Assessing the quality of open spatial data for mobile location-based services research and applications

NASA Astrophysics Data System (ADS)

Ciepłuch, C.; Mooney, P.; Jacob, R.; Zheng, J.; Winstanely, A. C.

2011-12-01

New trends in GIS such as Volunteered Geographical Information (VGI), Citizen Science, and Urban Sensing, have changed the shape of the geoinformatics landscape. The OpenStreetMap (OSM) project provided us with an exciting, evolving, free and open solution as a base dataset for our geoserver and spatial data provider for our research. OSM is probably the best known and best supported example of VGI and user generated spatial content on the Internet. In this paper we will describe current results from the development of quality indicators for measures for OSM data. Initially we have analysed the Ireland OSM data in grid cells (5km) to gather statistical data about the completeness, accuracy, and fitness for purpose of the underlying spatial data. This analysis included: density of user contributions, spatial density of points and polygons, types of tags and metadata used, dominant contributors in a particular area or for a particular geographic feature type, etc. There greatest OSM activity and spatial data density is highly correlated with centres of large population. The ability to quantify and assess if VGI, such as OSM, is of sufficient quality for mobile mapping applications and Location-based services is critical to the future success of VGI as a spatial data source for these technologies.

Spatial Differentiation of Landscape Values in the Murray River Region of Victoria, Australia

NASA Astrophysics Data System (ADS)

Zhu, Xuan; Pfueller, Sharron; Whitelaw, Paul; Winter, Caroline

2010-05-01

This research advances the understanding of the location of perceived landscape values through a statistically based approach to spatial analysis of value densities. Survey data were obtained from a sample of people living in and using the Murray River region, Australia, where declining environmental quality prompted a reevaluation of its conservation status. When densities of 12 perceived landscape values were mapped using geographic information systems (GIS), valued places clustered along the entire river bank and in associated National/State Parks and reserves. While simple density mapping revealed high value densities in various locations, it did not indicate what density of a landscape value could be regarded as a statistically significant hotspot or distinguish whether overlapping areas of high density for different values indicate identical or adjacent locations. A spatial statistic Getis-Ord Gi* was used to indicate statistically significant spatial clusters of high value densities or “hotspots”. Of 251 hotspots, 40% were for single non-use values, primarily spiritual, therapeutic or intrinsic. Four hotspots had 11 landscape values. Two, lacking economic value, were located in ecologically important river red gum forests and two, lacking wilderness value, were near the major towns of Echuca-Moama and Albury-Wodonga. Hotspots for eight values showed statistically significant associations with another value. There were high associations between learning and heritage values while economic and biological diversity values showed moderate associations with several other direct and indirect use values. This approach may improve confidence in the interpretation of spatial analysis of landscape values by enhancing understanding of value relationships.

Characterizing Fishing Effort and Spatial Extent of Coastal Fisheries

PubMed Central

Stewart, Kelly R.; Lewison, Rebecca L.; Dunn, Daniel C.; Bjorkland, Rhema H.; Kelez, Shaleyla; Halpin, Patrick N.; Crowder, Larry B.

2010-01-01

Biodiverse coastal zones are often areas of intense fishing pressure due to the high relative density of fishing capacity in these nearshore regions. Although overcapacity is one of the central challenges to fisheries sustainability in coastal zones, accurate estimates of fishing pressure in coastal zones are limited, hampering the assessment of the direct and collateral impacts (e.g., habitat degradation, bycatch) of fishing. We compiled a comprehensive database of fishing effort metrics and the corresponding spatial limits of fisheries and used a spatial analysis program (FEET) to map fishing effort density (measured as boat-meters per km2) in the coastal zones of six ocean regions. We also considered the utility of a number of socioeconomic variables as indicators of fishing pressure at the national level; fishing density increased as a function of population size and decreased as a function of coastline length. Our mapping exercise points to intra and interregional ‘hotspots’ of coastal fishing pressure. The significant and intuitive relationships we found between fishing density and population size and coastline length may help with coarse regional characterizations of fishing pressure. However, spatially-delimited fishing effort data are needed to accurately map fishing hotspots, i.e., areas of intense fishing activity. We suggest that estimates of fishing effort, not just target catch or yield, serve as a necessary measure of fishing activity, which is a key link to evaluating sustainability and environmental impacts of coastal fisheries. PMID:21206903

Fractional Order Spatiotemporal Chaos with Delay in Spatial Nonlinear Coupling

NASA Astrophysics Data System (ADS)

Zhang, Yingqian; Wang, Xingyuan; Liu, Liyan; Liu, Jia

We investigate the spatiotemporal dynamics with fractional order differential logistic map with delay under nonlinear chaotic maps for spatial coupling connections. Here, the coupling methods between lattices are the nonlinear chaotic map coupling of lattices. The fractional order differential logistic map with delay breaks the limits of the range of parameter μ ∈ [3.75, 4] in the classical logistic map for chaotic states. The Kolmogorov-Sinai entropy density and universality, and bifurcation diagrams are employed to investigate the chaotic behaviors of the proposed model in this paper. The proposed model can also be applied for cryptography, which is verified in a color image encryption scheme in this paper.

Development of an Asset Value Map for Disaster Risk Assessment in China by Spatial Disaggregation Using Ancillary Remote Sensing Data.

PubMed

Wu, Jidong; Li, Ying; Li, Ning; Shi, Peijun

2018-01-01

The extent of economic losses due to a natural hazard and disaster depends largely on the spatial distribution of asset values in relation to the hazard intensity distribution within the affected area. Given that statistical data on asset value are collected by administrative units in China, generating spatially explicit asset exposure maps remains a key challenge for rapid postdisaster economic loss assessment. The goal of this study is to introduce a top-down (or downscaling) approach to disaggregate administrative-unit level asset value to grid-cell level. To do so, finding the highly correlated "surrogate" indicators is the key. A combination of three data sets-nighttime light grid, LandScan population grid, and road density grid, is used as ancillary asset density distribution information for spatializing the asset value. As a result, a high spatial resolution asset value map of China for 2015 is generated. The spatial data set contains aggregated economic value at risk at 30 arc-second spatial resolution. Accuracy of the spatial disaggregation reflects redistribution errors introduced by the disaggregation process as well as errors from the original ancillary data sets. The overall accuracy of the results proves to be promising. The example of using the developed disaggregated asset value map in exposure assessment of watersheds demonstrates that the data set offers immense analytical flexibility for overlay analysis according to the hazard extent. This product will help current efforts to analyze spatial characteristics of exposure and to uncover the contributions of both physical and social drivers of natural hazard and disaster across space and time. © 2017 Society for Risk Analysis.

Predicting Anthropogenic Noise Contributions to US Waters.

PubMed

Gedamke, Jason; Ferguson, Megan; Harrison, Jolie; Hatch, Leila; Henderson, Laurel; Porter, Michael B; Southall, Brandon L; Van Parijs, Sofie

2016-01-01

To increase understanding of the potential effects of chronic underwater noise in US waters, the National Oceanic and Atmospheric Administration (NOAA) organized two working groups in 2011, collectively called "CetSound," to develop tools to map the density and distribution of cetaceans (CetMap) and predict the contribution of human activities to underwater noise (SoundMap). The SoundMap effort utilized data on density, distribution, acoustic signatures of dominant noise sources, and environmental descriptors to map estimated temporal, spatial, and spectral contributions to background noise. These predicted soundscapes are an initial step toward assessing chronic anthropogenic noise impacts on the ocean's varied acoustic habitats and the animals utilizing them.

Multiple Scales of Control on the Structure and Spatial Distribution of Woody Vegetation in African Savanna Watersheds

PubMed Central

Vaughn, Nicholas R.; Asner, Gregory P.; Smit, Izak P. J.; Riddel, Edward S.

2015-01-01

Factors controlling savanna woody vegetation structure vary at multiple spatial and temporal scales, and as a consequence, unraveling their combined effects has proven to be a classic challenge in savanna ecology. We used airborne LiDAR (light detection and ranging) to map three-dimensional woody vegetation structure throughout four savanna watersheds, each contrasting in geologic substrate and climate, in Kruger National Park, South Africa. By comparison of the four watersheds, we found that geologic substrate had a stronger effect than climate in determining watershed-scale differences in vegetation structural properties, including cover, height and crown density. Generalized Linear Models were used to assess the spatial distribution of woody vegetation structural properties, including cover, height and crown density, in relation to mapped hydrologic, topographic and fire history traits. For each substrate and climate combination, models incorporating topography, hydrology and fire history explained up to 30% of the remaining variation in woody canopy structure, but inclusion of a spatial autocovariate term further improved model performance. Both crown density and the cover of shorter woody canopies were determined more by unknown factors likely to be changing on smaller spatial scales, such as soil texture, herbivore abundance or fire behavior, than by our mapped regional-scale changes in topography and hydrology. We also detected patterns in spatial covariance at distances up to 50–450 m, depending on watershed and structural metric. Our results suggest that large-scale environmental factors play a smaller role than is often attributed to them in determining woody vegetation structure in southern African savannas. This highlights the need for more spatially-explicit, wide-area analyses using high resolution remote sensing techniques. PMID:26660502

Multiple Scales of Control on the Structure and Spatial Distribution of Woody Vegetation in African Savanna Watersheds.

PubMed

Vaughn, Nicholas R; Asner, Gregory P; Smit, Izak P J; Riddel, Edward S

2015-01-01

Factors controlling savanna woody vegetation structure vary at multiple spatial and temporal scales, and as a consequence, unraveling their combined effects has proven to be a classic challenge in savanna ecology. We used airborne LiDAR (light detection and ranging) to map three-dimensional woody vegetation structure throughout four savanna watersheds, each contrasting in geologic substrate and climate, in Kruger National Park, South Africa. By comparison of the four watersheds, we found that geologic substrate had a stronger effect than climate in determining watershed-scale differences in vegetation structural properties, including cover, height and crown density. Generalized Linear Models were used to assess the spatial distribution of woody vegetation structural properties, including cover, height and crown density, in relation to mapped hydrologic, topographic and fire history traits. For each substrate and climate combination, models incorporating topography, hydrology and fire history explained up to 30% of the remaining variation in woody canopy structure, but inclusion of a spatial autocovariate term further improved model performance. Both crown density and the cover of shorter woody canopies were determined more by unknown factors likely to be changing on smaller spatial scales, such as soil texture, herbivore abundance or fire behavior, than by our mapped regional-scale changes in topography and hydrology. We also detected patterns in spatial covariance at distances up to 50-450 m, depending on watershed and structural metric. Our results suggest that large-scale environmental factors play a smaller role than is often attributed to them in determining woody vegetation structure in southern African savannas. This highlights the need for more spatially-explicit, wide-area analyses using high resolution remote sensing techniques.

Particle visualization in high-power impulse magnetron sputtering. I. 2D density mapping

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

Britun, Nikolay, E-mail: nikolay.britun@umons.ac.be; Palmucci, Maria; Konstantinidis, Stephanos

2015-04-28

Time-resolved characterization of an Ar-Ti high-power impulse magnetron sputtering discharge has been performed. This paper deals with two-dimensional density mapping in the discharge volume obtained by laser-induced fluorescence imaging. The time-resolved density evolution of Ti neutrals, singly ionized Ti atoms (Ti{sup +}), and Ar metastable atoms (Ar{sup met}) in the area above the sputtered cathode is mapped for the first time in this type of discharges. The energetic characteristics of the discharge species are additionally studied by Doppler-shift laser-induced fluorescence imaging. The questions related to the propagation of both the neutral and ionized discharge particles, as well as to theirmore » spatial density distributions, are discussed.« less

Integrating population dynamics into mapping human exposure to seismic hazard

NASA Astrophysics Data System (ADS)

Freire, S.; Aubrecht, C.

2012-11-01

Disaster risk is not fully characterized without taking into account vulnerability and population exposure. Assessment of earthquake risk in urban areas would benefit from considering the variation of population distribution at more detailed spatial and temporal scales, and from a more explicit integration of this improved demographic data with existing seismic hazard maps. In the present work, "intelligent" dasymetric mapping is used to model population dynamics at high spatial resolution in order to benefit the analysis of spatio-temporal exposure to earthquake hazard in a metropolitan area. These night- and daytime-specific population densities are then classified and combined with seismic intensity levels to derive new spatially-explicit four-class-composite maps of human exposure. The presented approach enables a more thorough assessment of population exposure to earthquake hazard. Results show that there are significantly more people potentially at risk in the daytime period, demonstrating the shifting nature of population exposure in the daily cycle and the need to move beyond conventional residence-based demographic data sources to improve risk analyses. The proposed fine-scale maps of human exposure to seismic intensity are mainly aimed at benefiting visualization and communication of earthquake risk, but can be valuable in all phases of the disaster management process where knowledge of population densities is relevant for decision-making.

Spatial relationship between bone formation and mechanical stimulus within cortical bone: Combining 3D fluorochrome mapping and poroelastic finite element modelling.

PubMed

Carrieroa, A; Pereirab, A F; Wilson, A J; Castagno, S; Javaheri, B; Pitsillides, A A; Marenzana, M; Shefelbine, S J

2018-06-01

Bone is a dynamic tissue and adapts its architecture in response to biological and mechanical factors. Here we investigate how cortical bone formation is spatially controlled by the local mechanical environment in the murine tibia axial loading model (C57BL/6). We obtained 3D locations of new bone formation by performing 'slice and view' 3D fluorochrome mapping of the entire bone and compared these sites with the regions of high fluid velocity or strain energy density estimated using a finite element model, validated with ex-vivo bone surface strain map acquired ex-vivo using digital image correlation. For the comparison, 2D maps of the average bone formation and peak mechanical stimulus on the tibial endosteal and periosteal surface across the entire cortical surface were created. Results showed that bone formed on the periosteal and endosteal surface in regions of high fluid flow. Peak strain energy density predicted only the formation of bone periosteally. Understanding how the mechanical stimuli spatially relates with regions of cortical bone formation in response to loading will eventually guide loading regime therapies to maintain or restore bone mass in specific sites in skeletal pathologies.

Biometric recognition via fixation density maps

NASA Astrophysics Data System (ADS)

Rigas, Ioannis; Komogortsev, Oleg V.

2014-05-01

This work introduces and evaluates a novel eye movement-driven biometric approach that employs eye fixation density maps for person identification. The proposed feature offers a dynamic representation of the biometric identity, storing rich information regarding the behavioral and physical eye movement characteristics of the individuals. The innate ability of fixation density maps to capture the spatial layout of the eye movements in conjunction with their probabilistic nature makes them a particularly suitable option as an eye movement biometrical trait in cases when free-viewing stimuli is presented. In order to demonstrate the effectiveness of the proposed approach, the method is evaluated on three different datasets containing a wide gamut of stimuli types, such as static images, video and text segments. The obtained results indicate a minimum EER (Equal Error Rate) of 18.3 %, revealing the perspectives on the utilization of fixation density maps as an enhancing biometrical cue during identification scenarios in dynamic visual environments.

Maternal choline supplementation improves spatial mapping and increases basal forebrain cholinergic neuron number and size in aged Ts65Dn mice

PubMed Central

Ash, Jessica A.; Velazquez, Ramon; Kelley, Christy M.; Powers, Brian E.; Ginsberg, Stephen D.; Mufson, Elliott J.; Strupp, Barbara J.

2014-01-01

Down syndrome (DS) is marked by intellectual disability (ID) and early-onset of Alzheimer’s disease (AD) neuropathology, including basal forebrain cholinergic neuron (BFCN) degeneration. The present study tested the hypothesis that maternal choline supplementation (MCS) lessens hippocampal dysfunction and protects against BFCN degeneration in the Ts65Dn mouse model of DS and AD. During pregnancy and lactation, dams were assigned to either a choline sufficient (1.1 g/kg choline chloride) or choline supplemented (5.0 g/kg choline chloride) diet. Between 13 and 17 months of age, offspring were tested in the radial arm water maze (RAWM) to examine spatial learning and memory followed by unbiased quantitative morphometry of BFCNs. Spatial mapping was significantly impaired in unsupplemented Ts65Dn mice relative to normal disomic (2N) littermates. Additionally, a significantly lower number and density of medial septum (MS) hippocampal projection BFCNs was also found in unsupplemented Ts65Dn mice. Notably, MCS significantly improved spatial mapping and increased number, density, and size of MS BFCNs in Ts65Dn offspring. Moreover, the density and number of MS BFCNs correlated significantly with spatial memory proficiency, providing powerful support for a functional relationship between these behavioral and morphometric effects of MCS for the trisomic offspring. Thus, increasing maternal choline intake during pregnancy may represent a safe and effective treatment approach for expectant mothers carrying a DS fetus, as well as a possible means of BFCN neuroprotection during aging for the population at large. PMID:24932939

In vivo correlation mapping microscopy

NASA Astrophysics Data System (ADS)

McGrath, James; Alexandrov, Sergey; Owens, Peter; Subhash, Hrebesh; Leahy, Martin

2016-04-01

To facilitate regular assessment of the microcirculation in vivo, noninvasive imaging techniques such as nailfold capillaroscopy are required in clinics. Recently, a correlation mapping technique has been applied to optical coherence tomography (OCT), which extends the capabilities of OCT to microcirculation morphology imaging. This technique, known as correlation mapping optical coherence tomography, has been shown to extract parameters, such as capillary density and vessel diameter, and key clinical markers associated with early changes in microvascular diseases. However, OCT has limited spatial resolution in both the transverse and depth directions. Here, we extend this correlation mapping technique to other microscopy modalities, including confocal microscopy, and take advantage of the higher spatial resolution offered by these modalities. The technique is achieved as a processing step on microscopy images and does not require any modification to the microscope hardware. Results are presented which show that this correlation mapping microscopy technique can extend the capabilities of conventional microscopy to enable mapping of vascular networks in vivo with high spatial resolution in both the transverse and depth directions.

Spatial fuel data products of the LANDFIRE Project

USGS Publications Warehouse

Reeves, M.C.; Ryan, K.C.; Rollins, M.G.; Thompson, T.G.

2009-01-01

The Landscape Fire and Resource Management Planning Tools (LANDFIRE) Project is mapping wildland fuels, vegetation, and fire regime characteristics across the United States. The LANDFIRE project is unique because of its national scope, creating an integrated product suite at 30-m spatial resolution and complete spatial coverage of all lands within the 50 states. Here we describe development of the LANDFIRE wildland fuels data layers for the conterminous 48 states: surface fire behavior fuel models, canopy bulk density, canopy base height, canopy cover, and canopy height. Surface fire behavior fuel models are mapped by developing crosswalks to vegetation structure and composition created by LANDFIRE. Canopy fuels are mapped using regression trees relating field-referenced estimates of canopy base height and canopy bulk density to satellite imagery, biophysical gradients and vegetation structure and composition data. Here we focus on the methods and data used to create the fuel data products, discuss problems encountered with the data, provide an accuracy assessment, demonstrate recent use of the data during the 2007 fire season, and discuss ideas for updating, maintaining and improving LANDFIRE fuel data products.

Mapping Tree Density at the Global Scale

NASA Astrophysics Data System (ADS)

Covey, K. R.; Crowther, T. W.; Glick, H.; Bettigole, C.; Bradford, M.

2015-12-01

The global extent and distribution of forest trees is central to our understanding of the terrestrial biosphere. We provide the first spatially continuous map of forest tree density at a global-scale. This map reveals that the global number of trees is approximately 3.04 trillion, an order of magnitude higher than the previous estimate. Of these trees, approximately 1.39 trillion exist in tropical and subtropical regions, with 0.74, and 0.61 trillion in boreal and temperate regions, respectively. Biome-level trends in tree density demonstrate the importance of climate and topography in controlling local tree densities at finer scales, as well as the overwhelming impact of humans across most of the world. Based on our projected tree densities, we estimate that deforestation is currently responsible for removing over 15 billion trees each year, and the global number of trees has fallen by approximately 46% since the start of human civilization.

Mapping tree density at a global scale

NASA Astrophysics Data System (ADS)

Crowther, T. W.; Glick, H. B.; Covey, K. R.; Bettigole, C.; Maynard, D. S.; Thomas, S. M.; Smith, J. R.; Hintler, G.; Duguid, M. C.; Amatulli, G.; Tuanmu, M.-N.; Jetz, W.; Salas, C.; Stam, C.; Piotto, D.; Tavani, R.; Green, S.; Bruce, G.; Williams, S. J.; Wiser, S. K.; Huber, M. O.; Hengeveld, G. M.; Nabuurs, G.-J.; Tikhonova, E.; Borchardt, P.; Li, C.-F.; Powrie, L. W.; Fischer, M.; Hemp, A.; Homeier, J.; Cho, P.; Vibrans, A. C.; Umunay, P. M.; Piao, S. L.; Rowe, C. W.; Ashton, M. S.; Crane, P. R.; Bradford, M. A.

2015-09-01

The global extent and distribution of forest trees is central to our understanding of the terrestrial biosphere. We provide the first spatially continuous map of forest tree density at a global scale. This map reveals that the global number of trees is approximately 3.04 trillion, an order of magnitude higher than the previous estimate. Of these trees, approximately 1.39 trillion exist in tropical and subtropical forests, with 0.74 trillion in boreal regions and 0.61 trillion in temperate regions. Biome-level trends in tree density demonstrate the importance of climate and topography in controlling local tree densities at finer scales, as well as the overwhelming effect of humans across most of the world. Based on our projected tree densities, we estimate that over 15 billion trees are cut down each year, and the global number of trees has fallen by approximately 46% since the start of human civilization.

Mapping tree density at a global scale.

PubMed

Crowther, T W; Glick, H B; Covey, K R; Bettigole, C; Maynard, D S; Thomas, S M; Smith, J R; Hintler, G; Duguid, M C; Amatulli, G; Tuanmu, M-N; Jetz, W; Salas, C; Stam, C; Piotto, D; Tavani, R; Green, S; Bruce, G; Williams, S J; Wiser, S K; Huber, M O; Hengeveld, G M; Nabuurs, G-J; Tikhonova, E; Borchardt, P; Li, C-F; Powrie, L W; Fischer, M; Hemp, A; Homeier, J; Cho, P; Vibrans, A C; Umunay, P M; Piao, S L; Rowe, C W; Ashton, M S; Crane, P R; Bradford, M A

2015-09-10

The global extent and distribution of forest trees is central to our understanding of the terrestrial biosphere. We provide the first spatially continuous map of forest tree density at a global scale. This map reveals that the global number of trees is approximately 3.04 trillion, an order of magnitude higher than the previous estimate. Of these trees, approximately 1.39 trillion exist in tropical and subtropical forests, with 0.74 trillion in boreal regions and 0.61 trillion in temperate regions. Biome-level trends in tree density demonstrate the importance of climate and topography in controlling local tree densities at finer scales, as well as the overwhelming effect of humans across most of the world. Based on our projected tree densities, we estimate that over 15 billion trees are cut down each year, and the global number of trees has fallen by approximately 46% since the start of human civilization.

Dynamical Mapping of Anopheles darlingi Densities in a Residual Malaria Transmission Area of French Guiana by Using Remote Sensing and Meteorological Data

PubMed Central

Adde, Antoine; Roux, Emmanuel; Mangeas, Morgan; Dessay, Nadine; Nacher, Mathieu; Dusfour, Isabelle; Girod, Romain; Briolant, Sébastien

2016-01-01

Local variation in the density of Anopheles mosquitoes and the risk of exposure to bites are essential to explain the spatial and temporal heterogeneities in the transmission of malaria. Vector distribution is driven by environmental factors. Based on variables derived from satellite imagery and meteorological observations, this study aimed to dynamically model and map the densities of Anopheles darlingi in the municipality of Saint-Georges de l’Oyapock (French Guiana). Longitudinal sampling sessions of An. darlingi densities were conducted between September 2012 and October 2014. Landscape and meteorological data were collected and processed to extract a panel of variables that were potentially related to An. darlingi ecology. Based on these data, a robust methodology was formed to estimate a statistical predictive model of the spatial-temporal variations in the densities of An. darlingi in Saint-Georges de l’Oyapock. The final cross-validated model integrated two landscape variables—dense forest surface and built surface—together with four meteorological variables related to rainfall, evapotranspiration, and the minimal and maximal temperatures. Extrapolation of the model allowed the generation of predictive weekly maps of An. darlingi densities at a resolution of 10-m. Our results supported the use of satellite imagery and meteorological data to predict malaria vector densities. Such fine-scale modeling approach might be a useful tool for health authorities to plan control strategies and social communication in a cost-effective, targeted, and timely manner. PMID:27749938

Dynamical Mapping of Anopheles darlingi Densities in a Residual Malaria Transmission Area of French Guiana by Using Remote Sensing and Meteorological Data.

PubMed

Adde, Antoine; Roux, Emmanuel; Mangeas, Morgan; Dessay, Nadine; Nacher, Mathieu; Dusfour, Isabelle; Girod, Romain; Briolant, Sébastien

2016-01-01

Local variation in the density of Anopheles mosquitoes and the risk of exposure to bites are essential to explain the spatial and temporal heterogeneities in the transmission of malaria. Vector distribution is driven by environmental factors. Based on variables derived from satellite imagery and meteorological observations, this study aimed to dynamically model and map the densities of Anopheles darlingi in the municipality of Saint-Georges de l'Oyapock (French Guiana). Longitudinal sampling sessions of An. darlingi densities were conducted between September 2012 and October 2014. Landscape and meteorological data were collected and processed to extract a panel of variables that were potentially related to An. darlingi ecology. Based on these data, a robust methodology was formed to estimate a statistical predictive model of the spatial-temporal variations in the densities of An. darlingi in Saint-Georges de l'Oyapock. The final cross-validated model integrated two landscape variables-dense forest surface and built surface-together with four meteorological variables related to rainfall, evapotranspiration, and the minimal and maximal temperatures. Extrapolation of the model allowed the generation of predictive weekly maps of An. darlingi densities at a resolution of 10-m. Our results supported the use of satellite imagery and meteorological data to predict malaria vector densities. Such fine-scale modeling approach might be a useful tool for health authorities to plan control strategies and social communication in a cost-effective, targeted, and timely manner.

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.

Preliminary isostatic gravity map of the Sonoma volcanic field and vicinity, Sonoma and Napa Counties, California

USGS Publications Warehouse

Langenheim, V.E.; Roberts, C.W.; McCabe, C.A.; McPhee, D.K.; Tilden, J.E.; Jachens, R.C.

2006-01-01

This isostatic residual gravity map is part of a three-dimensional mapping effort focused on the subsurface distribution of rocks of the Sonoma volcanic field in Napa and Sonoma counties, northern California. This map will serve as a basis for modeling the shapes of basins beneath the Santa Rosa Plain and Napa and Sonoma Valleys, and for determining the location and geometry of faults within the area. Local spatial variations in the Earth's gravity field (after accounting for variations caused by elevation, terrain, and deep crustal structure explained below) reflect the distribution of densities in the mid to upper crust. Densities often can be related to rock type, and abrupt spatial changes in density commonly mark lithologic boundaries. High-density basement rocks exposed within the northern San Francisco Bay area include those of the Mesozoic Franciscan Complex and Great Valley Sequence present in the mountainous areas of the quadrangle. Alluvial sediment and Tertiary sedimentary rocks are characterized by low densities. However, with increasing depth of burial and age, the densities of these rocks may become indistinguishable from those of basement rocks. Tertiary volcanic rocks are characterized by a wide range in densities, but, on average, are less dense than the Mesozoic basement rocks. Isostatic residual gravity values within the map area range from about -41 mGal over San Pablo Bay to about 11 mGal near Greeg Mountain 10 km east of St. Helena. Steep linear gravity gradients are coincident with the traces of several Quaternary strike-slip faults, most notably along the West Napa fault bounding the west side of Napa Valley, the projection of the Hayward fault in San Pablo Bay, the Maacama Fault, and the Rodgers Creek fault in the vicinity of Santa Rosa. These gradients result from juxtaposing dense basement rocks against thick Tertiary volcanic and sedimentary rocks.

Assessing future vent opening locations at the Somma-Vesuvio volcanic complex: 2. Probability maps of the caldera for a future Plinian/sub-Plinian event with uncertainty quantification

NASA Astrophysics Data System (ADS)

Tadini, A.; Bevilacqua, A.; Neri, A.; Cioni, R.; Aspinall, W. P.; Bisson, M.; Isaia, R.; Mazzarini, F.; Valentine, G. A.; Vitale, S.; Baxter, P. J.; Bertagnini, A.; Cerminara, M.; de Michieli Vitturi, M.; Di Roberto, A.; Engwell, S.; Esposti Ongaro, T.; Flandoli, F.; Pistolesi, M.

2017-06-01

In this study, we combine reconstructions of volcanological data sets and inputs from a structured expert judgment to produce a first long-term probability map for vent opening location for the next Plinian or sub-Plinian eruption of Somma-Vesuvio. In the past, the volcano has exhibited significant spatial variability in vent location; this can exert a significant control on where hazards materialize (particularly of pyroclastic density currents). The new vent opening probability mapping has been performed through (i) development of spatial probability density maps with Gaussian kernel functions for different data sets and (ii) weighted linear combination of these spatial density maps. The epistemic uncertainties affecting these data sets were quantified explicitly with expert judgments and implemented following a doubly stochastic approach. Various elicitation pooling metrics and subgroupings of experts and target questions were tested to evaluate the robustness of outcomes. Our findings indicate that (a) Somma-Vesuvio vent opening probabilities are distributed inside the whole caldera, with a peak corresponding to the area of the present crater, but with more than 50% probability that the next vent could open elsewhere within the caldera; (b) there is a mean probability of about 30% that the next vent will open west of the present edifice; (c) there is a mean probability of about 9.5% that the next medium-large eruption will enlarge the present Somma-Vesuvio caldera, and (d) there is a nonnegligible probability (mean value of 6-10%) that the next Plinian or sub-Plinian eruption will have its initial vent opening outside the present Somma-Vesuvio caldera.

Uncertainties in mapping forest carbon in urban ecosystems.

PubMed

Chen, Gang; Ozelkan, Emre; Singh, Kunwar K; Zhou, Jun; Brown, Marilyn R; Meentemeyer, Ross K

2017-02-01

Spatially explicit urban forest carbon estimation provides a baseline map for understanding the variation in forest vertical structure, informing sustainable forest management and urban planning. While high-resolution remote sensing has proven promising for carbon mapping in highly fragmented urban landscapes, data cost and availability are the major obstacle prohibiting accurate, consistent, and repeated measurement of forest carbon pools in cities. This study aims to evaluate the uncertainties of forest carbon estimation in response to the combined impacts of remote sensing data resolution and neighborhood spatial patterns in Charlotte, North Carolina. The remote sensing data for carbon mapping were resampled to a range of resolutions, i.e., LiDAR point cloud density - 5.8, 4.6, 2.3, and 1.2 pt s/m 2 , aerial optical NAIP (National Agricultural Imagery Program) imagery - 1, 5, 10, and 20 m. Urban spatial patterns were extracted to represent area, shape complexity, dispersion/interspersion, diversity, and connectivity of landscape patches across the residential neighborhoods with built-up densities from low, medium-low, medium-high, to high. Through statistical analyses, we found that changing remote sensing data resolution introduced noticeable uncertainties (variation) in forest carbon estimation at the neighborhood level. Higher uncertainties were caused by the change of LiDAR point density (causing 8.7-11.0% of variation) than changing NAIP image resolution (causing 6.2-8.6% of variation). For both LiDAR and NAIP, urban neighborhoods with a higher degree of anthropogenic disturbance unveiled a higher level of uncertainty in carbon mapping. However, LiDAR-based results were more likely to be affected by landscape patch connectivity, and the NAIP-based estimation was found to be significantly influenced by the complexity of patch shape. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spatially varying density dependence drives a shifting mosaic of survival in a recovering apex predator (Canis lupus).

PubMed

O'Neil, Shawn T; Bump, Joseph K; Beyer, Dean E

2017-11-01

Understanding landscape patterns in mortality risk is crucial for promoting recovery of threatened and endangered species. Humans affect mortality risk in large carnivores such as wolves ( Canis lupus ), but spatiotemporally varying density dependence can significantly influence the landscape of survival. This potentially occurs when density varies spatially and risk is unevenly distributed. We quantified spatiotemporal sources of variation in survival rates of gray wolves ( C. lupus ) during a 21-year period of population recovery in the Upper Peninsula of Michigan, USA. We focused on mapping risk across time using Cox Proportional Hazards (CPH) models with time-dependent covariates, thus exploring a shifting mosaic of survival. Extended CPH models and time-dependent covariates revealed influences of seasonality, density dependence and experience, as well as individual-level factors and landscape predictors of risk. We used results to predict the shifting landscape of risk at the beginning, middle, and end of the wolf recovery time series. Survival rates varied spatially and declined over time. Long-term change was density-dependent, with landscape predictors such as agricultural land cover and edge densities contributing negatively to survival. Survival also varied seasonally and depended on individual experience, sex, and resident versus transient status. The shifting landscape of survival suggested that increasing density contributed to greater potential for human conflict and wolf mortality risk. Long-term spatial variation in key population vital rates is largely unquantified in many threatened, endangered, and recovering species. Variation in risk may indicate potential for source-sink population dynamics, especially where individuals preemptively occupy suitable territories, which forces new individuals into riskier habitat types as density increases. We encourage managers to explore relationships between adult survival and localized changes in population density. Density-dependent risk maps can identify increasing conflict areas or potential habitat sinks which may persist due to high recruitment in adjacent habitats.

Arc_Mat: a Matlab-based spatial data analysis toolbox

NASA Astrophysics Data System (ADS)

Liu, Xingjian; Lesage, James

2010-03-01

This article presents an overview of Arc_Mat, a Matlab-based spatial data analysis software package whose source code has been placed in the public domain. An earlier version of the Arc_Mat toolbox was developed to extract map polygon and database information from ESRI shapefiles and provide high quality mapping in the Matlab software environment. We discuss revisions to the toolbox that: utilize enhanced computing and graphing capabilities of more recent versions of Matlab, restructure the toolbox with object-oriented programming features, and provide more comprehensive functions for spatial data analysis. The Arc_Mat toolbox functionality includes basic choropleth mapping; exploratory spatial data analysis that provides exploratory views of spatial data through various graphs, for example, histogram, Moran scatterplot, three-dimensional scatterplot, density distribution plot, and parallel coordinate plots; and more formal spatial data modeling that draws on the extensive Spatial Econometrics Toolbox functions. A brief review of the design aspects of the revised Arc_Mat is described, and we provide some illustrative examples that highlight representative uses of the toolbox. Finally, we discuss programming with and customizing the Arc_Mat toolbox functionalities.

Using Moran's I and GIS to study the spatial pattern of forest litter carbon density in a subtropical region of southeastern China

NASA Astrophysics Data System (ADS)

Fu, W. J.; Jiang, P. K.; Zhou, G. M.; Zhao, K. L.

2014-04-01

Spatial pattern information of carbon density in forest ecosystem including forest litter carbon (FLC) plays an important role in evaluating carbon sequestration potentials. The spatial variation of FLC density in the typical subtropical forests in southeastern China was investigated using Moran's I, geostatistics and a geographical information system (GIS). A total of 839 forest litter samples were collected based on a 12 km (south-north) × 6 km (east-west) grid system in Zhejiang province. Forest litter carbon density values were very variable, ranging from 10.2 kg ha-1 to 8841.3 kg ha-1, with an average of 1786.7 kg ha-1. The aboveground biomass had the strongest positive correlation with FLC density, followed by forest age and elevation. Global Moran's I revealed that FLC density had significant positive spatial autocorrelation. Clear spatial patterns were observed using local Moran's I. A spherical model was chosen to fit the experimental semivariogram. The moderate "nugget-to-sill" (0.536) value revealed that both natural and anthropogenic factors played a key role in spatial heterogeneity of FLC density. High FLC density values were mainly distributed in northwestern and western part of Zhejiang province, which were related to adopting long-term policy of forest conservation in these areas, while Hang-Jia-Hu (HJH) Plain, Jin-Qu (JQ) Basin and coastal areas had low FLC density due to low forest coverage and intensive management of economic forests. These spatial patterns were in line with the spatial-cluster map described by local Moran's I. Therefore, Moran's I, combined with geostatistics and GIS, could be used to study spatial patterns of environmental variables related to forest ecosystem.

Improving the Accuracy of Mapping Urban Vegetation Carbon Density by Combining Shadow Remove, Spectral Unmixing Analysis and Spatial Modeling

NASA Astrophysics Data System (ADS)

Qie, G.; Wang, G.; Wang, M.

2016-12-01

Mixed pixels and shadows due to buildings in urban areas impede accurate estimation and mapping of city vegetation carbon density. In most of previous studies, these factors are often ignored, which thus result in underestimation of city vegetation carbon density. In this study we presented an integrated methodology to improve the accuracy of mapping city vegetation carbon density. Firstly, we applied a linear shadow remove analysis (LSRA) on remotely sensed Landsat 8 images to reduce the shadow effects on carbon estimation. Secondly, we integrated a linear spectral unmixing analysis (LSUA) with a linear stepwise regression (LSR), a logistic model-based stepwise regression (LMSR) and k-Nearest Neighbors (kNN), and utilized and compared the integrated models on shadow-removed images to map vegetation carbon density. This methodology was examined in Shenzhen City of Southeast China. A data set from a total of 175 sample plots measured in 2013 and 2014 was used to train the models. The independent variables statistically significantly contributing to improving the fit of the models to the data and reducing the sum of squared errors were selected from a total of 608 variables derived from different image band combinations and transformations. The vegetation fraction from LSUA was then added into the models as an important independent variable. The estimates obtained were evaluated using a cross-validation method. Our results showed that higher accuracies were obtained from the integrated models compared with the ones using traditional methods which ignore the effects of mixed pixels and shadows. This study indicates that the integrated method has great potential on improving the accuracy of urban vegetation carbon density estimation. Key words: Urban vegetation carbon, shadow, spectral unmixing, spatial modeling, Landsat 8 images

Phase transitions in coupled map lattices and in associated probabilistic cellular automata.

PubMed

Just, Wolfram

2006-10-01

Analytical tools are applied to investigate piecewise linear coupled map lattices in terms of probabilistic cellular automata. The so-called disorder condition of probabilistic cellular automata is closely related with attracting sets in coupled map lattices. The importance of this condition for the suppression of phase transitions is illustrated by spatially one-dimensional systems. Invariant densities and temporal correlations are calculated explicitly. Ising type phase transitions are found for one-dimensional coupled map lattices acting on repelling sets and for a spatially two-dimensional Miller-Huse-like system with stable long time dynamics. Critical exponents are calculated within a finite size scaling approach. The relevance of detailed balance of the resulting probabilistic cellular automaton for the critical behavior is pointed out.

Prioritizing landscapes for longleaf pine conservation

USGS Publications Warehouse

Grand, James B.; Kleiner, Kevin J.

2016-01-01

We developed a spatially explicit model and map, as a decision support tool (DST), to aid conservation agencies creating or maintaining open pine ecosystems. The tool identified areas that are likely to provide the greatest benefit to focal bird populations based on a comprehensive landscape analysis. We used NLCD 2011, SSURGO, and SEGAP data to map the density of desired resources for open pine ecosystems and six focal species of birds and 2 reptiles within the historic range of longleaf pine east of the Mississippi River. Binary rasters were created of sites with desired characteristics such as land form, hydrology, land use and land cover, soils, potential habitat for focal species, and putative source populations of focal species. Each raster was smoothed using a kernel density estimator. Rasters were combined and scaled to map priority locations for the management of each focal species. Species’ rasters were combined and scaled to provide maps of overall priority for birds and for birds and reptiles. The spatial data can be used to identify high priority areas for conservation or to compare areas under consideration for maintenance or creation of open pine ecosystems.

Resource-Constrained Spatial Hot Spot Identification

DTIC Science & Technology

2011-01-01

into three categories ( Cameron and Leitner, 2005):2 Thematic Mapping. Concentrations of events are color-coded in discrete geo- graphic areas that...of Boston burglary events in 1999 and provided by Cameron and Leitner (2005). The first map reflects burglary rates per 100,000 residents by Census...Burglary Rates, 1999 RAND A8567-22 1 0 1 2 Miles Thematic mapping Kernel density interpolation Hierarchical clustering Source: Cameron and Leitner, 2005. For

Shapes on a plane: Evaluating the impact of projection distortion on spatial binning

USGS Publications Warehouse

Battersby, Sarah E.; Strebe, Daniel “daan”; Finn, Michael P.

2017-01-01

One method for working with large, dense sets of spatial point data is to aggregate the measure of the data into polygonal containers, such as political boundaries, or into regular spatial bins such as triangles, squares, or hexagons. When mapping these aggregations, the map projection must inevitably distort relationships. This distortion can impact the reader’s ability to compare count and density measures across the map. Spatial binning, particularly via hexagons, is becoming a popular technique for displaying aggregate measures of point data sets. Increasingly, we see questionable use of the technique without attendant discussion of its hazards. In this work, we discuss when and why spatial binning works and how mapmakers can better understand the limitations caused by distortion from projecting to the plane. We introduce equations for evaluating distortion’s impact on one common projection (Web Mercator) and discuss how the methods used generalize to other projections. While we focus on hexagonal binning, these same considerations affect spatial bins of any shape, and more generally, any analysis of geographic data performed in planar space.

Using a Mach-Zehnder interferometer to deduce nitrogen density mapping

NASA Astrophysics Data System (ADS)

Boudaoud, F.; Lemerini, M.

2015-07-01

This work presents an optical method using the Mach-Zehnder interferometer. We especially diagnose a pure nitrogen gas subjected to a point to plane corona discharge, and visualize the density spatial map. The interelectrode distance equals 6 mm and the variation of the optical path has been measured at different pressures: 220 Torr, 400 Torr, and 760 Torr. The interferograms are recorded with a CCD camera, and the numerical analysis of these interferograms is assured by the inverse Abel transformation. The nitrogen density is extracted through the Gladstone-Dale relation. The obtained results are in close agreement with values available in the literature.

Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites.

PubMed

Mitchard, Edward T A; Feldpausch, Ted R; Brienen, Roel J W; Lopez-Gonzalez, Gabriela; Monteagudo, Abel; Baker, Timothy R; Lewis, Simon L; Lloyd, Jon; Quesada, Carlos A; Gloor, Manuel; Ter Steege, Hans; Meir, Patrick; Alvarez, Esteban; Araujo-Murakami, Alejandro; Aragão, Luiz E O C; Arroyo, Luzmila; Aymard, Gerardo; Banki, Olaf; Bonal, Damien; Brown, Sandra; Brown, Foster I; Cerón, Carlos E; Chama Moscoso, Victor; Chave, Jerome; Comiskey, James A; Cornejo, Fernando; Corrales Medina, Massiel; Da Costa, Lola; Costa, Flavia R C; Di Fiore, Anthony; Domingues, Tomas F; Erwin, Terry L; Frederickson, Todd; Higuchi, Niro; Honorio Coronado, Euridice N; Killeen, Tim J; Laurance, William F; Levis, Carolina; Magnusson, William E; Marimon, Beatriz S; Marimon Junior, Ben Hur; Mendoza Polo, Irina; Mishra, Piyush; Nascimento, Marcelo T; Neill, David; Núñez Vargas, Mario P; Palacios, Walter A; Parada, Alexander; Pardo Molina, Guido; Peña-Claros, Marielos; Pitman, Nigel; Peres, Carlos A; Poorter, Lourens; Prieto, Adriana; Ramirez-Angulo, Hirma; Restrepo Correa, Zorayda; Roopsind, Anand; Roucoux, Katherine H; Rudas, Agustin; Salomão, Rafael P; Schietti, Juliana; Silveira, Marcos; de Souza, Priscila F; Steininger, Marc K; Stropp, Juliana; Terborgh, John; Thomas, Raquel; Toledo, Marisol; Torres-Lezama, Armando; van Andel, Tinde R; van der Heijden, Geertje M F; Vieira, Ima C G; Vieira, Simone; Vilanova-Torre, Emilio; Vos, Vincent A; Wang, Ophelia; Zartman, Charles E; Malhi, Yadvinder; Phillips, Oliver L

2014-08-01

The accurate mapping of forest carbon stocks is essential for understanding the global carbon cycle, for assessing emissions from deforestation, and for rational land-use planning. Remote sensing (RS) is currently the key tool for this purpose, but RS does not estimate vegetation biomass directly, and thus may miss significant spatial variations in forest structure. We test the stated accuracy of pantropical carbon maps using a large independent field dataset. Tropical forests of the Amazon basin. The permanent archive of the field plot data can be accessed at: http://dx.doi.org/10.5521/FORESTPLOTS.NET/2014_1. Two recent pantropical RS maps of vegetation carbon are compared to a unique ground-plot dataset, involving tree measurements in 413 large inventory plots located in nine countries. The RS maps were compared directly to field plots, and kriging of the field data was used to allow area-based comparisons. The two RS carbon maps fail to capture the main gradient in Amazon forest carbon detected using 413 ground plots, from the densely wooded tall forests of the north-east, to the light-wooded, shorter forests of the south-west. The differences between plots and RS maps far exceed the uncertainties given in these studies, with whole regions over- or under-estimated by > 25%, whereas regional uncertainties for the maps were reported to be < 5%. Pantropical biomass maps are widely used by governments and by projects aiming to reduce deforestation using carbon offsets, but may have significant regional biases. Carbon-mapping techniques must be revised to account for the known ecological variation in tree wood density and allometry to create maps suitable for carbon accounting. The use of single relationships between tree canopy height and above-ground biomass inevitably yields large, spatially correlated errors. This presents a significant challenge to both the forest conservation and remote sensing communities, because neither wood density nor species assemblages can be reliably mapped from space.

Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites

PubMed Central

Mitchard, Edward T A; Feldpausch, Ted R; Brienen, Roel J W; Lopez-Gonzalez, Gabriela; Monteagudo, Abel; Baker, Timothy R; Lewis, Simon L; Lloyd, Jon; Quesada, Carlos A; Gloor, Manuel; ter Steege, Hans; Meir, Patrick; Alvarez, Esteban; Araujo-Murakami, Alejandro; Aragão, Luiz E O C; Arroyo, Luzmila; Aymard, Gerardo; Banki, Olaf; Bonal, Damien; Brown, Sandra; Brown, Foster I; Cerón, Carlos E; Chama Moscoso, Victor; Chave, Jerome; Comiskey, James A; Cornejo, Fernando; Corrales Medina, Massiel; Da Costa, Lola; Costa, Flavia R C; Di Fiore, Anthony; Domingues, Tomas F; Erwin, Terry L; Frederickson, Todd; Higuchi, Niro; Honorio Coronado, Euridice N; Killeen, Tim J; Laurance, William F; Levis, Carolina; Magnusson, William E; Marimon, Beatriz S; Marimon Junior, Ben Hur; Mendoza Polo, Irina; Mishra, Piyush; Nascimento, Marcelo T; Neill, David; Núñez Vargas, Mario P; Palacios, Walter A; Parada, Alexander; Pardo Molina, Guido; Peña-Claros, Marielos; Pitman, Nigel; Peres, Carlos A; Poorter, Lourens; Prieto, Adriana; Ramirez-Angulo, Hirma; Restrepo Correa, Zorayda; Roopsind, Anand; Roucoux, Katherine H; Rudas, Agustin; Salomão, Rafael P; Schietti, Juliana; Silveira, Marcos; de Souza, Priscila F; Steininger, Marc K; Stropp, Juliana; Terborgh, John; Thomas, Raquel; Toledo, Marisol; Torres-Lezama, Armando; van Andel, Tinde R; van der Heijden, Geertje M F; Vieira, Ima C G; Vieira, Simone; Vilanova-Torre, Emilio; Vos, Vincent A; Wang, Ophelia; Zartman, Charles E; Malhi, Yadvinder; Phillips, Oliver L

2014-01-01

Aim The accurate mapping of forest carbon stocks is essential for understanding the global carbon cycle, for assessing emissions from deforestation, and for rational land-use planning. Remote sensing (RS) is currently the key tool for this purpose, but RS does not estimate vegetation biomass directly, and thus may miss significant spatial variations in forest structure. We test the stated accuracy of pantropical carbon maps using a large independent field dataset. Location Tropical forests of the Amazon basin. The permanent archive of the field plot data can be accessed at: http://dx.doi.org/10.5521/FORESTPLOTS.NET/2014_1 Methods Two recent pantropical RS maps of vegetation carbon are compared to a unique ground-plot dataset, involving tree measurements in 413 large inventory plots located in nine countries. The RS maps were compared directly to field plots, and kriging of the field data was used to allow area-based comparisons. Results The two RS carbon maps fail to capture the main gradient in Amazon forest carbon detected using 413 ground plots, from the densely wooded tall forests of the north-east, to the light-wooded, shorter forests of the south-west. The differences between plots and RS maps far exceed the uncertainties given in these studies, with whole regions over- or under-estimated by > 25%, whereas regional uncertainties for the maps were reported to be < 5%. Main conclusions Pantropical biomass maps are widely used by governments and by projects aiming to reduce deforestation using carbon offsets, but may have significant regional biases. Carbon-mapping techniques must be revised to account for the known ecological variation in tree wood density and allometry to create maps suitable for carbon accounting. The use of single relationships between tree canopy height and above-ground biomass inevitably yields large, spatially correlated errors. This presents a significant challenge to both the forest conservation and remote sensing communities, because neither wood density nor species assemblages can be reliably mapped from space. PMID:26430387

Spatial aspects of tree mortality strongly differ between young and old-growth forests.

PubMed

Larson, Andrew J; Lutz, James A; Donato, Daniel C; Freund, James A; Swanson, Mark E; HilleRisLambers, Janneke; Sprugel, Douglas G; Franklin, Jerry F

2015-11-01

Rates and spatial patterns of tree mortality are predicted to change during forest structural development. In young forests, mortality should be primarily density dependent due to competition for light, leading to an increasingly spatially uniform pattern of surviving trees. In contrast, mortality in old-growth forests should be primarily caused by contagious and spatially autocorrelated agents (e.g., insects, wind), causing spatial aggregation of surviving trees to increase through time. We tested these predictions by contrasting a three-decade record of tree mortality from replicated mapped permanent plots located in young (< 60-year-old) and old-growth (> 300-year-old) Abies amabilis forests. Trees in young forests died at a rate of 4.42% per year, whereas trees in old-growth forests died at 0.60% per year. Tree mortality in young forests was significantly aggregated, strongly density dependent, and caused live tree patterns to become more uniform through time. Mortality in old-growth forests was spatially aggregated, but was density independent and did not change the spatial pattern of surviving trees. These results extend current theory by demonstrating that density-dependent competitive mortality leading to increasingly uniform tree spacing in young forests ultimately transitions late in succession to a more diverse tree mortality regime that maintains spatial heterogeneity through time.

Human population, urban settlement patterns and their impact on Plasmodium falciparum malaria endemicity.

PubMed

Tatem, Andrew J; Guerra, Carlos A; Kabaria, Caroline W; Noor, Abdisalan M; Hay, Simon I

2008-10-27

The efficient allocation of financial resources for malaria control and the optimal distribution of appropriate interventions require accurate information on the geographic distribution of malaria risk and of the human populations it affects. Low population densities in rural areas and high population densities in urban areas can influence malaria transmission substantially. Here, the Malaria Atlas Project (MAP) global database of Plasmodium falciparum parasite rate (PfPR) surveys, medical intelligence and contemporary population surfaces are utilized to explore these relationships and other issues involved in combining malaria risk maps with those of human population distribution in order to define populations at risk more accurately. First, an existing population surface was examined to determine if it was sufficiently detailed to be used reliably as a mask to identify areas of very low and very high population density as malaria free regions. Second, the potential of international travel and health guidelines (ITHGs) for identifying malaria free cities was examined. Third, the differences in PfPR values between surveys conducted in author-defined rural and urban areas were examined. Fourth, the ability of various global urban extent maps to reliably discriminate these author-based classifications of urban and rural in the PfPR database was investigated. Finally, the urban map that most accurately replicated the author-based classifications was analysed to examine the effects of urban classifications on PfPR values across the entire MAP database. Masks of zero population density excluded many non-zero PfPR surveys, indicating that the population surface was not detailed enough to define areas of zero transmission resulting from low population densities. In contrast, the ITHGs enabled the identification and mapping of 53 malaria free urban areas within endemic countries. Comparison of PfPR survey results showed significant differences between author-defined 'urban' and 'rural' designations in Africa, but not for the remainder of the malaria endemic world. The Global Rural Urban Mapping Project (GRUMP) urban extent mask proved most accurate for mapping these author-defined rural and urban locations, and further sub-divisions of urban extents into urban and peri-urban classes enabled the effects of high population densities on malaria transmission to be mapped and quantified. The availability of detailed, contemporary census and urban extent data for the construction of coherent and accurate global spatial population databases is often poor. These known sources of uncertainty in population surfaces and urban maps have the potential to be incorporated into future malaria burden estimates. Currently, insufficient spatial information exists globally to identify areas accurately where population density is low enough to impact upon transmission. Medical intelligence does however exist to reliably identify malaria free cities. Moreover, in Africa, urban areas that have a significant effect on malaria transmission can be mapped.

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.

Evaluation of realistic layouts for next generation on-scalp MEG: spatial information density maps.

PubMed

Riaz, Bushra; Pfeiffer, Christoph; Schneiderman, Justin F

2017-08-01

While commercial magnetoencephalography (MEG) systems are the functional neuroimaging state-of-the-art in terms of spatio-temporal resolution, MEG sensors have not changed significantly since the 1990s. Interest in newer sensors that operate at less extreme temperatures, e.g., high critical temperature (high-T c ) SQUIDs, optically-pumped magnetometers, etc., is growing because they enable significant reductions in head-to-sensor standoff (on-scalp MEG). Various metrics quantify the advantages of on-scalp MEG, but a single straightforward one is lacking. Previous works have furthermore been limited to arbitrary and/or unrealistic sensor layouts. We introduce spatial information density (SID) maps for quantitative and qualitative evaluations of sensor arrays. SID-maps present the spatial distribution of information a sensor array extracts from a source space while accounting for relevant source and sensor parameters. We use it in a systematic comparison of three practical on-scalp MEG sensor array layouts (based on high-T c SQUIDs) and the standard Elekta Neuromag TRIUX magnetometer array. Results strengthen the case for on-scalp and specifically high-T c SQUID-based MEG while providing a path for the practical design of future MEG systems. SID-maps are furthermore general to arbitrary magnetic sensor technologies and source spaces and can thus be used for design and evaluation of sensor arrays for magnetocardiography, magnetic particle imaging, etc.

Identifying landscape features associated with Rift Valley fever virus transmission, Ferlo region, Senegal, using very high spatial resolution satellite imagery.

PubMed

Soti, Valérie; Chevalier, Véronique; Maura, Jonathan; Bégué, Agnès; Lelong, Camille; Lancelot, Renaud; Thiongane, Yaya; Tran, Annelise

2013-03-01

Dynamics of most of vector-borne diseases are strongly linked to global and local environmental changes. Landscape changes are indicators of human activities or natural processes that are likely to modify the ecology of the diseases. Here, a landscape approach developed at a local scale is proposed for extracting mosquito favourable biotopes, and for testing ecological parameters when identifying risk areas of Rift Valley fever (RVF) transmission. The study was carried out around Barkedji village, Ferlo region, Senegal. In order to test whether pond characteristics may influence the density and the dispersal behaviour of RVF vectors, and thus the spatial variation in RVFV transmission, we used a very high spatial resolution remote sensing image (2.4 m resolution) provided by the Quickbird sensor to produce a detailed land-cover map of the study area. Based on knowledge of vector and disease ecology, seven landscape attributes were defined at the pond level and computed from the land-cover map. Then, the relationships between landscape attributes and RVF serologic incidence rates in small ruminants were analyzed through a beta-binomial regression. Finally, the best statistical model according to the Akaike Information Criterion corrected for small samples (AICC), was used to map areas at risk for RVF. Among the derived landscape variables, the vegetation density index (VDI) computed within a 500 m buffer around ponds was positively correlated with serologic incidence (p<0.001), suggesting that the risk of RVF transmission was higher in the vicinity of ponds surrounded by a dense vegetation cover. The final risk map of RVF transmission displays a heterogeneous spatial distribution, corroborating previous findings from the same area. Our results highlight the potential of very high spatial resolution remote sensing data for identifying environmental risk factors and mapping RVF risk areas at a local scale.

Identifying landscape features associated with Rift Valley fever virus transmission, Ferlo region, Senegal, using very high spatial resolution satellite imagery

PubMed Central

2013-01-01

Introduction Dynamics of most of vector-borne diseases are strongly linked to global and local environmental changes. Landscape changes are indicators of human activities or natural processes that are likely to modify the ecology of the diseases. Here, a landscape approach developed at a local scale is proposed for extracting mosquito favourable biotopes, and for testing ecological parameters when identifying risk areas of Rift Valley fever (RVF) transmission. The study was carried out around Barkedji village, Ferlo region, Senegal. Methods In order to test whether pond characteristics may influence the density and the dispersal behaviour of RVF vectors, and thus the spatial variation in RVFV transmission, we used a very high spatial resolution remote sensing image (2.4 m resolution) provided by the Quickbird sensor to produce a detailed land-cover map of the study area. Based on knowledge of vector and disease ecology, seven landscape attributes were defined at the pond level and computed from the land-cover map. Then, the relationships between landscape attributes and RVF serologic incidence rates in small ruminants were analyzed through a beta-binomial regression. Finally, the best statistical model according to the Akaike Information Criterion corrected for small samples (AICC), was used to map areas at risk for RVF. Results Among the derived landscape variables, the vegetation density index (VDI) computed within a 500 m buffer around ponds was positively correlated with serologic incidence (p<0.001), suggesting that the risk of RVF transmission was higher in the vicinity of ponds surrounded by a dense vegetation cover. The final risk map of RVF transmission displays a heterogeneous spatial distribution, corroborating previous findings from the same area. Conclusions Our results highlight the potential of very high spatial resolution remote sensing data for identifying environmental risk factors and mapping RVF risk areas at a local scale. PMID:23452759

Support for the existence of invertible maps between electronic densities and non-analytic 1-body external potentials in non-relativistic time-dependent quantum mechanics

NASA Astrophysics Data System (ADS)

Mosquera, Martín A.

2017-10-01

Provided the initial state, the Runge-Gross theorem establishes that the time-dependent (TD) external potential of a system of non-relativistic electrons determines uniquely their TD electronic density, and vice versa (up to a constant in the potential). This theorem requires the TD external potential and density to be Taylor-expandable around the initial time of the propagation. This paper presents an extension without this restriction. Given the initial state of the system and evolution of the density due to some TD scalar potential, we show that a perturbative (not necessarily weak) TD potential that induces a non-zero divergence of the external force-density, inside a small spatial subset and immediately after the initial propagation time, will cause a change in the density within that subset, implying that the TD potential uniquely determines the TD density. In this proof, we assume unitary evolution of wavefunctions and first-order differentiability (which does not imply analyticity) in time of the internal and external force-densities, electronic density, current density, and their spatial derivatives over the small spatial subset and short time interval.

Spatial and Temporal Analysis of Eruption Locations, Compositions, and Styles in Northern Harrat Rahat, Kingdom of Saudi Arabia

NASA Astrophysics Data System (ADS)

Dietterich, H. R.; Stelten, M. E.; Downs, D. T.; Champion, D. E.

