varies over time indicating that ECa is not a good proxy for soil moisture estimation at the investigated site.Occasionally observed stronger correlations between ECa and soil moisture may be explained by background dependencies of ECa to other state variables such as pore water electrical conductivity. The results will help to improve conceptual understanding for hydrological model studies at similar or smaller scales, and to transfer observation concepts and process understanding to larger or less instrumented sites, as well as to constrain the use of EMI-based ECa data for hydrological applications.

Spatial and temporal variability of clouds and precipitation over Germany: multiscale simulations across the "gray zone"

NASA Astrophysics Data System (ADS)

Barthlott, C.; Hoose, C.

2015-11-01

This paper assesses the resolution dependance of clouds and precipitation over Germany by numerical simulations with the COnsortium for Small-scale MOdeling (COSMO) model. Six intensive observation periods of the HOPE (HD(CP)2 Observational Prototype Experiment) measurement campaign conducted in spring 2013 and 1 summer day of the same year are simulated. By means of a series of grid-refinement resolution tests (horizontal grid spacing 2.8, 1 km, 500, and 250 m), the applicability of the COSMO model to represent real weather events in the gray zone, i.e., the scale ranging between the mesoscale limit (no turbulence resolved) and the large-eddy simulation limit (energy-containing turbulence resolved), is tested. To the authors' knowledge, this paper presents the first non-idealized COSMO simulations in the peer-reviewed literature at the 250-500 m scale. It is found that the kinetic energy spectra derived from model output show the expected -5/3 slope, as well as a dependency on model resolution, and that the effective resolution lies between 6 and 7 times the nominal resolution. Although the representation of a number of processes is enhanced with resolution (e.g., boundary-layer thermals, low-level convergence zones, gravity waves), their influence on the temporal evolution of precipitation is rather weak. However, rain intensities vary with resolution, leading to differences in the total rain amount of up to +48 %. Furthermore, the location of rain is similar for the springtime cases with moderate and strong synoptic forcing, whereas significant differences are obtained for the summertime case with air mass convection. Domain-averaged liquid water paths and cloud condensate profiles are used to analyze the temporal and spatial variability of the simulated clouds. Finally, probability density functions of convection-related parameters are analyzed to investigate their dependance on model resolution and their impact on cloud formation and subsequent precipitation.

Effects of vegetation heterogeneity and surface topography on spatial scaling of net primary productivity

NASA Astrophysics Data System (ADS)

Chen, J. M.; Chen, X.; Ju, W.

2013-03-01

Due to the heterogeneous nature of the land surface, spatial scaling is an inevitable issue in the development of land models coupled with low-resolution Earth system models (ESMs) for predicting land-atmosphere interactions and carbon-climate feedbacks. In this study, a simple spatial scaling algorithm is developed to correct errors in net primary productivity (NPP) estimates made at a coarse spatial resolution based on sub-pixel information of vegetation heterogeneity and surface topography. An eco-hydrological model BEPS-TerrainLab, which considers both vegetation and topographical effects on the vertical and lateral water flows and the carbon cycle, is used to simulate NPP at 30 m and 1 km resolutions for a 5700 km2 watershed with an elevation range from 518 m to 3767 m in the Qinling Mountain, Shaanxi Province, China. Assuming that the NPP simulated at 30 m resolution represents the reality and that at 1 km resolution is subject to errors due to sub-pixel heterogeneity, a spatial scaling index (SSI) is developed to correct the coarse resolution NPP values pixel by pixel. The agreement between the NPP values at these two resolutions is improved considerably from R2 = 0.782 to R2 = 0.884 after the correction. The mean bias error (MBE) in NPP modeled at the 1 km resolution is reduced from 14.8 g C m-2 yr-1 to 4.8 g C m-2 yr-1 in comparison with NPP modeled at 30 m resolution, where the mean NPP is 668 g C m-2 yr-1. The range of spatial variations of NPP at 30 m resolution is larger than that at 1 km resolution. Land cover fraction is the most important vegetation factor to be considered in NPP spatial scaling, and slope is the most important topographical factor for NPP spatial scaling especially in mountainous areas, because of its influence on the lateral water redistribution, affecting water table, soil moisture and plant growth. Other factors including leaf area index (LAI), elevation and aspect have small and additive effects on improving the spatial scaling between these two resolutions.

Effects of vegetation heterogeneity and surface topography on spatial scaling of net primary productivity

NASA Astrophysics Data System (ADS)

Chen, J. M.; Chen, X.; Ju, W.

2013-07-01

Due to the heterogeneous nature of the land surface, spatial scaling is an inevitable issue in the development of land models coupled with low-resolution Earth system models (ESMs) for predicting land-atmosphere interactions and carbon-climate feedbacks. In this study, a simple spatial scaling algorithm is developed to correct errors in net primary productivity (NPP) estimates made at a coarse spatial resolution based on sub-pixel information of vegetation heterogeneity and surface topography. An eco-hydrological model BEPS-TerrainLab, which considers both vegetation and topographical effects on the vertical and lateral water flows and the carbon cycle, is used to simulate NPP at 30 m and 1 km resolutions for a 5700 km2 watershed with an elevation range from 518 m to 3767 m in the Qinling Mountain, Shanxi Province, China. Assuming that the NPP simulated at 30 m resolution represents the reality and that at 1 km resolution is subject to errors due to sub-pixel heterogeneity, a spatial scaling index (SSI) is developed to correct the coarse resolution NPP values pixel by pixel. The agreement between the NPP values at these two resolutions is improved considerably from R2 = 0.782 to R2 = 0.884 after the correction. The mean bias error (MBE) in NPP modelled at the 1 km resolution is reduced from 14.8 g C m-2 yr-1 to 4.8 g C m-2 yr-1 in comparison with NPP modelled at 30 m resolution, where the mean NPP is 668 g C m-2 yr-1. The range of spatial variations of NPP at 30 m resolution is larger than that at 1 km resolution. Land cover fraction is the most important vegetation factor to be considered in NPP spatial scaling, and slope is the most important topographical factor for NPP spatial scaling especially in mountainous areas, because of its influence on the lateral water redistribution, affecting water table, soil moisture and plant growth. Other factors including leaf area index (LAI) and elevation have small and additive effects on improving the spatial scaling between these two resolutions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Ke; Chen, Guang-Hong, E-mail: gchen7@wisc.edu; Garrett, John

Purpose: Statistical model based iterative reconstruction (MBIR) methods have been introduced to clinical CT systems and are being used in some clinical diagnostic applications. The purpose of this paper is to experimentally assess the unique spatial resolution characteristics of this nonlinear reconstruction method and identify its potential impact on the detectabilities and the associated radiation dose levels for specific imaging tasks. Methods: The thoracic section of a pediatric phantom was repeatedly scanned 50 or 100 times using a 64-slice clinical CT scanner at four different dose levels [CTDI{sub vol} =4, 8, 12, 16 (mGy)]. Both filtered backprojection (FBP) and MBIRmore » (Veo{sup ®}, GE Healthcare, Waukesha, WI) were used for image reconstruction and results were compared with one another. Eight test objects in the phantom with contrast levels ranging from 13 to 1710 HU were used to assess spatial resolution. The axial spatial resolution was quantified with the point spread function (PSF), while the z resolution was quantified with the slice sensitivity profile. Both were measured locally on the test objects and in the image domain. The dependence of spatial resolution on contrast and dose levels was studied. The study also features a systematic investigation of the potential trade-off between spatial resolution and locally defined noise and their joint impact on the overall image quality, which was quantified by the image domain-based channelized Hotelling observer (CHO) detectability index d′. Results: (1) The axial spatial resolution of MBIR depends on both radiation dose level and image contrast level, whereas it is supposedly independent of these two factors in FBP. The axial spatial resolution of MBIR always improved with an increasing radiation dose level and/or contrast level. (2) The axial spatial resolution of MBIR became equivalent to that of FBP at some transitional contrast level, above which MBIR demonstrated superior spatial resolution than FBP (and vice versa); the value of this transitional contrast highly depended on the dose level. (3) The PSFs of MBIR could be approximated as Gaussian functions with reasonably good accuracy. (4) Thez resolution of MBIR showed similar contrast and dose dependence. (5) Noise standard deviation assessed on the edges of objects demonstrated a trade-off with spatial resolution in MBIR. (5) When both spatial resolution and image noise were considered using the CHO analysis, MBIR led to significant improvement in the overall CT image quality for both high and low contrast detection tasks at both standard and low dose levels. Conclusions: Due to the intrinsic nonlinearity of the MBIR method, many well-known CT spatial resolution and noise properties have been modified. In particular, dose dependence and contrast dependence have been introduced to the spatial resolution of CT images by MBIR. The method has also introduced some novel noise-resolution trade-off not seen in traditional CT images. While the benefits of MBIR regarding the overall image quality, as demonstrated in this work, are significant, the optimal use of this method in clinical practice demands a thorough understanding of its unique physical characteristics.« less

High-resolution scanning precession electron diffraction: Alignment and spatial resolution.

PubMed

Barnard, Jonathan S; Johnstone, Duncan N; Midgley, Paul A

2017-03-01

Methods are presented for aligning the pivot point of a precessing electron probe in the scanning transmission electron microscope (STEM) and for assessing the spatial resolution in scanning precession electron diffraction (SPED) experiments. The alignment procedure is performed entirely in diffraction mode, minimising probe wander within the bright-field (BF) convergent beam electron diffraction (CBED) disk and is used to obtain high spatial resolution SPED maps. Through analysis of the power spectra of virtual bright-field images extracted from the SPED data, the precession-induced blur was measured as a function of precession angle. At low precession angles, SPED spatial resolution was limited by electronic noise in the scan coils; whereas at high precession angles SPED spatial resolution was limited by tilt-induced two-fold astigmatism caused by the positive spherical aberration of the probe-forming lens. Copyright © 2016 Elsevier B.V. All rights reserved.

Field-based landslide susceptibility assessment in a data-scarce environment: the populated areas of the Rwenzori Mountains

NASA Astrophysics Data System (ADS)

Jacobs, Liesbet; Dewitte, Olivier; Poesen, Jean; Sekajugo, John; Nobile, Adriano; Rossi, Mauro; Thiery, Wim; Kervyn, Matthieu

2018-01-01

The inhabited zone of the Ugandan Rwenzori Mountains is affected by landslides, frequently causing loss of life, damage to infrastructure and loss of livelihood. This area of ca. 1230 km2 is characterized by contrasting geomorphologic, climatic and lithological patterns, resulting in different landslide types. In this study, the spatial pattern of landslide susceptibility is investigated based on an extensive field inventory constructed for five representative areas within the region (153 km2) and containing over 450 landslides. To achieve a reliable susceptibility assessment, the effects of (1) using different topographic data sources and spatial resolutions and (2) changing the scale of assessment by comparing local and regional susceptibility models on the susceptibility model performances are investigated using a pixel-based logistic regression approach. Topographic data are extracted from different digital elevation models (DEMs) based on radar interferometry (SRTM and TanDEM-X) and optical stereophotogrammetry (ASTER DEM). Susceptibility models using the radar-based DEMs tend to outperform the ones using the ASTER DEM. The model spatial resolution is varied between 10, 20, 30 and 90 m. The optimal resolution depends on the location of the investigated area within the region but the lowest model resolution (90 m) rarely yields the best model performances while the highest model resolution (10 m) never results in significant increases in performance compared to the 20 m resolution. Models built for the local case studies generally have similar or better performances than the regional model and better reflect site-specific controlling factors. At the regional level the effect of distinguishing landslide types between shallow and deep-seated landslides is investigated. The separation of landslide types allows us to improve model performances for the prediction of deep-seated landslides and to better understand factors influencing the occurrence of shallow landslides such as tangent curvature and total rainfall. Finally, the landslide susceptibility assessment is overlaid with a population density map in order to identify potential landslide risk hotspots, which could direct research and policy action towards reduced landslide risk in this under-researched, landslide-prone region.

Effect of Electric Field Gradient on Sub-nanometer Spatial Resolution of Tip-enhanced Raman Spectroscopy

PubMed Central

Meng, Lingyan; Yang, Zhilin; Chen, Jianing; Sun, Mengtao

2015-01-01

Tip-enhanced Raman spectroscopy (TERS) with sub-nanometer spatial resolution has been recently demonstrated experimentally. However, the physical mechanism underlying is still under discussion. Here we theoretically investigate the electric field gradient of a coupled tip-substrate system. Our calculations suggest that the ultra-high spatial resolution of TERS can be partially attributed to the electric field gradient effect owning to its tighter spatial confinement and sensitivity to the infrared (IR)-active of molecules. Particularly, in the case of TERS of flat-lying H2TBPP molecules,we find the electric field gradient enhancement is the dominating factor for the high spatial resolution, which qualitatively coincides with previous experimental report. Our theoretical study offers a new paradigm for understanding the mechanisms of the ultra-high spatial resolution demonstrated in tip-enhanced spectroscopy which is of importance but neglected. PMID:25784161

Physical vs. photolithographic patterning of plasma polymers: an investigation by ToF-SSIMS and multivariate analysis

PubMed Central

Mishra, Gautam; Easton, Christopher D.; McArthur, Sally L.

2009-01-01

Physical and photolithographic techniques are commonly used to create chemical patterns for a range of technologies including cell culture studies, bioarrays and other biomedical applications. In this paper, we describe the fabrication of chemical micropatterns from commonly used plasma polymers. Atomic force microcopy (AFM) imaging, Time-of-Flight Static Secondary Ion Mass Spectrometry (ToF-SSIMS) imaging and multivariate analysis have been employed to visualize the chemical boundaries created by these patterning techniques and assess the spatial and chemical resolution of the patterns. ToF-SSIMS analysis demonstrated that well defined chemical and spatial boundaries were obtained from photolithographic patterning, while the resolution of physical patterning via a transmission electron microscopy (TEM) grid varied depending on the properties of the plasma system including the substrate material. In general, physical masking allowed diffusion of the plasma species below the mask and bleeding of the surface chemistries. Multivariate analysis techniques including Principal Component Analysis (PCA) and Region of Interest (ROI) assessment were used to investigate the ToF-SSIMS images of a range of different plasma polymer patterns. In the most challenging case, where two strongly reacting polymers, allylamine and acrylic acid were deposited, PCA confirmed the fabrication of micropatterns with defined spatial resolution. ROI analysis allowed for the identification of an interface between the two plasma polymers for patterns fabricated using the photolithographic technique which has been previously overlooked. This study clearly demonstrated the versatility of photolithographic patterning for the production of multichemistry plasma polymer arrays and highlighted the need for complimentary characterization and analytical techniques during the fabrication plasma polymer micropatterns. PMID:19950941

Diurnal Cycles of High Resolution Land Surface Temperatures (LSTs) Determined from UAV Platforms Across a Range of Surface Types

NASA Astrophysics Data System (ADS)

McCabe, M.; Rosas Aguilar, J.; Parkes, S. D.; Aragon, B.

2017-12-01

Observation of land surface temperature (LST) has many practical uses, from studying boundary layer dynamics and land-atmosphere coupling, to investigating surface properties such as soil moisture status, heat stress and surface heat fluxes. Typically, LST is observed via satellite based sensors such as LandSat or via point measurements using IR radiometers. These measurements provide either good spatial coverage and resolution or good temporal coverage. However, neither are able to provide the needed spatial and temporal resolution for many of the research applications described above. Technological developments in the use of Unmanned Aerial Vehicles (UAVs), together with small thermal frame cameras, has enabled a capacity to overcome this spatiotemporal constraint. Utilising UAV platforms to collect LST measurements across diurnal cycles provides an opportunity to study how meteorological and surface properties vary in both space and time. Here we describe the collection of LST data from a multi-rotor UAV across a study domain that is observed multiple times throughout the day. Flights over crops of Rhodes grass and alfalfa, along with a bare desert surface, were repeated with between 8 and 11 surveys covering the period from early morning to sunset. Analysis of the collected thermal imagery shows that the constructed LST maps illustrate a strong diurnal cycle consistent with expected trends, but with considerable spatial and temporal variability observed within and between the different domains. These results offer new insights into the dynamics of land surface behavior in both dry and wet soil conditions and at spatiotemporal scales that are unable to be replicated using traditional satellite platforms.

Resolving vorticity-driven lateral fire spread using the WRF-Fire coupled atmosphere-fire numerical model

NASA Astrophysics Data System (ADS)

Simpson, C. C.; Sharples, J. J.; Evans, J. P.

2014-09-01

Vorticity-driven lateral fire spread (VLS) is a form of dynamic fire behaviour, during which a wildland fire spreads rapidly across a steep leeward slope in a direction approximately transverse to the background winds. VLS is often accompanied by a downwind extension of the active flaming region and intense pyro-convection. In this study, the WRF-Fire (WRF stands for Weather Research and Forecasting) coupled atmosphere-fire model is used to examine the sensitivity of resolving VLS to both the horizontal and vertical grid spacing, and the fire-to-atmosphere coupling from within the model framework. The atmospheric horizontal and vertical grid spacing are varied between 25 and 90 m, and the fire-to-atmosphere coupling is either enabled or disabled. At high spatial resolutions, the inclusion of fire-to-atmosphere coupling increases the upslope and lateral rate of spread by factors of up to 2.7 and 9.5, respectively. This increase in the upslope and lateral rate of spread diminishes at coarser spatial resolutions, and VLS is not modelled for a horizontal and vertical grid spacing of 90 m. The lateral fire spread is driven by fire whirls formed due to an interaction between the background winds and the vertical circulation generated at the flank of the fire front as part of the pyro-convective updraft. The laterally advancing fire fronts become the dominant contributors to the extreme pyro-convection. The results presented in this study demonstrate that both high spatial resolution and two-way atmosphere-fire coupling are required to model VLS with WRF-Fire.

Spatial resolution properties of motion-compensated tomographic image reconstruction methods.

PubMed

Chun, Se Young; Fessler, Jeffrey A

2012-07-01

Many motion-compensated image reconstruction (MCIR) methods have been proposed to correct for subject motion in medical imaging. MCIR methods incorporate motion models to improve image quality by reducing motion artifacts and noise. This paper analyzes the spatial resolution properties of MCIR methods and shows that nonrigid local motion can lead to nonuniform and anisotropic spatial resolution for conventional quadratic regularizers. This undesirable property is akin to the known effects of interactions between heteroscedastic log-likelihoods (e.g., Poisson likelihood) and quadratic regularizers. This effect may lead to quantification errors in small or narrow structures (such as small lesions or rings) of reconstructed images. This paper proposes novel spatial regularization design methods for three different MCIR methods that account for known nonrigid motion. We develop MCIR regularization designs that provide approximately uniform and isotropic spatial resolution and that match a user-specified target spatial resolution. Two-dimensional PET simulations demonstrate the performance and benefits of the proposed spatial regularization design methods.

Development of a spatio-temporal disaggregation method (DisNDVI) for generating a time series of fine resolution NDVI images

NASA Astrophysics Data System (ADS)

Bindhu, V. M.; Narasimhan, B.

2015-03-01

Normalized Difference Vegetation Index (NDVI), a key parameter in understanding the vegetation dynamics, has high spatial and temporal variability. However, continuous monitoring of NDVI is not feasible at fine spatial resolution (<60 m) owing to the long revisit time needed by the satellites to acquire the fine spatial resolution data. Further, the study attains significance in the case of humid tropical regions of the earth, where the prevailing atmospheric conditions restrict availability of fine resolution cloud free images at a high temporal frequency. As an alternative to the lack of high resolution images, the current study demonstrates a novel disaggregation method (DisNDVI) which integrates the spatial information from a single fine resolution image and temporal information in terms of crop phenology from time series of coarse resolution images to generate estimates of NDVI at fine spatial and temporal resolution. The phenological variation of the pixels captured at the coarser scale provides the basis for relating the temporal variability of the pixel with the NDVI available at fine resolution. The proposed methodology was tested over a 30 km × 25 km spatially heterogeneous study area located in the south of Tamil Nadu, India. The robustness of the algorithm was assessed by an independent comparison of the disaggregated NDVI and observed NDVI obtained from concurrent Landsat ETM+ imagery. The results showed good spatial agreement across the study area dominated with agriculture and forest pixels, with a root mean square error of 0.05. The validation done at the coarser scale showed that disaggregated NDVI spatially averaged to 240 m compared well with concurrent MODIS NDVI at 240 m (R2 > 0.8). The validation results demonstrate the effectiveness of DisNDVI in improving the spatial and temporal resolution of NDVI images for utility in fine scale hydrological applications such as crop growth monitoring and estimation of evapotranspiration.

Geostationary Spectrograph (GeoSpec) for Earth and Atmospheric Science Applications

NASA Technical Reports Server (NTRS)

Janz, Scott J.

2003-01-01

GeoSpec will support several possible future mission concepts in the Atmospheric Sciences and in Land and Ocean Sciences by measurement of both chemically linked atmospheric trace gas concentrations and profiles of important molecules such as OS, N02, CH20 and SO2 and at the same time coastal and ocean pollution events, tidal effects, and the origin and evolution of aerosol plumes. The instrument design concept we will describe is a dual spectrograph covering the WMS wavelength region of 310- 481 nm and the VIS/NIR wavelength region of 500-900 nm. A third channel in the short- wave infrared (SWIR) region between 2.2 p and 2.4 pn for total column measurements of CO, CH4, and N20 will also be described. The goal is to design a system capable of making moderate spatial resolution (750 meters at nadir) hyperspectral measurements (0.2 to 1.2 nm resolution) from a geostationary orbit. This would enable studies of time- varying pollution and coastal change processes with a temporal resolution of 5 minutes on a regional scale to 1 hour on a continental scale. Technological advances in the design and fabrication of convex holographic gratings and large format, high dynamic range PIN/CMOS detectors at the focal plane will be exploited. By simply changing the focal length of the front-end telescope GeoSpec can accommodate different orbital altitudes, including low Earth orbit, the Sun-side Lagrangian point L1, and/or different spatial resolutions.

Multisensor data fusion across time and space

NASA Astrophysics Data System (ADS)

Villeneuve, Pierre V.; Beaven, Scott G.; Reed, Robert A.

2014-06-01

Field measurement campaigns typically deploy numerous sensors having different sampling characteristics for spatial, temporal, and spectral domains. Data analysis and exploitation is made more difficult and time consuming as the sample data grids between sensors do not align. This report summarizes our recent effort to demonstrate feasibility of a processing chain capable of "fusing" image data from multiple independent and asynchronous sensors into a form amenable to analysis and exploitation using commercially-available tools. Two important technical issues were addressed in this work: 1) Image spatial registration onto a common pixel grid, 2) Image temporal interpolation onto a common time base. The first step leverages existing image matching and registration algorithms. The second step relies upon a new and innovative use of optical flow algorithms to perform accurate temporal upsampling of slower frame rate imagery. Optical flow field vectors were first derived from high-frame rate, high-resolution imagery, and then finally used as a basis for temporal upsampling of the slower frame rate sensor's imagery. Optical flow field values are computed using a multi-scale image pyramid, thus allowing for more extreme object motion. This involves preprocessing imagery to varying resolution scales and initializing new vector flow estimates using that from the previous coarser-resolution image. Overall performance of this processing chain is demonstrated using sample data involving complex too motion observed by multiple sensors mounted to the same base. Multiple sensors were included, including a high-speed visible camera, up to a coarser resolution LWIR camera.

How Attention Affects Spatial Resolution

PubMed Central

Carrasco, Marisa; Barbot, Antoine

2015-01-01

We summarize and discuss a series of psychophysical studies on the effects of spatial covert attention on spatial resolution, our ability to discriminate fine patterns. Heightened resolution is beneficial in most, but not all, visual tasks. We show how endogenous attention (voluntary, goal driven) and exogenous attention (involuntary, stimulus driven) affect performance on a variety of tasks mediated by spatial resolution, such as visual search, crowding, acuity, and texture segmentation. Exogenous attention is an automatic mechanism that increases resolution regardless of whether it helps or hinders performance. In contrast, endogenous attention flexibly adjusts resolution to optimize performance according to task demands. We illustrate how psychophysical studies can reveal the underlying mechanisms of these effects and allow us to draw linking hypotheses with known neurophysiological effects of attention. PMID:25948640

MODIS Vegetative Cover Conversion and Vegetation Continuous Fields

NASA Astrophysics Data System (ADS)

Carroll, Mark; Townshend, John; Hansen, Matthew; DiMiceli, Charlene; Sohlberg, Robert; Wurster, Karl

Land cover change occurs at various spatial and temporal scales. For example, large-scale mechanical removal of forests for agro-industrial activities contrasts with the small-scale clearing of subsistence farmers. Such dynamics vary in spatial extent and rate of land conversion. Such changes are attributable to both natural and anthropogenic factors. For example, lightning- or human-ignited fires burn millions of acres of land surface each year. Further, land cover conversion requires ­contrasting with the land cover modification. In the first instance, the dynamic represents extensive categorical change between two land cover types. Land cover modification mechanisms such as selective logging and woody encroachment depict changes within a given land cover type rather than a conversion from one land cover type to another. This chapter describes the production of two standard MODIS land products used to document changes in global land cover. The Vegetative Cover Conversion (VCC) product is designed primarily to serve as a global alarm for areas where land cover change occurs rapidly (Zhan et al. 2000). The Vegetation Continuous Fields (VCF) product is designed to continuously ­represent ground cover as a proportion of basic vegetation traits. Terra's launch in December 1999 afforded a new opportunity to observe the entire Earth every 1.2 days at 250-m spatial resolution. The MODIS instrument's appropriate spatial and ­temporal resolutions provide the opportunity to substantially improve the characterization of the land surface and changes occurring thereupon (Townshend et al. 1991).

Super-resolution optical microscopy for studying membrane structure and dynamics.

PubMed

Sezgin, Erdinc

2017-07-12

Investigation of cell membrane structure and dynamics requires high spatial and temporal resolution. The spatial resolution of conventional light microscopy is limited due to the diffraction of light. However, recent developments in microscopy enabled us to access the nano-scale regime spatially, thus to elucidate the nanoscopic structures in the cellular membranes. In this review, we will explain the resolution limit, address the working principles of the most commonly used super-resolution microscopy techniques and summarise their recent applications in the biomembrane field.