2017-12-01

Harrat Rahat is a predominantly mafic, 20,000 km2 volcanic field in western Saudi Arabia with an elongate volcanic axis extending 310 km north-south. Prior mapping suggests that the youngest eruptions were concentrated in northernmost Harrat Rahat, where our new geologic mapping and geochronology reveal >300 eruptive vents with ages ranging from 1.2 Ma to a historic eruption in 1256 CE. Eruption compositions and styles vary spatially and temporally within the volcanic field, where extensive alkali basaltic lavas dominate, but more evolved compositions erupted episodically as clusters of trachytic domes and small-volume pyroclastic flows. Analysis of vent locations, compositions, and eruption styles shows the evolution of the volcanic field and allows assessment of the spatio-temporal probabilities of vent opening and eruption styles. We link individual vents and fissures to eruptions and their deposits using field relations, petrography, geochemistry, paleomagnetism, and 40Ar/39Ar and 36Cl geochronology. Eruption volumes and deposit extents are derived from geologic mapping and topographic analysis. Spatial density analysis with kernel density estimation captures vent densities of up to 0.2 %/km2 along the north-south running volcanic axis, decaying quickly away to the east but reaching a second, lower high along a secondary axis to the west. Temporal trends show slight younging of mafic eruption ages to the north in the past 300 ka, as well as clustered eruptions of trachytes over the past 150 ka. Vent locations, timing, and composition are integrated through spatial probability weighted by eruption age for each compositional range to produce spatio-temporal models of vent opening probability. These show that the next mafic eruption is most probable within the north end of the main (eastern) volcanic axis, whereas more evolved compositions are most likely to erupt within the trachytic centers further to the south. These vent opening probabilities, combined with corresponding eruption properties, can be used as the basis for lava flow and tephra fall hazard maps.

Mapping Reef Fish and the Seascape: Using Acoustics and Spatial Modeling to Guide Coastal Management

PubMed Central

Costa, Bryan; Taylor, J. Christopher; Kracker, Laura; Battista, Tim; Pittman, Simon

2014-01-01

Reef fish distributions are patchy in time and space with some coral reef habitats supporting higher densities (i.e., aggregations) of fish than others. Identifying and quantifying fish aggregations (particularly during spawning events) are often top priorities for coastal managers. However, the rapid mapping of these aggregations using conventional survey methods (e.g., non-technical SCUBA diving and remotely operated cameras) are limited by depth, visibility and time. Acoustic sensors (i.e., splitbeam and multibeam echosounders) are not constrained by these same limitations, and were used to concurrently map and quantify the location, density and size of reef fish along with seafloor structure in two, separate locations in the U.S. Virgin Islands. Reef fish aggregations were documented along the shelf edge, an ecologically important ecotone in the region. Fish were grouped into three classes according to body size, and relationships with the benthic seascape were modeled in one area using Boosted Regression Trees. These models were validated in a second area to test their predictive performance in locations where fish have not been mapped. Models predicting the density of large fish (≥29 cm) performed well (i.e., AUC = 0.77). Water depth and standard deviation of depth were the most influential predictors at two spatial scales (100 and 300 m). Models of small (≤11 cm) and medium (12–28 cm) fish performed poorly (i.e., AUC = 0.49 to 0.68) due to the high prevalence (45–79%) of smaller fish in both locations, and the unequal prevalence of smaller fish in the training and validation areas. Integrating acoustic sensors with spatial modeling offers a new and reliable approach to rapidly identify fish aggregations and to predict the density large fish in un-surveyed locations. This integrative approach will help coastal managers to prioritize sites, and focus their limited resources on areas that may be of higher conservation value. PMID:24454886

MABEL Photon-Counting Laser Altimetry Data in Alaska for ICESat-2 Simulations and Development

NASA Technical Reports Server (NTRS)

Brunt, Kelly; Neumann, T. A.; Amundson, M.; Kavanaugh, J. L.; Moussavi, M. S.; Walsh, K. M.; Cook, W. B.; Markus, T.

2016-01-01

Multiple Altimeter Beam Experimental Lidar (MABEL) maps Alaskan crevasses in detail, using 50 of the expected along-track Advanced Topographic Laser Altimeter System (ATLAS) signal-photon densities over summer ice sheets. Ice, Cloud, and Land Elevation Satellite 2 (ICESat-2) along-track data density, and spatial data density due to the multiple-beam strategy, will provide a new dataset to mid-latitude alpine glacier researchers.

Preliminary Isostatic Gravity Map of Joshua Tree National Park and Vicinity, Southern California

USGS Publications Warehouse

Langenheim, V.E.; Biehler, Shawn; McPhee, D.K.; McCabe, C.A.; Watt, J.T.; Anderson, M.L.; Chuchel, B.A.; Stoffer, P.

2007-01-01

This isostatic residual gravity map is part of an effort to map the three-dimensional distribution of rocks in Joshua Tree National Park, southern California. This map will serve as a basis for modeling the shape of basins beneath the Park and in adjacent valleys and also for determining the location and geometry of faults within the area. Local spatial variations in the Earth's gravity field, after accounting for variations caused by elevation, terrain, and deep crustal structure, reflect the distribution of densities in the mid- to upper crust. Densities often can be related to rock type, and abrupt spatial changes in density commonly mark lithologic or structural boundaries. High-density basement rocks exposed within the Eastern Transverse Ranges include crystalline rocks that range in age from Proterozoic to Mesozoic and these rocks are generally present in the mountainous areas of the quadrangle. Alluvial sediments, usually located in the valleys, and Tertiary sedimentary rocks are characterized by low densities. However, with increasing depth of burial and age, the densities of these rocks may become indistinguishable from those of basement rocks. Tertiary volcanic rocks are characterized by a wide range of densities, but, on average, are less dense than the pre-Cenozoic basement rocks. Basalt within the Park is as dense as crystalline basement, but is generally thin (less than 100 m thick; e.g., Powell, 2003). Isostatic residual gravity values within the map area range from about 44 mGal over Coachella Valley to about 8 mGal between the Mecca Hills and the Orocopia Mountains. Steep linear gravity gradients are coincident with the traces of several Quaternary strike-slip faults, most notably along the San Andreas Fault bounding the east side of Coachella Valley and east-west-striking, left-lateral faults, such as the Pinto Mountain, Blue Cut, and Chiriaco Faults (Fig. 1). Gravity gradients also define concealed basin-bounding faults, such as those beneath the Chuckwalla Valley (e.g. Rotstein and others, 1976). These gradients result from juxtaposing dense basement rocks against thick Cenozoic sedimentary rocks.

Derivation of a northern-hemispheric biomass map for use in global carbon cycle models

NASA Astrophysics Data System (ADS)

Thurner, Martin; Beer, Christian; Santoro, Maurizio; Carvalhais, Nuno; Wutzler, Thomas; Schepaschenko, Dmitry; Shvidenko, Anatoly; Kompter, Elisabeth; Levick, Shaun; Schmullius, Christiane

2013-04-01

Quantifying the state and the change of the World's forests is crucial because of their ecological, social and economic value. Concerning their ecological importance, forests provide important feedbacks on the global carbon, energy and water cycles. In addition to their influence on albedo and evapotranspiration, they have the potential to sequester atmospheric carbon dioxide and thus to mitigate global warming. The current state and inter-annual variability of forest carbon stocks remain relatively unexplored, but remote sensing can serve to overcome this shortcoming. While for the tropics wall-to-wall estimates of above-ground biomass have been recently published, up to now there was a lack of similar products covering boreal and temperate forests. Recently, estimates of forest growing stock volume (GSV) were derived from ENVISAT ASAR C-band data for latitudes above 30° N. Utilizing a wood density and a biomass compartment database, a forest carbon density map covering North-America, Europe and Asia with 0.01° resolution could be derived out of this dataset. Allometric functions between stem, branches, root and foliage biomass were fitted and applied for different leaf types (broadleaf, needleleaf deciduous, needleleaf evergreen forest). Additionally, this method enabled uncertainty estimation of the resulting carbon density map. Intercomparisons with inventory-based biomass products in Russia, Europe and the USA proved the high accuracy of this approach at a regional scale (r2 = 0.70 - 0.90). Based on the final biomass map, the forest carbon stocks and densities (excluding understorey vegetation) for three biomes were estimated across three continents. While 40.7 ± 15.7 Gt of carbon were found to be stored in boreal forests, temperate broadleaf/mixed forests and temperate conifer forests contain 24.5 ± 9.4 Gt(C) and 14.5 ± 4.8 Gt(C), respectively. In terms of carbon density, most of the carbon per area is stored in temperate conifer (62.1 ± 20.7 Mg(C)/ha(Forest)) and broadleaf/mixed forests (58.0 ± 22.1 Mg(C)/ha(Forest)), whereas boreal forests have a carbon density of only 40.0 ± 15.4 Mg(C)/ha(Forest). While European forest carbon stocks are relatively small, the carbon density is higher compared to the other continents. The derived biomass map substantially improves the knowledge on the current carbon stocks of the northern-hemispheric boreal and temperate forests, serving as a new benchmark for spatially explicit and consistent biomass mapping with moderate spatial resolution. This product can be of great value for global carbon cycle models as well as national carbon monitoring systems. Further investigations concentrate on improving biomass parameterizations and representations in such kind of models. The presented map will help to improve the simulation of biomass spatial patterns and variability and enables identifying the dominant influential factors like climatic conditions and disturbances.

Surficial geologic map of the Amboy 30' x 60' quadrangle, San Bernardino County, California

USGS Publications Warehouse

Bedford, David R.; Miller, David M.; Phelps, Geoffrey A.

2010-01-01

The surficial geologic map of the Amboy 30' x 60' quadrangle presents characteristics of surficial materials for an area of approximately 5,000 km2 in the eastern Mojave Desert of southern California. This map consists of new surficial mapping conducted between 2000 and 2007, as well as compilations from previous surficial mapping. Surficial geologic units are mapped and described based on depositional process and age categories that reflect the mode of deposition, pedogenic effects following deposition, and, where appropriate, the lithologic nature of the material. Many physical properties were noted and measured during the geologic mapping. This information was used to classify surficial deposits and to understand their ecological importance. We focus on physical properties that drive hydrologic, biologic, and physical processes such as particle-size distribution (PSD) and bulk density. The database contains point data representing locations of samples for both laboratory determined physical properties and semiquantitative field-based information in the database. We include the locations of all field observations and note the type of information collected in the field to help assist in assessing the quality of the mapping. The publication is separated into three parts: documentation, spatial data, and printable map graphics of the database. Documentation includes this pamphlet, which provides a discussion of the surficial geology and units and the map. Spatial data are distributed as ArcGIS Geodatabase in Microsoft Access format and are accompanied by a readme file, which describes the database contents, and FGDC metadata for the spatial map information. Map graphics files are distributed as Postscript and Adobe Portable Document Format (PDF) files that provide a view of the spatial database at the mapped scale.

Preliminary surficial geologic map database of the Amboy 30 x 60 minute quadrangle, California

USGS Publications Warehouse

Bedford, David R.; Miller, David M.; Phelps, Geoffrey A.

2006-01-01

The surficial geologic map database of the Amboy 30x60 minute quadrangle presents characteristics of surficial materials for an area approximately 5,000 km2 in the eastern Mojave Desert of California. This map consists of new surficial mapping conducted between 2000 and 2005, as well as compilations of previous surficial mapping. Surficial geology units are mapped and described based on depositional process and age categories that reflect the mode of deposition, pedogenic effects occurring post-deposition, and, where appropriate, the lithologic nature of the material. The physical properties recorded in the database focus on those that drive hydrologic, biologic, and physical processes such as particle size distribution (PSD) and bulk density. This version of the database is distributed with point data representing locations of samples for both laboratory determined physical properties and semi-quantitative field-based information. Future publications will include the field and laboratory data as well as maps of distributed physical properties across the landscape tied to physical process models where appropriate. The database is distributed in three parts: documentation, spatial map-based data, and printable map graphics of the database. Documentation includes this file, which provides a discussion of the surficial geology and describes the format and content of the map data, a database 'readme' file, which describes the database contents, and FGDC metadata for the spatial map information. Spatial data are distributed as Arc/Info coverage in ESRI interchange (e00) format, or as tabular data in the form of DBF3-file (.DBF) file formats. Map graphics files are distributed as Postscript and Adobe Portable Document Format (PDF) files, and are appropriate for representing a view of the spatial database at the mapped scale.

Mapping the spatial distribution of star formation in cluster galaxies at z ~0.5 with the Grism Lens-Amplified Survey from Space (GLASS)

NASA Astrophysics Data System (ADS)

Vulcani, B.; Treu, T.; Schmidt, K. B.; Poggianti, B. M.; Dressler, A.; Fontana, A.; Bradač, M.; Brammer, G. B.; Hoag, A.; Huang, K.; Malkan, M.; Pentericci, L.; Trenti, M.; von der Linden, A.; Abramson, L.; He, J.; Morris, G.

2016-06-01

What physical processes regulate star formation in dense environments? Understanding why galaxy evolution is environment dependent is one of the key questions of current astrophysics. I will present the first characterization of the spatial distribution of star formation in cluster galaxies at z~0.5, and compare to a field control sample, in order to quantify the role of different physical processes that are believed to be responsible for shutting down star formation (Vulcani et al. 2015, Vulcani et al. in prep). The analysis makes use of data from the Grism Lens-Amplified Survey from Space (GLASS), a large HST cycle-21 program targeting 10 massive galaxy clusters with extensive HST imaging from CLASH and the Frontier Field Initiative. The program consists of 140 primary and 140 parallel orbits of near-infrared WCF3 and optical ACS slitless grism observations, which result in 3D spectroscopy of hundreds of galaxies. The grism data are used to produce spatially resolved maps of the star formation density, while the stellar mass density and optical surface brightness are obtained from multiband imaging. I will describe quantitative measures of the spatial location and extent of the star formation rate. I will show that both in clusters and in the field, Hα is more extended than the rest-frame UV continuum in 60% of the cases, consistent with diffuse star formation and inside out growth. The Hα emission appears more extended in cluster galaxies than in the field, pointing perhaps to ionized gas being stripped and/or star formation being enhanced at large radii. The peak of the Hα emission and that of the continuum are offset by less than 1 kpc. I will also correlate the properties of the Hα maps to the cluster global properties, such as the hot gas density, and the surface mass density. The characterization of the spatial distribution of Halpha provides a new window, yet poorly exploited, on the mechanisms that regulate star formation and morphological transformation in dense environments.

Wild boar mapping using population-density statistics: From polygons to high resolution raster maps.

PubMed

Pittiglio, Claudia; Khomenko, Sergei; Beltran-Alcrudo, Daniel

2018-01-01

The wild boar is an important crop raider as well as a reservoir and agent of spread of swine diseases. Due to increasing densities and expanding ranges worldwide, the related economic losses in livestock and agricultural sectors are significant and on the rise. Its management and control would strongly benefit from accurate and detailed spatial information on species distribution and abundance, which are often available only for small areas. Data are commonly available at aggregated administrative units with little or no information about the distribution of the species within the unit. In this paper, a four-step geostatistical downscaling approach is presented and used to disaggregate wild boar population density statistics from administrative units of different shape and size (polygons) to 5 km resolution raster maps by incorporating auxiliary fine scale environmental variables. 1) First a stratification method was used to define homogeneous bioclimatic regions for the analysis; 2) Under a geostatistical framework, the wild boar densities at administrative units, i.e. subnational areas, were decomposed into trend and residual components for each bioclimatic region. Quantitative relationships between wild boar data and environmental variables were estimated through multiple regression and used to derive trend components at 5 km spatial resolution. Next, the residual components (i.e., the differences between the trend components and the original wild boar data at administrative units) were downscaled at 5 km resolution using area-to-point kriging. The trend and residual components obtained at 5 km resolution were finally added to generate fine scale wild boar estimates for each bioclimatic region. 3) These maps were then mosaicked to produce a final output map of predicted wild boar densities across most of Eurasia. 4) Model accuracy was assessed at each different step using input as well as independent data. We discuss advantages and limits of the method and its potential application in animal health.

Wild boar mapping using population-density statistics: From polygons to high resolution raster maps

PubMed Central

Pittiglio, Claudia; Khomenko, Sergei

2018-01-01

The wild boar is an important crop raider as well as a reservoir and agent of spread of swine diseases. Due to increasing densities and expanding ranges worldwide, the related economic losses in livestock and agricultural sectors are significant and on the rise. Its management and control would strongly benefit from accurate and detailed spatial information on species distribution and abundance, which are often available only for small areas. Data are commonly available at aggregated administrative units with little or no information about the distribution of the species within the unit. In this paper, a four-step geostatistical downscaling approach is presented and used to disaggregate wild boar population density statistics from administrative units of different shape and size (polygons) to 5 km resolution raster maps by incorporating auxiliary fine scale environmental variables. 1) First a stratification method was used to define homogeneous bioclimatic regions for the analysis; 2) Under a geostatistical framework, the wild boar densities at administrative units, i.e. subnational areas, were decomposed into trend and residual components for each bioclimatic region. Quantitative relationships between wild boar data and environmental variables were estimated through multiple regression and used to derive trend components at 5 km spatial resolution. Next, the residual components (i.e., the differences between the trend components and the original wild boar data at administrative units) were downscaled at 5 km resolution using area-to-point kriging. The trend and residual components obtained at 5 km resolution were finally added to generate fine scale wild boar estimates for each bioclimatic region. 3) These maps were then mosaicked to produce a final output map of predicted wild boar densities across most of Eurasia. 4) Model accuracy was assessed at each different step using input as well as independent data. We discuss advantages and limits of the method and its potential application in animal health. PMID:29768413

Local breast density assessment using reacquired mammographic images.

PubMed

García, Eloy; Diaz, Oliver; Martí, Robert; Diez, Yago; Gubern-Mérida, Albert; Sentís, Melcior; Martí, Joan; Oliver, Arnau

2017-08-01

The aim of this paper is to evaluate the spatial glandular volumetric tissue distribution as well as the density measures provided by Volpara™ using a dataset composed of repeated pairs of mammograms, where each pair was acquired in a short time frame and in a slightly changed position of the breast. We conducted a retrospective analysis of 99 pairs of repeatedly acquired full-field digital mammograms from 99 different patients. The commercial software Volpara™ Density Maps (Volpara Solutions, Wellington, New Zealand) is used to estimate both the global and the local glandular tissue distribution in each image. The global measures provided by Volpara™, such as breast volume, volume of glandular tissue, and volumetric breast density are compared between the two acquisitions. The evaluation of the local glandular information is performed using histogram similarity metrics, such as intersection and correlation, and local measures, such as statistics from the difference image and local gradient correlation measures. Global measures showed a high correlation (breast volume R=0.99, volume of glandular tissue R=0.94, and volumetric breast density R=0.96) regardless the anode/filter material. Similarly, histogram intersection and correlation metric showed that, for each pair, the images share a high degree of information. Regarding the local distribution of glandular tissue, small changes in the angle of view do not yield significant differences in the glandular pattern, whilst changes in the breast thickness between both acquisition affect the spatial parenchymal distribution. This study indicates that Volpara™ Density Maps is reliable in estimating the local glandular tissue distribution and can be used for its assessment and follow-up. Volpara™ Density Maps is robust to small variations of the acquisition angle and to the beam energy, although divergences arise due to different breast compression conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Geostatistical analysis of disease data: accounting for spatial support and population density in the isopleth mapping of cancer mortality risk using area-to-point Poisson kriging

PubMed Central

Goovaerts, Pierre

2006-01-01

Background Geostatistical techniques that account for spatially varying population sizes and spatial patterns in the filtering of choropleth maps of cancer mortality were recently developed. Their implementation was facilitated by the initial assumption that all geographical units are the same size and shape, which allowed the use of geographic centroids in semivariogram estimation and kriging. Another implicit assumption was that the population at risk is uniformly distributed within each unit. This paper presents a generalization of Poisson kriging whereby the size and shape of administrative units, as well as the population density, is incorporated into the filtering of noisy mortality rates and the creation of isopleth risk maps. An innovative procedure to infer the point-support semivariogram of the risk from aggregated rates (i.e. areal data) is also proposed. Results The novel methodology is applied to age-adjusted lung and cervix cancer mortality rates recorded for white females in two contrasted county geographies: 1) state of Indiana that consists of 92 counties of fairly similar size and shape, and 2) four states in the Western US (Arizona, California, Nevada and Utah) forming a set of 118 counties that are vastly different geographical units. Area-to-point (ATP) Poisson kriging produces risk surfaces that are less smooth than the maps created by a naïve point kriging of empirical Bayesian smoothed rates. The coherence constraint of ATP kriging also ensures that the population-weighted average of risk estimates within each geographical unit equals the areal data for this unit. Simulation studies showed that the new approach yields more accurate predictions and confidence intervals than point kriging of areal data where all counties are simply collapsed into their respective polygon centroids. Its benefit over point kriging increases as the county geography becomes more heterogeneous. Conclusion A major limitation of choropleth maps is the common biased visual perception that larger rural and sparsely populated areas are of greater importance. The approach presented in this paper allows the continuous mapping of mortality risk, while accounting locally for population density and areal data through the coherence constraint. This form of Poisson kriging will facilitate the analysis of relationships between health data and putative covariates that are typically measured over different spatial supports. PMID:17137504

Integrating proximal soil sensing techniques and terrain indexes to generate 3D maps of soil restrictive layers in the Palouse region, Washington, USA

NASA Astrophysics Data System (ADS)

Poggio, Matteo; Brown, David J.; Gasch, Caley K.; Brooks, Erin S.; Yourek, Matt A.

2015-04-01

In the Palouse region of eastern Washington and northern Idaho (USA), spatially discontinuous restrictive layers impede rooting growth and water infiltration. Consequently, accurate maps showing the depth and spatial extent of these restrictive layers are essential for watershed hydrologic modeling appropriate for precision agriculture. In this presentation, we report on the use of a Visible and Near-Infrared (VisNIR) penetrometer fore optic to construct detailed maps of three wheat fields in the Palouse region. The VisNIR penetrometer was used to deliver in situ soil reflectance to an Analytical Spectral Devices (ASD, Boulder, CO, USA) spectrometer and simultaneously acquire insertion force. With a hydraulic push-type soil coring systems for insertion (e.g. Giddings), we collected soil spectra and insertion force data along 41m x 41m grid points (2 fields) and 50m x 50m grid points (1 field) to ≈80cm depth, in addition to interrogation points at 36 representative instrumented locations per field. At each of the 36 instrumented locations, two soil cores were extracted for laboratory determination of clay content and bulk density. We developed calibration models of soil clay content and bulk density with spectra and insertion force collected in situ, using partial least squares regression 2 (PLSR2). Applying spline functions, we delineated clay and bulk density profiles at each points (grid and 24 locations). The soil profiles were then used as inputs in a regression-kriging model with terrain indexes and ECa data (derived from an EM38 field survey, Geonics, Mississauga, Ontario, Canada) as covariates to generate 3D soil maps. Preliminary results show that the VisNIR penetrometer can capture the spatial patterns of restrictive layers. Work is ongoing to evaluate the prediction accuracy of penetrometer-derived 3D clay content and restriction layer maps.

Mapping low-frequency carbon radio recombination lines towards Cassiopeia A at 340, 148, 54, and 43 MHz

NASA Astrophysics Data System (ADS)

Salas, P.; Oonk, J. B. R.; van Weeren, R. J.; Wolfire, M. G.; Emig, K. L.; Toribio, M. C.; Röttgering, H. J. A.; Tielens, A. G. G. M.

2018-04-01

Quantitative understanding of the interstellar medium requires knowledge of its physical conditions. Low-frequency carbon radio recombination lines (CRRLs) trace cold interstellar gas and can be used to determine its physical conditions (e.g. electron temperature and density). In this work, we present spatially resolved observations of the low-frequency (≤390 MHz) CRRLs centred around C268α, C357α, C494α, and C539α towards Cassiopeia A on scales of ≤1.2 pc. We compare the spatial distribution of CRRLs with other interstellar medium tracers. This comparison reveals a spatial offset between the peak of the CRRLs and other tracers, which is very characteristic for photodissociation regions and that we take as evidence for CRRLs being preferentially detected from the surfaces of molecular clouds. Using the CRRLs, we constrain the gas electron temperature and density. These constraints on the gas conditions suggest variations of less than a factor of 2 in pressure over ˜1 pc scales, and an average hydrogen density of 200-470 cm-3. From the electron temperature and density maps, we also constrain the ionized carbon emission measure, column density, and path length. Based on these, the hydrogen column density is larger than 1022 cm-2, with a peak of ˜4 × 1022 cm-2 towards the south of Cassiopeia A. Towards the southern peak, the line-of-sight length is ˜40 pc over a ˜2 pc wide structure, which implies that the gas is a thin surface layer on a large (molecular) cloud that is only partially intersected by Cassiopeia A. These observations highlight the utility of CRRLs as tracers of low-density extended H I and CO-dark gas halo's around molecular clouds.

Predicting Intra-Urban Population Densities in Africa using SAR and Optical Remote Sensing Data

NASA Astrophysics Data System (ADS)

Linard, C.; Steele, J.; Forget, Y.; Lopez, J.; Shimoni, M.

2017-12-01

The population of Africa is predicted to double over the next 40 years, driving profound social, environmental and epidemiological changes within rapidly growing cities. Estimations of within-city variations in population density must be improved in order to take urban heterogeneities into account and better help urban research and decision making, especially for vulnerability and health assessments. Satellite remote sensing offers an effective solution for mapping settlements and monitoring urbanization at different spatial and temporal scales. In Africa, the urban landscape is covered by slums and small houses, where the heterogeneity is high and where the man-made materials are natural. Innovative methods that combine optical and SAR data are therefore necessary for improving settlement mapping and population density predictions. An automatic method was developed to estimate built-up densities using recent and archived optical and SAR data and a multi-temporal database of built-up densities was produced for 48 African cities. Geo-statistical methods were then used to study the relationships between census-derived population densities and satellite-derived built-up attributes. Best predictors were combined in a Random Forest framework in order to predict intra-urban variations in population density in any large African city. Models show significant improvement of our spatial understanding of urbanization and urban population distribution in Africa in comparison to the state of the art.

Evaluation of groundwater potential using geospatial techniques

NASA Astrophysics Data System (ADS)

Hussein, Abdul-Aziz; Govindu, Vanum; Nigusse, Amare Gebre Medhin

2017-09-01

The issue of unsustainable groundwater utilization is becoming increasingly an evident problem and the key concern for many developing countries. One of the problems is the absence of updated spatial information on the quantity and distribution of groundwater resource. Like the other developing countries, groundwater evaluation in Ethiopia has been usually conducted using field survey which is not feasible in terms of time and resource. This study was conducted in Northern Ethiopia, Wollo Zone, in Gerardo River Catchment district to spatially delineate the groundwater potential areas using geospatial and MCDA tools. To do so, eight major biophysical and environmental factors like geomorphology, lithology, slope, rainfall, land use land cover (LULC), soil, lineament density and drainage density were considered. The sources of these data were satellite image, digital elevation model (DEM), existing thematic maps and metrological station data. Landsat image was used in ERDAS Imagine to drive the LULC of the area, while the geomorphology, soil, and lithology of the area were identified and classified through field survey and digitized from existing maps using the ArcGIS software. The slope, lineament and drainage density of the area were derived from DEM using spatial analysis tools. The rainfall surface map was generated using the thissen polygon interpolation. Finally, after all these thematic maps were organized, weighted value determination for each factor and its field value was computed using IDRSI software. At last, all the factors were integrated together and computed the model using the weighted overlay so that potential groundwater areas were mapped. The findings depicted that the most potential groundwater areas are found in the central and eastern parts of the study area, while the northern and western parts of the Gerado River Catchment have poor potential of groundwater availability. This is mainly due to the cumulative effect of steep topographic and high drainage density. At last, once the potential groundwater areas were identified, cross validation of the resultant model was carefully carried out using existing data of dung wells and bore holes. The point data of dung wells and bore holes were overlaid on groundwater potential suitability map and coincide with the expected values. Generally, from this study, it can be concluded that RS and GIS with the help of MCDA are important tools in monitoring and evaluation of groundwater resource potential areas.

The rubber plantation environment and Lassa fever epidemics in Liberia, 2008-2012: a spatial regression.

PubMed

Olugasa, Babasola O; Dogba, John B; Ogunro, Bamidele; Odigie, Eugene A; Nykoi, Jomah; Ojo, Johnson F; Taiwo, Olalekan; Kamara, Abraham; Mulbah, Charles K; Fasunla, Ayotunde J

2014-10-01

As Lassa fever continues to be a public health challenge in West Africa, it is critical to produce good maps of its risk pattern for use in active surveillance and control intervention. We identified eight spatial features related to the rubber plantation environment and used them as explanatory variables for Lassa fever (LF) outbreaks on the Uniroyal Liberian Agricultural Company (LAC) rubber plantation environment in Grand Bassa County, Liberia. We computed classical and spatial lag regression models on all spatial features, including proximity of residential camp to rubber tree-edge, main road in the plantation, LAC hospital, rice farmland, household refuse dump, human population density, post-harvest storage density of rice and density of rodent deterrent on rice storage. We found significant (p=0.0024) spatial autocorrelation between LF cases and the spatial features we have considered. We concluded that the rubber plantation environment influenced Mastomys species' breeding and transmission of Lassa virus along spatial scale to humans. The risk factors identified in this study offered a baseline for more effective surveillance and control of LF in the post-civil conflict Liberia. Copyright © 2014 Elsevier Ltd. All rights reserved.

Mapping the Physical and Chemical Conditions of the Ring Nebula

NASA Astrophysics Data System (ADS)

Leal-Ferreira, Marcelo L.; Aleman, Isabel; Gaughan, Andrea; Ladjal, Djazia; Ueta, Toshiya; Kerber, Samuel; Conn, Blair; Gardiner, Rhiannon; Tielens, Alexander G. G. M.

2017-10-01

We observed the Planetary Nebula NGC 6720 with the Gemini Telescope and the Gemini Multi-Object Spectrographs. We obtained spatial maps of 36 emission-lines in the wavelength range between 3600 Å and 9400 Å. We derived maps of c(Hβ), electronic densities, electronic temperatures, ionic and elemental abundances, and Ionization Correction Factors (ICFs) in the source and investigated the mass-loss history of the progenitor. The elemental abundance results indicate the need for ICFs based on three-dimensional photoionization models.

Experimental determination of the correlation properties of plasma turbulence using 2D BES systems

NASA Astrophysics Data System (ADS)

Fox, M. F. J.; Field, A. R.; van Wyk, F.; Ghim, Y.-c.; Schekochihin, A. A.; the MAST Team

2017-04-01

A procedure is presented to map from the spatial correlation parameters of a turbulent density field (the radial and binormal correlation lengths and wavenumbers, and the fluctuation amplitude) to correlation parameters that would be measured by a beam emission spectroscopy (BES) diagnostic. The inverse mapping is also derived, which results in resolution criteria for recovering correct correlation parameters, depending on the spatial response of the instrument quantified in terms of point-spread functions (PSFs). Thus, a procedure is presented that allows for a systematic comparison between theoretical predictions and experimental observations. This procedure is illustrated using the Mega-Ampere Spherical Tokamak BES system and the validity of the underlying assumptions is tested on fluctuating density fields generated by direct numerical simulations using the gyrokinetic code GS2. The measurement of the correlation time, by means of the cross-correlation time-delay method, is also investigated and is shown to be sensitive to the fluctuating radial component of velocity, as well as to small variations in the spatial properties of the PSFs.

Measuring high-density built environment for public health research: Uncertainty with respect to data, indicator design and spatial scale.

PubMed

Sun, Guibo; Webster, Chris; Ni, Michael Y; Zhang, Xiaohu

2018-05-07

Uncertainty with respect to built environment (BE) data collection, measure conceptualization and spatial scales is evident in urban health research, but most findings are from relatively lowdensity contexts. We selected Hong Kong, an iconic high-density city, as the study area as limited research has been conducted on uncertainty in such areas. We used geocoded home addresses (n=5732) from a large population-based cohort in Hong Kong to extract BE measures for the participants' place of residence based on an internationally recognized BE framework. Variability of the measures was mapped and Spearman's rank correlation calculated to assess how well the relationships among indicators are preserved across variables and spatial scales. We found extreme variations and uncertainties for the 180 measures collected using comprehensive data and advanced geographic information systems modelling techniques. We highlight the implications of methodological selection and spatial scales of the measures. The results suggest that more robust information regarding urban health research in high-density city would emerge if greater consideration were given to BE data, design methods and spatial scales of the BE measures.

Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps.

PubMed

Mitchard, Edward Ta; Saatchi, Sassan S; Baccini, Alessandro; Asner, Gregory P; Goetz, Scott J; Harris, Nancy L; Brown, Sandra

2013-10-26

Mapping the aboveground biomass of tropical forests is essential both for implementing conservation policy and reducing uncertainties in the global carbon cycle. Two medium resolution (500 m - 1000 m) pantropical maps of vegetation biomass have been recently published, and have been widely used by sub-national and national-level activities in relation to Reducing Emissions from Deforestation and forest Degradation (REDD+). Both maps use similar input data layers, and are driven by the same spaceborne LiDAR dataset providing systematic forest height and canopy structure estimates, but use different ground datasets for calibration and different spatial modelling methodologies. Here, we compare these two maps to each other, to the FAO's Forest Resource Assessment (FRA) 2010 country-level data, and to a high resolution (100 m) biomass map generated for a portion of the Colombian Amazon. We find substantial differences between the two maps, in particular in central Amazonia, the Congo basin, the south of Papua New Guinea, the Miombo woodlands of Africa, and the dry forests and savannas of South America. There is little consistency in the direction of the difference. However, when the maps are aggregated to the country or biome scale there is greater agreement, with differences cancelling out to a certain extent. When comparing country level biomass stocks, the two maps agree with each other to a much greater extent than to the FRA 2010 estimates. In the Colombian Amazon, both pantropical maps estimate higher biomass than the independent high resolution map, but show a similar spatial distribution of this biomass. Biomass mapping has progressed enormously over the past decade, to the stage where we can produce globally consistent maps of aboveground biomass. We show that there are still large uncertainties in these maps, in particular in areas with little field data. However, when used at a regional scale, different maps appear to converge, suggesting we can provide reasonable stock estimates when aggregated over large regions. Therefore we believe the largest uncertainties for REDD+ activities relate to the spatial distribution of biomass and to the spatial pattern of forest cover change, rather than to total globally or nationally summed carbon density.

Use of spatial capture–recapture to estimate density of Andean bears in northern Ecuador

USGS Publications Warehouse

Molina, Santiago; Fuller, Angela K.; Morin, Dana J.; Royle, J. Andrew

2017-01-01

The Andean bear (Tremarctos ornatus) is the only extant species of bear in South America and is considered threatened across its range and endangered in Ecuador. Habitat loss and fragmentation is considered a critical threat to the species, and there is a lack of knowledge regarding its distribution and abundance. The species is thought to occur at low densities, making field studies designed to estimate abundance or density challenging. We conducted a pilot camera-trap study to estimate Andean bear density in a recently identified population of Andean bears northwest of Quito, Ecuador, during 2012. We compared 12 candidate spatial capture–recapture models including covariates on encounter probability and density and estimated a density of 7.45 bears/100 km2 within the region. In addition, we estimated that approximately 40 bears used a recently named Andean bear corridor established by the Secretary of Environment, and we produced a density map for this area. Use of a rub-post with vanilla scent attractant allowed us to capture numerous photographs for each event, improving our ability to identify individual bears by unique facial markings. This study provides the first empirically derived density estimate for Andean bears in Ecuador and should provide direction for future landscape-scale studies interested in conservation initiatives requiring spatially explicit estimates of density.

Use of micro-photoluminescence as a contactless measure of the 2D electron density in a GaAs quantum well

NASA Astrophysics Data System (ADS)

Kamburov, D.; Baldwin, K. W.; West, K. W.; Lyon, S.; Pfeiffer, L. N.; Pinczuk, A.

2017-06-01

We compare micro-photoluminescence (μPL) as a measure of the electron density in a clean, two-dimensional (2D) system confined in a GaAs quantum well (QW) to the standard magneto-transport technique. Our study explores the PL shape evolution across a number of molecular beam epitaxy-grown samples with different QW widths and 2D electron densities and notes its correspondence with the density obtained in magneto-transport measurements on these samples. We also measure the 2D density in a top-gated quantum well sample using both PL and transport and find that the two techniques agree to within a few percent over a wide range of gate voltages. We find that the PL measurements are sensitive to gate-induced 2D density changes on the order of 109 electrons/cm2. The spatial resolution of the PL density measurement in our experiments is 40 μm, which is already substantially better than the millimeter-scale resolution now possible in spatial density mapping using magneto-transport. Our results establish that μPL can be used as a reliable high spatial resolution technique for future contactless measurements of density variations in a 2D electron system.

Building a time series of water vapour maps: A first step towards assimilation of Interferometric SAR data in forecasting models

NASA Astrophysics Data System (ADS)

Nico, Giovanni; Mateus, Pedro; Catalão, João.

2010-05-01

The knowledge of water vapor spatial distribution in the Earth's atmosphere at a given time is an important information for numerical forecasting. In fact this is the most varying atmospheric constituent both in space and in time. The water vapor is basically concentrated in the troposphere, the atmosphere layer where the most important phenomena related to weather occur. This layer is destabilized by radiative heating and vertical wind shear near the surfce. The accuracy of quantitative precipitation forecasting over a given region strongly depends on the knowledge of the temporal and spatial variations in the water vapor spatial distribution. Currently, measurements based on ground-based and upper-air sounding networks furnish water vapor distribution only at a coarse scales. This could not be enough to capture variations of the local concentrations of water vapor. Spaceborne radiometer observations can observe atmospheric layers above 3 km due to absorption by water vapor and in any case maps of vater vapour density are too coarse. Availability of GPS measurements of on a routine basis is improving numerical forecasting. However, the density of meuserements which can be obtained by a GPS network is too low to capture spatial variations of local concentrations of water vapor. Synthetic Aperture Radar (SAR) interferometry provides maps of temporal variations of the vertically integrated water vapor density with a horizontal resolution as fine as 10-20 m depending on the radar wavelength and over a swath typically 100 km wide. In the past, the availability of the tandem ERS-1/2 interferometric SAR data allowed to get maps of the vertically-integrated with a temporal baseline of 1 day. In those maps it was possible to recognize signature of a precipitating cumulonimbus cloud, the effects of a cold front and the phenomenon of horizontal convective rolls. Current interferometric spaceborne missions use SAR sensors working at different frequency bands: L (ALOS-PALSAR), C (ENVISAT-ASAR, RADARSAT) and X (TerraSAR, Cosmo-Sky-Med) and with a repetition cycle ranging from 11 (TerraSAR-X) to 35 days (ENVISAT-ASAR). From each SAR sensor, it can be obtained a map of the temporal changes of the IPW occurred between the two subsequent acquisitions by interferometrically processing the SAR data. The accuracy of these maps depends on the radar wavelength and on spatial filtering. A procedure to properly merge all these maps could give information about the temporal evolution of the IPW spatial distribution with a sampling period shorter than the revisiting times of each of the SAR sensors. The main difficulty of this operation is related to the fact that the integration of temporal changes of IPW is not direct when maps are obtained by different SAR sensors. The aim of this work is to describe a methodologiy to merge IPW maps obtained by the different SAR sensor based on the availbality of GPS time series measuring the IPW over the same area. The Lisbon region, Portugal, was chosen as a study area. This region is monitored by a network of 12 GPS permanent stations covering an area of about squared kilometers. A set of SAR interferograms were processed using data acquired by ENVISAT-ASAR and TerraSAR-X mission over the Lisbon region during the period from 2009 to 2010. A time series with GPS measurement of IPW was processed to cover the time interval between the first and last SAR acquisition. This time series is then used to integrate all maps of temporal changes of IPW obtained by the different interferometric SAR couples. This results in a time series giving with the information about the spatial distribution of the IPW.

Mapping Wintering Waterfowl Distributions Using Weather Surveillance Radar

PubMed Central

Buler, Jeffrey J.; Randall, Lori A.; Fleskes, Joseph P.; Barrow, Wylie C.; Bogart, Tianna; Kluver, Daria

2012-01-01

The current network of weather surveillance radars within the United States readily detects flying birds and has proven to be a useful remote-sensing tool for ornithological study. Radar reflectivity measures serve as an index to bird density and have been used to quantitatively map landbird distributions during migratory stopover by sampling birds aloft at the onset of nocturnal migratory flights. Our objective was to further develop and validate a similar approach for mapping wintering waterfowl distributions using weather surveillance radar observations at the onset of evening flights. We evaluated data from the Sacramento, CA radar (KDAX) during winters 1998–1999 and 1999–2000. We determined an optimal sampling time by evaluating the accuracy and precision of radar observations at different times during the onset of evening flight relative to observed diurnal distributions of radio-marked birds on the ground. The mean time of evening flight initiation occurred 23 min after sunset with the strongest correlations between reflectivity and waterfowl density on the ground occurring almost immediately after flight initiation. Radar measures became more spatially homogeneous as evening flight progressed because birds dispersed from their departure locations. Radars effectively detected birds to a mean maximum range of 83 km during the first 20 min of evening flight. Using a sun elevation angle of −5° (28 min after sunset) as our optimal sampling time, we validated our approach using KDAX data and additional data from the Beale Air Force Base, CA (KBBX) radar during winter 1998–1999. Bias-adjusted radar reflectivity of waterfowl aloft was positively related to the observed diurnal density of radio-marked waterfowl locations on the ground. Thus, weather radars provide accurate measures of relative wintering waterfowl density that can be used to comprehensively map their distributions over large spatial extents. PMID:22911816

Mapping wintering waterfowl distributions using weather surveillance radar.

PubMed

Buler, Jeffrey J; Randall, Lori A; Fleskes, Joseph P; Barrow, Wylie C; Bogart, Tianna; Kluver, Daria

2012-01-01

The current network of weather surveillance radars within the United States readily detects flying birds and has proven to be a useful remote-sensing tool for ornithological study. Radar reflectivity measures serve as an index to bird density and have been used to quantitatively map landbird distributions during migratory stopover by sampling birds aloft at the onset of nocturnal migratory flights. Our objective was to further develop and validate a similar approach for mapping wintering waterfowl distributions using weather surveillance radar observations at the onset of evening flights. We evaluated data from the Sacramento, CA radar (KDAX) during winters 1998-1999 and 1999-2000. We determined an optimal sampling time by evaluating the accuracy and precision of radar observations at different times during the onset of evening flight relative to observed diurnal distributions of radio-marked birds on the ground. The mean time of evening flight initiation occurred 23 min after sunset with the strongest correlations between reflectivity and waterfowl density on the ground occurring almost immediately after flight initiation. Radar measures became more spatially homogeneous as evening flight progressed because birds dispersed from their departure locations. Radars effectively detected birds to a mean maximum range of 83 km during the first 20 min of evening flight. Using a sun elevation angle of -5° (28 min after sunset) as our optimal sampling time, we validated our approach using KDAX data and additional data from the Beale Air Force Base, CA (KBBX) radar during winter 1998-1999. Bias-adjusted radar reflectivity of waterfowl aloft was positively related to the observed diurnal density of radio-marked waterfowl locations on the ground. Thus, weather radars provide accurate measures of relative wintering waterfowl density that can be used to comprehensively map their distributions over large spatial extents.

Integrating Entropy-Based Naïve Bayes and GIS for Spatial Evaluation of Flood Hazard.

PubMed

Liu, Rui; Chen, Yun; Wu, Jianping; Gao, Lei; Barrett, Damian; Xu, Tingbao; Li, Xiaojuan; Li, Linyi; Huang, Chang; Yu, Jia

2017-04-01

Regional flood risk caused by intensive rainfall under extreme climate conditions has increasingly attracted global attention. Mapping and evaluation of flood hazard are vital parts in flood risk assessment. This study develops an integrated framework for estimating spatial likelihood of flood hazard by coupling weighted naïve Bayes (WNB), geographic information system, and remote sensing. The north part of Fitzroy River Basin in Queensland, Australia, was selected as a case study site. The environmental indices, including extreme rainfall, evapotranspiration, net-water index, soil water retention, elevation, slope, drainage proximity, and density, were generated from spatial data representing climate, soil, vegetation, hydrology, and topography. These indices were weighted using the statistics-based entropy method. The weighted indices were input into the WNB-based model to delineate a regional flood risk map that indicates the likelihood of flood occurrence. The resultant map was validated by the maximum inundation extent extracted from moderate resolution imaging spectroradiometer (MODIS) imagery. The evaluation results, including mapping and evaluation of the distribution of flood hazard, are helpful in guiding flood inundation disaster responses for the region. The novel approach presented consists of weighted grid data, image-based sampling and validation, cell-by-cell probability inferring and spatial mapping. It is superior to an existing spatial naive Bayes (NB) method for regional flood hazard assessment. It can also be extended to other likelihood-related environmental hazard studies. © 2016 Society for Risk Analysis.

Communicating and Evaluating the Causes of Seismicity in Oklahoma Using ArcGIS Online Story Map Web Applications

NASA Astrophysics Data System (ADS)

Justman, D.; Rose, K.; Bauer, J. R.; Miller, R., III; Vasylkivska, V.; Romeo, L.

2016-12-01

ArcGIS Online story maps allows users to communicate complex topics with geospatially enabled stories. This story map web application entitled "Evaluating the Mysteries of Seismicity in Oklahoma" has been employed as part of a broader research effort investigating the relationships between spatiotemporal systems and seismicity to understand the recent increase in seismicity by reviewing literature, exploring, and performing analyses on key datasets. It offers information about the unprecedented increase in seismic events since 2008, earthquake history, the risk to the population, physical mechanisms behind earthquakes, natural and anthropogenic earthquake factors, and individual & cumulative spatial extents of these factors. The cumulative spatial extents for natural, anthropogenic, and all combined earthquake factors were determined using the Cumulative Spatial Impact Layers (CSILs) tool developed at the National Energy Technology Laboratory (NETL). Results show positive correlations between the average number of influences (datasets related to individual factors) and the number of earthquakes for every 100 square mile grid cell in Oklahoma, along with interesting spatial correlations for the individual & cumulative spatial extents of these factors when overlaid with earthquake density and a hotspot analysis for earthquake magnitude from 2010 to 2015.

The Flint Food Store Survey: combining spatial analysis with a modified Nutrition Environment Measures Survey in Stores (NEMS-S) to measure the community and consumer nutrition environments.

PubMed

Shaver, Erika R; Sadler, Richard C; Hill, Alex B; Bell, Kendall; Ray, Myah; Choy-Shin, Jennifer; Lerner, Joy; Soldner, Teresa; Jones, Andrew D

2018-06-01

The goal of the present study was to use a methodology that accurately and reliably describes the availability, price and quality of healthy foods at both the store and community levels using the Nutrition Environment Measures Survey in Stores (NEMS-S), to propose a spatial methodology for integrating these store and community data into measures for defining objective food access. Two hundred and sixty-five retail food stores in and within 2 miles (3·2 km) of Flint, Michigan, USA, were mapped using ArcGIS mapping software. A survey based on the validated NEMS-S was conducted at each retail food store. Scores were assigned to each store based on a modified version of the NEMS-S scoring system and linked to the mapped locations of stores. Neighbourhood characteristics (race and socio-economic distress) were appended to each store. Finally, spatial and kernel density analyses were run on the mapped store scores to obtain healthy food density metrics. Regression analyses revealed that neighbourhoods with higher socio-economic distress had significantly lower dairy sub-scores compared with their lower-distress counterparts (β coefficient=-1·3; P=0·04). Additionally, supermarkets were present only in neighbourhoods with <60 % African-American population and low socio-economic distress. Two areas in Flint had an overall NEMS-S score of 0. By identifying areas with poor access to healthy foods via a validated metric, this research can be used help local government and organizations target interventions to high-need areas. Furthermore, the methodology used for the survey and the mapping exercise can be replicated in other cities to provide comparable results.

Assessing spatial inequalities in accessing community pharmacies: a mixed geographically weighted approach.

PubMed

Domnich, Alexander; Arata, Lucia; Amicizia, Daniela; Signori, Alessio; Gasparini, Roberto; Panatto, Donatella

2016-11-16

Geographical accessibility is an important determinant for the utilisation of community pharmacies. The present study explored patterns of spatial accessibility with respect to pharmacies in Liguria, Italy, a region with particular geographical and demographic features. Municipal density of pharmacies was proxied as the number of pharmacies per capita and per km2, and spatial autocorrelation analysis was performed to identify spatial clusters. Both non-spatial and spatial models were constructed to predict the study outcome. Spatial autocorrelation analysis showed a highly significant clustered pattern in the density of pharmacies per capita (I=0.082) and per km2 (I=0.295). Potentially under-supplied areas were mostly located in the mountainous hinterland. Ordinary least-squares (OLS) regressions established a significant positive relationship between the density of pharmacies and income among municipalities located at high altitudes, while no such association was observed in lower-lying areas. However, residuals of the OLS models were spatially auto-correlated. The best-fitting mixed geographically weighted regression (GWR) models outperformed the corresponding OLS models. Pharmacies per capita were best predicted by two local predictors (altitude and proportion of immigrants) and two global ones (proportion of elderly residents and income), while the local terms population, mean altitude and rural status and the global term income functioned as independent variables predicting pharmacies per km2. The density of pharmacies in Liguria was found to be associated with both socio-economic and landscape factors. Mapping of mixed GWR results would be helpful to policy-makers.

Multiscale Reconstruction for Magnetic Resonance Fingerprinting

PubMed Central

Pierre, Eric Y.; Ma, Dan; Chen, Yong; Badve, Chaitra; Griswold, Mark A.

2015-01-01

Purpose To reduce acquisition time needed to obtain reliable parametric maps with Magnetic Resonance Fingerprinting. Methods An iterative-denoising algorithm is initialized by reconstructing the MRF image series at low image resolution. For subsequent iterations, the method enforces pixel-wise fidelity to the best-matching dictionary template then enforces fidelity to the acquired data at slightly higher spatial resolution. After convergence, parametric maps with desirable spatial resolution are obtained through template matching of the final image series. The proposed method was evaluated on phantom and in-vivo data using the highly-undersampled, variable-density spiral trajectory and compared with the original MRF method. The benefits of additional sparsity constraints were also evaluated. When available, gold standard parameter maps were used to quantify the performance of each method. Results The proposed approach allowed convergence to accurate parametric maps with as few as 300 time points of acquisition, as compared to 1000 in the original MRF work. Simultaneous quantification of T1, T2, proton density (PD) and B0 field variations in the brain was achieved in vivo for a 256×256 matrix for a total acquisition time of 10.2s, representing a 3-fold reduction in acquisition time. Conclusions The proposed iterative multiscale reconstruction reliably increases MRF acquisition speed and accuracy. PMID:26132462

An evaluation of potential sampling locations in a reservoir with emphasis on conserved spatial correlation structure.

PubMed

Yenilmez, Firdes; Düzgün, Sebnem; Aksoy, Aysegül

2015-01-01

In this study, kernel density estimation (KDE) was coupled with ordinary two-dimensional kriging (OK) to reduce the number of sampling locations in measurement and kriging of dissolved oxygen (DO) concentrations in Porsuk Dam Reservoir (PDR). Conservation of the spatial correlation structure in the DO distribution was a target. KDE was used as a tool to aid in identification of the sampling locations that would be removed from the sampling network in order to decrease the total number of samples. Accordingly, several networks were generated in which sampling locations were reduced from 65 to 10 in increments of 4 or 5 points at a time based on kernel density maps. DO variograms were constructed, and DO values in PDR were kriged. Performance of the networks in DO estimations were evaluated through various error metrics, standard error maps (SEM), and whether the spatial correlation structure was conserved or not. Results indicated that smaller number of sampling points resulted in loss of information in regard to spatial correlation structure in DO. The minimum representative sampling points for PDR was 35. Efficacy of the sampling location selection method was tested against the networks generated by experts. It was shown that the evaluation approach proposed in this study provided a better sampling network design in which the spatial correlation structure of DO was sustained for kriging.

Spatial accuracy of a simplified disaggregation method for traffic emissions applied in seven mid-sized Chilean cities

NASA Astrophysics Data System (ADS)

Ossés de Eicker, Margarita; Zah, Rainer; Triviño, Rubén; Hurni, Hans

The spatial accuracy of top-down traffic emission inventory maps obtained with a simplified disaggregation method based on street density was assessed in seven mid-sized Chilean cities. Each top-down emission inventory map was compared against a reference, namely a more accurate bottom-up emission inventory map from the same study area. The comparison was carried out using a combination of numerical indicators and visual interpretation. Statistically significant differences were found between the seven cities with regard to the spatial accuracy of their top-down emission inventory maps. In compact cities with a simple street network and a single center, a good accuracy of the spatial distribution of emissions was achieved with correlation values>0.8 with respect to the bottom-up emission inventory of reference. In contrast, the simplified disaggregation method is not suitable for complex cities consisting of interconnected nuclei, resulting in correlation values<0.5. Although top-down disaggregation of traffic emissions generally exhibits low accuracy, the accuracy is significantly higher in compact cities and might be further improved by applying a correction factor for the city center. Therefore, the method can be used by local environmental authorities in cities with limited resources and with little knowledge on the pollution situation to get an overview on the spatial distribution of the emissions generated by traffic activities.

Coherent visualization of spatial data adapted to roles, tasks, and hardware

NASA Astrophysics Data System (ADS)

Wagner, Boris; Peinsipp-Byma, Elisabeth

2012-06-01

Modern crisis management requires that users with different roles and computer environments have to deal with a high volume of various data from different sources. For this purpose, Fraunhofer IOSB has developed a geographic information system (GIS) which supports the user depending on available data and the task he has to solve. The system provides merging and visualization of spatial data from various civilian and military sources. It supports the most common spatial data standards (OGC, STANAG) as well as some proprietary interfaces, regardless if these are filebased or database-based. To set the visualization rules generic Styled Layer Descriptors (SLDs) are used, which are an Open Geospatial Consortium (OGC) standard. SLDs allow specifying which data are shown, when and how. The defined SLDs consider the users' roles and task requirements. In addition it is possible to use different displays and the visualization also adapts to the individual resolution of the display. Too high or low information density is avoided. Also, our system enables users with different roles to work together simultaneously using the same data base. Every user is provided with the appropriate and coherent spatial data depending on his current task. These so refined spatial data are served via the OGC services Web Map Service (WMS: server-side rendered raster maps), or the Web Map Tile Service - (WMTS: pre-rendered and cached raster maps).

Assessment of sand encroachment in Kuwait using GIS

NASA Astrophysics Data System (ADS)

Al-Helal, Anwar B.; Al-Awadhi, Jasem M.

2006-04-01

Assessment of sand encroachment in Kuwait using Geographical Information System (GIS) technology has been formulated as a Multi-Criteria Decision Making problem. The Delphi method and Analytical Hierarchy Process were adopted as evaluating techniques, in which experts’ judgments were analyzed for objectively estimating and weighting control factors. Seven triggering factors, depicted in the form of maps, were identified and ordered according to their priority. These factors are (1) wind energy; (2) surface sediment; (3) vegetation density; (4) land use; (5) drainage density; (6) topographic change and (7) vegetation type. The factor maps were digitized, converted to raster data and overlaid to determine their possible spatial relationships. Applying a susceptibility model, a map of sand encroachment susceptibility in Kuwait was developed. The map showed that the areas of very high and high sand encroachment susceptibility are located within the main corridor of sand pathway that coincides with the northwesterly dominant wind direction.

Connecting People to Place: Stories, Science, Deep Maps, and Geo-Quests for Place-Based Learning

NASA Astrophysics Data System (ADS)

Hagley, C. A.; Silbernagel, J.; Host, G.; Hart, D. A.; Axler, R.; Fortner, R. W.; Axler, M.; Smith, V.; Drewes, A.; Bartsch, W.; Danz, N.; Mathews, J.; Wagler, M.

2016-02-01

The St. Louis River Estuary project (stlouisriverestuary.org) is about connecting the stories with the science of this special place to enhance spatial awareness and stewardship of the estuary. The stories, or spatial narratives, are told through vignettes of local resource activities, framed by perspectives of local people. The spatial narratives, developed through interviews and research, target six key activities of the estuary. The science is based on stressor gradients research, incorporating factors such as population and road density, pollutant point source density, and land use. The stressor gradient developed based on these factors was used as a basis for sampling water quality and plant and macroinvertebrate communities, with the intent of quantifying relationships between land-based stressors and aquatic ecosystem indicators of condition. The stories and science are interwoven, located in place on a Deep Map, and played out in GeoQuests to illustrate the complexity and multiple perspectives within the estuary's social, economic and ecological systems. Students, decision-makers, and Lake Superior enthusiasts can engage more deeply in the complexity of the stories and science by challenging themselves with these GeoQuests played on mobile devices. We hope these place-based learning tools will be valuable in advancing spatial literacy and conversation around environmental sustainability in coastal communities.

Can Process Understanding Help Elucidate The Structure Of The Critical Zone? Comparing Process-Based Soil Formation Models With Digital Soil Mapping.

NASA Astrophysics Data System (ADS)

Vanwalleghem, T.; Román, A.; Peña, A.; Laguna, A.; Giráldez, J. V.

2017-12-01

There is a need for better understanding the processes influencing soil formation and the resulting distribution of soil properties in the critical zone. Soil properties can exhibit strong spatial variation, even at the small catchment scale. Especially soil carbon pools in semi-arid, mountainous areas are highly uncertain because bulk density and stoniness are very heterogeneous and rarely measured explicitly. In this study, we explore the spatial variability in key soil properties (soil carbon stocks, stoniness, bulk density and soil depth) as a function of processes shaping the critical zone (weathering, erosion, soil water fluxes and vegetation patterns). We also compare the potential of traditional digital soil mapping versus a mechanistic soil formation model (MILESD) for predicting these key soil properties. Soil core samples were collected from 67 locations at 6 depths. Total soil organic carbon stocks were 4.38 kg m-2. Solar radiation proved to be the key variable controlling soil carbon distribution. Stone content was mostly controlled by slope, indicating the importance of erosion. Spatial distribution of bulk density was found to be highly random. Finally, total carbon stocks were predicted using a random forest model whose main covariates were solar radiation and NDVI. The model predicts carbon stocks that are double as high on north versus south-facing slopes. However, validation showed that these covariates only explained 25% of the variation in the dataset. Apparently, present-day landscape and vegetation properties are not sufficient to fully explain variability in the soil carbon stocks in this complex terrain under natural vegetation. This is attributed to a high spatial variability in bulk density and stoniness, key variables controlling carbon stocks. Similar results were obtained with the mechanistic soil formation model MILESD, suggesting that more complex models might be needed to further explore this high spatial variability.

Spatial distribution of deaths due to Alzheimer's disease in the state of São Paulo, Brazil.

PubMed

Almeida, Milena Cristina da Silva; Gomes, Camila de Moraes Santos; Nascimento, Luiz Fernando Costa

2014-01-01

Alzheimer's disease is a common cause of dementia and identifying possible spatial patterns of mortality due to this disease may enable preventive actions. The objective of this study was to identify spatial distribution patterns of mortality due to Alzheimer's disease in the state of São Paulo. Ecological and exploratory study conducted in all municipalities in the state of São Paulo. Data on Alzheimer's disease mortality in the state of São Paulo between 2004 and 2009 were obtained from DATASUS (the Department of Informatics in the Brazilian Ministry of Health). Death rates per 100,000 inhabitants were then calculated and spatial analysis was performed by constructing a death rate map, global Moran index and local Moran index, which were used to obtain the Moran map. The kernel technique was also applied. The Terra View 4.0.0 software was used. 13,030 deaths due to Alzheimer were reported in the state of São Paulo (rate of 5.33 deaths/100,000 inhabitants). São José do Rio Preto, Ribeirão Preto, Bauru and Araçatuba had higher rates. The Moran index was I = 0.085 (P < 0.002). The Moran map identified 42 municipalities that merit intervention and the kernel estimator identified a high density of deaths in the northwestern region of the state. Higher densities of deaths due to Alzheimer were concentrated more to the north and northwest of the state of São Paulo. It was possible to identify municipalities that have priority for interventions to reduce the death rates due to this disease.

Plasma density irregularities and Total Electron Content gradients over Europe

NASA Astrophysics Data System (ADS)

Zakharenkova, I.; Kotulak, K.; Cherniak, I.; Krankowski, A.; Froń, A.

2017-12-01

Perturbations of the ionospheric plasma density are crucial from the scientific and application points of view, as they can severe affect radio signals used in the Global Navigation Satellite Systems (GNSS) and low frequency radio astronomy. For several decades the ionospheric irregularities have been extensively studied by different techniques, including ground-based GNSS observations. Spatial distribution of ionospheric disturbances can be specified by horizontal gradients of the ionospheric density (total electron content, TEC). Another, widely used tool in irregularities monitoring is the rate of TEC index (ROTI). Recently, the Northern Hemisphere ROTI product has been implemented to the International GNSS Service (IGS) and available for community. In this study, we present climatology of the spatial TEC gradients occurred over European region at high to middle latitudes. We developed the TEC gradient maps based on the high-resolution (0.5 degree in latitude and longitude) regional TEC maps covering Europe. The obtained climatological characteristics of the spatial TEC gradients are superimposed and analyzed with the global and regional ROTI product in order to reveal development of highly intense plasma irregularities occurred at high and middle latitudes. During geomagnetic storm the complex of physical processes at auroal zone leads to development of intnse ionospheric irregularities and travelling ionospheric disturbances (TIDs). We presents results of the geomagnetic storm analysis including the 2013 and 2015 St. Patrick's Day geomagnetic storms.

The Heat Exposure Integrated Deprivation Index (HEIDI): A data-driven approach to quantifying neighborhood risk during extreme hot weather.

PubMed

Krstic, Nikolas; Yuchi, Weiran; Ho, Hung Chak; Walker, Blake B; Knudby, Anders J; Henderson, Sarah B

2017-12-01

Mortality attributable to extreme hot weather is a growing concern in many urban environments, and spatial heat vulnerability indexes are often used to identify areas at relatively higher and lower risk. Three indexes were developed for greater Vancouver, Canada using a pool of 20 potentially predictive variables categorized to reflect social vulnerability, population density, temperature exposure, and urban form. One variable was chosen from each category: an existing deprivation index, senior population density, apparent temperature, and road density, respectively. The three indexes were constructed from these variables using (1) unweighted, (2) weighted, and (3) data-driven Heat Exposure Integrated Deprivation Index (HEIDI) approaches. The performance of each index was assessed using mortality data from 1998-2014, and the maps were compared with respect to spatial patterns identified. The population-weighted spatial correlation between the three indexes ranged from 0.68-0.89. The HEIDI approach produced a graduated map of vulnerability, whereas the other approaches primarily identified areas of highest risk. All indexes performed best under extreme temperatures, but HEIDI was more useful at lower thresholds. Each of the indexes in isolation provides valuable information for public health protection, but combining the HEIDI approach with unweighted and weighted methods provides richer information about areas most vulnerable to heat. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Accounting for surface reflectance in the derivation of vertical column densities of NO2 from airborne imaging DOAS

NASA Astrophysics Data System (ADS)

Meier, Andreas Carlos; Schönhardt, Anja; Richter, Andreas; Bösch, Tim; Seyler, André; Constantin, Daniel Eduard; Shaiganfar, Reza; Merlaud, Alexis; Ruhtz, Thomas; Wagner, Thomas; van Roozendael, Michel; Burrows, John. P.

2016-04-01

Nitrogen oxides, NOx (NOx = NO + NO2) play a key role in tropospheric chemistry. In addition to their directly harmful effects on the respiratory system of living organisms, they influence the levels of tropospheric ozone and contribute to acid rain and eutrophication of ecosystems. As they are produced in combustion processes, they can serve as an indicator for anthropogenic air pollution. In the late summers of 2014 and 2015, two extensive measurement campaigns were conducted in Romania by several European research institutes, with financial support from ESA. The AROMAT / AROMAT-2 campaigns (Airborne ROmanian Measurements of Aerosols and Trace gases) were dedicated to measurements of air quality parameters utilizing newly developed instrumentation at state-of-the-art. The experiences gained will help to calibrate and validate the measurements taken by the upcoming Sentinel-S5p mission scheduled for launch in 2016. The IUP Bremen contributed to these campaigns with its airborne imaging DOAS (Differential Optical Absorption Spectroscopy) instrument AirMAP (Airborne imaging DOAS instrument for Measurements of Atmospheric Pollution). AirMAP allows retrieving spatial distributions of trace gas columns densities in a stripe below the aircraft. The measurements have a high spatial resolution of approximately 30 x 80 m2 (along x across track) at a typical flight altitude of 3000 m. Supported by the instrumental setup and the large swath, gapless maps of trace gas distributions above a large city, like Bucharest or Berlin, can be acquired within a time window of approximately two hours. These properties make AirMAP a valuable tool for the validation of trace gas measurements from space. DOAS retrievals yield the density of absorbers integrated along the light path of the measurement. The light path is altered with a changing surface reflectance, leading to enhanced / reduced slant column densities of NO2 depending on surface properties. This effect must be considered in the derivation of air mass factors used to convert the measurements into vertical columns. Due to the high-resolution measurements, no data product of surface reflectance with sufficient spatial resolution is available. Thus the surface reflectance is estimated from AirMAP's own spectra. In this work the results of the research flights will be presented. The study focuses on the validation of AirMAP's measurements by comparison to other ground-based platforms like (mobile) MAX-DOAS measurements. Conclusions will be drawn on the quality of the measurements, their applicability for satellite data validation and possible improvements for future measurements.

Theory of a Quantum Scanning Microscope for Cold Atoms

NASA Astrophysics Data System (ADS)

Yang, D.; Laflamme, C.; Vasilyev, D. V.; Baranov, M. A.; Zoller, P.

2018-03-01

We propose and analyze a scanning microscope to monitor "live" the quantum dynamics of cold atoms in a cavity QED setup. The microscope measures the atomic density with subwavelength resolution via dispersive couplings to a cavity and homodyne detection within the framework of continuous measurement theory. We analyze two modes of operation. First, for a fixed focal point the microscope records the wave packet dynamics of atoms with time resolution set by the cavity lifetime. Second, a spatial scan of the microscope acts to map out the spatial density of stationary quantum states. Remarkably, in the latter case, for a good cavity limit, the microscope becomes an effective quantum nondemolition device, such that the spatial distribution of motional eigenstates can be measured backaction free in single scans, as an emergent quantum nondemolition measurement.

Theory of a Quantum Scanning Microscope for Cold Atoms.

PubMed

Yang, D; Laflamme, C; Vasilyev, D V; Baranov, M A; Zoller, P

2018-03-30

We propose and analyze a scanning microscope to monitor "live" the quantum dynamics of cold atoms in a cavity QED setup. The microscope measures the atomic density with subwavelength resolution via dispersive couplings to a cavity and homodyne detection within the framework of continuous measurement theory. We analyze two modes of operation. First, for a fixed focal point the microscope records the wave packet dynamics of atoms with time resolution set by the cavity lifetime. Second, a spatial scan of the microscope acts to map out the spatial density of stationary quantum states. Remarkably, in the latter case, for a good cavity limit, the microscope becomes an effective quantum nondemolition device, such that the spatial distribution of motional eigenstates can be measured backaction free in single scans, as an emergent quantum nondemolition measurement.

Quantifying volcanic hazard at Campi Flegrei caldera (Italy) with uncertainty assessment: 2. Pyroclastic density current invasion maps

NASA Astrophysics Data System (ADS)

Neri, Augusto; Bevilacqua, Andrea; Esposti Ongaro, Tomaso; Isaia, Roberto; Aspinall, Willy P.; Bisson, Marina; Flandoli, Franco; Baxter, Peter J.; Bertagnini, Antonella; Iannuzzi, Enrico; Orsucci, Simone; Pistolesi, Marco; Rosi, Mauro; Vitale, Stefano

2015-04-01

Campi Flegrei (CF) is an example of an active caldera containing densely populated settlements at very high risk of pyroclastic density currents (PDCs). We present here an innovative method for assessing background spatial PDC hazard in a caldera setting with probabilistic invasion maps conditional on the occurrence of an explosive event. The method encompasses the probabilistic assessment of potential vent opening positions, derived in the companion paper, combined with inferences about the spatial density distribution of PDC invasion areas from a simplified flow model, informed by reconstruction of deposits from eruptions in the last 15 ka. The flow model describes the PDC kinematics and accounts for main effects of topography on flow propagation. Structured expert elicitation is used to incorporate certain sources of epistemic uncertainty, and a Monte Carlo approach is adopted to produce a set of probabilistic hazard maps for the whole CF area. Our findings show that, in case of eruption, almost the entire caldera is exposed to invasion with a mean probability of at least 5%, with peaks greater than 50% in some central areas. Some areas outside the caldera are also exposed to this danger, with mean probabilities of invasion of the order of 5-10%. Our analysis suggests that these probability estimates have location-specific uncertainties which can be substantial. The results prove to be robust with respect to alternative elicitation models and allow the influence on hazard mapping of different sources of uncertainty, and of theoretical and numerical assumptions, to be quantified.

Hydrologic controls on basin-scale distribution of benthic macroinvertebrates

NASA Astrophysics Data System (ADS)

Bertuzzo, E.; Ceola, S.; Singer, G. A.; Battin, T. J.; Montanari, A.; Rinaldo, A.

2013-12-01

The presentation deals with the role of streamflow variability on basin-scale distributions of benthic macroinvertebrates. Specifically, we present a probabilistic analysis of the impacts of the variability along the river network of relevant hydraulic variables on the density of benthic macroinvertebrate species. The relevance of this work is based on the implications of the predictability of macroinvertebrate patterns within a catchment on fluvial ecosystem health, being macroinvertebrates commonly used as sensitive indicators, and on the effects of anthropogenic activity. The analytical tools presented here outline a novel procedure of general nature aiming at a spatially-explicit quantitative assessment of how near-bed flow variability affects benthic macroinvertebrate abundance. Moving from the analytical characterization of the at-a-site probability distribution functions (pdfs) of streamflow and bottom shear stress, a spatial extension to a whole river network is performed aiming at the definition of spatial maps of streamflow and bottom shear stress. Then, bottom shear stress pdf, coupled with habitat suitability curves (e.g., empirical relations between species density and bottom shear stress) derived from field studies are used to produce maps of macroinvertebrate suitability to shear stress conditions. Thus, moving from measured hydrologic conditions, possible effects of river streamflow alterations on macroinvertebrate densities may be fairly assessed. We apply this framework to an Austrian river network, used as benchmark for the analysis, for which rainfall and streamflow time-series and river network hydraulic properties and macroinvertebrate density data are available. A comparison between observed vs "modeled" species' density in three locations along the examined river network is also presented. Although the proposed approach focuses on a single controlling factor, it shows important implications with water resources management and fluvial ecosystem protection.

Detection of an electron beam in a high density plasma via an electrostatic probe

NASA Astrophysics Data System (ADS)

Majeski, Stephen; Yoo, Jongsoo; Zweben, Stewart; Yamada, Masaaki; Ji, Hantao

2017-10-01

The perturbation in floating potential by an electron beam is detected by a 1D floating potential probe array to evaluate the use of an electron beam for magnetic field line mapping in the Magnetic Reconnection Experiment (MRX) plasma. The MRX plasma is relatively high density (1013 cm-3) and low temperature (5 eV). Beam electrons are emitted from a tungsten filament and are accelerated by a 200 V potential across the sheath. They stream along the magnetic field lines towards the probe array. The spatial electron beam density profile is assumed to be a Gaussian along the radial axis of MRX and the effective beam width is determined from the radial profile of the floating potential. The magnitude of the perturbation is in agreement with theoretical predictions and the location of the perturbation is also in agreement with field line mapping. In addition, no significant broadening of the electron beam is observed after propagation for tens of centimeters through the high density plasma. These results demonstrate that this method of field line mapping is, in principle, feasible in high density plasmas. This work is supported by the DOE Contract No. DE-AC0209CH11466.

Twenty-four-micrometer-pitch microelectrode array with 6912-channel readout at 12 kHz via highly scalable implementation for high-spatial-resolution mapping of action potentials.

PubMed

Ogi, Jun; Kato, Yuri; Matoba, Yoshihisa; Yamane, Chigusa; Nagahata, Kazunori; Nakashima, Yusaku; Kishimoto, Takuya; Hashimoto, Shigeki; Maari, Koichi; Oike, Yusuke; Ezaki, Takayuki

2017-12-19

A 24-μm-pitch microelectrode array (MEA) with 6912 readout channels at 12 kHz and 23.2-μV rms random noise is presented. The aim is to reduce noise in a "highly scalable" MEA with a complementary metal-oxide-semiconductor integration circuit (CMOS-MEA), in which a large number of readout channels and a high electrode density can be expected. Despite the small dimension and the simplicity of the in-pixel circuit for the high electrode-density and the relatively large number of readout channels of the prototype CMOS-MEA chip developed in this work, the noise within the chip is successfully reduced to less than half that reported in a previous work, for a device with similar in-pixel circuit simplicity and a large number of readout channels. Further, the action potential was clearly observed on cardiomyocytes using the CMOS-MEA. These results indicate the high-scalability of the CMOS-MEA. The highly scalable CMOS-MEA provides high-spatial-resolution mapping of cell action potentials, and the mapping can aid understanding of complex activities in cells, including neuron network activities.

Electric currents and coronal heating in NOAA active region 6952

NASA Technical Reports Server (NTRS)

Metcalf, T. R.; Canfield, R. C.; Hudson, H. S.; Mickey, D. L.; Wulser, J. -P.; Martens, P. C. H.; Tsuneta, S.

1994-01-01

We examine the spatial and temporal relationship between coronal structures observed with the soft X-ray telescope (SXT) on board the Yohkoh spacecraft and the vertical electric current density derived from photospheric vector magnetograms obtained using the Stokes Polarimeter at the Mees Solar Observatory. We focus on a single active region: AR 6952 which we observed on 7 days during 1991 December. For 11 independent maps of the vertical electric current density co-aligned with non-flaring X-ray images, we search for a morphological relationship between sites of high vertical current density in the photosphere and enhanced X-ray emission in the overlying corona. We find no compelling spatial or temporal correlation between the sites of vertical current and the bright X-ray structures in this active region.

Surface Snow Density of East Antarctica Derived from In-Situ Observations

NASA Astrophysics Data System (ADS)

Tian, Y.; Zhang, S.; Du, W.; Chen, J.; Xie, H.; Tong, X.; Li, R.

2018-04-01

Models based on physical principles or semi-empirical parameterizations have used to compute the firn density, which is essential for the study of surface processes in the Antarctic ice sheet. However, parameterization of surface snow density is often challenged by the description of detailed local characterization. In this study we propose to generate a surface density map for East Antarctica from all the filed observations that are available. Considering that the observations are non-uniformly distributed around East Antarctica, obtained by different methods, and temporally inhomogeneous, the field observations are used to establish an initial density map with a grid size of 30 × 30 km2 in which the observations are averaged at a temporal scale of five years. We then construct an observation matrix with its columns as the map grids and rows as the temporal scale. If a site has an unknown density value for a period, we will set it to 0 in the matrix. In order to construct the main spatial and temple information of surface snow density matrix we adopt Empirical Orthogonal Function (EOF) method to decompose the observation matrix and only take first several lower-order modes, because these modes already contain most information of the observation matrix. However, there are a lot of zeros in the matrix and we solve it by using matrix completion algorithm, and then we derive the time series of surface snow density at each observation site. Finally, we can obtain the surface snow density by multiplying the modes interpolated by kriging with the corresponding amplitude of the modes. Comparative analysis have done between our surface snow density map and model results. The above details will be introduced in the paper.

Modeling photo-bleaching kinetics to map local variations in rod rhodopsin density

NASA Astrophysics Data System (ADS)

Ehler, M.; Dobrosotskaya, J.; King, E. J.; Czaja, W.; Bonner, R. F.

2011-03-01

Localized rod photoreceptor and rhodopsin losses have been observed in post mortem histology both in normal aging and in age-related maculopathy. We propose to noninvasively map local rod rhodopsin density through analysis of the brightening of the underlying lipofuscin autofluorescence (LAF) in confocal scanning laser ophthalmoscopy (cSLO) imaging sequences starting in the dark adapted eye. The detected LAF increases as rhodopsin is bleached (time constant ~ 25sec) by the average retinal irradiance of the cSLO 488nm laser beam. We fit parameters of analytical expressions for the kinetics of rhodopsin bleaching that Lamb validated using electroretinogram recordings in human. By performing localized (~ 100μm) kinetic analysis, we create high resolution maps of the rhodopsin density. This new noninvasive imaging and analysis approach appears well-suited for measuring localized changes in the rod photoreceptors and correlating them at high spatial resolution with localized pathological changes of the retinal pigment epithelium (RPE) seen in steady-state LAF images.

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

Fertig, Fabian, E-mail: fabian.fertig@ise.fraunhofer.de; Greulich, Johannes; Rein, Stefan

We present a spatially resolved method to determine the short-circuit current density of crystalline silicon solar cells by means of lock-in thermography. The method utilizes the property of crystalline silicon solar cells that the short-circuit current does not differ significantly from the illuminated current under moderate reverse bias. Since lock-in thermography images locally dissipated power density, this information is exploited to extract values of spatially resolved current density under short-circuit conditions. In order to obtain an accurate result, one or two illuminated lock-in thermography images and one dark lock-in thermography image need to be recorded. The method can be simplifiedmore » in a way that only one image is required to generate a meaningful short-circuit current density map. The proposed method is theoretically motivated, and experimentally validated for monochromatic illumination in comparison to the reference method of light-beam induced current.« less

CRISM Multispectral and Hyperspectral Mapping Data - A Global Data Set for Hydrated Mineral Mapping

NASA Astrophysics Data System (ADS)

Seelos, F. P.; Hash, C. D.; Murchie, S. L.; Lim, H.

2017-12-01

The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) is a visible through short-wave infrared hyperspectral imaging spectrometer (VNIR S-detector: 364-1055 nm; IR L-detector: 1001-3936 nm; 6.55 nm sampling) that has been in operation on the Mars Reconnaissance Orbiter (MRO) since 2006. Over the course of the MRO mission, CRISM has acquired 290,000 individual mapping observation segments (mapping strips) with a variety of observing modes and data characteristics (VNIR/IR; 100/200 m/pxl; multi-/hyper-spectral band selection) over a wide range of observing conditions (atmospheric state, observation geometry, instrument state). CRISM mapping data coverage density varies primarily with latitude and secondarily due to seasonal and operational considerations. The aggregate global IR mapping data coverage currently stands at 85% ( 80% at the equator with 40% repeat sampling), which is sufficient spatial sampling density to support the assembly of empirically optimized radiometrically consistent mapping mosaic products. The CRISM project has defined a number of mapping mosaic data products (e.g. Multispectral Reduced Data Record (MRDR) map tiles) with varying degrees of observation-specific processing and correction applied prior to mosaic assembly. A commonality among the mosaic products is the presence of inter-observation radiometric discrepancies which are traceable to variable observation circumstances or associated atmospheric/photometric correction residuals. The empirical approach to radiometric reconciliation leverages inter-observation spatial overlaps and proximal relationships to construct a graph that encodes the mosaic structure and radiometric discrepancies. The graph theory abstraction allows the underling structure of the msaic to be evaluated and the corresponding optimization problem configured so it is well-posed. Linear and non-linear least squares optimization is then employed to derive a set of observation- and wavelength- specific model parameters for a series of transform functions that minimize the total radiometric discrepancy across the mosaic. This empirical approach to CRISM data radiometric reconciliation and the utility of the resulting mapping data mosaic products for hydrated mineral mapping will be presented.

High-resolution measurements of the spatial and temporal evolution of megagauss magnetic fields created in intense short-pulse laser-plasma interactions

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

Chatterjee, Gourab, E-mail: gourab@tifr.res.in; Singh, Prashant Kumar; Adak, Amitava

A pump-probe polarimetric technique is demonstrated, which provides a complete, temporally and spatially resolved mapping of the megagauss magnetic fields generated in intense short-pulse laser-plasma interactions. A normally incident time-delayed probe pulse reflected from its critical surface undergoes a change in its ellipticity according to the magneto-optic Cotton-Mouton effect due to the azimuthal nature of the ambient self-generated megagauss magnetic fields. The temporal resolution of the magnetic field mapping is typically of the order of the pulsewidth, limited by the laser intensity contrast, whereas a spatial resolution of a few μm is achieved by this optical technique. High-harmonics of themore » probe can be employed to penetrate deeper into the plasma to even near-solid densities. The spatial and temporal evolution of the megagauss magnetic fields at the target front as well as at the target rear are presented. The μm-scale resolution of the magnetic field mapping provides valuable information on the filamentary instabilities at the target front, whereas probing the target rear mirrors the highly complex fast electron transport in intense laser-plasma interactions.« less

Multiscale reconstruction for MR fingerprinting.

PubMed

Pierre, Eric Y; Ma, Dan; Chen, Yong; Badve, Chaitra; Griswold, Mark A

2016-06-01

To reduce the acquisition time needed to obtain reliable parametric maps with Magnetic Resonance Fingerprinting. An iterative-denoising algorithm is initialized by reconstructing the MRF image series at low image resolution. For subsequent iterations, the method enforces pixel-wise fidelity to the best-matching dictionary template then enforces fidelity to the acquired data at slightly higher spatial resolution. After convergence, parametric maps with desirable spatial resolution are obtained through template matching of the final image series. The proposed method was evaluated on phantom and in vivo data using the highly undersampled, variable-density spiral trajectory and compared with the original MRF method. The benefits of additional sparsity constraints were also evaluated. When available, gold standard parameter maps were used to quantify the performance of each method. The proposed approach allowed convergence to accurate parametric maps with as few as 300 time points of acquisition, as compared to 1000 in the original MRF work. Simultaneous quantification of T1, T2, proton density (PD), and B0 field variations in the brain was achieved in vivo for a 256 × 256 matrix for a total acquisition time of 10.2 s, representing a three-fold reduction in acquisition time. The proposed iterative multiscale reconstruction reliably increases MRF acquisition speed and accuracy. Magn Reson Med 75:2481-2492, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Community context and sub-neighborhood scale detail to explain dengue, chikungunya and Zika patterns in Cali, Colombia.

PubMed

Krystosik, Amy R; Curtis, Andrew; Buritica, Paola; Ajayakumar, Jayakrishnan; Squires, Robert; Dávalos, Diana; Pacheco, Robinson; Bhatta, Madhav P; James, Mark A

2017-01-01

Cali, Colombia has experienced chikungunya and Zika outbreaks and hypoendemic dengue. Studies have explained Cali's dengue patterns but lack the sub-neighborhood-scale detail investigated here. Spatial-video geonarratives (SVG) with Ministry of Health officials and Community Health Workers were collected in hotspots, providing perspective on perceptions of why dengue, chikungunya and Zika hotspots exist, impediments to control, and social outcomes. Using spatial video and Google Street View, sub-neighborhood features possibly contributing to incidence were mapped to create risk surfaces, later compared with dengue, chikungunya and Zika case data. SVG captured insights in 24 neighborhoods. Trash and water risks in Calipso were mapped using SVG results. Perceived risk factors included proximity to standing water, canals, poverty, invasions, localized violence and military migration. These risks overlapped case density maps and identified areas that are suitable for transmission but are possibly underreporting to the surveillance system. Resulting risk maps with local context could be leveraged to increase vector-control efficiency- targeting key areas of environmental risk.

Spatial Variability of Sources and Mixing State of Atmospheric Particles in a Metropolitan Area.

PubMed

Ye, Qing; Gu, Peishi; Li, Hugh Z; Robinson, Ellis S; Lipsky, Eric; Kaltsonoudis, Christos; Lee, Alex K Y; Apte, Joshua S; Robinson, Allen L; Sullivan, Ryan C; Presto, Albert A; Donahue, Neil M

2018-05-30

Characterizing intracity variations of atmospheric particulate matter has mostly relied on fixed-site monitoring and quantifying variability in terms of different bulk aerosol species. In this study, we performed ground-based mobile measurements using a single-particle mass spectrometer to study spatial patterns of source-specific particles and the evolution of particle mixing state in 21 areas in the metropolitan area of Pittsburgh, PA. We selected sampling areas based on traffic density and restaurant density with each area ranging from 0.2 to 2 km 2 . Organics dominate particle composition in all of the areas we sampled while the sources of organics differ. The contribution of particles from traffic and restaurant cooking varies greatly on the neighborhood scale. We also investigate how primary and aged components in particles mix across the urban scale. Lastly we quantify and map the particle mixing state for all areas we sampled and discuss the overall pattern of mixing state evolution and its implications. We find that in the upwind and downwind of the urban areas, particles are more internally mixed while in the city center, particle mixing state shows large spatial heterogeneity that is mostly driven by emissions. This study is to our knowledge, the first study to perform fine spatial scale mapping of particle mixing state using ground-based mobile measurement and single-particle mass spectrometry.

Self-optimizing Monte Carlo method for nuclear well logging simulation

NASA Astrophysics Data System (ADS)

Liu, Lianyan

1997-09-01

In order to increase the efficiency of Monte Carlo simulation for nuclear well logging problems, a new method has been developed for variance reduction. With this method, an importance map is generated in the regular Monte Carlo calculation as a by-product, and the importance map is later used to conduct the splitting and Russian roulette for particle population control. By adopting a spatial mesh system, which is independent of physical geometrical configuration, the method allows superior user-friendliness. This new method is incorporated into the general purpose Monte Carlo code MCNP4A through a patch file. Two nuclear well logging problems, a neutron porosity tool and a gamma-ray lithology density tool are used to test the performance of this new method. The calculations are sped up over analog simulation by 120 and 2600 times, for the neutron porosity tool and for the gamma-ray lithology density log, respectively. The new method enjoys better performance by a factor of 4~6 times than that of MCNP's cell-based weight window, as per the converged figure-of-merits. An indirect comparison indicates that the new method also outperforms the AVATAR process for gamma-ray density tool problems. Even though it takes quite some time to generate a reasonable importance map from an analog run, a good initial map can create significant CPU time savings. This makes the method especially suitable for nuclear well logging problems, since one or several reference importance maps are usually available for a given tool. Study shows that the spatial mesh sizes should be chosen according to the mean-free-path. The overhead of the importance map generator is 6% and 14% for neutron and gamma-ray cases. The learning ability towards a correct importance map is also demonstrated. Although false-learning may happen, physical judgement can help diagnose with contributon maps. Calibration and analysis are performed for the neutron tool and the gamma-ray tool. Due to the fact that a very good initial importance map is always available after the first point has been calculated, high computing efficiency is maintained. The availability of contributon maps provides an easy way of understanding the logging measurement and analyzing for the depth of investigation.

A spatial approach for the epidemiology of antibiotic use and resistance in community-based studies: the emergence of urban clusters of Escherichia coli quinolone resistance in Sao Paulo, Brasil

PubMed Central

2011-01-01

Background Population antimicrobial use may influence resistance emergence. Resistance is an ecological phenomenon due to potential transmissibility. We investigated spatial and temporal patterns of ciprofloxacin (CIP) population consumption related to E. coli resistance emergence and dissemination in a major Brazilian city. A total of 4,372 urinary tract infection E. coli cases, with 723 CIP resistant, were identified in 2002 from two outpatient centres. Cases were address geocoded in a digital map. Raw CIP consumption data was transformed into usage density in DDDs by CIP selling points influence zones determination. A stochastic model coupled with a Geographical Information System was applied for relating resistance and usage density and for detecting city areas of high/low resistance risk. Results E. coli CIP resistant cluster emergence was detected and significantly related to usage density at a level of 5 to 9 CIP DDDs. There were clustered hot-spots and a significant global spatial variation in the residual resistance risk after allowing for usage density. Conclusions There were clustered hot-spots and a significant global spatial variation in the residual resistance risk after allowing for usage density. The usage density of 5-9 CIP DDDs per 1,000 inhabitants within the same influence zone was the resistance triggering level. This level led to E. coli resistance clustering, proving that individual resistance emergence and dissemination was affected by antimicrobial population consumption. PMID:21356088

Analysis of tsunami disaster map by Geographic Information System (GIS): Aceh Singkil-Indonesia

NASA Astrophysics Data System (ADS)

Farhan, A.; Akhyar, H.

2017-02-01

Tsunami risk map is used by stakeholder as a base to decide evacuation plan and evaluates from disaster. Aceh Singkil district of Aceh- Indonesia’s disaster maps have been developed and analyzed by using GIS tool. Overlay methods through algorithms are used to produce hazard map, vulnerability, capacity and finally created disaster risk map. Spatial maps are used topographic maps, administrative map, SRTM. The parameters are social, economic, physical environmental vulnerability, a level of exposed people, parameters of houses, public building, critical facilities, productive land, population density, sex ratio, poor ratio, disability ratio, age group ratio, the protected forest, natural forest, and mangrove forest. The results show high-risk tsunami disaster at nine villages; moderate levels are seventeen villages, and other villages are shown in the low level of tsunami risk disaster.

Capability of applying morphometric parameters of relief in river basins for geomorphological zoning of a territory

NASA Astrophysics Data System (ADS)

Ivanov, M. A.; Yermolaev, O. P.

2018-01-01

Information about morphometric characteristics of relief is necessary for researches devoted to geographic characteristics of territory, its zoning, assessment of erosion processes, geoecological condition and others. For the Volga Federal District for the first time a spatial database of geomorphometric parameters 1: 200 000 scale was created, based on a river basin approach. Watersheds are used as a spatial units created by semi-automated method using the terrain and hydrological modeling techniques implemented in the TAS GIS and WhiteBox GIS. As input data DEMs SRTM and Aster GDEM and hydrographic network vectorized from topographic maps were used. Using DEM highlighted above for each river basin, basic morphometric relief characteristics such as mean height, slope steepness, slope length, height range, river network density and factor LS were calculated. Basins belonging to the geomorphological regions and landscape zones was determined, according to the map of geomorphological zoning and landscape map. Analysis of variance revealed a statistically significant relationship between these characteristics and geomorphological regions and landscape zones. Consequently, spatial trends of changes of analyzed morphometric characteristics were revealed.

Identifying residential neighbourhood types from settlement points in a machine learning approach.

PubMed

Jochem, Warren C; Bird, Tomas J; Tatem, Andrew J

2018-05-01

Remote sensing techniques are now commonly applied to map and monitor urban land uses to measure growth and to assist with development and planning. Recent work in this area has highlighted the use of textures and other spatial features that can be measured in very high spatial resolution imagery. Far less attention has been given to using geospatial vector data (i.e. points, lines, polygons) to map land uses. This paper presents an approach to distinguish residential settlement types (regular vs. irregular) using an existing database of settlement points locating structures. Nine data features describing the density, distance, angles, and spacing of the settlement points are calculated at multiple spatial scales. These data are analysed alone and with five common remote sensing measures on elevation, slope, vegetation, and nighttime lights in a supervised machine learning approach to classify land use areas. The method was tested in seven provinces of Afghanistan (Balkh, Helmand, Herat, Kabul, Kandahar, Kunduz, Nangarhar). Overall accuracy ranged from 78% in Kandahar to 90% in Nangarhar. This research demonstrates the potential to accurately map land uses from even the simplest representation of structures.

Digital mining claim density map for federal lands in Nevada: 1996

USGS Publications Warehouse

Hyndman, Paul C.; Campbell, Harry W.

1999-01-01

This report describes a digital map generated by the U.S. Geological Survey (USGS) to provide digital spatial mining claim density information for federal lands in Nevada as of March 1997. Mining claim data is earth science information deemed to be relevant to the assessment of historic, current, and future ecological, economic, and social systems. There is no paper map included in this Open-File report. In accordance with the Federal Land Policy and Management Act of 1976 (FLPMA), all unpatented mining claims, mill, and tunnel sites must be recorded at the appropriate Bureau of Land Management (BLM) State office. BLM maintains a cumulative computer listing of mining claims in the MCRS database with locations given by meridian, township, range, and section. A mining claim is considered closed when the claim is relinquished or a formal BLM decision declaring the mining claim null and void has been issued and the appeal period has expired. All other mining claims filed with BLM are considered to be open and actively held. The digital map (figure 1.) with the mining claim density database available in this report are suitable for geographic information system (GIS)-based regional assessments at a scale of 1:100,000 or smaller.

Digital mining claim density map for federal lands in Utah: 1996

USGS Publications Warehouse

Hyndman, Paul C.; Campbell, Harry W.

1999-01-01

This report describes a digital map generated by the U.S. Geological Survey (USGS) to provide digital spatial mining claim density information for federal lands in Utah as of March 1997. Mining claim data is earth science information deemed to be relevant to the assessment of historic, current, and future ecological, economic, and social systems. There is no paper map included in this Open-File report. In accordance with the Federal Land Policy and Management Act of 1976 (FLPMA), all unpatented mining claims, mill, and tunnel sites must be recorded at the appropriate BLM State office. BLM maintains a cumulative computer listing of mining claims in the MCRS database with locations given by meridian, township, range, and section. A mining claim is considered closed when the claim is relinquished or a formal BLM decision declaring the mining claim null and void has been issued and the appeal period has expired. All other mining claims filed with BLM are considered to be open and actively held. The digital map (figure 1.) with the mining claim density database available in this report are suitable for geographic information system (GIS)-based regional assessments at a scale of 1:100,000 or smaller.

Digital mining claim density map for federal lands in Wyoming: 1996

USGS Publications Warehouse

Hyndman, Paul C.; Campbell, Harry W.

1999-01-01

This report describes a digital map generated by the U.S. Geological Survey (USGS) to provide digital spatial mining claim density information for federal lands in Wyoming as of March 1997. Mining claim data is earth science information deemed to be relevant to the assessment of historic, current, and future ecological, economic, and social systems. There is no paper map included in this Open-File report. In accordance with the Federal Land Policy and Management Act of 1976 (FLPMA), all unpatented mining claims, mill, and tunnel sites must be recorded at the appropriate BLM State office. BLM maintains a cumulative computer listing of mining claims in the Mining Claim Recordation System (MCRS) database with locations given by meridian, township, range, and section. A mining claim is considered closed when the claim is relinquished or a formal BLM decision declaring the mining claim null and void has been issued and the appeal period has expired. All other mining claims filed with BLM are considered to be open and actively held. The digital map (figure 1.) with the mining claim density database available in this report are suitable for geographic information system (GIS)-based regional assessments at a scale of 1:100,000 or smaller.

Digital mining claim density map for federal lands in Colorado: 1996

USGS Publications Warehouse

Hyndman, Paul C.; Campbell, Harry W.

1999-01-01

This report describes a digital map generated by the U.S. Geological Survey (USGS) to provide digital spatial mining claim density information for federal lands in Colorado as of March 1997. Mining claim data is earth science information deemed to be relevant to the assessment of historic, current, and future ecological, economic, and social systems. There is no paper map included in this Open-File report. In accordance with the Federal Land Policy and Management Act of 1976 (FLPMA), all unpatented mining claims, mill, and tunnel sites must be recorded at the appropriate BLM State office. BLM maintains a cumulative computer listing of mining claims in the Mining Claim Recordation System (MCRS) database with locations given by meridian, township, range, and section. A mining claim is considered closed when the claim is relinquished or a formal BLM decision declaring the mining claim null and void has been issued and the appeal period has expired. All other mining claims filed with BLM are considered to be open and actively held. The digital map (figure 1.) with the mining claim density database available in this report are suitable for geographic information system (GIS)-based regional assessments at a scale of 1:100,000 or smaller.

Digital mining claim density map for federal lands in California: 1996

USGS Publications Warehouse

Hyndman, Paul C.; Campbell, Harry W.

1999-01-01

This report describes a digital map generated by the U.S. Geological Survey (USGS) to provide digital spatial mining claim density information for federal lands in California as of March 1997. Mining claim data is earth science information deemed to be relevant to the assessment of historic, current, and future ecological, economic, and social systems. There is no paper map included in this Open-File report. In accordance with the Federal Land Policy and Management Act of 1976 (FLPMA), all unpatented mining claims, mill, and tunnel sites must be recorded at the appropriate BLM State office. BLM maintains a cumulative computer listing of mining claims in the MCRS database with locations given by meridian, township, range, and section. A mining claim is considered closed when the claim is relinquished or a formal BLM decision declaring the mining claim null and void has been issued and the appeal period has expired. All other mining claims filed with BLM are considered to be open and actively held. The digital map (figure 1.) with the mining claim density database available in this report are suitable for geographic information system (GIS)-based regional assessments at a scale of 1:100,000 or smaller.

Digital mining claim density map for federal lands in New Mexico: 1996

USGS Publications Warehouse

Hyndman, Paul C.; Campbell, Harry W.

1999-01-01

This report describes a digital map generated by the U.S. Geological Survey (USGS) to provide digital spatial mining claim density information for federal lands in New Mexico as of March 1997. Mining claim data is earth science information deemed to be relevant to the assessment of historic, current, and future ecological, economic, and social systems. There is no paper map included in this Open-File report. In accordance with the Federal Land Policy and Management Act of 1976 (FLPMA), all unpatented mining claims, mill, and tunnel sites must be recorded at the appropriate BLM State office. BLM maintains a cumulative computer listing of mining claims in the MCRS database with locations given by meridian, township, range, and section. A mining claim is considered closed when the claim is relinquished or a formal BLM decision declaring the mining claim null and void has been issued and the appeal period has expired. All other mining claims filed with BLM are considered to be open and actively held. The digital map (figure 1.) with the mining claim density database available in this report are suitable for geographic information system (GIS)-based regional assessments at a scale of 1:100,000 or smaller.

Digital mining claim density map for federal lands in Washington: 1996

USGS Publications Warehouse

Hyndman, Paul C.; Campbell, Harry W.

1999-01-01

This report describes a digital map generated by the U.S. Geological Survey (USGS) to provide digital spatial mining claim density information for federal lands in Washington as of March 1997. Mining claim data is earth science information deemed to be relevant to the assessment of historic, current, and future ecological, economic, and social systems. There is no paper map included in this Open-File report. In accordance with the Federal Land Policy and Management Act of 1976 (FLPMA), all unpatented mining claims, mill, and tunnel sites must be recorded at the appropriate BLM State office. BLM maintains a cumulative computer listing of mining claims in the Mining Claim Recordation System (MCRS) database with locations given by meridian, township, range, and section. A mining claim is considered closed when the claim is relinquished or a formal BLM decision declaring the mining claim null and void has been issued and the appeal period has expired. All other mining claims filed with BLM are considered to be open and actively held. The digital map (figure 1.) with the mining claim density database available in this report are suitable for geographic information system (GIS)-based regional assessments at a scale of 1:100,000 or smaller.

Digital mining claim density map for federal lands in Arizona: 1996

USGS Publications Warehouse

Hyndman, Paul C.; Campbell, Harry W.

1999-01-01

This report describes a digital map generated by the U.S. Geological Survey (USGS) to provide digital spatial mining claim density information for federal lands in Arizona as of March 1997. Mining claim data is earth science information deemed to be relevant to the assessment of historic, current, and future ecological, economic, and social systems. There is no paper map included in this Open-File report. In accordance with the Federal Land Policy and Management Act of 1976 (FLPMA), all unpatented mining claims, mill, and tunnel sites must be recorded at the appropriate BLM State office. BLM maintains a cumulative computer listing of mining claims in the MCRS database with locations given by meridian, township, range, and section. A mining claim is considered closed when the claim is relinquished or a formal BLM decision declaring the mining claim null and void has been issued and the appeal period has expired. All other mining claims filed with BLM are considered to be open and actively held. The digital map (figure 1.) with the mining claim density database available in this report are suitable for geographic information system (GIS)-based regional assessments at a scale of 1:100,000 or smaller.

Imputing forest carbon stock estimates from inventory plots to a nationally continuous coverage

PubMed Central

2013-01-01

The U.S. has been providing national-scale estimates of forest carbon (C) stocks and stock change to meet United Nations Framework Convention on Climate Change (UNFCCC) reporting requirements for years. Although these currently are provided as national estimates by pool and year to meet greenhouse gas monitoring requirements, there is growing need to disaggregate these estimates to finer scales to enable strategic forest management and monitoring activities focused on various ecosystem services such as C storage enhancement. Through application of a nearest-neighbor imputation approach, spatially extant estimates of forest C density were developed for the conterminous U.S. using the U.S.’s annual forest inventory. Results suggest that an existing forest inventory plot imputation approach can be readily modified to provide raster maps of C density across a range of pools (e.g., live tree to soil organic carbon) and spatial scales (e.g., sub-county to biome). Comparisons among imputed maps indicate strong regional differences across C pools. The C density of pools closely related to detrital input (e.g., dead wood) is often highest in forests suffering from recent mortality events such as those in the northern Rocky Mountains (e.g., beetle infestations). In contrast, live tree carbon density is often highest on the highest quality forest sites such as those found in the Pacific Northwest. Validation results suggest strong agreement between the estimates produced from the forest inventory plots and those from the imputed maps, particularly when the C pool is closely associated with the imputation model (e.g., aboveground live biomass and live tree basal area), with weaker agreement for detrital pools (e.g., standing dead trees). Forest inventory imputed plot maps provide an efficient and flexible approach to monitoring diverse C pools at national (e.g., UNFCCC) and regional scales (e.g., Reducing Emissions from Deforestation and Forest Degradation projects) while allowing timely incorporation of empirical data (e.g., annual forest inventory). PMID:23305341

Optimization of magnetic flux density measurement using multiple RF receiver coils and multi-echo in MREIT.

PubMed

Jeong, Woo Chul; Chauhan, Munish; Sajib, Saurav Z K; Kim, Hyung Joong; Serša, Igor; Kwon, Oh In; Woo, Eung Je

2014-09-07

Magnetic Resonance Electrical Impedance Tomography (MREIT) is an MRI method that enables mapping of internal conductivity and/or current density via measurements of magnetic flux density signals. The MREIT measures only the z-component of the induced magnetic flux density B = (Bx, By, Bz) by external current injection. The measured noise of Bz complicates recovery of magnetic flux density maps, resulting in lower quality conductivity and current-density maps. We present a new method for more accurate measurement of the spatial gradient of the magnetic flux density gradient (∇ Bz). The method relies on the use of multiple radio-frequency receiver coils and an interleaved multi-echo pulse sequence that acquires multiple sampling points within each repetition time. The noise level of the measured magnetic flux density Bz depends on the decay rate of the signal magnitude, the injection current duration, and the coil sensitivity map. The proposed method uses three key steps. The first step is to determine a representative magnetic flux density gradient from multiple receiver coils by using a weighted combination and by denoising the measured noisy data. The second step is to optimize the magnetic flux density gradient by using multi-echo magnetic flux densities at each pixel in order to reduce the noise level of ∇ Bz and the third step is to remove a random noise component from the recovered ∇ Bz by solving an elliptic partial differential equation in a region of interest. Numerical simulation experiments using a cylindrical phantom model with included regions of low MRI signal to noise ('defects') verified the proposed method. Experimental results using a real phantom experiment, that included three different kinds of anomalies, demonstrated that the proposed method reduced the noise level of the measured magnetic flux density. The quality of the recovered conductivity maps using denoised ∇ Bz data showed that the proposed method reduced the conductivity noise level up to 3-4 times at each anomaly region in comparison to the conventional method.

Candidate-penetrative-fracture mapping of the Grand Canyon area, Arizona, from spatial correlation of deep geophysical features and surficial lineaments

USGS Publications Warehouse

Gettings, Mark E.; Bultman, Mark W.

2005-01-01

Some aquifers of the southwestern Colorado Plateaus Province are deeply buried and overlain by several impermeable shale layers, and so recharge to the aquifer probably is mainly by seepage down penetrative-fracture systems. The purpose of this 2-year study, sponsored by the U.S. National Park Service, was to map candidate deep penetrative fractures over a 120,000-km2 area, using gravity and aeromagnetic-anomaly data together with surficial-fracture data. The study area was on the Colorado Plateau south of the Grand Canyon and west of Black Mesa; mapping was carried out at a scale of 1:250,000. The resulting database constitutes a spatially registered estimate of deep-fracture locations. Candidate penetrative fractures were located by spatial correlation of horizontal- gradient and analytic-signal maximums of gravity and magnetic anomalies with major surficial lineaments obtained from geologic, topographic, side-looking-airborne-radar, and satellite imagery. The maps define a subset of candidate penetrative fractures because of limitations in the data coverage and the analytical technique. In particular, the data and analytical technique used cannot predict whether the fractures are open or closed. Correlations were carried out by using image-processing software, such that every pixel on the resulting images was coded to uniquely identify which datasets are correlated. The technique correctly identified known and many new deep fracture systems. The resulting penetrative-fracture-distribution maps constitute an objectively obtained, repeatable dataset and a benchmark from which additional studies can begin. The maps also define in detail the tectonic fabrics of the southwestern Colorado Plateaus Province. Overlaying the correlated lineaments on the normalized-density-of-vegetation-index image reveals that many of these lineaments correlate with the boundaries of vegetation zones in drainages and canyons and so may be controlling near-surface water availability in some places. Many derivative products can be produced from the database, such as fracture-density-estimate maps, and maps with the number of correlations color-coded to estimate the possible quality of correlation. The database contained in this report is designed to be used in a geographic information system and image-processing systems, and most data layers are in georeferenced tagged image format (Geotiff) or ARC grids. The report includes 163 map plates and various metadata, supporting, and statistical diagram files.

Spatial pattern analysis of Cu, Zn and Ni and their interpretation in the Campania region (Italy)

NASA Astrophysics Data System (ADS)

Petrik, Attila; Albanese, Stefano; Jordan, Gyozo; Rolandi, Roberto; De Vivo, Benedetto

2017-04-01

The uniquely abundant Campanian topsoil dataset enabled us to perform a spatial pattern analysis on 3 potentially toxic elements of Cu, Zn and Ni. This study is focusing on revealing the spatial texture and distribution of these elements by spatial point pattern and image processing analysis such as lineament density and spatial variability index calculation. The application of these methods on geochemical data provides a new and efficient tool to understand the spatial variation of concentrations and their background/baseline values. The determination and quantification of spatial variability is crucial to understand how fast the change in concentration is in a certain area and what processes might govern the variation. The spatial variability index calculation and image processing analysis including lineament density enables us to delineate homogenous areas and analyse them with respect to lithology and land use. Identification of spatial outliers and their patterns were also investigated by local spatial autocorrelation and image processing analysis including the determination of local minima and maxima points and singularity index analysis. The spatial variability of Cu and Zn reveals the highest zone (Cu: 0.5 MAD, Zn: 0.8-0.9 MAD, Median Deviation Index) along the coast between Campi Flegrei and the Sorrento Peninsula with the vast majority of statistically identified outliers and high-high spatial clustered points. The background/baseline maps of Cu and Zn reveals a moderate to high variability (Cu: 0.3 MAD, Zn: 0.4-0.5 MAD) NW-SE oriented zone including disrupted patches from Bisaccia to Mignano following the alluvial plains of Appenine's rivers. This zone has high abundance of anomaly concentrations identified using singularity analysis and it also has a high density of lineaments. The spatial variability of Ni shows the highest variability zone (0.6-0.7 MAD) around Campi Flegrei where the majority of low outliers are concentrated. The variability of background/baseline map of Ni reveals a shift to the east in case of highest variability zones coinciding with limestone outcrops. The high segmented area between Mignano and Bisaccia partially follows the alluvial plains of Appenine's rivers which seem to be playing a crucial role in the distribution and redistribution pattern of Cu, Zn and Ni in Campania. The high spatial variability zones of the later elements are located in topsoils on volcanoclastic rocks and are mostly related to cultivation and urbanised areas.

Mapping atomic contact between pentacene and a Au surface using scanning tunneling spectroscopy.

PubMed

Song, Young Jae; Lee, Kyuho; Kim, Seong Heon; Choi, Byoung-Young; Yu, Jaejun; Kuk, Young

2010-03-10

We mapped spatially varying intramolecular electronic structures on a pentacene-gold interface using scanning tunneling spectroscopy. Along with ab initio calculations based on density functional theory, we found that the directional nature of the d orbitals of Au atoms plays an important role in the interaction at the pentacene-gold contact. The gold-induced interface states are broadened and shifted by various pentacene-gold distances determined by the various registries of a pentacene molecule on a gold substrate.

A Kennicutt-Schmidt relation at molecular cloud scales and beyond

NASA Astrophysics Data System (ADS)

Khoperskov, Sergey A.; Vasiliev, Evgenii O.

2017-06-01

Using N-body/gasdynamic simulations of a Milky Way-like galaxy, we analyse a Kennicutt-Schmidt (KS) relation, Σ _SFR ∝ Σ _gas^N, at different spatial scales. We simulate synthetic observations in CO lines and ultraviolet (UV) band. We adopt the star formation rate (SFR) defined in two ways: based on free fall collapse of a molecular cloud - ΣSFR, cl, and calculated by using a UV flux calibration - ΣSFR,UV. We study a KS relation for spatially smoothed maps with effective spatial resolution from molecular cloud scales to several hundred parsecs. We find that for spatially and kinematically resolved molecular clouds the Σ _{SFR, cl} ∝ σ _{gas}^N relation follows the power law with index N ≈ 1.4. Using UV flux as SFR calibrator, we confirm a systematic offset between the ΣSFR,UV and Σgas distributions on scales compared to molecular cloud sizes. Degrading resolution of our simulated maps for surface densities of gas and SFRs, we establish that there is no relation ΣSFR,UV -Σgas below the resolution ˜50 pc. We find a transition range around scales ˜50-120 pc, where the power-law index N increases from 0 to 1-1.8 and saturates for scales larger ˜120 pc. A value of the index saturated depends on a surface gas density threshold and it becomes steeper for higher Σgas threshold. Averaging over scales with size of ≳ 150 pc the power-law index N equals 1.3-1.4 for surface gas density threshold ˜5 M⊙ pc-2. At scales ≳ 120 pc surface SFR densities determined by using CO data and UV flux, ΣSFR,UV/SFR, cl, demonstrate a discrepancy about a factor of 3. We argue that this may be originated from overestimating (constant) values of conversion factor, star formation efficiency or UV calibration used in our analysis.

Structure of massive star forming clumps from the Red MSX Source Survey

NASA Astrophysics Data System (ADS)

Figura, Charles C.; Urquhart, J. S.; Morgan, L.

2014-01-01

We present ammonia (1,1) and (2,2) emission maps of 61 high-mass star forming regions drawn from the Red MSX Source (RMS) Survey and observed with the Green Bank Telescope's K-Band Focal Plane Array. We use these observations to investigate the spatial distribution of the environmental conditions associated with this sample of embedded massive young stellar objects (MYSOs). Ammonia is an excellent high-density tracer of star-forming regions as its hyperfine structure allows relatively simple characterisation of the molecular environment. These maps are used to measure the column density, kinetic gas temperature distributions and velocity structure across these regions. We compare the distribution of these properties to that of the associated dust and mid-infrared emission traced by the ATLASGAL 870 micron emission maps and the Spitzer GLIMPSE IRAC images. We present a summary of these results and highlight some of more interesting finds.

Clustering the Orion B giant molecular cloud based on its molecular emission.

PubMed

Bron, Emeric; Daudon, Chloé; Pety, Jérôme; Levrier, François; Gerin, Maryvonne; Gratier, Pierre; Orkisz, Jan H; Guzman, Viviana; Bardeau, Sébastien; Goicoechea, Javier R; Liszt, Harvey; Öberg, Karin; Peretto, Nicolas; Sievers, Albrecht; Tremblin, Pascal

2018-02-01

Previous attempts at segmenting molecular line maps of molecular clouds have focused on using position-position-velocity data cubes of a single molecular line to separate the spatial components of the cloud. In contrast, wide field spectral imaging over a large spectral bandwidth in the (sub)mm domain now allows one to combine multiple molecular tracers to understand the different physical and chemical phases that constitute giant molecular clouds (GMCs). We aim at using multiple tracers (sensitive to different physical processes and conditions) to segment a molecular cloud into physically/chemically similar regions (rather than spatially connected components), thus disentangling the different physical/chemical phases present in the cloud. We use a machine learning clustering method, namely the Meanshift algorithm, to cluster pixels with similar molecular emission, ignoring spatial information. Clusters are defined around each maximum of the multidimensional Probability Density Function (PDF) of the line integrated intensities. Simple radiative transfer models were used to interpret the astrophysical information uncovered by the clustering analysis. A clustering analysis based only on the J = 1 - 0 lines of three isotopologues of CO proves suffcient to reveal distinct density/column density regimes ( n H ~ 100 cm -3 , ~ 500 cm -3 , and > 1000 cm -3 ), closely related to the usual definitions of diffuse, translucent and high-column-density regions. Adding two UV-sensitive tracers, the J = 1 - 0 line of HCO + and the N = 1 - 0 line of CN, allows us to distinguish two clearly distinct chemical regimes, characteristic of UV-illuminated and UV-shielded gas. The UV-illuminated regime shows overbright HCO + and CN emission, which we relate to a photochemical enrichment effect. We also find a tail of high CN/HCO + intensity ratio in UV-illuminated regions. Finer distinctions in density classes ( n H ~ 7 × 10 3 cm -3 ~ 4 × 10 4 cm -3 ) for the densest regions are also identified, likely related to the higher critical density of the CN and HCO + (1 - 0) lines. These distinctions are only possible because the high-density regions are spatially resolved. Molecules are versatile tracers of GMCs because their line intensities bear the signature of the physics and chemistry at play in the gas. The association of simultaneous multi-line, wide-field mapping and powerful machine learning methods such as the Meanshift clustering algorithm reveals how to decode the complex information available in these molecular tracers.

Geographical Distribution of Biomass Carbon in Tropical Southeast Asian Forests: A Database (NPD-068)

DOE Data Explorer

Brown, Sandra [University of Illinois, Urbana, Illinois (USA); Iverson, Louis R. [University of Illinois, Urbana, Illinois (USA); Prasad, Anantha [University of Illinois, Urbana, Illinois (USA); Beaty, Tammy W. [CDIAC, Oak Ridge National Laboratory, Oak Ridge, TN (USA); Olsen, Lisa M. [CDIAC, Oak Ridge National Laboratory, Oak Ridge, TN (USA); Cushman, Robert M. [CDIAC, Oak Ridge National Laboratory, Oak Ridge, TN (USA); Brenkert, Antoinette L. [CDIAC, Oak Ridge National Laboratory, Oak Ridge, TN (USA)

2001-03-01

A database was generated of estimates of geographically referenced carbon densities of forest vegetation in tropical Southeast Asia for 1980. A geographic information system (GIS) was used to incorporate spatial databases of climatic, edaphic, and geomorphological indices and vegetation to estimate potential (i.e., in the absence of human intervention and natural disturbance) carbon densities of forests. The resulting map was then modified to estimate actual 1980 carbon density as a function of population density and climatic zone. The database covers the following 13 countries: Bangladesh, Brunei, Cambodia (Campuchea), India, Indonesia, Laos, Malaysia, Myanmar (Burma), Nepal, the Philippines, Sri Lanka, Thailand, and Vietnam.

Mapping, Bayesian Geostatistical Analysis and Spatial Prediction of Lymphatic Filariasis Prevalence in Africa

PubMed Central

Slater, Hannah; Michael, Edwin

2013-01-01

There is increasing interest to control or eradicate the major neglected tropical diseases. Accurate modelling of the geographic distributions of parasitic infections will be crucial to this endeavour. We used 664 community level infection prevalence data collated from the published literature in conjunction with eight environmental variables, altitude and population density, and a multivariate Bayesian generalized linear spatial model that allows explicit accounting for spatial autocorrelation and incorporation of uncertainty in input data and model parameters, to construct the first spatially-explicit map describing LF prevalence distribution in Africa. We also ran the best-fit model against predictions made by the HADCM3 and CCCMA climate models for 2050 to predict the likely distributions of LF under future climate and population changes. We show that LF prevalence is strongly influenced by spatial autocorrelation between locations but is only weakly associated with environmental covariates. Infection prevalence, however, is found to be related to variations in population density. All associations with key environmental/demographic variables appear to be complex and non-linear. LF prevalence is predicted to be highly heterogenous across Africa, with high prevalences (>20%) estimated to occur primarily along coastal West and East Africa, and lowest prevalences predicted for the central part of the continent. Error maps, however, indicate a need for further surveys to overcome problems with data scarcity in the latter and other regions. Analysis of future changes in prevalence indicates that population growth rather than climate change per se will represent the dominant factor in the predicted increase/decrease and spread of LF on the continent. We indicate that these results could play an important role in aiding the development of strategies that are best able to achieve the goals of parasite elimination locally and globally in a manner that may also account for the effects of future climate change on parasitic infection. PMID:23951194

Remote sensing and spatial statistical techniques for modelling Ommatissus lybicus (Hemiptera: Tropiduchidae) habitat and population densities

PubMed Central

Kwan, Paul; Welch, Mitchell

2017-01-01

In order to understand the distribution and prevalence of Ommatissus lybicus (Hemiptera: Tropiduchidae) as well as analyse their current biographical patterns and predict their future spread, comprehensive and detailed information on the environmental, climatic, and agricultural practices are essential. The spatial analytical techniques such as Remote Sensing and Spatial Statistics Tools, can help detect and model spatial links and correlations between the presence, absence and density of O. lybicus in response to climatic, environmental, and human factors. The main objective of this paper is to review remote sensing and relevant analytical techniques that can be applied in mapping and modelling the habitat and population density of O. lybicus. An exhaustive search of related literature revealed that there are very limited studies linking location-based infestation levels of pests like the O. lybicus with climatic, environmental, and human practice related variables. This review also highlights the accumulated knowledge and addresses the gaps in this area of research. Furthermore, it makes recommendations for future studies, and gives suggestions on monitoring and surveillance methods in designing both local and regional level integrated pest management strategies of palm tree and other affected cultivated crops. PMID:28875085

Remote sensing and spatial statistical techniques for modelling Ommatissus lybicus (Hemiptera: Tropiduchidae) habitat and population densities.

PubMed

Al-Kindi, Khalifa M; Kwan, Paul; R Andrew, Nigel; Welch, Mitchell

2017-01-01

In order to understand the distribution and prevalence of Ommatissus lybicus (Hemiptera: Tropiduchidae) as well as analyse their current biographical patterns and predict their future spread, comprehensive and detailed information on the environmental, climatic, and agricultural practices are essential. The spatial analytical techniques such as Remote Sensing and Spatial Statistics Tools, can help detect and model spatial links and correlations between the presence, absence and density of O. lybicus in response to climatic, environmental, and human factors. The main objective of this paper is to review remote sensing and relevant analytical techniques that can be applied in mapping and modelling the habitat and population density of O. lybicus . An exhaustive search of related literature revealed that there are very limited studies linking location-based infestation levels of pests like the O. lybicus with climatic, environmental, and human practice related variables. This review also highlights the accumulated knowledge and addresses the gaps in this area of research. Furthermore, it makes recommendations for future studies, and gives suggestions on monitoring and surveillance methods in designing both local and regional level integrated pest management strategies of palm tree and other affected cultivated crops.

Spatial mapping of humeral head bone density.