Comparison of the resulting error in data fusion techniques when used with remote sensing, earth observation, and in-situ data sets for water quality applications

NASA Astrophysics Data System (ADS)

Ziemba, Alexander; El Serafy, Ghada

2016-04-01

Ecological modeling and water quality investigations are complex processes which can require a high level of parameterization and a multitude of varying data sets in order to properly execute the model in question. Since models are generally complex, their calibration and validation can benefit from the application of data and information fusion techniques. The data applied to ecological models comes from a wide range of sources such as remote sensing, earth observation, and in-situ measurements, resulting in a high variability in the temporal and spatial resolution of the various data sets available to water quality investigators. It is proposed that effective fusion into a comprehensive singular set will provide a more complete and robust data resource with which models can be calibrated, validated, and driven by. Each individual product contains a unique valuation of error resulting from the method of measurement and application of pre-processing techniques. The uncertainty and error is further compounded when the data being fused is of varying temporal and spatial resolution. In order to have a reliable fusion based model and data set, the uncertainty of the results and confidence interval of the data being reported must be effectively communicated to those who would utilize the data product or model outputs in a decision making process[2]. Here we review an array of data fusion techniques applied to various remote sensing, earth observation, and in-situ data sets whose domains' are varied in spatial and temporal resolution. The data sets examined are combined in a manner so that the various classifications, complementary, redundant, and cooperative, of data are all assessed to determine classification's impact on the propagation and compounding of error. In order to assess the error of the fused data products, a comparison is conducted with data sets containing a known confidence interval and quality rating. We conclude with a quantification of the performance of the data fusion techniques and a recommendation on the feasibility of applying of the fused products in operating forecast systems and modeling scenarios. The error bands and confidence intervals derived can be used in order to clarify the error and confidence of water quality variables produced by prediction and forecasting models. References [1] F. Castanedo, "A Review of Data Fusion Techniques", The Scientific World Journal, vol. 2013, pp. 1-19, 2013. [2] T. Keenan, M. Carbone, M. Reichstein and A. Richardson, "The model-data fusion pitfall: assuming certainty in an uncertain world", Oecologia, vol. 167, no. 3, pp. 587-597, 2011.

Stochastic speckle noise compensation in optical coherence tomography using non-stationary spline-based speckle noise modelling.

PubMed

Cameron, Andrew; Lui, Dorothy; Boroomand, Ameneh; Glaister, Jeffrey; Wong, Alexander; Bizheva, Kostadinka

2013-01-01

Optical coherence tomography (OCT) allows for non-invasive 3D visualization of biological tissue at cellular level resolution. Often hindered by speckle noise, the visualization of important biological tissue details in OCT that can aid disease diagnosis can be improved by speckle noise compensation. A challenge with handling speckle noise is its inherent non-stationary nature, where the underlying noise characteristics vary with the spatial location. In this study, an innovative speckle noise compensation method is presented for handling the non-stationary traits of speckle noise in OCT imagery. The proposed approach centers on a non-stationary spline-based speckle noise modeling strategy to characterize the speckle noise. The novel method was applied to ultra high-resolution OCT (UHROCT) images of the human retina and corneo-scleral limbus acquired in-vivo that vary in tissue structure and optical properties. Test results showed improved performance of the proposed novel algorithm compared to a number of previously published speckle noise compensation approaches in terms of higher signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and better overall visual assessment.

Stochastic speckle noise compensation in optical coherence tomography using non-stationary spline-based speckle noise modelling

PubMed Central

Cameron, Andrew; Lui, Dorothy; Boroomand, Ameneh; Glaister, Jeffrey; Wong, Alexander; Bizheva, Kostadinka

2013-01-01

Optical coherence tomography (OCT) allows for non-invasive 3D visualization of biological tissue at cellular level resolution. Often hindered by speckle noise, the visualization of important biological tissue details in OCT that can aid disease diagnosis can be improved by speckle noise compensation. A challenge with handling speckle noise is its inherent non-stationary nature, where the underlying noise characteristics vary with the spatial location. In this study, an innovative speckle noise compensation method is presented for handling the non-stationary traits of speckle noise in OCT imagery. The proposed approach centers on a non-stationary spline-based speckle noise modeling strategy to characterize the speckle noise. The novel method was applied to ultra high-resolution OCT (UHROCT) images of the human retina and corneo-scleral limbus acquired in-vivo that vary in tissue structure and optical properties. Test results showed improved performance of the proposed novel algorithm compared to a number of previously published speckle noise compensation approaches in terms of higher signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and better overall visual assessment. PMID:24049697

Multi-scale modeling of diffusion-controlled reactions in polymers: renormalisation of reactivity parameters.

PubMed

Everaers, Ralf; Rosa, Angelo

2012-01-07

The quantitative description of polymeric systems requires hierarchical modeling schemes, which bridge the gap between the atomic scale, relevant to chemical or biomolecular reactions, and the macromolecular scale, where the longest relaxation modes occur. Here, we use the formalism for diffusion-controlled reactions in polymers developed by Wilemski, Fixman, and Doi to discuss the renormalisation of the reactivity parameters in polymer models with varying spatial resolution. In particular, we show that the adjustments are independent of chain length. As a consequence, it is possible to match reactions times between descriptions with different resolution for relatively short reference chains and to use the coarse-grained model to make quantitative predictions for longer chains. We illustrate our results by a detailed discussion of the classical problem of chain cyclization in the Rouse model, which offers the simplest example of a multi-scale descriptions, if we consider differently discretized Rouse models for the same physical system. Moreover, we are able to explore different combinations of compact and non-compact diffusion in the local and large-scale dynamics by varying the embedding dimension.

The fusion of satellite and UAV data: simulation of high spatial resolution band

NASA Astrophysics Data System (ADS)

Jenerowicz, Agnieszka; Siok, Katarzyna; Woroszkiewicz, Malgorzata; Orych, Agata

2017-10-01

Remote sensing techniques used in the precision agriculture and farming that apply imagery data obtained with sensors mounted on UAV platforms became more popular in the last few years due to the availability of low- cost UAV platforms and low- cost sensors. Data obtained from low altitudes with low- cost sensors can be characterised by high spatial and radiometric resolution but quite low spectral resolution, therefore the application of imagery data obtained with such technology is quite limited and can be used only for the basic land cover classification. To enrich the spectral resolution of imagery data acquired with low- cost sensors from low altitudes, the authors proposed the fusion of RGB data obtained with UAV platform with multispectral satellite imagery. The fusion is based on the pansharpening process, that aims to integrate the spatial details of the high-resolution panchromatic image with the spectral information of lower resolution multispectral or hyperspectral imagery to obtain multispectral or hyperspectral images with high spatial resolution. The key of pansharpening is to properly estimate the missing spatial details of multispectral images while preserving their spectral properties. In the research, the authors presented the fusion of RGB images (with high spatial resolution) obtained with sensors mounted on low- cost UAV platforms and multispectral satellite imagery with satellite sensors, i.e. Landsat 8 OLI. To perform the fusion of UAV data with satellite imagery, the simulation of the panchromatic bands from RGB data based on the spectral channels linear combination, was conducted. Next, for simulated bands and multispectral satellite images, the Gram-Schmidt pansharpening method was applied. As a result of the fusion, the authors obtained several multispectral images with very high spatial resolution and then analysed the spatial and spectral accuracies of processed images.

Predicting Fish Growth Potential and Identifying Water Quality Constraints: A Spatially-Explicit Bioenergetics Approach

NASA Astrophysics Data System (ADS)

Budy, Phaedra; Baker, Matthew; Dahle, Samuel K.

2011-10-01

Anthropogenic impairment of water bodies represents a global environmental concern, yet few attempts have successfully linked fish performance to thermal habitat suitability and fewer have distinguished co-varying water quality constraints. We interfaced fish bioenergetics, field measurements, and Thermal Remote Imaging to generate a spatially-explicit, high-resolution surface of fish growth potential, and next employed a structured hypothesis to detect relationships among measures of fish performance and co-varying water quality constraints. Our thermal surface of fish performance captured the amount and spatial-temporal arrangement of thermally-suitable habitat for three focal species in an extremely heterogeneous reservoir, but interpretation of this pattern was initially confounded by seasonal covariation of water residence time and water quality. Subsequent path analysis revealed that in terms of seasonal patterns in growth potential, catfish and walleye responded to temperature, positively and negatively, respectively; crappie and walleye responded to eutrophy (negatively). At the high eutrophy levels observed in this system, some desired fishes appear to suffer from excessive cultural eutrophication within the context of elevated temperatures whereas others appear to be largely unaffected or even enhanced. Our overall findings do not lead to the conclusion that this system is degraded by pollution; however, they do highlight the need to use a sensitive focal species in the process of determining allowable nutrient loading and as integrators of habitat suitability across multiple spatial and temporal scales. We provide an integrated approach useful for quantifying fish growth potential and identifying water quality constraints on fish performance at spatial scales appropriate for whole-system management.

An inverse approach to determining spatially varying arterial compliance using ultrasound imaging

NASA Astrophysics Data System (ADS)

Mcgarry, Matthew; Li, Ronny; Apostolakis, Iason; Nauleau, Pierre; Konofagou, Elisa E.

2016-08-01

The mechanical properties of arteries are implicated in a wide variety of cardiovascular diseases, many of which are expected to involve a strong spatial variation in properties that can be depicted by diagnostic imaging. A pulse wave inverse problem (PWIP) is presented, which can produce spatially resolved estimates of vessel compliance from ultrasound measurements of the vessel wall displacements. The 1D equations governing pulse wave propagation in a flexible tube are parameterized by the spatially varying properties, discrete cosine transform components of the inlet pressure boundary conditions, viscous loss constant and a resistance outlet boundary condition. Gradient descent optimization is used to fit displacements from the model to the measured data by updating the model parameters. Inversion of simulated data showed that the PWIP can accurately recover the correct compliance distribution and inlet pressure under realistic conditions, even under high simulated measurement noise conditions. Silicone phantoms with known compliance contrast were imaged with a clinical ultrasound system. The PWIP produced spatially and quantitatively accurate maps of the phantom compliance compared to independent static property estimates, and the known locations of stiff inclusions (which were as small as 7 mm). The PWIP is necessary for these phantom experiments as the spatiotemporal resolution, measurement noise and compliance contrast does not allow accurate tracking of the pulse wave velocity using traditional approaches (e.g. 50% upstroke markers). Results from simulations indicate reflections generated from material interfaces may negatively affect wave velocity estimates, whereas these reflections are accounted for in the PWIP and do not cause problems.

Large-watershed flood simulation and forecasting based on different-resolution distributed hydrological model

NASA Astrophysics Data System (ADS)

Li, J.

2017-12-01

Large-watershed flood simulation and forecasting is very important for a distributed hydrological model in the application. There are some challenges including the model's spatial resolution effect, model performance and accuracy and so on. To cope with the challenge of the model's spatial resolution effect, different model resolution including 1000m*1000m, 600m*600m, 500m*500m, 400m*400m, 200m*200m were used to build the distributed hydrological model—Liuxihe model respectively. The purpose is to find which one is the best resolution for Liuxihe model in Large-watershed flood simulation and forecasting. This study sets up a physically based distributed hydrological model for flood forecasting of the Liujiang River basin in south China. Terrain data digital elevation model (DEM), soil type and land use type are downloaded from the website freely. The model parameters are optimized by using an improved Particle Swarm Optimization(PSO) algorithm; And parameter optimization could reduce the parameter uncertainty that exists for physically deriving model parameters. The different model resolution (200m*200m—1000m*1000m ) are proposed for modeling the Liujiang River basin flood with the Liuxihe model in this study. The best model's spatial resolution effect for flood simulation and forecasting is 200m*200m.And with the model's spatial resolution reduction, the model performance and accuracy also become worse and worse. When the model resolution is 1000m*1000m, the flood simulation and forecasting result is the worst, also the river channel divided based on this resolution is differs from the actual one. To keep the model with an acceptable performance, minimum model spatial resolution is needed. The suggested threshold model spatial resolution for modeling the Liujiang River basin flood is a 500m*500m grid cell, but the model spatial resolution with a 200m*200m grid cell is recommended in this study to keep the model at a best performance.

Analysis of the impact of spatial resolution on land/water classifications using high-resolution aerial imagery

USGS Publications Warehouse

Enwright, Nicholas M.; Jones, William R.; Garber, Adrienne L.; Keller, Matthew J.

2014-01-01

Long-term monitoring efforts often use remote sensing to track trends in habitat or landscape conditions over time. To most appropriately compare observations over time, long-term monitoring efforts strive for consistency in methods. Thus, advances and changes in technology over time can present a challenge. For instance, modern camera technology has led to an increasing availability of very high-resolution imagery (i.e. submetre and metre) and a shift from analogue to digital photography. While numerous studies have shown that image resolution can impact the accuracy of classifications, most of these studies have focused on the impacts of comparing spatial resolution changes greater than 2 m. Thus, a knowledge gap exists on the impacts of minor changes in spatial resolution (i.e. submetre to about 1.5 m) in very high-resolution aerial imagery (i.e. 2 m resolution or less). This study compared the impact of spatial resolution on land/water classifications of an area dominated by coastal marsh vegetation in Louisiana, USA, using 1:12,000 scale colour-infrared analogue aerial photography (AAP) scanned at four different dot-per-inch resolutions simulating ground sample distances (GSDs) of 0.33, 0.54, 1, and 2 m. Analysis of the impact of spatial resolution on land/water classifications was conducted by exploring various spatial aspects of the classifications including density of waterbodies and frequency distributions in waterbody sizes. This study found that a small-magnitude change (1–1.5 m) in spatial resolution had little to no impact on the amount of water classified (i.e. percentage mapped was less than 1.5%), but had a significant impact on the mapping of very small waterbodies (i.e. waterbodies ≤ 250 m2). These findings should interest those using temporal image classifications derived from very high-resolution aerial photography as a component of long-term monitoring programs.

Polymeric spatial resolution test patterns for mass spectrometry imaging using nano-thermal analysis with atomic force microscopy

DOE PAGES

Tai, Tamin; Kertesz, Vilmos; Lin, Ming -Wei; ...

2017-05-11

As the spatial resolution of mass spectrometry imaging technologies has begun to reach into the nanometer regime, finding readily available or easily made resolution reference materials has become particularly challenging for molecular imaging purposes. This study describes the fabrication, characterization and use of vertical line array polymeric spatial resolution test patterns for nano-thermal analysis/atomic force microscopy/mass spectrometry chemical imaging.

Polymeric spatial resolution test patterns for mass spectrometry imaging using nano-thermal analysis with atomic force microscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tai, Tamin; Kertesz, Vilmos; Lin, Ming -Wei

As the spatial resolution of mass spectrometry imaging technologies has begun to reach into the nanometer regime, finding readily available or easily made resolution reference materials has become particularly challenging for molecular imaging purposes. This study describes the fabrication, characterization and use of vertical line array polymeric spatial resolution test patterns for nano-thermal analysis/atomic force microscopy/mass spectrometry chemical imaging.

Spatial Variations in Drought Persistence in the South-Central U.S.

NASA Astrophysics Data System (ADS)

Leasor, Z. T.; Quiring, S. M.

2016-12-01

Drought is one of the most prominent climatic hazards in the south-central United States. This study examines spatial variations in meteorological drought persistence using high-resolution PRISM gridded precipitation data from 1900-2015. The Standardized Precipitation Index (SPI) is used to represent meteorological drought conditions. The study region covers Texas, Oklahoma, and Kansas. Droughts are first divided into different severity categories using the classification employed by the U.S. National Drought Monitor. The frequency and duration of each drought event is determined and this is used to calculate drought persistence. Our results indicate that drought persistence in the south-central U.S. varies as a function of drought severity. In addition, drought persistence also varies substantially over space and time. The probability of drought termination is a function of drought severity, geographic location and time of the year. In addition, there is evidence that drought persistence is influenced by global teleconnections and land-atmosphere interactions. The results of this drought persistence climatology can benefit seasonal forecasting and the current understanding of drought recovery.

High density event-related potential data acquisition in cognitive neuroscience.

PubMed

Slotnick, Scott D

2010-04-16

Functional magnetic resonance imaging (fMRI) is currently the standard method of evaluating brain function in the field of Cognitive Neuroscience, in part because fMRI data acquisition and analysis techniques are readily available. Because fMRI has excellent spatial resolution but poor temporal resolution, this method can only be used to identify the spatial location of brain activity associated with a given cognitive process (and reveals virtually nothing about the time course of brain activity). By contrast, event-related potential (ERP) recording, a method that is used much less frequently than fMRI, has excellent temporal resolution and thus can track rapid temporal modulations in neural activity. Unfortunately, ERPs are under utilized in Cognitive Neuroscience because data acquisition techniques are not readily available and low density ERP recording has poor spatial resolution. In an effort to foster the increased use of ERPs in Cognitive Neuroscience, the present article details key techniques involved in high density ERP data acquisition. Critically, high density ERPs offer the promise of excellent temporal resolution and good spatial resolution (or excellent spatial resolution if coupled with fMRI), which is necessary to capture the spatial-temporal dynamics of human brain function.

Hyperspectral imagery super-resolution by compressive sensing inspired dictionary learning and spatial-spectral regularization.

PubMed

Huang, Wei; Xiao, Liang; Liu, Hongyi; Wei, Zhihui

2015-01-19

Due to the instrumental and imaging optics limitations, it is difficult to acquire high spatial resolution hyperspectral imagery (HSI). Super-resolution (SR) imagery aims at inferring high quality images of a given scene from degraded versions of the same scene. This paper proposes a novel hyperspectral imagery super-resolution (HSI-SR) method via dictionary learning and spatial-spectral regularization. The main contributions of this paper are twofold. First, inspired by the compressive sensing (CS) framework, for learning the high resolution dictionary, we encourage stronger sparsity on image patches and promote smaller coherence between the learned dictionary and sensing matrix. Thus, a sparsity and incoherence restricted dictionary learning method is proposed to achieve higher efficiency sparse representation. Second, a variational regularization model combing a spatial sparsity regularization term and a new local spectral similarity preserving term is proposed to integrate the spectral and spatial-contextual information of the HSI. Experimental results show that the proposed method can effectively recover spatial information and better preserve spectral information. The high spatial resolution HSI reconstructed by the proposed method outperforms reconstructed results by other well-known methods in terms of both objective measurements and visual evaluation.

Atmospheric Moisture Budget and Spatial Resolution Dependence of Precipitation Extremes in Aquaplanet Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Qing; Leung, Lai-Yung R.; Rauscher, Sara

This study investigates the resolution dependency of precipitation extremes in an aqua-planet framework. Strong resolution dependency of precipitation extremes is seen over both tropics and extra-tropics, and the magnitude of this dependency also varies with dynamical cores. Moisture budget analyses based on aqua-planet simulations with the Community Atmosphere Model (CAM) using the Model for Prediction Across Scales (MPAS) and High Order Method Modeling Environment (HOMME) dynamical cores but the same physics parameterizations suggest that during precipitation extremes moisture supply for surface precipitation is mainly derived from advective moisture convergence. The resolution dependency of precipitation extremes mainly originates from advective moisturemore » transport in the vertical direction. At most vertical levels over the tropics and in the lower atmosphere over the subtropics, the vertical eddy transport of mean moisture field dominates the contribution to precipitation extremes and its resolution dependency. Over the subtropics, the source of moisture, its associated energy, and the resolution dependency during extremes are dominated by eddy transport of eddies moisture at the mid- and upper-troposphere. With both MPAS and HOMME dynamical cores, the resolution dependency of the vertical advective moisture convergence is mainly explained by dynamical changes (related to vertical velocity or omega), although the vertical gradients of moisture act like averaging kernels to determine the sensitivity of the overall resolution dependency to the changes in omega at different vertical levels. The natural reduction of variability with coarser resolution, represented by areal data averaging (aggregation) effect, largely explains the resolution dependency in omega. The thermodynamic changes, which likely result from non-linear feedback in response to the large dynamical changes, are small compared to the overall changes in dynamics (omega). However, after excluding the data aggregation effect in omega, thermodynamic changes become relatively significant in offsetting the effect of dynamics leading to reduce differences between the simulated and aggregated results. Compared to MPAS, the simulated stronger vertical motion with HOMME also results in larger resolution dependency. Compared to the simulation at fine resolution, the vertical motion during extremes is insufficiently resolved/parameterized at the coarser resolution even after accounting for the natural reduction in variability with coarser resolution, and this is more distinct in the simulation with HOMME. To reduce uncertainties in simulated precipitation extremes, future development in cloud parameterizations must address their sensitivity to spatial resolution as well as dynamical cores.« less

Combining InSAR and GPS to Determine Transient Movement and Thickness of a Seasonally Active Low-Gradient Translational Landslide

NASA Astrophysics Data System (ADS)

Hu, Xie; Lu, Zhong; Pierson, Thomas C.; Kramer, Rebecca; George, David L.

2018-02-01

The combined application of continuous Global Positioning System data (high temporal resolution) with spaceborne interferometric synthetic aperture radar data (high spatial resolution) can reveal much more about the complexity of large landslide movement than is possible with geodetic measurements tied to only a few specific measurement sites. This approach is applied to an 4 km2 reactivated translational landslide in the Columbia River Gorge (Washington State), which moves mainly during the winter rainy season. Results reveal the complex three-dimensional shape of the landslide mass, how onset of sliding relates to cumulative rainfall, how surface velocity during sliding varies with location on the topographically complex landslide surface, and how the ground surface subsides slightly in weeks prior to downslope sliding.

Combining InSAR and GPS to determine transient movement and thickness of a seasonally active low-gradient translational landslide

USGS Publications Warehouse

Hu, Xie; Lu, Zhong; Pierson, Thomas C.; Kramer, Rebecca; George, David L.

2018-01-01

The combined application of continuous Global Positioning System data (high temporal resolution) with spaceborne interferometric synthetic aperture radar data (high spatial resolution) can reveal much more about the complexity of large landslide movement than is possible with geodetic measurements tied to only a few specific measurement sites. This approach is applied to an ~4 km2 reactivated translational landslide in the Columbia River Gorge (Washington State), which moves mainly during the winter rainy season. Results reveal the complex three-dimensional shape of the landslide mass, how onset of sliding relates to cumulative rainfall, how surface velocity during sliding varies with location on the topographically complex landslide surface, and how the ground surface subsides slightly in weeks prior to downslope sliding.

Uranus' cloud structure and scattering particle properties from IRTF SpeX observations

NASA Astrophysics Data System (ADS)

Tice, D. S.; Irwin, P. G. J.; Fletcher, L. N.; Teanby, N. A.; Orton, G. S.; Davis, G. R.

2011-10-01

Observations of Uranus were made in August 2009 with the SpeX spectrograph at the NASA Infrared Telescope Facility (IRTF). Analysed spectra range from 0.8 to 1.8 μm at a spatial resolution of 0.5" and a spectral resolution of R = 1,200. Spectra from 0.818 to 0.834 μm, a region characterised by both strong hydrogen quadrupole and methane absorptions are considered to determine methane content. Evidence indicates that methane abundance varies with latitude. NEMESIS, an optimal estimation retrieval code with full-scattering capability, is employed to analyse the full range of data. Cloud and haze properties in the upper troposphere and stratosphere are characterised, and are consistent with other current literature. New information on single scattering albedos and particle size distributions are inferred.

Overset grid applications on distributed memory MIMD computers

NASA Technical Reports Server (NTRS)

Chawla, Kalpana; Weeratunga, Sisira

1994-01-01

Analysis of modern aerospace vehicles requires the computation of flowfields about complex three dimensional geometries composed of regions with varying spatial resolution requirements. Overset grid methods allow the use of proven structured grid flow solvers to address the twin issues of geometrical complexity and the resolution variation by decomposing the complex physical domain into a collection of overlapping subdomains. This flexibility is accompanied by the need for irregular intergrid boundary communication among the overlapping component grids. This study investigates a strategy for implementing such a static overset grid implicit flow solver on distributed memory, MIMD computers; i.e., the 128 node Intel iPSC/860 and the 208 node Intel Paragon. Performance data for two composite grid configurations characteristic of those encountered in present day aerodynamic analysis are also presented.

Demonstration of Airborne Wide Area Assessment Technologies at Pueblo Precision Bombing Ranges, Colorado. Hyperspectral Imaging, Version 2.0

DTIC Science & Technology

2007-09-27

the spatial and spectral resolution ...variety of geological and vegetation mapping efforts, the Hymap sensor offered the best available combination of spectral and spatial resolution , signal... The limitations of the technology currently relate to spatial and spectral resolution and geo- correction accuracy. Secondly, HSI datasets

The effect of spatial resolution upon cloud optical property retrievals. I - Optical thickness

NASA Technical Reports Server (NTRS)

Feind, Rand E.; Christopher, Sundar A.; Welch, Ronald M.

1992-01-01

High spectral and spatial resolution Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery is used to study the effects of spatial resolution upon fair weather cumulus cloud optical thickness retrievals. As a preprocessing step, a variation of the Gao and Goetz three-band ratio technique is used to discriminate clouds from the background. The combination of the elimination of cloud shadow pixels and using the first derivative of the histogram allows for accurate cloud edge discrimination. The data are progressively degraded from 20 m to 960 m spatial resolution. The results show that retrieved cloud area increases with decreasing spatial resolution. The results also show that there is a monotonic decrease in retrieved cloud optical thickness with decreasing spatial resolution. It is also demonstrated that the use of a single, monospectral reflectance threshold is inadequate for identifying cloud pixels in fair weather cumulus scenes and presumably in any inhomogeneous cloud field. Cloud edges have a distribution of reflectance thresholds. The incorrect identification of cloud edges significantly impacts the accurate retrieval of cloud optical thickness values.

Emotional cues enhance the attentional effects on spatial and temporal resolution.

PubMed

Bocanegra, Bruno R; Zeelenberg, René

2011-12-01

In the present study, we demonstrated that the emotional significance of a spatial cue enhances the effect of covert attention on spatial and temporal resolution (i.e., our ability to discriminate small spatial details and fast temporal flicker). Our results indicated that fearful face cues, as compared with neutral face cues, enhanced the attentional benefits in spatial resolution but also enhanced the attentional deficits in temporal resolution. Furthermore, we observed that the overall magnitudes of individuals' attentional effects correlated strongly with the magnitude of the emotion × attention interaction effect. Combined, these findings provide strong support for the idea that emotion enhances the strength of a cue's attentional response.

HESS Opinions: The need for process-based evaluation of large-domain hyper-resolution models

NASA Astrophysics Data System (ADS)

Melsen, Lieke A.; Teuling, Adriaan J.; Torfs, Paul J. J. F.; Uijlenhoet, Remko; Mizukami, Naoki; Clark, Martyn P.

2016-03-01

A meta-analysis on 192 peer-reviewed articles reporting on applications of the variable infiltration capacity (VIC) model in a distributed way reveals that the spatial resolution at which the model is applied has increased over the years, while the calibration and validation time interval has remained unchanged. We argue that the calibration and validation time interval should keep pace with the increase in spatial resolution in order to resolve the processes that are relevant at the applied spatial resolution. We identified six time concepts in hydrological models, which all impact the model results and conclusions. Process-based model evaluation is particularly relevant when models are applied at hyper-resolution, where stakeholders expect credible results both at a high spatial and temporal resolution.

HESS Opinions: The need for process-based evaluation of large-domain hyper-resolution models

NASA Astrophysics Data System (ADS)

Melsen, L. A.; Teuling, A. J.; Torfs, P. J. J. F.; Uijlenhoet, R.; Mizukami, N.; Clark, M. P.

2015-12-01

A meta-analysis on 192 peer-reviewed articles reporting applications of the Variable Infiltration Capacity (VIC) model in a distributed way reveals that the spatial resolution at which the model is applied has increased over the years, while the calibration and validation time interval has remained unchanged. We argue that the calibration and validation time interval should keep pace with the increase in spatial resolution in order to resolve the processes that are relevant at the applied spatial resolution. We identified six time concepts in hydrological models, which all impact the model results and conclusions. Process-based model evaluation is particularly relevant when models are applied at hyper-resolution, where stakeholders expect credible results both at a high spatial and temporal resolution.

Evaluation of Satellite Remote Sensing Albedo Retrievals over the Ablation Area of the Southwestern Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Moustafa, Samiah E.; Rennermalm, Asa K.; Roman, Miguel O.; Wang, Zhuosen; Schaaf, Crystal B.; Smith, Laurence C.; Koenig, Lora S.; Erb, Angela

2017-01-01

MODerate resolution Imaging Spectroradiometer (MODIS) albedo products have been validated over spatially uniform, snow-covered areas of the Greenland ice sheet (GrIS) using the so-called single 'point-to-pixel' method. This study expands on this methodology by applying a 'multiple-point-to-pixel' method and examination of spatial autocorrelation (here using semivariogram analysis) by using in situ observations, high-resolution World- View-2 (WV-2) surface reflectances, and MODIS Collection V006 daily blue-sky albedo over a spatially heterogeneous surfaces in the lower ablation zone in southwest Greenland. Our results using 232 ground-based samples within two MODIS pixels, one being more spatial heterogeneous than the other, show little difference in accuracy among narrow and broad band albedos (except for Band 2). Within the more homogenous pixel area, in situ and MODIS albedos were very close (error varied from -4% to +7%) and within the range of ASD standard errors. The semivariogram analysis revealed that the minimum observational footprint needed for a spatially representative sample is 30 m. In contrast, over the more spatially heterogeneous surface pixel, a minimum footprint size was not quantifiable due to spatial autocorrelation, and far exceeds the effective resolution of the MODIS retrievals. Over the high spatial heterogeneity surface pixel, MODIS is lower than ground measurements by 4-7%, partly due to a known in situ undersampling of darker surfaces that often are impassable by foot (e.g., meltwater features and shadowing effects over crevasses). Despite the sampling issue, our analysis errors are very close to the stated general accuracy of the MODIS product of 5%. Thus, our study suggests that the MODIS albedo product performs well in a very heterogeneous, low-albedo, area of the ice sheet ablation zone. Furthermore, we demonstrate that single 'point-to-pixel' methods alone are insufficient in characterizing and validating the variation of surface albedo displayed in the lower ablation area. This is true because the distribution of in situ data deviations from MODIS albedo show a substantial range, with the average values for the 10th and 90th percentiles being -0.30 and 0.43 across all bands. Thus, if only single point is taken for ground validation, and is randomly selected from either distribution tails, the error would appear to be considerable. Given the need for multiple in-situ points, concurrent albedo measurements derived from existing AWSs, (low-flying vehicles (airborne or unmanned) and high-resolution imagery (WV-2)) are needed to resolve high sub-pixel variability in the ablation zone, and thus, further improve our characterization of Greenland's surface albedo.

The influence of different signal-to-background ratios on spatial resolution and F18-FDG-PET quantification using point spread function and time-of-flight reconstruction.

PubMed

Rogasch, Julian Mm; Hofheinz, Frank; Lougovski, Alexandr; Furth, Christian; Ruf, Juri; Großer, Oliver S; Mohnike, Konrad; Hass, Peter; Walke, Mathias; Amthauer, Holger; Steffen, Ingo G

2014-12-01

F18-fluorodeoxyglucose positron-emission tomography (FDG-PET) reconstruction algorithms can have substantial influence on quantitative image data used, e.g., for therapy planning or monitoring in oncology. We analyzed radial activity concentration profiles of differently reconstructed FDG-PET images to determine the influence of varying signal-to-background ratios (SBRs) on the respective spatial resolution, activity concentration distribution, and quantification (standardized uptake value [SUV], metabolic tumor volume [MTV]). Measurements were performed on a Siemens Biograph mCT 64 using a cylindrical phantom containing four spheres (diameter, 30 to 70 mm) filled with F18-FDG applying three SBRs (SBR1, 16:1; SBR2, 6:1; SBR3, 2:1). Images were reconstructed employing six algorithms (filtered backprojection [FBP], FBP + time-of-flight analysis [FBP + TOF], 3D-ordered subset expectation maximization [3D-OSEM], 3D-OSEM + TOF, point spread function [PSF], PSF + TOF). Spatial resolution was determined by fitting the convolution of the object geometry with a Gaussian point spread function to radial activity concentration profiles. MTV delineation was performed using fixed thresholds and semiautomatic background-adapted thresholding (ROVER, ABX, Radeberg, Germany). The pairwise Wilcoxon test revealed significantly higher spatial resolutions for PSF + TOF (up to 4.0 mm) compared to PSF, FBP, FBP + TOF, 3D-OSEM, and 3D-OSEM + TOF at all SBRs (each P < 0.05) with the highest differences for SBR1 decreasing to the lowest for SBR3. Edge elevations in radial activity profiles (Gibbs artifacts) were highest for PSF and PSF + TOF declining with decreasing SBR (PSF + TOF largest sphere; SBR1, 6.3%; SBR3, 2.7%). These artifacts induce substantial SUVmax overestimation compared to the reference SUV for PSF algorithms at SBR1 and SBR2 leading to substantial MTV underestimation in threshold-based segmentation. In contrast, both PSF algorithms provided the lowest deviation of SUVmean from reference SUV at SBR1 and SBR2. At high contrast, the PSF algorithms provided the highest spatial resolution and lowest SUVmean deviation from the reference SUV. In contrast, both algorithms showed the highest deviations in SUVmax and threshold-based MTV definition. At low contrast, all investigated reconstruction algorithms performed approximately equally. The use of PSF algorithms for quantitative PET data, e.g., for target volume definition or in serial PET studies, should be performed with caution - especially if comparing SUV of lesions with high and low contrasts.

Effect of spatial resolution on remote sensing estimation of total evaporation in the uMngeni catchment, South Africa

NASA Astrophysics Data System (ADS)

Shoko, Cletah; Clark, David; Mengistu, Michael; Dube, Timothy; Bulcock, Hartley

2015-01-01

This study evaluated the effect of two readily available multispectral sensors: the newly launched 30 m spatial resolution Landsat 8 and the long-serving 1000 m moderate resolution imaging spectroradiometer (MODIS) datasets in the spatial representation of total evaporation in the heterogeneous uMngeni catchment, South Africa, using the surface energy balance system model. The results showed that sensor spatial resolution plays a critical role in the accurate estimation of energy fluxes and total evaporation across a heterogeneous catchment. Landsat 8 estimates showed better spatial representation of the biophysical parameters and total evaporation for different land cover types, due to the relatively higher spatial resolution compared to the coarse spatial resolution MODIS sensor. Moreover, MODIS failed to capture the spatial variations of total evaporation estimates across the catchment. Analysis of variance (ANOVA) results showed that MODIS-based total evaporation estimates did not show any significant differences across different land cover types (one-way ANOVA; F1.924=1.412, p=0.186). However, Landsat 8 images yielded significantly different estimates between different land cover types (one-way ANOVA; F1.993=5.185, p<0.001). The validation results showed that Landsat 8 estimates were more comparable to eddy covariance (EC) measurements than the MODIS-based total evaporation estimates. EC measurement on May 23, 2013, was 3.8 mm/day, whereas the Landsat 8 estimate on the same day was 3.6 mm/day, with MODIS showing significantly lower estimates of 2.3 mm/day. The findings of this study underscore the importance of spatial resolution in estimating spatial variations of total evaporation at the catchment scale, thus, they provide critical information on the relevance of the readily available remote sensing products in water resources management in data-scarce environments.

Spatial resolution limits for the isotropic-3D PET detector X’tal cube

NASA Astrophysics Data System (ADS)

Yoshida, Eiji; Tashima, Hideaki; Hirano, Yoshiyuki; Inadama, Naoko; Nishikido, Fumihiko; Murayama, Hideo; Yamaya, Taiga

2013-11-01

Positron emission tomography (PET) has become a popular imaging method in metabolism, neuroscience, and molecular imaging. For dedicated human brain and small animal PET scanners, high spatial resolution is needed to visualize small objects. To improve the spatial resolution, we are developing the X’tal cube, which is our new PET detector to achieve isotropic 3D positioning detectability. We have shown that the X’tal cube can achieve 1 mm3 uniform crystal identification performance with the Anger-type calculation even at the block edges. We plan to develop the X’tal cube with even smaller 3D grids for sub-millimeter crystal identification. In this work, we investigate spatial resolution of a PET scanner based on the X’tal cube using Monte Carlo simulations for predicting resolution performance in smaller 3D grids. For spatial resolution evaluation, a point source emitting 511 keV photons was simulated by GATE for all physical processes involved in emission and interaction of positrons. We simulated two types of animal PET scanners. The first PET scanner had a detector ring 14.6 cm in diameter composed of 18 detectors. The second PET scanner had a detector ring 7.8 cm in diameter composed of 12 detectors. After the GATE simulations, we converted the interacting 3D position information to digitalized positions for realistic segmented crystals. We simulated several X’tal cubes with cubic crystals from (0.5 mm)3 to (2 mm)3 in size. Also, for evaluating the effect of DOI resolution, we simulated several X’tal cubes with crystal thickness from (0.5 mm)3 to (9 mm)3. We showed that sub-millimeter spatial resolution was possible using cubic crystals smaller than (1.0 mm)3 even with the assumed physical processes. Also, the weighted average spatial resolutions of both PET scanners with (0.5 mm)3 cubic crystals were 0.53 mm (14.6 cm ring diameter) and 0.48 mm (7.8 cm ring diameter). For the 7.8 cm ring diameter, spatial resolution with 0.5×0.5×1.0 mm3 crystals was improved 39% relative to the (1 mm)3 cubic crystals. On the other hand, spatial resolution with (0.5 mm)3 cubic crystals was improved 47% relative to the (1 mm)3 cubic crystals. The X’tal cube promises better spatial resolution for the 3D crystal block with isotropic resolution.

Progress toward accurate high spatial resolution actinide analysis by EPMA

NASA Astrophysics Data System (ADS)

Jercinovic, M. J.; Allaz, J. M.; Williams, M. L.

2010-12-01

High precision, high spatial resolution EPMA of actinides is a significant issue for geochronology, resource geochemistry, and studies involving the nuclear fuel cycle. Particular interest focuses on understanding of the behavior of Th and U in the growth and breakdown reactions relevant to actinide-bearing phases (monazite, zircon, thorite, allanite, etc.), and geochemical fractionation processes involving Th and U in fluid interactions. Unfortunately, the measurement of minor and trace concentrations of U in the presence of major concentrations of Th and/or REEs is particularly problematic, especially in complexly zoned phases with large compositional variation on the micro or nanoscale - spatial resolutions now accessible with modern instruments. Sub-micron, high precision compositional analysis of minor components is feasible in very high Z phases where scattering is limited at lower kV (15kV or less) and where the beam diameter can be kept below 400nm at high current (e.g. 200-500nA). High collection efficiency spectrometers and high performance electron optics in EPMA now allow the use of lower overvoltage through an exceptional range in beam current, facilitating higher spatial resolution quantitative analysis. The U LIII edge at 17.2 kV precludes L-series analysis at low kV (high spatial resolution), requiring careful measurements of the actinide M series. Also, U-La detection (wavelength = 0.9A) requires the use of LiF (220) or (420), not generally available on most instruments. Strong peak overlaps of Th on U make highly accurate interference correction mandatory, with problems compounded by the ThMIV and ThMV absorption edges affecting peak, background, and interference calibration measurements (especially the interference of the Th M line family on UMb). Complex REE bearing phases such as monazite, zircon, and allanite have particularly complex interference issues due to multiple peak and background overlaps from elements present in the activation volume, as well as interferences from fluorescence at a distance from adjacent phases or distinct compositional domains in the same phase. Interference corrections for elements detected during boundary fluorescence are further complicated by X-ray focusing geometry considerations. Additional complications arise from the high current densities required for high spatial resolution and high count precision, such as fluctuations in internal charge distribution and peak shape changes as satellite production efficiency varies from calibration to analysis. No flawless method has yet emerged. Extreme care in interference corrections, especially where multiple and sometime mutual overlaps are present, and maximum care (and precision) in background characterization to account for interferences and curvature (e.g., WDS scan or multipoint regression), are crucial developments. Calibration curves from multiple peak and interference calibration measurements at different concentrations, and iterative software methodologies for incorporating absorption edge effects, and non-linearities in interference corrections due to peak shape changes and off-axis X-ray defocussing during boundary fluorescence at a distance, are directions with significant potential.

The ASTER emergency scheduling system: A new project linking near-real-time satellite monitoring of disasters to the acquisition of high-resolution remote sensing data

NASA Astrophysics Data System (ADS)

Ramsey, M.; Dehn, J.; Wessels, R.; Byrnes, J.; Duda, K.; Maldonado, L.; Dwyer, J.

2004-12-01

Numerous government agencies and university partnerships are currently utilizing orbital instruments with high-temporal/low-spatial resolution (e.g. MODIS, AVHRR) to monitor hazards. These hazards are varied and include both natural (volcanic eruptions, severe weather, wildfires, earthquake damage) and anthropogenic (environmental damage, urban terrorism). Although monitoring a hazardous situation is critical, a key strategy of NASA's Earth science program is to develop a scientific understanding of the Earth system and its responses to changes, as well as to improve prediction of hazard onset. In order to develop a quantitative scientific basis from which to model transient geological and climatological hazards, much higher spatial/spectral resolution datasets are required. Such datasets are sparse, currently available from certain government (e.g. ASTER, Hyperion) and commercial (e.g. IKONOS, QuickBird) instruments. However, only ASTER has the capability to acquire high spatial resolution data from the visible to thermal infrared (TIR) wavelength region in conjunction with digital elevation models (DEM) generation. These capabilities are particularly useful for numerous aspects of volcanic remote sensing. For example, multispectral TIR data are critical for monitoring low temperature anomalies and mapping both chemical and textural variations on volcanic surfaces. Because ASTER data are scheduled in advance and the raw data are sent to Japan for calibration processing, rapid acquisition of hazards becomes problematic. However, a "rapid response" mode does exist for ASTER data scheduling and processing, but its availability is limited and requires significant human interaction. A newly-funded NASA ASTER science team project seeks to link this ASTER rapid response pathway to larger-scale monitoring alerts, which are already in-place and in-use by other organizations. By refining the initial event detection criteria and improving interfaces between these organizations and the ASTER project, we expect to minimize lag time and use existing monitoring tools as triggers for the emergency response of ASTER. The first phase of this project will be integrated into the Alaska Volcano Observatory's current near-real-time volcanic monitoring system, which relies on high temporal/low spatial resolution orbital data. This synergy will allow small-scale activity to be targeted for science and response, and a calibration baseline between each sensor to be established. If successful, this will be the first time that high spatial resolution, multispectral satellite data will be routinely scheduled, acquired, and analyzed in a "rapid response" mode within an existing hazard monitoring framework. Initial testing of this system is now underway using data from previous eruptions in the north Pacific region, and modifications to the rapid data flow procedure within the ASTER science and support structure has begun.

Characterizing tree canopy temperature heterogeneity using an unmanned aircraft-borne thermal imager

NASA Astrophysics Data System (ADS)

Messinger, M.; Powell, R.; Silman, M.; Wright, M.; Nicholson, W.

2013-12-01

Leaf temperature (Tleaf) is an important control on many physiological processes such as photosynthesis and respiration, is a key variable for characterizing canopy energy fluxes, and is a valuable metric for identifying plant water stress or disease. Traditional methods of Tleaf measurement involve either the use of thermocouples, a time and labor-intensive method that samples sparsely in space, or the use of air temperature (Tair) as a proxy measure, which can introduce inaccuracies due to near constant canopy-atmosphere energy flux. Thermal infrared (TIR) imagery provides an efficient means of collecting Tleaf for large areas. Existing satellite and aircraft-based TIR imagery is, however, limited by low spatial and/or temporal resolution, while crane-mounted camera systems have strictly limited spatial extents. Unmanned aerial systems (UAS) offer new opportunities to acquire high spatial and temporal resolution imagery on demand. Here, we demonstrate the feasibility of collecting tree canopy Tleaf data using a small multirotor UAS fitted with a high spatial resolution TIR imager. The goals of this pilot study were to a) characterize basic patterns of within crown Tleaf for 4 study species and b) identify trends in Tleaf between species with varying leaf morphologies and canopy structures. TIR imagery was acquired for individual tree crowns of 4 species common to the North Carolina Piedmont ecoregion (Quercus phellos, Pinus strobus, Liriodendron tulipifera, Magnolia grandiflora) in an urban park environment. Due to significantly above-average summer precipitation, we assumed that none of the sampled trees was limited by soil water availability. We flew the TIR imaging system over 3-4 individuals of each of the 4 target species on 3 separate days. Imagery of all individuals was collected within the same 2-hour period in the afternoon on all days. There was low wind and partly cloudy skies during imaging. Tair, relative humidity, and wind speed were recorded at each site. Emissivity was assumed to be 0.98 for all species. Acquired images had a pixel resolution of <3 cm and measurement accuracy of ×1° C. We found the UAS-borne TIR imaging system to be an effective tool for collection of high resolution canopy imagery. The system imaged all targeted crowns quickly and reliably, providing a viable alternative to current methods of canopy Tleaf measurement. Analysis of the imagery indicated significant variability in Tleaf both within and between crowns. We identified trends in Tleaf related to average leaf size, shape, and crown structural traits. These data on the heterogeneity of Tleaf can further our understanding of canopy-atmosphere energy exchange. This pilot study demonstrates the promise of UAS-borne TIR sensors for acquiring high spatial resolution imagery at the scale of individual tree crowns.

Spatial resolution limitation of liquid crystal spatial light modulator

NASA Astrophysics Data System (ADS)

Wang, Xinghua; Wang, Bin; McManamon, Paul F., III; Pouch, John J.; Miranda, Felix A.; Anderson, James E.; Bos, Philip J.

2004-10-01

The effect of fringing electric fields in a liquid crystal (LC) Optical Phased Array (OPA), also referred to as a spatial light modulator (SLM), is a governing factor that determines the diffraction efficiency (DE) of the LC OPA for high resolution spatial phase modulation. In this article, the fringing field effect in a high resolution LC OPA is studied by accurate modeling the DE of the LC blazed gratings by LC director simulation and Finite Difference Time Domain (FDTD) simulation. Influence factors that contribute significantly to the DE are discussed. Such results provide fundamental understanding for high resolution LC devices.

The Use of High-Resolution Pléiades Images to Extract Volcanic-Cloud Top Heights and Plume Elevation Models: examples on Mount Etna (Italy) and Mount Ontake (Japan)

NASA Astrophysics Data System (ADS)

de Michele, Marcello; Raucoules, Daniel; Corradini, Stefano; Merucci, Luca; spinetti, claudia

2017-04-01

Accurate and spatially-detailed knowledge of Volcanic Cloud Top Height (VCTH) and velocity is crucial in volcanology. As an example, the ash/gas dispersion in the atmosphere, their impact and lifetime around the globe, greatly depends on the injection altitude. The VCTH is critical for ash dispersion modelling and air traffic security. Furthermore, the volcanic plume height during explosive volcanism is the primary parameter for estimating mass eruption rate. Satellite remote sensing offers a comprehensive and safe way to estimate VCTH. Recently, it has been shown that high spatial resolution optical imagery from Landsat-8 OLI sensor can be used to extract Volcanic Cloud Top Height with a precision of 250 meters and an accuracy or 300m (de Michele et al., 2016). This method allows to extract a Plume Elevation Model (PEM) by jointly measuring the parallax between two optical bands acquired with a time lag varying from 0.1 to 2.5 seconds depending on the bands chosen and the sensors employed. The measure of the parallax is biased because the volcanic cloud is moving between the two images acquisitions, even if the time lag is short. The precision of our measurements is enhanced by compensating the parallax by measuring the velocity of the volcanic cloud in the perpendicular-to-epipolar direction (which is height independent) and correcting the initial parallax measurement. In this study, we push this methodology forward. We apply it to the very high spatial resolution Pleiades data (1m pixel spacing) provided by the French Space Agency (CNES). We apply the method on Mount Etna, during the 05 September 2015 eruptive episode and on Mount Ontake eruption occurring on 30 September 2014. We are able to extract VCTH as a PEM with high spatial resolution and improved precision. Since Pléiades has an improved revisit time (1day), our method has potential for routine monitoring of volcanic plumes in clear sky conditions and when the VCTH is higher than meteo clouds.

SU-G-TeP2-11: Initial Evaluation of a Novel Split-Filter Dual-Energy CT for Use in Radiation Oncology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, J; Huang, J; Szczykutowicz, T

2016-06-15

Purpose: To perform an initial evaluation of a novel split-filter dual-energy CT (DECT) system with the goal of understanding the clinical utility and limitations of the system for radiation therapy. Methods: Several phantoms were imaged using the split-filter DECT technique on the Siemens Edge CT scanner using a range of clinically-relevant doses. The optimum-contrast reconstruction, the mixed reconstruction, and the monoenergetic reconstructions (ranging from 40 keV to 190 keV) were evaluated. Each image was analyzed for CT number accuracy, uniformity, noise, low-contrast visibility (LCV), spatial resolution and geometric distortion. For comparison purposes, all parameters were evaluated on 120 kVp single-energymore » CT (SECT) scans used for treatment planning, as well as, a sequential-scan DECT technique for corresponding doses. Results: For all DECT reconstructions no observable geometric distortion was found. Both the optimal-contrast and mixed images demonstrated slight improvements in LCV and noise when compared to the SECT, and slight reductions in CT number accuracy and spatial resolution. The CT numbers trended as expected for the monoenergetic reconstructions, with CT number accuracy within 50 HU for materials of density <2 g/cm3. Spatial resolution increased with energy, and for monoenergetic reconstructions >70 keV the spatial resolution exceeded that of the SECT. The noise in the monoenergetic reconstructions increased with decreasing energy. Thus, the image uniformity, signal-to-noise ratio and LCV were diminished at lower energies (70 keV). Applying iterative reconstruction techniques to the low-energy images reduced noise and improved LCV. The signal-to-noise ratio was stable for energies >100 keV. Conclusion: The initial commissioning of the novel split-filter DECT technology demonstrated favorable results for clinical implementation. The mixed reconstruction showed potential as a replacement for the treatment planning SECT. The image parameters for the monoenergetic reconstructions varied appropriately with energy. This work provides an initial understanding of the limitations and potential applications for monoenergetic imaging.« less

Lidar-based multinomial classification algorithms for tropical forest degradation status: Implications for biomass estimation

NASA Astrophysics Data System (ADS)

Duffy, P.; Keller, M.; Longo, M.; Morton, D. C.; dos-Santos, M. N.; Pinagé, E. R.

2017-12-01

There is an urgent need to quantify the effects of land use and land cover change on carbon stocks in tropical forests to support REDD+ policies and improve characterization of global carbon budgets. This need is underscored by the fact that the variability in forest biomass estimates from global forest carbon maps is artificially low relative to estimates generated from forest inventory and high-resolution airborne lidar data. Both deforestation and degradation processes (e.g. logging, fire, and fragmentation) affect carbon fluxes at varying spatial and temporal scales. While the spatial extent and impact of deforestation has been relatively well characterized, the quantification of degradation processes is still poorly constrained. In the Brazilian Amazon, the largest source of uncertainty in CO2 emissions estimates is data on changes in tropical forest carbon stocks through time, followed closely by incomplete information on the carbon losses from forest degradation. In this work, we present a method for classifying the degradation status of tropical forests using higher order moments (skewness and kurtosis) of lidar return distributions aggregated at grids with resolution ranging from 50 m to 250 m. Across multiple spatial resolutions, we quantify the strength of the functional relationship between the lidar returns and the classification based on historical time series of Landsat imagery. Our results show that the higher order moments of the lidar return distributions provide sufficient information to build multinomial models that accurately classify the landscape into intact, logged, and burned forests. Model fit improved with coarser spatial resolution with Kappa statistics of 0.70 at 50 m, and 0.77 at 250 m. In addition, multi-class AUC was estimated as 0.87 at 50 m, and 0.95 at 250 m. This classification provides important information regarding the applicability of the use of lidar data for regional monitoring of recent logging, as well as the trajectory of the carbon budget. Differentiating between the biomass changes associated with deforestation and degradation processes is critical for accurate accounting of disturbance impacts on carbon cycling within the Brazilian Amazon and global tropical forests.

Spatiotemporal exposure modeling of ambient erythemal ultraviolet radiation.