PubMed

Alidousti, Hamidreza; Giles, Joshua W; Emery, Roger J H; Jeffers, Jonathan

2017-09-01

Short-stem humeral replacements achieve fixation by anchoring to the metaphyseal trabecular bone. Fixing the implant in high-density bone can provide strong fixation and reduce the risk of loosening. However, there is a lack of data mapping the bone density distribution in the proximal humerus. The aim of the study was to investigate the bone density in proximal humerus. Eight computed tomography scans of healthy cadaveric humeri were used to map bone density distribution in the humeral head. The proximal humeral head was divided into 12 slices parallel to the humeral anatomic neck. Each slice was then divided into 4 concentric circles. The slices below the anatomic neck, where short-stem implants have their fixation features, were further divided into radial sectors. The average bone density for each of these regions was calculated, and regions of interest were compared using a repeated-measures analysis of variance with significance set at P < .05. Average apparent bone density was found to decrease from proximal to distal regions, with the majority of higher bone density proximal to the anatomic neck of the humerus (P < .05). Below the anatomic neck, bone density increases from central to peripheral regions, where cortical bone eventually occupies the space (P < .05). In distal slices below the anatomic neck, a higher bone density distribution in the medial calcar region was also observed. This study indicates that it is advantageous with respect to implant fixation to preserve some bone above the anatomic neck and epiphyseal plate and to use the denser bone at the periphery. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

High-energy Gamma Rays from the Milky Way: Three-dimensional Spatial Models for the Cosmic-Ray and Radiation Field Densities in the Interstellar Medium

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

Porter, T. A.; Moskalenko, I. V.; Jóhannesson, G., E-mail: tporter@stanford.edu

High-energy γ -rays of interstellar origin are produced by the interaction of cosmic-ray (CR) particles with the diffuse gas and radiation fields in the Galaxy. The main features of this emission are well understood and are reproduced by existing CR propagation models employing 2D galactocentric cylindrically symmetrical geometry. However, the high-quality data from instruments like the Fermi Large Area Telescope reveal significant deviations from the model predictions on few to tens of degrees scales, indicating the need to include the details of the Galactic spiral structure and thus requiring 3D spatial modeling. In this paper, the high-energy interstellar emissions frommore » the Galaxy are calculated using the new release of the GALPROP code employing 3D spatial models for the CR source and interstellar radiation field (ISRF) densities. Three models for the spatial distribution of CR sources are used that are differentiated by their relative proportion of input luminosity attributed to the smooth disk or spiral arms. Two ISRF models are developed based on stellar and dust spatial density distributions taken from the literature that reproduce local near- to far-infrared observations. The interstellar emission models that include arms and bulges for the CR source and ISRF densities provide plausible physical interpretations for features found in the residual maps from high-energy γ -ray data analysis. The 3D models for CR and ISRF densities provide a more realistic basis that can be used for the interpretation of the nonthermal interstellar emissions from the Galaxy.« less

High-resolution mapping of the triangle of Koch: Spatial heterogeneity of fast pathway atrionodal connections.

PubMed

Chua, Kelvin; Upadhyay, Gaurav A; Lee, Elliot; Aziz, Zaid; Beaser, Andrew D; Ozcan, Cevher; Broman, Michael; Nayak, Hemal M; Tung, Roderick

2018-03-01

Dedicated mapping studies of the triangle of Koch to characterize retrograde fast pathway activation have not been previously performed using high-resolution, 3-dimensional, multielectrode mapping technology. To delineate the activation pattern and spatial distribution of the retrograde fast pathway within the triangle of Koch during typical atrioventricular nodal reentrant tachycardia (AVNRT) and right ventricular pacing in a consecutive series of patients using the Rhythmia mapping system (Boston Scientific, Natick, MA). A total of 18 patients with symptomatic typical AVNRT referred for ablation underwent ultra high-density mapping of atrial activation with minielectrode basket configuration during tachycardia. The earliest atrial activation was mapped using automated annotation, with manual overreading by 2 independent observers. The triangle of Koch was classified into 3 anatomic regions: anteroseptal (His), midseptal, and posteroseptal (coronary sinus roof). Thirteen patients underwent mapping of atrial activation during ventricular pacing. A median of 422 mapping points (interquartile range 258-896 points) was acquired within the triangle of Koch during tachycardia. The most common site of earliest atrial activation within the triangle of Koch was anterior in 67% of patients (n = 12). Midseptal early atrial activation was seen in 17% (n = 3), and posteroseptal activation was observed in 11% (n = 2). One patient exhibited broad simultaneous activation of the entire triangle of Koch. Slow pathway potentials were not identified. With high-resolution multielectrode mapping, atrial activation during typical AVNRT exhibited anatomic variability and spatially heterogeneous activation within the triangle of Koch. These findings highlight the limitations of an anatomically based classification of atrioventricular nodal retrograde pathways. Copyright © 2017 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

Spatio-temporal evolution of forest fires in Portugal

NASA Astrophysics Data System (ADS)

Tonini, Marj; Pereira, Mário G.; Parente, Joana

2017-04-01

A key issue in fire management is the ability to explore and try to predict where and when fires are more likely to occur. This information can be useful to understand the triggering factors of ignitions and for planning strategies to reduce forest fires, to manage the sources of ignition and to identify areas and frame period at risk. Therefore, producing maps displaying forest fires location and their occurrence in time can be of great help for accurately forecasting these hazardous events. In a fire prone country as Portugal, where thousands of events occurs each year, it is involved to drive information about fires over densities and recurrences just by looking at the original arrangement of the mapped ignition points or burnt areas. In this respect, statistical methods originally developed for spatio-temporal stochastic point processes can be employed to find a structure within these large datasets. In the present study, the authors propose an approach to analyze and visualize the evolution in space and in time of forest fires occurred in Portugal during a long frame period (1990 - 2013). Data came from the Portuguese mapped burnt areas official geodatabase (by the Institute for the Conservation of Nature and Forests), which is the result of interpreted satellite measurements. The following statistical analyses were performed: the geographically-weighted summary statistics, to analyze the local variability of the average burned area; the space-time Kernel density, to elaborate smoothed density surfaces representing over densities of fires classed by size and on North vs South region. Finally, we emploied the volume rendering thecnique to visualize the spatio-temporal evolution of these events into a unique map: this representation allows visually inspecting areas and time-step more affected from a high aggregation of forest fires. It results that during the whole investigated period over densities are mainly located in the northern regions, while in the southern areas spread hot-spot are spatially randomly distributed and temporally more concentrated in the frame 2000 - 2004. To conclude, this study let us to identify a multitude of clustering space-time features of forest fires in Portugal, which can be useful for a better planning of educational activities and prevention campaigns as well as for a better allocation of monitoring systems and firefighting. References: Tonini M., Pereira M. G., Parente J. (2016) - Evolution of forest fires in Portugal: from spatio-temporal point events to smoothed density maps. Natural Hazard, doi:10.1007/s11069-016-2637-x Lu B., Harris P., Charlton M., Brunsdon C. (2014) - The GWmodel R package: further topics for exploring spatial heterogeneity using geographically weighted models. Geo-spatial Information Science, Vol. 17: 85-101 Rowlingson B., Diggle P., Bivand M.R. (2012) - Splancs: spatial point pattern analysis code in S-Plus. Computers and Geosciences, Vol. 19: 627-655 Acknowledgements: This work was supported by: (i) the FIREXTR project, PTDC/ATP¬GEO/0462/2014; (ii) the project Interact - Integrative Research in Environment,Agro-Chain and Technology, NORTE-01-0145-FEDER-000017, research line BEST, cofinanced by FEDER/NORTE 2020; and, (iii) European Investment Funds by FEDER/COMPETE/POCI-Operacional Competitiveness and Internacionalization Programme, under Project POCI-01-0145-FEDER-006958 and National Funds by FCT - Portuguese Foundation for Science and Technology, under the project UID/AGR/04033. We are especially grateful to ICNF for providing the fire.

The Herschel-SPIRE Point Source Catalog Version 2

NASA Astrophysics Data System (ADS)

Schulz, Bernhard; Marton, Gábor; Valtchanov, Ivan; María Pérez García, Ana; Pintér, Sándor; Appleton, Phil; Kiss, Csaba; Lim, Tanya; Lu, Nanyao; Papageorgiou, Andreas; Pearson, Chris; Rector, John; Sánchez Portal, Miguel; Shupe, David; Tóth, Viktor L.; Van Dyk, Schuyler; Varga-Verebélyi, Erika; Xu, Kevin

2018-01-01

The Herschel-SPIRE instrument mapped about 8% of the sky in Submillimeter broad-band filters centered at 250, 350, and 500 microns (1199, 857, 600 GHz) with spatial resolutions of 17.9”, 24.2”, and 35.4” respectively. We present here the 2nd version of the SPIRE Point Source Catalog (SPSC). Stacking on WISE 22 micron catalog sources led to the identification of 108 maps, out of 6878, that had astrometry offsets of greater than 5”. After fixing these deviations and re-derivation of all affected map-mosaics, we repeated the systematic and homogeneous source extraction performed on all maps, using an improved version of the 4 different photometry extraction methods that were already employed in the generation of the first version catalog. Only regions affected by strong Galactic emission, mostly in the Galactic Plane, were excluded, as they exceeded the limits of the available source extraction methods. Aimed primarily at point sources, that allow for the best photometric accuracy, the catalog contains also significant fractions of slightly extended sources. With most SPIRE maps being confusion limited, uncertainties in flux densities were established as a function of structure noise and flux density, based on the results of artificial source insertion experiments into real data along a range of celestial backgrounds. Many sources have been rejected that do not pass the imposed SNR threshold, especially at flux densities approaching the extragalactic confusion limit. A range of additional flags provide information on the reliability of the flux information, as well as the spatial extent and orientation of a source. The catalog should be particularly helpful for determining cold dust content in extragalactic and galactic sources with low to moderate background confusion. We present an overview of catalog construction, detailed content, and validation results, with focus on the improvements achieved in the second version that is soon to be released.

Spatial relationships among cereal yields and selected soil physical and chemical properties.

PubMed

Lipiec, Jerzy; Usowicz, Bogusław

2018-08-15

Sandy soils occupy large area in Poland (about 50%) and in the world. This study aimed at determining spatial relationships of cereal yields and the selected soil physical and chemical properties in three study years (2001-2003) on low productive sandy Podzol soil (Podlasie, Poland). The yields and soil properties in plough and subsoil layers were determined at 72-150 points. The test crops were: wheat, wheat and barley mixture and oats. To explore the spatial relationship between cereal yields and each soil property spatial statistics was used. The best fitting models were adjusted to empirical semivariance and cross-semivariance, which were used to draw maps using kriging. Majority of the soil properties and crop yields exhibited low and medium variability (coefficient of variation 5-70%). The effective ranges of the spatial dependence (the distance at which data are autocorrelated) for yields and all soil properties were 24.3-58.5m and 10.5-373m, respectively. Nugget to sill ratios showed that crop yields and soil properties were strongly spatially dependent except bulk density. Majority of the pairs in cross-semivariograms exhibited strong spatial interdependence. The ranges of the spatial dependence varied in plough layer between 54.6m for yield×pH up to 2433m for yield×silt content. Corresponding ranges in subsoil were 24.8m for crop yield×clay content in 2003 and 1404m for yield×bulk density. Kriging maps allowed separating sub-field area with the lowest yield and soil cation exchange capacity, organic carbon content and pH. This area had lighter color on the aerial photograph due to high content of the sand and low content of soil organic carbon. The results will help farmers at identifying sub-field areas for applying localized management practices to improve these soil properties and further spatial studies in larger scale. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Spatial analysis of geologic and hydrologic features relating to sinkhole occurrence in Jefferson County, West Virginia

USGS Publications Warehouse

Doctor, Daniel H.; Doctor, Katarina Z.

2012-01-01

In this study the influence of geologic features related to sinkhole susceptibility was analyzed and the results were mapped for the region of Jefferson County, West Virginia. A model of sinkhole density was constructed using Geographically Weighted Regression (GWR) that estimated the relations among discrete geologic or hydrologic features and sinkhole density at each sinkhole location. Nine conditioning factors on sinkhole occurrence were considered as independent variables: distance to faults, fold axes, fracture traces oriented along bedrock strike, fracture traces oriented across bedrock strike, ponds, streams, springs, quarries, and interpolated depth to groundwater. GWR model parameter estimates for each variable were evaluated for significance, and the results were mapped. The results provide visual insight into the influence of these variables on localized sinkhole density, and can be used to provide an objective means of weighting conditioning factors in models of sinkhole susceptibility or hazard risk.

Analysis of interstellar fragmentation structure based on IRAS images

NASA Technical Reports Server (NTRS)

Scalo, John M.

1989-01-01

The goal of this project was to develop new tools for the analysis of the structure of densely sampled maps of interstellar star-forming regions. A particular emphasis was on the recognition and characterization of nested hierarchical structure and fractal irregularity, and their relation to the level of star formation activity. The panoramic IRAS images provided data with the required range in spatial scale, greater than a factor of 100, and in column density, greater than a factor of 50. In order to construct a densely sampled column density map of a cloud complex which is both self-gravitating and not (yet?) stirred up much by star formation, a column density image of the Taurus region has been constructed from IRAS data. The primary drawback to using the IRAS data for this purpose is that it contains no velocity information, and the possible importance of projection effects must be kept in mind.

Spatially encoded phase-contrast MRI-3D MRI movies of 1D and 2D structures at millisecond resolution.

PubMed

Merboldt, Klaus-Dietmar; Uecker, Martin; Voit, Dirk; Frahm, Jens

2011-10-01

This work demonstrates that the principles underlying phase-contrast MRI may be used to encode spatial rather than flow information along a perpendicular dimension, if this dimension contains an MRI-visible object at only one spatial location. In particular, the situation applies to 3D mapping of curved 2D structures which requires only two projection images with different spatial phase-encoding gradients. These phase-contrast gradients define the field of view and mean spin-density positions of the object in the perpendicular dimension by respective phase differences. When combined with highly undersampled radial fast low angle shot (FLASH) and image reconstruction by regularized nonlinear inversion, spatial phase-contrast MRI allows for dynamic 3D mapping of 2D structures in real time. First examples include 3D MRI movies of the acting human hand at a temporal resolution of 50 ms. With an even simpler technique, 3D maps of curved 1D structures may be obtained from only three acquisitions of a frequency-encoded MRI signal with two perpendicular phase encodings. Here, 3D MRI movies of a rapidly rotating banana were obtained at 5 ms resolution or 200 frames per second. In conclusion, spatial phase-contrast 3D MRI of 2D or 1D structures is respective two or four orders of magnitude faster than conventional 3D MRI. Copyright © 2011 Wiley-Liss, Inc.

Use of Activity Space in a Tuberculosis Outbreak: Bringing Homeless Persons Into Spatial Analyses.

PubMed

Worrell, Mary Claire; Kramer, Michael; Yamin, Aliya; Ray, Susan M; Goswami, Neela D

2017-01-01

Tuberculosis (TB) causes significant morbidity and mortality in US cities, particularly in poor, transient populations. During a TB outbreak in Fulton County, Atlanta, GA, we aimed to determine whether local maps created from multiple locations of personal activity per case would differ significantly from traditional maps created from single residential address. Data were abstracted for patients with TB disease diagnosed in 2008-2014 and receiving care at the Fulton County Health Department. Clinical and activity location data were abstracted from charts. Kernel density methods, activity space analysis, and overlay with homeless shelter locations were used to characterize case spatial distribution when using single versus multiple addresses. Data were collected for 198 TB cases, with over 30% homeless US-born cases included. Greater spatial dispersion of cases was found when utilizing multiple versus single addresses per case. Activity spaces of homeless and isoniazid (INH)-resistant cases were more spatially congruent with one another than non-homeless and INH-susceptible cases ( P < .0001 and P < .0001, respectively). Innovative spatial methods allowed us to more comprehensively capture the geography of TB-infected homeless persons, who made up a large portion of the Fulton County outbreak. We demonstrate how activity space analysis, prominent in exposure science and chronic disease, supports that routine capture of multiple location TB data may facilitate spatially different public health interventions than traditional surveillance maps. © The Author 2017. Published by Oxford University Press on behalf of Infectious Diseases Society of America.

Methods used to parameterize the spatially-explicit components of a state-and-transition simulation model

USGS Publications Warehouse

Sleeter, Rachel; Acevedo, William; Soulard, Christopher E.; Sleeter, Benjamin M.

2015-01-01

Spatially-explicit state-and-transition simulation models of land use and land cover (LULC) increase our ability to assess regional landscape characteristics and associated carbon dynamics across multiple scenarios. By characterizing appropriate spatial attributes such as forest age and land-use distribution, a state-and-transition model can more effectively simulate the pattern and spread of LULC changes. This manuscript describes the methods and input parameters of the Land Use and Carbon Scenario Simulator (LUCAS), a customized state-and-transition simulation model utilized to assess the relative impacts of LULC on carbon stocks for the conterminous U.S. The methods and input parameters are spatially explicit and describe initial conditions (strata, state classes and forest age), spatial multipliers, and carbon stock density. Initial conditions were derived from harmonization of multi-temporal data characterizing changes in land use as well as land cover. Harmonization combines numerous national-level datasets through a cell-based data fusion process to generate maps of primary LULC categories. Forest age was parameterized using data from the North American Carbon Program and spatially-explicit maps showing the locations of past disturbances (i.e. wildfire and harvest). Spatial multipliers were developed to spatially constrain the location of future LULC transitions. Based on distance-decay theory, maps were generated to guide the placement of changes related to forest harvest, agricultural intensification/extensification, and urbanization. We analyze the spatially-explicit input parameters with a sensitivity analysis, by showing how LUCAS responds to variations in the model input. This manuscript uses Mediterranean California as a regional subset to highlight local to regional aspects of land change, which demonstrates the utility of LUCAS at many scales and applications.

Parasol cell mosaics are unlikely to drive the formation of structured orientation maps in primary visual cortex.

PubMed

Hore, Victoria R A; Troy, John B; Eglen, Stephen J

2012-11-01

The receptive fields of on- and off-center parasol cell mosaics independently tile the retina to ensure efficient sampling of visual space. A recent theoretical model represented the on- and off-center mosaics by noisy hexagonal lattices of slightly different density. When the two lattices are overlaid, long-range Moiré interference patterns are generated. These Moiré interference patterns have been suggested to drive the formation of highly structured orientation maps in visual cortex. Here, we show that noisy hexagonal lattices do not capture the spatial statistics of parasol cell mosaics. An alternative model based upon local exclusion zones, termed as the pairwise interaction point process (PIPP) model, generates patterns that are statistically indistinguishable from parasol cell mosaics. A key difference between the PIPP model and the hexagonal lattice model is that the PIPP model does not generate Moiré interference patterns, and hence stimulated orientation maps do not show any hexagonal structure. Finally, we estimate the spatial extent of spatial correlations in parasol cell mosaics to be only 200-350 μm, far less than that required to generate Moiré interference. We conclude that parasol cell mosaics are too disordered to drive the formation of highly structured orientation maps in visual cortex.

Shallow landslide prediction and analysis with risk assessment using a spatial model in the coastal region in the state of São Paulo, Brazil

NASA Astrophysics Data System (ADS)

Camarinha, P. I. M.; Canavesi, V.; Alvalá, R. C. S.

2013-10-01

In Brazil, most of the disasters involving landslide occur in coastal regions, with population density concentrated on steep slopes. Thus, different approaches have been used to evaluate the landslide risk, although the greatest difficulty is related to the scarcity of spatial data with good quality. In this context, four cities located on the southeast coast of Brazil - Santos, Cubatão, Caraguatatuba and Ubatuba - in a region with the rough reliefs of the Serra do Mar and with a history of natural disasters were evaluated. Spatial prediction by fuzzy gamma technique was used for the landslide susceptibility mapping, considering environmental variables from data and software in the public domain. To validate the susceptibility mapping results, it was overlapped with risk sectors provided by the Geological Survey of Brazil (CPRM). A positive correlation was observed between the classes most susceptible and the location of these sectors. The results were also analyzed from the categorization of risk levels provided by CPRM. To compare the approach with other studies using landslide-scar maps, correlated indexes were evaluated, which also showed satisfactory results, thus indicating that the methodology presented is appropriate for risk assessment in urban areas and can be replicated to municipalities that do not have risk areas mapped.

An integrated approach of analytical network process and fuzzy based spatial decision making systems applied to landslide risk mapping

NASA Astrophysics Data System (ADS)

Abedi Gheshlaghi, Hassan; Feizizadeh, Bakhtiar

2017-09-01

Landslides in mountainous areas render major damages to residential areas, roads, and farmlands. Hence, one of the basic measures to reduce the possible damage is by identifying landslide-prone areas through landslide mapping by different models and methods. The purpose of conducting this study is to evaluate the efficacy of a combination of two models of the analytical network process (ANP) and fuzzy logic in landslide risk mapping in the Azarshahr Chay basin in northwest Iran. After field investigations and a review of research literature, factors affecting the occurrence of landslides including slope, slope aspect, altitude, lithology, land use, vegetation density, rainfall, distance to fault, distance to roads, distance to rivers, along with a map of the distribution of occurred landslides were prepared in GIS environment. Then, fuzzy logic was used for weighting sub-criteria, and the ANP was applied to weight the criteria. Next, they were integrated based on GIS spatial analysis methods and the landslide risk map was produced. Evaluating the results of this study by using receiver operating characteristic curves shows that the hybrid model designed by areas under the curve 0.815 has good accuracy. Also, according to the prepared map, a total of 23.22% of the area, amounting to 105.38 km2, is in the high and very high-risk class. Results of this research are great of importance for regional planning tasks and the landslide prediction map can be used for spatial planning tasks and for the mitigation of future hazards in the study area.

On Galactic Density Modeling in the Presence of Dust Extinction

NASA Astrophysics Data System (ADS)

Bovy, Jo; Rix, Hans-Walter; Green, Gregory M.; Schlafly, Edward F.; Finkbeiner, Douglas P.

2016-02-01

Inferences about the spatial density or phase-space structure of stellar populations in the Milky Way require a precise determination of the effective survey volume. The volume observed by surveys such as Gaia or near-infrared spectroscopic surveys, which have good coverage of the Galactic midplane region, is highly complex because of the abundant small-scale structure in the three-dimensional interstellar dust extinction. We introduce a novel framework for analyzing the importance of small-scale structure in the extinction. This formalism demonstrates that the spatially complex effect of extinction on the selection function of a pencil-beam or contiguous sky survey is equivalent to a low-pass filtering of the extinction-affected selection function with the smooth density field. We find that the angular resolution of current 3D extinction maps is sufficient for analyzing Gaia sub-samples of millions of stars. However, the current distance resolution is inadequate and needs to be improved by an order of magnitude, especially in the inner Galaxy. We also present a practical and efficient method for properly taking the effect of extinction into account in analyses of Galactic structure through an effective selection function. We illustrate its use with the selection function of red-clump stars in APOGEE using and comparing a variety of current 3D extinction maps.

Textural analysis of historical aerial photography to characterize woody plant encroachment in South African savanna

Treesearch

Andrew T. Hudak; Carol A. Wessman

1998-01-01

Transitions from grassland to shrubland through woody plant encroachment result in potentially significant shifts in savanna ecosystem function. Given high resolution imagery, a textural index could prove useful for mapping woody plant densities and monitoring woody plant encroachment across savanna landscapes. Spatial heterogeneity introduced through mixtures of...

From innervation density to tactile acuity: 1. Spatial representation.

PubMed

Brown, Paul B; Koerber, H Richard; Millecchia, Ronald

2004-06-11

We tested the hypothesis that the population receptive field representation (a superposition of the excitatory receptive field areas of cells responding to a tactile stimulus) provides spatial information sufficient to mediate one measure of static tactile acuity. In psychophysical tests, two-point discrimination thresholds on the hindlimbs of adult cats varied as a function of stimulus location and orientation, as they do in humans. A statistical model of the excitatory low threshold mechanoreceptive fields of spinocervical, postsynaptic dorsal column and spinothalamic tract neurons was used to simulate the population receptive field representations in this neural population of the one- and two-point stimuli used in the psychophysical experiments. The simulated and observed thresholds were highly correlated. Simulated and observed thresholds' relations to physiological and anatomical variables such as stimulus location and orientation, receptive field size and shape, map scale, and innervation density were strikingly similar. Simulated and observed threshold variations with receptive field size and map scale obeyed simple relationships predicted by the signal detection model, and were statistically indistinguishable from each other. The population receptive field representation therefore contains information sufficient for this discrimination.

Absolute atomic hydrogen densities in a radio frequency discharge measured by two-photon laser induced fluorescence imaging

NASA Astrophysics Data System (ADS)

Chérigier, L.; Czarnetzki, U.; Luggenhölscher, D.; Schulz-von der Gathen, V.; Döbele, H. F.

1999-01-01

Absolute atomic hydrogen densities were measured in the gaseous electronics conference reference cell parallel plate reactor by Doppler-free two-photon absorption laser induced fluorescence spectroscopy (TALIF) at λ=205 nm. The capacitively coupled radio frequency discharge was operated at 13.56 MHz in pure hydrogen under various input power and pressure conditions. The Doppler-free excitation technique with an unfocused laser beam together with imaging the fluorescence radiation by an intensified charge coupled device camera allows instantaneous spatial resolution along the radial direction. Absolute density calibration is obtained with the aid of a flow tube reactor and titration with NO2. The influence of spatial intensity inhomogenities along the laser beam and subsequent fluorescence are corrected by TALIF in xenon. A full mapping of the absolute density distribution between the electrodes was obtained. The detection limit for atomic hydrogen amounts to about 2×1018 m-3. The dissociation degree is of the order of a few percent.

The Use of Electromagnetic Induction Techniques for Soil Mapping

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Doolittle, Jim

2015-04-01

Soils have high natural spatial variability. This has been recognized for a long time, and many methods of mapping that spatial variability have been investigated. One technique that has received considerable attention over the last ~30 years is electromagnetic induction (EMI). Particularly when coupled with modern GPS and GIS systems, EMI techniques have allowed the rapid and relatively inexpensive collection of large spatially-related data sets that can be correlated to soil properties that either directly or indirectly influence electrical conductance in the soil. Soil electrical conductivity is directly controlled by soil water content, soluble salt content, clay content and mineralogy, and temperature. A wide range of indirect controls have been identified, such as soil organic matter content and bulk density; both influence water relationships in the soil. EMI techniques work best in areas where there are large changes in one soil property that influences soil electrical conductance, and don't work as well when soil properties that influence electrical conductance are largely homogenous. This presentation will present examples of situations where EMI techniques were successful as well as a couple of examples of situations where EMI was not so useful in mapping the spatial variability of soil properties. Reasons for both the successes and failures will be discussed.

Geometric Modeling for Computer Vision

DTIC Science & Technology

1974-10-01

within a distance R of a locus X ,Y,Z; spatial uniqueness refers to the property that physical solids can not occupy the same space simultaneously. A...density functions W«p( X ,Y,Z). Unfortunately such density functions can no» be writtrn out for objects such as a typing chair or a plastic horse...be approximated by a surface function 2 = F( X ,Y). For example landscape may be represented by geodetic maps in such a 2-D fashion. By definition, a

The structure, isostasy and gravity field of the Levant continental margin and the southeast Mediterranean area

NASA Astrophysics Data System (ADS)

Segev, Amit; Rybakov, Michael; Lyakhovsky, Vladimir; Hofstetter, Avraham; Tibor, Gidon; Goldshmidt, Vladimir; Ben Avraham, Zvi

2006-10-01

A 3-D layered structure of the Levant and the southeastern Mediterranean lithospheric plates was constructed using interpretations of seismic measurements and borehole data. Structural maps of three principal interfaces, elevation, top basement and the Moho, were constructed for the area studied. This area includes the African, Sinai and Arabian plates, the Herodotus and the Levant marine basins and the Nile sedimentary cone. In addition, an isopach map of the Pliocene sediments, as well as the contemporaneous amount of denuded rock units, was prepared to enable setting up the structural map of the base Pliocene sediment. Variable density distributions are suggested for the sedimentary succession in accord with its composition and compaction. The spatial density distribution in the crystalline crust was calculated by weighting the thicknesses of the lower mafic and the upper felsic crustal layers, with densities of 2.9 g/cm 3 and 2.77 g/cm 3, respectively. Results of the local (Airy) isostatic modeling with compensation on the Moho interface show significant deviations from the local isostasy and require variable density distribution in the upper mantle. Moving the compensation level to the base of the lithosphere (˜ 100 km depth) and adopting density variations in the mantle lithosphere yielded isostatic compensation (± 200 m) over most of the area studied. The spatial pattern obtained of a density distribution with a range of ± 0.05 g/cm 3 is supported by a regional heat flux. Simulations of the flexure (Vening Meinesz) isostasy related to the Pliocene to Recent sedimentary loading and unloading revealed concentric oscillatory negative and positive anomalies mostly related to the Nile sedimentary cone. Such anomalies may explain the rapid subsidence in the Levant Basin and the arching in central Israel, northern Sinai and Egypt during Pliocene-Recent times. Comparison between the observed (Bouguer) gravity and the calculated gravity for the constructed 3-D lithospheric structure, which has variable density distributions, provided a good match and an independent constraint for the large-scale structure suggested and confirmed an oceanic nature for the Levant Basin lithosphere.

High resolution mapping of NO2 column densities along the western shore of Lake Michigan and the Los Angeles Basin during May/June 2017

NASA Astrophysics Data System (ADS)

Judd, L. M.; Al-Saadi, J. A.; Janz, S. J.; Kowalewski, M. G.; Szykman, J.; Swap, R.; Abuhassan, N.; Cede, A.; Valin, L.; Williams, D.; Stanier, C. O.

2017-12-01

The airborne Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) UV/VIS mapping spectrometer was used to make measurements for the Lake Michigan Ozone Study (LMOS) along the western shore of Lake Michigan and for the Student Airborne Research Program (SARP) in the Los Angeles Basin during May and June 2017. This instrument has the capability of retrieving NO2 column densities at sub-urban spatial scales (nominally 250 m x 250 m) and is being used as a testbed for future geostationary air quality retrievals. LMOS was a multi-agency collaborative observational effort to better understand ozone pollution along Lake Michigan's western shore, where coastal monitors exceed current ozone standards. With 21 science flights during the 5-week campaign period, GeoTASO acquired data for constraining emissions along the western coast of Lake Michigan and observed how these emissions dispersed and influenced the local air quality. During SARP flights, GeoTASO was used to map the Los Angeles Basin five times over two days, observing NO2 Differential Slant Column densities (DSCs) ranging from over 50x1015 molecules cm-2 down to GeoTASO's detection limit ( 1.5x1015 molecules cm-2 at 250 m x 250 m). This work presents the spatial distribution of preliminary NO2 DSCs observations over both research areas, and shows how this it changed at hourly to multi-day timescales under varying meteorological conditions. Both LMOS and SARP included coincident column NO2 measurements from networks of ground-based Pandora spectrometers specifically set up for these campaigns, and a comparison of coincident observations will be shown. Consistent features were observed throughout these flights, including continual emission `hot-spots' and the redistribution of NO2 plumes by land-water circulations. One goal of this work is to investigate how the fine spatial features observed (e.g. power plant plumes) will be depicted in satellite observations at coarser spatial resolutions. These results will help the community understand how to interpret space-based observations in areas subject to large NO2 spatial heterogeneity, as well as what we can expect to detect with future geostationary air quality sensors over a range of pollution environments.

[Spatial analysis of road traffic accidents with fatalities in Spain, 2008-2011].

PubMed

Gómez-Barroso, Diana; López-Cuadrado, Teresa; Llácer, Alicia; Palmera Suárez, Rocío; Fernández-Cuenca, Rafael

2015-09-01

To estimate the areas of greatest density of road traffic accidents with fatalities at 24 hours per km(2)/year in Spain from 2008 to 2011, using a geographic information system. Accidents were geocodified using the road and kilometer points where they occurred. The average nearest neighbor was calculated to detect possible clusters and to obtain the bandwidth for kernel density estimation. A total of 4775 accidents were analyzed, of which 73.3% occurred on conventional roads. The estimated average distance between accidents was 1,242 meters, and the average expected distance was 10,738 meters. The nearest neighbor index was 0.11, indicating that there were aggregations of accidents in space. A map showing the kernel density was obtained with a resolution of 1 km(2), which identified the areas of highest density. This methodology allowed a better approximation to locating accident risks by taking into account kilometer points. The map shows areas where there was a greater density of accidents. This could be an advantage in decision-making by the relevant authorities. Copyright © 2014 SESPAS. Published by Elsevier Espana. All rights reserved.

Using Cloud-to-Ground Lightning Climatologies to Initialize Gridded Lightning Threat Forecasts for East Central Florida

NASA Technical Reports Server (NTRS)

Lambert, Winnie; Sharp, David; Spratt, Scott; Volkmer, Matthew

2005-01-01

Each morning, the forecasters at the National Weather Service in Melbourn, FL (NWS MLB) produce an experimental cloud-to-ground (CG) lightning threat index map for their county warning area (CWA) that is posted to their web site (http://www.srh.weather.gov/mlb/ghwo/lightning.shtml) . Given the hazardous nature of lightning in central Florida, especially during the warm season months of May-September, these maps help users factor the threat of lightning, relative to their location, into their daily plans. The maps are color-coded in five levels from Very Low to Extreme, with threat level definitions based on the probability of lightning occurrence and the expected amount of CG activity. On a day in which thunderstorms are expected, there are typically two or more threat levels depicted spatially across the CWA. The locations of relative lightning threat maxima and minima often depend on the position and orientation of the low-level ridge axis, forecast propagation and interaction of sea/lake/outflow boundaries, expected evolution of moisture and stability fields, and other factors that can influence the spatial distribution of thunderstorms over the CWA. The lightning threat index maps are issued for the 24-hour period beginning at 1200 UTC (0700 AM EST) each day with a grid resolution of 5 km x 5 km. Product preparation is performed on the AWIPS Graphical Forecast Editor (GFE), which is the standard NWS platform for graphical editing. Currently, the forecasters create each map manually, starting with a blank map. To improve efficiency of the forecast process, NWS MLB requested that the Applied Meteorology Unit (AMU) create gridded warm season lightning climatologies that could be used as first-guess inputs to initialize lightning threat index maps. The gridded values requested included CG strike densities and frequency of occurrence stratified by synoptic-scale flow regime. The intent is to increase consistency between forecasters while enabling them to focus on the mesoscale detail of the forecast, ultimately benefiting the end-users of the product. Several studies took place at the Florida State University (FSU) and NWS Tallahassee (TAE) for which they created daily flow regimes using Florida 1200 UTC synoptic soundings and CG strike densities from National Lightning Detection Network (NLDN) data. The densities were created on a 2.5 km x 2.5 km grid for every hour of every day during the warm seasons in the years 1989-2004. The grids encompass an area that includes the entire state of Florida and adjacent Atlantic and Gulf of Mexico waters. Personnel at the two organizations provided this data and supporting software for the work performed by the AMU. The densities were first stratified by flow regime, then by time in 1-, 3-, 6-, 12-, and 24-hour increments while maintaining the 2.5 km x 2.5 km grid resolution. A CG frequency of occurrence was calculated for each stratification and grid box by counting the number of days with lightning and dividing by the total number of days in the data set. New CG strike densities were calculated for each stratification and grid box by summing the strike number values over all warm seasons, then normalized by dividing the summed values by the number of lightning days. This makes the densities conditional on whether lightning occurred. The frequency climatology values will be used by forecasters as proxy inputs for lightning prObability, while the density climatology values will be used for CG amount. In addition to the benefits outlined above, these climatologies will provide improved temporal and spatial resolution, expansion of the lightning threat area to include adjacent coastal waters, and potential to extend the forecast to include the day-2 period. This presentation will describe the lightning threat index map, discuss the work done to create the maps initialized with climatological guidance, and show examples of the climatological CG lightning densities and frequencies of occurren based on flow regime.

Delineating recurrent fish spawning habitats in the North Sea

NASA Astrophysics Data System (ADS)

Lelièvre, S.; Vaz, S.; Martin, C. S.; Loots, C.

2014-08-01

The functional value of spawning habitats makes them critically important for the completion of fish life cycles and spawning grounds are now considered to be “essential habitats”. Inter-annual fluctuations in spawning ground distributions of dab (Limanda Limanda), plaice (Pleuronectes platessa), cod (Gadus morhua) and whiting (Merlangius merlangus) were investigated in the southern North Sea and eastern English Channel, from 2006 to 2009. The preferential spawning habitats of these species were modelled using generalised linear models, with egg distribution being used as proxy of spawners' location. Egg spatial and temporal distributions were explored based on six environmental variables: sea surface temperature and salinity, chlorophyll a concentration, depth, bedstress and seabed sediment types. In most cases, egg density was found to be strongly related to these environmental variables. Egg densities were positively correlated with shallow to intermediate depths having low temperature and relatively high salinity. Habitat models were used to map annual, i.e. 2006 to 2009, winter spatial distributions of eggs, for each species separately. Then, annual maps were combined to explore the spatial variability of each species' spawning grounds, and define recurrent, occasional, rare and unfavourable spawning areas. The recurrent spawning grounds of all four species were located in the south-eastern part of the study area, mainly along the Dutch and German coasts. This study contributes knowledge necessary to the spatial management of fishery resources in the area, and may also be used to identify marine areas with particular habitat features that need to be preserved.

Compositional cokriging for mapping the probability risk of groundwater contamination by nitrates.

PubMed

Pardo-Igúzquiza, Eulogio; Chica-Olmo, Mario; Luque-Espinar, Juan A; Rodríguez-Galiano, Víctor

2015-11-01

Contamination by nitrates is an important cause of groundwater pollution and represents a potential risk to human health. Management decisions must be made using probability maps that assess the nitrate concentration potential of exceeding regulatory thresholds. However these maps are obtained with only a small number of sparse monitoring locations where the nitrate concentrations have been measured. It is therefore of great interest to have an efficient methodology for obtaining those probability maps. In this paper, we make use of the fact that the discrete probability density function is a compositional variable. The spatial discrete probability density function is estimated by compositional cokriging. There are several advantages in using this approach: (i) problems of classical indicator cokriging, like estimates outside the interval (0,1) and order relations, are avoided; (ii) secondary variables (e.g. aquifer parameters) can be included in the estimation of the probability maps; (iii) uncertainty maps of the probability maps can be obtained; (iv) finally there are modelling advantages because the variograms and cross-variograms of real variables that do not have the restrictions of indicator variograms and indicator cross-variograms. The methodology was applied to the Vega de Granada aquifer in Southern Spain and the advantages of the compositional cokriging approach were demonstrated. Copyright © 2015 Elsevier B.V. All rights reserved.

Community context and sub-neighborhood scale detail to explain dengue, chikungunya and Zika patterns in Cali, Colombia

PubMed Central

Curtis, Andrew; Buritica, Paola; Ajayakumar, Jayakrishnan; Squires, Robert; Dávalos, Diana; Pacheco, Robinson; Bhatta, Madhav P.; James, Mark A.

2017-01-01

Background Cali, Colombia has experienced chikungunya and Zika outbreaks and hypoendemic dengue. Studies have explained Cali’s dengue patterns but lack the sub-neighborhood-scale detail investigated here. Methods Spatial-video geonarratives (SVG) with Ministry of Health officials and Community Health Workers were collected in hotspots, providing perspective on perceptions of why dengue, chikungunya and Zika hotspots exist, impediments to control, and social outcomes. Using spatial video and Google Street View, sub-neighborhood features possibly contributing to incidence were mapped to create risk surfaces, later compared with dengue, chikungunya and Zika case data. Results SVG captured insights in 24 neighborhoods. Trash and water risks in Calipso were mapped using SVG results. Perceived risk factors included proximity to standing water, canals, poverty, invasions, localized violence and military migration. These risks overlapped case density maps and identified areas that are suitable for transmission but are possibly underreporting to the surveillance system. Conclusion Resulting risk maps with local context could be leveraged to increase vector-control efficiency- targeting key areas of environmental risk. PMID:28767730

The Transition from Diffuse to Dense Gas in Herschel Dust Emission Maps

NASA Astrophysics Data System (ADS)

Goldsmith, Paul

Dense cores in dark clouds are the sites where young stars form. These regions manifest as relatively small (<0.1pc) pockets of cold and dense gas. If we wish to understand the star formation process, we have to understand the physical conditions in dense cores. This has been a main aim of star formation research in the past decade. Today, we do indeed possess a good knowledge of the density and velocity structure of cores, as well as their chemical evolution and physical lifetime. However, we do not understand well how dense cores form out of the diffuse gas clouds surrounding them. It is crucial that we constrain the relationship between dense cores and their environment: if we only understand dense cores, we may be able to understand how individual stars form --- but we would not know how the star forming dense cores themselves come into existence. We therefore propose to obtain data sets that reveal both dense cores and the clouds containing them in the same map. Based on these maps, we will study how dense cores form out of their natal clouds. Since cores form stars, this knowledge is crucial for the development of a complete theoretical and observational understanding of the formation of stars and their planets, as envisioned in NASA's Strategic Science Plan. Fortunately, existing archival data allow to derive exactly the sort of maps we need for our analysis. Here, we describe a program that exclusively builds on PACS and SPIRE dust emission imaging data from the NASA-supported Herschel mission. The degree-sized wide-field Herschel maps of the nearby (<260pc) Polaris Flare and Aquila Rift clouds are ideal for our work. They permit to resolve dense cores (<0.1pc), while the maps also reveal large-scale cloud structure (5pc and larger). We will generate column density maps from these dust emission maps and then run a tree-based hierarchical multi-scale structure analysis on them. Only this procedure permits to exploit the full potential of the maps: we will characterize cloud structure over a vast range of spatial scales. This work has many advantages over previous studies, where information about dense cores and their environment was pieced together using a variety of methods an instruments. Now, the Herschel maps permit for the first time to characterize both molecular clouds and their cores in one shot in a single data set. We use these data to answer a variety of simple yet very important questions. First, we study whether dense cores have sharp boundaries. If such boundaries exist, they would indicate that dense cores have an individual identity well-separate from the near-fractal cloud structure on larger spatial scales. Second, we will --- in very approximate sense --- derive global density gradients for molecular clouds from radii <0.1pc to 5pc and larger. These "synoptic" density gradients provide a useful quantitative description of the relation between cloud material at very different spatial scales. Also, these measurements can be compared to synoptic density gradients derived in the same fashion for theoretical cloud models. Third, we study how dense cores are nested into the "clumps" forming molecular clouds, i.e., we study whether the most massive dense cores in a cloud (<0.1pc) reside in the most massive regions identified on lager spatial scale (1pc and larger). This will show how the properties of dense cores are influenced by their environment. Our study will derive unique constraints to cloud structure. But our small sample forbids to make strong statements. This pilot study does thus prepare future larger efforts. Our entire project builds on data reduction and analysis methods which our team has used in the past. This guarantees a swift completion of the project with predictable efficiency. We present pilot studies that demonstrate that the data and analysis methods are suited to tackle the science goals. This project is thus guaranteed to return significant results.

Measurement of carbon nanotube microstructure relative density by optical attenuation and observation of size-dependent variations.

PubMed

Park, Sei Jin; Schmidt, Aaron J; Bedewy, Mostafa; Hart, A John

2013-07-21

Engineering the density of carbon nanotube (CNT) forest microstructures is vital to applications such as electrical interconnects, micro-contact probes, and thermal interface materials. For CNT forests on centimeter-scale substrates, weight and volume can be used to calculate density. However, this is not suitable for smaller samples, including individual microstructures, and moreover does not enable mapping of spatial density variations within the forest. We demonstrate that the relative mass density of individual CNT microstructures can be measured by optical attenuation, with spatial resolution equaling the size of the focused spot. For this, a custom optical setup was built to measure the transmission of a focused laser beam through CNT microstructures. The transmittance was correlated with the thickness of the CNT microstructures by Beer-Lambert-Bouguer law to calculate the attenuation coefficient. We reveal that the density of CNT microstructures grown by CVD can depend on their size, and that the overall density of arrays of microstructures is affected significantly by run-to-run process variations. Further, we use the technique to quantify the change in CNT microstructure density due to capillary densification. This is a useful and accessible metrology technique for CNTs in future microfabrication processes, and will enable direct correlation of density to important properties such as stiffness and electrical conductivity.

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.

Complex mountain terrain and disturbance history drive variation in forest aboveground live carbon density in the western Oregon Cascades, USA

PubMed Central

Zald, Harold S.J.; Spies, Thomas A.; Seidl, Rupert; Pabst, Robert J.; Olsen, Keith A.; Steel, E. Ashley

2016-01-01

Forest carbon (C) density varies tremendously across space due to the inherent heterogeneity of forest ecosystems. Variation of forest C density is especially pronounced in mountainous terrain, where environmental gradients are compressed and vary at multiple spatial scales. Additionally, the influence of environmental gradients may vary with forest age and developmental stage, an important consideration as forest landscapes often have a diversity of stand ages from past management and other disturbance agents. Quantifying forest C density and its underlying environmental determinants in mountain terrain has remained challenging because many available data sources lack the spatial grain and ecological resolution needed at both stand and landscape scales. The objective of this study was to determine if environmental factors influencing aboveground live carbon (ALC) density differed between young versus old forests. We integrated aerial light detection and ranging (lidar) data with 702 field plots to map forest ALC density at a grain of 25 m across the H.J. Andrews Experimental Forest, a 6369 ha watershed in the Cascade Mountains of Oregon, USA. We used linear regressions, random forest ensemble learning (RF) and sequential autoregressive modeling (SAR) to reveal how mapped forest ALC density was related to climate, topography, soils, and past disturbance history (timber harvesting and wildfires). ALC increased with stand age in young managed forests, with much greater variation of ALC in relation to years since wildfire in old unmanaged forests. Timber harvesting was the most important driver of ALC across the entire watershed, despite occurring on only 23% of the landscape. More variation in forest ALC density was explained in models of young managed forests than in models of old unmanaged forests. Besides stand age, ALC density in young managed forests was driven by factors influencing site productivity, whereas variation in ALC density in old unmanaged forests was also affected by finer scale topographic conditions associated with sheltered sites. Past wildfires only had a small influence on current ALC density, which may be a result of long times since fire and/or prevalence of non-stand replacing fire. Our results indicate that forest ALC density depends on a suite of multi-scale environmental drivers mediated by complex mountain topography, and that these relationships are dependent on stand age. The high and context-dependent spatial variability of forest ALC density has implications for quantifying forest carbon stores, establishing upper bounds of potential carbon sequestration, and scaling field data to landscape and regional scales. PMID:27041818

Spatial luminescence imaging of dopant incorporation in CdTe Films

DOE PAGES

Guthrey, Harvey; Moseley, John; Colegrove, Eric; ...

2017-01-25

State-of-the-art cathodoluminescence (CL) spectrum imaging with spectrum-per-pixel CL emission mapping is applied to spatially profile how dopant elements are incorporated into Cadmium telluride (CdTe). Emission spectra and intensity monitor the spatial distribution of additional charge carriers through characteristic variations in the CL emission based on computational modeling. Our results show that grain boundaries play a role in incorporating dopants in CdTe exposed to copper, phosphorus, and intrinsic point defects in CdTe. Furthermore, the image analysis provides critical, unique feedback to understand dopant incorporation and activation in the inhomogeneous CdTe material, which has struggled to reach high levels of hole density.

Digital mining claim density map for federal lands in Idaho: 1996

USGS Publications Warehouse

Hyndman, Paul C.; Campbell, Harry W.

1999-01-01

This report describes a digital map generated by the U.S. Geological Survey (USGS) to provide digital spatial mining claim density information for federal lands in Idaho as of March 1997. Mining claim data is earth science information deemed to be relevant to the assessment of historic, current, and future ecological, economic, and social systems. There is no paper map included in this Open-File report. In accordance with the Federal Land Policy and Management Act of 1976 (FLPMA), all unpatented mining claims, mill and tunnel sites must be recorded at the appropriate Bureau of Land Management (BLM) State office. BLM maintains a cumulative computer listing of mining claims in the Mining Claim Recordation System (MCRS) database with locations given by meridian, township, range, and section. A mining claim is considered closed when the claim is relinquished or a formal BLM decision declaring the mining claim null and void has been issued and the appeal period has expired. All other mining claims filed with BLM are considered to be open and actively held. The digital map (figure 1.) with the mining claim density database available in this report are suitable for geographic information system (GIS)-based regional assessments at a scale of 1:100,000 or smaller.

Digital mining claim density map for federal lands in Oregon: 1996

USGS Publications Warehouse

Hyndman, Paul C.; Campbell, Harry W.

1999-01-01

This report describes a digital map generated by the U.S. Geological Survey (USGS) to provide digital spatial mining claim density information for federal lands in Oregon as of March 1997. Mining claim data is earth science information deemed to be relevant to the assessment of historic, current, and future ecological, economic, and social systems. There is no paper map included in this Open-File report. In accordance with the Federal Land Policy and Management Act of 1976 (FLPMA), all unpatented mining claims, mill and tunnel sites must be recorded at the appropriate Bureau of Land Management (BLM) State office. BLM maintains a cumulative computer listing of mining claims in the Mining Claim Recordation System (MCRS) database with locations given by meridian, township, range, and section. A mining claim is considered closed when the claim is relinquished or a formal BLM decision declaring the mining claim null and void has been issued and the appeal period has expired. All other mining claims filed with BLM are considered to be open and actively held. The digital map (figure 1.) with the mining claim density database available in this report are suitable for geographic information system (GIS)-based regional assessments at a scale of 1:100,000 or smaller.

Isostatic gravity map of the Point Sur 30 x 60 quadrangle and adjacent areas, California

USGS Publications Warehouse

Watt, J.T.; Morin, R.L.; Langenheim, V.E.

2011-01-01

This isostatic residual gravity map is part of a regional effort to investigate the tectonics and water resources of the central Coast Range. This map serves as a basis for modeling the shape of basins and for determining the location and geometry of faults in the area. Local spatial variations in the Earth's gravity field (after removing variations caused by instrument drift, earth-tides, latitude, elevation, terrain, and deep crustal structure), as expressed by the isostatic anomaly, reflect the distribution of densities in the mid- to upper crust, which in turn can be related to rock type. Steep gradients in the isostatic gravity field often indicate lithologic or structural boundaries. Gravity highs reflect the Mesozoic granitic and Franciscan Complex basement rocks that comprise both the northwest-trending Santa Lucia and Gabilan Ranges, whereas gravity lows in Salinas Valley and the offshore basins reflect the thick accumulations of low-density alluvial and marine sediment. Gravity lows also occur where there are thick deposits of low-density Monterey Formation in the hills southeast of Arroyo Seco (>2 km, Marion, 1986). Within the map area, isostatic residual gravity values range from approximately -60 mGal offshore in the northern part of the Sur basin to approximately 22 mGal in the Santa Lucia Range.

The influence of landscape features on road development in a loess region, China.

PubMed

Bi, Xiaoli; Wang, Hui; Zhou, Rui

2011-10-01

Many ecologists focus on the effects of roads on landscapes, yet few consider how landscapes affect road systems. In this study, therefore, we quantitatively evaluated how land cover, topography, and building density affected the length density, node density, spatial pattern, and location of roads in Dongzhi Yuan, a typical loess region in China. Landscape factors and roads were mapped using images from SPOT satellite (Système Probatoire d'Observation de la Terre), initiated by the French space agency and a digital elevation model (DEM). Detrended canonical correspondence analysis (DCCA), a useful ordination technique to explain species-environment relations in community ecology, was applied to evaluate the ways in which landscapes may influence roads. The results showed that both farmland area and building density were positively correlated with road variables, whereas gully density and the coefficient of variation (CV of DEM) showed negative correlations. The CV of DEM, farmland area, grassland area, and building density explained variation in node density, length density, and the spatial pattern of roads, whereas gully density and building density explained variation in variables representing road location. In addition, node density, rather than length density, was the primary road variable affected by landscape variables. The results showed that the DCCA was effective in explaining road-landscape relations. Understanding these relations can provide information for landscape managers and transportation planners.

Mapping Seabird Sensitivity to Offshore Wind Farms

PubMed Central

Bradbury, Gareth; Trinder, Mark; Furness, Bob; Banks, Alex N.; Caldow, Richard W. G.; Hume, Duncan

2014-01-01

We present a Geographic Information System (GIS) tool, SeaMaST (Seabird Mapping and Sensitivity Tool), to provide evidence on the use of sea areas by seabirds and inshore waterbirds in English territorial waters, mapping their relative sensitivity to offshore wind farms. SeaMaST is a freely available evidence source for use by all connected to the offshore wind industry and will assist statutory agencies in assessing potential risks to seabird populations from planned developments. Data were compiled from offshore boat and aerial observer surveys spanning the period 1979–2012. The data were analysed using distance analysis and Density Surface Modelling to produce predicted bird densities across a grid covering English territorial waters at a resolution of 3 km×3 km. Coefficients of Variation were estimated for each grid cell density, as an indication of confidence in predictions. Offshore wind farm sensitivity scores were compiled for seabird species using English territorial waters. The comparative risks to each species of collision with turbines and displacement from operational turbines were reviewed and scored separately, and the scores were multiplied by the bird density estimates to produce relative sensitivity maps. The sensitivity maps reflected well the amassed distributions of the most sensitive species. SeaMaST is an important new tool for assessing potential impacts on seabird populations from offshore development at a time when multiple large areas of development are proposed which overlap with many seabird species’ ranges. It will inform marine spatial planning as well as identifying priority areas of sea usage by marine birds. Example SeaMaST outputs are presented. PMID:25210739

Mapping seabird sensitivity to offshore wind farms.

PubMed

Bradbury, Gareth; Trinder, Mark; Furness, Bob; Banks, Alex N; Caldow, Richard W G; Hume, Duncan

2014-01-01

We present a Geographic Information System (GIS) tool, SeaMaST (Seabird Mapping and Sensitivity Tool), to provide evidence on the use of sea areas by seabirds and inshore waterbirds in English territorial waters, mapping their relative sensitivity to offshore wind farms. SeaMaST is a freely available evidence source for use by all connected to the offshore wind industry and will assist statutory agencies in assessing potential risks to seabird populations from planned developments. Data were compiled from offshore boat and aerial observer surveys spanning the period 1979-2012. The data were analysed using distance analysis and Density Surface Modelling to produce predicted bird densities across a grid covering English territorial waters at a resolution of 3 km×3 km. Coefficients of Variation were estimated for each grid cell density, as an indication of confidence in predictions. Offshore wind farm sensitivity scores were compiled for seabird species using English territorial waters. The comparative risks to each species of collision with turbines and displacement from operational turbines were reviewed and scored separately, and the scores were multiplied by the bird density estimates to produce relative sensitivity maps. The sensitivity maps reflected well the amassed distributions of the most sensitive species. SeaMaST is an important new tool for assessing potential impacts on seabird populations from offshore development at a time when multiple large areas of development are proposed which overlap with many seabird species' ranges. It will inform marine spatial planning as well as identifying priority areas of sea usage by marine birds. Example SeaMaST outputs are presented.

Sustainable and Smart City Planning Using Spatial Data in Wallonia

NASA Astrophysics Data System (ADS)

Stephenne, N.; Beaumont, B.; Hallot, E.; Wolff, E.; Poelmans, L.; Baltus, C.

2016-09-01

Simulating population distribution and land use changes in space and time offer opportunities for smart city planning. It provides a holistic and dynamic vision of fast changing urban environment to policy makers. Impacts, such as environmental and health risks or mobility issues, of policies can be assessed and adapted consequently. In this paper, we suppose that "Smart" city developments should be sustainable, dynamic and participative. This paper addresses these three smart objectives in the context of urban risk assessment in Wallonia, Belgium. The sustainable, dynamic and participative solution includes (i) land cover and land use mapping using remote sensing and GIS, (ii) population density mapping using dasymetric mapping, (iii) predictive modelling of land use changes and population dynamics and (iv) risk assessment. The comprehensive and long-term vision of the territory should help to draw sustainable spatial planning policies, to adapt remote sensing acquisition, to update GIS data and to refine risk assessment from regional to city scale.

An Investigation of the Relationship Between fMRI and ERP Source Localized Measurements of Brain Activity during Face Processing

PubMed Central

Richards, Todd; Webb, Sara Jane; Murias, Michael; Merkle, Kristen; Kleinhans, Natalia M.; Johnson, L. Clark; Poliakov, Andrew; Aylward, Elizabeth; Dawson, Geraldine

2013-01-01

Brain activity patterns during face processing have been extensively explored with functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs). ERP source localization adds a spatial dimension to the ERP time series recordings, which allows for a more direct comparison and integration with fMRI findings. The goals for this study were (1) to compare the spatial descriptions of neuronal activity during face processing obtained with fMRI and ERP source localization using low-resolution electro-magnetic tomography (LORETA), and (2) to use the combined information from source localization and fMRI to explore how the temporal sequence of brain activity during face processing is summarized in fMRI activation maps. fMRI and high-density ERP data were acquired in separate sessions for 17 healthy adult males for a face and object processing task. LORETA statistical maps for the comparison of viewing faces and viewing houses were coregistered and compared to fMRI statistical maps for the same conditions. The spatial locations of face processing-sensitive activity measured by fMRI and LORETA were found to overlap in a number of areas including the bilateral fusiform gyri, the right superior, middle and inferior temporal gyri, and the bilateral precuneus. Both the fMRI and LORETA solutions additionally demon-strated activity in regions that did not overlap. fMRI and LORETA statistical maps of face processing-sensitive brain activity were found to converge spatially primarily at LORETA solution latencies that were within 18 ms of the N170 latency. The combination of data from these techniques suggested that electrical brain activity at the latency of the N170 is highly represented in fMRI statistical maps. PMID:19322649

Comparison of Object-Based Image Analysis Approaches to Mapping New Buildings in Accra, Ghana Using Multi-Temporal QuickBird Satellite Imagery

PubMed Central

Tsai, Yu Hsin; Stow, Douglas; Weeks, John

2013-01-01

The goal of this study was to map and quantify the number of newly constructed buildings in Accra, Ghana between 2002 and 2010 based on high spatial resolution satellite image data. Two semi-automated feature detection approaches for detecting and mapping newly constructed buildings based on QuickBird very high spatial resolution satellite imagery were analyzed: (1) post-classification comparison; and (2) bi-temporal layerstack classification. Feature Analyst software based on a spatial contextual classifier and ENVI Feature Extraction that uses a true object-based image analysis approach of image segmentation and segment classification were evaluated. Final map products representing new building objects were compared and assessed for accuracy using two object-based accuracy measures, completeness and correctness. The bi-temporal layerstack method generated more accurate results compared to the post-classification comparison method due to less confusion with background objects. The spectral/spatial contextual approach (Feature Analyst) outperformed the true object-based feature delineation approach (ENVI Feature Extraction) due to its ability to more reliably delineate individual buildings of various sizes. Semi-automated, object-based detection followed by manual editing appears to be a reliable and efficient approach for detecting and enumerating new building objects. A bivariate regression analysis was performed using neighborhood-level estimates of new building density regressed on a census-derived measure of socio-economic status, yielding an inverse relationship with R2 = 0.31 (n = 27; p = 0.00). The primary utility of the new building delineation results is to support spatial analyses of land cover and land use and demographic change. PMID:24415810

Directional semivariogram analysis to identify and rank controls on the spatial variability of fracture networks

NASA Astrophysics Data System (ADS)

Hanke, John R.; Fischer, Mark P.; Pollyea, Ryan M.