PubMed

VoPham, Trang; Hart, Jaime E; Bertrand, Kimberly A; Sun, Zhibin; Tamimi, Rulla M; Laden, Francine

2016-11-24

Ultraviolet B (UV-B) radiation plays a multifaceted role in human health, inducing DNA damage and representing the primary source of vitamin D for most humans; however, current U.S. UV exposure models are limited in spatial, temporal, and/or spectral resolution. Area-to-point (ATP) residual kriging is a geostatistical method that can be used to create a spatiotemporal exposure model by downscaling from an area- to point-level spatial resolution using fine-scale ancillary data. A stratified ATP residual kriging approach was used to predict average July noon-time erythemal UV (UV Ery ) (mW/m 2 ) biennially from 1998 to 2012 by downscaling National Aeronautics and Space Administration (NASA) Total Ozone Mapping Spectrometer (TOMS) and Ozone Monitoring Instrument (OMI) gridded remote sensing images to a 1 km spatial resolution. Ancillary data were incorporated in random intercept linear mixed-effects regression models. Modeling was performed separately within nine U.S. regions to satisfy stationarity and account for locally varying associations between UV Ery and predictors. Cross-validation was used to compare ATP residual kriging models and NASA grids to UV-B Monitoring and Research Program (UVMRP) measurements (gold standard). Predictors included in the final regional models included surface albedo, aerosol optical depth (AOD), cloud cover, dew point, elevation, latitude, ozone, surface incoming shortwave flux, sulfur dioxide (SO 2 ), year, and interactions between year and surface albedo, AOD, cloud cover, dew point, elevation, latitude, and SO 2 . ATP residual kriging models more accurately estimated UV Ery at UVMRP monitoring stations on average compared to NASA grids across the contiguous U.S. (average mean absolute error [MAE] for ATP, NASA: 15.8, 20.3; average root mean square error [RMSE]: 21.3, 25.5). ATP residual kriging was associated with positive percent relative improvements in MAE (0.6-31.5%) and RMSE (3.6-29.4%) across all regions compared to NASA grids. ATP residual kriging incorporating fine-scale spatial predictors can provide more accurate, high-resolution UV Ery estimates compared to using NASA grids and can be used in epidemiologic studies examining the health effects of ambient UV.

Remote monitoring of tamarisk defoliation and evapotranspiration following saltcedar leaf beetle attack

USGS Publications Warehouse

Dennison, P.E.; Nagler, P.L.; Hultine, K.R.; Glenn, E.P.; Ehleringer, J.R.

2009-01-01

Tamarisk (Tamarix spp.) has invaded riparian ecosystems throughout the Western United States, including significant portions of riparian ecosystems within U.S. National Parks and Monuments. Recently, the saltcedar leaf beetle (Diorhabda elongata) was released as a tamarisk biocontrol agent. Although initial releases have been monitored, no comprehensive program is currently in place to monitor the rapid spread of Diorhabda that has resulted from numerous subsequent releases by county and state agencies. Long term monitoring of tamarisk defoliation and its impacts on habitat and water resources is needed. This study examines the potential for using higher spatial resolution Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data and lower spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) data for monitoring defoliation caused by Diorhabda and subsequent changes in evapotranspiration (ET). Widespread tamarisk defoliation was observed in an eastern Utah study area during summer 2007. ASTER normalized difference vegetation index (NDVI) showed only minor changes between 2005 and 2006, but a significant drop in NDVI was found within riparian areas between 2006 and 2007. The decrease in NDVI caused by defoliation was apparent despite partial refoliation within the study area. MODIS time series data revealed that absolute decline in EVI varied by site, but that the timing of EVI decline during summer 2007 was early with respect to phenological patterns from 2001 through 2006. Defoliation caused decreases in ET values estimated from both ASTER and MODIS data. MODIS estimated ET declined earlier than in previous years, although annual ET was not significantly different than ET in previous years due to high year-to-year variability. Challenges to detection and monitoring of tamarisk defoliation include spectral mixing of tamarisk and other cover types at subpixel spatial resolution, spatial coregistration of time series images, the timing of image acquisition, and changes unrelated to defoliation in non-tamarisk land cover over time. Continued development of the techniques presented in this paper may allow monitoring the spread of Diorhabda and assessment of potential water salvage resulting from biocontrol of tamarisk. ?? 2009 Elsevier Inc.

Influence of Rainfall Product on Hydrological and Sediment Outputs when Calibrating the STREAP Rainfall Generator for the CAESAR-Lisflood Landscape Evolution Model

NASA Astrophysics Data System (ADS)

Skinner, Christopher; Peleg, Nadav; Quinn, Niall

2017-04-01

The use of Landscape Evolution Models often requires a timeseries of rainfall to drive the model. The spatial and temporal resolution of the driving data has an impact on several model outputs, including the shape of the landscape itself. Attempts to compensate for the spatiotemporal smoothing of local rainfall intensities are insufficient and may exacerbate these issues, meaning that to produce the best results the model needs to be run with data of highest spatial and temporal resolutions available. Some rainfall generators are able to produce timeseries with high spatial and temporal resolution. Observed data is used for the calibration of these generators. However, rainfall observations are highly uncertain and vary between different products (e.g. raingauges, weather radar) which may cascade through the Landscape Evolution Model. Here, we used the STREAP rainfall generator to produce high spatial (1km) and temporal (hourly) resolution ensembles of rainfall for a 50-year period, and used these to drive the CAESAR-Lisflood Landscape Evolution Model for a test catchment. Three different calibrations of STREAP were used against different products: gridded raingauge (TBR), weather radar (NIMROD), and a merged of the two. Analysis of the discharge and sediment yields from the model runs showed that the models run by STREAP calibrated by the different products were statistically significantly different, with the raingauge calibration producing 12.4 % more sediment on average over the 50-year period. The merged product produced results which were between the raingauge and radar products. The results demonstrate the importance of considering the selection of rainfall driving data on Landscape Evolution Modelling. Rainfall products are highly uncertain, different instruments will observe rainfall differently, and these uncertainties are clearly shown to cascade through the calibration of the rainfall generator and the Landscape Evolution Model. Merging raingauge and radar products is a common practise operationally, and by using features of both to calibrate the rainfall generator it is likely a more robust rainfall timeseries is produced.

A technique for enhancing and matching the resolution of microwave measurements from the SSM/I instrument

NASA Technical Reports Server (NTRS)

Robinson, Wayne D.; Kummerrow, Christian; Olson, William S.

1992-01-01

A correction technique is presented for matching the resolution of all the frequencies of the satelliteborne Special Sensor Microwave/Imager (SSM/I) to the about-25-km spatial resolution of the 37-GHz channel. This entails, on the one hand, the enhancement of the spatial resolution of the 19- and 22-GHz channels, and on the other, the degrading of that of the 85-GHz channel. The Backus and Gilbert (1970) approach is found to yield sufficient spatial resolution to render such a correction worthwhile.

High spatial resolution distributed optical fiber dynamic strain sensor with enhanced frequency and strain resolution.

PubMed

Masoudi, Ali; Newson, Trevor P

2017-01-15

A distributed optical fiber dynamic strain sensor with high spatial and frequency resolution is demonstrated. The sensor, which uses the ϕ-OTDR interrogation technique, exhibited a higher sensitivity thanks to an improved optical arrangement and a new signal processing procedure. The proposed sensing system is capable of fully quantifying multiple dynamic perturbations along a 5 km long sensing fiber with a frequency and spatial resolution of 5 Hz and 50 cm, respectively. The strain resolution of the sensor was measured to be 40 nε.

Multi-scale analysis of a household level agent-based model of landcover change.

PubMed

Evans, Tom P; Kelley, Hugh

2004-08-01

Scale issues have significant implications for the analysis of social and biophysical processes in complex systems. These same scale implications are likewise considerations for the design and application of models of landcover change. Scale issues have wide-ranging effects from the representativeness of data used to validate models to aggregation errors introduced in the model structure. This paper presents an analysis of how scale issues affect an agent-based model (ABM) of landcover change developed for a research area in the Midwest, USA. The research presented here explores how scale factors affect the design and application of agent-based landcover change models. The ABM is composed of a series of heterogeneous agents who make landuse decisions on a portfolio of cells in a raster-based programming environment. The model is calibrated using measures of fit derived from both spatial composition and spatial pattern metrics from multi-temporal landcover data interpreted from historical aerial photography. A model calibration process is used to find a best-fit set of parameter weights assigned to agents' preferences for different landuses (agriculture, pasture, timber production, and non-harvested forest). Previous research using this model has shown how a heterogeneous set of agents with differing preferences for a portfolio of landuses produces the best fit to landcover changes observed in the study area. The scale dependence of the model is explored by varying the resolution of the input data used to calibrate the model (observed landcover), ancillary datasets that affect land suitability (topography), and the resolution of the model landscape on which agents make decisions. To explore the impact of these scale relationships the model is run with input datasets constructed at the following spatial resolutions: 60, 90, 120, 150, 240, 300 and 480 m. The results show that the distribution of landuse-preference weights differs as a function of scale. In addition, with the gradient descent model fitting method used in this analysis the model was not able to converge to an acceptable fit at the 300 and 480 m spatial resolutions. This is a product of the ratio of the input cell resolution to the average parcel size in the landscape. This paper uses these findings to identify scale considerations in the design, development, validation and application of ABMs of landcover change.

Study of satellite retrieved aerosol optical depth spatial resolution effect on particulate matter concentration prediction

NASA Astrophysics Data System (ADS)

Strandgren, J.; Mei, L.; Vountas, M.; Burrows, J. P.; Lyapustin, A.; Wang, Y.

2014-10-01

The Aerosol Optical Depth (AOD) spatial resolution effect is investigated for the linear correlation between satellite retrieved AOD and ground level particulate matter concentrations (PM2.5). The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for the Moderate Resolution Imaging Spectroradiometer (MODIS) for obtaining AOD with a high spatial resolution of 1 km and provides a good dataset for the study of the AOD spatial resolution effect on the particulate matter concentration prediction. 946 Environmental Protection Agency (EPA) ground monitoring stations across the contiguous US have been used to investigate the linear correlation between AOD and PM2.5 using AOD at different spatial resolutions (1, 3 and 10 km) and for different spatial scales (urban scale, meso-scale and continental scale). The main conclusions are: (1) for both urban, meso- and continental scale the correlation between PM2.5 and AOD increased significantly with increasing spatial resolution of the AOD, (2) the correlation between AOD and PM2.5 decreased significantly as the scale of study region increased for the eastern part of the US while vice versa for the western part of the US, (3) the correlation between PM2.5 and AOD is much more stable and better over the eastern part of the US compared to western part due to the surface characteristics and atmospheric conditions like the fine mode fraction.

Employing temporal self-similarity across the entire time domain in computed tomography reconstruction

PubMed Central

Kazantsev, D.; Van Eyndhoven, G.; Lionheart, W. R. B.; Withers, P. J.; Dobson, K. J.; McDonald, S. A.; Atwood, R.; Lee, P. D.

2015-01-01

There are many cases where one needs to limit the X-ray dose, or the number of projections, or both, for high frame rate (fast) imaging. Normally, it improves temporal resolution but reduces the spatial resolution of the reconstructed data. Fortunately, the redundancy of information in the temporal domain can be employed to improve spatial resolution. In this paper, we propose a novel regularizer for iterative reconstruction of time-lapse computed tomography. The non-local penalty term is driven by the available prior information and employs all available temporal data to improve the spatial resolution of each individual time frame. A high-resolution prior image from the same or a different imaging modality is used to enhance edges which remain stationary throughout the acquisition time while dynamic features tend to be regularized spatially. Effective computational performance together with robust improvement in spatial and temporal resolution makes the proposed method a competitive tool to state-of-the-art techniques. PMID:25939621

Resolution for color photography

NASA Astrophysics Data System (ADS)

Hubel, Paul M.; Bautsch, Markus

2006-02-01

Although it is well known that luminance resolution is most important, the ability to accurately render colored details, color textures, and colored fabrics cannot be overlooked. This includes the ability to accurately render single-pixel color details as well as avoiding color aliasing. All consumer digital cameras on the market today record in color and the scenes people are photographing are usually color. Yet almost all resolution measurements made on color cameras are done using a black and white target. In this paper we present several methods for measuring and quantifying color resolution. The first method, detailed in a previous publication, uses a slanted-edge target of two colored surfaces in place of the standard black and white edge pattern. The second method employs the standard black and white targets recommended in the ISO standard, but records these onto the camera through colored filters thus giving modulation between black and one particular color component; red, green, and blue color separation filters are used in this study. The third method, conducted at Stiftung Warentest, an independent consumer organization of Germany, uses a whitelight interferometer to generate fringe pattern targets of varying color and spatial frequency.

Change of spatial information under rescaling: A case study using multi-resolution image series

NASA Astrophysics Data System (ADS)

Chen, Weirong; Henebry, Geoffrey M.

Spatial structure in imagery depends on a complicated interaction between the observational regime and the types and arrangements of entities within the scene that the image portrays. Although block averaging of pixels has commonly been used to simulate coarser resolution imagery, relatively little attention has been focused on the effects of simple rescaling on spatial structure and the explanation and a possible solution to the problem. Yet, if there are significant differences in spatial variance between rescaled and observed images, it may affect the reliability of retrieved biogeophysical quantities. To investigate these issues, a nested series of high spatial resolution digital imagery was collected at a research site in eastern Nebraska in 2001. An airborne Kodak DCS420IR camera acquired imagery at three altitudes, yielding nominal spatial resolutions ranging from 0.187 m to 1 m. The red and near infrared (NIR) bands of the co-registered image series were normalized using pseudo-invariant features, and the normalized difference vegetation index (NDVI) was calculated. Plots of grain sorghum planted in orthogonal crop row orientations were extracted from the image series. The finest spatial resolution data were then rescaled by averaging blocks of pixels to produce a rescaled image series that closely matched the spatial resolution of the observed image series. Spatial structures of the observed and rescaled image series were characterized using semivariogram analysis. Results for NDVI and its component bands show, as expected, that decreasing spatial resolution leads to decreasing spatial variability and increasing spatial dependence. However, compared to the observed data, the rescaled images contain more persistent spatial structure that exhibits limited variation in both spatial dependence and spatial heterogeneity. Rescaling via simple block averaging fails to consider the effect of scene object shape and extent on spatial information. As the features portrayed by pixels are equally weighted regardless of the shape and extent of the underlying scene objects, the rescaled image retains more of the original spatial information than would occur through direct observation at a coarser sensor spatial resolution. In contrast, for the observed images, due to the effect of the modulation transfer function (MTF) of the imaging system, high frequency features like edges are blurred or lost as the pixel size increases, resulting in greater variation in spatial structure. Successive applications of a low-pass spatial convolution filter are shown to mimic a MTF. Accordingly, it is recommended that such a procedure be applied prior to rescaling by simple block averaging, if insufficient image metadata exist to replicate the net MTF of the imaging system, as might be expected in land cover change analysis studies using historical imagery.

Satellite image fusion based on principal component analysis and high-pass filtering.

PubMed

Metwalli, Mohamed R; Nasr, Ayman H; Allah, Osama S Farag; El-Rabaie, S; Abd El-Samie, Fathi E

2010-06-01

This paper presents an integrated method for the fusion of satellite images. Several commercial earth observation satellites carry dual-resolution sensors, which provide high spatial resolution or simply high-resolution (HR) panchromatic (pan) images and low-resolution (LR) multi-spectral (MS) images. Image fusion methods are therefore required to integrate a high-spectral-resolution MS image with a high-spatial-resolution pan image to produce a pan-sharpened image with high spectral and spatial resolutions. Some image fusion methods such as the intensity, hue, and saturation (IHS) method, the principal component analysis (PCA) method, and the Brovey transform (BT) method provide HR MS images, but with low spectral quality. Another family of image fusion methods, such as the high-pass-filtering (HPF) method, operates on the basis of the injection of high frequency components from the HR pan image into the MS image. This family of methods provides less spectral distortion. In this paper, we propose the integration of the PCA method and the HPF method to provide a pan-sharpened MS image with superior spatial resolution and less spectral distortion. The experimental results show that the proposed fusion method retains the spectral characteristics of the MS image and, at the same time, improves the spatial resolution of the pan-sharpened image.

High-Spatial and High-Mass Resolution Imaging of Surface Metabolites of Arabidopsis thaliana by Laser Desorption-Ionization Mass Spectrometry Using Colloidal Silver

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jun, Ji Hyun; Song, Zhihong; Liu, Zhenjiu

High-spatial resolution and high-mass resolution techniques are developed and adopted for the mass spectrometric imaging of epicuticular lipids on the surface of Arabidopsis thaliana. Single cell level spatial resolution of {approx}12 {micro}m was achieved by reducing the laser beam size by using an optical fiber with 25 {micro}m core diameter in a vacuum matrix-assisted laser desorption ionization-linear ion trap (vMALDI-LTQ) mass spectrometer and improved matrix application using an oscillating capillary nebulizer. Fine chemical images of a whole flower were visualized in this high spatial resolution showing substructure of an anther and single pollen grains at the stigma and anthers. Themore » LTQ-Orbitrap with a MALDI ion source was adopted to achieve MS imaging in high mass resolution. Specifically, isobaric silver ion adducts of C29 alkane (m/z 515.3741) and C28 aldehyde (m/z 515.3377), indistinguishable in low-resolution LTQ, can now be clearly distinguished and their chemical images could be separately constructed. In the application to roots, the high spatial resolution allowed molecular MS imaging of secondary roots and the high mass resolution allowed direct identification of lipid metabolites on root surfaces.« less

Superharmonic imaging with chirp coded excitation: filtering spectrally overlapped harmonics.

PubMed

Harput, Sevan; McLaughlan, James; Cowell, David M J; Freear, Steven

2014-11-01

Superharmonic imaging improves the spatial resolution by using the higher order harmonics generated in tissue. The superharmonic component is formed by combining the third, fourth, and fifth harmonics, which have low energy content and therefore poor SNR. This study uses coded excitation to increase the excitation energy. The SNR improvement is achieved on the receiver side by performing pulse compression with harmonic matched filters. The use of coded signals also introduces new filtering capabilities that are not possible with pulsed excitation. This is especially important when using wideband signals. For narrowband signals, the spectral boundaries of the harmonics are clearly separated and thus easy to filter; however, the available imaging bandwidth is underused. Wideband excitation is preferable for harmonic imaging applications to preserve axial resolution, but it generates spectrally overlapping harmonics that are not possible to filter in time and frequency domains. After pulse compression, this overlap increases the range side lobes, which appear as imaging artifacts and reduce the Bmode image quality. In this study, the isolation of higher order harmonics was achieved in another domain by using the fan chirp transform (FChT). To show the effect of excitation bandwidth in superharmonic imaging, measurements were performed by using linear frequency modulated chirp excitation with varying bandwidths of 10% to 50%. Superharmonic imaging was performed on a wire phantom using a wideband chirp excitation. Results were presented with and without applying the FChT filtering technique by comparing the spatial resolution and side lobe levels. Wideband excitation signals achieved a better resolution as expected, however range side lobes as high as -23 dB were observed for the superharmonic component of chirp excitation with 50% fractional bandwidth. The proposed filtering technique achieved >50 dB range side lobe suppression and improved the image quality without affecting the axial resolution.

The spatial resolution of a rotating gamma camera tomographic facility.

PubMed

Webb, S; Flower, M A; Ott, R J; Leach, M O; Inamdar, R

1983-12-01

An important feature determining the spatial resolution in transverse sections reconstructed by convolution and back-projection is the frequency filter corresponding to the convolution kernel. Equations have been derived giving the theoretical spatial resolution, for a perfect detector and noise-free data, using four filter functions. Experiments have shown that physical constraints will always limit the resolution that can be achieved with a given system. The experiments indicate that the region of the frequency spectrum between KN/2 and KN where KN is the Nyquist frequency does not contribute significantly to resolution. In order to investigate the physical effect of these filter functions, the spatial resolution of reconstructed images obtained with a GE 400T rotating gamma camera has been measured. The results obtained serve as an aid to choosing appropriate reconstruction filters for use with a rotating gamma camera system.

A high time and spatial resolution MRPC designed for muon tomography

NASA Astrophysics Data System (ADS)

Shi, L.; Wang, Y.; Huang, X.; Wang, X.; Zhu, W.; Li, Y.; Cheng, J.

2014-12-01

A prototype of cosmic muon scattering tomography system has been set up in Tsinghua University in Beijing. Multi-gap Resistive Plate Chamber (MRPC) is used in the system to get the muon tracks. Compared with other detectors, MRPC can not only provide the track but also the Time of Flight (ToF) between two detectors which can estimate the energy of particles. To get a more accurate track and higher efficiency of the tomography system, a new type of high time and two-dimensional spatial resolution MRPC has been developed. A series of experiments have been done to measure the efficiency, time resolution and spatial resolution. The results show that the efficiency can reach 95% and its time resolution is around 65 ps. The cluster size is around 4 and the spatial resolution can reach 200 μ m.

150-μm Spatial Resolution Using Photon-Counting Detector Computed Tomography Technology: Technical Performance and First Patient Images.

PubMed

Leng, Shuai; Rajendran, Kishore; Gong, Hao; Zhou, Wei; Halaweish, Ahmed F; Henning, Andre; Kappler, Steffen; Baer, Matthias; Fletcher, Joel G; McCollough, Cynthia H

2018-05-28

The aims of this study were to quantitatively assess two new scan modes on a photon-counting detector computed tomography system, each designed to maximize spatial resolution, and to qualitatively demonstrate potential clinical impact using patient data. This Health Insurance Portability Act-compliant study was approved by our institutional review board. Two high-spatial-resolution scan modes (Sharp and UHR) were evaluated using phantoms to quantify spatial resolution and image noise, and results were compared with the standard mode (Macro). Patients were scanned using a conventional energy-integrating detector scanner and the photon-counting detector scanner using the same radiation dose. In first patient images, anatomic details were qualitatively evaluated to demonstrate potential clinical impact. Sharp and UHR modes had a 69% and 87% improvement in in-plane spatial resolution, respectively, compared with Macro mode (10% modulation-translation-function values of 16.05, 17.69, and 9.48 lp/cm, respectively). The cutoff spatial frequency of the UHR mode (32.4 lp/cm) corresponded to a limiting spatial resolution of 150 μm. The full-width-at-half-maximum values of the section sensitivity profiles were 0.41, 0.44, and 0.67 mm for the thinnest image thickness for each mode (0.25, 0.25, and 0.5 mm, respectively). At the same in-plane spatial resolution, Sharp and UHR images had up to 15% lower noise than Macro images. Patient images acquired in Sharp mode demonstrated better delineation of fine anatomic structures compared with Macro mode images. Phantom studies demonstrated superior resolution and noise properties for the Sharp and UHR modes relative to the standard Macro mode and patient images demonstrated the potential benefit of these scan modes for clinical practice.

The Analytical Limits of Modeling Short Diffusion Timescales

NASA Astrophysics Data System (ADS)

Bradshaw, R. W.; Kent, A. J.

2016-12-01

Chemical and isotopic zoning in minerals is widely used to constrain the timescales of magmatic processes such as magma mixing and crystal residence, etc. via diffusion modeling. Forward modeling of diffusion relies on fitting diffusion profiles to measured compositional gradients. However, an individual measurement is essentially an average composition for a segment of the gradient defined by the spatial resolution of the analysis. Thus there is the potential for the analytical spatial resolution to limit the timescales that can be determined for an element of given diffusivity, particularly where the scale of the gradient approaches that of the measurement. Here we use a probabilistic modeling approach to investigate the effect of analytical spatial resolution on estimated timescales from diffusion modeling. Our method investigates how accurately the age of a synthetic diffusion profile can be obtained by modeling an "unknown" profile derived from discrete sampling of the synthetic compositional gradient at a given spatial resolution. We also include the effects of analytical uncertainty and the position of measurements relative to the diffusion gradient. We apply this method to the spatial resolutions of common microanalytical techniques (LA-ICP-MS, SIMS, EMP, NanoSIMS). Our results confirm that for a given diffusivity, higher spatial resolution gives access to shorter timescales, and that each analytical spacing has a minimum timescale, below which it overestimates the timescale. For example, for Ba diffusion in plagioclase at 750 °C timescales are accurate (within 20%) above 10, 100, 2,600, and 71,000 years at 0.3, 1, 5, and 25 mm spatial resolution, respectively. For Sr diffusion in plagioclase at 750 °C, timescales are accurate above 0.02, 0.2, 4, and 120 years at the same spatial resolutions. Our results highlight the importance of selecting appropriate analytical techniques to estimate accurate diffusion-based timescales.

Spatial and Angular Resolution Enhancement of Light Fields Using Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Gul, M. Shahzeb Khan; Gunturk, Bahadir K.

2018-05-01

Light field imaging extends the traditional photography by capturing both spatial and angular distribution of light, which enables new capabilities, including post-capture refocusing, post-capture aperture control, and depth estimation from a single shot. Micro-lens array (MLA) based light field cameras offer a cost-effective approach to capture light field. A major drawback of MLA based light field cameras is low spatial resolution, which is due to the fact that a single image sensor is shared to capture both spatial and angular information. In this paper, we present a learning based light field enhancement approach. Both spatial and angular resolution of captured light field is enhanced using convolutional neural networks. The proposed method is tested with real light field data captured with a Lytro light field camera, clearly demonstrating spatial and angular resolution improvement.

Spatial and Angular Resolution Enhancement of Light Fields Using Convolutional Neural Networks.

PubMed

Gul, M Shahzeb Khan; Gunturk, Bahadir K

2018-05-01

Light field imaging extends the traditional photography by capturing both spatial and angular distribution of light, which enables new capabilities, including post-capture refocusing, post-capture aperture control, and depth estimation from a single shot. Micro-lens array (MLA) based light field cameras offer a cost-effective approach to capture light field. A major drawback of MLA based light field cameras is low spatial resolution, which is due to the fact that a single image sensor is shared to capture both spatial and angular information. In this paper, we present a learning based light field enhancement approach. Both spatial and angular resolution of captured light field is enhanced using convolutional neural networks. The proposed method is tested with real light field data captured with a Lytro light field camera, clearly demonstrating spatial and angular resolution improvement.

Compact advanced extreme-ultraviolet imaging spectrometer for spatiotemporally varying tungsten spectra from fusion plasmas.

PubMed

Song, Inwoo; Seon, C R; Hong, Joohwan; An, Y H; Barnsley, R; Guirlet, R; Choe, Wonho

2017-09-01

A compact advanced extreme-ultraviolet (EUV) spectrometer operating in the EUV wavelength range of a few nanometers to measure spatially resolved line emissions from tungsten (W) was developed for studying W transport in fusion plasmas. This system consists of two perpendicularly crossed slits-an entrance aperture and a space-resolved slit-inside a chamber operating as a pinhole, which enables the system to obtain a spatial distribution of line emissions. Moreover, a so-called v-shaped slit was devised to manage the aperture size for measuring the spatial resolution of the system caused by the finite width of the pinhole. A back-illuminated charge-coupled device was used as a detector with 2048 × 512 active pixels, each with dimensions of 13.5 × 13.5 μm 2 . After the alignment and installation on Korea superconducting tokamak advanced research, the preliminary results were obtained during the 2016 campaign. Several well-known carbon atomic lines in the 2-7 nm range originating from intrinsic carbon impurities were observed and used for wavelength calibration. Further, the time behavior of their spatial distributions is presented.