2018-03-01

In this study, the directional semivariogram is deployed to investigate the spatial variability of map-scale fracture network attributes in the Paradox Basin, Utah. The relative variability ratio (R) is introduced as the ratio of integrated anisotropic semivariogram models, and R is shown to be an effective metric for quantifying the magnitude of spatial variability for any two azimuthal directions. R is applied to a GIS-based data set comprising roughly 1200 fractures, in an area which is bounded by a map-scale anticline and a km-scale normal fault. This analysis reveals that proximity to the fault strongly influences the magnitude of spatial variability for both fracture intensity and intersection density within 1-2 km. Additionally, there is significant anisotropy in the spatial variability, which is correlated with trends of the anticline and fault. The direction of minimum spatial correlation is normal to the fault at proximal distances, and gradually rotates and becomes subparallel to the fold axis over the same 1-2 km distance away from the fault. We interpret these changes to reflect varying scales of influence of the fault and the fold on fracture network development: the fault locally influences the magnitude and variability of fracture network attributes, whereas the fold sets the background level and structure of directional variability.

Bridging scale gaps between regional maps of forest aboveground biomass and field sampling plots using TanDEM-X data

NASA Astrophysics Data System (ADS)

Ni, W.; Zhang, Z.; Sun, G.

2017-12-01

Several large-scale maps of forest AGB have been released [1] [2] [3]. However, these existing global or regional datasets were only approximations based on combining land cover type and representative values instead of measurements of actual forest aboveground biomass or forest heights [4]. Rodríguez-Veiga et al[5] reported obvious discrepancies of existing forest biomass stock maps with in-situ observations in Mexico. One of the biggest challenges to the credibility of these maps comes from the scale gaps between the size of field sampling plots used to develop(or validate) estimation models and the pixel size of these maps and the availability of field sampling plots with sufficient size for the verification of these products [6]. It is time-consuming and labor-intensive to collect sufficient number of field sampling data over the plot size of the same as resolutions of regional maps. The smaller field sampling plots cannot fully represent the spatial heterogeneity of forest stands as shown in Figure 1. Forest AGB is directly determined by forest heights, diameter at breast height (DBH) of each tree, forest density and tree species. What measured in the field sampling are the geometrical characteristics of forest stands including the DBH, tree heights and forest densities. The LiDAR data is considered as the best dataset for the estimation of forest AGB. The main reason is that LiDAR can directly capture geometrical features of forest stands by its range detection capabilities.The remotely sensed dataset, which is capable of direct measurements of forest spatial structures, may serve as a ladder to bridge the scale gaps between the pixel size of regional maps of forest AGB and field sampling plots. Several researches report that TanDEM-X data can be used to characterize the forest spatial structures [7, 8]. In this study, the forest AGB map of northeast China were produced using ALOS/PALSAR data taking TanDEM-X data as a bridges. The TanDEM-X InSAR data used in this study and forest AGB map was shown in Figure 2. The technique details and further analysis will be given in the final report. AcknowledgmentThis work was supported in part by the National Basic Research Program of China (Grant No. 2013CB733401, 2013CB733404), and in part by the National Natural Science Foundation of China (Grant Nos. 41471311, 41371357, 41301395).

Influence of macular pigment optical density spatial distribution on intraocular scatter.

PubMed

Putnam, Christopher M; Bland, Pauline J; Bassi, Carl J

This study evaluated the summed measures of macular pigment optical density (MPOD) spatial distribution and their effects on intraocular scatter using a commercially available device (C-Quant, Oculus, USA). A customized heterochromatic flicker photometer (cHFP) device was used to measure MPOD spatial distribution across the central 16° using a 1° stimulus. MPOD was calculated as a discrete measure and summed measures across the central 1°, 3.3°, 10° and 16° diameters. Intraocular scatter was determined as a mean of 5 trials in which reliability and repeatability measures were met using the C-Quant. MPOD spatial distribution maps were constructed and the effects of both discrete and summed values on intraocular scatter were examined. Spatial mapping identified mean values for discrete MPOD [0.32 (s.d.=0.08)], MPOD summed across central 1° [0.37 (s.d.=0.11)], MPOD summed across central 3.3° [0.85 (s.d.=0.20)], MPOD summed across central 10° [1.60 (s.d.=0.35)] and MPOD summed across central 16° [1.78 (s.d.=0.39)]. Mean intraocular scatter was 0.83 (s.d.=0.16) log units. While there were consistent trends for an inverse relationship between MPOD and scatter, these relationships were not statistically significant. Correlations between the highest and lowest quartiles of MPOD within the central 1° were near significance. While there was an overall trend of decreased intraocular forward scatter with increased MPOD consistent with selective short wavelength visible light attenuation, neither discrete nor summed values of MPOD significantly influence intraocular scatter as measured by the C-Quant device. Published by Elsevier España, S.L.U.

A comparison of multiple indicator kriging and area-to-point Poisson kriging for mapping patterns of herbivore species abundance in Kruger National Park, South Africa

PubMed Central

Kerry, Ruth; Goovaerts, Pierre; Smit, Izak P.J.; Ingram, Ben R.

2015-01-01

Kruger National Park (KNP), South Africa, provides protected habitats for the unique animals of the African savannah. For the past 40 years, annual aerial surveys of herbivores have been conducted to aid management decisions based on (1) the spatial distribution of species throughout the park and (2) total species populations in a year. The surveys are extremely time consuming and costly. For many years, the whole park was surveyed, but in 1998 a transect survey approach was adopted. This is cheaper and less time consuming but leaves gaps in the data spatially. Also the distance method currently employed by the park only gives estimates of total species populations but not their spatial distribution. We compare the ability of multiple indicator kriging and area-to-point Poisson kriging to accurately map species distribution in the park. A leave-one-out cross-validation approach indicates that multiple indicator kriging makes poor estimates of the number of animals, particularly the few large counts, as the indicator variograms for such high thresholds are pure nugget. Poisson kriging was applied to the prediction of two types of abundance data: spatial density and proportion of a given species. Both Poisson approaches had standardized mean absolute errors (St. MAEs) of animal counts at least an order of magnitude lower than multiple indicator kriging. The spatial density, Poisson approach (1), gave the lowest St. MAEs for the most abundant species and the proportion, Poisson approach (2), did for the least abundant species. Incorporating environmental data into Poisson approach (2) further reduced St. MAEs. PMID:25729318

A comparison of multiple indicator kriging and area-to-point Poisson kriging for mapping patterns of herbivore species abundance in Kruger National Park, South Africa.

PubMed

Kerry, Ruth; Goovaerts, Pierre; Smit, Izak P J; Ingram, Ben R

Kruger National Park (KNP), South Africa, provides protected habitats for the unique animals of the African savannah. For the past 40 years, annual aerial surveys of herbivores have been conducted to aid management decisions based on (1) the spatial distribution of species throughout the park and (2) total species populations in a year. The surveys are extremely time consuming and costly. For many years, the whole park was surveyed, but in 1998 a transect survey approach was adopted. This is cheaper and less time consuming but leaves gaps in the data spatially. Also the distance method currently employed by the park only gives estimates of total species populations but not their spatial distribution. We compare the ability of multiple indicator kriging and area-to-point Poisson kriging to accurately map species distribution in the park. A leave-one-out cross-validation approach indicates that multiple indicator kriging makes poor estimates of the number of animals, particularly the few large counts, as the indicator variograms for such high thresholds are pure nugget. Poisson kriging was applied to the prediction of two types of abundance data: spatial density and proportion of a given species. Both Poisson approaches had standardized mean absolute errors (St. MAEs) of animal counts at least an order of magnitude lower than multiple indicator kriging. The spatial density, Poisson approach (1), gave the lowest St. MAEs for the most abundant species and the proportion, Poisson approach (2), did for the least abundant species. Incorporating environmental data into Poisson approach (2) further reduced St. MAEs.

Mapping the spatial distribution of star formation in cluster galaxies at z ~0.5 with the Grism Lens-Amplified Survey from Space (GLASS)

NASA Astrophysics Data System (ADS)

Vulcani, Benedetta

2015-08-01

What physical processes regulate star formation in dense environments? Understanding why galaxy evolution is environment dependent is one of the key questions of current astrophysics. I will present the first characterization of the spatial distribution of star formation in cluster galaxies at z~0.5, in order to quantify the role of different physical processes that are believed to be responsible for shutting down star formation. The analysis makes use of data from the Grism Lens-Amplified Survey from Space (GLASS), a large HST cycle-21 program targeting 10 massive galaxy clusters with extensive HST imaging from CLASH and the Frontier Field Initiative. The program consists of 140 primary and 140 parallel orbits of near-infrared WCF3 and optical ACS slitless grism observations, which result in 3D spectroscopy of hundreds of galaxies. The grism data are used to produce spatially resolved maps of the star formation density, while the stellar mass density and optical surface brightness are obtained from multiband imaging. I will describe quantitative measures of the spatial location and extend of the star formation rate, showing that about half of the cluster members with significant Halpha detection have diffused star formation, larger than the optical counterpart. This suggests that star formation occurs out to larger radii than the rest frame continuum. For some systems, nuclear star forming regions are found. I will also present a comparison between the Halpha distribution observed in cluster and field galaxies. The characterization of the spatial distribution of Halpha provides a new window, yet poorly exploited, on the mechanisms that regulate star formation and morphological transformation in dense environments.

Combining binary decision tree and geostatistical methods to estimate snow distribution in a mountain watershed

USGS Publications Warehouse

Balk, Benjamin; Elder, Kelly

2000-01-01

We model the spatial distribution of snow across a mountain basin using an approach that combines binary decision tree and geostatistical techniques. In April 1997 and 1998, intensive snow surveys were conducted in the 6.9‐km2 Loch Vale watershed (LVWS), Rocky Mountain National Park, Colorado. Binary decision trees were used to model the large‐scale variations in snow depth, while the small‐scale variations were modeled through kriging interpolation methods. Binary decision trees related depth to the physically based independent variables of net solar radiation, elevation, slope, and vegetation cover type. These decision tree models explained 54–65% of the observed variance in the depth measurements. The tree‐based modeled depths were then subtracted from the measured depths, and the resulting residuals were spatially distributed across LVWS through kriging techniques. The kriged estimates of the residuals were added to the tree‐based modeled depths to produce a combined depth model. The combined depth estimates explained 60–85% of the variance in the measured depths. Snow densities were mapped across LVWS using regression analysis. Snow‐covered area was determined from high‐resolution aerial photographs. Combining the modeled depths and densities with a snow cover map produced estimates of the spatial distribution of snow water equivalence (SWE). This modeling approach offers improvement over previous methods of estimating SWE distribution in mountain basins.

Rooting strategies in a subtropical savanna: a landscape-scale three-dimensional assessment.

PubMed

Zhou, Yong; Boutton, Thomas W; Wu, X Ben; Wright, Cynthia L; Dion, Anais L

2018-04-01

In resource-limited savannas, the distribution and abundance of fine roots play an important role in acquiring essential resources and structuring vegetation patterns and dynamics. However, little is known regarding the three-dimensional distribution of fine roots in savanna ecosystems at the landscape scale. We quantified spatial patterns of fine root density to a depth of 1.2 m in a subtropical savanna landscape using spatially specific sampling. Kriged maps revealed that fine root density was highest at the centers of woody patches, decreased towards the canopy edges, and reached lowest values within the grassland matrix throughout the entire soil profile. Lacunarity analyses indicated that spatial heterogeneities of fine root density decreased continuously to a depth of 50 cm and then increased in deeper portions of the soil profile across this landscape. This vertical pattern might be related to inherent differences in root distribution between trees/shrubs and herbaceous species, and the presence/absence of an argillic horizon across this landscape. The greater density of fine roots beneath woody patches in both upper and lower portions of the soil profile suggests an ability to acquire disproportionately more resources than herbaceous species, which may facilitate the development and persistence of woody patches across this landscape.

Clustering the Orion B giant molecular cloud based on its molecular emission

PubMed Central

Bron, Emeric; Daudon, Chloé; Pety, Jérôme; Levrier, François; Gerin, Maryvonne; Gratier, Pierre; Orkisz, Jan H.; Guzman, Viviana; Bardeau, Sébastien; Goicoechea, Javier R.; Liszt, Harvey; Öberg, Karin; Peretto, Nicolas; Sievers, Albrecht; Tremblin, Pascal

2017-01-01

Context Previous attempts at segmenting molecular line maps of molecular clouds have focused on using position-position-velocity data cubes of a single molecular line to separate the spatial components of the cloud. In contrast, wide field spectral imaging over a large spectral bandwidth in the (sub)mm domain now allows one to combine multiple molecular tracers to understand the different physical and chemical phases that constitute giant molecular clouds (GMCs). Aims We aim at using multiple tracers (sensitive to different physical processes and conditions) to segment a molecular cloud into physically/chemically similar regions (rather than spatially connected components), thus disentangling the different physical/chemical phases present in the cloud. Methods We use a machine learning clustering method, namely the Meanshift algorithm, to cluster pixels with similar molecular emission, ignoring spatial information. Clusters are defined around each maximum of the multidimensional Probability Density Function (PDF) of the line integrated intensities. Simple radiative transfer models were used to interpret the astrophysical information uncovered by the clustering analysis. Results A clustering analysis based only on the J = 1 – 0 lines of three isotopologues of CO proves suffcient to reveal distinct density/column density regimes (nH ~ 100 cm−3, ~ 500 cm−3, and > 1000 cm−3), closely related to the usual definitions of diffuse, translucent and high-column-density regions. Adding two UV-sensitive tracers, the J = 1 − 0 line of HCO+ and the N = 1 − 0 line of CN, allows us to distinguish two clearly distinct chemical regimes, characteristic of UV-illuminated and UV-shielded gas. The UV-illuminated regime shows overbright HCO+ and CN emission, which we relate to a photochemical enrichment effect. We also find a tail of high CN/HCO+ intensity ratio in UV-illuminated regions. Finer distinctions in density classes (nH ~ 7 × 103 cm−3 ~ 4 × 104 cm−3) for the densest regions are also identified, likely related to the higher critical density of the CN and HCO+ (1 – 0) lines. These distinctions are only possible because the high-density regions are spatially resolved. Conclusions Molecules are versatile tracers of GMCs because their line intensities bear the signature of the physics and chemistry at play in the gas. The association of simultaneous multi-line, wide-field mapping and powerful machine learning methods such as the Meanshift clustering algorithm reveals how to decode the complex information available in these molecular tracers. PMID:29456256

Deriving Continuous Fields of Tree Cover at 1-m over the Continental United States From the National Agriculture Imagery Program (NAIP) Imagery to Reduce Uncertainties in Forest Carbon Stock Estimation

NASA Astrophysics Data System (ADS)

Ganguly, S.; Basu, S.; Mukhopadhyay, S.; Michaelis, A.; Milesi, C.; Votava, P.; Nemani, R. R.

2013-12-01

An unresolved issue with coarse-to-medium resolution satellite-based forest carbon mapping over regional to continental scales is the high level of uncertainty in above ground biomass (AGB) estimates caused by the absence of forest cover information at a high enough spatial resolution (current spatial resolution is limited to 30-m). To put confidence in existing satellite-derived AGB density estimates, it is imperative to create continuous fields of tree cover at a sufficiently high resolution (e.g. 1-m) such that large uncertainties in forested area are reduced. The proposed work will provide means to reduce uncertainty in present satellite-derived AGB maps and Forest Inventory and Analysis (FIA) based regional estimates. Our primary objective will be to create Very High Resolution (VHR) estimates of tree cover at a spatial resolution of 1-m for the Continental United States using all available National Agriculture Imaging Program (NAIP) color-infrared imagery from 2010 till 2012. We will leverage the existing capabilities of the NASA Earth Exchange (NEX) high performance computing and storage facilities. The proposed 1-m tree cover map can be further aggregated to provide percent tree cover at any medium-to-coarse resolution spatial grid, which will aid in reducing uncertainties in AGB density estimation at the respective grid and overcome current limitations imposed by medium-to-coarse resolution land cover maps. We have implemented a scalable and computationally-efficient parallelized framework for tree-cover delineation - the core components of the algorithm [that] include a feature extraction process, a Statistical Region Merging image segmentation algorithm and a classification algorithm based on Deep Belief Network and a Feedforward Backpropagation Neural Network algorithm. An initial pilot exercise has been performed over the state of California (~11,000 scenes) to create a wall-to-wall 1-m tree cover map and the classification accuracy has been assessed. Results show an improvement in accuracy of tree-cover delineation as compared to existing forest cover maps from NLCD, especially over fragmented, heterogeneous and urban landscapes. Estimates of VHR tree cover will complement and enhance the accuracy of present remote-sensing based AGB modeling approaches and forest inventory based estimates at both national and local scales. A requisite step will be to characterize the inherent uncertainties in tree cover estimates and propagate them to estimate AGB.

Mapping and simulating systematics due to spatially-varying observing conditions in DES science verification data

DOE PAGES

Leistedt, B.; Peiris, H. V.; Elsner, F.; ...

2016-10-17

Spatially-varying depth and characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, in particular in deep multi-epoch surveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. Wemore » illustrate the complementarity of these two approaches by comparing the SV data with the BCC-UFig, a synthetic sky catalogue generated by forward-modelling of the DES SV images. We then analyse the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially-varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and well-captured by the maps of observing conditions. The combined use of the maps, the SV data and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on N(z), the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak lensing analyses. However, they will need to be carefully characterised in upcoming phases of DES in order to avoid biasing the inferred cosmological results. The framework presented is relevant to all multi-epoch surveys, and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope, which will require detailed null-tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky.« less

MAPPING AND SIMULATING SYSTEMATICS DUE TO SPATIALLY VARYING OBSERVING CONDITIONS IN DES SCIENCE VERIFICATION DATA

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

Leistedt, B.; Peiris, H. V.; Elsner, F.

Spatially varying depth and the characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, particularly in deep multi-epoch surveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES-SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. Wemore » illustrate the complementary nature of these two approaches by comparing the SV data with BCC-UFig, a synthetic sky catalog generated by forward-modeling of the DES-SV images. We analyze the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and are well-captured by the maps of observing conditions. The combined use of the maps, the SV data, and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on N(z), the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak-lensing analyses. However, they will need to be carefully characterized in upcoming phases of DES in order to avoid biasing the inferred cosmological results. The framework presented here is relevant to all multi-epoch surveys and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope, which will require detailed null tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky« less

Mapping and simulating systematics due to spatially-varying observing conditions in DES science verification data

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

Leistedt, B.; Peiris, H. V.; Elsner, F.

Spatially-varying depth and characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, in particular in deep multi-epoch surveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. Wemore » illustrate the complementarity of these two approaches by comparing the SV data with the BCC-UFig, a synthetic sky catalogue generated by forward-modelling of the DES SV images. We then analyse the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially-varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and well-captured by the maps of observing conditions. The combined use of the maps, the SV data and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on N(z), the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak lensing analyses. However, they will need to be carefully characterised in upcoming phases of DES in order to avoid biasing the inferred cosmological results. The framework presented is relevant to all multi-epoch surveys, and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope, which will require detailed null-tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky.« less

Method for Pre-Conditioning a Measured Surface Height Map for Model Validation

NASA Technical Reports Server (NTRS)

Sidick, Erkin

2012-01-01

This software allows one to up-sample or down-sample a measured surface map for model validation, not only without introducing any re-sampling errors, but also eliminating the existing measurement noise and measurement errors. Because the re-sampling of a surface map is accomplished based on the analytical expressions of Zernike-polynomials and a power spectral density model, such re-sampling does not introduce any aliasing and interpolation errors as is done by the conventional interpolation and FFT-based (fast-Fourier-transform-based) spatial-filtering method. Also, this new method automatically eliminates the measurement noise and other measurement errors such as artificial discontinuity. The developmental cycle of an optical system, such as a space telescope, includes, but is not limited to, the following two steps: (1) deriving requirements or specs on the optical quality of individual optics before they are fabricated through optical modeling and simulations, and (2) validating the optical model using the measured surface height maps after all optics are fabricated. There are a number of computational issues related to model validation, one of which is the "pre-conditioning" or pre-processing of the measured surface maps before using them in a model validation software tool. This software addresses the following issues: (1) up- or down-sampling a measured surface map to match it with the gridded data format of a model validation tool, and (2) eliminating the surface measurement noise or measurement errors such that the resulted surface height map is continuous or smoothly-varying. So far, the preferred method used for re-sampling a surface map is two-dimensional interpolation. The main problem of this method is that the same pixel can take different values when the method of interpolation is changed among the different methods such as the "nearest," "linear," "cubic," and "spline" fitting in Matlab. The conventional, FFT-based spatial filtering method used to eliminate the surface measurement noise or measurement errors can also suffer from aliasing effects. During re-sampling of a surface map, this software preserves the low spatial-frequency characteristic of a given surface map through the use of Zernike-polynomial fit coefficients, and maintains mid- and high-spatial-frequency characteristics of the given surface map by the use of a PSD model derived from the two-dimensional PSD data of the mid- and high-spatial-frequency components of the original surface map. Because this new method creates the new surface map in the desired sampling format from analytical expressions only, it does not encounter any aliasing effects and does not cause any discontinuity in the resultant surface map.

Breast density characterization using texton distributions.

PubMed

Petroudi, Styliani; Brady, Michael

2011-01-01

Breast density has been shown to be one of the most significant risks for developing breast cancer, with women with dense breasts at four to six times higher risk. The Breast Imaging Reporting and Data System (BI-RADS) has a four class classification scheme that describes the different breast densities. However, there is great inter and intra observer variability among clinicians in reporting a mammogram's density class. This work presents a novel texture classification method and its application for the development of a completely automated breast density classification system. The new method represents the mammogram using textons, which can be thought of as the building blocks of texture under the operational definition of Leung and Malik as clustered filter responses. The new proposed method characterizes the mammographic appearance of the different density patterns by evaluating the texton spatial dependence matrix (TDSM) in the breast region's corresponding texton map. The TSDM is a texture model that captures both statistical and structural texture characteristics. The normalized TSDM matrices are evaluated for mammograms from the different density classes and corresponding texture models are established. Classification is achieved using a chi-square distance measure. The fully automated TSDM breast density classification method is quantitatively evaluated on mammograms from all density classes from the Oxford Mammogram Database. The incorporation of texton spatial dependencies allows for classification accuracy reaching over 82%. The breast density classification accuracy is better using texton TSDM compared to simple texton histograms.

Bulk tank milk prevalence and production losses, spatial analysis, and predictive risk mapping of Ostertagia ostertagi infections in Mexican cattle herds.

PubMed

Villa-Mancera, Abel; Pastelín-Rojas, César; Olivares-Pérez, Jaime; Córdova-Izquierdo, Alejandro; Reynoso-Palomar, Alejandro

2018-05-01

This study investigated the prevalence, production losses, spatial clustering, and predictive risk mapping in different climate zones in five states of Mexico. The bulk tank milk samples obtained between January and April 2015 were analyzed for antibodies against Ostertagia ostertagi using the Svanovir ELISA. A total of 1204 farm owners or managers answered the questionnaire. The overall herd prevalence and mean optical density ratio (ODR) of parasite were 61.96% and 0.55, respectively. Overall, the production loss was approximately 0.542 kg of milk per parasited cow per day (mean ODR = 0.92, 142 farms, 11.79%). The spatial disease cluster analysis using SatScan software indicated that two high-risk clusters were observed. In the multivariable analysis, three models were tested for potential association with the ELISA results supported by climatic, environmental, and management factors. The final logistic regression model based on both climatic/environmental and management variables included the factors rainfall, elevation, land surface temperature (LST) day, and parasite control program that were significantly associated with an increased risk of infection. Geostatistical kriging was applied to generate a risk map for the presence of parasite in dairy cattle herds in Mexico. The results indicate that climatic and meteorological factors had a higher potential impact on the spatial distribution of O. ostertagi than the management factors.

Seismo-electromagnetic anomalies observed by Fomosat-1 and GIM TEC during January 27 1999 to July 2004

NASA Astrophysics Data System (ADS)

Yu, C. Y.; Liu, J. Y. G.

2014-12-01

In this study, we examine the pre-earthquake ionospheric anomalies (PEIAs) by the electron density (Ne) and ion temperature (Ti) observed by FORMOSAT-1 (ROCSAT-1) satellite during magnitude greater than 7.0 worldwide earthquakes during 1999-2004. Meanwhile, PEIAs is also currently investigated to have a better understanding of the spatial distribution of the ROCSAT-1 SIPs. Total electron density (TEC) of the global ionosphere map (GIM) confirm that the anomalous feature appear near the epicenters before the earthquakes.

Global mapping of highly pathogenic avian influenza H5N1 and H5Nx clade 2.3.4.4 viruses with spatial cross-validation

PubMed Central

Dhingra, Madhur S; Artois, Jean; Robinson, Timothy P; Linard, Catherine; Chaiban, Celia; Xenarios, Ioannis; Engler, Robin; Liechti, Robin; Kuznetsov, Dmitri; Xiao, Xiangming; Dobschuetz, Sophie Von; Claes, Filip; Newman, Scott H; Dauphin, Gwenaëlle; Gilbert, Marius

2016-01-01

Global disease suitability models are essential tools to inform surveillance systems and enable early detection. We present the first global suitability model of highly pathogenic avian influenza (HPAI) H5N1 and demonstrate that reliable predictions can be obtained at global scale. Best predictions are obtained using spatial predictor variables describing host distributions, rather than land use or eco-climatic spatial predictor variables, with a strong association with domestic duck and extensively raised chicken densities. Our results also support a more systematic use of spatial cross-validation in large-scale disease suitability modelling compared to standard random cross-validation that can lead to unreliable measure of extrapolation accuracy. A global suitability model of the H5 clade 2.3.4.4 viruses, a group of viruses that recently spread extensively in Asia and the US, shows in comparison a lower spatial extrapolation capacity than the HPAI H5N1 models, with a stronger association with intensively raised chicken densities and anthropogenic factors. DOI: http://dx.doi.org/10.7554/eLife.19571.001 PMID:27885988

A ubiquitous method for street scale spatial data collection and analysis in challenging urban environments: mapping health risks using spatial video in Haiti

PubMed Central

2013-01-01

Background Fine-scale and longitudinal geospatial analysis of health risks in challenging urban areas is often limited by the lack of other spatial layers even if case data are available. Underlying population counts, residential context, and associated causative factors such as standing water or trash locations are often missing unless collected through logistically difficult, and often expensive, surveys. The lack of spatial context also hinders the interpretation of results and designing intervention strategies structured around analytical insights. This paper offers a ubiquitous spatial data collection approach using a spatial video that can be used to improve analysis and involve participatory collaborations. A case study will be used to illustrate this approach with three health risks mapped at the street scale for a coastal community in Haiti. Methods Spatial video was used to collect street and building scale information, including standing water, trash accumulation, presence of dogs, cohort specific population characteristics, and other cultural phenomena. These data were digitized into Google Earth and then coded and analyzed in a GIS using kernel density and spatial filtering approaches. The concentrations of these risks around area schools which are sometimes sources of diarrheal disease infection because of the high concentration of children and variable sanitary practices will show the utility of the method. In addition schools offer potential locations for cholera education interventions. Results Previously unavailable fine scale health risk data vary in concentration across the town, with some schools being proximate to greater concentrations of the mapped risks. The spatial video is also used to validate coded data and location specific risks within these “hotspots”. Conclusions Spatial video is a tool that can be used in any environment to improve local area health analysis and intervention. The process is rapid and can be repeated in study sites through time to track spatio-temporal dynamics of the communities. Its simplicity should also be used to encourage local participatory collaborations. PMID:23587358

A ubiquitous method for street scale spatial data collection and analysis in challenging urban environments: mapping health risks using spatial video in Haiti.

PubMed

Curtis, Andrew; Blackburn, Jason K; Widmer, Jocelyn M; Morris, J Glenn

2013-04-15

Fine-scale and longitudinal geospatial analysis of health risks in challenging urban areas is often limited by the lack of other spatial layers even if case data are available. Underlying population counts, residential context, and associated causative factors such as standing water or trash locations are often missing unless collected through logistically difficult, and often expensive, surveys. The lack of spatial context also hinders the interpretation of results and designing intervention strategies structured around analytical insights. This paper offers a ubiquitous spatial data collection approach using a spatial video that can be used to improve analysis and involve participatory collaborations. A case study will be used to illustrate this approach with three health risks mapped at the street scale for a coastal community in Haiti. Spatial video was used to collect street and building scale information, including standing water, trash accumulation, presence of dogs, cohort specific population characteristics, and other cultural phenomena. These data were digitized into Google Earth and then coded and analyzed in a GIS using kernel density and spatial filtering approaches. The concentrations of these risks around area schools which are sometimes sources of diarrheal disease infection because of the high concentration of children and variable sanitary practices will show the utility of the method. In addition schools offer potential locations for cholera education interventions. Previously unavailable fine scale health risk data vary in concentration across the town, with some schools being proximate to greater concentrations of the mapped risks. The spatial video is also used to validate coded data and location specific risks within these "hotspots". Spatial video is a tool that can be used in any environment to improve local area health analysis and intervention. The process is rapid and can be repeated in study sites through time to track spatio-temporal dynamics of the communities. Its simplicity should also be used to encourage local participatory collaborations.

Modeling shape and topology of low-resolution density maps of biological macromolecules.

PubMed Central

De-Alarcón, Pedro A; Pascual-Montano, Alberto; Gupta, Amarnath; Carazo, Jose M

2002-01-01

In the present work we develop an efficient way of representing the geometry and topology of volumetric datasets of biological structures from medium to low resolution, aiming at storing and querying them in a database framework. We make use of a new vector quantization algorithm to select the points within the macromolecule that best approximate the probability density function of the original volume data. Connectivity among points is obtained with the use of the alpha shapes theory. This novel data representation has a number of interesting characteristics, such as 1) it allows us to automatically segment and quantify a number of important structural features from low-resolution maps, such as cavities and channels, opening the possibility of querying large collections of maps on the basis of these quantitative structural features; 2) it provides a compact representation in terms of size; 3) it contains a subset of three-dimensional points that optimally quantify the densities of medium resolution data; and 4) a general model of the geometry and topology of the macromolecule (as opposite to a spatially unrelated bunch of voxels) is easily obtained by the use of the alpha shapes theory. PMID:12124252

ON GALACTIC DENSITY MODELING IN THE PRESENCE OF DUST EXTINCTION

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

Bovy, Jo; Rix, Hans-Walter; Schlafly, Edward F.

Inferences about the spatial density or phase-space structure of stellar populations in the Milky Way require a precise determination of the effective survey volume. The volume observed by surveys such as Gaia or near-infrared spectroscopic surveys, which have good coverage of the Galactic midplane region, is highly complex because of the abundant small-scale structure in the three-dimensional interstellar dust extinction. We introduce a novel framework for analyzing the importance of small-scale structure in the extinction. This formalism demonstrates that the spatially complex effect of extinction on the selection function of a pencil-beam or contiguous sky survey is equivalent to amore » low-pass filtering of the extinction-affected selection function with the smooth density field. We find that the angular resolution of current 3D extinction maps is sufficient for analyzing Gaia sub-samples of millions of stars. However, the current distance resolution is inadequate and needs to be improved by an order of magnitude, especially in the inner Galaxy. We also present a practical and efficient method for properly taking the effect of extinction into account in analyses of Galactic structure through an effective selection function. We illustrate its use with the selection function of red-clump stars in APOGEE using and comparing a variety of current 3D extinction maps.« less

Spatial and Global Sensory Suppression Mapping Encompassing the Central 10° Field in Anisometropic Amblyopia.

PubMed

Li, Jingjing; Li, Jinrong; Chen, Zidong; Liu, Jing; Yuan, Junpeng; Cai, Xiaoxiao; Deng, Daming; Yu, Minbin

2017-01-01

We investigate the efficacy of a novel dichoptic mapping paradigm in evaluating visual function of anisometropic amblyopes. Using standard clinical measures of visual function (visual acuity, stereo acuity, Bagolini lenses, and neutral density filters) and a novel quantitative mapping technique, 26 patients with anisometropic amblyopia (mean age = 19.15 ± 4.42 years) were assessed. Two additional psychophysical interocular suppression measurements were tested with dichoptic global motion coherence and binocular phase combination tasks. Luminance reduction was achieved by placing neutral density filters in front of the normal eye. Our study revealed that suppression changes across the central 10° visual field by mean luminance modulation in amblyopes as well as normal controls. Using simulation and an elimination of interocular suppression, we identified a novel method to effectively reflect the distribution of suppression in anisometropic amblyopia. Additionally, the new quantitative mapping technique was in good agreement with conventional clinical measures, such as interocular acuity difference (P < 0.001) and stereo acuity (P = 0.005). There was a good consistency between the results of interocular suppression with dichoptic mapping paradigm and the results of the other two psychophysical methods (suppression mapping versus binocular phase combination, P < 0.001; suppression mapping versus global motion coherence, P = 0.005). The dichoptic suppression mapping technique is an effective method to represent impaired visual function in patients with anisometropic amblyopia. It offers a potential in "micro-"antisuppression mapping tests and therapies for amblyopia.

Characterization of the spatial variability of soil available zinc at various sampling densities using grouped soil type information.

PubMed

Song, Xiao-Dong; Zhang, Gan-Lin; Liu, Feng; Li, De-Cheng; Zhao, Yu-Guo

2016-11-01

The influence of anthropogenic activities and natural processes involved high uncertainties to the spatial variation modeling of soil available zinc (AZn) in plain river network regions. Four datasets with different sampling densities were split over the Qiaocheng district of Bozhou City, China. The difference of AZn concentrations regarding soil types was analyzed by the principal component analysis (PCA). Since the stationarity was not indicated and effective ranges of four datasets were larger than the sampling extent (about 400 m), two investigation tools, namely F3 test and stationarity index (SI), were employed to test the local non-stationarity. Geographically weighted regression (GWR) technique was performed to describe the spatial heterogeneity of AZn concentrations under the non-stationarity assumption. GWR based on grouped soil type information (GWRG for short) was proposed so as to benefit the local modeling of soil AZn within each soil-landscape unit. For reference, the multiple linear regression (MLR) model, a global regression technique, was also employed and incorporated the same predictors as in the GWR models. Validation results based on 100 times realization demonstrated that GWRG outperformed MLR and can produce similar or better accuracy than the GWR approach. Nevertheless, GWRG can generate better soil maps than GWR for limit soil data. Two-sample t test of produced soil maps also confirmed significantly different means. Variogram analysis of the model residuals exhibited weak spatial correlation, rejecting the use of hybrid kriging techniques. As a heuristically statistical method, the GWRG was beneficial in this study and potentially for other soil properties.

Poultry, pig and the risk of BSE following the feed ban in France--a spatial analysis.

PubMed

Abrial, David; Calavas, Didier; Jarrige, Nathalie; Ducrot, Christian

2005-01-01

A spatial analysis was carried out in order to analyse the reason why the risk of Bovine Spongiform Encephalopathy (BSE) was spatially heterogeneous in France, during the period following the feed ban of Meat and Bone Meal to cattle. The hypothesis of cross-contamination between cattle feedstuff and monogastric feedstuff, which was strongly suggested from previous investigations, was assessed, with the assumption that the higher the pig or poultry density is in a given area, the higher the risk of cross-contamination and cattle infection might be. The data concerned the 467 BSE cases born in France after the ban of meat and bone meal (July 1990) and detected between July 1st, 2001 and December 31, 2003, when the surveillance system was optimal and not spatially biased. The disease mapping models were elaborated with the Bayesian graphical modelling methods and based on a Poisson distribution with spatial smoothing (hierarchical approach) and covariates. The parameters were estimated by a Markov Chain Monte Carlo simulation method. The main result was that the poultry density did not significantly influence the risk of BSE whereas the pig density was significantly associated with an increase in the risk of 2.4% per 10 000 pigs. The areas with a significant pig effect were located in regions with a high pig density as well as a high ratio of pigs to cattle. Despite the absence of a global effect of poultry density on the BSE risk, some areas had a significant poultry effect and the risk was better explained in some others when considering both pig and poultry densities. These findings were in agreement with the hypothesis of cross-contamination, which could take place at the feedstuff factory, during the shipment of food or on the farm. Further studies are needed to more precisely explore how the cross-contamination happened.

SU-G-JeP2-02: A Unifying Multi-Atlas Approach to Electron Density Mapping Using Multi-Parametric MRI for Radiation Treatment Planning

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

Ren, S; Tianjin University, Tianjin; Hara, W

Purpose: MRI has a number of advantages over CT as a primary modality for radiation treatment planning (RTP). However, one key bottleneck problem still remains, which is the lack of electron density information in MRI. In the work, a reliable method to map electron density is developed by leveraging the differential contrast of multi-parametric MRI. Methods: We propose a probabilistic Bayesian approach for electron density mapping based on T1 and T2-weighted MRI, using multiple patients as atlases. For each voxel, we compute two conditional probabilities: (1) electron density given its image intensity on T1 and T2-weighted MR images, and (2)more » electron density given its geometric location in a reference anatomy. The two sources of information (image intensity and spatial location) are combined into a unifying posterior probability density function using the Bayesian formalism. The mean value of the posterior probability density function provides the estimated electron density. Results: We evaluated the method on 10 head and neck patients and performed leave-one-out cross validation (9 patients as atlases and remaining 1 as test). The proposed method significantly reduced the errors in electron density estimation, with a mean absolute HU error of 138, compared with 193 for the T1-weighted intensity approach and 261 without density correction. For bone detection (HU>200), the proposed method had an accuracy of 84% and a sensitivity of 73% at specificity of 90% (AUC = 87%). In comparison, the AUC for bone detection is 73% and 50% using the intensity approach and without density correction, respectively. Conclusion: The proposed unifying method provides accurate electron density estimation and bone detection based on multi-parametric MRI of the head with highly heterogeneous anatomy. This could allow for accurate dose calculation and reference image generation for patient setup in MRI-based radiation treatment planning.« less

Spatial mapping and statistical reproducibility of an array of 256 one-dimensional quantum wires

NASA Astrophysics Data System (ADS)

Al-Taie, H.; Smith, L. W.; Lesage, A. A. J.; See, P.; Griffiths, J. P.; Beere, H. E.; Jones, G. A. C.; Ritchie, D. A.; Kelly, M. J.; Smith, C. G.

2015-08-01

We utilize a multiplexing architecture to measure the conductance properties of an array of 256 split gates. We investigate the reproducibility of the pinch off and one-dimensional definition voltage as a function of spatial location on two different cooldowns, and after illuminating the device. The reproducibility of both these properties on the two cooldowns is high, the result of the density of the two-dimensional electron gas returning to a similar state after thermal cycling. The spatial variation of the pinch-off voltage reduces after illumination; however, the variation of the one-dimensional definition voltage increases due to an anomalous feature in the center of the array. A technique which quantifies the homogeneity of split-gate properties across the array is developed which captures the experimentally observed trends. In addition, the one-dimensional definition voltage is used to probe the density of the wafer at each split gate in the array on a micron scale using a capacitive model.

Spatially-explicit models of global tree density.

PubMed

Glick, Henry B; Bettigole, Charlie; Maynard, Daniel S; Covey, Kristofer R; Smith, Jeffrey R; Crowther, Thomas W

2016-08-16

Remote sensing and geographic analysis of woody vegetation provide means of evaluating the distribution of natural resources, patterns of biodiversity and ecosystem structure, and socio-economic drivers of resource utilization. While these methods bring geographic datasets with global coverage into our day-to-day analytic spheres, many of the studies that rely on these strategies do not capitalize on the extensive collection of existing field data. We present the methods and maps associated with the first spatially-explicit models of global tree density, which relied on over 420,000 forest inventory field plots from around the world. This research is the result of a collaborative effort engaging over 20 scientists and institutions, and capitalizes on an array of analytical strategies. Our spatial data products offer precise estimates of the number of trees at global and biome scales, but should not be used for local-level estimation. At larger scales, these datasets can contribute valuable insight into resource management, ecological modelling efforts, and the quantification of ecosystem services.

A GIS/Remote Sensing-based methodology for groundwater potentiality assessment in Tirnavos area, Greece

NASA Astrophysics Data System (ADS)

Oikonomidis, D.; Dimogianni, S.; Kazakis, N.; Voudouris, K.

2015-06-01

The aim of this paper is to assess the groundwater potentiality combining Geographic Information Systems and Remote Sensing with data obtained from the field, as an additional tool to the hydrogeological research. The present study was elaborated in the broader area of Tirnavos, covering 419.4 km2. The study area is located in Thessaly (central Greece) and is crossed by two rivers, Pinios and Titarisios. Agriculture is one of the main elements of Thessaly's economy resulting in intense agricultural activity and consequently increased exploitation of groundwater resources. Geographic Information Systems (GIS) and Remote Sensing (RS) were used in order to create a map that depicts the likelihood of existence of groundwater, consisting of five classes, showing the groundwater potentiality and ranging from very high to very low. The extraction of this map is based on the study of input data such as: rainfall, potential recharge, lithology, lineament density, slope, drainage density and depth to groundwater. Weights were assigned to all these factors according to their relevance to groundwater potential and eventually a map based on weighted spatial modeling system was created. Furthermore, a groundwater quality suitability map was illustrated by overlaying the groundwater potentiality map with the map showing the potential zones for drinking groundwater in the study area. The results provide significant information and the maps could be used from local authorities for groundwater exploitation and management.

One map policy (OMP) implementation strategy to accelerate mapping of regional spatial planing (RTRW) in Indonesia

NASA Astrophysics Data System (ADS)

Hasyim, Fuad; Subagio, Habib; Darmawan, Mulyanto

2016-06-01

A preparation of spatial planning documents require basic geospatial information and thematic accuracies. Recently these issues become important because spatial planning maps are impartial attachment of the regional act draft on spatial planning (PERDA). The needs of geospatial information in the preparation of spatial planning maps preparation can be divided into two major groups: (i). basic geospatial information (IGD), consist of of Indonesia Topographic maps (RBI), coastal and marine environmental maps (LPI), and geodetic control network and (ii). Thematic Geospatial Information (IGT). Currently, mostly local goverment in Indonesia have not finished their regulation draft on spatial planning due to some constrain including technical aspect. Some constrain in mapping of spatial planning are as follows: the availability of large scale ofbasic geospatial information, the availability of mapping guidelines, and human resources. Ideal conditions to be achieved for spatial planning maps are: (i) the availability of updated geospatial information in accordance with the scale needed for spatial planning maps, (ii) the guideline of mapping for spatial planning to support local government in completion their PERDA, and (iii) capacity building of local goverment human resources to completed spatial planning maps. The OMP strategies formulated to achieve these conditions are: (i) accelerating of IGD at scale of 1:50,000, 1: 25,000 and 1: 5,000, (ii) to accelerate mapping and integration of Thematic Geospatial Information (IGT) through stocktaking availability and mapping guidelines, (iii) the development of mapping guidelines and dissemination of spatial utilization and (iv) training of human resource on mapping technology.

Spatial heterogeneity and temporal evolution of malaria transmission risk in Dakar, Senegal, according to remotely sensed environmental data.

PubMed

Machault, Vanessa; Vignolles, Cécile; Pagès, Frédéric; Gadiaga, Libasse; Gaye, Abdoulaye; Sokhna, Cheikh; Trape, Jean-François; Lacaux, Jean-Pierre; Rogier, Christophe

2010-09-03

The United Nations forecasts that by 2050, more than 60% of the African population will live in cities. Thus, urban malaria is considered an important emerging health problem in that continent. Remote sensing (RS) and geographic information systems (GIS) are useful tools for addressing the challenge of assessing, understanding and spatially focusing malaria control activities. The objectives of the present study were to use high spatial resolution SPOT (Satellite Pour l'Observation de la Terre) satellite images to identify some urban environmental factors in Dakar associated with Anopheles arabiensis densities, to assess the persistence of these associations and to describe spatial changes in at-risk environments using a decadal time scale. Two SPOT images from the 1996 and 2007 rainy seasons in Dakar were processed to extract environmental factors, using supervised classification of land use and land cover, and a calculation of NDVI (Normalized Difference Vegetation Index) and distance to vegetation. Linear regressions were fitted to identify the ecological factors associated with An. arabiensis aggressiveness measured in 1994-97 in the South and centre districts of Dakar. Risk maps for populated areas were computed and compared for 1996 and 2007 using the results of the statistical models. Almost 60% of the variability in anopheline aggressiveness measured in 1994-97 was explained with only one variable: the built-up area in a 300-m radius buffer around the catching points. This association remained stable between 1996 and 2007. Risk maps were drawn by inverting the statistical association. The total increase of the built-up areas in Dakar was about 30% between 1996 and 2007. In proportion to the total population of the city, the population at high risk for malaria fell from 32% to 20%, whereas the low-risk population rose from 29 to 41%. Environmental data retrieved from high spatial resolution SPOT satellite images were associated with An. arabiensis densities in Dakar urban setting, which allowed to generate malaria transmission risk maps. The evolution of the risk was quantified, and the results indicated there are benefits of urbanization in Dakar, since the proportion of the low risk population increased while urbanization progressed.

Modelling Soil-Landscapes in Coastal California Hills Using Fine Scale Terrestrial Lidar

NASA Astrophysics Data System (ADS)

Prentice, S.; Bookhagen, B.; Kyriakidis, P. C.; Chadwick, O.

2013-12-01

Digital elevation models (DEMs) are the dominant input to spatially explicit digital soil mapping (DSM) efforts due to their increasing availability and the tight coupling between topography and soil variability. Accurate characterization of this coupling is dependent on DEM spatial resolution and soil sampling density, both of which may limit analyses. For example, DEM resolution may be too coarse to accurately reflect scale-dependent soil properties yet downscaling introduces artifactual uncertainty unrelated to deterministic or stochastic soil processes. We tackle these limitations through a DSM effort that couples moderately high density soil sampling with a very fine scale terrestrial lidar dataset (20 cm) implemented in a semiarid rolling hillslope domain where terrain variables change rapidly but smoothly over short distances. Our guiding hypothesis is that in this diffusion-dominated landscape, soil thickness is readily predicted by continuous terrain attributes coupled with catenary hillslope segmentation. We choose soil thickness as our keystone dependent variable for its geomorphic and hydrologic significance, and its tendency to be a primary input to synthetic ecosystem models. In defining catenary hillslope position we adapt a logical rule-set approach that parses common terrain derivatives of curvature and specific catchment area into discrete landform elements (LE). Variograms and curvature-area plots are used to distill domain-scale terrain thresholds from short range order noise characteristic of very fine-scale spatial data. The revealed spatial thresholds are used to condition LE rule-set inputs, rendering a catenary LE map that leverages the robustness of fine-scale terrain data to create a generalized interpretation of soil geomorphic domains. Preliminary regressions show that continuous terrain variables alone (curvature, specific catchment area) only partially explain soil thickness, and only in a subset of soils. For example, at spatial scales up 20, curvature explains 40% of soil thickness variance among soils <3 m deep, while soils >3 m deep show no clear relation to curvature. To further demonstration our geomorphic segmentation approach, we apply it to DEM domains where diffusion processes are less dominant than in our primary study area. Classified landform map derived from fine scale terrestrial lidar. Color classes depict hydrogeomorphic process domains in zero order watersheds.

Bedrock mapping of buried valley networks using seismic reflection and airborne electromagnetic data

NASA Astrophysics Data System (ADS)

Oldenborger, G. A.; Logan, C. E.; Hinton, M. J.; Pugin, A. J.-M.; Sapia, V.; Sharpe, D. R.; Russell, H. A. J.

2016-05-01

In glaciated terrain, buried valleys often host aquifers that are significant groundwater resources. However, given the range of scales, spatial complexity and depth of burial, buried valleys often remain undetected or insufficiently mapped. Accurate and thorough mapping of bedrock topography is a crucial step in detecting and delineating buried valleys and understanding formative valley processes. We develop a bedrock mapping procedure supported by the combination of seismic reflection data and helicopter time-domain electromagnetic data with water well records for the Spiritwood buried valley aquifer system in Manitoba, Canada. The limited spatial density of water well bedrock observations precludes complete depiction of the buried valley bedrock topography and renders the water well records alone inadequate for accurate hydrogeological model building. Instead, we leverage the complementary strengths of seismic reflection and airborne electromagnetic data for accurate local detection of the sediment-bedrock interface and for spatially extensive coverage, respectively. Seismic reflection data are used to define buried valley morphology in cross-section beneath survey lines distributed over a regional area. A 3D model of electrical conductivity is derived from inversion of the airborne electromagnetic data and used to extrapolate buried valley morphology over the entire survey area. A spatially variable assignment of the electrical conductivity at the bedrock surface is applied to different features of the buried valley morphology identified in the seismic cross-sections. Electrical conductivity is then used to guide construction of buried valley shapes between seismic sections. The 3D locus of points defining each morphological valley feature is constructed using a path optimization routine that utilizes deviation from the assigned electrical conductivities as the cost function. Our resulting map represents a bedrock surface of unprecedented detail with more complexity than has been suggested by previous investigations. Our procedure is largely data-driven with an adaptable degree of expert user input that provides a clear protocol for incorporating different types of geophysical data into the bedrock mapping procedure.

Differences in Looking at Own- and Other-Race Faces Are Subtle and Analysis-Dependent: An Account of Discrepant Reports.

PubMed

Arizpe, Joseph; Kravitz, Dwight J; Walsh, Vincent; Yovel, Galit; Baker, Chris I

2016-01-01

The Other-Race Effect (ORE) is the robust and well-established finding that people are generally poorer at facial recognition of individuals of another race than of their own race. Over the past four decades, much research has focused on the ORE because understanding this phenomenon is expected to elucidate fundamental face processing mechanisms and the influence of experience on such mechanisms. Several recent studies of the ORE in which the eye-movements of participants viewing own- and other-race faces were tracked have, however, reported highly conflicting results regarding the presence or absence of differential patterns of eye-movements to own- versus other-race faces. This discrepancy, of course, leads to conflicting theoretical interpretations of the perceptual basis for the ORE. Here we investigate fixation patterns to own- versus other-race (African and Chinese) faces for Caucasian participants using different analysis methods. While we detect statistically significant, though subtle, differences in fixation pattern using an Area of Interest (AOI) approach, we fail to detect significant differences when applying a spatial density map approach. Though there were no significant differences in the spatial density maps, the qualitative patterns matched the results from the AOI analyses reflecting how, in certain contexts, Area of Interest (AOI) analyses can be more sensitive in detecting the differential fixation patterns than spatial density analyses, due to spatial pooling of data with AOIs. AOI analyses, however, also come with the limitation of requiring a priori specification. These findings provide evidence that the conflicting reports in the prior literature may be at least partially accounted for by the differences in the statistical sensitivity associated with the different analysis methods employed across studies. Overall, our results suggest that detection of differences in eye-movement patterns can be analysis-dependent and rests on the assumptions inherent in the given analysis.

Differences in Looking at Own- and Other-Race Faces Are Subtle and Analysis-Dependent: An Account of Discrepant Reports

PubMed Central

Arizpe, Joseph; Kravitz, Dwight J.; Walsh, Vincent; Yovel, Galit; Baker, Chris I.

2016-01-01

The Other-Race Effect (ORE) is the robust and well-established finding that people are generally poorer at facial recognition of individuals of another race than of their own race. Over the past four decades, much research has focused on the ORE because understanding this phenomenon is expected to elucidate fundamental face processing mechanisms and the influence of experience on such mechanisms. Several recent studies of the ORE in which the eye-movements of participants viewing own- and other-race faces were tracked have, however, reported highly conflicting results regarding the presence or absence of differential patterns of eye-movements to own- versus other-race faces. This discrepancy, of course, leads to conflicting theoretical interpretations of the perceptual basis for the ORE. Here we investigate fixation patterns to own- versus other-race (African and Chinese) faces for Caucasian participants using different analysis methods. While we detect statistically significant, though subtle, differences in fixation pattern using an Area of Interest (AOI) approach, we fail to detect significant differences when applying a spatial density map approach. Though there were no significant differences in the spatial density maps, the qualitative patterns matched the results from the AOI analyses reflecting how, in certain contexts, Area of Interest (AOI) analyses can be more sensitive in detecting the differential fixation patterns than spatial density analyses, due to spatial pooling of data with AOIs. AOI analyses, however, also come with the limitation of requiring a priori specification. These findings provide evidence that the conflicting reports in the prior literature may be at least partially accounted for by the differences in the statistical sensitivity associated with the different analysis methods employed across studies. Overall, our results suggest that detection of differences in eye-movement patterns can be analysis-dependent and rests on the assumptions inherent in the given analysis. PMID:26849447

Official crime data versus collaborative crime mapping at a Brazilian city

NASA Astrophysics Data System (ADS)

Brito, P. L.; Jesus, E. G. V.; Sant'Ana, R. M. S.; Martins, C.; Delgado, J. P. M.; Fernandes, V. O.

2014-11-01

In July of 2013 a group of undergraduate students from the Federal University of Bahia, Brazil, published a collaborative web map called "Where I Was Robbed". Their initial efforts in publicizing their web map were restricted to announce it at a local radio as a tool of social interest. In two months the map had almost 10.000 reports, 155 reports per day and people from more the 350 cities had already reported a crime. The present study consists in an investigation about this collaborative web map spatial correlation to official robbery data registered at the Secretary of Public Safety database, for the city of Salvador, Bahia. Kernel density estimator combined with map algebra was used to the investigation. Spatial correlations with official robbery data for the city of Salvador were not found initially, but after standardizing collaborative data and mining official registers, both data pointed at very similar areas as the main hot spots for pedestrian robbery. Both areas are located at two of the most economical active areas of the city, although web map crimes reports were more concentrated in an area with higher income population. This results and discussions indicates that this collaborative application is been used mainly by mid class and upper class parcel of the city population, but can still provide significant information on public safety priority areas. Therefore, extended divulgation, on local papers, radio and TV, of the collaborative crime map application and partnership with official agencies are strongly recommended.

2-D Density and Directional Analysis of Fault Systems in the Zagros Region (Iran) on a Regional Scale

NASA Astrophysics Data System (ADS)

Hashemi, Seyed Naser; Baizidi, Chavare

2018-04-01

In this paper, 2-D spatial variation of the frequency and length density and frequency-length relation of large-scale faults in the Zagros region (Iran), as a typical fold-and-thrust belt, were examined. Moreover, the directional analysis of these faults as well as the scale dependence of the orientations was studied. For this purpose, a number of about 8000 faults with L ≥ 1.0 km were extracted from the geological maps covering the region, and then, the data sets were analyzed. The overall pattern of the frequency/length distribution of the total faults of the region acceptably fits with a power-law relation with exponent 1.40, with an obvious change in the gradient in L = 12.0 km. In addition, maps showing the spatial variation of fault densities over the region indicate that the maximum values of the frequency and length density of the faults are attributed to the northeastern part of the region and parallel to the suture zone, respectively, and the fault density increases towards the central parts of the belt. Moreover, the directional analysis of the fault trends gives a dominant preferred orientation trend of 300°-330° and the assessment of the scale dependence of the fault directions demonstrates that larger faults show higher degrees of preferred orientations. As a result, it is concluded that the evolutionary path of the faulting process in this region can be explained by increasing the number of faults rather than the growth in the fault lengths and also it seems that the regional-scale faults in this region are generated by a nearly steady-state tectonic stress regime.

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.

From Head to Sword: The Clustering Properties of Stars in Orion

NASA Astrophysics Data System (ADS)

Gomez, Mercedes; Lada, Charles J.

1998-04-01

We investigate the structure in the spatial distributions of optically selected samples of young stars in the Head (lambda Orionis) and in the Sword (Orion A) regions of the constellation of Orion with the aid of stellar surface density maps and the two-point angular correlation function. The distributions of young stars in both regions are found to be nonrandom and highly clustered. Stellar surface density maps reveal three distinct clusters in the lambda Ori region. The two-point correlation function displays significant features at angular scales that correspond to the radii and separations of the three clusters identified in the surface density maps. Most young stars in the lambda Ori region (~80%) are presently found within these three clusters, consistent with the idea that the majority of young stars in this region were formed in dense protostellar clusters that have significantly expanded since their formation. Over a scale of ~0.05d-0.5d the correlation function is well described by a single power law that increases smoothly with decreasing angular scale. This suggests that, within the clusters, the stars either are themselves hierarchically clustered or have a volume density distribution that falls steeply with radius. The relative lack of Hα emission-line stars in the one cluster in this region that contains OB stars suggests a timescale for emission-line activity of less than 4 Myr around late-type stars in the cluster and may indicate that the lifetimes of protoplanetary disks around young stellar objects are reduced in clusters containing O stars. The spatial distribution of young stars in the Orion A region is considerably more complex. The angular correlation function of the OB stars (which are mostly foreground to the Orion A molecular cloud) is very similar to that of the Hα stars (which are located mostly within the molecular cloud) and significantly different from that of the young stars in the lambda Ori region. This suggests that, although spatially separated, both populations in the Orion A region may have originated from a similar fragmentation process. Stellar surface density maps and modeling of the angular correlation function suggest that somewhat less than half of the OB and Hα stars in the Orion A cloud are presently within well-defined stellar clusters. Although all the OB stars could have originated in rich clusters, a significant fraction of the Hα stars appear to have formed outside such clusters in a more spatially dispersed manner. The close similarity of the angular correlation functions of the OB and Hα stars toward the molecular cloud, in conjunction with the earlier indications of a relatively high star formation rate and high gas pressure in this cloud, is consistent with the idea that older, foreground OB stars triggered the current episode of star formation in the Orion A cloud. One of the OB clusters (Upper Sword) that is foreground to the cloud does not appear to be associated with any of the clusterings of emission-line stars, again suggesting a timescale (<4 Myr) for emission-line activity and disk lifetimes around late-type stars born in OB clusters.

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.

Producing a satellite-derived map and modelling Spartina alterniflora expansion for Willapa Bay in Washington State

NASA Astrophysics Data System (ADS)

Berlin, Cynthia Jane

1998-12-01

This research addresses the identification of the areal extent of the intertidal wetlands of Willapa Bay, Washington, and the evaluation of the potential for exotic Spartina alterniflora (smooth cordgrass) expansion in the bay using a spatial geographic approach. It is hoped that the results will address not only the management needs of the study area but provide a research design that may be applied to studies of other coastal wetlands. Four satellite images, three Landsat Multi-Spectral (MSS) and one Thematic Mapper (TM), are used to derive a map showing areas of water, low, middle and high intertidal, and upland. Two multi-date remote sensing mapping techniques are assessed: a supervised classification using density-slicing and an unsupervised classification using an ISODATA algorithm. Statistical comparisons are made between the resultant derived maps and the U.S.G.S. topographic maps for the Willapa Bay area. The potential for Spartina expansion in the bay is assessed using a sigmoidal (logistic) growth model and a spatial modelling procedure for four possible growth scenarios: without management controls (Business-as-Usual), with moderate management controls (e.g. harvesting to eliminate seed setting), under a hypothetical increase in the growth rate that may reflect favorable environmental changes, and under a hypothetical decrease in the growth rate that may reflect aggressive management controls. Comparisons for the statistics of the two mapping techniques suggest that although the unsupervised classification method performed satisfactorily, the supervised classification (density-slicing) method provided more satisfactory results. Results from the modelling of potential Spartina expansion suggest that Spartina expansion will proceed rapidly for the Business-as-Usual and hypothetical increase in the growth rate scenario, and at a slower rate for the elimination of seed setting and hypothetical decrease in the growth rate scenarios, until all potential habitat is filled.

Examination of ionic wind and cathode sheath effects in a E-field premixed flame with ion density measurements

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

Jacobs, Stewart V., E-mail: svj0001@uah.edu; Xu, Kunning G., E-mail: gabe.xu@uah.edu

2016-04-15

The effect of the ionic wind on a premixed methane-air flame under a DC electric field is studied via mapping of the ion density with Langmuir probes. Ion densities were observed to increase near the burner with increasing electrode voltage up to 6 kV. Past this electrode supply voltage, ion densities ceased increasing and began to decline in some locations within the premixed flame. The increased ion density is caused by an increase in ionic wind force and cathode sheath thickness. The plateau in density is due to the cathode sheath fully encompassing the flame front which is the ion source,more » thereby collecting all ions in the flame. The spatial density data support the ionic wind hypothesis and provide further explanation of its limits based on the plasma sheath.« less

Mapping spatial variation in rock properties in relationship to scale-dependent structure using spectral curvature

NASA Astrophysics Data System (ADS)

Stewart, S. A.; Wynn, T. J.

2000-08-01

Maps of the three-dimensional geometry of geologic surfaces show that structural curvature commonly varies with scale of observation: This fact can be viewed as superposition of structures at different wavelengths. Rock properties such as fracture density and orientation reflect the contribution of superimposed structures. For this reason, characterization of geologic surfaces is fundamentally different from purely geometrical characterization, for which local description of surface properties is sufficient. We show that measured curvature decays according to a power law with increasing size of measurement window, so short-wavelength curvatures do not obscure long-wavelength curvatures in the same data set. This property can be taken advantage of in a simple technique for automatically mapping multiwavelength curvatures. At each point on a surface, curvature is measured at a range of wavelengths. This curvature spectrum can be analyzed in map view or collapsed into a single value at each point in space. The results indicate that complex geologic surfaces can be characterized without any prior knowledge of structural wavelengths and orientation. The method should prove useful in applications requiring knowledge of spatial variation in rock properties from remotely sensed data, such as exploration for hydrocarbon reservoirs or nuclear waste repositories.

Evaluation of bioreactor-cultivated bone by magnetic resonance microscopy and FTIR microspectroscopy.

PubMed

Chesnick, Ingrid E; Avallone, Francis A; Leapman, Richard D; Landis, William J; Eidelman, Naomi; Potter, Kimberlee

2007-04-01

We present a three-dimensional mineralizing model based on a hollow fiber bioreactor (HFBR) inoculated with primary osteoblasts isolated from embryonic chick calvaria. Using non-invasive magnetic resonance microscopy (MRM), the growth and development of the mineralized tissue around the individual fibers were monitored over a period of 9 weeks. Spatial maps of the water proton MRM properties of the intact tissue, with 78 microm resolution, were used to determine changes in tissue composition with development. Unique changes in the mineral and collagen content of the tissue were detected with high specificity by proton density (PD) and magnetization transfer ratio (MTR) maps, respectively. At the end of the growth period, the presence of a bone-like tissue was verified by histology and the formation of poorly crystalline apatite was verified by selected area electron diffraction and electron probe X-ray microanalysis. FTIR microspectroscopy confirmed the heterogeneous nature of the bone-like tissue formed. FTIR-derived phosphate maps confirmed that those locations with the lowest PD values contained the most mineral, and FTIR-derived collagen maps confirmed that bright pixels on MTR maps corresponded to regions of high collagen content. In conclusion, the spatial mapping of tissue constituents by FTIR microspectroscopy corroborated the findings of non-invasive MRM measurements and supported the role of MRM in monitoring the bone formation process in vitro.

Evaluation of Bioreactor-Cultivated Bone by Magnetic Resonance Microscopy and FTIR Microspectroscopy

PubMed Central

Chesnick, Ingrid E.; Avallone, Frank; Leapman, Richard D.; Landis, William J.; Eidelman, Naomi; Potter, Kimberlee

2007-01-01

We present a three-dimensional mineralizing model based on a hollow fiber bioreactor (HFBR) inoculated with primary osteoblasts isolated from embryonic chick calvaria. Using non-invasive magnetic resonance microscopy (MRM), the growth and development of the mineralized tissue around the individual fibers were monitored over a period of nine weeks. Spatial maps of the water proton MRM properties of the intact tissue, with 78 μm resolution, were used to determine changes in tissue composition with development. Unique changes in the mineral and collagen content of the tissue were detected with high specificity by proton density (PD) and magnetization transfer ratio (MTR) maps, respectively. At the end of the growth period, the presence of a bone-like tissue was verified by histology and the formation of poorly crystalline apatite was verified by selected area electron diffraction and electron probe X-ray microanalysis. FTIR microspectroscopy confirmed the heterogeneous nature of the bone-like tissue formed. FTIR-derived phosphate maps confirmed that those locations with the lowest PD values contained the most mineral, and FTIR-derived collagen maps confirmed that bright pixels on MTR maps corresponded to regions of high collagen content. In conclusion, the spatial mapping of tissue constituents by FTIR microspectroscopy corroborated the findings of non-invasive MRM measurements and supported the role of MRM in monitoring the bone formation process in vitro. PMID:17174620

Influence of Topographic and Hydrographic Factors on the Spatial Distribution of Leptospirosis Disease in São Paulo County, Brazil: An Approach Using Geospatial Techniques and GIS Analysis

NASA Astrophysics Data System (ADS)

Ferreira, M. C.; Ferreira, M. F. M.

2016-06-01

Leptospirosis is a zoonosis caused by Leptospira genus bacteria. Rodents, especially Rattus norvegicus, are the most frequent hosts of this microorganism in the cities. The human transmission occurs by contact with urine, blood or tissues of the rodent and contacting water or mud contaminated by rodent urine. Spatial patterns of concentration of leptospirosis are related to the multiple environmental and socioeconomic factors, like housing near flooding areas, domestic garbage disposal sites and high-density of peoples living in slums located near river channels. We used geospatial techniques and geographical information system (GIS) to analysing spatial relationship between the distribution of leptospirosis cases and distance from rivers, river density in the census sector and terrain slope factors, in Sao Paulo County, Brazil. To test this methodology we used a sample of 183 geocoded leptospirosis cases confirmed in 2007, ASTER GDEM2 data, hydrography and census sectors shapefiles. Our results showed that GIS and geospatial analysis techniques improved the mapping of the disease and permitted identify the spatial pattern of association between location of cases and spatial distribution of the environmental variables analyzed. This study showed also that leptospirosis cases might be more related to the census sectors located on higher river density areas and households situated at shorter distances from rivers. In the other hand, it was not possible to assert that slope terrain contributes significantly to the location of leptospirosis cases.

Identifying the driving forces of urban expansion and its environmental impact in Jakarta-Bandung mega urban region

NASA Astrophysics Data System (ADS)

Pravitasari, A. E.; Rustiadi, E.; Mulya, S. P.; Setiawan, Y.; Fuadina, L. N.; Murtadho, A.

2018-05-01

The socio-economic development in Jakarta-Bandung Mega Urban Region (JBMUR) caused the increasing of urban expansion and led to a variety of environmental damage such as uncontrolled land use conversion and raising anthropogenic disaster. The objectives of this study are: (1) to identify the driving forces of urban expansion that occurs on JBMUR and (2) to analyze the environmental quality decline on JBMUR by producing time series spatial distribution map and spatial autocorrelation of floods and landslide as the proxy of anthropogenic disaster. The driving forces of urban expansion in this study were identified by employing Geographically Weighted Regression (GWR) model using 6 (six) independent variables, namely: population density, percentage of agricultural land, distance to the center of capital city/municipality, percentage of household who works in agricultural sector, distance to the provincial road, and distance to the local road. The GWR results showed that local demographic, social and economic factors including distance to the road spatially affect urban expansion in JBMUR. The time series spatial distribution map of floods and landslide event showed the spatial cluster of anthropogenic disaster in some areas. Through Local Moran Index, we found that environmental damage in one location has a significant impact on the condition of its surrounding area.

Complex Spatial Structure in a Population of Didymopanax pittieri, A Tree of Wind-Exposed Lower Montane Rain Forest

NASA Technical Reports Server (NTRS)

Lawton, Robert M.; Lawton, Robert O.

2010-01-01

Didymopanax pittieri is a common shade-intolerant tree colonizing treefall gaps in the elfin forests on windswept ridgecrests in the lower montane rain forests of the Cordillera de Tilarain, Costa Rica. All D. pittieri taller than > 0.5 m in a 5.2-ha elfin forested portion of a gridded study watershed in the Monteverde Cloud Forest Preserve were located, mapped, and measured. This local population of D. pittieri is spatially inhomogeneous, in that density increases with increasing wind exposure; D. pittieri are more abundant near ridge crests than lower on windward slopes. The important and ubiquitous phenomenon of spatial inhomogeneity in population density is addressed and corrected for in spatial analyses by the application of the inhomogeneous version of Ripley's K. The spatial patterns of four size classes of D. pittieri (<5 cm dbh, 5-10 cm dbh, 10-20 cm dbh, and> 20 cm dbh) were investigated. Within the large-scale trend in density driven by wind exposure, D. pittieri saplings are clumped at the scale of treefall gaps and at the scale of patches of aggregated gaps. D. pittieri 5-10 cm dbh are randomly distributed, apparently due to competitive thinning of sapling clumps during the early stages of gap-phase regeneration. D. pittieri larger than 10 cm dbh are overdispersed at a scale larger than that of patches of gaps. Natural disturbance can influence the distribution of shade intolerant tree populations at several different spatial scales, and can have discordant effects at different life history stages.

LORETA imaging of P300 in schizophrenia with individual MRI and 128-channel EEG.

PubMed

Pae, Ji Soo; Kwon, Jun Soo; Youn, Tak; Park, Hae-Jeong; Kim, Myung Sun; Lee, Boreom; Park, Kwang Suk

2003-11-01

We investigated the characteristics of P300 generators in schizophrenics by using voxel-based statistical parametric mapping of current density images. P300 generators, produced by a rare target tone of 1500 Hz (15%) under a frequent nontarget tone of 1000 Hz (85%), were measured in 20 right-handed schizophrenics and 21 controls. Low-resolution electromagnetic tomography (LORETA), using a realistic head model of the boundary element method based on individual MRI, was applied to the 128-channel EEG. Three-dimensional current density images were reconstructed from the LORETA intensity maps that covered the whole cortical gray matter. Spatial normalization and intensity normalization of the smoothed current density images were used to reduce anatomical variance and subject-specific global activity and statistical parametric mapping (SPM) was applied for the statistical analysis. We found that the sources of P300 were consistently localized at the left superior parietal area in normal subjects, while those of schizophrenics were diversely distributed. Upon statistical comparison, schizophrenics, with globally reduced current densities, showed a significant P300 current density reduction in the left medial temporal area and in the left inferior parietal area, while both left prefrontal and right orbitofrontal areas were relatively activated. The left parietotemporal area was found to correlate negatively with Positive and Negative Syndrome Scale total scores of schizophrenic patients. In conclusion, the reduced and increased areas of current density in schizophrenic patients suggest that the medial temporal and frontal areas contribute to the pathophysiology of schizophrenia, the frontotemporal circuitry abnormality.

Shadows and Dust: Mid-Infrared Extinction Mapping of the Initial Conditions of Massive Star and Star Cluster Formation

NASA Astrophysics Data System (ADS)

Tan, Jonathan

We describe a research plan to develop and extend the mid-infrared (MIR) extinction mapping technique presented by Butler & Tan (2009), who studied Infrared Dark Clouds (IRDCs) using Spitzer Space Telescope Infrared Array Camera (IRAC) 8 micron images. This method has the ability to probe the detailed spatial structure of very high column density regions, i.e. the gas clouds thought to represent the initial conditions for massive star and star cluster formation. We will analyze the data Spitzer obtained at other wavelengths, i.e. the IRAC bands at 3.6, 4.5 and 5.8 microns, and the Multiband Imaging Photometer (MIPS) bands, especially at 24 microns. This will allow us to measure the dust extinction law across the MIR and search for evidence of dust grain evolution, e.g. grain growth and ice mantle formation, as a function of gas density and column density. We will also study the detailed structure of the extinction features, including individual cores that may form single stars or close binaries, especially focusing on those cores that may form massive stars. By studying independent dark cores in a given IRDC, we will be able to test if they have a common minimum observed intensity, which we will then attribute to the foreground. This is a new method that should allow us to more accurately map distant, high column density IRDCs, probing more extreme regimes of star formation. We will combine MIR extinction mapping, which works best at high column densities, with near- IR mapping based on 2MASS images of star fields, which is most useful at lower columns that probe the extended giant molecular cloud structure. This information is crucial to help understand the formation process of IRDCs, which may be the rate limiting step for global galactic star formation rates. We will use our new extinction mapping methods to analyze large samples of IRDCs and thus search the Galaxy for the most extreme examples of high column density cores and assess the global star formation efficiency in dense gas. We will estimate the ability of future NASA missions, such as JWST, to carry out MIR extinction mapping science. We will develop the results of this research into an E/PO presentation to be included in the various public outreach events organized and courses taught by the PI.

Predicting the spatial extent of liquefaction from geospatial and earthquake specific parameters

USGS Publications Warehouse

Zhu, Jing; Baise, Laurie G.; Thompson, Eric M.; Wald, David J.; Knudsen, Keith L.; Deodatis, George; Ellingwood, Bruce R.; Frangopol, Dan M.

2014-01-01

The spatially extensive damage from the 2010-2011 Christchurch, New Zealand earthquake events are a reminder of the need for liquefaction hazard maps for anticipating damage from future earthquakes. Liquefaction hazard mapping as traditionally relied on detailed geologic mapping and expensive site studies. These traditional techniques are difficult to apply globally for rapid response or loss estimation. We have developed a logistic regression model to predict the probability of liquefaction occurrence in coastal sedimentary areas as a function of simple and globally available geospatial features (e.g., derived from digital elevation models) and standard earthquake-specific intensity data (e.g., peak ground acceleration). Some of the geospatial explanatory variables that we consider are taken from the hydrology community, which has a long tradition of using remotely sensed data as proxies for subsurface parameters. As a result of using high resolution, remotely-sensed, and spatially continuous data as a proxy for important subsurface parameters such as soil density and soil saturation, and by using a probabilistic modeling framework, our liquefaction model inherently includes the natural spatial variability of liquefaction occurrence and provides an estimate of spatial extent of liquefaction for a given earthquake. To provide a quantitative check on how the predicted probabilities relate to spatial extent of liquefaction, we report the frequency of observed liquefaction features within a range of predicted probabilities. The percentage of liquefaction is the areal extent of observed liquefaction within a given probability contour. The regional model and the results show that there is a strong relationship between the predicted probability and the observed percentage of liquefaction. Visual inspection of the probability contours for each event also indicates that the pattern of liquefaction is well represented by the model.

Geographic Information System Software to Remodel Population Data Using Dasymetric Mapping Methods

USGS Publications Warehouse

Sleeter, Rachel; Gould, Michael

2007-01-01

The U.S. Census Bureau provides decadal demographic data collected at the household level and aggregated to larger enumeration units for anonymity purposes. Although this system is appropriate for the dissemination of large amounts of national demographic data, often the boundaries of the enumeration units do not reflect the distribution of the underlying statistical phenomena. Conventional mapping methods such as choropleth mapping, are primarily employed due to their ease of use. However, the analytical drawbacks of choropleth methods are well known ranging from (1) the artificial transition of population at the boundaries of mapping units to (2) the assumption that the phenomena is evenly distributed across the enumeration unit (when in actuality there can be significant variation). Many methods to map population distribution have been practiced in geographic information systems (GIS) and remote sensing fields. Many cartographers prefer dasymetric mapping to map population because of its ability to more accurately distribute data over geographic space. Similar to ?choropleth maps?, a dasymetric map utilizes standardized data (for example, census data). However, rather than using arbitrary enumeration zones to symbolize population distribution, a dasymetric approach introduces ancillary information to redistribute the standardized data into zones relative to land use and land cover (LULC), taking into consideration actual changing densities within the boundaries of the enumeration unit. Thus, new zones are created that correlate to the function of the map, capturing spatial variations in population density. The transfer of data from census enumeration units to ancillary-driven homogenous zones is performed by a process called areal interpolation.

Mercury Slovenian soils: High, medium and low sample density geochemical maps

NASA Astrophysics Data System (ADS)

Gosar, Mateja; Šajn, Robert; Teršič, Tamara

2017-04-01

Regional geochemical survey was conducted in whole territory of Slovenia (20273 km2). High, medium and low sample density surveys were compared. High sample density represented the regional geochemical data set supplemented by local high-density sampling data (irregular grid, n=2835). Medium-density soil sampling was performed in a 5 x 5 km grid (n=817) and low-density geochemical survey was conducted in a sampling grid 25 x 25 km (n=54). Mercury distribution in Slovenian soils was determined with models of mercury distribution in soil using all three data sets. A distinct Hg anomaly in western part of Slovenia is evident on all three models. It is a consequence of 500-years of mining and ore processing in the second largest mercury mine in the world, the Idrija mine. The determined mercury concentrations revealed an important difference between the western and the eastern parts of the country. For the medium scale geochemical mapping is the median value (0.151 mg /kg) for western Slovenia almost 2-fold higher than the median value (0.083 mg/kg) in eastern Slovenia. Besides the Hg median for the western part of Slovenia exceeds the Hg median for European soil by a factor of 4 (Gosar et al., 2016). Comparing these sample density surveys, it was shown that high sampling density allows the identification and characterization of anthropogenic influences on a local scale, while medium- and low-density sampling reveal general trends in the mercury spatial distribution, but are not appropriate for identifying local contamination in industrial regions and urban areas. The resolution of the pattern generated is the best when the high-density survey on a regional scale is supplemented with the geochemical data of the high-density surveys on a local scale. References: Gosar, M, Šajn, R, Teršič, T. Distribution pattern of mercury in the Slovenian soil: geochemical mapping based on multiple geochemical datasets. Journal of geochemical exploration, 2016, 167/38-48.

Auditory Spatial Attention Representations in the Human Cerebral Cortex

PubMed Central

Kong, Lingqiang; Michalka, Samantha W.; Rosen, Maya L.; Sheremata, Summer L.; Swisher, Jascha D.; Shinn-Cunningham, Barbara G.; Somers, David C.

2014-01-01

Auditory spatial attention serves important functions in auditory source separation and selection. Although auditory spatial attention mechanisms have been generally investigated, the neural substrates encoding spatial information acted on by attention have not been identified in the human neocortex. We performed functional magnetic resonance imaging experiments to identify cortical regions that support auditory spatial attention and to test 2 hypotheses regarding the coding of auditory spatial attention: 1) auditory spatial attention might recruit the visuospatial maps of the intraparietal sulcus (IPS) to create multimodal spatial attention maps; 2) auditory spatial information might be encoded without explicit cortical maps. We mapped visuotopic IPS regions in individual subjects and measured auditory spatial attention effects within these regions of interest. Contrary to the multimodal map hypothesis, we observed that auditory spatial attentional modulations spared the visuotopic maps of IPS; the parietal regions activated by auditory attention lacked map structure. However, multivoxel pattern analysis revealed that the superior temporal gyrus and the supramarginal gyrus contained significant information about the direction of spatial attention. These findings support the hypothesis that auditory spatial information is coded without a cortical map representation. Our findings suggest that audiospatial and visuospatial attention utilize distinctly different spatial coding schemes. PMID:23180753

Spatial capture-recapture models for search-encounter data

USGS Publications Warehouse

Royle, J. Andrew; Kery, Marc; Guelat, Jerome

2011-01-01

1. Spatial capture–recapture models make use of auxiliary data on capture location to provide density estimates for animal populations. Previously, models have been developed primarily for fixed trap arrays which define the observable locations of individuals by a set of discrete points. 2. Here, we develop a class of models for 'search-encounter' data, i.e. for detections of recognizable individuals in continuous space, not restricted to trap locations. In our hierarchical model, detection probability is related to the average distance between individual location and the survey path. The locations are allowed to change over time owing to movements of individuals, and individual locations are related formally by a model describing individual activity or home range centre which is itself regarded as a latent variable in the model. We provide a Bayesian analysis of the model in WinBUGS, and develop a custom MCMC algorithm in the R language. 3. The model is applied to simulated data and to territory mapping data for the Willow Tit from the Swiss Breeding Bird Survey MHB. While the observed density was 15 territories per nominal 1 km2 plot of unknown effective sample area, the model produced a density estimate of 21∙12 territories per square km (95% posterior interval: 17–26). 4. Spatial capture–recapture models are relevant to virtually all animal population studies that seek to estimate population size or density, yet existing models have been proposed mainly for conventional sampling using arrays of traps. Our model for search-encounter data, where the spatial pattern of searching can be arbitrary and may change over occasions, greatly expands the scope and utility of spatial capture–recapture models.

Spatial distribution and health risk assessment of toxic metals associated with receptor population density in street dust: a case study of Xiandao District, Changsha, Middle China.

PubMed

Li, Fei; Huang, Jinhui; Zeng, Guangming; Huang, Xiaolong; Liu, Wenchu; Wu, Haipeng; Yuan, Yujie; He, Xiaoxiao; Lai, Mingyong

2015-05-01

Spatial characteristics of the properties (dust organic material and pH), concentrations, and enrichment levels of toxic metals (Ni, Hg, Mn and As) in street dust from Xiandao District (Middle China) were investigated. Method of incorporating receptor population density into noncarcinogenic health risk assessment based on local land use map and geostatistics was developed to identify their priority pollutants/regions of concern. Mean enrichment factors of studied metals decreased in the order of Hg ≈ As > Mn > Ni. For noncarcinogenic effects, the exposure pathway which resulted in the highest levels of exposure risk for children and adults was ingestion except Hg (inhalation of vapors), followed by dermal contact and inhalation. Hazard indexes (HIs) for As, Hg, Mn, and Ni to children and adults revealed the following order: As > Hg > Mn > Ni. Mean HI for As exceeded safe level (1) for children, and the maximum HI (0.99) for Hg was most approached the safe level. Priority regions of concern were indentified in A region at each residential population density and the areas of B at high and moderate residential population density for As and the high residential density area within A region for Hg, respectively. The developed method was proved useful due to its improvement on previous study for making the priority areas of environmental management spatially hierarchical and thus reducing the probability of excessive environmental management.

The Three-dimensional Spatial Distribution of Interstellar Gas in the Milky Way: Implications for Cosmic Rays and High-energy Gamma-ray Emissions

NASA Astrophysics Data System (ADS)

Jóhannesson, Guđlaugur; Porter, Troy A.; Moskalenko, Igor V.

2018-03-01

Direct measurements of cosmic ray (CR) species combined with observations of their associated γ-ray emissions can be used to constrain models of CR propagation, trace the structure of the Galaxy, and search for signatures of new physics. The spatial density distribution of interstellar gas is a vital element for all these studies. So far, models have employed the 2D cylindrically symmetric geometry, but their accuracy is well behind that of the available data. In this paper, 3D spatial density models for neutral and molecular hydrogen are constructed based on empirical model fitting to gas line-survey data. The developed density models incorporate spiral arms and account for the warping of the disk, and the increasing gas scale height with radial distance from the Galactic center. They are employed together with the GALPROP CR propagation code to investigate how the new 3D gas models affect calculations of CR propagation and high-energy γ-ray intensity maps. The calculations reveal non-trivial features that are directly related to the new gas models. The best-fit values for propagation model parameters employing 3D gas models are presented and they differ significantly from those derived with the 2D gas density models that have been widely used. The combination of 3D CR and gas density models provide a more realistic basis for the interpretation of non-thermal emissions from the Galaxy.

Spatial variation in osteon population density at the human femoral midshaft: histomorphometric adaptations to habitual load environment.

PubMed

Gocha, Timothy P; Agnew, Amanda M

2016-05-01

Intracortical remodeling, and the osteons it produces, is one aspect of the bone microstructure that is influenced by and, in turn, can influence its mechanical properties. Previous research examining the spatial distribution of intracortical remodeling density across the femoral midshaft has been limited to either considering only small regions of the cortex or, when looking at the entirety of the cortex, considering only a single individual. This study examined the spatial distribution of all remodeling events (intact osteons, fragmentary osteons, and resorptive bays) across the entirety of the femoral midshaft in a sample of 30 modern cadaveric donors. The sample consisted of 15 males and 15 females, aged 21-97 years at time of death. Using geographic information systems software, the femoral cortex was subdivided radially into thirds and circumferentially into octants, and the spatial location of all remodeling events was marked. Density maps and calculation of osteon population density in cortical regions of interest revealed that remodeling density is typically highest in the periosteal third of the bone, particularly in the lateral and anterolateral regions of the cortex. Due to modeling drift, this area of the midshaft femur has some of the youngest primary tissue, which consequently reveals that the lateral and anterolateral regions of the femoral midshaft have higher remodeling rates than elsewhere in the cortex. This is likely the result of tension/shear forces and/or greater strain magnitudes acting upon the anterolateral femur, which results in a greater amount of microdamage in need of repair than is seen in the medial and posterior regions of the femoral midshaft, which are more subject to compressive forces and/or lesser strain magnitudes. © 2015 Anatomical Society.

Global patterns of current and future road infrastructure

NASA Astrophysics Data System (ADS)

Meijer, Johan R.; Huijbregts, Mark A. J.; Schotten, Kees C. G. J.; Schipper, Aafke M.

2018-06-01

Georeferenced information on road infrastructure is essential for spatial planning, socio-economic assessments and environmental impact analyses. Yet current global road maps are typically outdated or characterized by spatial bias in coverage. In the Global Roads Inventory Project we gathered, harmonized and integrated nearly 60 geospatial datasets on road infrastructure into a global roads dataset. The resulting dataset covers 222 countries and includes over 21 million km of roads, which is two to three times the total length in the currently best available country-based global roads datasets. We then related total road length per country to country area, population density, GDP and OECD membership, resulting in a regression model with adjusted R 2 of 0.90, and found that that the highest road densities are associated with densely populated and wealthier countries. Applying our regression model to future population densities and GDP estimates from the Shared Socioeconomic Pathway (SSP) scenarios, we obtained a tentative estimate of 3.0–4.7 million km additional road length for the year 2050. Large increases in road length were projected for developing nations in some of the world’s last remaining wilderness areas, such as the Amazon, the Congo basin and New Guinea. This highlights the need for accurate spatial road datasets to underpin strategic spatial planning in order to reduce the impacts of roads in remaining pristine ecosystems.

Stochastic Evolution of Augmented Born-Infeld Equations

NASA Astrophysics Data System (ADS)

Holm, Darryl D.

2018-06-01

This paper compares the results of applying a recently developed method of stochastic uncertainty quantification designed for fluid dynamics to the Born-Infeld model of nonlinear electromagnetism. The similarities in the results are striking. Namely, the introduction of Stratonovich cylindrical noise into each of their Hamiltonian formulations introduces stochastic Lie transport into their dynamics in the same form for both theories. Moreover, the resulting stochastic partial differential equations retain their unperturbed form, except for an additional term representing induced Lie transport by the set of divergence-free vector fields associated with the spatial correlations of the cylindrical noise. The explanation for this remarkable similarity lies in the method of construction of the Hamiltonian for the Stratonovich stochastic contribution to the motion in both cases, which is done via pairing spatial correlation eigenvectors for cylindrical noise with the momentum map for the deterministic motion. This momentum map is responsible for the well-known analogy between hydrodynamics and electromagnetism. The momentum map for the Maxwell and Born-Infeld theories of electromagnetism treated here is the 1-form density known as the Poynting vector. Two appendices treat the Hamiltonian structures underlying these results.

Mapping the Upper Subsurface of MARS Using Radar Polarimetry

NASA Technical Reports Server (NTRS)

Carter, L. M.; Rincon, R.; Berkoski, L.

2012-01-01

Future human exploration of Mars will require detailed knowledge of the surface and upper several meters of the subsurface in potential landing sites. Likewise, many of the Planetary Science Decadal Survey science goals, such as understanding the history of Mars climate change, determining how the surface was altered through processes like volcanism and fluvial activity, and locating regions that may have been hospitable to life in the past, would be significantly advanced through mapping of the upper meters of the surface. Synthetic aperture radar (SAR) is the only remote sensing technique capable of penetrating through meters of material and imaging buried surfaces at high (meters to tens-of-meters) spatial resolution. SAR is capable of mapping the boundaries of buried units and radar polarimetry can provide quantitative information about the roughness of surface and subsurface units, depth of burial of stratigraphic units, and density of materials. Orbital SAR systems can obtain broad coverage at a spatial scale relevant to human and robotic surface operations. A polarimetric SAR system would greatly increase the safety and utility of future landed systems including sample caching.

Ising-like patterns of spatial synchrony in population biology

NASA Astrophysics Data System (ADS)

Noble, Andrew; Hastings, Alan; Machta, Jon

2014-03-01

Systems of coupled dynamical oscillators can undergo a phase transition between synchronous and asynchronous phases. In the case of coupled map lattices, the spontaneous symmetry breaking of a temporal-phase order parameter is known to exhibit Ising-like critical behavior. Here, we investigate a noisy coupled map motivated by the study of spatial synchrony in ecological populations far from the extinction threshold. Ising-like patterns of criticality, as well as spinodal decomposition and homogeneous nucleation, emerge from the nonlinear interactions of environmental fluctuations in habitat quality, local density-dependence in reproduction, and dispersal. In the mean-field limit, the correspondence to the Ising model is exact: the fixed points of our dynamical system are given by the equation of state for Weiss mean-field theory under an appropriate mapping of parameters. We have strong evidence that a quantitative correspondence persists, both near and far from the critical point, in the presence of fluctuations. Our results provide a formal connection between equilibrium statistical physics and population biology. This work is supported by the National Science Foundation under Grant No. 1344187.

Combined Exact-Repeat and Geodetic Mission Altimetry for High-Resolution Empirical Tide Mapping

NASA Astrophysics Data System (ADS)

Zaron, E. D.

2014-12-01

The configuration of present and historical exact-repeat mission (ERM) altimeter ground tracks determines the maximum resolution of empirical tidal maps obtained with ERM data. Although the mode-1 baroclinic tide is resolvable at mid-latitudes in the open ocean, the ability to detect baroclinic and barotropic tides near islands and complex coastlines is limited, in part, by ERM track density. In order to obtain higher resolution maps, the possibility of combining ERM and geodetic mission (GM) altimetry is considered, using a combination of spatial thin-plate splines and temporal harmonic analysis. Given the present spatial and temporal distribution of GM missions, it is found that GM data can contribute to resolving tidal features smaller than 75 km, provided the signal amplitude is greater than about 1 cm. Uncertainties in the mean sea surface and environmental corrections are significant components of the GM error budget, and methods to optimize data selection and along-track filtering are still being optimized. Application to two regions, Monterey Bay and Luzon Strait, finds evidence for complex tidal fields in agreement with independent observations and modeling studies.

Spatial Decomposition of Translational Water–Water Correlation Entropy in Binding Pockets

PubMed Central

2015-01-01

A number of computational tools available today compute the thermodynamic properties of water at surfaces and in binding pockets by using inhomogeneous solvation theory (IST) to analyze explicit-solvent simulations. Such methods enable qualitative spatial mappings of both energy and entropy around a solute of interest and can also be applied quantitatively. However, the entropy estimates of existing methods have, to date, been almost entirely limited to the first-order terms in the IST’s entropy expansion. These first-order terms account for localization and orientation of water molecules in the field of the solute but not for the modification of water–water correlations by the solute. Here, we present an extension of the Grid Inhomogeneous Solvation Theory (GIST) approach which accounts for water–water translational correlations. The method involves rewriting the two-point density of water in terms of a conditional density and utilizes the efficient nearest-neighbor entropy estimation approach. Spatial maps of this second order term, for water in and around the synthetic host cucurbit[7]uril and in the binding pocket of the enzyme Factor Xa, reveal mainly negative contributions, indicating solute-induced water–water correlations relative to bulk water; particularly strong signals are obtained for sites at the entrances of cavities or pockets. This second-order term thus enters with the same, negative, sign as the first order translational and orientational terms. Numerical and convergence properties of the methodology are examined. PMID:26636620

Simulated GOLD Observations of Atmospheric Waves

NASA Astrophysics Data System (ADS)

Correira, J.; Evans, J. S.; Lumpe, J. D.; Rusch, D. W.; Chandran, A.; Eastes, R.; Codrescu, M.

2016-12-01

The Global-scale Observations of the Limb and Disk (GOLD) mission will measure structures in the Earth's airglow layer due to dynamical forcing by vertically and horizontally propagating waves. These measurements focus on global-scale structures, including compositional and temperature responses resulting from dynamical forcing. Daytime observations of far-UV emissions by GOLD will be used to generate two-dimensional maps of the ratio of atomic oxygen and molecular nitrogen column densities (ΣO/N2 ) as well as neutral temperature that provide signatures of large-scale spatial structure. In this presentation, we use simulations to demonstrate GOLD's capability to deduce periodicities and spatial dimensions of large-scale waves from the spatial and temporal evolution observed in composition and temperature maps. Our simulations include sophisticated forward modeling of the upper atmospheric airglow that properly accounts for anisotropy in neutral and ion composition, temperature, and solar illumination. Neutral densities and temperatures used in the simulations are obtained from global circulation and climatology models that have been perturbed by propagating waves with a range of amplitudes, periods, and sources of excitation. Modeling of airglow emission and predictions of ΣO/N2 and neutral temperatures are performed with the Atmospheric Ultraviolet Radiance Integrated Code (AURIC) and associated derived product algorithms. Predicted structure in ΣO/N2 and neutral temperature due to dynamical forcing by propagating waves is compared to existing observations. Realistic GOLD Level 2 data products are generated from simulated airglow emission using algorithm code that will be implemented operationally at the GOLD Science Data Center.

LINDENS: A program for lineament length and density analysis*1

NASA Astrophysics Data System (ADS)

Casas, Antonio M.; Cortés, Angel L.; Maestro, Adolfo; Soriano, M. Asunción; Riaguas, Andres; Bernal, Javier

2000-11-01

Analysis of lineaments from satellite images normally includes the determination of their orientation and density. The spatial variation in the orientation and/or number of lineaments must be obtained by means of a network of cells, the lineaments included in each cell being analysed separately. The program presented in this work, LINDENS, allows the density of lineaments (number of lineaments per km 2 and length of lineaments per km 2) to be estimated. It also provides a tool for classifying the lineaments contained in different cells, so that their orientation can be represented in frequency histograms and/or rose diagrams. The input file must contain the planar coordinates of the beginning and end of each lineament. The density analysis is done by creating a network of square cells, and counting the number of lineaments that are contained within each cell, that have one of their ends within the cell or that cross-cut the cell boundary. The lengths of lineaments are then calculated. To obtain a representative density map the cell size must be fixed according to: (1) the average lineament length; (2) the distance between the lineaments; and (3) the boundaries of zones with low densities due to lithology or outcrop features. An example from the Neogene Duero Basin (Northern Spain) is provided to test the reliability of the density maps obtained with different cell sizes.

Emergence of kinetic behavior in streaming ultracold neutral plasmas

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

McQuillen, P.; Castro, J.; Bradshaw, S. J.

2015-04-15

We create streaming ultracold neutral plasmas by tailoring the photoionizing laser beam that creates the plasma. By varying the electron temperature, we control the relative velocity of the streaming populations, and, in conjunction with variation of the plasma density, this controls the ion collisionality of the colliding streams. Laser-induced fluorescence is used to map the spatially resolved density and velocity distribution function for the ions. We identify the lack of local thermal equilibrium and distinct populations of interpenetrating, counter-streaming ions as signatures of kinetic behavior. Experimental data are compared with results from a one-dimensional, two-fluid numerical simulation.

Digital Mapping of Soil Organic Carbon Contents and Stocks in Denmark

PubMed Central

Adhikari, Kabindra; Hartemink, Alfred E.; Minasny, Budiman; Bou Kheir, Rania; Greve, Mette B.; Greve, Mogens H.

2014-01-01

Estimation of carbon contents and stocks are important for carbon sequestration, greenhouse gas emissions and national carbon balance inventories. For Denmark, we modeled the vertical distribution of soil organic carbon (SOC) and bulk density, and mapped its spatial distribution at five standard soil depth intervals (0−5, 5−15, 15−30, 30−60 and 60−100 cm) using 18 environmental variables as predictors. SOC distribution was influenced by precipitation, land use, soil type, wetland, elevation, wetness index, and multi-resolution index of valley bottom flatness. The highest average SOC content of 20 g kg−1 was reported for 0−5 cm soil, whereas there was on average 2.2 g SOC kg−1 at 60−100 cm depth. For SOC and bulk density prediction precision decreased with soil depth, and a standard error of 2.8 g kg−1 was found at 60−100 cm soil depth. Average SOC stock for 0−30 cm was 72 t ha−1 and in the top 1 m there was 120 t SOC ha−1. In total, the soils stored approximately 570 Tg C within the top 1 m. The soils under agriculture had the highest amount of carbon (444 Tg) followed by forest and semi-natural vegetation that contributed 11% of the total SOC stock. More than 60% of the total SOC stock was present in Podzols and Luvisols. Compared to previous estimates, our approach is more reliable as we adopted a robust quantification technique and mapped the spatial distribution of SOC stock and prediction uncertainty. The estimation was validated using common statistical indices and the data and high-resolution maps could be used for future soil carbon assessment and inventories. PMID:25137066

Digital mapping of soil organic carbon contents and stocks in Denmark.

PubMed

Adhikari, Kabindra; Hartemink, Alfred E; Minasny, Budiman; Bou Kheir, Rania; Greve, Mette B; Greve, Mogens H

2014-01-01

Estimation of carbon contents and stocks are important for carbon sequestration, greenhouse gas emissions and national carbon balance inventories. For Denmark, we modeled the vertical distribution of soil organic carbon (SOC) and bulk density, and mapped its spatial distribution at five standard soil depth intervals (0-5, 5-15, 15-30, 30-60 and 60-100 cm) using 18 environmental variables as predictors. SOC distribution was influenced by precipitation, land use, soil type, wetland, elevation, wetness index, and multi-resolution index of valley bottom flatness. The highest average SOC content of 20 g kg(-1) was reported for 0-5 cm soil, whereas there was on average 2.2 g SOC kg(-1) at 60-100 cm depth. For SOC and bulk density prediction precision decreased with soil depth, and a standard error of 2.8 g kg(-1) was found at 60-100 cm soil depth. Average SOC stock for 0-30 cm was 72 t ha(-1) and in the top 1 m there was 120 t SOC ha(-1). In total, the soils stored approximately 570 Tg C within the top 1 m. The soils under agriculture had the highest amount of carbon (444 Tg) followed by forest and semi-natural vegetation that contributed 11% of the total SOC stock. More than 60% of the total SOC stock was present in Podzols and Luvisols. Compared to previous estimates, our approach is more reliable as we adopted a robust quantification technique and mapped the spatial distribution of SOC stock and prediction uncertainty. The estimation was validated using common statistical indices and the data and high-resolution maps could be used for future soil carbon assessment and inventories.

Remodeling census population with spatial information from Landsat TM imagery

USGS Publications Warehouse

Yuan, Y.; Smith, R.M.; Limp, W.F.

1997-01-01

In geographic information systems (GIS) studies there has been some difficulty integrating socioeconomic and physiogeographic data. One important type of socioeconomic data, census data, offers a wide range of socioeconomic information, but is aggregated within arbitrary enumeration districts (EDs). Values reflect either raw counts or, when standardized, the mean densities in the EDs. On the other hand, remote sensing imagery, an important type of physiogeographic data, provides large quantities of information with more spatial details than census data. Based on the dasymetric mapping principle, this study applies multivariable regression to examine the correlation between population counts from census and land cover types. The land cover map is classified from LandSat TM imagery. The correlation is high. Census population counts are remodeled to a GIS raster layer based on the discovered correlations coupled with scaling techniques, which offset influences from other than land cover types. The GIS raster layer depicts the population distribution with much more spatial detail than census data offer. The resulting GIS raster layer is ready to be analyzed or integrated with other GIS data. ?? 1998 Elsevier Science Ltd. All rights reserved.

Visualizing statistical significance of disease clusters using cartograms.

PubMed

Kronenfeld, Barry J; Wong, David W S

2017-05-15

Health officials and epidemiological researchers often use maps of disease rates to identify potential disease clusters. Because these maps exaggerate the prominence of low-density districts and hide potential clusters in urban (high-density) areas, many researchers have used density-equalizing maps (cartograms) as a basis for epidemiological mapping. However, we do not have existing guidelines for visual assessment of statistical uncertainty. To address this shortcoming, we develop techniques for visual determination of statistical significance of clusters spanning one or more districts on a cartogram. We developed the techniques within a geovisual analytics framework that does not rely on automated significance testing, and can therefore facilitate visual analysis to detect clusters that automated techniques might miss. On a cartogram of the at-risk population, the statistical significance of a disease cluster is determinate from the rate, area and shape of the cluster under standard hypothesis testing scenarios. We develop formulae to determine, for a given rate, the area required for statistical significance of a priori and a posteriori designated regions under certain test assumptions. Uniquely, our approach enables dynamic inference of aggregate regions formed by combining individual districts. The method is implemented in interactive tools that provide choropleth mapping, automated legend construction and dynamic search tools to facilitate cluster detection and assessment of the validity of tested assumptions. A case study of leukemia incidence analysis in California demonstrates the ability to visually distinguish between statistically significant and insignificant regions. The proposed geovisual analytics approach enables intuitive visual assessment of statistical significance of arbitrarily defined regions on a cartogram. Our research prompts a broader discussion of the role of geovisual exploratory analyses in disease mapping and the appropriate framework for visually assessing the statistical significance of spatial clusters.

Validating national landslide susceptibility and hazard maps for Caribbean island countries: the case of Dominica and tropical storm Erika.

NASA Astrophysics Data System (ADS)

van Westen, Cees; Jetten, Victor; Alkema, Dinand

2016-04-01

The aim of this study was to generate national-scale landslide susceptibility and hazard maps for four Caribbean islands, as part of the World Bank project CHARIM (Caribbean Handbook on Disaster Geoinformation Management, www.charim.net). This paper focuses on the results for the island country of Dominica, located in the Eastern part of the Caribbean, in-between Guadalupe and Martinique. The available data turned out to be insufficient to generate reliable results. We therefore generated a new database of disaster events for Dominica using all available data, making use of many different sources. We compiled landslide inventories for five recent rainfall events from the maintenance records of the Ministry of Public Works, and generated a completely new landslide inventory using multi-temporal visual image interpretation, and generated an extensive landslide database for Dominica. We analyzed the triggering conditions for landslides as far as was possible given the available data, and generated rainfall magnitude-frequency relations. We applied a method for landslide susceptibility assessment which combined bi-variate statistical analysis, that provided indications on the importance of the possible contributing factors, with an expert-based iterative weighing approach using Spatial Multi-Criteria Evaluation. The method is transparent, as the stakeholders (e.g. the engineers and planners from the four countries) and other consultants can consult the criteria trees and evaluate the standardization and weights, and make adjustments. The landslide susceptibility map was converted into a landslide hazard map using landslide density and frequencies for so called major, moderate and minor triggering events. The landslide hazard map was produced in May 2015. A major rainfall event occurred on Dominica following the passage of tropical storm Erika on 26 to 28 August 2015. An event-based landslide inventory for this event was produced by UNOSAT using very high resolution optical images, and an additional field-based inventory was obtained from BRGM. These were used to analyze the predictive capabilities of the national-scale landslide susceptibility and hazard maps. Although the spatial patterns of the landslide susceptibility map was fairly accurate in predicting the locations of the landslides triggered by the recent tropical storm, the landslide densities and related frequencies used for the hazard assessment turned out to deviate considerably taking into account the spatial landslide pattern and estimated frequency of rainfall for tropical storm Erika. This study demonstrates the importance of reconstructing landslide inventories for a variety of triggering events, and the requirement of including landslide inventory data of a major event in the hazard assessment.

Ionospheric tomography by gradient-enhanced kriging with STEC measurements and ionosonde characteristics

NASA Astrophysics Data System (ADS)

Minkwitz, David; van den Boogaart, Karl Gerald; Gerzen, Tatjana; Hoque, Mainul; Hernández-Pajares, Manuel

2016-11-01

The estimation of the ionospheric electron density by kriging is based on the optimization of a parametric measurement covariance model. First, the extension of kriging with slant total electron content (STEC) measurements based on a spatial covariance to kriging with a spatial-temporal covariance model, assimilating STEC data of a sliding window, is presented. Secondly, a novel tomography approach by gradient-enhanced kriging (GEK) is developed. Beyond the ingestion of STEC measurements, GEK assimilates ionosonde characteristics, providing peak electron density measurements as well as gradient information. Both approaches deploy the 3-D electron density model NeQuick as a priori information and estimate the covariance parameter vector within a maximum likelihood estimation for the dedicated tomography time stamp. The methods are validated in the European region for two periods covering quiet and active ionospheric conditions. The kriging with spatial and spatial-temporal covariance model is analysed regarding its capability to reproduce STEC, differential STEC and foF2. Therefore, the estimates are compared to the NeQuick model results, the 2-D TEC maps of the International GNSS Service and the DLR's Ionospheric Monitoring and Prediction Center, and in the case of foF2 to two independent ionosonde stations. Moreover, simulated STEC and ionosonde measurements are used to investigate the electron density profiles estimated by the GEK in comparison to a kriging with STEC only. The results indicate a crucial improvement in the initial guess by the developed methods and point out the potential compensation for a bias in the peak height hmF2 by means of GEK.

Liana abundance, diversity, and distribution on Barro Colorado Island, Panama.

PubMed

Schnitzer, Stefan A; Mangan, Scott A; Dalling, James W; Baldeck, Claire A; Hubbell, Stephen P; Ledo, Alicia; Muller-Landau, Helene; Tobin, Michael F; Aguilar, Salomon; Brassfield, David; Hernandez, Andres; Lao, Suzanne; Perez, Rolando; Valdes, Oldemar; Yorke, Suzanne Rutishauser

2012-01-01

Lianas are a key component of tropical forests; however, most surveys are too small to accurately quantify liana community composition, diversity, abundance, and spatial distribution - critical components for measuring the contribution of lianas to forest processes. In 2007, we tagged, mapped, measured the diameter, and identified all lianas ≥1 cm rooted in a 50-ha plot on Barro Colorado Island, Panama (BCI). We calculated liana density, basal area, and species richness for both independently rooted lianas and all rooted liana stems (genets plus clones). We compared spatial aggregation patterns of liana and tree species, and among liana species that varied in the amount of clonal reproduction. We also tested whether liana and tree densities have increased on BCI compared to surveys conducted 30-years earlier. This study represents the most comprehensive spatially contiguous sampling of lianas ever conducted and, over the 50 ha area, we found 67,447 rooted liana stems comprising 162 species. Rooted lianas composed nearly 25% of the woody stems (trees and lianas), 35% of woody species richness, and 3% of woody basal area. Lianas were spatially aggregated within the 50-ha plot and the liana species with the highest proportion of clonal stems more spatially aggregated than the least clonal species, possibly indicating clonal stem recruitment following canopy disturbance. Over the past 30 years, liana density increased by 75% for stems ≥1 cm diameter and nearly 140% for stems ≥5 cm diameter, while tree density on BCI decreased 11.5%; a finding consistent with other neotropical forests. Our data confirm that lianas contribute substantially to tropical forest stem density and diversity, they have highly clumped distributions that appear to be driven by clonal stem recruitment into treefall gaps, and they are increasing relative to trees, thus indicating that lianas will play a greater role in the future dynamics of BCI and other neotropical forests.

Are we failing to protect threatened mangroves in the Sundarbans world heritage ecosystem?

PubMed

Sarker, Swapan K; Reeve, Richard; Thompson, Jill; Paul, Nirmal K; Matthiopoulos, Jason

2016-02-16

The Sundarbans, the largest mangrove ecosystem in the world, is under threat from historical and future human exploitation and sea level rise. Limited scientific knowledge on the spatial ecology of the mangroves in this world heritage ecosystem has been a major impediment to conservation efforts. Here, for the first time, we report on habitat suitability analyses and spatial density maps for the four most prominent mangrove species--Heritiera fomes, Excoecaria agallocha, Ceriops decandra and Xylocarpus mekongensis. Globally endangered H. fomes abundances declined as salinity increased. Responses to nutrients, elevation, and stem density varied between species. H. fomes and X. mekongensis preferred upstream habitats. E. agallocha and C. decandra preferred down-stream and mid-stream habitats. Historical harvesting had negative influences on H. fomes, C. decandra and X. mekongensis abundances. The established protected area network does not support the most suitable habitats of these threatened species. We therefore recommend a reconfiguration of the network to include these suitable habitats and ensure their immediate protection. These novel habitat insights and spatial predictions can form the basis for future forest studies and spatial conservation planning, and have implications for more effective conservation of the Sundarbans mangroves and the many other species that rely on them.

Spatiotemporal Dynamics of Whitefly Bemisia tabaci (Hemiptera: Aleyrodidae) in Commercial Watermelon Crops.

PubMed

Lima, Carlos H O; Sarmento, Renato A; Galdino, Tarcísio V S; Pereira, Poliana S; Silva, Joedna; Souza, Danival J; Dos Santos, Gil R; Costa, Thiago L; Picanço, Marcelo C

2018-04-16

Spatiotemporal dynamics studies of crop pests enable the determination of the colonization pattern and dispersion of these insects in the landscape. Geostatistics is an efficient tool for these studies: to determine the spatial distribution pattern of the pest in the crops and to make maps that represent this situation. Analysis of these maps across the development of plants can be used as a tool in precision agriculture programs. Watermelon, Citrullus lanatus (Thunb.) Matsum. and Nakai (Cucurbitales: Cucurbitaceae), is the second most consumed fruit in the world, and the whitefly Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) is one of the most important pests of this crop. Thus, the objective of this work was to determine the spatiotemporal distribution of B. tabaci in commercial watermelon crops using geostatistics. For 2 yr, we monitored adult whitefly densities in eight watermelon crops in a tropical climate region. The location of the samples and other crops in the landscape was georeferenced. Experimental data were submitted to geostatistical analysis. The colonization of B. tabaci had two patterns. In the first, the colonization started at the outermost parts of the crop. In the second, the insects occupied the whole area of the crop since the beginning of cultivation. The maximum distance between sites of watermelon crops in which spatial dependence of B. tabaci densities was observed was 19.69 m. The adult B. tabaci densities in the eight watermelon fields were positively correlated with rainfall and relative humidity, whereas wind speed negatively affected whiteflies population.

Modelling population distribution using remote sensing imagery and location-based data

NASA Astrophysics Data System (ADS)

Song, J.; Prishchepov, A. V.

2017-12-01

Detailed spatial distribution of population density is essential for city studies such as urban planning, environmental pollution and city emergency, even estimate pressure on the environment and human exposure and risks to health. However, most of the researches used census data as the detailed dynamic population distribution are difficult to acquire, especially in microscale research. This research describes a method using remote sensing imagery and location-based data to model population distribution at the function zone level. Firstly, urban functional zones within a city were mapped by high-resolution remote sensing images and POIs. The workflow of functional zones extraction includes five parts: (1) Urban land use classification. (2) Segmenting images in built-up area. (3) Identification of functional segments by POIs. (4) Identification of functional blocks by functional segmentation and weight coefficients. (5) Assessing accuracy by validation points. The result showed as Fig.1. Secondly, we applied ordinary least square and geographically weighted regression to assess spatial nonstationary relationship between light digital number (DN) and population density of sampling points. The two methods were employed to predict the population distribution over the research area. The R²of GWR model were in the order of 0.7 and typically showed significant variations over the region than traditional OLS model. The result showed as Fig.2.Validation with sampling points of population density demonstrated that the result predicted by the GWR model correlated well with light value. The result showed as Fig.3. Results showed: (1) Population density is not linear correlated with light brightness using global model. (2) VIIRS night-time light data could estimate population density integrating functional zones at city level. (3) GWR is a robust model to map population distribution, the adjusted R2 of corresponding GWR models were higher than the optimal OLS models, confirming that GWR models demonstrate better prediction accuracy. So this method provide detailed population density information for microscale citizen studies.

Mapping the Distribution of Anthrax in Mainland China, 2005-2013.

PubMed

Chen, Wan-Jun; Lai, Sheng-Jie; Yang, Yang; Liu, Kun; Li, Xin-Lou; Yao, Hong-Wu; Li, Yu; Zhou, Hang; Wang, Li-Ping; Mu, Di; Yin, Wen-Wu; Fang, Li-Qun; Yu, Hong-Jie; Cao, Wu-Chun

2016-04-01

Anthrax, a global re-emerging zoonotic disease in recent years is enzootic in mainland China. Despite its significance to the public health, spatiotemporal distributions of the disease in human and livestock and its potential driving factors remain poorly understood. Using the national surveillance data of human and livestock anthrax from 2005 to 2013, we conducted a retrospective epidemiological study and risk assessment of anthrax in mainland China. The potential determinants for the temporal and spatial distributions of human anthrax were also explored. We found that the majority of human anthrax cases were located in six provinces in western and northeastern China, and five clustering areas with higher incidences were identified. The disease mostly peaked in July or August, and males aged 30-49 years had higher incidence than other subgroups. Monthly incidence of human anthrax was positively correlated with monthly average temperature, relative humidity and monthly accumulative rainfall with lags of 0-2 months. A boosted regression trees (BRT) model at the county level reveals that densities of cattle, sheep and human, coverage of meadow, coverage of typical grassland, elevation, coverage of topsoil with pH > 6.1, concentration of organic carbon in topsoil, and the meteorological factors have contributed substantially to the spatial distribution of the disease. The model-predicted probability of occurrence of human cases in mainland China was mapped at the county level. Anthrax in China was characterized by significant seasonality and spatial clustering. The spatial distribution of human anthrax was largely driven by livestock husbandry, human density, land cover, elevation, topsoil features and climate. Enhanced surveillance and intervention for livestock and human anthrax in the high-risk regions, particularly on the Qinghai-Tibetan Plateau, is the key to the prevention of human infections.

Mapping the Distribution of Anthrax in Mainland China, 2005–2013

PubMed Central

Yang, Yang; Liu, Kun; Li, Xin-Lou; Yao, Hong-Wu; Li, Yu; Zhou, Hang; Wang, Li-Ping; Mu, Di; Yin, Wen-Wu; Fang, Li-Qun; Yu, Hong-Jie; Cao, Wu-Chun

2016-01-01

Background Anthrax, a global re-emerging zoonotic disease in recent years is enzootic in mainland China. Despite its significance to the public health, spatiotemporal distributions of the disease in human and livestock and its potential driving factors remain poorly understood. Methodology/Principal Findings Using the national surveillance data of human and livestock anthrax from 2005 to 2013, we conducted a retrospective epidemiological study and risk assessment of anthrax in mainland China. The potential determinants for the temporal and spatial distributions of human anthrax were also explored. We found that the majority of human anthrax cases were located in six provinces in western and northeastern China, and five clustering areas with higher incidences were identified. The disease mostly peaked in July or August, and males aged 30–49 years had higher incidence than other subgroups. Monthly incidence of human anthrax was positively correlated with monthly average temperature, relative humidity and monthly accumulative rainfall with lags of 0–2 months. A boosted regression trees (BRT) model at the county level reveals that densities of cattle, sheep and human, coverage of meadow, coverage of typical grassland, elevation, coverage of topsoil with pH > 6.1, concentration of organic carbon in topsoil, and the meteorological factors have contributed substantially to the spatial distribution of the disease. The model-predicted probability of occurrence of human cases in mainland China was mapped at the county level. Conclusions/Significance Anthrax in China was characterized by significant seasonality and spatial clustering. The spatial distribution of human anthrax was largely driven by livestock husbandry, human density, land cover, elevation, topsoil features and climate. Enhanced surveillance and intervention for livestock and human anthrax in the high-risk regions, particularly on the Qinghai-Tibetan Plateau, is the key to the prevention of human infections. PMID:27097318

Clustering the Orion B giant molecular cloud based on its molecular emission

NASA Astrophysics Data System (ADS)

Bron, Emeric; Daudon, Chloé; Pety, Jérôme; Levrier, François; Gerin, Maryvonne; Gratier, Pierre; Orkisz, Jan H.; Guzman, Viviana; Bardeau, Sébastien; Goicoechea, Javier R.; Liszt, Harvey; Öberg, Karin; Peretto, Nicolas; Sievers, Albrecht; Tremblin, Pascal

2018-02-01

Context. Previous attempts at segmenting molecular line maps of molecular clouds have focused on using position-position-velocity data cubes of a single molecular line to separate the spatial components of the cloud. In contrast, wide field spectral imaging over a large spectral bandwidth in the (sub)mm domain now allows one to combine multiple molecular tracers to understand the different physical and chemical phases that constitute giant molecular clouds (GMCs). Aims: We aim at using multiple tracers (sensitive to different physical processes and conditions) to segment a molecular cloud into physically/chemically similar regions (rather than spatially connected components), thus disentangling the different physical/chemical phases present in the cloud. Methods: We use a machine learning clustering method, namely the Meanshift algorithm, to cluster pixels with similar molecular emission, ignoring spatial information. Clusters are defined around each maximum of the multidimensional probability density function (PDF) of the line integrated intensities. Simple radiative transfer models were used to interpret the astrophysical information uncovered by the clustering analysis. Results: A clustering analysis based only on the J = 1-0 lines of three isotopologues of CO proves sufficient to reveal distinct density/column density regimes (nH 100 cm-3, 500 cm-3, and >1000 cm-3), closely related to the usual definitions of diffuse, translucent and high-column-density regions. Adding two UV-sensitive tracers, the J = 1-0 line of HCO+ and the N = 1-0 line of CN, allows us to distinguish two clearly distinct chemical regimes, characteristic of UV-illuminated and UV-shielded gas. The UV-illuminated regime shows overbright HCO+ and CN emission, which we relate to a photochemical enrichment effect. We also find a tail of high CN/HCO+ intensity ratio in UV-illuminated regions. Finer distinctions in density classes (nH 7 × 103 cm-3, 4 × 104 cm-3) for the densest regions are also identified, likely related to the higher critical density of the CN and HCO+ (1-0) lines. These distinctions are only possible because the high-density regions are spatially resolved. Conclusions: Molecules are versatile tracers of GMCs because their line intensities bear the signature of the physics and chemistry at play in the gas. The association of simultaneous multi-line, wide-field mapping and powerful machine learning methods such as the Meanshift clustering algorithm reveals how to decode the complex information available in these molecular tracers. Data products associated with this paper are available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/610/A12 and at http://www.iram.fr/ pety/ORION-B

Inferring the three-dimensional distribution of dust in the Galaxy with a non-parametric method . Preparing for Gaia

NASA Astrophysics Data System (ADS)

Rezaei Kh., S.; Bailer-Jones, C. A. L.; Hanson, R. J.; Fouesneau, M.

2017-02-01

We present a non-parametric model for inferring the three-dimensional (3D) distribution of dust density in the Milky Way. Our approach uses the extinction measured towards stars at different locations in the Galaxy at approximately known distances. Each extinction measurement is proportional to the integrated dust density along its line of sight (LoS). Making simple assumptions about the spatial correlation of the dust density, we can infer the most probable 3D distribution of dust across the entire observed region, including along sight lines which were not observed. This is possible because our model employs a Gaussian process to connect all LoS. We demonstrate the capability of our model to capture detailed dust density variations using mock data and simulated data from the Gaia Universe Model Snapshot. We then apply our method to a sample of giant stars observed by APOGEE and Kepler to construct a 3D dust map over a small region of the Galaxy. Owing to our smoothness constraint and its isotropy, we provide one of the first maps which does not show the "fingers of God" effect.

New Mars free-air and Bouguer gravity: Correlation with topography, geology and large impact basins

NASA Technical Reports Server (NTRS)

Frey, Herbert; Bills, Bruce G.; Kiefer, Walter S.; Nerem, R. Steven; Roark, James H.; Zuber, Maria T.