Multi-Resolution Analysis of MODIS and ASTER Satellite Data for Water Classification

DTIC Science & Technology

2006-09-01

spectral bands, but also with different pixel resolutions . The overall goal... the total water surface. Due to the constraint that high spatial resolution satellite images are low temporal resolution , one needs a reliable method...at 15 m resolution , were processed. We used MODIS reflectance data from MOD02 Level 1B data. Even the spatial resolution of the 1240 nm

Definition of the Spatial Resolution of X-Ray Microanalysis in Thin Foils

NASA Technical Reports Server (NTRS)

Williams, D. B.; Michael, J. R.; Goldstein, J. I.; Romig, A. D., Jr.

1992-01-01

The spatial resolution of X-ray microanalysis in thin foils is defined in terms of the incident electron beam diameter and the average beam broadening. The beam diameter is defined as the full width tenth maximum of a Gaussian intensity distribution. The spatial resolution is calculated by a convolution of the beam diameter and the average beam broadening. This definition of the spatial resolution can be related simply to experimental measurements of composition profiles across interphase interfaces. Monte Carlo calculations using a high-speed parallel supercomputer show good agreement with this definition of the spatial resolution and calculations based on this definition. The agreement is good over a range of specimen thicknesses and atomic number, but is poor when excessive beam tailing distorts the assumed Gaussian electron intensity distributions. Beam tailing occurs in low-Z materials because of fast secondary electrons and in high-Z materials because of plural scattering.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krishnan, Venkat; Cole, Wesley

Power sector capacity expansion models (CEMs) have a broad range of spatial resolutions. This paper uses the Regional Energy Deployment System (ReEDS) model, a long-term national scale electric sector CEM, to evaluate the value of high spatial resolution for CEMs. ReEDS models the United States with 134 load balancing areas (BAs) and captures the variability in existing generation parameters, future technology costs, performance, and resource availability using very high spatial resolution data, especially for wind and solar modeled at 356 resource regions. In this paper we perform planning studies at three different spatial resolutions--native resolution (134 BAs), state-level, and NERCmore » region level--and evaluate how results change under different levels of spatial aggregation in terms of renewable capacity deployment and location, associated transmission builds, and system costs. The results are used to ascertain the value of high geographically resolved models in terms of their impact on relative competitiveness among renewable energy resources.« less

4Pi microscopy deconvolution with a variable point-spread function.

PubMed

Baddeley, David; Carl, Christian; Cremer, Christoph

2006-09-20

To remove the axial sidelobes from 4Pi images, deconvolution forms an integral part of 4Pi microscopy. As a result of its high axial resolution, the 4Pi point spread function (PSF) is particularly susceptible to imperfect optical conditions within the sample. This is typically observed as a shift in the position of the maxima under the PSF envelope. A significantly varying phase shift renders deconvolution procedures based on a spatially invariant PSF essentially useless. We present a technique for computing the forward transformation in the case of a varying phase at a computational expense of the same order of magnitude as that of the shift invariant case, a method for the estimation of PSF phase from an acquired image, and a deconvolution procedure built on these techniques.

Easy way to determine quantitative spatial resolution distribution for a general inverse problem

NASA Astrophysics Data System (ADS)

An, M.; Feng, M.

2013-12-01

The spatial resolution computation of a solution was nontrivial and more difficult than solving an inverse problem. Most geophysical studies, except for tomographic studies, almost uniformly neglect the calculation of a practical spatial resolution. In seismic tomography studies, a qualitative resolution length can be indicatively given via visual inspection of the restoration of a synthetic structure (e.g., checkerboard tests). An effective strategy for obtaining quantitative resolution length is to calculate Backus-Gilbert resolution kernels (also referred to as a resolution matrix) by matrix operation. However, not all resolution matrices can provide resolution length information, and the computation of resolution matrix is often a difficult problem for very large inverse problems. A new class of resolution matrices, called the statistical resolution matrices (An, 2012, GJI), can be directly determined via a simple one-parameter nonlinear inversion performed based on limited pairs of random synthetic models and their inverse solutions. The total procedure were restricted to forward/inversion processes used in the real inverse problem and were independent of the degree of inverse skill used in the solution inversion. Spatial resolution lengths can be directly given during the inversion. Tests on 1D/2D/3D model inversion demonstrated that this simple method can be at least valid for a general linear inverse problem.

An ultrasonic noncontact method to monitor the doneness of bakery products

NASA Astrophysics Data System (ADS)

Chimenti, D. E.; Faeth, L.

2000-05-01

The paper describes a method using ultrasonics and fluid dynamics to assess the state of "doneness" of bakery products, such as bread loaves, online and in situ. The problem in the baking industry is that bread doneness determined by time and temperature can be inaccurate, leaving some product underbaked. We describe a noncontact method using air-pulse excitation and air-coupled ultrasonic motion sensing to infer the state of doneness of the baking loaf while still in the oven and on a moving belt. The ultrasonic sensor operates at 100 kHz using a toneburst excitation and pitch-catch transducer geometry. The problem is one of detecting small (50 micron) movements in the loaf, whose position may vary up to several mm. Further, the loaf movements caused by the air-pulse excitation are rapid (20 to 50 msec). We present a signal-processing system, incorporating a boxcar integrator, that functions as a pulsed, time-domain acoustic interferometer. This instrument is capable of both the high time and spatial resolution essential for the successful operation of the instrument. We estimate a spatial resolution of 30 micron and a temporal resolution of 5 msec, using 100 kHz acoustic waves. The results of numerous in-oven measurements on one-pound bread loaves during the bake cycle will be presented to illustrate the performance of the instrument.

Cerebral TOF Angiography at 7T: Impact of B1+ Shimming with a 16-Channel Transceiver Array

PubMed Central

Schmitter, Sebastian; Wu, Xiaoping; Adriany, Gregor; Auerbach, Edward J.; Uğurbil, Kâmil; Van de Moortele, Pierre-François

2014-01-01

Purpose Time-of-flight (TOF) MR imaging is clinically among the most common cerebral non-contrast enhanced MR angiography techniques allowing for high spatial resolution. As shown by several groups TOF contrast significantly improves at ultra-high field (UHF) of B0=7T, however, spatially varying transmit B1 (B1+) fields at 7T reduce TOF contrast uniformity, typically resulting in sub-optimal contrast and reduced vessel conspicuity in the brain periphery. Methods Using a 16-channel B1+ shimming system we compare different dynamically applied B1+ phase shimming approaches on the RF excitation to improve contrast homogeneity for a (0.5 mm)3 resolution multi-slab TOF acquisition. In addition, B1+ shimming applied on the venous saturation pulse was investigated to improve venous suppression, subcutaneous fat signal reduction and enhanced background suppression originating from MT effect. Results B1+ excitation homogeneity was improved by a factor 2.2 to 2.6 on average depending on the shimming approach, compared to a standard CP-like phase setting, leading to improved vessel conspicuity particularly in the periphery. Stronger saturation, higher fat suppression and improved background suppression were observed when dynamically applying B1+ shimming on the venous saturation pulse. Conclusion B1+ shimming can significantly improve high resolution TOF vascular investigations at UHF, holding strong promise for non contrast-enhanced clinical applications. PMID:23640915

P69 Using the NASA-Unified WRF to Assess the Impacts of Real-Time Vegetation on Simulations of Severe Weather

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; LaFontaine, Frank J.; Kumar, Sujay V.; Peters-Lidard, Christa D.

2012-01-01

Since June 2010, the NASA Short-term Prediction Research and Transition (SPoRT; Goodman et al. 2004; Darden et al. 2010; Stano et al. 2012; Fuell et al. 2012) Center has been generating a real-time Normalized Difference Vegetation Index (NDVI) and corresponding Green Vegetation Fraction (GVF) composite based on reflectances from NASA s Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. This dataset is generated at 0.01 resolution across the Continental United States (CONUS), and updated daily. The goal of producing such a vegetation dataset is to improve over the default climatological GVF dataset in land surface and numerical weather prediction models, in order to have better simulations of heat and moisture exchange between the land surface and the planetary boundary layer. Details on the SPoRT/MODIS vegetation composite algorithm are presented in Case et al. (2011). Vegetation indices such as GVF and Leaf Area Index (LAI) are used by land surface models (LSMs) to represent the horizontal and vertical density of plant vegetation (Gutman and Ignatov 1998), in order to calculate transpiration, interception and radiative shading. Both of these indices are related to the NDVI; however, there is an inherent ambiguity in determining GVF and LAI simultaneously from NDVI, as described in Gutman and Ignatov (1998). One practice is to specify the LAI while allowing the GVF to vary both spatially and temporally, as is done in the Noah LSM (Chen and Dudhia 2001; Ek et al. 2003). Operational versions of Noah within several of the National Centers for Environmental Prediction (NCEP) global and regional modeling systems hold the LAI fixed, while the GVF varies according to a global monthly climatology. This GVF climatology was derived from NDVI data on the NOAA Advanced Very High Resolution Radiometer (AVHRR) polar orbiting satellite, using information from 1985 to 1991 (Gutman and Ignatov 1998; Jiang et al. 2010). Representing data at the mid-point of every month, the climatological dataset is on a grid with 0.144 (16 km) spatial resolution and is distributed with the community WRF model (Ek et al. 2003; Jiang et al. 2010; Skamarock et al. 2008).

A comparative experimental evaluation of uncertainty estimation methods for two-component PIV

NASA Astrophysics Data System (ADS)

Boomsma, Aaron; Bhattacharya, Sayantan; Troolin, Dan; Pothos, Stamatios; Vlachos, Pavlos

2016-09-01

Uncertainty quantification in planar particle image velocimetry (PIV) measurement is critical for proper assessment of the quality and significance of reported results. New uncertainty estimation methods have been recently introduced generating interest about their applicability and utility. The present study compares and contrasts current methods, across two separate experiments and three software packages in order to provide a diversified assessment of the methods. We evaluated the performance of four uncertainty estimation methods, primary peak ratio (PPR), mutual information (MI), image matching (IM) and correlation statistics (CS). The PPR method was implemented and tested in two processing codes, using in-house open source PIV processing software (PRANA, Purdue University) and Insight4G (TSI, Inc.). The MI method was evaluated in PRANA, as was the IM method. The CS method was evaluated using DaVis (LaVision, GmbH). Utilizing two PIV systems for high and low-resolution measurements and a laser doppler velocimetry (LDV) system, data were acquired in a total of three cases: a jet flow and a cylinder in cross flow at two Reynolds numbers. LDV measurements were used to establish a point validation against which the high-resolution PIV measurements were validated. Subsequently, the high-resolution PIV measurements were used as a reference against which the low-resolution PIV data were assessed for error and uncertainty. We compared error and uncertainty distributions, spatially varying RMS error and RMS uncertainty, and standard uncertainty coverages. We observed that qualitatively, each method responded to spatially varying error (i.e. higher error regions resulted in higher uncertainty predictions in that region). However, the PPR and MI methods demonstrated reduced uncertainty dynamic range response. In contrast, the IM and CS methods showed better response, but under-predicted the uncertainty ranges. The standard coverages (68% confidence interval) ranged from approximately 65%-77% for PPR and MI methods, 40%-50% for IM and near 50% for CS. These observations illustrate some of the strengths and weaknesses of the methods considered herein and identify future directions for development and improvement.

Towards breaking the spatial resolution barriers: An optical flow and super-resolution approach for sea ice motion estimation

NASA Astrophysics Data System (ADS)

Petrou, Zisis I.; Xian, Yang; Tian, YingLi

2018-04-01

Estimation of sea ice motion at fine scales is important for a number of regional and local level applications, including modeling of sea ice distribution, ocean-atmosphere and climate dynamics, as well as safe navigation and sea operations. In this study, we propose an optical flow and super-resolution approach to accurately estimate motion from remote sensing images at a higher spatial resolution than the original data. First, an external example learning-based super-resolution method is applied on the original images to generate higher resolution versions. Then, an optical flow approach is applied on the higher resolution images, identifying sparse correspondences and interpolating them to extract a dense motion vector field with continuous values and subpixel accuracies. Our proposed approach is successfully evaluated on passive microwave, optical, and Synthetic Aperture Radar data, proving appropriate for multi-sensor applications and different spatial resolutions. The approach estimates motion with similar or higher accuracy than the original data, while increasing the spatial resolution of up to eight times. In addition, the adopted optical flow component outperforms a state-of-the-art pattern matching method. Overall, the proposed approach results in accurate motion vectors with unprecedented spatial resolutions of up to 1.5 km for passive microwave data covering the entire Arctic and 20 m for radar data, and proves promising for numerous scientific and operational applications.

Use of UAS remote sensing data to estimate crop ET at high spatial resolution

USDA-ARS?s Scientific Manuscript database

Estimation of the spatial distribution of evapotranspiration (ET) based on remotely sensed imagery has become useful for managing water in irrigated agricultural at various spatial scales. However, data acquired by conventional satellites (Landsat, ASTER, etc.) lack the spatial resolution to capture...

Sub-millimetre DOI detector based on monolithic LYSO and digital SiPM for a dedicated small-animal PET system.

PubMed

Marcinkowski, Radosław; Mollet, Pieter; Van Holen, Roel; Vandenberghe, Stefaan

2016-03-07

The mouse model is widely used in a vast range of biomedical and preclinical studies. Thanks to the ability to detect and quantify biological processes at the molecular level in vivo, PET has become a well-established tool in these investigations. However, the need to visualize and quantify radiopharmaceuticals in anatomic structures of millimetre or less requires good spatial resolution and sensitivity from small-animal PET imaging systems.In previous work we have presented a proof-of-concept of a dedicated high-resolution small-animal PET scanner based on thin monolithic scintillator crystals and Digital Photon Counter photosensor. The combination of thin monolithic crystals and MLE positioning algorithm resulted in an excellent spatial resolution of 0.7 mm uniform in the entire field of view (FOV). However, the limitation of the scanner was its low sensitivity due to small thickness of the lutetium-yttrium oxyorthosilicate (LYSO) crystals (2 mm).Here we present an improved detector design for a small-animal PET system that simultaneously achieves higher sensitivity and sustains a sub-millimetre spatial resolution. The proposed detector consists of a 5 mm thick monolithic LYSO crystal optically coupled to a Digital Photon Counter. Mean nearest neighbour (MNN) positioning combined with depth of interaction (DOI) decoding was employed to achieve sub-millimetre spatial resolution. To evaluate detector performance the intrinsic spatial resolution, energy resolution and coincidence resolving time (CRT) were measured. The average intrinsic spatial resolution of the detector was 0.60 mm full-width-at-half-maximum (FWHM). A DOI resolution of 1.66 mm was achieved. The energy resolution was 23% FWHM at 511 keV and CRT of 529 ps were measured. The improved detector design overcomes the sensitivity limitation of the previous design by increasing the nominal sensitivity of the detector block and retains an excellent intrinsic spatial resolution.

The robustness of T2 value as a trabecular structural index at multiple spatial resolutions of 7 Tesla MRI.

PubMed

Lee, D K; Song, Y K; Park, B W; Cho, H P; Yeom, J S; Cho, G; Cho, H

2018-04-15

To evaluate the robustness of MR transverse relaxation times of trabecular bone from spin-echo and gradient-echo acquisitions at multiple spatial resolutions of 7 T. The effects of MRI resolutions to T 2 and T2* of trabecular bone were numerically evaluated by Monte Carlo simulations. T 2 , T2*, and trabecular structural indices from multislice multi-echo and UTE acquisitions were measured in defatted human distal femoral condyles on a 7 T scanner. Reference structural indices were extracted from high-resolution microcomputed tomography images. For bovine knee trabecular samples with intact bone marrow, T 2 and T2* were measured by degrading spatial resolutions on a 7 T system. In the defatted trabecular experiment, both T 2 and T2* values showed strong ( |r| > 0.80) correlations with trabecular spacing and number, at a high spatial resolution of 125 µm 3 . The correlations for MR image-segmentation-derived structural indices were significantly degraded ( |r| < 0.50) at spatial resolutions of 250 and 500 µm 3 . The correlations for T2* rapidly dropped ( |r| < 0.50) at a spatial resolution of 500 µm 3 , whereas those for T 2 remained consistently high ( |r| > 0.85). In the bovine trabecular experiments with intact marrow, low-resolution (approximately 1 mm 3 , 2 minutes) T 2 values did not shorten ( |r| > 0.95 with respect to approximately 0.4 mm 3 , 11 minutes) and maintained consistent correlations ( |r| > 0.70) with respect to trabecular spacing (turbo spin echo, 22.5 minutes). T 2 measurements of trabeculae at 7 T are robust with degrading spatial resolution and may be preferable in assessing trabecular spacing index with reduced scan time, when high-resolution 3D micro-MRI is difficult to obtain. © 2018 International Society for Magnetic Resonance in Medicine.

Ionospheric TEC Weather Map Over South America

NASA Astrophysics Data System (ADS)

Takahashi, H.; Wrasse, C. M.; Denardini, C. M.; Pádua, M. B.; de Paula, E. R.; Costa, S. M. A.; Otsuka, Y.; Shiokawa, K.; Monico, J. F. Galera; Ivo, A.; Sant'Anna, N.

2016-11-01

Ionospheric weather maps using the total electron content (TEC) monitored by ground-based Global Navigation Satellite Systems (GNSS) receivers over South American continent, TECMAP, have been operationally produced by Instituto Nacional de Pesquisas Espaciais's Space Weather Study and Monitoring Program (Estudo e Monitoramento Brasileiro de Clima Especial) since 2013. In order to cover the whole continent, four GNSS receiver networks, (Rede Brasileiro de Monitoramento Contínuo) RBMC/Brazilian Institute for Geography and Statistics, Low-latitude Ionospheric Sensor Network, International GNSS Service, and Red Argentina de Monitoreo Satelital Continuo, in total 140 sites, have been used. TECMAPs with a time resolution of 10 min are produced in 12 h time delay. Spatial resolution of the map is rather low, varying between 50 and 500 km depending on the density of the observation points. Large day-to-day variabilities of the equatorial ionization anomaly have been observed. Spatial gradient of TEC from the anomaly trough (total electron content unit, 1 TECU = 1016 el m-2 (TECU) <10) to the crest region (TECU > 80) causes a large ionospheric range delay in the GNSS positioning system. Ionospheric plasma bubbles, their seeding and development, could be monitored. This plasma density (spatial and temporal) variability causes not only the GNSS-based positioning error but also radio wave scintillations. Monitoring of these phenomena by TEC mapping becomes an important issue for space weather concern for high-technology positioning system and telecommunication.

High Resolution MALDI Imaging Mass Spectrometry of Retinal Tissue Lipids

NASA Astrophysics Data System (ADS)

Anderson, David M. G.; Ablonczy, Zsolt; Koutalos, Yiannis; Spraggins, Jeffrey; Crouch, Rosalie K.; Caprioli, Richard M.; Schey, Kevin L.

2014-08-01

Matrix assisted laser desorption ionization imaging mass spectrometry (MALDI IMS) has the ability to provide an enormous amount of information on the abundances and spatial distributions of molecules within biological tissues. The rapid progress in the development of this technology significantly improves our ability to analyze smaller and smaller areas and features within tissues. The mammalian eye has evolved over millions of years to become an essential asset for survival, providing important sensory input of an organism's surroundings. The highly complex sensory retina of the eye is comprised of numerous cell types organized into specific layers with varying dimensions, the thinnest of which is the 10 μm retinal pigment epithelium (RPE). This single cell layer and the photoreceptor layer contain the complex biochemical machinery required to convert photons of light into electrical signals that are transported to the brain by axons of retinal ganglion cells. Diseases of the retina, including age-related macular degeneration (AMD), retinitis pigmentosa, and diabetic retinopathy, occur when the functions of these cells are interrupted by molecular processes that are not fully understood. In this report, we demonstrate the use of high spatial resolution MALDI IMS and FT-ICR tandem mass spectrometry in the Abca4 -/- knockout mouse model of Stargardt disease, a juvenile onset form of macular degeneration. The spatial distributions and identity of lipid and retinoid metabolites are shown to be unique to specific retinal cell layers.

Modeling of light distribution in the brain for topographical imaging

NASA Astrophysics Data System (ADS)

Okada, Eiji; Hayashi, Toshiyuki; Kawaguchi, Hiroshi

2004-07-01

Multi-channel optical imaging system can obtain a topographical distribution of the activated region in the brain cortex by a simple mapping algorithm. Near-infrared light is strongly scattered in the head and the volume of tissue that contributes to the change in the optical signal detected with source-detector pair on the head surface is broadly distributed in the brain. This scattering effect results in poor resolution and contrast in the topographic image of the brain activity. We report theoretical investigations on the spatial resolution of the topographic imaging of the brain activity. The head model for the theoretical study consists of five layers that imitate the scalp, skull, subarachnoid space, gray matter and white matter. The light propagation in the head model is predicted by Monte Carlo simulation to obtain the spatial sensitivity profile for a source-detector pair. The source-detector pairs are one dimensionally arranged on the surface of the model and the distance between the adjoining source-detector pairs are varied from 4 mm to 32 mm. The change in detected intensity caused by the absorption change is obtained by Monte Carlo simulation. The position of absorption change is reconstructed by the conventional mapping algorithm and the reconstruction algorithm using the spatial sensitivity profiles. We discuss the effective interval between the source-detector pairs and the choice of reconstruction algorithms to improve the topographic images of brain activity.

Quantification of ultrasonic texture intra-heterogeneity via volumetric stochastic modeling for tissue characterization.

PubMed

Al-Kadi, Omar S; Chung, Daniel Y F; Carlisle, Robert C; Coussios, Constantin C; Noble, J Alison

2015-04-01

Intensity variations in image texture can provide powerful quantitative information about physical properties of biological tissue. However, tissue patterns can vary according to the utilized imaging system and are intrinsically correlated to the scale of analysis. In the case of ultrasound, the Nakagami distribution is a general model of the ultrasonic backscattering envelope under various scattering conditions and densities where it can be employed for characterizing image texture, but the subtle intra-heterogeneities within a given mass are difficult to capture via this model as it works at a single spatial scale. This paper proposes a locally adaptive 3D multi-resolution Nakagami-based fractal feature descriptor that extends Nakagami-based texture analysis to accommodate subtle speckle spatial frequency tissue intensity variability in volumetric scans. Local textural fractal descriptors - which are invariant to affine intensity changes - are extracted from volumetric patches at different spatial resolutions from voxel lattice-based generated shape and scale Nakagami parameters. Using ultrasound radio-frequency datasets we found that after applying an adaptive fractal decomposition label transfer approach on top of the generated Nakagami voxels, tissue characterization results were superior to the state of art. Experimental results on real 3D ultrasonic pre-clinical and clinical datasets suggest that describing tumor intra-heterogeneity via this descriptor may facilitate improved prediction of therapy response and disease characterization. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

On the assessment of spatial resolution of PET systems with iterative image reconstruction

NASA Astrophysics Data System (ADS)

Gong, Kuang; Cherry, Simon R.; Qi, Jinyi

2016-03-01

Spatial resolution is an important metric for performance characterization in PET systems. Measuring spatial resolution is straightforward with a linear reconstruction algorithm, such as filtered backprojection, and can be performed by reconstructing a point source scan and calculating the full-width-at-half-maximum (FWHM) along the principal directions. With the widespread adoption of iterative reconstruction methods, it is desirable to quantify the spatial resolution using an iterative reconstruction algorithm. However, the task can be difficult because the reconstruction algorithms are nonlinear and the non-negativity constraint can artificially enhance the apparent spatial resolution if a point source image is reconstructed without any background. Thus, it was recommended that a background should be added to the point source data before reconstruction for resolution measurement. However, there has been no detailed study on the effect of the point source contrast on the measured spatial resolution. Here we use point source scans from a preclinical PET scanner to investigate the relationship between measured spatial resolution and the point source contrast. We also evaluate whether the reconstruction of an isolated point source is predictive of the ability of the system to resolve two adjacent point sources. Our results indicate that when the point source contrast is below a certain threshold, the measured FWHM remains stable. Once the contrast is above the threshold, the measured FWHM monotonically decreases with increasing point source contrast. In addition, the measured FWHM also monotonically decreases with iteration number for maximum likelihood estimate. Therefore, when measuring system resolution with an iterative reconstruction algorithm, we recommend using a low-contrast point source and a fixed number of iterations.

Full Spatial Resolution Infrared Sounding Application in the Preconvection Environment

NASA Astrophysics Data System (ADS)

Liu, C.; Liu, G.; Lin, T.

2013-12-01

Advanced infrared (IR) sounders such as the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI) provide atmospheric temperature and moisture profiles with high vertical resolution and high accuracy in preconvection environments. The derived atmospheric stability indices such as convective available potential energy (CAPE) and lifted index (LI) from advanced IR soundings can provide critical information 1 ; 6 h before the development of severe convective storms. Three convective storms are selected for the evaluation of applying AIRS full spatial resolution soundings and the derived products on providing warning information in the preconvection environments. In the first case, the AIRS full spatial resolution soundings revealed local extremely high atmospheric instability 3 h ahead of the convection on the leading edge of a frontal system, while the second case demonstrates that the extremely high atmospheric instability is associated with the local development of severe thunderstorm in the following hours. The third case is a local severe storm that occurred on 7-8 August 2010 in Zhou Qu, China, which caused more than 1400 deaths and left another 300 or more people missing. The AIRS full spatial resolution LI product shows the atmospheric instability 3.5 h before the storm genesis. The CAPE and LI from AIRS full spatial resolution and operational AIRS/AMSU soundings along with Geostationary Operational Environmental Satellite (GOES) Sounder derived product image (DPI) products were analyzed and compared. Case studies show that full spatial resolution AIRS retrievals provide more useful warning information in the preconvection environments for determining favorable locations for convective initiation (CI) than do the coarser spatial resolution operational soundings and lower spectral resolution GOES Sounder retrievals. The retrieved soundings are also tested in a regional data assimilation WRF 3D-var system to evaluate the potential assist in the NWP model.

Ultra high spatial and temporal resolution breast imaging at 7T.