1993-01-01

Free-air and Bouguer gravity anomalies from a 50x50 field (MGM635), derived at the Goddard Space Flight Center, with global topography, geology, and the distribution of large impact basins was compared. The free-air gravity anomalies were derived from re-analysis of Viking Orbiter and Mariner 9 tracking data and have a spatial resolution of 250-300 km. Bouguer anomalies were calculated using a 50x50 expansion of the current Mars topography and the GSFC degree 50 geoid as the equipotential reference surface. Rotational flattening was removed using a moment of inertia of 0.365 and the corrections from Table B2 of Sleep and Phillips. Crustal density and mean density were assumed to be 2.9 and 3.93 gm/cm(sup 3). The spherical harmonic topography used has zero mean elevation, and differs from the USGS maps by about 2 km. Comparisons with global geology use a simplified map with about 1/3 the number of units on the current maps. For correlation with impact basins, the recent compilation by Schultz and Frey was used.

MAPPING SPATIAL THEMATIC ACCURACY WITH FUZZY SETS

EPA Science Inventory

Thematic map accuracy is not spatially homogenous but variable across a landscape. Properly analyzing and representing spatial pattern and degree of thematic map accuracy would provide valuable information for using thematic maps. However, current thematic map accuracy measures (...

Spatial patterns of a tropical tree species growing under an eucalyptus plantation in South-East Brazil.

PubMed

Higuchi, P; Silva, A C; Louzada, J N C; Machado, E L M

2010-05-01

The objectives of this study were to evaluate the influence of propagules source and the implication of tree size class on the spatial pattern of Xylopia brasiliensis Spreng. individuals growing under the canopy of an experimental plantation of eucalyptus. To this end, all individuals of Xylopia brasiliensis with diameter at soil height (dsh) > 1 cm were mapped in the understory of a 3.16 ha Eucalyptus spp. and Corymbia spp. plantation, located in the municipality of Lavras, SE Brazil. The largest nearby mature tree of X. brasiliensis was considered as the propagules source. Linear regressions were used to assess the influence of the distance of propagules source on the population parameters (density, basal area and height). The spatial pattern of trees was assessed through the Ripley K function. The overall pattern showed that the propagules source distance had strong influence over spatial distribution of trees, mainly the small ones, indicating that the closer the distance from the propagules source, the higher the tree density and the lower the mean tree height. The population showed different spatial distribution patterns according to the spatial scale and diameter class considered. While small trees tended to be aggregated up to around 80 m, the largest individuals were randomly distributed in the area. A plausible explanation for observed patterns might be limited seed rain and intra-population competition.

Landsat phenological metrics and their relation to aboveground carbon in the Brazilian Savanna.

PubMed

Schwieder, M; Leitão, P J; Pinto, J R R; Teixeira, A M C; Pedroni, F; Sanchez, M; Bustamante, M M; Hostert, P

2018-05-15

The quantification and spatially explicit mapping of carbon stocks in terrestrial ecosystems is important to better understand the global carbon cycle and to monitor and report change processes, especially in the context of international policy mechanisms such as REDD+ or the implementation of Nationally Determined Contributions (NDCs) and the UN Sustainable Development Goals (SDGs). Especially in heterogeneous ecosystems, such as Savannas, accurate carbon quantifications are still lacking, where highly variable vegetation densities occur and a strong seasonality hinders consistent data acquisition. In order to account for these challenges we analyzed the potential of land surface phenological metrics derived from gap-filled 8-day Landsat time series for carbon mapping. We selected three areas located in different subregions in the central Brazil region, which is a prominent example of a Savanna with significant carbon stocks that has been undergoing extensive land cover conversions. Here phenological metrics from the season 2014/2015 were combined with aboveground carbon field samples of cerrado sensu stricto vegetation using Random Forest regression models to map the regional carbon distribution and to analyze the relation between phenological metrics and aboveground carbon. The gap filling approach enabled to accurately approximate the original Landsat ETM+ and OLI EVI values and the subsequent derivation of annual phenological metrics. Random Forest model performances varied between the three study areas with RMSE values of 1.64 t/ha (mean relative RMSE 30%), 2.35 t/ha (46%) and 2.18 t/ha (45%). Comparable relationships between remote sensing based land surface phenological metrics and aboveground carbon were observed in all study areas. Aboveground carbon distributions could be mapped and revealed comprehensible spatial patterns. Phenological metrics were derived from 8-day Landsat time series with a spatial resolution that is sufficient to capture gradual changes in carbon stocks of heterogeneous Savanna ecosystems. These metrics revealed the relationship between aboveground carbon and the phenology of the observed vegetation. Our results suggest that metrics relating to the seasonal minimum and maximum values were the most influential variables and bear potential to improve spatially explicit mapping approaches in heterogeneous ecosystems, where both spatial and temporal resolutions are critical.

Spatial Substructure in the M87 Globular Cluster System

NASA Astrophysics Data System (ADS)

Feng, Yuting; Zhang, Yunhao; Guhathakurta, Puragra; Peng, Eric; Lim, Sungsoon

2018-01-01

Based on the observation of Next Generation Virgo Cluster Survey (NGVS) project, we obtained the u,g,r,i,z and Ks band photometric information of all the objects in the 2 degree × 2 degree area (Pilot Region) around M87, the major subcluster of Virgo. By adapting an Extreme Deconvolution method, which classifies objects into Globular Clusters (GCs), galaxies and foreground stars with their color and morphology data, we got a purer-than-ever GC distribution map with a depth to gmag=25 in Pilot Region. After masking galaxy GCs, smoothing with a 10arcmin Gaussian kernel and performing a flat field correction, we show the GC density map of M87, and got a good sersic fitting of GC radial distribution with a sersic index~2.2 in the central ellipse part (45arcmin semi major axis area of M87). We quantitatively compared our GC sample with a substructure-free mock data set, which was generated from the smoothed density map as well as the sersic fitting, by calculating the 2 point correlation function (TPCF) value in different parts of the map. After separately performing such comparison with mocks based on different galaxy masking radii which vary from 4 times g band effective radius to 10, we found signals of remarkable spatial enhancement in certain directions in the central ellipse of M87, as well as halo substructures shown as lumpiness and holes in the outer region. We present the estimated scales of these substructures from the TPCF results, and, managed to locate them with a statistical analysis of the pixelized GC map. Apart from all results listed above, we discuss the constant, extra-galactic substructure signal at a scale of ~3kpc, which does not diminish with masking sizes, as the evidence of merging and accretion history of M87.

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

Fertig, Fabian, E-mail: fabian.fertig@ise.fraunhofer.de; Greulich, Johannes; Rein, Stefan

Spatially resolved determination of solar cell parameters is beneficial for loss analysis and optimization of conversion efficiency. One key parameter that has been challenging to access by an imaging technique on solar cell level is short-circuit current density. This work discusses the robustness of a recently suggested approach to determine short-circuit current density spatially resolved based on a series of lock-in thermography images and options for a simplified image acquisition procedure. For an accurate result, one or two emissivity-corrected illuminated lock-in thermography images and one dark lock-in thermography image have to be recorded. The dark lock-in thermography image can bemore » omitted if local shunts are negligible. Furthermore, it is shown that omitting the correction of lock-in thermography images for local emissivity variations only leads to minor distortions for standard silicon solar cells. Hence, adequate acquisition of one image only is sufficient to generate a meaningful map of short-circuit current density. Beyond that, this work illustrates the underlying physics of the recently proposed method and demonstrates its robustness concerning varying excitation conditions and locally increased series resistance. Experimentally gained short-circuit current density images are validated for monochromatic illumination in comparison to the reference method of light-beam induced current.« less

Surface Wave Tomography with Spatially Varying Smoothing Based on Continuous Model Regionalization

NASA Astrophysics Data System (ADS)

Liu, Chuanming; Yao, Huajian

2017-03-01

Surface wave tomography based on continuous regionalization of model parameters is widely used to invert for 2-D phase or group velocity maps. An inevitable problem is that the distribution of ray paths is far from homogeneous due to the spatially uneven distribution of stations and seismic events, which often affects the spatial resolution of the tomographic model. We present an improved tomographic method with a spatially varying smoothing scheme that is based on the continuous regionalization approach. The smoothness of the inverted model is constrained by the Gaussian a priori model covariance function with spatially varying correlation lengths based on ray path density. In addition, a two-step inversion procedure is used to suppress the effects of data outliers on tomographic models. Both synthetic and real data are used to evaluate this newly developed tomographic algorithm. In the synthetic tests, when the contrived model has different scales of anomalies but with uneven ray path distribution, we compare the performance of our spatially varying smoothing method with the traditional inversion method, and show that the new method is capable of improving the recovery in regions of dense ray sampling. For real data applications, the resulting phase velocity maps of Rayleigh waves in SE Tibet produced using the spatially varying smoothing method show similar features to the results with the traditional method. However, the new results contain more detailed structures and appears to better resolve the amplitude of anomalies. From both synthetic and real data tests we demonstrate that our new approach is useful to achieve spatially varying resolution when used in regions with heterogeneous ray path distribution.

LiDAR collection in August 2015 over the East River Watershed, Colorado, USA

DOE Data Explorer

Wainwright, Haruko [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Williams, Kenneth

2017-01-01

Airborne LiDAR data were acquired over the study area on August 10th, 2015, using a Riegl Q1560 dual-channel LiDAR system mounted on a Piper Navajo. The survey was performed by Quantum Spatial in collaboration with Eagle Mapping Ltd. The data complies with the USGS QL1 standard [Heideman, 2014] with the point density more than 8 pulse per m2.

Identifying Population Vulnerable to Extreme Heat Events in San Jose, California.

NASA Astrophysics Data System (ADS)

Rivera, A. L.

2016-12-01

The extreme heat days not only make cities less comfortable for living but also they are associated with increased morbidity and mortality. Mapping studies have demonstrated spatial variability in heat vulnerability. A study conducted between 2000 and 2011 in New York City shows that deaths during heat waves was more likely to occur in black individuals, at home in census tracts which received greater public assistance. This map project intends to portray areas in San Jose California that are vulnerable to extreme heat events. The variables considered to build a vulnerability index are: land surface temperature, vegetated areas (NDVI), and people exposed to these area (population density).

Combining area-based and individual-level data in the geostatistical mapping of late-stage cancer incidence.

PubMed

Goovaerts, Pierre

2009-01-01

This paper presents a geostatistical approach to incorporate individual-level data (e.g. patient residences) and area-based data (e.g. rates recorded at census tract level) into the mapping of late-stage cancer incidence, with an application to breast cancer in three Michigan counties. Spatial trends in cancer incidence are first estimated from census data using area-to-point binomial kriging. This prior model is then updated using indicator kriging and individual-level data. Simulation studies demonstrate the benefits of this two-step approach over methods (kernel density estimation and indicator kriging) that process only residence data.

Community Seismic Network (CSN)

NASA Astrophysics Data System (ADS)

Clayton, R. W.; Kohler, M. D.; Heaton, T. H.; Massari, A.; Guy, R.; Bunn, J.; Chandy, M.

2015-12-01

The CSN now has approximately 600 stations in the northern Los Angeles region. The sensors are class-C MEMs accelerometers that are packaged with backup power and data memory and are connected to a cloud-based processing system through the Internet. Most of the sensors are located in an xy-spatial network with an average minimum station spacing of 800 m. This density allows the lateral variations in ground motion to be determined, which will lead to detailed microzonation maps of the region. Approximately 100 of the sensors are located on campuses of the Los Angeles Unified School District (LAUSD), and this is part of a plan to provide schools with critical earthquake information immediately following an earthquake using the ShakeCast system. The software system in the sensors is being upgraded to allow on site measurements of PGA and PVA to be sent directly to the ShakeMap and earthquake early warning systems. More than 160 of the sensor packages are located on multiple floors of buildings with typically one or two 3-component sensors per floor. With these data we can identify traveling waves in the building, as well as determine the eigenfrequencies and mode shapes. By monitoring these quantities with high spatial density before, during, and after a major shaking event, we hope to determine the state of health of the structure.

Drivers of Non-Native Aquatic Species Invasions across the ...

EPA Pesticide Factsheets

Background/Question/Methods Mapping the geographic distribution of non-native aquatic species is a critically important precursor to understanding the anthropogenic and environmental factors that drive freshwater biological invasions. Such efforts are often limited to local scales and/or to a single taxa, missing the opportunity to observe and understand the drivers of macroscale invasion patterns at sub-continental or continental scales. Here we map the distribution of exotic freshwater species richness across the continental United States using publicly accessible species occurrence data (e.g GBIF) and investigate the role of human activity in driving macroscale patterns of aquatic invasion. Using a dasymetric model of human population density and a spatially explicit model of recreational freshwater fishing demand, we analyzed the effect of these metrics of human influence on non-native aquatic species richness at the watershed scale, while controlling for spatial and sampling bias. We also assessed the effects that a temporal mismatch between occurrence data (collected since 1815) and cross-sectional predictors (developed using 2010 data) may have on model fit. Results/Conclusions Our results indicated that non-native aquatic species richness exhibits a highly patchy distribution, with hotspots in the Northeast, Great Lakes, Florida, and human population centers on the Pacific coast. These richness patterns are correlated with population density, but are m

Simple Z2 lattice gauge theories at finite fermion density

NASA Astrophysics Data System (ADS)

Prosko, Christian; Lee, Shu-Ping; Maciejko, Joseph

2017-11-01

Lattice gauge theories are a powerful language to theoretically describe a variety of strongly correlated systems, including frustrated magnets, high-Tc superconductors, and topological phases. However, in many cases gauge fields couple to gapless matter degrees of freedom, and such theories become notoriously difficult to analyze quantitatively. In this paper we study several examples of Z2 lattice gauge theories with gapless fermions at finite density, in one and two spatial dimensions, that are either exactly soluble or whose solution reduces to that of a known problem. We consider complex fermions (spinless and spinful) as well as Majorana fermions and study both theories where Gauss' law is strictly imposed and those where all background charge sectors are kept in the physical Hilbert space. We use a combination of duality mappings and the Z2 slave-spin representation to map our gauge theories to models of gauge-invariant fermions that are either free, or with on-site interactions of the Hubbard or Falicov-Kimball type that are amenable to further analysis. In 1D, the phase diagrams of these theories include free-fermion metals, insulators, and superconductors, Luttinger liquids, and correlated insulators. In 2D, we find a variety of gapped and gapless phases, the latter including uniform and spatially modulated flux phases featuring emergent Dirac fermions, some violating Luttinger's theorem.

A Geospatial Database for Wind and Solar Energy Applications: The Kingdom of Bahrain Study Case

NASA Astrophysics Data System (ADS)

Al-Joburi, Khalil; Dahman, Nidal

2017-11-01

This research is aimed at designing, implementing, and testing a geospatial database for wind and solar energy applications in the Kingdom of Bahrain. All decision making needed to determine economic feasibility and establish site location for wind turbines or solar panels depends primarily on geospatial feature theme information and non-spatial (attribute) data for wind, solar, rainfall, temperature and weather characteristics of a particular region. Spatial data includes, but is not limited to, digital elevation, slopes, land use, zonings, parks, population density, road utility maps, and other related information. Digital elevations for over 450,000 spot at 50 m spatial horizontal resolution plus field surveying and GPS (at selected locations) was obtained from the Surveying and Land Registration Bureau (SLRB). Road, utilities, and population density are obtained from the Central Information Organization (CIO). Land use zoning, recreational parks, and other data are obtained from the Ministry of Municipalities and Agricultural Affairs. Wind, solar, humidity, rainfall, and temperature data are obtained from the Ministry of Transportation, Civil Aviation Section. LandSat Satellite and others images are obtained from NASA and online sources respectively. The collected geospatial data was geo-referenced to Ain el-Abd UTM Zone 39 North. 3D Digital Elevation Model (DEM)-50 m spatial resolutions was created using SLRB spot elevations. Slope and aspect maps were generate based on the DEM. Supervised image classification to identify open spaces was performed utilizing satellite images. Other geospatial data was converted to raster format with the same cell resolution. Non-spatial data are entered as an attribute to spatial features. To eliminate ambiguous solution, multi-criteria GIS model is developed based on, vector (discrete point, line, and polygon representations) as well as raster model (continuous representation). The model was tested at the Al-Areen proposed project, a relatively small area (15 km2). Optimum site spatial location for the location of wind turbines and solar panels was determined and initial results indicates that the combination of wind and solar energy would be sufficient for the project to meet the energy demand at the present per capita consummation rate..

Spatial assessment of soil organic carbon and physicochemical properties in a horticultural orchard at arid zone of India using geostatistical approaches.

PubMed

Singh, Akath; Santra, Priyabrata; Kumar, Mahesh; Panwar, Navraten; Meghwal, P R

2016-09-01

Soil organic carbon (SOC) is a major indicator of long-term sustenance of agricultural production system. Apart from sustaining productivity, SOC plays a crucial role in context of climate change. Keeping in mind these potentials, spatial variation of SOC contents of a fruit orchard comprising several arid fruit plantations located at arid region of India is assessed in this study through geostatistical approaches. For this purpose, surface and subsurface soil samples from 175 locations from a fruit orchard spreading over 14.33 ha area were collected along with geographical coordinates. SOC content and soil physicochemical properties of collected soil samples were determined followed by geostatistical analysis for mapping purposes. Average SOC stock density of the orchard was 14.48 Mg ha(-1) for 0- to 30-cm soil layer ranging from 9.01 Mg ha(-1) in Carissa carandas to 19.52 Mg ha(-1) in Prosopis cineraria block. Range of spatial variation of SOC content was found about 100 m, while two other soil physicochemical properties, e.g., pH and electrical conductivity (EC) also showed similar spatial trend. This indicated that minimum sampling distance for future SOC mapping programme may be kept lower than 100 m for better accuracy. Ordinary kriging technique satisfactorily predicted SOC contents (in percent) at unsampled locations with root-mean-squared residual (RMSR) of 0.35-0.37. Co-kriging approach was found slightly superior (RMSR = 0.26-0.28) than ordinary kriging for spatial prediction of SOC contents because of significant correlations of SOC contents with pH and EC. Uncertainty of SOC estimation was also presented in terms of 90 % confidence interval. Spatial estimates of SOC stock through ordinary kriging or co-kriging approach were also found with low uncertainty of estimation than non-spatial estimates, e.g., arithmetic averaging approach. Among different fruit block plantations of the orchard, the block with Prosopis cineraria ('khejri') has higher SOC stock density than others.

The Effect of Arc Proximity on Hydrothermal Activity Along Spreading Centers: New Evidence From the Mariana Back Arc (12.7°N-18.3°N)

NASA Astrophysics Data System (ADS)

Baker, Edward T.; Walker, Sharon L.; Resing, Joseph A.; Chadwick, William W.; Merle, Susan G.; Anderson, Melissa O.; Butterfield, David A.; Buck, Nathan J.; Michael, Susanna

2017-11-01

Back-arc spreading centers (BASCs) form a distinct class of ocean spreading ridges distinguished by steep along-axis gradients in spreading rate and by additional magma supplied through subduction. These characteristics can affect the population and distribution of hydrothermal activity on BASCs compared to mid-ocean ridges (MORs). To investigate this hypothesis, we comprehensively explored 600 km of the southern half of the Mariana BASC. We used water column mapping and seafloor imaging to identify 19 active vent sites, an increase of 13 over the current listing in the InterRidge Database (IRDB), on the bathymetric highs of 7 of the 11 segments. We identified both high and low (i.e., characterized by a weak or negligible particle plume) temperature discharge occurring on segment types spanning dominantly magmatic to dominantly tectonic. Active sites are concentrated on the two southernmost segments, where distance to the adjacent arc is shortest (<40 km), spreading rate is highest (>48 mm/yr), and tectonic extension is pervasive. Re-examination of hydrothermal data from other BASCs supports the generalization that hydrothermal site density increases on segments <90 km from an adjacent arc. Although exploration quality varies greatly among BASCs, present data suggest that, for a given spreading rate, the mean spatial density of hydrothermal activity varies little between MORs and BASCs. The present global database, however, may be misleading. On both BASCs and MORs, the spatial density of hydrothermal sites mapped by high-quality water-column surveys is 2-7 times greater than predicted by the existing IRDB trend of site density versus spreading rate.

Within-field spatial distribution of Megacopta cribraria (Hemiptera: Plataspidae) in soybean (Fabales: Fabaceae).

PubMed

Seiter, Nicholas J; Reay-Jones, Francis P F; Greene, Jeremy K

2013-12-01

The recently introduced plataspid Megacopta cribraria (F.) can infest fields of soybean (Glycine max (L.) Merrill) in the southeastern United States. Grid sampling in four soybean fields was conducted in 2011 and 2012 to study the spatial distribution of M. cribraria adults, nymphs, and egg masses. Peak oviposition typically occurred in early August, while peak levels of adults occurred in mid-late September. The overall sex ratio was slightly biased at 53.1 ± 0.2% (SEM) male. Sweep samples of nymphs were biased toward late instars. All three life stages exhibited a generally aggregated spatial distribution based on Taylor's power law, Iwao's patchiness regression, and spatial analysis by distance indices (SADIE). Interpolation maps of local SADIE aggregation indices showed clusters of adults and nymphs located at field edges, and mean densities of adults were higher in samples taken from field edges than in those taken from field interiors. Adults and nymphs were often spatially associated based on SADIE, indicating spatial stability across life stages.

Mapping spatial resources with GPS animal telemetry: foraging manatees locate seagrass beds in the Ten Thousand Islands, Florida, USA

USGS Publications Warehouse

Slone, Daniel H.; Reid, James P.; Kenworthy, W. Judson

2013-01-01

Turbid water conditions make the delineation and characterization of benthic habitats difficult by traditional in situ and remote sensing methods. Here, we develop and validate modeling and sampling methodology for detecting and characterizing seagrass beds by analyzing GPS telemetry records from radio-tagged manatees. Between October 2002 and October 2005, 14 manatees were tracked in the Ten Thousand Islands (TTI) in southwest Florida (USA) using Global Positioning System (GPS) tags. High density manatee use areas were found to occur off each island facing the open, nearshore waters of the Gulf of Mexico. We implemented a spatially stratified random sampling plan and used a camera-based sampling technique to observe and record bottom observations of seagrass and macroalgae presence and abundance. Five species of seagrass were identified in our study area: Halodule wrightii, Thalassia testudinum, Syringodium filiforme, Halophila engelmannii, and Halophila decipiens. A Bayesian model was developed to choose and parameterize a spatial process function that would describe the observed patterns of seagrass and macroalgae. The seagrasses were found in depths <2 m and in the higher manatee use strata, whereas macroalgae was found at moderate densities at all sampled depths and manatee use strata. The manatee spatial data showed a strong association with seagrass beds, a relationship that increased seagrass sampling efficiency. Our camera-based field sampling proved to be effective for assessing seagrass density and spatial coverage under turbid water conditions, and would be an effective monitoring tool to detect changes in seagrass beds.

Analysis of interstellar cloud structure based on IRAS images

NASA Technical Reports Server (NTRS)

Scalo, John M.

1992-01-01

The goal of this project was to develop new tools for the analysis of the structure of densely sampled maps of interstellar star-forming regions. A particular emphasis was on the recognition and characterization of nested hierarchical structure and fractal irregularity, and their relation to the level of star formation activity. The panoramic IRAS images provided data with the required range in spatial scale, greater than a factor of 100, and in column density, greater than a factor of 50. In order to construct densely sampled column density maps of star-forming clouds, column density images of four nearby cloud complexes were constructed from IRAS data. The regions have various degrees of star formation activity, and most of them have probably not been affected much by the disruptive effects of young massive stars. The largest region, the Scorpius-Ophiuchus cloud complex, covers about 1000 square degrees (it was subdivided into a few smaller regions for analysis). Much of the work during the early part of the project focused on an 80 square degree region in the core of the Taurus complex, a well-studied region of low-mass star formation.

Dynamic population mapping using mobile phone data.

PubMed

Deville, Pierre; Linard, Catherine; Martin, Samuel; Gilbert, Marius; Stevens, Forrest R; Gaughan, Andrea E; Blondel, Vincent D; Tatem, Andrew J

2014-11-11

During the past few decades, technologies such as remote sensing, geographical information systems, and global positioning systems have transformed the way the distribution of human population is studied and modeled in space and time. However, the mapping of populations remains constrained by the logistics of censuses and surveys. Consequently, spatially detailed changes across scales of days, weeks, or months, or even year to year, are difficult to assess and limit the application of human population maps in situations in which timely information is required, such as disasters, conflicts, or epidemics. Mobile phones (MPs) now have an extremely high penetration rate across the globe, and analyzing the spatiotemporal distribution of MP calls geolocated to the tower level may overcome many limitations of census-based approaches, provided that the use of MP data is properly assessed and calibrated. Using datasets of more than 1 billion MP call records from Portugal and France, we show how spatially and temporarily explicit estimations of population densities can be produced at national scales, and how these estimates compare with outputs produced using alternative human population mapping methods. We also demonstrate how maps of human population changes can be produced over multiple timescales while preserving the anonymity of MP users. With similar data being collected every day by MP network providers across the world, the prospect of being able to map contemporary and changing human population distributions over relatively short intervals exists, paving the way for new applications and a near real-time understanding of patterns and processes in human geography.

Dynamic population mapping using mobile phone data

PubMed Central

Deville, Pierre; Martin, Samuel; Gilbert, Marius; Stevens, Forrest R.; Gaughan, Andrea E.; Blondel, Vincent D.; Tatem, Andrew J.

2014-01-01

During the past few decades, technologies such as remote sensing, geographical information systems, and global positioning systems have transformed the way the distribution of human population is studied and modeled in space and time. However, the mapping of populations remains constrained by the logistics of censuses and surveys. Consequently, spatially detailed changes across scales of days, weeks, or months, or even year to year, are difficult to assess and limit the application of human population maps in situations in which timely information is required, such as disasters, conflicts, or epidemics. Mobile phones (MPs) now have an extremely high penetration rate across the globe, and analyzing the spatiotemporal distribution of MP calls geolocated to the tower level may overcome many limitations of census-based approaches, provided that the use of MP data is properly assessed and calibrated. Using datasets of more than 1 billion MP call records from Portugal and France, we show how spatially and temporarily explicit estimations of population densities can be produced at national scales, and how these estimates compare with outputs produced using alternative human population mapping methods. We also demonstrate how maps of human population changes can be produced over multiple timescales while preserving the anonymity of MP users. With similar data being collected every day by MP network providers across the world, the prospect of being able to map contemporary and changing human population distributions over relatively short intervals exists, paving the way for new applications and a near real-time understanding of patterns and processes in human geography. PMID:25349388

Rangeland biomass estimation demonstration. [Texas Experimenta Ranch

NASA Technical Reports Server (NTRS)

Newton, R. W. (Principal Investigator); Boyd, W. E.; Clark, B. V.

1982-01-01

Because of their sensitivity to chlorophyll density, green leaf density, and leaf water density, two hand-held radiometers which have sensor bands coinciding with thematic mapper bands 3, 4, and 5 were used to calibrate green biomass to LANDSAT spectral ratios as a step towards using portable radiometers to speed up ground data acquisition. Two field reflectance panels monitored incoming radiation concurrently with sampling. Software routines were developed and used to extract data from uncorrected tapes of MSS data provided in NASA LANDSAT universal format. A LANDSAT biomass calibration curve estimated the range biomass over a four scene area and displayed this information spatially as a product in a format of use to ranchers. The regional biomass contour map is discussed.

Evolutionary status of the pre-protostellar core L1498

NASA Technical Reports Server (NTRS)

Kuiper, T. B.; Langer, W. D.; Velusamy, T.; Levin, S. M. (Principal Investigator)

1996-01-01

L1498 is a classic example of a dense cold pre-protostellar core. To study the evolutionary status, the structure, dynamics, and chemical properties of this core we have obtained high spatial and high spectral resolution observations of molecules tracing densities of 10(3)-10(5) cm-3. We observed CCS, NH3, C3H2, and HC7N with NASA's DSN 70 m antennas. We also present large-scale maps of C18O and 13CO observed with the AT&T 7 m antenna. For the high spatial resolution maps of selected regions within the core we used the VLA for CCS at 22 GHz, and the Owens Valley Radio Observatory (OVRO) MMA for CCS at 94 GHz and CS (2-1). The 22 GHz CCS emission marks a high-density [n(H2) > 10(4) cm -3] core, which is elongated with a major axis along the SE-NW direction. NH3 and C3H2 emissions are located inside the boundary of the CCS emission. C18O emission traces a lower density gas extending beyond the CCS boundary. Along the major axis of the dense core, CCS, NH3 and C3H2 emission show evidence of limb brightening. The observations are consistent with a chemically differentiated onion-shell structure for the L1498 core, with NH3 in the inner and CCS in the outer parts of the core. The high angular resolution (9"-12") spectral line maps obtained by combining NASA Goldstone 70 m and VLA data resolve the CCS 22 GHz emission in the southeast and northwest boundaries into arclike enhancements, supporting the picture that CCS emission originates in a shell outside the NH3 emitting region. Interferometric maps of CCS at 94 GHz and CS at 98 GHz show that their emitting regions contain several small-scale dense condensations. We suggest that the differences between the CCS, CS, C3H2, and NH3 emission are caused by a time-dependent effect as the core evolves slowly. We interpret the chemical and physical properties of L1498 in terms of a quasi-static (or slowly contracting) dense core in which the outer envelope is still growing. The growth rate of the core is determined by the density increase in the CCS shell resulting from the accretion of the outer low-density gas traced by C18O. We conclude that L1498 could become unstable to rapid collapse to form a protostar in less than 5 x 10(6) yr.

ALMA Measurements of the HNC and HC3N Distributions in Titan's Atmosphere

NASA Astrophysics Data System (ADS)

Cordiner, M. A.; Nixon, C. A.; Teanby, N. A.; Irwin, P. G. J.; Serigano, J.; Charnley, S. B.; Milam, S. N.; Mumma, M. J.; Lis, D. C.; Villanueva, G.; Paganini, L.; Kuan, Y.-J.; Remijan, A. J.

2014-11-01

We present spectrally and spatially resolved maps of HNC and HC3N emission from Titan's atmosphere, obtained using the Atacama Large Millimeter/submillimeter Array on 2013 November 17. These maps show anisotropic spatial distributions for both molecules, with resolved emission peaks in Titan's northern and southern hemispheres. The HC3N maps indicate enhanced concentrations of this molecule over the poles, consistent with previous studies of Titan's photochemistry and atmospheric circulation. Differences between the spectrally integrated flux distributions of HNC and HC3N show that these species are not co-spatial. The observed spectral line shapes are consistent with HNC being concentrated predominantly in the mesosphere and above (at altitudes z >~ 400 km), whereas HC3N is abundant at a broader range of altitudes (z ≈ 70-600 km). From spatial variations in the HC3N line profile, the locations of the HC3N emission peaks are shown to be variable as a function of altitude. The peaks in the integrated emission from HNC and the line core (upper atmosphere) component of HC3N (at z >~ 300 km) are found to be asymmetric with respect to Titan's polar axis, indicating that the mesosphere may be more longitudinally variable than previously thought. The spatially integrated HNC and HC3N spectra are modeled using the NEMESIS planetary atmosphere code and the resulting best-fitting disk-averaged vertical mixing ratio profiles are found to be in reasonable agreement with previous measurements for these species. Vertical column densities of the best-fitting gradient models for HNC and HC3N are 1.9 × 1013 cm-2 and 2.3 × 1014 cm-2, respectively.

Spatially resolved spectrophotometry of Comet P/Stephan-Oterma

NASA Technical Reports Server (NTRS)

Cochran, A. L.; Barker, E. S.

1985-01-01

Observations of Comet P/Stephan-Oterma were made with an Intensified Dissector Scanner spectrograph on the McDonald Observatory 2.7-m telescope during the period from July 1980 to February 1981. These spectra cover a range of heliocentric distances from 2.3 AU preperihelion to 1.8 AU postperihelion. A small aperture was used to map the spatial distributions of the gases in the coma. Column densities of the observed cometary emissions (CN, C3, CH, and C2) were calculated, and it is shown that Stephan-Oterma appeared nearly spherically symmetric. These date are used by Cochran (1985) to constrain chemical models of Stephan-Oterma.

Radiofrequency Electromagnetic Field Map of Timisoara

NASA Astrophysics Data System (ADS)

Stefu, N.; Solyom, I.; Arama, A.

2015-12-01

There are many electromagnetic field (EMF) sources nowadays acting simultaneously, especially in urban areas, making the theoretical estimation of electromagnetic power at ground level very difficult. This paper reports on EMF maps built with measurements collected in Timisoara, at various radiofrequencies. A grid of 15×15 squares was built (approximate resolution 400m x 400m) and measurements of the average and maximum values of the electric field E, magnetic field H and total power density S at 0.9, 1.8 and 2.4 GHz were collected in every node of the grid. Positions of the nodes in terms of latitude and longitude were also collected. Maps were built presenting the spatial distribution of the measured quantities over Timisoara. Potential influences of EMF on public health are discussed.

Analyzing the spatio-temporal relationship between dengue vector larval density and land-use using factor analysis and spatial ring mapping

PubMed Central

2012-01-01

Background Dengue, a mosquito-borne febrile viral disease, is found in tropical and sub-tropical regions and is now extending its range to temperate regions. The spread of the dengue viruses mainly depends on vector population (Aedes aegypti and Aedes albopictus), which is influenced by changing climatic conditions and various land-use/land-cover types. Spatial display of the relationship between dengue vector density and land-cover types is required to describe a near-future viral outbreak scenario. This study is aimed at exploring how land-cover types are linked to the behavior of dengue-transmitting mosquitoes. Methods Surveys were conducted in 92 villages of Phitsanulok Province Thailand. The sampling was conducted on three separate occasions in the months of March, May and July. Dengue indices, i.e. container index (C.I.), house index (H.I.) and Breteau index (B.I.) were used to map habitats conducible to dengue vector growth. Spatial epidemiological analysis using Bivariate Pearson’s correlation was conducted to evaluate the level of interdependence between larval density and land-use types. Factor analysis using principal component analysis (PCA) with varimax rotation was performed to ascertain the variance among land-use types. Furthermore, spatial ring method was used as to visualize spatially referenced, multivariate and temporal data in single information graphic. Results Results of dengue indices showed that the settlements around gasoline stations/workshops, in the vicinity of marsh/swamp and rice paddy appeared to be favorable habitat for dengue vector propagation at highly significant and positive correlation (p = 0.001) in the month of May. Settlements around the institutional areas were highly significant and positively correlated (p = 0.01) with H.I. in the month of March. Moreover, dengue indices in the month of March showed a significant and positive correlation (p <= 0.05) with deciduous forest. The H.I. of people living around horticulture land were significantly and positively correlated (p = 0.05) during the month of May, and perennial vegetation showed a highly significant and positive correlation (p = 0.001) in the month of March with C.I. and significant and positive correlation (p <= 0.05) with B.I., respectively. Conclusions The study concluded that gasoline stations/workshops, rice paddy, marsh/swamp and deciduous forests played highly significant role in dengue vector growth. Thus, the spatio-temporal relationships of dengue vector larval density and land-use types may help to predict favorable dengue habitat, and thereby enables public healthcare managers to take precautionary measures to prevent impending dengue outbreak. PMID:23043443

Analyzing the spatio-temporal relationship between dengue vector larval density and land-use using factor analysis and spatial ring mapping.

PubMed

Sarfraz, Muhammad Shahzad; Tripathi, Nitin K; Tipdecho, Taravudh; Thongbu, Thawisak; Kerdthong, Pornsuk; Souris, Marc

2012-10-09

Dengue, a mosquito-borne febrile viral disease, is found in tropical and sub-tropical regions and is now extending its range to temperate regions. The spread of the dengue viruses mainly depends on vector population (Aedes aegypti and Aedes albopictus), which is influenced by changing climatic conditions and various land-use/land-cover types. Spatial display of the relationship between dengue vector density and land-cover types is required to describe a near-future viral outbreak scenario. This study is aimed at exploring how land-cover types are linked to the behavior of dengue-transmitting mosquitoes. Surveys were conducted in 92 villages of Phitsanulok Province Thailand. The sampling was conducted on three separate occasions in the months of March, May and July. Dengue indices, i.e. container index (C.I.), house index (H.I.) and Breteau index (B.I.) were used to map habitats conducible to dengue vector growth. Spatial epidemiological analysis using Bivariate Pearson's correlation was conducted to evaluate the level of interdependence between larval density and land-use types. Factor analysis using principal component analysis (PCA) with varimax rotation was performed to ascertain the variance among land-use types. Furthermore, spatial ring method was used as to visualize spatially referenced, multivariate and temporal data in single information graphic. Results of dengue indices showed that the settlements around gasoline stations/workshops, in the vicinity of marsh/swamp and rice paddy appeared to be favorable habitat for dengue vector propagation at highly significant and positive correlation (p = 0.001) in the month of May. Settlements around the institutional areas were highly significant and positively correlated (p = 0.01) with H.I. in the month of March. Moreover, dengue indices in the month of March showed a significant and positive correlation (p <= 0.05) with deciduous forest. The H.I. of people living around horticulture land were significantly and positively correlated (p = 0.05) during the month of May, and perennial vegetation showed a highly significant and positive correlation (p = 0.001) in the month of March with C.I. and significant and positive correlation (p <= 0.05) with B.I., respectively. The study concluded that gasoline stations/workshops, rice paddy, marsh/swamp and deciduous forests played highly significant role in dengue vector growth. Thus, the spatio-temporal relationships of dengue vector larval density and land-use types may help to predict favorable dengue habitat, and thereby enables public healthcare managers to take precautionary measures to prevent impending dengue outbreak.

Mapping the Centimeter-Scale Spatial Variability of PAHs and Microbial Populations in the Rhizosphere of Two Plants

PubMed Central

Bourceret, Amélia; Leyval, Corinne; de Fouquet, Chantal; Cébron, Aurélie

2015-01-01

Rhizoremediation uses root development and exudation to favor microbial activity. Thus it can enhance polycyclic aromatic hydrocarbon (PAH) biodegradation in contaminated soils. Spatial heterogeneity of rhizosphere processes, mainly linked to the root development stage and to the plant species, could explain the contrasted rhizoremediation efficiency levels reported in the literature. Aim of the present study was to test if spatial variability in the whole plant rhizosphere, explored at the centimetre-scale, would influence the abundance of microorganisms (bacteria and fungi), and the abundance and activity of PAH-degrading bacteria, leading to spatial variability in PAH concentrations. Two contrasted rhizospheres were compared after 37 days of alfalfa or ryegrass growth in independent rhizotron devices. Almost all spiked PAHs were degraded, and the density of the PAH-degrading bacterial populations increased in both rhizospheres during the incubation period. Mapping of multiparametric data through geostatistical estimation (kriging) revealed that although root biomass was spatially structured, PAH distribution was not. However a greater variability of the PAH content was observed in the rhizosphere of alfalfa. Yet, in the ryegrass-planted rhizotron, the Gram-positive PAH-degraders followed a reverse depth gradient to root biomass, but were positively correlated to the soil pH and carbohydrate concentrations. The two rhizospheres structured the microbial community differently: a fungus-to-bacterium depth gradient similar to the root biomass gradient only formed in the alfalfa rhizotron. PMID:26599438

Random waves in the brain: Symmetries and defect generation in the visual cortex

NASA Astrophysics Data System (ADS)

Schnabel, M.; Kaschube, M.; Löwel, S.; Wolf, F.

2007-06-01

How orientation maps in the visual cortex of the brain develop is a matter of long standing debate. Experimental and theoretical evidence suggests that their development represents an activity-dependent self-organization process. Theoretical analysis [1] exploring this hypothesis predicted that maps at an early developmental stage are realizations of Gaussian random fields exhibiting a rigorous lower bound for their densities of topological defects, called pinwheels. As a consequence, lower pinwheel densities, if observed in adult animals, are predicted to develop through the motion and annihilation of pinwheel pairs. Despite of being valid for a large class of developmental models this result depends on the symmetries of the models and thus of the predicted random field ensembles. In [1] invariance of the orientation map's statistical properties under independent space rotations and orientation shifts was assumed. However, full rotation symmetry appears to be broken by interactions of cortical neurons, e.g. selective couplings between groups of neurons with collinear orientation preferences [2]. A recently proposed new symmetry, called shift-twist symmetry [3], stating that spatial rotations have to occur together with orientation shifts in order to be an appropriate symmetry transformation, is more consistent with this organization. Here we generalize our random field approach to this important symmetry class. We propose a new class of shift-twist symmetric Gaussian random fields and derive the general correlation functions of this ensemble. It turns out that despite strong effects of the shift-twist symmetry on the structure of the correlation functions and on the map layout the lower bound on the pinwheel densities remains unaffected, predicting pinwheel annihilation in systems with low pinwheel densities.

Reservoir area of influence and implications for fisheries management

USGS Publications Warehouse

Martin, Dustin R.; Chizinski, Christopher J.; Pope, Kevin L.

2015-01-01

Understanding the spatial area that a reservoir draws anglers from, defined as the reservoir's area of influence, and the potential overlap of that area of influence between reservoirs is important for fishery managers. Our objective was to define the area of influence for reservoirs of the Salt Valley regional fishery in southeastern Nebraska using kernel density estimation. We used angler survey data obtained from in-person interviews at 17 reservoirs during 2009–2012. The area of influence, defined by the 95% kernel density, for reservoirs within the Salt Valley regional fishery varied, indicating that anglers use reservoirs differently across the regional fishery. Areas of influence reveal angler preferences in a regional context, indicating preferred reservoirs with a greater area of influence. Further, differences in areas of influences across time and among reservoirs can be used as an assessment following management changes on an individual reservoir or within a regional fishery. Kernel density estimation provided a clear method for creating spatial maps of areas of influence and provided a two-dimensional view of angler travel, as opposed to the traditional mean travel distance assessment.

Getting to Know a Place: Built Environment Walkability and Children’s Spatial Representation of Their Home-School (h–s) Route

PubMed Central

Moran, Mika R.; Eizenberg, Efrat; Plaut, Pnina

2017-01-01

The literature on environmental walkability to date has mainly focused on walking and related health outcomes. While previous studies suggest associations between walking and spatial knowledge, the associations between environmental walkability and spatial knowledge is yet to be explored. The current study addresses this lacuna in research by exploring children’s mental representations of their home-school (h–s) route, vis-à-vis objectively measured environmental attributes along the actual routes. Ninety-two children aged 10–12 years old (5th and 6th graders) drew sketch maps depicting their h–s route and drew the actual route on a neighborhood map, in addition to completing a brief survey. h–s routes went through Geographic Information Systems (GIS) analysis, yielding an en-route walkability index and its components. Children in traditional neighborhoods outperformed in the route’s orientation and structure, but not in the richness of the drawn maps. The orientation and structure of the drawn routes was related to objectively measured walkability, density, street connectivity and commercial land-uses along h–s routes. These associations remained significant among children who walked to school, but not among those who were driven to school. These findings highlight the importance of urban form and school travel mode in acquiring navigation skills and getting to know one’s neighborhood. PMID:28587315

NeuroMap: A Spline-Based Interactive Open-Source Software for Spatiotemporal Mapping of 2D and 3D MEA Data

PubMed Central

Abdoun, Oussama; Joucla, Sébastien; Mazzocco, Claire; Yvert, Blaise

2010-01-01

A major characteristic of neural networks is the complexity of their organization at various spatial scales, from microscopic local circuits to macroscopic brain-scale areas. Understanding how neural information is processed thus entails the ability to study them at multiple scales simultaneously. This is made possible using microelectrodes array (MEA) technology. Indeed, high-density MEAs provide large-scale coverage (several square millimeters) of whole neural structures combined with microscopic resolution (about 50 μm) of unit activity. Yet, current options for spatiotemporal representation of MEA-collected data remain limited. Here we present NeuroMap, a new interactive Matlab-based software for spatiotemporal mapping of MEA data. NeuroMap uses thin plate spline interpolation, which provides several assets with respect to conventional mapping methods used currently. First, any MEA design can be considered, including 2D or 3D, regular or irregular, arrangements of electrodes. Second, spline interpolation allows the estimation of activity across the tissue with local extrema not necessarily at recording sites. Finally, this interpolation approach provides a straightforward analytical estimation of the spatial Laplacian for better current sources localization. In this software, coregistration of 2D MEA data on the anatomy of the neural tissue is made possible by fine matching of anatomical data with electrode positions using rigid-deformation-based correction of anatomical pictures. Overall, NeuroMap provides substantial material for detailed spatiotemporal analysis of MEA data. The package is distributed under GNU General Public License and available at http://sites.google.com/site/neuromapsoftware. PMID:21344013

NeuroMap: A Spline-Based Interactive Open-Source Software for Spatiotemporal Mapping of 2D and 3D MEA Data.

PubMed

Abdoun, Oussama; Joucla, Sébastien; Mazzocco, Claire; Yvert, Blaise

2011-01-01

A major characteristic of neural networks is the complexity of their organization at various spatial scales, from microscopic local circuits to macroscopic brain-scale areas. Understanding how neural information is processed thus entails the ability to study them at multiple scales simultaneously. This is made possible using microelectrodes array (MEA) technology. Indeed, high-density MEAs provide large-scale coverage (several square millimeters) of whole neural structures combined with microscopic resolution (about 50 μm) of unit activity. Yet, current options for spatiotemporal representation of MEA-collected data remain limited. Here we present NeuroMap, a new interactive Matlab-based software for spatiotemporal mapping of MEA data. NeuroMap uses thin plate spline interpolation, which provides several assets with respect to conventional mapping methods used currently. First, any MEA design can be considered, including 2D or 3D, regular or irregular, arrangements of electrodes. Second, spline interpolation allows the estimation of activity across the tissue with local extrema not necessarily at recording sites. Finally, this interpolation approach provides a straightforward analytical estimation of the spatial Laplacian for better current sources localization. In this software, coregistration of 2D MEA data on the anatomy of the neural tissue is made possible by fine matching of anatomical data with electrode positions using rigid-deformation-based correction of anatomical pictures. Overall, NeuroMap provides substantial material for detailed spatiotemporal analysis of MEA data. The package is distributed under GNU General Public License and available at http://sites.google.com/site/neuromapsoftware.

Landslide susceptibility revealed by LIDAR imagery and historical records, Seattle, Washington

USGS Publications Warehouse

Schulz, W.H.

2007-01-01

Light detection and ranging (LIDAR) data were used to visually map landslides, headscarps, and denuded slopes in Seattle, Washington. Four times more landslides were mapped than by previous efforts that used aerial photographs. The mapped landforms (landslides, headscarps, and denuded slopes) were created by many individual landslides. The spatial distribution of mapped landforms and 1308 historical landslides show that historical landslide activity has been concentrated on the mapped landforms, and that most of the landslide activity that created the landforms was prehistoric. Thus, the spatial densities of historical landslides on the landforms provide approximations of the landforms' relative susceptibilities to future landsliding. Historical landslide characteristics appear to be closely related to landform type so relative susceptibilities were determined for landslides with various characteristics. No strong relations were identified between stratigraphy and landslide occurrence; however, landslide characteristics and slope morphology appear to be related to stratigraphic conditions. Human activity is responsible for causing about 80% of historical Seattle landslides. The distribution of mapped landforms and human-caused landslides suggests the probable characteristics of future human-caused landslides on each of the landforms. The distribution of mapped landforms and historical landslides suggests that erosion of slope-toes by surface water has been a necessary condition for causing Seattle landslides. Human activity has largely arrested this erosion, which implies that landslide activity will decrease with time as hillsides naturally stabilize. However, evaluation of glacial-age analogs of areas of recent slope-toe erosion suggests that landslide activity in Seattle will continue for the foreseeable future. ?? 2006 Elsevier B.V. All rights reserved.

Spatial heterogeneity and temporal evolution of malaria transmission risk in Dakar, Senegal, according to remotely sensed environmental data

PubMed Central

2010-01-01

Background The United Nations forecasts that by 2050, more than 60% of the African population will live in cities. Thus, urban malaria is considered an important emerging health problem in that continent. Remote sensing (RS) and geographic information systems (GIS) are useful tools for addressing the challenge of assessing, understanding and spatially focusing malaria control activities. The objectives of the present study were to use high spatial resolution SPOT (Satellite Pour l'Observation de la Terre) satellite images to identify some urban environmental factors in Dakar associated with Anopheles arabiensis densities, to assess the persistence of these associations and to describe spatial changes in at-risk environments using a decadal time scale. Methods Two SPOT images from the 1996 and 2007 rainy seasons in Dakar were processed to extract environmental factors, using supervised classification of land use and land cover, and a calculation of NDVI (Normalized Difference Vegetation Index) and distance to vegetation. Linear regressions were fitted to identify the ecological factors associated with An. arabiensis aggressiveness measured in 1994-97 in the South and centre districts of Dakar. Risk maps for populated areas were computed and compared for 1996 and 2007 using the results of the statistical models. Results Almost 60% of the variability in anopheline aggressiveness measured in 1994-97 was explained with only one variable: the built-up area in a 300-m radius buffer around the catching points. This association remained stable between 1996 and 2007. Risk maps were drawn by inverting the statistical association. The total increase of the built-up areas in Dakar was about 30% between 1996 and 2007. In proportion to the total population of the city, the population at high risk for malaria fell from 32% to 20%, whereas the low-risk population rose from 29 to 41%. Conclusions Environmental data retrieved from high spatial resolution SPOT satellite images were associated with An. arabiensis densities in Dakar urban setting, which allowed to generate malaria transmission risk maps. The evolution of the risk was quantified, and the results indicated there are benefits of urbanization in Dakar, since the proportion of the low risk population increased while urbanization progressed. PMID:20815867

The development of wing shape in Lepidoptera: mitotic density, not orientation, is the primary determinant of shape.

PubMed

Nijhout, H Frederik; Cinderella, Margaret; Grunert, Laura W

2014-03-01

The wings of butterflies and moths develop from imaginal disks whose structure is always congruent with the final adult wing. It is therefore possible to map every point on the imaginal disk to a location on the adult wing throughout ontogeny. We studied the growth patterns of the wings of two distantly related species with very different adult wing shapes, Junonia coenia and Manduca sexta. The shape of the wing disks change throughout their growth phase in a species-specific pattern. We measured mitotic densities and mitotic orientation in successive stages of wing development approximately one cell division apart. Cell proliferation was spatially patterned, and the density of mitoses was highly correlated with local growth. Unlike other systems in which the direction of mitoses has been viewed as the primary determinant of directional growth, we found that in these two species the direction of growth was only weakly correlated with the orientation of mitoses. Directional growth appears to be imposed by a constantly changing spatial pattern of cell division coupled with a weak bias in the orientation of cell division. Because growth and cell division in imaginal disk require ecdysone and insulin signaling, the changing spatial pattern of cell division may due to a changing pattern of expression of receptors or downstream elements in the signaling pathways for one or both of these hormones. Evolution of wing shape comes about by changes in the progression of spatial patterns of cell division. © 2014 Wiley Periodicals, Inc.

Identifying western yellow-billed cuckoo breeding habitat with a dual modelling approach

USGS Publications Warehouse

Johnson, Matthew J.; Hatten, James R.; Holmes, Jennifer A.; Shafroth, Patrick B.

2017-01-01

The western population of the yellow-billed cuckoo (Coccyzus americanus) was recently listed as threatened under the federal Endangered Species Act. Yellow-billed cuckoo conservation efforts require the identification of features and area requirements associated with high quality, riparian forest habitat at spatial scales that range from nest microhabitat to landscape, as well as lower-suitability areas that can be enhanced or restored. Spatially explicit models inform conservation efforts by increasing ecological understanding of a target species, especially at landscape scales. Previous yellow-billed cuckoo modelling efforts derived plant-community maps from aerial photography, an expensive and oftentimes inconsistent approach. Satellite models can remotely map vegetation features (e.g., vegetation density, heterogeneity in vegetation density or structure) across large areas with near perfect repeatability, but they usually cannot identify plant communities. We used aerial photos and satellite imagery, and a hierarchical spatial scale approach, to identify yellow-billed cuckoo breeding habitat along the Lower Colorado River and its tributaries. Aerial-photo and satellite models identified several key features associated with yellow-billed cuckoo breeding locations: (1) a 4.5 ha core area of dense cottonwood-willow vegetation, (2) a large native, heterogeneously dense forest (72 ha) around the core area, and (3) moderately rough topography. The odds of yellow-billed cuckoo occurrence decreased rapidly as the amount of tamarisk cover increased or when cottonwood-willow vegetation was limited. We achieved model accuracies of 75–80% in the project area the following year after updating the imagery and location data. The two model types had very similar probability maps, largely predicting the same areas as high quality habitat. While each model provided unique information, a dual-modelling approach provided a more complete picture of yellow-billed cuckoo habitat requirements and will be useful for management and conservation activities.

Lidar-based fracture characterization: An outcrop-scale study of the Woodford Shale, McAlister Shale Pit, Oklahoma

NASA Astrophysics Data System (ADS)

Hanzel, Jason

The use of lidar (light detection and ranging), a remote sensing tool based on principles of laser optometry, in mapping complex, multi-scale fracture networks had not been rigorously tested prior to this study despite its foreseeable utility in interpreting rock fabric with imprints of complex tectonic evolution. This thesis demonstrates lidar-based characterization of the Woodford Shale where intense fracturing could be due to both tectonism and mineralogy. The study area is the McAlister Shale Pit in south-central Oklahoma where both the upper and middle sections of the Woodford Shale are exposed and can be lidar-mapped. Lidar results are validated using hand-measured strike and dips of fracture planes, thin sections and mineral chemistry of selected samples using X-ray diffraction (XRD). Complexity of the fracture patterns as well as inaccessibility of multiple locations within the shale pit makes hand-measurement prone to errors and biases; lidar provides an opportunity for less biased and more efficient field mapping. Fracture mapping with lidar is a multi-step process. The lidar data are converted from point clouds into a mesh through triangulation. User-defined parameters such as size and orientation of the individual triangular elements are then used to group similar elements into surfaces. The strike and dip attribute of the simulated surfaces are visualized in an equal area lower hemisphere projection stereonet. Three fracture sets were identified in the upper and middle sections with common orientation but substantially different spatial density. Measured surface attributes and spatial density relations from lidar were validated using their hand-measured counterparts. Thin section analysis suggests that high fracture density in the upper Woodford measured by both the lidar and the hand-measured data could be due to high quartz. A significant finding of this study is the reciprocal relation between lidar intensity and gamma-ray (GR), which is generally used to infer outcrop mineralogy. XRD analysis of representative samples along the common profiles show that both GR and lidar intensity were influenced by the same minerals in essentially opposite ways. Results strongly suggest that the lidar cannot only remotely map the geomorphology, but also the relative mineralogical variations to the first order of approximation.

Using Flow Regime Lightning and Sounding Climatologies to Initialize Gridded Lightning Threat Forecasts for East Central Florida

NASA Technical Reports Server (NTRS)

Lambert, Winifred; Short, David; Wolkmer, Matthew; Sharp, David; Spratt, Scott

2006-01-01

Each morning, the forecasters at the National Weather Service in Melbourne, FL (NWS MLB) produce an experimental cloud-to-ground (CG) lightning threat index map for their county warning area (CWA) that is posted to their web site (http://www.srh.weather.gov/mlb/ghwo/lightning.shtml) . Given the hazardous nature of lightning in East Central Florida, especially during the warm season months of May September, these maps help users factor the threat of lightning, relative to their location, into their daily plans. The maps are color-coded in five levels from Very Low to Extreme, with threat level definitions based on the probability of lightning occurrence and the expected amount of CG activity. On a day in which thunderstorms are expected, there are typically two or more threat levels depicted spatially across the CWA. The locations of relative lightning threat maxima and minima often depend on the position and orientation of the low-level ridge axis, forecast propagation and interaction of sea/lake/outflow boundaries, expected evolution of moisture and stability fields, and other factors that can influence the spatial distribution of thunderstorms over the CWA. The lightning threat index maps are issued for the 24-hour period beginning at 1200 UTC each day with a grid resolution of 5 km x 5 km. Product preparation is performed on the AWIPS Graphical Forecast Editor (GFE), which is the standard NWS platform for graphical editing. Currently, the forecasters create each map manually, starting with a blank map. To improve efficiency of the forecast process, NWS MLB requested that the Applied Meteorology Unit (AMU) create gridded warm season lightning climatologies that could be used as first-guess inputs to initialize lightning threat index maps. The gridded values requested included CG strike densities and frequency of occurrence stratified by synoptic-scale flow regime. The intent is to improve consistency between forecasters while allowing them to focus on the mesoscale detail of the forecast, ultimately benefiting the end-users of the product. Several studies took place at the Florida State University (FSU) and NWS Tallahassee (TAE) in which they created daily flow regimes using Florida 1200 UTC synoptic soundings and CG strike densities, or number of strikes per specified area. The soundings used to determine the flow regimes were taken at Miami (MIA), Tampa (TBW), and Jacksonville (JAX), FL, and the lightning data for the strike densities came from the National Lightning Detection Network (NLDN). The densities were created on a 2.5 km x 2.5 km grid for every hour of every day during the warm seasons in the years 1989-2004. The grids encompass an area that includes the entire state of Florida and adjacent Atlantic and Gulf of Mexico waters. Personnel at FSU and NWS TAE provided this data and supporting software for the work performed by the AMU.

Using Flow Regime Lightning and Sounding Climatologies to Initialize Gridded Lightning Threat Forecasts for East Central Florida

NASA Technical Reports Server (NTRS)

Lambert, Winifred; Short, David; Volkmer, Matthew; Sharp, David; Spratt, Scott

2007-01-01

Each morning, the forecasters at the National Weather Service in Melbourne, FL (NWS MLB) produce an experimental cloud-to-ground (CG) lightning threat index map for their county warning area (CWA) that is posted to their web site (httl://www.srh.weather.gov/mlb/ghwo/lightning.shtml) . Given the hazardous nature of lightning in East Central Florida, especially during the warm season months of May September, these maps help users factor the threat of lightning, relative to their location, into their daily plans. The maps are color-coded in five levels from Very Low to Extreme, with threat level definitions based on the probability of lightning occurrence and the expected amount of CG activity. On a day in which thunderstorms are expected, there are typically two or more threat levels depicted spatially across the CWA. The locations of relative lightning threat maxima and minima often depend on the position and orientation of the low-level ridge axis, forecast propagation and interaction of sea/lake/outflow boundaries, expected evolution of moisture and stability fields, and other factors that can influence the spatial distribution of thunderstorms over the CWA. The lightning threat index maps are issued for the 24-hour period beginning at 1200 UTC each day with a grid resolution of 5 km x 5 km. Product preparation is performed on the AWIPS Graphical Forecast Editor (GFE), which is the standard NWS platform for graphical editing. Until recently, the forecasters created each map manually, starting with a blank map. To improve efficiency of the forecast process, NWS MLB requested that the Applied Meteorology Unit (AMU) create gridded warm season lightning climatologies that could be used as first-guess inputs to initialize lightning threat index maps. The gridded values requested included CG strike densities and frequency of occurrence stratified by synoptic-scale flow regime. The intent was to improve consistency between forecasters while allowing them to focus on the mesoscale detail of the forecast. Several studies took place at the Florida State University (FSU) and NWS Tallahassee (TAE) in which they created daily flow regimes using Florida 1200 UTC synoptic soundings and CG strike densities, or number of strikes per specified area. The soundings used to determine the flow regimes were taken at Miami (MIA), Tampa (TBW), and Jacksonville (JAX), FL, and the lightning data for the strike densities came from the National Lightning Detection Network (NLDN). The densities were created on a 2.5 km x 2.5 km grid for every hour of every day during the warm seasons in the years 1989-2004. The grids encompass an area that includes the entire state of Florida and adjacent Atlantic and Gulf of Mexico waters. Personnel at FSU and NWS TAE provided this data and supporting software for the work performed by the AMU.