PubMed

van de Bank, B L; Voogt, I J; Italiaander, M; Stehouwer, B L; Boer, V O; Luijten, P R; Klomp, D W J

2013-04-01

There is a need to obtain higher specificity in the detection of breast lesions using MRI. To address this need, Dynamic Contrast-Enhanced (DCE) MRI has been combined with other structural and functional MRI techniques. Unfortunately, owing to time constraints structural images at ultra-high spatial resolution can generally not be obtained during contrast uptake, whereas the relatively low spatial resolution of functional imaging (e.g. diffusion and perfusion) limits the detection of small lesions. To be able to increase spatial as well as temporal resolution simultaneously, the sensitivity of MR detection needs to increase as well as the ability to effectively accelerate the acquisition. The required gain in signal-to-noise ratio (SNR) can be obtained at 7T, whereas acceleration can be obtained with high-density receiver coil arrays. In this case, morphological imaging can be merged with DCE-MRI, and other functional techniques can be obtained at higher spatial resolution, and with less distortion [e.g. Diffusion Weighted Imaging (DWI)]. To test the feasibility of this concept, we developed a unilateral breast coil for 7T. It comprises a volume optimized dual-channel transmit coil combined with a 30-channel receive array coil. The high density of small coil elements enabled efficient acceleration in any direction to acquire ultra high spatial resolution MRI of close to 0.6 mm isotropic detail within a temporal resolution of 69 s, high spatial resolution MRI of 1.5 mm isotropic within an ultra high temporal resolution of 6.7 s and low distortion DWI at 7T, all validated in phantoms, healthy volunteers and a patient with a lesion in the right breast classified as Breast Imaging Reporting and Data System (BI-RADS) IV. Copyright © 2012 John Wiley & Sons, Ltd.

High Efficiency Multi-shot Interleaved Spiral-In/Out Acquisition for High Resolution BOLD fMRI

PubMed Central

Jung, Youngkyoo; Samsonov, Alexey A.; Liu, Thomas T.; Buracas, Giedrius T.

2012-01-01

Growing demand for high spatial resolution BOLD functional MRI faces a challenge of the spatial resolution vs. coverage or temporal resolution tradeoff, which can be addressed by methods that afford increased acquisition efficiency. Spiral acquisition trajectories have been shown to be superior to currently prevalent echo-planar imaging in terms of acquisition efficiency, and high spatial resolution can be achieved by employing multiple-shot spiral acquisition. The interleaved spiral in-out trajectory is preferred over spiral-in due to increased BOLD signal CNR and higher acquisition efficiency than that of spiral-out or non-interleaved spiral in/out trajectories (1), but to date applicability of the multi-shot interleaved spiral in-out for high spatial resolution imaging has not been studied. Herein we propose multi-shot interleaved spiral in-out acquisition and investigate its applicability for high spatial resolution BOLD fMRI. Images reconstructed from interleaved spiral-in and -out trajectories possess artifacts caused by differences in T2* decay, off-resonance and k-space errors associated with the two trajectories. We analyze the associated errors and demonstrate that application of conjugate phase reconstruction and spectral filtering can substantially mitigate these image artifacts. After applying these processing steps, the multishot interleaved spiral in-out pulse sequence yields high BOLD CNR images at in-plane resolution below 1x1 mm while preserving acceptable temporal resolution (4 s) and brain coverage (15 slices of 2 mm thickness). Moreover, this method yields sufficient BOLD CNR at 1.5 mm isotropic resolution for detection of activation in hippocampus associated with cognitive tasks (Stern memory task). The multi-shot interleaved spiral in-out acquisition is a promising technique for high spatial resolution BOLD fMRI applications. PMID:23023395

Rockfall hazard analysis using LiDAR and spatial modeling

NASA Astrophysics Data System (ADS)

Lan, Hengxing; Martin, C. Derek; Zhou, Chenghu; Lim, Chang Ho

2010-05-01

Rockfalls have been significant geohazards along the Canadian Class 1 Railways (CN Rail and CP Rail) since their construction in the late 1800s. These rockfalls cause damage to infrastructure, interruption of business, and environmental impacts, and their occurrence varies both spatially and temporally. The proactive management of these rockfall hazards requires enabling technologies. This paper discusses a hazard assessment strategy for rockfalls along a section of a Canadian railway using LiDAR and spatial modeling. LiDAR provides accurate topographical information of the source area of rockfalls and along their paths. Spatial modeling was conducted using Rockfall Analyst, a three dimensional extension to GIS, to determine the characteristics of the rockfalls in terms of travel distance, velocity and energy. Historical rockfall records were used to calibrate the physical characteristics of the rockfall processes. The results based on a high-resolution digital elevation model from a LiDAR dataset were compared with those based on a coarse digital elevation model. A comprehensive methodology for rockfall hazard assessment is proposed which takes into account the characteristics of source areas, the physical processes of rockfalls and the spatial attribution of their frequency and energy.

Developing a semi/automated protocol to post-process large volume, High-resolution airborne thermal infrared (TIR) imagery for urban waste heat mapping

NASA Astrophysics Data System (ADS)

Rahman, Mir Mustafizur

In collaboration with The City of Calgary 2011 Sustainability Direction and as part of the HEAT (Heat Energy Assessment Technologies) project, the focus of this research is to develop a semi/automated 'protocol' to post-process large volumes of high-resolution (H-res) airborne thermal infrared (TIR) imagery to enable accurate urban waste heat mapping. HEAT is a free GeoWeb service, designed to help Calgary residents improve their home energy efficiency by visualizing the amount and location of waste heat leaving their homes and communities, as easily as clicking on their house in Google Maps. HEAT metrics are derived from 43 flight lines of TABI-1800 (Thermal Airborne Broadband Imager) data acquired on May 13--14, 2012 at night (11:00 pm--5:00 am) over The City of Calgary, Alberta (˜825 km 2) at a 50 cm spatial resolution and 0.05°C thermal resolution. At present, the only way to generate a large area, high-spatial resolution TIR scene is to acquire separate airborne flight lines and mosaic them together. However, the ambient sensed temperature within, and between flight lines naturally changes during acquisition (due to varying atmospheric and local micro-climate conditions), resulting in mosaicked images with different temperatures for the same scene components (e.g. roads, buildings), and mosaic join-lines arbitrarily bisect many thousands of homes. In combination these effects result in reduced utility and classification accuracy including, poorly defined HEAT Metrics, inaccurate hotspot detection and raw imagery that are difficult to interpret. In an effort to minimize these effects, three new semi/automated post-processing algorithms (the protocol) are described, which are then used to generate a 43 flight line mosaic of TABI-1800 data from which accurate Calgary waste heat maps and HEAT metrics can be generated. These algorithms (presented as four peer-reviewed papers)---are: (a) Thermal Urban Road Normalization (TURN)---used to mitigate the microclimatic variability within a thermal flight line based on varying road temperatures; (b) Automated Polynomial Relative Radiometric Normalization (RRN)---which mitigates the between flight line radiometric variability; and (c) Object Based Mosaicking (OBM)---which minimizes the geometric distortion along the mosaic edge between each flight line. A modified Emissivity Modulation technique is also described to correct H-res TIR images for emissivity. This combined radiometric and geometric post-processing protocol (i) increases the visual agreement between TABI-1800 flight lines, (ii) improves radiometric agreement within/between flight lines, (iii) produces a visually seamless mosaic, (iv) improves hot-spot detection and landcover classification accuracy, and (v) provides accurate data for thermal-based HEAT energy models. Keywords: Thermal Infrared, Post-Processing, High Spatial Resolution, Airborne, Thermal Urban Road Normalization (TURN), Relative Radiometric Normalization (RRN), Object Based Mosaicking (OBM), TABI-1800, HEAT, and Automation.

Evaluating metrics of local topographic position for multiscale geomorphometric analysis

NASA Astrophysics Data System (ADS)

Newman, D. R.; Lindsay, J. B.; Cockburn, J. M. H.

2018-07-01

The field of geomorphometry has increasingly moved towards the use of multiscale analytical techniques, due to the availability of fine-resolution digital elevation models (DEMs) and the inherent scale-dependency of many DEM-derived attributes such as local topographic position (LTP). LTP is useful for landform and soils mapping and numerous other environmental applications. Multiple LTP metrics have been proposed and applied in the literature; however, elevation percentile (EP) is notable for its robustness to elevation error and applicability to non-Gaussian local elevation distributions, both of which are common characteristics of DEM data sets. Multiscale LTP analysis involves the estimation of spatial patterns using a range of neighborhood sizes, traditionally achieved by applying spatial filtering techniques with varying kernel sizes. While EP can be demonstrated to provide accurate estimates of LTP, the computationally intensive method of its calculation makes it unsuited to multiscale LTP analysis, particularly at large neighborhood sizes or with fine-resolution DEMs. This research assessed the suitability of three LTP metrics for multiscale terrain characterization by quantifying their computational efficiency and by comparing their ability to approximate EP spatial patterns under varying topographic conditions. The tested LTP metrics included: deviation from mean elevation (DEV), percent elevation range (PER), and the novel relative topographic position (RTP) index. The results demonstrated that DEV, calculated using the integral image technique, offers fast and scale-invariant computation. DEV spatial patterns were strongly correlated with EP (r2 range of 0.699 to 0.967) under all tested topographic conditions. RTP was also a strong predictor of EP (r2 range of 0.594 to 0.917). PER was the weakest predictor of EP (r2 range of 0.031 to 0.801) without offering a substantial improvement in computational efficiency over RTP. PER was therefore determined to be unsuitable for most multiscale applications. It was concluded that the scale-invariant property offered by the integral image used by the DEV method counters the minor losses in robustness compared to EP, making DEV the optimal LTP metric for multiscale applications.

Generating Vegetation Leaf Area Index Earth System Data Record from Multiple Sensors. Part 1; Theory

NASA Technical Reports Server (NTRS)

Ganguly, Sangram; Schull, Mitchell A.; Samanta, Arindam; Shabanov, Nikolay V.; Milesi, Cristina; Nemani, Ramakrishna R.; Knyazikhin, Yuri; Myneni, Ranga B.

2008-01-01

The generation of multi-decade long Earth System Data Records (ESDRs) of Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) from remote sensing measurements of multiple sensors is key to monitoring long-term changes in vegetation due to natural and anthropogenic influences. Challenges in developing such ESDRs include problems in remote sensing science (modeling of variability in global vegetation, scaling, atmospheric correction) and sensor hardware (differences in spatial resolution, spectral bands, calibration, and information content). In this paper, we develop a physically based approach for deriving LAI and FPAR products from the Advanced Very High Resolution Radiometer (AVHRR) data that are of comparable quality to the Moderate resolution Imaging Spectroradiometer (MODIS) LAI and FPAR products, thus realizing the objective of producing a long (multi-decadal) time series of these products. The approach is based on the radiative transfer theory of canopy spectral invariants which facilitates parameterization of the canopy spectral bidirectional reflectance factor (BRF). The methodology permits decoupling of the structural and radiometric components and obeys the energy conservation law. The approach is applicable to any optical sensor, however, it requires selection of sensor-specific values of configurable parameters, namely, the single scattering albedo and data uncertainty. According to the theory of spectral invariants, the single scattering albedo is a function of the spatial scale, and thus, accounts for the variation in BRF with sensor spatial resolution. Likewise, the single scattering albedo accounts for the variation in spectral BRF with sensor bandwidths. The second adjustable parameter is data uncertainty, which accounts for varying information content of the remote sensing measurements, i.e., Normalized Difference Vegetation Index (NDVI, low information content), vs. spectral BRF (higher information content). Implementation of this approach indicates good consistency in LAI values retrieved from NDVI (AVHRRmode) and spectral BRF (MODIS-mode). Specific details of the implementation and evaluation of the derived products are detailed in the second part of this two-paper series.

An Observation-based Assessment of Instrument Requirements for a Future Precipitation Process Observing System

NASA Astrophysics Data System (ADS)

Nelson, E.; L'Ecuyer, T. S.; Wood, N.; Smalley, M.; Kulie, M.; Hahn, W.

2017-12-01

Global models exhibit substantial biases in the frequency, intensity, duration, and spatial scales of precipitation systems. Much of this uncertainty stems from an inadequate representation of the processes by which water is cycled between the surface and atmosphere and, in particular, those that govern the formation and maintenance of cloud systems and their propensity to form the precipitation. Progress toward improving precipitation process models requires observing systems capable of quantifying the coupling between the ice content, vertical mass fluxes, and precipitation yield of precipitating cloud systems. Spaceborne multi-frequency, Doppler radar offers a unique opportunity to address this need but the effectiveness of such a mission is heavily dependent on its ability to actually observe the processes of interest in the widest possible range of systems. Planning for a next generation precipitation process observing system should, therefore, start with a fundamental evaluation of the trade-offs between sensitivity, resolution, sampling, cost, and the overall potential scientific yield of the mission. Here we provide an initial assessment of the scientific and economic trade-space by evaluating hypothetical spaceborne multi-frequency radars using a combination of current real-world and model-derived synthetic observations. Specifically, we alter the field of view, vertical resolution, and sensitivity of a hypothetical Ka- and W-band radar system and propagate those changes through precipitation detection and intensity retrievals. The results suggest that sampling biases introduced by reducing sensitivity disproportionately affect the light rainfall and frozen precipitation regimes that are critical for warm cloud feedbacks and ice sheet mass balance, respectively. Coarser spatial resolution observations introduce regime-dependent biases in both precipitation occurrence and intensity that depend on cloud regime, with even the sign of the bias varying within a single storm system. It is suggested that the next generation spaceborne radar have a minimum sensitivity of -5 dBZ and spatial resolution of at least 3 km at all frequencies to adequately sample liquid and ice phase precipitation processes globally.

Developing a bright 17 keV x-ray source for probing high-energy-density states of matter at high spatial resolution

NASA Astrophysics Data System (ADS)

Huntington, C. M.; Park, H.-S.; Maddox, B. R.; Barrios, M. A.; Benedetti, R.; Braun, D. G.; Hohenberger, M.; Landen, O. L.; Regan, S. P.; Wehrenberg, C. E.; Remington, B. A.

2015-04-01

A set of experiments were performed on the National Ignition Facility (NIF) to develop and optimize a bright, 17 keV x-ray backlighter probe using laser-irradiated Nb foils. High-resolution one-dimensional imaging was achieved using a 15 μm wide slit in a Ta substrate to aperture the Nb Heα x-rays onto an open-aperture, time integrated camera. To optimize the x-ray source for imaging applications, the effect of laser pulse shape and spatial profile on the target was investigated. Two laser pulse shapes were used—a "prepulse" shape that included a 3 ns, low-intensity laser foot preceding the high-energy 2 ns square main laser drive, and a pulse without the laser foot. The laser spatial profile was varied by the use of continuous phase plates (CPPs) on a pair of shots compared to beams at best focus, without CPPs. A comprehensive set of common diagnostics allowed for a direct comparison of imaging resolution, total x-ray conversion efficiency, and x-ray spectrum between shots. The use of CPPs was seen to reduce the high-energy tail of the x-ray spectrum, whereas the laser pulse shape had little effect on the high-energy tail. The measured imaging resolution was comparably high for all combinations of laser parameters, but a higher x-ray flux was achieved without phase plates. This increased flux was the result of smaller laser spot sizes, which allowed us to arrange the laser focal spots from multiple beams and produce an x-ray source which was more localized behind the slit aperture. Our experiments are a first demonstration of point-projection geometry imaging at NIF at the energies (>10 keV) necessary for imaging denser, higher-Z targets than have previously been investigated.

Use of nanotomographic images for structure analysis of carbonate rocks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nagata, Rodrigo; Appoloni, Carlos Roberto

Carbonate rocks store more than 50% of world's petroleum. These rocks' structures are highly complex and vary depending on many factors regarding their formation, e.g., lithification and diagenesis. In order to perform an effective extraction of petroleum it is necessary to know petrophysical parameters, such as total porosity, pore size and permeability of the reservoir rocks. Carbonate rocks usually have a range of pore sizes that goes from nanometers to meters or even dozen of meters. The nanopores and micropores might play an important role in the pores connectivity of carbonate rocks. X-ray computed tomography (CT) has been widely usedmore » to analyze petrophysical parameters in recent years. This technique has the capability to generate 2D images of the samples' inner structure and also allows the 3D reconstruction of the actual analyzed volume. CT is a powerful technique, but its results depend on the spatial resolution of the generated image. Spatial resolution is a measurement parameter that indicates the smallest object that can be detected. There are great difficulties to generate images with nanoscale resolution (nanotomographic images). In this work three carbonate rocks, one dolomite and two limestones (that will be called limestone A and limestone B) were analyzed by nanotomography. The measurements were performed with the SkyScan2011 nanotomograph, operated at 60 kV and 200 μA to measure the dolomite sample and 40 kV and 200 μA to measure the limestone samples. Each sample was measured with a given spatial resolution (270 nm for the dolomite sample, 360 nm for limestone A and 450 nm for limestone B). The achieved results for total porosity were: 3.09 % for dolomite, 0.65% for limestone A and 3.74% for limestone B. This paper reports the difficulties to acquire nanotomographic images and further analysis about the samples' pore sizes.« less

Silicon detectors for combined MR-PET and MR-SPECT imaging

NASA Astrophysics Data System (ADS)

Studen, A.; Brzezinski, K.; Chesi, E.; Cindro, V.; Clinthorne, N. H.; Cochran, E.; Grošičar, B.; Grkovski, M.; Honscheid, K.; Kagan, H.; Lacasta, C.; Llosa, G.; Mikuž, M.; Stankova, V.; Weilhammer, P.; Žontar, D.

2013-02-01

Silicon based devices can extend PET-MR and SPECT-MR imaging to applications, where their advantages in performance outweigh benefits of high statistical counts. Silicon is in many ways an excellent detector material with numerous advantages, among others: excellent energy and spatial resolution, mature processing technology, large signal to noise ratio, relatively low price, availability, versatility and malleability. The signal in silicon is also immune to effects of magnetic field at the level normally used in MR devices. Tests in fields up to 7 T were performed in a study to determine effects of magnetic field on positron range in a silicon PET device. The curvature of positron tracks in direction perpendicular to the field's orientation shortens the distance between emission and annihilation point of the positron. The effect can be fully appreciated for a rotation of the sample for a fixed field direction, compressing range in all dimensions. A popular Ga-68 source was used showing a factor of 2 improvement in image noise compared to zero field operation. There was also a little increase in noise as the reconstructed resolution varied between 2.5 and 1.5 mm. A speculative applications can be recognized in both emission modalities, SPECT and PET. Compton camera is a subspecies of SPECT, where a silicon based scatter as a MR compatible part could inserted into the MR bore and the secondary detector could operate in less constrained environment away from the magnet. Introducing a Compton camera also relaxes requirements of the radiotracers used, extending the range of conceivable photon energies beyond 140.5 keV of the Tc-99m. In PET, one could exploit the compressed sub-millimeter range of positrons in the magnetic field. To exploit the advantage, detectors with spatial resolution commensurate to the effect must be used with silicon being an excellent candidate. Measurements performed outside of the MR achieving spatial resolution below 1 mm are reported.

The influence of spatial resolution and smoothing on the detectability of resting-state and task fMRI.

PubMed

Molloy, Erin K; Meyerand, Mary E; Birn, Rasmus M

2014-02-01

Functional MRI blood oxygen level-dependent (BOLD) signal changes can be subtle, motivating the use of imaging parameters and processing strategies that maximize the temporal signal-to-noise ratio (tSNR) and thus the detection power of neuronal activity-induced fluctuations. Previous studies have shown that acquiring data at higher spatial resolutions results in greater percent BOLD signal changes, and furthermore that spatially smoothing higher resolution fMRI data improves tSNR beyond that of data originally acquired at a lower resolution. However, higher resolution images come at the cost of increased acquisition time, and the number of image volumes also influences detectability. The goal of our study is to determine how the detection power of neuronally induced BOLD fluctuations acquired at higher spatial resolutions and then spatially smoothed compares to data acquired at the lower resolutions with the same imaging duration. The number of time points acquired during a given amount of imaging time is a practical consideration given the limited ability of certain populations to lie still in the MRI scanner. We compare acquisitions at three different in-plane spatial resolutions (3.50×3.50mm(2), 2.33×2.33mm(2), 1.75×1.75mm(2)) in terms of their tSNR, contrast-to-noise ratio, and the power to detect both task-related activation and resting-state functional connectivity. The impact of SENSE acceleration, which speeds up acquisition time increasing the number of images collected, is also evaluated. Our results show that after spatially smoothing the data to the same intrinsic resolution, lower resolution acquisitions have a slightly higher detection power of task-activation in some, but not all, brain areas. There were no significant differences in functional connectivity as a function of resolution after smoothing. Similarly, the reduced tSNR of fMRI data acquired with a SENSE factor of 2 is offset by the greater number of images acquired, resulting in few significant differences in detection power of either functional activation or connectivity after spatial smoothing. © 2013.

Mapping Chinese tallow with color-infrared photography

USGS Publications Warehouse

Ramsey, Elijah W.; Nelson, G.A.; Sapkota, S.K.; Seeger, E.B.; Martella, K.D.

2002-01-01

Airborne color-infrared photography (CIR) (1:12,000 scale) was used to map localized occurrences of the widespread and aggressive Chinese tallow (Sapium sebiferum), an invasive species. Photography was collected during senescence when Chinese tallow's bright red leaves presented a high spectral contrast within the native bottomland hardwood and upland forests and marsh land-cover types. Mapped occurrences were conservative because not all senescing tallow leaves are bright red simultaneously. To simulate low spectral but high spatial resolution satellite/airborne image and digital video data, the CIR photography was transformed into raster images at spatial resolutions approximating 0.5 in and 1.0 m. The image data were then spectrally classified for the occurrence of bright red leaves associated with senescing Chinese tallow. Classification accuracies were greater than 95 percent at both spatial resolutions. There was no significant difference in either forest in the detection of tallow or inclusion of non-tallow trees associated with the two spatial resolutions. In marshes, slightly more tallow occurrences were mapped with the lower spatial resolution, but there were also more misclassifications of native land covers as tallow. Combining all land covers, there was no difference at detecting tallow occurrences (equal omission errors) between the two resolutions, but the higher spatial resolution was associated with less inclusion of non-tallow land covers as tallow (lower commission error). Overall, these results confirm that high spatial (???1 m) but low spectral resolution remote sensing data can be used for mapping Chinese tallow trees in dominant environments found in coastal and adjacent upland landscapes.

A Comparison of Spatial and Spectral Image Resolution for Mapping Invasive Plants in Coastal California

NASA Astrophysics Data System (ADS)

Underwood, Emma C.; Ustin, Susan L.; Ramirez, Carlos M.

2007-01-01

We explored the potential of detecting three target invasive species: iceplant ( Carpobrotus edulis), jubata grass ( Cortaderia jubata), and blue gum ( Eucalyptus globulus) at Vandenberg Air Force Base, California. We compared the accuracy of mapping six communities (intact coastal scrub, iceplant invaded coastal scrub, iceplant invaded chaparral, jubata grass invaded chaparral, blue gum invaded chaparral, and intact chaparral) using four images with different combinations of spatial and spectral resolution: hyperspectral AVIRIS imagery (174 wavebands, 4 m spatial resolution), spatially degraded AVIRIS (174 bands, 30 m), spectrally degraded AVIRIS (6 bands, 4 m), and both spatially and spectrally degraded AVIRIS (6 bands, 30 m, i.e., simulated Landsat ETM data). Overall success rates for classifying the six classes was 75% (kappa 0.7) using full resolution AVIRIS, 58% (kappa 0.5) for the spatially degraded AVIRIS, 42% (kappa 0.3) for the spectrally degraded AVIRIS, and 37% (kappa 0.3) for the spatially and spectrally degraded AVIRIS. A true Landsat ETM image was also classified to illustrate that the results from the simulated ETM data were representative, which provided an accuracy of 50% (kappa 0.4). Mapping accuracies using different resolution images are evaluated in the context of community heterogeneity (species richness, diversity, and percent species cover). Findings illustrate that higher mapping accuracies are achieved with images possessing high spectral resolution, thus capturing information across the visible and reflected infrared solar spectrum. Understanding the tradeoffs in spectral and spatial resolution can assist land managers in deciding the most appropriate imagery with respect to target invasives and community characteristics.

Imaging of turbulent structures and tomographic reconstruction of TORPEX plasma emissivity

NASA Astrophysics Data System (ADS)

Iraji, D.; Furno, I.; Fasoli, A.; Theiler, C.

2010-12-01

In the TORPEX [A. Fasoli et al., Phys. Plasmas 13, 055902 (2006)], a simple magnetized plasma device, low frequency electrostatic fluctuations associated with interchange waves, are routinely measured by means of extensive sets of Langmuir probes. To complement the electrostatic probe measurements of plasma turbulence and study of plasma structures smaller than the spatial resolution of probes array, a nonperturbative direct imaging system has been developed on TORPEX, including a fast framing Photron-APX-RS camera and an image intensifier unit. From the line-integrated camera images, we compute the poloidal emissivity profile of the plasma by applying a tomographic reconstruction technique using a pixel method and solving an overdetermined set of equations by singular value decomposition. This allows comparing statistical, spectral, and spatial properties of visible light radiation with electrostatic fluctuations. The shape and position of the time-averaged reconstructed plasma emissivity are observed to be similar to those of the ion saturation current profile. In the core plasma, excluding the electron cyclotron and upper hybrid resonant layers, the mean value of the plasma emissivity is observed to vary with (Te)α(ne)β, in which α =0.25-0.7 and β =0.8-1.4, in agreement with collisional radiative model. The tomographic reconstruction is applied to the fast camera movie acquired with 50 kframes/s rate and 2 μs of exposure time to obtain the temporal evolutions of the emissivity fluctuations. Conditional average sampling is also applied to visualize and measure sizes of structures associated with the interchange mode. The ω-time and the two-dimensional k-space Fourier analysis of the reconstructed emissivity fluctuations show the same interchange mode that is detected in the ω and k spectra of the ion saturation current fluctuations measured by probes. Small scale turbulent plasma structures can be detected and tracked in the reconstructed emissivity movies with the spatial resolution down to 2 cm, well beyond the spatial resolution of the probe array.

Error Estimation in an Optimal Interpolation Scheme for High Spatial and Temporal Resolution SST Analyses

NASA Technical Reports Server (NTRS)

Rigney, Matt; Jedlovec, Gary; LaFontaine, Frank; Shafer, Jaclyn

2010-01-01

Heat and moisture exchange between ocean surface and atmosphere plays an integral role in short-term, regional NWP. Current SST products lack both spatial and temporal resolution to accurately capture small-scale features that affect heat and moisture flux. NASA satellite is used to produce high spatial and temporal resolution SST analysis using an OI technique.

Instrumentation in molecular imaging.

PubMed

Wells, R Glenn

2016-12-01

In vivo molecular imaging is a challenging task and no single type of imaging system provides an ideal solution. Nuclear medicine techniques like SPECT and PET provide excellent sensitivity but have poor spatial resolution. Optical imaging has excellent sensitivity and spatial resolution, but light photons interact strongly with tissues and so only small animals and targets near the surface can be accurately visualized. CT and MRI have exquisite spatial resolution, but greatly reduced sensitivity. To overcome the limitations of individual modalities, molecular imaging systems often combine individual cameras together, for example, merging nuclear medicine cameras with CT or MRI to allow the visualization of molecular processes with both high sensitivity and high spatial resolution.

Microdome-gooved Gd(2)O(2)S:Tb scintillator for flexible and high resolution digital radiography.

PubMed

Jung, Phill Gu; Lee, Chi Hoon; Bae, Kong Myeong; Lee, Jae Min; Lee, Sang Min; Lim, Chang Hwy; Yun, Seungman; Kim, Ho Kyung; Ko, Jong Soo

2010-07-05

A flexible microdome-grooved Gd(2)O(2)S:Tb scintillator is simulated, fabricated, and characterized for digital radiography applications. According to Monte Carlo simulation results, the dome-grooved structure has a high spatial resolution, which is verified by X-ray image performance of the scintillator. The proposed scintillator has lower X-ray sensitivity than a nonstructured scintillator but almost two times higher spatial resolution at high spatial frequency. Through evaluation of the X-ray performance of the fabricated scintillators, we confirm that the microdome-grooved scintillator can be applied to next-generation flexible digital radiography systems requiring high spatial resolution.

Raman spectroscopy-based detection of chemical contaminants in food powders

NASA Astrophysics Data System (ADS)

Chao, Kuanglin; Dhakal, Sagar; Qin, Jianwei; Kim, Moon; Bae, Abigail

2016-05-01

Raman spectroscopy technique has proven to be a reliable method for qualitative detection of chemical contaminants in food ingredients and products. For quantitative imaging-based detection, each contaminant particle in a food sample must be detected and it is important to determine the necessary spatial resolution needed to effectively detect the contaminant particles. This study examined the effective spatial resolution required for detection of maleic acid in tapioca starch and benzoyl peroxide in wheat flour. Each chemical contaminant was mixed into its corresponding food powder at a concentration of 1% (w/w). Raman spectral images were collected for each sample, leveled across a 45 mm x 45 mm area, using different spatial resolutions. Based on analysis of these images, a spatial resolution of 0.5mm was selected as effective spatial resolution for detection of maleic acid in starch and benzoyl peroxide in flour. An experiment was then conducted using the 0.5mm spatial resolution to demonstrate Raman imaging-based quantitative detection of these contaminants for samples prepared at 0.1%, 0.3%, and 0.5% (w/w) concentrations. The results showed a linear correlation between the detected numbers of contaminant pixels and the actual concentrations of contaminant.

Fusion and quality analysis for remote sensing images using contourlet transform

NASA Astrophysics Data System (ADS)

Choi, Yoonsuk; Sharifahmadian, Ershad; Latifi, Shahram

2013-05-01

Recent developments in remote sensing technologies have provided various images with high spatial and spectral resolutions. However, multispectral images have low spatial resolution and panchromatic images have low spectral resolution. Therefore, image fusion techniques are necessary to improve the spatial resolution of spectral images by injecting spatial details of high-resolution panchromatic images. The objective of image fusion is to provide useful information by improving the spatial resolution and the spectral information of the original images. The fusion results can be utilized in various applications, such as military, medical imaging, and remote sensing. This paper addresses two issues in image fusion: i) image fusion method and ii) quality analysis of fusion results. First, a new contourlet-based image fusion method is presented, which is an improvement over the wavelet-based fusion. This fusion method is then applied to a case study to demonstrate its fusion performance. Fusion framework and scheme used in the study are discussed in detail. Second, quality analysis for the fusion results is discussed. We employed various quality metrics in order to analyze the fusion results both spatially and spectrally. Our results indicate that the proposed contourlet-based fusion method performs better than the conventional wavelet-based fusion methods.

Impaired temporal, not just spatial, resolution in amblyopia.

PubMed

Spang, Karoline; Fahle, Manfred

2009-11-01

In amblyopia, neuronal deficits deteriorate spatial vision including visual acuity, possibly because of a lack of use-dependent fine-tuning of afferents to the visual cortex during infancy; but temporal processing may deteriorate as well. Temporal, rather than spatial, resolution was investigated in patients with amblyopia by means of a task based on time-defined figure-ground segregation. Patients had to indicate the quadrant of the visual field where a purely time-defined square appeared. The results showed a clear decrease in temporal resolution of patients' amblyopic eyes compared with the dominant eyes in this task. The extent of this decrease in figure-ground segregation based on time of motion onset only loosely correlated with the decrease in spatial resolution and spanned a smaller range than did the spatial loss. Control experiments with artificially induced blur in normal observers confirmed that the decrease in temporal resolution was not simply due to the acuity loss. Amblyopia not only decreases spatial resolution, but also temporal factors such as time-based figure-ground segregation, even at high stimulus contrasts. This finding suggests that the realm of neuronal processes that may be disturbed in amblyopia is larger than originally thought.

Single shot trajectory design for region-specific imaging using linear and nonlinear magnetic encoding fields.

PubMed

Layton, Kelvin J; Gallichan, Daniel; Testud, Frederik; Cocosco, Chris A; Welz, Anna M; Barmet, Christoph; Pruessmann, Klaas P; Hennig, Jürgen; Zaitsev, Maxim

2013-09-01

It has recently been demonstrated that nonlinear encoding fields result in a spatially varying resolution. This work develops an automated procedure to design single-shot trajectories that create a local resolution improvement in a region of interest. The technique is based on the design of optimized local k-space trajectories and can be applied to arbitrary hardware configurations that employ any number of linear and nonlinear encoding fields. The trajectories designed in this work are tested with the currently available hardware setup consisting of three standard linear gradients and two quadrupolar encoding fields generated from a custom-built gradient insert. A field camera is used to measure the actual encoding trajectories up to third-order terms, enabling accurate reconstructions of these demanding single-shot trajectories, although the eddy current and concomitant field terms of the gradient insert have not been completely characterized. The local resolution improvement is demonstrated in phantom and in vivo experiments. Copyright © 2012 Wiley Periodicals, Inc.

Imaging thermal conductivity with nanoscale resolution using a scanning spin probe

DOE PAGES

Laraoui, Abdelghani; Aycock-Rizzo, Halley; Gao, Yang; ...

2015-11-20

The ability to probe nanoscale heat flow in a material is often limited by lack of spatial resolution. Here, we use a diamond-nanocrystal-hosted nitrogen-vacancy centre attached to the apex of a silicon thermal tip as a local temperature sensor. We apply an electrical current to heat up the tip and rely on the nitrogen vacancy to monitor the thermal changes the tip experiences as it is brought into contact with surfaces of varying thermal conductivity. By combining atomic force and confocal microscopy, we image phantom microstructures with nanoscale resolution, and attain excellent agreement between the thermal conductivity and topographic maps.more » The small mass and high thermal conductivity of the diamond host make the time response of our technique short, which we demonstrate by monitoring the tip temperature upon application of a heat pulse. Our approach promises multiple applications, from the investigation of phonon dynamics in nanostructures to the characterization of heterogeneous phase transitions and chemical reactions in various solid-state systems.« less

Measurement of replication structures at the nanometer scale using super-resolution light microscopy

PubMed Central

Baddeley, D.; Chagin, V. O.; Schermelleh, L.; Martin, S.; Pombo, A.; Carlton, P. M.; Gahl, A.; Domaing, P.; Birk, U.; Leonhardt, H.; Cremer, C.; Cardoso, M. C.

2010-01-01

DNA replication, similar to other cellular processes, occurs within dynamic macromolecular structures. Any comprehensive understanding ultimately requires quantitative data to establish and test models of genome duplication. We used two different super-resolution light microscopy techniques to directly measure and compare the size and numbers of replication foci in mammalian cells. This analysis showed that replication foci vary in size from 210 nm down to 40 nm. Remarkably, spatially modulated illumination (SMI) and 3D-structured illumination microscopy (3D-SIM) both showed an average size of 125 nm that was conserved throughout S-phase and independent of the labeling method, suggesting a basic unit of genome duplication. Interestingly, the improved optical 3D resolution identified 3- to 5-fold more distinct replication foci than previously reported. These results show that optical nanoscopy techniques enable accurate measurements of cellular structures at a level previously achieved only by electron microscopy and highlight the possibility of high-throughput, multispectral 3D analyses. PMID:19864256

Spatial Resolution and Refractive Index Contrast of Resonant Photonic Crystal Surfaces for Biosensing

PubMed Central

Triggs, G. J.; Fischer, M.; Stellinga, D.; Scullion, M. G.; Evans, G. J. O.; Krauss, T. F.

2015-01-01

By depositing a resolution test pattern on top of a Si3N4 photonic crystal resonant surface, we have measured the dependence of spatial resolution on refractive index contrast Δn. Our experimental results and finite-difference time-domain (FDTD) simulations at different refractive index contrasts show that the spatial resolution of our device reduces with reduced contrast, which is an important consideration in biosensing, where the contrast may be of order 10−2. We also compare 1-D and 2-D gratings, taking into account different incidence polarizations, leading to a better understanding of the excitation and propagation of the resonant modes in these structures, as well as how this contributes to the spatial resolution. At Δn = 0.077, we observe resolutions of 2 and 6 μm parallel to and perpendicular to the grooves of a 1-D grating, respectively, and show that for polarized illumination of a 2-D grating, resolution remains asymmetrical. Illumination of a 2-D grating at 45° results in symmetric resolution. At very low index contrast, the resolution worsens dramatically, particularly for Δn < 0.01, where we observe a resolution exceeding 10 μm for our device. In addition, we measure a reduction in the resonance linewidth as the index contrast becomes lower, corresponding to a longer resonant mode propagation length in the structure and contributing to the change in spatial resolution. PMID:26356353

First Flight of the Gamma-Ray Imager Polarimeter for Solar Flares (GRIPS) Instrument

NASA Technical Reports Server (NTRS)

Duncan, Nicole; Saint-Hilaire, P.; Shih, A. Y.; Hurford, G. J.; Bain, H. M.; Amman, M.; Mochizuki, A. B.; Hoberman, J.; Olson, J.; Maruca, B. A.;

First flight of the Gamma-Ray Imager/Polarimeter for Solar flares (GRIPS) instrument

NASA Astrophysics Data System (ADS)

Duncan, Nicole; Saint-Hilaire, P.; Shih, A. Y.; Hurford, G. J.; Bain, H. M.; Amman, M.; Mochizuki, B. A.; Hoberman, J.; Olson, J.; Maruca, B. A.; Godbole, N. M.; Smith, D. M.; Sample, J.; Kelley, N. A.; Zoglauer, A.; Caspi, A.; Kaufmann, P.; Boggs, S.; Lin, R. P.

2016-07-01

The Gamma-Ray Imager/Polarimeter for Solar flares (GRIPS) instrument is a balloon-borne telescope designed to study solar- are particle acceleration and transport. We describe GRIPS's first Antarctic long-duration flight in January 2016 and report preliminary calibration and science results. Electron and ion dynamics, particle abundances and the ambient plasma conditions in solar flares can be understood by examining hard X-ray (HXR) and gamma-ray emission (20 keV to 10 MeV). Enhanced imaging, spectroscopy and polarimetry of are emissions in this energy range are needed to study particle acceleration and transport questions. The GRIPS instrument is specifically designed to answer questions including: What causes the spatial separation between energetic electrons producing hard X-rays and energetic ions producing gamma-ray lines? How anisotropic are the relativistic electrons, and why can they dominate in the corona? How do the compositions of accelerated and ambient material vary with space and time, and why? GRIPS's key technological improvements over the current solar state of the art at HXR/gamma-ray energies, the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI), include 3D position-sensitive germanium detectors (3D-GeDs) and a single-grid modulation collimator, the multi-pitch rotating modulator (MPRM). The 3D-GeDs have spectral FWHM resolution of a few hundred keV and spatial resolution <1 mm3. For photons that Compton scatter, usually > 150 keV, the energy deposition sites can be tracked, providing polarization measurements as well as enhanced background reduction through Compton imaging. Each of GRIPS's detectors has 298 electrode strips read out with ASIC/FPGA electronics. In GRIPS's energy range, indirect imaging methods provide higher resolution than focusing optics or Compton imaging techniques. The MPRM gridimaging system has a single-grid design which provides twice the throughput of a bi-grid imaging system like RHESSI. The grid is composed of 2.5 cm deep tungsten-copper slats, and quasi-continuous FWHM angular coverage from 12.5-162 arcsecs are achieved by varying the slit pitch between 1-13 mm. This angular resolution is capable of imaging the separate magnetic loop footpoint emissions in a variety of are sizes. In comparison, RHESSI's 35-arcsec resolution at similar energies makes the footpoints resolvable in only the largest ares.

Performance characteristics of dedicated molecular breast imaging systems at low doses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Long, Zaiyang; Conners, Amy L.; Hunt, Katie N.

Purpose: The purpose of this study was to compare the system performance characteristics and lesion detection capability of two molecular breast imaging (MBI) systems: a multicrystal sodium iodide (NaI)-based single-head system and a cadmium zinc telluride (CZT)-based dual-head system at low administered doses (150–300 MBq) of Tc-99m sestamibi. Methods: System performance characteristics including count sensitivity, uniformity, energy resolution, and spatial resolution were measured using standard NEMA methods, or a modified version thereof in cases where the standard NEMA protocol could not be applied. A contrast-detail phantom with 48 lesions at varying depths from the collimator surface was used to assessmore » lesion contrast-to-noise-ratio (CNR) using background count densities comparable to those observed in patient studies performed with administered doses of 150 MBq Tc-99m sestamibi. Lesions with CNR >3 were deemed to be detectable. Thirty patients undergoing MBI examinations with administered doses of 150–300 MBq were scanned for an additional view on the pixelated NaI system. CNR was calculated for lesions observed on patient images. Background count densities of patient images were measured and compared between the two systems. Results: Over the central field of view, integral and differential uniformity were 6.1% and 4.2%, respectively, for the pixelated NaI system, and 3.8% and 2.7%, respectively, for the CZT system. Count sensitivity was 10.8 kcts/min/MBq for the NaI system and 32.9 kcts/min/MBq for the CZT system. Energy resolution was 13.5% on the pixelated NaI system and 4.5% on the CZT system. Spatial resolution (full-width at half-maximum) for the pixelated NaI detector was 4.2 mm at a distance of 1.2 cm from the collimator and 5.2 mm at 3.1 cm. Spatial resolution of a single CZT detector was 2.9 mm at a distance of 1.2 cm from the collimator and 4.7 mm at 3.1 cm. Effective spatial resolution obtained with dual-head CZT was below 4.7 mm throughout a simulated breast thickness of 6 cm. From contrast-detail phantom images of lesions at distances of 1.5–4.5 cm from the collimator face, the CZT system detected 124 of 144 (86%) of lesions compared to 97 of 144 (67%) with the NaI system. In patient studies, from comparison of the same view with both systems, a total of 7 breast lesions were identified on CZT system in seven patients, and 4 of 7 (57%) were detected on NaI system. Patient image background count densities on the CZT system were on average 3.4 times higher than those on the NaI system. Conclusions: The CZT system demonstrated better uniformity, count sensitivity, spatial resolution, energy resolution, and lesion detection in phantom and patient studies compared to the NaI system. At administered doses of 150–300 MBq Tc-99m sestamibi, patient results obtained with CZT systems may not be directly translatable to NaI systems.« less

High spatial resolution compressed sensing (HSPARSE) functional MRI.

PubMed

Fang, Zhongnan; Van Le, Nguyen; Choy, ManKin; Lee, Jin Hyung

2016-08-01

To propose a novel compressed sensing (CS) high spatial resolution functional MRI (fMRI) method and demonstrate the advantages and limitations of using CS for high spatial resolution fMRI. A randomly undersampled variable density spiral trajectory enabling an acceleration factor of 5.3 was designed with a balanced steady state free precession sequence to achieve high spatial resolution data acquisition. A modified k-t SPARSE method was then implemented and applied with a strategy to optimize regularization parameters for consistent, high quality CS reconstruction. The proposed method improves spatial resolution by six-fold with 12 to 47% contrast-to-noise ratio (CNR), 33 to 117% F-value improvement and maintains the same temporal resolution. It also achieves high sensitivity of 69 to 99% compared the original ground-truth, small false positive rate of less than 0.05 and low hemodynamic response function distortion across a wide range of CNRs. The proposed method is robust to physiological noise and enables detection of layer-specific activities in vivo, which cannot be resolved using the highest spatial resolution Nyquist acquisition. The proposed method enables high spatial resolution fMRI that can resolve layer-specific brain activity and demonstrates the significant improvement that CS can bring to high spatial resolution fMRI. Magn Reson Med 76:440-455, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Soil organic carbon - a large scale paired catchment assessment

NASA Astrophysics Data System (ADS)

Kunkel, V.; Hancock, G. R.; Wells, T.

2016-12-01

Soil organic carbon (SOC) concentration can vary both spatially and temporally driven by differences in soil properties, topography and climate. However most studies have focused on point scale data sets with a paucity of studies examining larger scale catchments. Here we examine the spatial and temporal distribution of SOC for two large catchments. The Krui (575 km2) and Merriwa River (675km2) catchments (New South Wales, Australia). Both have similar shape, soils, topography and orientation. We show that SOC distribution is very similar for both catchments and that elevation (and associated increase in soil moisture) is a major influence on SOC. We also show that there is little change in SOC from the initial assessment in 2006 to 2015 despite a major drought from 2003 to 2010 and extreme rainfall events in 2007 and 2010 -therefore SOC concentration appears robust. However, we found significant relationships between erosion and deposition patterns (as quantified using 137Cs) and SOC for both catchments again demonstrating a strong geomorphic relationship. Vegetation across the catchments was assessed using remote sensing (Landsat and MODIS). Vegetation patterns were temporally consistent with above ground biomass increasing with elevation. SOC could be predicted using both these low and high resolution remote sensing platforms. Results indicate that, although moderate resolution (250 m) allows for reasonable prediction of the spatial distribution of SOC, the higher resolution (30 m) improved the strength of the SOC-NDVI relationship. The relationship between SOC and 137Cs, as a surrogate for the erosion and deposition of SOC, suggested that sediment transport and deposition influences the distribution of SOC within the catchment. The findings demonstrate that over the large catchment scale and at the decadal time scale that SOC is relatively constant and can largely be predicted by topography.

Assessment of Observational Uncertainty in Extreme Precipitation Events over the Continental United States

NASA Astrophysics Data System (ADS)

Slinskey, E. A.; Loikith, P. C.; Waliser, D. E.; Goodman, A.

2017-12-01

Extreme precipitation events are associated with numerous societal and environmental impacts. Furthermore, anthropogenic climate change is projected to alter precipitation intensity across portions of the Continental United States (CONUS). Therefore, a spatial understanding and intuitive means of monitoring extreme precipitation over time is critical. Towards this end, we apply an event-based indicator, developed as a part of NASA's support of the ongoing efforts of the US National Climate Assessment, which assigns categories to extreme precipitation events based on 3-day storm totals as a basis for dataset intercomparison. To assess observational uncertainty across a wide range of historical precipitation measurement approaches, we intercompare in situ station data from the Global Historical Climatology Network (GHCN), satellite-derived precipitation data from NASA's Tropical Rainfall Measuring Mission (TRMM), gridded in situ station data from the Parameter-elevation Regressions on Independent Slopes Model (PRISM), global reanalysis from NASA's Modern Era Retrospective-Analysis version 2 (MERRA 2), and regional reanalysis with gauge data assimilation from NCEP's North American Regional Reanalysis (NARR). Results suggest considerable variability across the five-dataset suite in the frequency, spatial extent, and magnitude of extreme precipitation events. Consistent with expectations, higher resolution datasets were found to resemble station data best and capture a greater frequency of high-end extreme events relative to lower spatial resolution datasets. The degree of dataset agreement varies regionally, however all datasets successfully capture the seasonal cycle of precipitation extremes across the CONUS. These intercomparison results provide additional insight about observational uncertainty and the ability of a range of precipitation measurement and analysis products to capture extreme precipitation event climatology. While the event category threshold is fixed in this analysis, preliminary results from the development of a flexible categorization scheme, that scales with grid resolution, are presented.

Spatio-Temporal Analysis of MODIS Retrieved Precipitable Water Vapor over Urban and Rural Areas in the Philippines

NASA Astrophysics Data System (ADS)

Galvez, M. C. D.; Castilla, R. M.; Catenza, J. L. U.; Soronio, H.; Vallar, E. A.

2016-12-01

Precipitable water vapor (PWV) is a component of the atmosphere that significantly influences many atmospheric processes. It plays a dominant role in the high-energy thermodynamics of the atmosphere, notably, the genesis of storm systems. Remote sensing of the atmosphere using MODerate resolution Imaging Spectroradiometer (MODIS) offers a relatively inexpensive method to estimate atmospheric water vapour in the form of columnar measurements from its 936 nm near-infrared band. Daily Level 3 data with 1 degree grid spatial resolution from MODIS was used in order to determine the temporal and spatial variability of precipitable water between urban and rural areas in the Philippines. The PWV values were rasterized and spatially interpolated to be stored in a 1 kilometer grid resolution using the nearest-neighbor algorithm. General Linear Models were established to determine the main and interaction effects on PWV values of several categorical factors e.g. time, administrative region, and geographic classification. Comparison between the urban and rural areas in the Philippines showed that there is a significant difference between the values between these demographic dimensions. The mean PWV in the urban areas was found to be 0.0473 cm greater than the mean PWV of the rural areas. Lower levels of precipitable water vapour in rural places can be attributed to the low humidity as a result of a deficit of precipitation; while higher levels in urban areas can be accounted for by vehicle exhaust, industrial emissions, and irrigation of parks and gardens. In general, PWV varies depending on the season when solar insolation affects surface temperature, thus influencing the rate of evaporation. Using the regression line algorithm, the PWV values for rural areas have increased to 0.904 cm and 0.434 cm for urban areas from the year 2005 to 2015.

Contrast statistics for foveated visual systems: fixation selection by minimizing contrast entropy

NASA Astrophysics Data System (ADS)

Raj, Raghu; Geisler, Wilson S.; Frazor, Robert A.; Bovik, Alan C.

2005-10-01

The human visual system combines a wide field of view with a high-resolution fovea and uses eye, head, and body movements to direct the fovea to potentially relevant locations in the visual scene. This strategy is sensible for a visual system with limited neural resources. However, for this strategy to be effective, the visual system needs sophisticated central mechanisms that efficiently exploit the varying spatial resolution of the retina. To gain insight into some of the design requirements of these central mechanisms, we have analyzed the effects of variable spatial resolution on local contrast in 300 calibrated natural images. Specifically, for each retinal eccentricity (which produces a certain effective level of blur), and for each value of local contrast observed at that eccentricity, we measured the probability distribution of the local contrast in the unblurred image. These conditional probability distributions can be regarded as posterior probability distributions for the ``true'' unblurred contrast, given an observed contrast at a given eccentricity. We find that these conditional probability distributions are adequately described by a few simple formulas. To explore how these statistics might be exploited by central perceptual mechanisms, we consider the task of selecting successive fixation points, where the goal on each fixation is to maximize total contrast information gained about the image (i.e., minimize total contrast uncertainty). We derive an entropy minimization algorithm and find that it performs optimally at reducing total contrast uncertainty and that it also works well at reducing the mean squared error between the original image and the image reconstructed from the multiple fixations. Our results show that measurements of local contrast alone could efficiently drive the scan paths of the eye when the goal is to gain as much information about the spatial structure of a scene as possible.

Conjunction of color and form without attention: evidence from an orientation-contingent color aftereffect.

PubMed

Houck, M R; Hoffman, J E

1986-05-01

According to feature-integration theory (Treisman & Gelade, 1980), separable features such as color and shape exist in separate maps in preattentive vision and can be integrated only through the use of spatial attention. Many perceptual aftereffects, however, which are also assumed to reflect the features available in preattentive vision, are sensitive to conjunctions of features. One possible resolution of these views holds that adaptation to conjunctions depends on spatial attention. We tested this proposition by presenting observers with gratings varying in color and orientation. The resulting McCollough aftereffects were independent of whether the adaptation stimuli were presented inside or outside of the focus of spatial attention. Therefore, color and shape appear to be conjoined preattentively, when perceptual aftereffects are used as the measure. These same stimuli, however, appeared to be separable in two additional experiments that required observers to search for gratings of a specified color and orientation. These results show that different experimental procedures may be tapping into different stages of preattentive vision.

Perspectives on the geographic stability and mobility of people in cities

PubMed Central

Hanson, Susan

2005-01-01

A class of questions in the human environment sciences focuses on the relationship between individual or household behavior and local geographic context. Central to these questions is the nature of people's geographic mobility as well as the duration of their locational stability at varying spatial and temporal scales. The problem for researchers is that the processes of mobility/stability are temporally and spatially dynamic and therefore difficult to measure. Whereas time and space are continuous, analysts must select levels of aggregation for both length of time in place and spatial scale of place that fit with the problem in question. Previous work has emphasized mobility and suppressed stability as an analytic category. I focus here on stability and show how analyzing individuals' stability requires also analyzing their mobility. Through an empirical example centered on the relationship between entrepreneurship and place, I demonstrate how a spotlight on stability illuminates a resolution to the measurement problem by highlighting the interdependence between the time and space dimensions of stability/mobility. PMID:16230616

Accounting for Limited Detection Efficiency and Localization Precision in Cluster Analysis in Single Molecule Localization Microscopy

PubMed Central

Shivanandan, Arun; Unnikrishnan, Jayakrishnan; Radenovic, Aleksandra

2015-01-01

Single Molecule Localization Microscopy techniques like PhotoActivated Localization Microscopy, with their sub-diffraction limit spatial resolution, have been popularly used to characterize the spatial organization of membrane proteins, by means of quantitative cluster analysis. However, such quantitative studies remain challenged by the techniques’ inherent sources of errors such as a limited detection efficiency of less than 60%, due to incomplete photo-conversion, and a limited localization precision in the range of 10 – 30nm, varying across the detected molecules, mainly depending on the number of photons collected from each. We provide analytical methods to estimate the effect of these errors in cluster analysis and to correct for them. These methods, based on the Ripley’s L(r) – r or Pair Correlation Function popularly used by the community, can facilitate potentially breakthrough results in quantitative biology by providing a more accurate and precise quantification of protein spatial organization. PMID:25794150

Electric crosstalk impairs spatial resolution of multi-electrode arrays in retinal implants

NASA Astrophysics Data System (ADS)

Wilke, R. G. H.; Khalili Moghadam, G.; Lovell, N. H.; Suaning, G. J.; Dokos, S.

2011-08-01

Active multi-electrode arrays are used in vision prostheses, including optic nerve cuffs and cortical and retinal implants for stimulation of neural tissue. For retinal implants, arrays with up to 1500 electrodes are used in clinical trials. The ability to convey information with high spatial resolution is critical for these applications. To assess the extent to which spatial resolution is impaired by electric crosstalk, finite-element simulation of electric field distribution in a simplified passive tissue model of the retina is performed. The effects of electrode size, electrode spacing, distance to target cells, and electrode return configuration (monopolar, tripolar, hexagonal) on spatial resolution is investigated in the form of a mathematical model of electric field distribution. Results show that spatial resolution is impaired with increased distance from the electrode array to the target cells. This effect can be partly compensated by non-monopolar electrode configurations and larger electrode diameters, albeit at the expense of lower pixel densities due to larger covering areas by each stimulation electrode. In applications where multi-electrode arrays can be brought into close proximity to target cells, as presumably with epiretinal implants, smaller electrodes in monopolar configuration can provide the highest spatial resolution. However, if the implantation site is further from the target cells, as is the case in suprachoroidal approaches, hexagonally guarded electrode return configurations can convey higher spatial resolution. This paper was originally submitted for the special issue containing contributions from the Sixth Biennial Research Congress of The Eye and the Chip.

Quantifying the Precipitation Loss of Radiation Belt Electrons During a Rapid Dropout Event

NASA Astrophysics Data System (ADS)

Pham, K. H.; Tu, W.; Xiang, Z.

2017-10-01

Relativistic electron flux in the radiation belt can drop by orders of magnitude within the timespan of hours. In this study, we used the drift-diffusion model that includes azimuthal drift and pitch angle diffusion of electrons to simulate low-altitude electron distribution observed by POES/MetOp satellites for rapid radiation belt electron dropout event occurring on 1 May 2013. The event shows fast dropout of MeV energy electrons at L > 4 over a few hours, observed by the Van Allen Probes mission. By simulating the electron distributions observed by multiple POES satellites, we resolve the precipitation loss with both high spatial and temporal resolutions and a range of energies. We estimate the pitch angle diffusion coefficients as a function of energy, pitch angle, and L-shell and calculate corresponding electron lifetimes during the event. The simulation results show fast electron precipitation loss at L > 4 during the electron dropout, with estimated electron lifetimes on the order of half an hour for MeV energies. The electron loss rate shows strong energy dependence with faster loss at higher energies, which suggest that this dropout event is dominated by quick and localized scattering process that prefers higher energy electrons. The improved temporal and spatial resolutions of electron precipitation rates provided by multiple low-altitude observations can resolve fast-varying electron loss during rapid electron dropouts (over a few hours), which occur too fast for a single low-altitude satellite. The capability of estimating the fast-varying electron lifetimes during rapid dropout events is an important step in improving radiation belt model accuracy.

Resolution testing and limitations of geodetic and tsunami datasets for finite fault inversions along subduction zones

NASA Astrophysics Data System (ADS)

Williamson, A.; Newman, A. V.

2017-12-01

Finite fault inversions utilizing multiple datasets have become commonplace for large earthquakes pending data availability. The mixture of geodetic datasets such as Global Navigational Satellite Systems (GNSS) and InSAR, seismic waveforms, and when applicable, tsunami waveforms from Deep-Ocean Assessment and Reporting of Tsunami (DART) gauges, provide slightly different observations that when incorporated together lead to a more robust model of fault slip distribution. The merging of different datasets is of particular importance along subduction zones where direct observations of seafloor deformation over the rupture area are extremely limited. Instead, instrumentation measures related ground motion from tens to hundreds of kilometers away. The distance from the event and dataset type can lead to a variable degree of resolution, affecting the ability to accurately model the spatial distribution of slip. This study analyzes the spatial resolution attained individually from geodetic and tsunami datasets as well as in a combined dataset. We constrain the importance of distance between estimated parameters and observed data and how that varies between land-based and open ocean datasets. Analysis focuses on accurately scaled subduction zone synthetic models as well as analysis of the relationship between slip and data in recent large subduction zone earthquakes. This study shows that seafloor deformation sensitive datasets, like open-ocean tsunami waveforms or seafloor geodetic instrumentation, can provide unique offshore resolution for understanding most large and particularly tsunamigenic megathrust earthquake activity. In most environments, we simply lack the capability to resolve static displacements using land-based geodetic observations.

CO and Dust Properties in the TW Hya Disk from High-resolution ALMA Observations

NASA Astrophysics Data System (ADS)

Huang, Jane; Andrews, Sean M.; Cleeves, L. Ilsedore; Öberg, Karin I.; Wilner, David J.; Bai, Xuening; Birnstiel, Til; Carpenter, John; Hughes, A. Meredith; Isella, Andrea; Pérez, Laura M.; Ricci, Luca; Zhu, Zhaohuan

2018-01-01

We analyze high angular resolution ALMA observations of the TW Hya disk to place constraints on the CO and dust properties. We present new, sensitive observations of the 12CO J = 3 ‑ 2 line at a spatial resolution of 8 au (0.″14). The CO emission exhibits a bright inner core, a shoulder at r ≈ 70 au, and a prominent break in slope at r ≈ 90 au. Radiative transfer modeling is used to demonstrate that the emission morphology can be reasonably reproduced with a 12CO column density profile featuring a steep decrease at r ≈ 15 au and a secondary bump peaking at r ≈ 70 au. Similar features have been identified in observations of rarer CO isotopologues, which trace heights closer to the midplane. Substructure in the underlying gas distribution or radially varying CO depletion that affects much of the disk’s vertical extent may explain the shared emission features of the main CO isotopologues. We also combine archival 1.3 mm and 870 μm continuum observations to produce a spectral index map at a spatial resolution of 2 au. The spectral index rises sharply at the continuum emission gaps at radii of 25, 41, and 47 au. This behavior suggests that the grains within the gaps are no larger than a few millimeters. Outside the continuum gaps, the low spectral index values of α ≈ 2 indicate either that grains up to centimeter size are present or that the bright continuum rings are marginally optically thick at millimeter wavelengths.

Requirements for a reliable millennium temperature reconstruction

NASA Astrophysics Data System (ADS)

Christiansen, Bo; Ljungqvist, Fredrik

2014-05-01

Quantitative temperature reconstructions are hampered by several problems. Proxy records are sparse which is witnessed by the fact that roughly half of all available high-resolution millennia-long proxy data have been published in the last five years. Moreover, proxies are inhomogeneously distributed around the globe and they often have coarse temporal resolution. The period of overlap between proxies and instrumental observations - the calibration period - is brief and dominated by a strong warming trend. Furthermore, proxies are often only weakly correlated to temperature and it is common that some form of screening procedure is applied to select only informative proxies. We study the influence of these limitations on the reliability of temperature reconstructions for the previous millennium. This influence depends on the spatial and temporal correlation structure of the surface temperature field. It also depends on the reconstruction methodology. We use gridded surface temperature data from GISTEMP and HadCRUT4 to investigate the geographical distribution of the spatial decorrelation length and of the temporal decorrelation time. The spatial decorrelation length varies with more than a factor of 5 with the largest values in the region dominated by the El Nino-Southern Oscillation. The temporal decorrelation time varies less with typical values of 1-2 years over land and 2-5 years over ocean. We also investigate the correlations between proxies and local temperatures (using the 91 proxies from Christiansen and Ljungqvist 2012) and between local temperatures and the NH mean temperature. These correlations have typical values around 0.3 but cover a wide range from weakly negative to larger than 0.8. The results outlined above allow us to identify regions where the effect of the lack of proxies is most important. They also inform us on the consequences of the short calibration period and on the influence of the recent trend. Finally, we demonstrate the effect of a weak proxy/temperature relationship on three different simple reconstruction methodologies. We show that the size and strength of this effect depends strongly on the chosen methodology.

The influence of multispectral scanner spatial resolution on forest feature classification

NASA Technical Reports Server (NTRS)

Sadowski, F. G.; Malila, W. A.; Sarno, J. E.; Nalepka, R. F.

1977-01-01

Inappropriate spatial resolution and corresponding data processing techniques may be major causes for non-optimal forest classification results frequently achieved from multispectral scanner (MSS) data. Procedures and results of empirical investigations are studied to determine the influence of MSS spatial resolution on the classification of forest features into levels of detail or hierarchies of information that might be appropriate for nationwide forest surveys and detailed in-place inventories. Two somewhat different, but related studies are presented. The first consisted of establishing classification accuracies for several hierarchies of features as spatial resolution was progressively coarsened from (2 meters) squared to (64 meters) squared. The second investigated the capabilities for specialized processing techniques to improve upon the results of conventional processing procedures for both coarse and fine resolution data.

Definition of SMOS Level 3 Land Products for the Villafranca del Castillo Data Processing Centre (CP34)

NASA Astrophysics Data System (ADS)

Lopez-Baeza, E.; Monsoriu Torres, A.; Font, J.; Alonso, O.

2009-04-01

The ESA SMOS (Soil Moisture and Ocean Salinity) Mission is planned to be launched in July 2009. The satellite will measure soil moisture over the continents and surface salinity of the oceans at resolutions that are sufficient for climatological-type studies. This paper describes the procedure to be used at the Spanish SMOS Level 3 and 4 Data Processing Centre (CP34) to generate Soil Moisture and other Land Surface Product maps from SMOS Level 2 data. This procedure can be used to map Soil Moisture, Vegetation Water Content and Soil Dielectric Constant data into different pre-defined spatial grids with fixed temporal frequency. The L3 standard Land Surface Products to be generated at CP34 are: Soil Moisture products: maximum spatial resolution with no spatial averaging, temporal averaging of 3 days, daily generation maximum spatial resolution with no spatial averaging, temporal averaging of 10 days, generation frequency of once every 10 days. b': maximum spatial resolution with no spatial averaging, temporal averaging of monthly decades (1st to 10th of the month, 11th to 20th of the month, 21st to last day of the month), generation frequency of once every decade monthly average, temporal averaging from L3 decade averages, monthly generation Seasonal average, temporal averaging from L3 monthly averages, seasonally generation yearly average, temporal averaging from L3 monthly averages, yearly generation Vegetation Water Content products: maximum spatial resolution with no spatial averaging, temporal averaging of 10 days, generation frequency of once every 10 days. a': maximum spatial resolution with no spatial averaging, temporal averaging of monthly decades (1st to 10th of the month, 11th to 20th of the month, 21st to last day of the month) using simple averaging method over the L2 products in ISEA grid, generation frequency of once every decade monthly average, temporal averaging from L3 decade averages, monthly generation seasonal average, temporal averaging from L3 monthly averages, seasonally generation yearly average, temporal averaging from L3 monthly averages, yearly generation Dielectric Constant products: (the dielectric constant products are delivered together with soil moisture products, with the same averaging periods and generation frequency): maximum spatial resolution with no spatial averaging, temporal averaging of 3 days, daily generation maximum spatial resolution with no spatial averaging, temporal averaging of 10 days, generation frequency of once every 10 days. b': maximum spatial resolution with no spatial averaging, temporal averaging of monthly decades (1st to 10th of the month, 11th to 20th of the month, 21st to last day of the month), generation frequency of once every decade monthly average, temporal averaging from L3 decade averages, monthly generation seasonal average, temporal averaging from L3 monthly averages, seasonally generation yearly average, temporal averaging from L3 monthly averages, yearly generation.

Simultaneous multiview capture and fusion improves spatial resolution in wide-field and light-sheet microscopy

PubMed Central

Wu, Yicong; Chandris, Panagiotis; Winter, Peter W.; Kim, Edward Y.; Jaumouillé, Valentin; Kumar, Abhishek; Guo, Min; Leung, Jacqueline M.; Smith, Corey; Rey-Suarez, Ivan; Liu, Huafeng; Waterman, Clare M.; Ramamurthi, Kumaran S.; La Riviere, Patrick J.; Shroff, Hari

2016-01-01

Most fluorescence microscopes are inefficient, collecting only a small fraction of the emitted light at any instant. Besides wasting valuable signal, this inefficiency also reduces spatial resolution and causes imaging volumes to exhibit significant resolution anisotropy. We describe microscopic and computational techniques that address these problems by simultaneously capturing and subsequently fusing and deconvolving multiple specimen views. Unlike previous methods that serially capture multiple views, our approach improves spatial resolution without introducing any additional illumination dose or compromising temporal resolution relative to conventional imaging. When applying our methods to single-view wide-field or dual-view light-sheet microscopy, we achieve a twofold improvement in volumetric resolution (~235 nm × 235 nm × 340 nm) as demonstrated on a variety of samples including microtubules in Toxoplasma gondii, SpoVM in sporulating Bacillus subtilis, and multiple protein distributions and organelles in eukaryotic cells. In every case, spatial resolution is improved with no drawback by harnessing previously unused fluorescence. PMID:27761486

High Resolution Aerosol Data from MODIS Satellite for Urban Air Quality Studies

NASA Technical Reports Server (NTRS)

Chudnovsky, A.; Lyapustin, A.; Wang, Y.; Tang, C.; Schwartz, J.; Koutrakis, P.

2013-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not suitable for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM(sub 2.5) as measured by the 27 EPA ground monitoring stations was investigated. These results were also compared to conventional MODIS 10 km AOD retrievals (MOD04) for the same days and locations. The coefficients of determination for MOD04 and for MAIAC are R(exp 2) =0.45 and 0.50 respectively, suggested that AOD is a reasonably good proxy for PM(sub 2.5) ground concentrations. Finally, we studied the relationship between PM(sub 2.5) and AOD at the intra-urban scale (10 km) in Boston. The fine resolution results indicated spatial variability in particle concentration at a sub-10 kilometer scale. A local analysis for the Boston area showed that the AOD-PM(sub 2.5) relationship does not depend on relative humidity and air temperatures below approximately 7 C. The correlation improves for temperatures above 7 - 16 C. We found no dependence on the boundary layer height except when the former was in the range 250-500 m. Finally, we apply a mixed effects model approach to MAIAC aerosol optical depth (AOD) retrievals from MODIS to predict PM(sub 2.5) concentrations within the greater Boston area. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations (out-of-sample R(exp 2) of 0.86). Therefore, adjustment for the daily variability in the AOD-PM(sub 2.5) relationship provides a means for obtaining spatially-resolved PM(sub 2.5) concentrations.

The Effect of Spatial and Temporal Resolution of Cine Phase Contrast MRI on Wall Shear Stress and Oscillatory Shear Index Assessment

PubMed Central

Gijsen, Frank J.; Marquering, Henk; van Ooij, Pim; vanBavel, Ed; Wentzel, Jolanda J.; Nederveen, Aart J.

2016-01-01

Introduction Wall shear stress (WSS) and oscillatory shear index (OSI) are associated with atherosclerotic disease. Both parameters are derived from blood velocities, which can be measured with phase-contrast MRI (PC-MRI). Limitations in spatiotemporal resolution of PC-MRI are known to affect these measurements. Our aim was to investigate the effect of spatiotemporal resolution using a carotid artery phantom. Methods A carotid artery phantom was connected to a flow set-up supplying pulsatile flow. MRI measurement planes were placed at the common carotid artery (CCA) and internal carotid artery (ICA). Two-dimensional PC-MRI measurements were performed with thirty different spatiotemporal resolution settings. The MRI flow measurement was validated with ultrasound probe measurements. Mean flow, peak flow, flow waveform, WSS and OSI were compared for these spatiotemporal resolutions using regression analysis. The slopes of the regression lines were reported in %/mm and %/100ms. The distribution of low and high WSS and OSI was compared between different spatiotemporal resolutions. Results The mean PC-MRI CCA flow (2.5±0.2mL/s) agreed with the ultrasound probe measurements (2.7±0.02mL/s). Mean flow (mL/s) depended only on spatial resolution (CCA:-13%/mm, ICA:-49%/mm). Peak flow (mL/s) depended on both spatial (CCA:-13%/mm, ICA:-17%/mm) and temporal resolution (CCA:-19%/100ms, ICA:-24%/100ms). Mean WSS (Pa) was in inverse relationship only with spatial resolution (CCA:-19%/mm, ICA:-33%/mm). OSI was dependent on spatial resolution for CCA (-26%/mm) and temporal resolution for ICA (-16%/100ms). The regions of low and high WSS and OSI matched for most of the spatiotemporal resolutions (CCA:30/30, ICA:28/30 cases for WSS; CCA:23/30, ICA:29/30 cases for OSI). Conclusion We show that both mean flow and mean WSS are independent of temporal resolution. Peak flow and OSI are dependent on both spatial and temporal resolution. However, the magnitude of mean and peak flow, WSS and OSI, and the spatial distribution of OSI and WSS did not exhibit a strong dependency on spatiotemporal resolution. PMID:27669568

Simulating the directional, spectral and textural properties of a large-scale scene at high resolution using a MODIS BRDF product

NASA Astrophysics Data System (ADS)

Rengarajan, Rajagopalan; Goodenough, Adam A.; Schott, John R.

2016-10-01

Many remote sensing applications rely on simulated scenes to perform complex interaction and sensitivity studies that are not possible with real-world scenes. These applications include the development and validation of new and existing algorithms, understanding of the sensor's performance prior to launch, and trade studies to determine ideal sensor configurations. The accuracy of these applications is dependent on the realism of the modeled scenes and sensors. The Digital Image and Remote Sensing Image Generation (DIRSIG) tool has been used extensively to model the complex spectral and spatial texture variation expected in large city-scale scenes and natural biomes. In the past, material properties that were used to represent targets in the simulated scenes were often assumed to be Lambertian in the absence of hand-measured directional data. However, this assumption presents a limitation for new algorithms that need to recognize the anisotropic behavior of targets. We have developed a new method to model and simulate large-scale high-resolution terrestrial scenes by combining bi-directional reflectance distribution function (BRDF) products from Moderate Resolution Imaging Spectroradiometer (MODIS) data, high spatial resolution data, and hyperspectral data. The high spatial resolution data is used to separate materials and add textural variations to the scene, and the directional hemispherical reflectance from the hyperspectral data is used to adjust the magnitude of the MODIS BRDF. In this method, the shape of the BRDF is preserved since it changes very slowly, but its magnitude is varied based on the high resolution texture and hyperspectral data. In addition to the MODIS derived BRDF, target/class specific BRDF values or functions can also be applied to features of specific interest. The purpose of this paper is to discuss the techniques and the methodology used to model a forest region at a high resolution. The simulated scenes using this method for varying view angles show the expected variations in the reflectance due to the BRDF effects of the Harvard forest. The effectiveness of this technique to simulate real sensor data is evaluated by comparing the simulated data with the Landsat 8 Operational Land Image (OLI) data over the Harvard forest. Regions of interest were selected from the simulated and the real data for different targets and their Top-of-Atmospheric (TOA) radiance were compared. After adjusting for scaling correction due to the difference in atmospheric conditions between the simulated and the real data, the TOA radiance is found to agree within 5 % in the NIR band and 10 % in the visible bands for forest targets under similar illumination conditions. The technique presented in this paper can be extended for other biomes (e.g. desert regions and agricultural regions) by using the appropriate geographic regions. Since the entire scene is constructed in a simulated environment, parameters such as BRDF or its effects can be analyzed for general or target specific algorithm improvements. Also, the modeling and simulation techniques can be used as a baseline for the development and comparison of new sensor designs and to investigate the operational and environmental factors that affects the sensor constellations such as Sentinel and Landsat missions.

Zonal wavefront sensing with enhanced spatial resolution.

PubMed

Pathak, Biswajit; Boruah, Bosanta R

2016-12-01

In this Letter, we introduce a scheme to enhance the spatial resolution of a zonal wavefront sensor. The zonal wavefront sensor comprises an array of binary gratings implemented by a ferroelectric spatial light modulator (FLCSLM) followed by a lens, in lieu of the array of lenses in the Shack-Hartmann wavefront sensor. We show that the fast response of the FLCSLM device facilitates quick display of several laterally shifted binary grating patterns, and the programmability of the device enables simultaneous capturing of each focal spot array. This eventually leads to a wavefront estimation with an enhanced spatial resolution without much sacrifice on the sensor frame rate, thus making the scheme suitable for high spatial resolution measurement of transient wavefronts. We present experimental and numerical simulation results to demonstrate the importance of the proposed wavefront sensing scheme.

Cities, traffic, and CO2: A multidecadal assessment of trends, drivers, and scaling relationships

PubMed Central

Gately, Conor K.; Hutyra, Lucy R.; Sue Wing, Ian

2015-01-01

Emissions of CO2 from road vehicles were 1.57 billion metric tons in 2012, accounting for 28% of US fossil fuel CO2 emissions, but the spatial distributions of these emissions are highly uncertain. We develop a new emissions inventory, the Database of Road Transportation Emissions (DARTE), which estimates CO2 emitted by US road transport at a resolution of 1 km annually for 1980–2012. DARTE reveals that urban areas are responsible for 80% of on-road emissions growth since 1980 and for 63% of total 2012 emissions. We observe nonlinearities between CO2 emissions and population density at broad spatial/temporal scales, with total on-road CO2 increasing nonlinearly with population density, rapidly up to 1,650 persons per square kilometer and slowly thereafter. Per capita emissions decline as density rises, but at markedly varying rates depending on existing densities. We make use of DARTE’s bottom-up construction to highlight the biases associated with the common practice of using population as a linear proxy for disaggregating national- or state-scale emissions. Comparing DARTE with existing downscaled inventories, we find biases of 100% or more in the spatial distribution of urban and rural emissions, largely driven by mismatches between inventory downscaling proxies and the actual spatial patterns of vehicle activity at urban scales. Given cities’ dual importance as sources of CO2 and an emerging nexus of climate mitigation initiatives, high-resolution estimates such as DARTE are critical both for accurately quantifying surface carbon fluxes and for verifying the effectiveness of emissions mitigation efforts at urban scales. PMID:25847992

Extending a prototype knowledge- and object-based image analysis model to coarser spatial resolution imagery: an example from the Missouri River

USGS Publications Warehouse

Strong, Laurence L.

2012-01-01

A prototype knowledge- and object-based image analysis model was developed to inventory and map least tern and piping plover habitat on the Missouri River, USA. The model has been used to inventory the state of sandbars annually for 4 segments of the Missouri River since 2006 using QuickBird imagery. Interpretation of the state of sandbars is difficult when images for the segment are acquired at different river stages and different states of vegetation phenology and canopy cover. Concurrent QuickBird and RapidEye images were classified using the model and the spatial correspondence of classes in the land cover and sandbar maps were analysed for the spatial extent of the images and at nest locations for both bird species. Omission and commission errors were low for unvegetated land cover classes used for nesting by both bird species and for land cover types with continuous vegetation cover and water. Errors were larger for land cover classes characterized by a mixture of sand and vegetation. Sandbar classification decisions are made using information on land cover class proportions and disagreement between sandbar classes was resolved using fuzzy membership possibilities. Regression analysis of area for a paired sample of 47 sandbars indicated an average positive bias, 1.15 ha, for RapidEye that did not vary with sandbar size. RapidEye has potential to reduce temporal uncertainty about least tern and piping plover habitat but would not be suitable for mapping sandbar erosion, and characterization of sandbar shapes or vegetation patches at fine spatial resolution.

Extending a prototype knowledge and object based image analysis model to coarser spatial resolution imagery: an example from the Missouri River

USGS Publications Warehouse

Strong, Laurence L.

2012-01-01

A prototype knowledge- and object-based image analysis model was developed to inventory and map least tern and piping plover habitat on the Missouri River, USA. The model has been used to inventory the state of sandbars annually for 4 segments of the Missouri River since 2006 using QuickBird imagery. Interpretation of the state of sandbars is difficult when images for the segment are acquired at different river stages and different states of vegetation phenology and canopy cover. Concurrent QuickBird and RapidEye images were classified using the model and the spatial correspondence of classes in the land cover and sandbar maps were analysed for the spatial extent of the images and at nest locations for both bird species. Omission and commission errors were low for unvegetated land cover classes used for nesting by both bird species and for land cover types with continuous vegetation cover and water. Errors were larger for land cover classes characterized by a mixture of sand and vegetation. Sandbar classification decisions are made using information on land cover class proportions and disagreement between sandbar classes was resolved using fuzzy membership possibilities. Regression analysis of area for a paired sample of 47 sandbars indicated an average positive bias, 1.15 ha, for RapidEye that did not vary with sandbar size. RapidEye has potential to reduce temporal uncertainty about least tern and piping plover habitat but would not be suitable for mapping sandbar erosion, and characterization of sandbar shapes or vegetation patches at fine spatial resolution.

Hyperspectral and multispectral data fusion based on linear-quadratic nonnegative matrix factorization

NASA Astrophysics Data System (ADS)

Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz

2017-04-01

This paper proposes three multisharpening approaches to enhance the spatial resolution of urban hyperspectral remote sensing images. These approaches, related to linear-quadratic spectral unmixing techniques, use a linear-quadratic nonnegative matrix factorization (NMF) multiplicative algorithm. These methods begin by unmixing the observable high-spectral/low-spatial resolution hyperspectral and high-spatial/low-spectral resolution multispectral images. The obtained high-spectral/high-spatial resolution features are then recombined, according to the linear-quadratic mixing model, to obtain an unobservable multisharpened high-spectral/high-spatial resolution hyperspectral image. In the first designed approach, hyperspectral and multispectral variables are independently optimized, once they have been coherently initialized. These variables are alternately updated in the second designed approach. In the third approach, the considered hyperspectral and multispectral variables are jointly updated. Experiments, using synthetic and real data, are conducted to assess the efficiency, in spatial and spectral domains, of the designed approaches and of linear NMF-based approaches from the literature. Experimental results show that the designed methods globally yield very satisfactory spectral and spatial fidelities for the multisharpened hyperspectral data. They also prove that these methods significantly outperform the used literature approaches.