Forest Canopy Cover and Height from MISR in Topographically Complex Southwestern US Landscape Assessed with High Quality Reference Data

NASA Technical Reports Server (NTRS)

Chopping, Mark; North, Malcolm; Chen, Jiquan; Schaaf, Crystal B.; Blair, J. Bryan; Martonchik, John V.; Bull, Michael A.

2012-01-01

This study addresses the retrieval of spatially contiguous canopy cover and height estimates in southwestern USforests via inversion of a geometric-optical (GO) model against surface bidirectional reflectance factor (BRF) estimates from the Multi-angle Imaging SpectroRadiometer (MISR). Model inversion can provide such maps if good estimates of the background bidirectional reflectance distribution function (BRDF) are available. The study area is in the Sierra National Forest in the Sierra Nevada of California. Tree number density, mean crown radius, and fractional cover reference estimates were obtained via analysis of QuickBird 0.6 m spatial resolution panchromatic imagery usingthe CANopy Analysis with Panchromatic Imagery (CANAPI) algorithm, while RH50, RH75 and RH100 (50, 75, and 100 energy return) height data were obtained from the NASA Laser Vegetation Imaging Sensor (LVIS), a full waveform light detection and ranging (lidar) instrument. These canopy parameters were used to drive a modified version of the simple GO model (SGM), accurately reproducing patterns ofMISR 672 nm band surface reflectance (mean RMSE 0.011, mean R2 0.82, N 1048). Cover and height maps were obtained through model inversion against MISR 672 nm reflectance estimates on a 250 m grid.The free parameters were tree number density and mean crown radius. RMSE values with respect to reference data for the cover and height retrievals were 0.05 and 6.65 m, respectively, with of 0.54 and 0.49. MISR can thus provide maps of forest cover and height in areas of topographic variation although refinements are required to improve retrieval precision.

Introduction of geospatial perspective to the ecology of fish-habitat relationships in Indonesian coral reefs: A remote sensing approach

NASA Astrophysics Data System (ADS)

Sawayama, Shuhei; Nurdin, Nurjannah; Akbar AS, Muhammad; Sakamoto, Shingo X.; Komatsu, Teruhisa

2015-06-01

Coral reef ecosystems worldwide are now being harmed by various stresses accompanying the degradation of fish habitats and thus knowledge of fish-habitat relationships is urgently required. Because conventional research methods were not practical for this purpose due to the lack of a geospatial perspective, we attempted to develop a research method integrating visual fish observation with a seabed habitat map and to expand knowledge to a two-dimensional scale. WorldView-2 satellite imagery of Spermonde Archipelago, Indonesia obtained in September 2012 was analyzed and classified into four typical substrates: live coral, dead coral, seagrass and sand. Overall classification accuracy of this map was 81.3% and considered precise enough for subsequent analyses. Three sub-areas (CC: continuous coral reef, BC: boundary of coral reef and FC: few live coral zone) around reef slopes were extracted from the map. Visual transect surveys for several fish species were conducted within each sub-area in June 2013. As a result, Mean density (Ind. / 300 m2) of Chaetodon octofasciatus, known as an obligate feeder of corals, was significantly higher at BC than at the others (p < 0.05), implying that this species' density is strongly influenced by spatial configuration of its habitat, like the "edge effect." This indicates that future conservation procedures for coral reef fishes should consider not only coral cover but also its spatial configuration. The present study also indicates that the introduction of a geospatial perspective derived from remote sensing has great potential to progress conventional ecological studies on coral reef fishes.

Recurrence quantification analysis applied to spatiotemporal pattern analysis in high-density mapping of human atrial fibrillation.

PubMed

Zeemering, Stef; Bonizzi, Pietro; Maesen, Bart; Peeters, Ralf; Schotten, Ulrich

2015-01-01

Spatiotemporal complexity of atrial fibrillation (AF) patterns is often quantified by annotated intracardiac contact mapping. We introduce a new approach that applies recurrence plot (RP) construction followed by recurrence quantification analysis (RQA) to epicardial atrial electrograms, recorded with a high-density grid of electrodes. In 32 patients with no history of AF (aAF, n=11), paroxysmal AF (PAF, n=12) and persistent AF (persAF, n=9), RPs were constructed using a phase space electrogram embedding dimension equal to the estimated AF cycle length. Spatial information was incorporated by 1) averaging the recurrence over all electrodes, and 2) by applying principal component analysis (PCA) to the matrix of embedded electrograms and selecting the first principal component as a representation of spatial diversity. Standard RQA parameters were computed on the constructed RPs and correlated to the number of fibrillation waves per AF cycle (NW). Averaged RP RQA parameters showed no correlation with NW. Correlations improved when applying PCA, with maximum correlation achieved between RP threshold and NW (RR1%, r=0.68, p <; 0.001) and RP determinism (DET, r=-0.64, p <; 0.001). All studied RQA parameters based on the PCA RP were able to discriminate between persAF and aAF/PAF (DET persAF 0.40 ± 0.11 vs. 0.59 ± 0.14/0.62 ± 0.16, p <; 0.01). RP construction and RQA combined with PCA provide a quick and reliable tool to visualize dynamical behaviour and to assess the complexity of contact mapping patterns in AF.

Statistical and Spatial Analysis of Bathymetric Data for the St. Clair River, 1971-2007

USGS Publications Warehouse

Bennion, David

2009-01-01

To address questions concerning ongoing geomorphic processes in the St. Clair River, selected bathymetric datasets spanning 36 years were analyzed. Comparisons of recent high-resolution datasets covering the upper river indicate a highly variable, active environment. Although statistical and spatial comparisons of the datasets show that some changes to the channel size and shape have taken place during the study period, uncertainty associated with various survey methods and interpolation processes limit the statistically certain results. The methods used to spatially compare the datasets are sensitive to small variations in position and depth that are within the range of uncertainty associated with the datasets. Characteristics of the data, such as the density of measured points and the range of values surveyed, can also influence the results of spatial comparison. With due consideration of these limitations, apparently active and ongoing areas of elevation change in the river are mapped and discussed.

Edge Density Imaging: Mapping the Anatomic Embedding of the Structural Connectome Within the White Matter of the Human Brain

PubMed Central

Owen, Julia P.; Chang, Yi-Shin; Mukherjee, Pratik

2015-01-01

The structural connectome has emerged as a powerful tool to characterize the network architecture of the human brain and shows great potential for generating important new biomarkers for neurologic and psychiatric disorders. The edges of the cerebral graph traverse white matter to interconnect cortical and subcortical nodes, although the anatomic embedding of these edges is generally overlooked in the literature. Mapping the paths of the connectome edges could elucidate the relative importance of individual white matter tracts to the overall network topology of the brain and also lead to a better understanding of the effect of regionally-specific white matter pathology on cognition and behavior. In this work, we introduce edge density imaging (EDI), which maps the number of network edges that pass through every white matter voxel. Test-retest analysis shows good to excellent reliability for edge density (ED) measurements, with consistent results using different cortical and subcortical parcellation schemes and different diffusion MR imaging acquisition parameters. We also demonstrate that ED yields complementary information to both traditional and emerging voxel-wise metrics of white matter microstructure and connectivity, including fractional anisotropy, track density, fiber orientation dispersion and neurite density. Our results demonstrate spatially ordered variations of ED throughout the white matter, notably including greater ED in posterior than anterior cerebral white matter. The EDI framework is employed to map the white matter regions that are enriched with pathways connecting rich club nodes and also those with high densities of intra-modular and inter-modular edges. We show that periventricular white matter has particularly high ED and high densities of rich club edges, which is significant for diseases in which these areas are selectively affected, ranging from white matter injury of prematurity in infants to leukoaraiosis in the elderly. Using edge betweenness centrality, we identify specific white matter regions involved in a large number of shortest paths, some containing highly connected rich club edges while others are relatively isolated within individual modules. Overall, these findings reveal an intricate relationship between white matter anatomy and the structural connectome, motivating further exploration of EDI for biomarkers of cognition and behavior. PMID:25592996

PHIBSS: MOLECULAR GAS, EXTINCTION, STAR FORMATION, AND KINEMATICS IN THE z = 1.5 STAR-FORMING GALAXY EGS13011166

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

Genzel, R.; Tacconi, L. J.; Kurk, J.

We report matched resolution imaging spectroscopy of the CO 3-2 line (with the IRAM Plateau de Bure millimeter interferometer) and of the H{alpha} line (with LUCI at the Large Binocular Telescope) in the massive z = 1.53 main-sequence galaxy EGS 13011166, as part of the ''Plateau de Bure high-z, blue-sequence survey'' (PHIBSS: Tacconi et al.). We combine these data with Hubble Space Telescope V-I-J-H-band maps to derive spatially resolved distributions of stellar surface density, star formation rate, molecular gas surface density, optical extinction, and gas kinematics. The spatial distribution and kinematics of the ionized and molecular gas are remarkably similarmore » and are well modeled by a turbulent, globally Toomre unstable, rotating disk. The stellar surface density distribution is smoother than the clumpy rest-frame UV/optical light distribution and peaks in an obscured, star-forming massive bulge near the dynamical center. The molecular gas surface density and the effective optical screen extinction track each other and are well modeled by a ''mixed'' extinction model. The inferred slope of the spatially resolved molecular gas to star formation rate relation, N = dlog{Sigma}{sub starform}/dlog{Sigma}{sub molgas}, depends strongly on the adopted extinction model, and can vary from 0.8 to 1.7. For the preferred mixed dust-gas model, we find N = 1.14 {+-} 0.1.« less

3He Diffusion MRI of the Lung

PubMed Central

Conradi, Mark S.; Yablonskiy, Dmitriy A.; Woods, Jason C.; Gierada, David S.; Jacob, Richard E.; Chang, Yulin V.; Choong, Cliff K.; Sukstanskii, Alex L.; Tanoli, Tariq; Lefrak, Stephen S.; Cooper, Joel D.

2007-01-01

Rationale and Objectives MR imaging of the restricted diffusion of laser-polarized 3He gas provides unique insights into the changes in lung microstructure in emphysema. Results We discuss measurements of ventilation (spin density), mean diffusivity, and the anisotropy of diffusion, which yields the mean acinar airway radius. In addition, the use of spatially modulated longitudinal magnetization allows diffusion to be measured over longer distances and times, with sensitivity to collateral ventilation paths. Early results are also presented for spin density and diffusivity maps made with a perfluorinated inert gas, C3F8. Methods Techniques for purging and imaging excised lungs are discussed. PMID:16253852

Retinal ganglion cell topography and spatial resolving power in penguins.

PubMed

Coimbra, João Paulo; Nolan, Paul M; Collin, Shaun P; Hart, Nathan S

2012-01-01

Penguins are a group of flightless seabirds that exhibit numerous morphological, behavioral and ecological adaptations to their amphibious lifestyle, but little is known about the topographic organization of neurons in their retinas. In this study, we used retinal wholemounts and stereological methods to estimate the total number and topographic distribution of retinal ganglion cells in addition to an anatomical estimate of spatial resolving power in two species of penguins: the little penguin, Eudyptula minor, and the king penguin, Aptenodytes patagonicus. The total number of ganglion cells per retina was approximately 1,200,000 in the little penguin and 1,110,000 in the king penguin. The topographic distribution of retinal ganglion cells in both species revealed the presence of a prominent horizontal visual streak with steeper gradients in the little penguin. The little penguin retinas showed ganglion cell density peaks of 21,867 cells/mm², affording spatial resolution in water of 17.07-17.46 cycles/degree (12.81-13.09 cycles/degree in air). In contrast, the king penguin showed a relatively lower peak density of ganglion cells of 14,222 cells/mm², but--due to its larger eye--slightly higher spatial resolution in water of 20.40 cycles/degree (15.30 cycles/degree in air). In addition, we mapped the distribution of giant ganglion cells in both penguin species using Nissl-stained wholemounts. In both species, topographic mapping of this cell type revealed the presence of an area gigantocellularis with a concentric organization of isodensity contours showing a peak in the far temporal retina of approximately 70 cells/mm² in the little penguin and 39 cells/mm² in the king penguin. Giant ganglion cell densities gradually fall towards the outermost isodensity contours revealing the presence of a vertically organized streak. In the little penguin, we confirmed our cytological characterization of giant ganglion cells using immunohistochemistry for microtubule-associated protein 2. This suite of retinal specializations, which is also observed in the closely related procellariiform seabirds, affords the eyes of the little and king penguins panoramic surveillance of the horizon and motion detection in the frontal visual field. Copyright © 2012 S. Karger AG, Basel.

Assessment of the vegetation cover in a burned area 22-years ago using remote sensing techniques and GIS analysis (Sierra de las Nieves, South of Spain).

NASA Astrophysics Data System (ADS)

Martínez-Murillo, Juan F.; Remond, Ricardo; Ruiz-Sinoga, José D.

2015-04-01

The study aim was to characterize the vegetation cover in a burned area 22-years ago considering the previous situation to wildfire in 1991 and the current one in 2013. The objectives were to: (i) compare the current and previous vegetation cover to widlfire; (ii) evaluate whether the current vegetation has recovered the previous cover to wildfire; and (iii) determine the spatial variability of vegetation recovery after 22-years since the wildfire. The study area is located in Sierra de las Nieves, South of Spain. It corresponds to an area affected by a wildfire in August 8th, 1991. The burned area was equal to 8156 ha. The burn severity was spatially very high. The main geographic features of the burned area are: mountainous topography (altitudes ranging from 250 m to 1500 m; slope gradient >25%; exposure mainly southfacing); igneous (peridotites), metamorphic (gneiss) and calcareous rocks (limestones); and predominant forest land use (Pinus pinaster sp. woodlands, 10%; pinus opened forest + shrubland, 40%; shrubland, 35%; and bare soil + grassland, 15%). Remote sensing techniques and GIS analysis has been applied to achieve the objectives. Landsat 5 and Landsat 8 images were used: July 13th, 1991 and July 1st, 2013, for the previous wildfire situation and 22-years after, respectively. The 1990 CORINE land cover was also considered to map 1991 land uses prior the wildfire. Likewise, the Andalucía Regional Government wildfire historic records were used to select the burned area and its geographical limit. 1991 and 2013 land cover map were obtained by means of object-oriented classifications. Also, NDVI and PVI1 vegetation indexes were calculated and mapped for both years. Finally, some images transformations and kernel density images were applied to determine the most recovered areas and to map the spatial concentration of bare soil and pine cover areas in 1991 and 2013, respectively. According to the results, the combination of remote sensing and GIS analysis let map the most recovered areas affected by the wildfire in 1991. The vegetation indexes indicated that the vegetation cover in 2013 was still lower than that mapped just before the 1991 widlfire in most of the burned area after 22-years. This result was also confirmed by other techniques applied. Finally, the kernel density surface let identify and locate the most recovered areas of pine cover as well as those areas that still remain totally or partially uncovered (bare soil.

Rapid case-based mapping of seasonal malaria transmission risk for strategic elimination planning in Swaziland

PubMed Central

2013-01-01

Background As successful malaria control programmes move towards elimination, they must identify residual transmission foci, target vector control to high-risk areas, focus on both asymptomatic and symptomatic infections, and manage importation risk. High spatial and temporal resolution maps of malaria risk can support all of these activities, but commonly available malaria maps are based on parasite rate, a poor metric for measuring malaria at extremely low prevalence. New approaches are required to provide case-based risk maps to countries seeking to identify remaining hotspots of transmission while managing the risk of transmission from imported cases. Methods Household locations and travel histories of confirmed malaria patients during 2011 were recorded through routine surveillance by the Swaziland National Malaria Control Programme for the higher transmission months of January to April and the lower transmission months of May to December. Household locations for patients with no travel history to endemic areas were compared against a random set of background points sampled proportionate to population density with respect to a set of variables related to environment, population density, vector control, and distance to the locations of identified imported cases. Comparisons were made separately for the high and low transmission seasons. The Random Forests regression tree classification approach was used to generate maps predicting the probability of a locally acquired case at 100 m resolution across Swaziland for each season. Results Results indicated that case households during the high transmission season tended to be located in areas of lower elevation, closer to bodies of water, in more sparsely populated areas, with lower rainfall and warmer temperatures, and closer to imported cases than random background points (all p < 0.001). Similar differences were evident during the low transmission season. Maps from the fit models suggested better predictive ability during the high season. Both models proved useful at predicting the locations of local cases identified in 2012. Conclusions The high-resolution mapping approaches described here can help elimination programmes understand the epidemiology of a disappearing disease. Generating case-based risk maps at high spatial and temporal resolution will allow control programmes to direct interventions proactively according to evidence-based measures of risk and ensure that the impact of limited resources is maximized to achieve and maintain malaria elimination. PMID:23398628

Rapid case-based mapping of seasonal malaria transmission risk for strategic elimination planning in Swaziland.

PubMed

Cohen, Justin M; Dlamini, Sabelo; Novotny, Joseph M; Kandula, Deepika; Kunene, Simon; Tatem, Andrew J

2013-02-11

As successful malaria control programmes move towards elimination, they must identify residual transmission foci, target vector control to high-risk areas, focus on both asymptomatic and symptomatic infections, and manage importation risk. High spatial and temporal resolution maps of malaria risk can support all of these activities, but commonly available malaria maps are based on parasite rate, a poor metric for measuring malaria at extremely low prevalence. New approaches are required to provide case-based risk maps to countries seeking to identify remaining hotspots of transmission while managing the risk of transmission from imported cases. Household locations and travel histories of confirmed malaria patients during 2011 were recorded through routine surveillance by the Swaziland National Malaria Control Programme for the higher transmission months of January to April and the lower transmission months of May to December. Household locations for patients with no travel history to endemic areas were compared against a random set of background points sampled proportionate to population density with respect to a set of variables related to environment, population density, vector control, and distance to the locations of identified imported cases. Comparisons were made separately for the high and low transmission seasons. The Random Forests regression tree classification approach was used to generate maps predicting the probability of a locally acquired case at 100 m resolution across Swaziland for each season. Results indicated that case households during the high transmission season tended to be located in areas of lower elevation, closer to bodies of water, in more sparsely populated areas, with lower rainfall and warmer temperatures, and closer to imported cases than random background points (all p < 0.001). Similar differences were evident during the low transmission season. Maps from the fit models suggested better predictive ability during the high season. Both models proved useful at predicting the locations of local cases identified in 2012. The high-resolution mapping approaches described here can help elimination programmes understand the epidemiology of a disappearing disease. Generating case-based risk maps at high spatial and temporal resolution will allow control programmes to direct interventions proactively according to evidence-based measures of risk and ensure that the impact of limited resources is maximized to achieve and maintain malaria elimination.

Identification of fine scale and landscape scale drivers of urban aboveground carbon stocks using high-resolution modeling and mapping.

PubMed

Mitchell, Matthew G E; Johansen, Kasper; Maron, Martine; McAlpine, Clive A; Wu, Dan; Rhodes, Jonathan R

2018-05-01

Urban areas are sources of land use change and CO 2 emissions that contribute to global climate change. Despite this, assessments of urban vegetation carbon stocks often fail to identify important landscape-scale drivers of variation in urban carbon, especially the potential effects of landscape structure variables at different spatial scales. We combined field measurements with Light Detection And Ranging (LiDAR) data to build high-resolution models of woody plant aboveground carbon across the urban portion of Brisbane, Australia, and then identified landscape scale drivers of these carbon stocks. First, we used LiDAR data to quantify the extent and vertical structure of vegetation across the city at high resolution (5×5m). Next, we paired this data with aboveground carbon measurements at 219 sites to create boosted regression tree models and map aboveground carbon across the city. We then used these maps to determine how spatial variation in land cover/land use and landscape structure affects these carbon stocks. Foliage densities above 5m height, tree canopy height, and the presence of ground openings had the strongest relationships with aboveground carbon. Using these fine-scale relationships, we estimate that 2.2±0.4 TgC are stored aboveground in the urban portion of Brisbane, with mean densities of 32.6±5.8MgCha -1 calculated across the entire urban land area, and 110.9±19.7MgCha -1 calculated within treed areas. Predicted carbon densities within treed areas showed strong positive relationships with the proportion of surrounding tree cover and how clumped that tree cover was at both 1km 2 and 1ha resolutions. Our models predict that even dense urban areas with low tree cover can have high carbon densities at fine scales. We conclude that actions and policies aimed at increasing urban carbon should focus on those areas where urban tree cover is most fragmented. Copyright © 2017 Elsevier B.V. All rights reserved.

Remote Sensing of Ionosphere by IONOLAB Group

NASA Astrophysics Data System (ADS)

Arikan, Feza

2016-07-01

Ionosphere is a temporally and spatially varying, dispersive, anisotropic and inhomogeneous medium that is characterized primarily by its electron density distribution. Electron density is a complex function of spatial and temporal variations of solar, geomagnetic, and seismic activities. Ionosphere is the main source of error for navigation and positioning systems and satellite communication. Therefore, characterization and constant monitoring of variability of the ionosphere is of utmost importance for the performance improvement of these systems. Since ionospheric electron density is not a directly measurable quantity, an important derivable parameter is the Total Electron Content (TEC), which is used widely to characterize the ionosphere. TEC is proportional to the total number of electrons on a line crossing the atmosphere. IONOLAB is a research group is formed by Hacettepe University, Bilkent University and Kastamonu University, Turkey gathered to handle the challenges of the ionosphere using state-of-the-art remote sensing and signal processing techniques. IONOLAB group provides unique space weather services of IONOLAB-TEC, International Reference Ionosphere extended to Plasmasphere (IRI-Plas) model based IRI-Plas-MAP, IRI-Plas-STEC and Online IRI-Plas-2015 model at www.ionolab.org. IONOLAB group has been working for imaging and monitoring of ionospheric structure for the last 15 years. TEC is estimated from dual frequency GPS receivers as IONOLAB-TEC using IONOLAB-BIAS. For high spatio-temporal resolution 2-D imaging or mapping, IONOLAB-MAP algorithm is developed that uses automated Universal Kriging or Ordinary Kriging in which the experimental semivariogram is fitted to Matern Function with Particle Swarm Optimization (PSO). For 3-D imaging of ionosphere and 1-D vertical profiles of electron density, state-of-the-art IRI-Plas model based IONOLAB-CIT algorithm is developed for regional reconstruction that employs Kalman Filters for state/temporal transition. IONOLAB group contributes to remote sensing of upper atmosphere, ionosphere and plasmasphere with continuing TUBITAK projects. IONOLAB group is open to joint research and collaboration with researchers from all disciplines that investigate the challenges of ionosphere and space weather. This study is supported by TUBITAK 114E541, 115E915 and Joint TUBITAK 114E092 and AS CR 14/001 projects.

Co-occurrence Patterns of the Dengue Vector Aedes aegypti and Aedes mediovitattus, a Dengue Competent Mosquito in Puerto Rico

PubMed Central

Little, Eliza; Barrera, Roberto; Seto, Karen C.; Diuk-Wasser, Maria

2015-01-01

Aedes aegypti is implicated in dengue transmission in tropical and subtropical urban areas around the world. Ae. aegypti populations are controlled through integrative vector management. However, the efficacy of vector control may be undermined by the presence of alternative, competent species. In Puerto Rico, a native mosquito, Ae. mediovittatus, is a competent dengue vector in laboratory settings and spatially overlaps with Ae. aegypti. It has been proposed that Ae. mediovittatus may act as a dengue reservoir during inter-epidemic periods, perpetuating endemic dengue transmission in rural Puerto Rico. Dengue transmission dynamics may therefore be influenced by the spatial overlap of Ae. mediovittatus, Ae. aegypti, dengue viruses, and humans. We take a landscape epidemiology approach to examine the association between landscape composition and configuration and the distribution of each of these Aedes species and their co-occurrence. We used remotely sensed imagery from a newly launched satellite to map landscape features at very high spatial resolution. We found that the distribution of Ae. aegypti is positively predicted by urban density and by the number of tree patches, Ae. mediovittatus is positively predicted by the number of tree patches, but negatively predicted by large contiguous urban areas, and both species are predicted by urban density and the number of tree patches. This analysis provides evidence that landscape composition and configuration is a surrogate for mosquito community composition, and suggests that mapping landscape structure can be used to inform vector control efforts as well as to inform urban planning. PMID:21989642

An integrated pan-tropical biomass map using multiple reference datasets.

PubMed

Avitabile, Valerio; Herold, Martin; Heuvelink, Gerard B M; Lewis, Simon L; Phillips, Oliver L; Asner, Gregory P; Armston, John; Ashton, Peter S; Banin, Lindsay; Bayol, Nicolas; Berry, Nicholas J; Boeckx, Pascal; de Jong, Bernardus H J; DeVries, Ben; Girardin, Cecile A J; Kearsley, Elizabeth; Lindsell, Jeremy A; Lopez-Gonzalez, Gabriela; Lucas, Richard; Malhi, Yadvinder; Morel, Alexandra; Mitchard, Edward T A; Nagy, Laszlo; Qie, Lan; Quinones, Marcela J; Ryan, Casey M; Ferry, Slik J W; Sunderland, Terry; Laurin, Gaia Vaglio; Gatti, Roberto Cazzolla; Valentini, Riccardo; Verbeeck, Hans; Wijaya, Arief; Willcock, Simon

2016-04-01

We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N-23.4 S) of 375 Pg dry mass, 9-18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15-21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5 Mg dry mass ha(-1) vs. 21 and 28 Mg ha(-1) for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets. © 2015 John Wiley & Sons Ltd.

Map scale effects on estimating the number of undiscovered mineral deposits

USGS Publications Warehouse

Singer, D.A.; Menzie, W.D.

2008-01-01

Estimates of numbers of undiscovered mineral deposits, fundamental to assessing mineral resources, are affected by map scale. Where consistently defined deposits of a particular type are estimated, spatial and frequency distributions of deposits are linked in that some frequency distributions can be generated by processes randomly in space whereas others are generated by processes suggesting clustering in space. Possible spatial distributions of mineral deposits and their related frequency distributions are affected by map scale and associated inclusions of non-permissive or covered geological settings. More generalized map scales are more likely to cause inclusion of geologic settings that are not really permissive for the deposit type, or that include unreported cover over permissive areas, resulting in the appearance of deposit clustering. Thus, overly generalized map scales can cause deposits to appear clustered. We propose a model that captures the effects of map scale and the related inclusion of non-permissive geologic settings on numbers of deposits estimates, the zero-inflated Poisson distribution. Effects of map scale as represented by the zero-inflated Poisson distribution suggest that the appearance of deposit clustering should diminish as mapping becomes more detailed because the number of inflated zeros would decrease with more detailed maps. Based on observed worldwide relationships between map scale and areas permissive for deposit types, mapping at a scale with twice the detail should cut permissive area size of a porphyry copper tract to 29% and a volcanic-hosted massive sulfide tract to 50% of their original sizes. Thus some direct benefits of mapping an area at a more detailed scale are indicated by significant reductions in areas permissive for deposit types, increased deposit density and, as a consequence, reduced uncertainty in the estimate of number of undiscovered deposits. Exploration enterprises benefit from reduced areas requiring detailed and expensive exploration, and land-use planners benefit from reduced areas of concern. ?? 2008 International Association for Mathematical Geology.

Making Space for Place: Mapping Tools and Practices to Teach for Spatial Justice

ERIC Educational Resources Information Center

Rubel, Laurie H.; Hall-Wieckert, Maren; Lim, Vivian Y.

2017-01-01

This article presents a set of spatial tools for classroom learning about spatial justice. As part of a larger team, we designed a curriculum that engaged 10 learners with 3 spatial tools: (a) an oversized floor map, (b) interactive geographic information systems (GIS) maps, and (c) participatory mapping. We analyze how these tools supported…

Patterns in woody vegetation structure across African savannas

NASA Astrophysics Data System (ADS)

Axelsson, Christoffer R.; Hanan, Niall P.

2017-07-01

Vegetation structure in water-limited systems is to a large degree controlled by ecohydrological processes, including mean annual precipitation (MAP) modulated by the characteristics of precipitation and geomorphology that collectively determine how rainfall is distributed vertically into soils or horizontally in the landscape. We anticipate that woody canopy cover, crown density, crown size, and the level of spatial aggregation among woody plants in the landscape will vary across environmental gradients. A high level of woody plant aggregation is most distinct in periodic vegetation patterns (PVPs), which emerge as a result of ecohydrological processes such as runoff generation and increased infiltration close to plants. Similar, albeit weaker, forces may influence the spatial distribution of woody plants elsewhere in savannas. Exploring these trends can extend our knowledge of how semi-arid vegetation structure is constrained by rainfall regime, soil type, topography, and disturbance processes such as fire. Using high-spatial-resolution imagery, a flexible classification framework, and a crown delineation method, we extracted woody vegetation properties from 876 sites spread over African savannas. At each site, we estimated woody cover, mean crown size, crown density, and the degree of aggregation among woody plants. This enabled us to elucidate the effects of rainfall regimes (MAP and seasonality), soil texture, slope, and fire frequency on woody vegetation properties. We found that previously documented increases in woody cover with rainfall is more consistently a result of increasing crown size than increasing density of woody plants. Along a gradient of mean annual precipitation from the driest (< 200 mm yr-1) to the wettest (1200-1400 mm yr-1) end, mean estimates of crown size, crown density, and woody cover increased by 233, 73, and 491 % respectively. We also found a unimodal relationship between mean crown size and sand content suggesting that maximal savanna tree sizes do not occur in either coarse sands or heavy clays. When examining the occurrence of PVPs, we found that the same factors that contribute to the formation of PVPs also correlate with higher levels of woody plant aggregation elsewhere in savannas and that rainfall seasonality plays a key role for the underlying processes.

Statistical density modification using local pattern matching

DOEpatents

Terwilliger, Thomas C.

2007-01-23

A computer implemented method modifies an experimental electron density map. A set of selected known experimental and model electron density maps is provided and standard templates of electron density are created from the selected experimental and model electron density maps by clustering and averaging values of electron density in a spherical region about each point in a grid that defines each selected known experimental and model electron density maps. Histograms are also created from the selected experimental and model electron density maps that relate the value of electron density at the center of each of the spherical regions to a correlation coefficient of a density surrounding each corresponding grid point in each one of the standard templates. The standard templates and the histograms are applied to grid points on the experimental electron density map to form new estimates of electron density at each grid point in the experimental electron density map.

A global map of mangrove forest soil carbon at 30 m spatial resolution

NASA Astrophysics Data System (ADS)

Sanderman, Jonathan; Hengl, Tomislav; Fiske, Greg; Solvik, Kylen; Adame, Maria Fernanda; Benson, Lisa; Bukoski, Jacob J.; Carnell, Paul; Cifuentes-Jara, Miguel; Donato, Daniel; Duncan, Clare; Eid, Ebrahem M.; Ermgassen, Philine zu; Ewers Lewis, Carolyn J.; Macreadie, Peter I.; Glass, Leah; Gress, Selena; Jardine, Sunny L.; Jones, Trevor G.; Ndemem Nsombo, Eugéne; Mizanur Rahman, Md; Sanders, Christian J.; Spalding, Mark; Landis, Emily

2018-05-01

With the growing recognition that effective action on climate change will require a combination of emissions reductions and carbon sequestration, protecting, enhancing and restoring natural carbon sinks have become political priorities. Mangrove forests are considered some of the most carbon-dense ecosystems in the world with most of the carbon stored in the soil. In order for mangrove forests to be included in climate mitigation efforts, knowledge of the spatial distribution of mangrove soil carbon stocks are critical. Current global estimates do not capture enough of the finer scale variability that would be required to inform local decisions on siting protection and restoration projects. To close this knowledge gap, we have compiled a large georeferenced database of mangrove soil carbon measurements and developed a novel machine-learning based statistical model of the distribution of carbon density using spatially comprehensive data at a 30 m resolution. This model, which included a prior estimate of soil carbon from the global SoilGrids 250 m model, was able to capture 63% of the vertical and horizontal variability in soil organic carbon density (RMSE of 10.9 kg m‑3). Of the local variables, total suspended sediment load and Landsat imagery were the most important variable explaining soil carbon density. Projecting this model across the global mangrove forest distribution for the year 2000 yielded an estimate of 6.4 Pg C for the top meter of soil with an 86–729 Mg C ha‑1 range across all pixels. By utilizing remotely-sensed mangrove forest cover change data, loss of soil carbon due to mangrove habitat loss between 2000 and 2015 was 30–122 Tg C with >75% of this loss attributable to Indonesia, Malaysia and Myanmar. The resulting map products from this work are intended to serve nations seeking to include mangrove habitats in payment-for- ecosystem services projects and in designing effective mangrove conservation strategies.

Mapping UV properties throughout the Cosmic Horseshoe: lessons from VLT-MUSE

NASA Astrophysics Data System (ADS)

James, Bethan L.; Auger, Matt; Pettini, Max; Stark, Daniel P.; Belokurov, V.; Carniani, Stefano

2018-05-01

We present the first spatially resolved rest-frame ultraviolet (UV) study of the gravitationally lensed galaxy, the `Cosmic Horseshoe' (J1148+1930) at z = 2.38. Our gravitational lens model shows that the system is made up of four star-forming regions, each ˜4-8 kpc2 in size, from which we extract four spatially exclusive regional spectra. We study the interstellar and wind absorption lines, along with C III] doublet emission lines, in each region to investigate any variation in emission/absorption line properties. The mapped C III] emission shows distinct kinematical structure, with velocity offsets of ˜±50 km s-1 between regions suggestive of a merging system, and a variation in equivalent width that indicates a change in ionization parameter and/or metallicity between the regions. Absorption line velocities reveal a range of outflow strengths, with gas outflowing in the range -200 ≲ v (km s-1) ≲ -50 relative to the systemic velocity of that region. Interestingly, the strongest gas outflow appears to emanate from the most diffuse star-forming region. The star formation rates remain relatively constant (˜8-16 M⊙ yr-1), mostly due to large uncertainties in reddening estimates. As such, the outflows appear to be `global' rather than `locally' sourced. We measure electron densities with a range of log (Ne) = 3.92-4.36 cm-3, and point out that such high densities may be common when measured using the C III] doublet due to its large critical density. Overall, our observations demonstrate that while it is possible to trace variations in large-scale gas kinematics, detecting inhomogeneities in physical gas properties and their effects on the outflowing gas may be more difficult. This study provides important lessons for the spatially resolved rest-frame UV studies expected with future observatories, such as James Webb Space Telescope.

Spatial structure and distribution of small pelagic fish in the northwestern Mediterranean Sea.

PubMed

Saraux, Claire; Fromentin, Jean-Marc; Bigot, Jean-Louis; Bourdeix, Jean-Hervé; Morfin, Marie; Roos, David; Van Beveren, Elisabeth; Bez, Nicolas

2014-01-01

Understanding the ecological and anthropogenic drivers of population dynamics requires detailed studies on habitat selection and spatial distribution. Although small pelagic fish aggregate in large shoals and usually exhibit important spatial structure, their dynamics in time and space remain unpredictable and challenging. In the Gulf of Lions (north-western Mediterranean), sardine and anchovy biomasses have declined over the past 5 years causing an important fishery crisis while sprat abundance rose. Applying geostatistical tools on scientific acoustic surveys conducted in the Gulf of Lions, we investigated anchovy, sardine and sprat spatial distributions and structures over 10 years. Our results show that sardines and sprats were more coastal than anchovies. The spatial structure of the three species was fairly stable over time according to variogram outputs, while year-to-year variations in kriged maps highlighted substantial changes in their location. Support for the McCall's basin hypothesis (covariation of both population density and presence area with biomass) was found only in sprats, the most variable of the three species. An innovative method to investigate species collocation at different scales revealed that globally the three species strongly overlap. Although species often co-occurred in terms of presence/absence, their biomass density differed at local scale, suggesting potential interspecific avoidance or different sensitivity to local environmental characteristics. Persistent favourable areas were finally detected, but their environmental characteristics remain to be determined.

The many faces of population density.

PubMed

Mayor, Stephen J; Schaefer, James A

2005-09-01

Population density, one of the most fundamental demographic attributes, may vary systematically with spatial scale, but this scale-sensitivity is incompletely understood. We used a novel approach-based on fully censused and mapped distributions of eastern grey squirrel (Sciurus carolinensis) dreys, beaver (Castor canadensis) lodges, and moose (Alces alces)--to explore the scale-dependence of population density and its relationship to landscape features. We identified population units at several scales, both objectively, using cluster analysis, and arbitrarily, using artificial bounds centred on high-abundance sites. Densities declined with census area. For dreys, this relationship was stronger in objective versus arbitrary population units. Drey density was inconsistently related to patch area, a relationship that was positive for all patches but negative when non-occupied patches were excluded. Drey density was negatively related to the proportion of green-space and positively related to the density of buildings or roads, relationships that were accentuated at coarser scales. Mean drey densities were more sensitive to scale when calculated as organism-weighted versus area-weighted averages. Greater understanding of these scaling effects is required to facilitate comparisons of population density across studies.

Astronomy in Denver: Spatial distributions of dust properties via far-IR broadband map with HerPlaNS

NASA Astrophysics Data System (ADS)

Asano, Kentaro; Ueta, Toshiya; Ladjal, Djazia; Exter, Katrina; Otsuka, Masaaki; HerPlaNS Consortium

2018-06-01

We present the results of our analyses on dust properties in all of Galactic planetary nebulae based on 5-band broadband images in the far-IR taken with the Herschel Space Observatory.By fitting surface brightness distributions of dust thermal emission at 70, 160, 250, 350 and 500 microns with a single-temperature modified black body function, we derive spatially resolved maps of the dust emissivity power-law index (beta) and dust temperature (Td), as well as the column density.We find that circumstellar dust grains in PNe occupy a specific region in the beta-Td space, which is distinct from that occupied by dust grains in the Interstellar Matter (ISM) and star forming regions (SFRs). Unlike those in the ISM and SFRs, dust grains in PNe exhibit little variation in beta while a large spread in Td, suggesting rather homogeneous dust properties.This work is part of the Herschel Planetary Nebula Survey Plus (HerPlaNS+) supported by the NASA Astrophysics Data Analysis Program.

Spatiotemporal distribution of Holocene populations in North America

PubMed Central

Chaput, Michelle A.; Kriesche, Björn; Betts, Matthew; Martindale, Andrew; Kulik, Rafal; Schmidt, Volker; Gajewski, Konrad

2015-01-01

As the Cordilleran and Laurentide Ice Sheets retreated, North America was colonized by human populations; however, the spatial patterns of subsequent population growth are unclear. Temporal frequency distributions of aggregated radiocarbon (14C) dates are used as a proxy of population size and can be used to track this expansion. The Canadian Archaeological Radiocarbon Database contains more than 35,000 14C dates and is used in this study to map the spatiotemporal demographic changes of Holocene populations in North America at a continental scale for the past 13,000 y. We use the kernel method, which converts the spatial distribution of 14C dates into estimates of population density at 500-y intervals. The resulting maps reveal temporally distinct, dynamic patterns associated with paleodemographic trends that correspond well to genetic, archaeological, and ethnohistoric evidence of human occupation. These results have implications for hypothesizing and testing migration routes into and across North America as well as the relative influence of North American populations on the evolution of the North American ecosystem. PMID:26351683

Words and Maps: Developmental Changes in Mental Models of Spatial Information Acquired from Descriptions and Depictions

ERIC Educational Resources Information Center

Uttal, David H.; Fisher, Joan A.; Taylor, Holly A.

2006-01-01

People acquire spatial information from many sources, including maps, verbal descriptions, and navigating in the environment. The different sources present spatial information in different ways. For example, maps can show many spatial relations simultaneously, but in a description, each spatial relation must be presented sequentially. The present…

GIS-supported investigation of human EHEC and cattle VTEC O157 infections in Sweden: geographical distribution, spatial variation and possible risk factors.

PubMed Central

Kistemann, Thomas; Zimmer, Sonja; Vågsholm, Ivar; Andersson, Yvonne

2004-01-01

This article describes the spatial and temporal distribution of verotoxin-producing Escherichia coli among humans (EHEC) and cattle (VTEC) in Sweden, in order to evaluate relationships between the incidence of EHEC in humans, prevalence of VTEC O157 in livestock and agricultural structure by an ecological study. The spatial patterns of the distribution of human infections were described and compared with spatial patterns of occurrence in cattle, using a Geographic Information System (GIS). The findings implicate a concentration of human infection and cattle prevalence in the southwest of Sweden. The use of probability mapping confirmed unusual patterns of infection rates. The comparison of human and cattle infection indicated a spatial and statistical association. The correlation between variables of the agricultural structure and human EHEC incidence was high, indicating a significant statistical association of cattle and farm density with human infection. The explained variation of a multiple linear regression model was 0.56. PMID:15188718

Spatio-temporal modeling with GIS and remote sensing for schistosomiasis control in Sichuan, China

NASA Astrophysics Data System (ADS)

Xu, Bing

Schistosomiasis is a water-borne parasitic disease endemic in tropical and subtropical areas. Its transmission requires certain kind of snail as the intermediate host. Some efforts have been made to mapping snail habitats with remote sensing and schistosomiasis transmission modeling. However, the modeling is limited to isolated residential groups and does not include spatial interaction among those groups. Remotely sensed data are only used in snail habitat classification, not in estimation of snail abundance that is an important parameter in schistosomiasis transmission modeling. This research overcomes the above two problems using innovative geographic information system (GIS) and remote sensing technology. A mountainous environment near Xichang, China, is chosen as the test site. Environmental and epidemiological data are stored in a GIS to support modeling. Snail abundance is estimated from land-cover and land-use fractions derived from high spatial resolution IKONOS satellite data. Spatial interaction is determined in consideration of neighborhoods, group areas, relative slopes among groups, and natural barriers. Land-cover and land-use information extracted from 4 m high resolution IKONOS data is used as reference in scaling up to the regional level. The scale-up is done with coarser resolution satellite data including Landsat Thematic Mapper (TM), EO-1 Advanced Land Imager (ALI) and Hyperion data all at 30 m resolution. Snail abundance is estimated by regressing snail survey data with land-cover and land-use fractions. An R2 of 0.87 is obtained between the average snail density predicted and that surveyed at the group level. With such a model, a snail density map is generated for all residential groups in the study area. A spatio-temporal model of schistosomiasis transmission is finally built to incorporate the spatial interaction caused by miracidia and cercaria migration. Comparing the model results with and without spatial interaction has revealed a number of advantages of the spatio-temporal model. Particularly, with the inclusion of spatial interaction, more effective control of schistosomiasis transmission over the whole study area can be achieved.

Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array

PubMed Central

Wang, Shichen; Wong, Debbie; Forrest, Kerrie; Allen, Alexandra; Chao, Shiaoman; Huang, Bevan E; Maccaferri, Marco; Salvi, Silvio; Milner, Sara G; Cattivelli, Luigi; Mastrangelo, Anna M; Whan, Alex; Stephen, Stuart; Barker, Gary; Wieseke, Ralf; Plieske, Joerg; International Wheat Genome Sequencing Consortium; Lillemo, Morten; Mather, Diane; Appels, Rudi; Dolferus, Rudy; Brown-Guedira, Gina; Korol, Abraham; Akhunova, Alina R; Feuillet, Catherine; Salse, Jerome; Morgante, Michele; Pozniak, Curtis; Luo, Ming-Cheng; Dvorak, Jan; Morell, Matthew; Dubcovsky, Jorge; Ganal, Martin; Tuberosa, Roberto; Lawley, Cindy; Mikoulitch, Ivan; Cavanagh, Colin; Edwards, Keith J; Hayden, Matthew; Akhunov, Eduard

2014-01-01

High-density single nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships between individuals in populations and studying marker–trait associations in mapping experiments. We developed a genotyping array including about 90 000 gene-associated SNPs and used it to characterize genetic variation in allohexaploid and allotetraploid wheat populations. The array includes a significant fraction of common genome-wide distributed SNPs that are represented in populations of diverse geographical origin. We used density-based spatial clustering algorithms to enable high-throughput genotype calling in complex data sets obtained for polyploid wheat. We show that these model-free clustering algorithms provide accurate genotype calling in the presence of multiple clusters including clusters with low signal intensity resulting from significant sequence divergence at the target SNP site or gene deletions. Assays that detect low-intensity clusters can provide insight into the distribution of presence–absence variation (PAV) in wheat populations. A total of 46 977 SNPs from the wheat 90K array were genetically mapped using a combination of eight mapping populations. The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat. PMID:24646323

Experimental power spectral density analysis for mid- to high-spatial frequency surface error control.

PubMed

Hoyo, Javier Del; Choi, Heejoo; Burge, James H; Kim, Geon-Hee; Kim, Dae Wook

2017-06-20

The control of surface errors as a function of spatial frequency is critical during the fabrication of modern optical systems. A large-scale surface figure error is controlled by a guided removal process, such as computer-controlled optical surfacing. Smaller-scale surface errors are controlled by polishing process parameters. Surface errors of only a few millimeters may degrade the performance of an optical system, causing background noise from scattered light and reducing imaging contrast for large optical systems. Conventionally, the microsurface roughness is often given by the root mean square at a high spatial frequency range, with errors within a 0.5×0.5  mm local surface map with 500×500 pixels. This surface specification is not adequate to fully describe the characteristics for advanced optical systems. The process for controlling and minimizing mid- to high-spatial frequency surface errors with periods of up to ∼2-3  mm was investigated for many optical fabrication conditions using the measured surface power spectral density (PSD) of a finished Zerodur optical surface. Then, the surface PSD was systematically related to various fabrication process parameters, such as the grinding methods, polishing interface materials, and polishing compounds. The retraceable experimental polishing conditions and processes used to produce an optimal optical surface PSD are presented.

Assessing the spatial distribution of Tuta absoluta (Lepidoptera: Gelechiidae) eggs in open-field tomato cultivation through geostatistical analysis.

PubMed

Martins, Júlio C; Picanço, Marcelo C; Silva, Ricardo S; Gonring, Alfredo Hr; Galdino, Tarcísio Vs; Guedes, Raul Nc

2018-01-01

The spatial distribution of insects is due to the interaction between individuals and the environment. Knowledge about the within-field pattern of spatial distribution of a pest is critical to planning control tactics, developing efficient sampling plans, and predicting pest damage. The leaf miner Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) is the main pest of tomato crops in several regions of the world. Despite the importance of this pest, the pattern of spatial distribution of T. absoluta on open-field tomato cultivation remains unknown. Therefore, this study aimed to characterize the spatial distribution of T. absoluta in 22 commercial open-field tomato cultivations with plants at the three phenological development stages by using geostatistical analysis. Geostatistical analysis revealed that there was strong evidence for spatially dependent (aggregated) T. absoluta eggs in 19 of the 22 sample tomato cultivations. The maps that were obtained demonstrated the aggregated structure of egg densities at the edges of the crops. Further, T. absoluta was found to accomplish egg dispersal along the rows more frequently than it does between rows. Our results indicate that the greatest egg densities of T. absoluta occur at the edges of tomato crops. These results are discussed in relation to the behavior of T. absoluta distribution within fields and in terms of their implications for improved sampling guidelines and precision targeting control methods that are essential for effective pest monitoring and management. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

[Estimation of Hunan forest carbon density based on spectral mixture analysis of MODIS data].

PubMed

Yan, En-ping; Lin, Hui; Wang, Guang-xing; Chen, Zhen-xiong

2015-11-01

With the fast development of remote sensing technology, combining forest inventory sample plot data and remotely sensed images has become a widely used method to map forest carbon density. However, the existence of mixed pixels often impedes the improvement of forest carbon density mapping, especially when low spatial resolution images such as MODIS are used. In this study, MODIS images and national forest inventory sample plot data were used to conduct the study of estimation for forest carbon density. Linear spectral mixture analysis with and without constraint, and nonlinear spectral mixture analysis were compared to derive the fractions of different land use and land cover (LULC) types. Then sequential Gaussian co-simulation algorithm with and without the fraction images from spectral mixture analyses were employed to estimate forest carbon density of Hunan Province. Results showed that 1) Linear spectral mixture analysis with constraint, leading to a mean RMSE of 0.002, more accurately estimated the fractions of LULC types than linear spectral and nonlinear spectral mixture analyses; 2) Integrating spectral mixture analysis model and sequential Gaussian co-simulation algorithm increased the estimation accuracy of forest carbon density to 81.5% from 74.1%, and decreased the RMSE to 5.18 from 7.26; and 3) The mean value of forest carbon density for the province was 30.06 t · hm(-2), ranging from 0.00 to 67.35 t · hm(-2). This implied that the spectral mixture analysis provided a great potential to increase the estimation accuracy of forest carbon density on regional and global level.

Electron transfer in a virtual quantum state of LiBH4 induced by strong optical fields and mapped by femtosecond x-ray diffraction.

PubMed

Stingl, J; Zamponi, F; Freyer, B; Woerner, M; Elsaesser, T; Borgschulte, A

2012-10-05

Transient polarizations connected with a spatial redistribution of electronic charge in a mixed quantum state are induced by optical fields of high amplitude. We determine for the first time the related transient electron density maps, applying femtosecond x-ray powder diffraction as a structure probe. The prototype ionic material LiBH4 driven nonresonantly by an intense sub-40 fs optical pulse displays a large-amplitude fully reversible electron transfer from the BH4(-) anion to the Li+ cation during excitation. Our results establish this mechanism as the source of the strong optical polarization which agrees quantitatively with theoretical estimates.

The wildland-urban interface raster dataset of Catalonia.

PubMed

Alcasena, Fermín J; Evers, Cody R; Vega-Garcia, Cristina

2018-04-01

We provide the wildland urban interface (WUI) map of the autonomous community of Catalonia (Northeastern Spain). The map encompasses an area of some 3.21 million ha and is presented as a 150-m resolution raster dataset. Individual housing location, structure density and vegetation cover data were used to spatially assess in detail the interface, intermix and dispersed rural WUI communities with a geographical information system. Most WUI areas concentrate in the coastal belt where suburban sprawl has occurred nearby or within unmanaged forests. This geospatial information data provides an approximation of residential housing potential for loss given a wildfire, and represents a valuable contribution to assist landscape and urban planning in the region.

On the soil moisture estimate at basin scale in Mediterranean basins with the ASAR sensor: the Mulargia basin case study

NASA Astrophysics Data System (ADS)

Fois, Laura; Montaldo, Nicola

2017-04-01

Soil moisture plays a key role in water and energy exchanges between soil, vegetation and atmosphere. For water resources planning and managementthesoil moistureneeds to be accurately and spatially monitored, specially where the risk of desertification is high, such as Mediterranean basins. In this sense active remote sensors are very attractive for soil moisture monitoring. But Mediterranean basinsaretypicallycharacterized by strong topography and high spatial variability of physiographic properties, and only high spatial resolution sensorsare potentially able to monitor the strong soil moisture spatial variability.In this regard the Envisat ASAR (Advanced Synthetic Aperture Radar) sensor offers the attractive opportunity ofsoil moisture mapping at fine spatial and temporal resolutions(up to 30 m, every 30 days). We test the ASAR sensor for soil moisture estimate in an interesting Sardinian case study, the Mulargia basin withan area of about 70 sq.km. The position of the Sardinia island in the center of the western Mediterranean Sea basin, its low urbanization and human activity make Sardinia a perfect reference laboratory for Mediterranean hydrologic studies. The Mulargia basin is a typical Mediterranean basinin water-limited conditions, and is an experimental basin from 2003. For soil moisture mapping23 satellite ASAR imagery at single and dual polarization were acquired for the 2003-2004period.Satellite observationsmay bevalidated through spatially distributed soil moisture ground-truth data, collected over the whole basin using the TDR technique and the gravimetric method, in days with available radar images. The results show that ASAR sensor observations can be successfully used for soil moisture mapping at different seasons, both wet and dry, but an accurate calibration with field data is necessary. We detect a strong relationship between the soil moisture spatial variability and the physiographic properties of the basin, such as soil water storage capacity, deep and texture of soils, type and density of vegetation, and topographic parameters. Finally we demonstrate that the high resolution ASAR imagery are an attractive tool for estimating surface soil moisture at basin scale, offering a unique opportunity for monitoring the soil moisture spatial variability in typical Mediterranean basins.

MAPPING SPATIAL ACCURACY AND ESTIMATING LANDSCAPE INDICATORS FROM THEMATIC LAND COVER MAPS USING FUZZY SET THEORY

EPA Science Inventory

The accuracy of thematic map products is not spatially homogenous, but instead variable across most landscapes. Properly analyzing and representing the spatial distribution (pattern) of thematic map accuracy would provide valuable user information for assessing appropriate applic...

Seismo-ionospheric anomalies in ionospheric TEC and plasma density before the 17 July 2006 M7.7 south of Java earthquake

NASA Astrophysics Data System (ADS)

Tao, Dan; Cao, Jinbin; Battiston, Roberto; Li, Liuyuan; Ma, Yuduan; Liu, Wenlong; Zhima, Zeren; Wang, Lanwei; Wray Dunlop, Malcolm

2017-04-01

In this paper, we report significant evidence for preseismic ionospheric anomalies in total electron content (TEC) of the global ionosphere map (GIM) and plasma density appearing on day 2 before the 17 July 2006 M7.7 south of Java earthquake. After distinguishing other anomalies related to the geomagnetic activities, we found a temporal precursor around the epicenter on day 2 before the earthquake (15 July 2006), which agrees well with the spatial variations in latitude-longitude-time (LLT) maps. Meanwhile, the sequences of latitude-time-TEC (LTT) plots reveal that the TECs on epicenter side anomalously decrease and lead to an anomalous asymmetric structure with respect to the magnetic equator in the daytime from day 2 before the earthquake. This anomalous asymmetric structure disappears after the earthquake. To further confirm these anomalies, we studied the plasma data from DEMETER satellite in the earthquake preparation zone (2046.4 km in radius) during the period from day 45 before to day 10 after the earthquake, and also found that the densities of both electron and total ion in the daytime significantly increase on day 2 before the earthquake. Very interestingly, O+ density increases significantly and H+ density decreases, while He+ remains relatively stable. These results indicate that there exists a distinct preseismic signal (preseismic ionospheric anomaly) over the epicenter.

Resource Needs and Pedagogical Value of Web Mapping for Spatial Thinking

ERIC Educational Resources Information Center

Manson, Steven; Shannon, Jerry; Eria, Sami; Kne, Len; Dyke, Kevin; Nelson, Sara; Batra, Lalit; Bonsal, Dudley; Kernik, Melinda; Immich, Jennifer; Matson, Laura

2014-01-01

Web mapping involves publishing and using maps via the Internet, and can range from presenting static maps to offering dynamic data querying and spatial analysis. Web mapping is seen as a promising way to support development of spatial thinking in the classroom but there are unanswered questions about how this promise plays out in reality. This…

Detecting Large-Scale Brain Networks Using EEG: Impact of Electrode Density, Head Modeling and Source Localization

PubMed Central

Liu, Quanying; Ganzetti, Marco; Wenderoth, Nicole; Mantini, Dante

2018-01-01

Resting state networks (RSNs) in the human brain were recently detected using high-density electroencephalography (hdEEG). This was done by using an advanced analysis workflow to estimate neural signals in the cortex and to assess functional connectivity (FC) between distant cortical regions. FC analyses were conducted either using temporal (tICA) or spatial independent component analysis (sICA). Notably, EEG-RSNs obtained with sICA were very similar to RSNs retrieved with sICA from functional magnetic resonance imaging data. It still remains to be clarified, however, what technological aspects of hdEEG acquisition and analysis primarily influence this correspondence. Here we examined to what extent the detection of EEG-RSN maps by sICA depends on the electrode density, the accuracy of the head model, and the source localization algorithm employed. Our analyses revealed that the collection of EEG data using a high-density montage is crucial for RSN detection by sICA, but also the use of appropriate methods for head modeling and source localization have a substantial effect on RSN reconstruction. Overall, our results confirm the potential of hdEEG for mapping the functional architecture of the human brain, and highlight at the same time the interplay between acquisition technology and innovative solutions in data analysis. PMID:29551969

Picturing Data With Uncertainty

NASA Technical Reports Server (NTRS)

Kao, David; Love, Alison; Dungan, Jennifer L.; Pang, Alex

2004-01-01

NASA is in the business of creating maps for scientific purposes to represent important biophysical or geophysical quantities over space and time. For example, maps of surface temperature over the globe tell scientists where and when the Earth is heating up; regional maps of the greenness of vegetation tell scientists where and when plants are photosynthesizing. There is always uncertainty associated with each value in any such map due to various factors. When uncertainty is fully modeled, instead of a single value at each map location, there is a distribution expressing a set of possible outcomes at each location. We consider such distribution data as multi-valued data since it consists of a collection of values about a single variable. Thus, a multi-valued data represents both the map and its uncertainty. We have been working on ways to visualize spatial multi-valued data sets effectively for fields with regularly spaced units or grid cells such as those in NASA's Earth science applications. A new way to display distributions at multiple grid locations is to project the distributions from an individual row, column or other user-selectable straight transect from the 2D domain. First at each grid cell in a given slice (row, column or transect), we compute a smooth density estimate from the underlying data. Such a density estimate for the probability density function (PDF) is generally more useful than a histogram, which is a classic density estimate. Then, the collection of PDFs along a given slice are presented vertically above the slice and form a wall. To minimize occlusion of intersecting slices, the corresponding walls are positioned at the far edges of the boundary. The PDF wall depicts the shapes of the distributions very dearly since peaks represent the modes (or bumps) in the PDFs. We've defined roughness as the number of peaks in the distribution. Roughness is another useful summary information for multimodal distributions. The uncertainty of the multi-valued data can also be interpreted by the number of peaks and the widths of the peaks as shown by the PDF walls.

Damage Assessment for Disaster Relief Efforts in Urban Areas Using Optical Imagery and LiDAR Data

NASA Astrophysics Data System (ADS)

Bahr, Thomas

2014-05-01

Imagery combined with LiDAR data and LiDAR-derived products provides a significant source of geospatial data which is of use in disaster mitigation planning. Feature rich building inventories can be constructed from tools with 3D rooftop extraction capabilities, and two dimensional outputs such as DSMs and DTMs can be used to generate layers to support routing efforts in Spatial Analyst and Network Analyst workflows. This allows us to leverage imagery and LiDAR tools for disaster mitigation or other scenarios. Software such as ENVI, ENVI LiDAR, and ArcGIS® Spatial and Network Analyst can therefore be used in conjunction to help emergency responders route ground teams in support of disaster relief efforts. This is exemplified by a case study against the background of the magnitude 7.0 earthquake that struck Haiti's capital city of Port-au-Prince on January 12, 2010. Soon after, both LiDAR data and an 8-band WorldView-2 scene were collected to map the disaster zone. The WorldView-2 scene was orthorectified and atmospherically corrected in ENVI prior to use. ENVI LiDAR was used to extract the DSM, DTM, buildings, and debris from the LiDAR data point cloud. These datasets provide a foundation for the 2D portion of the analysis. As the data was acquired over an area of dense urbanization, the majority of ground surfaces are roads, and standing buildings and debris are actually largely separable on the basis of elevation classes. To extract the road network of Port-au-Prince, the LiDAR-based feature height information was fused with the WorldView-2 scene, using ENVI's object-based feature extraction approach. This road network was converted to a network dataset for further analysis by the ArcGIS Network Analyst. For the specific case of Haiti, the distribution of blue tarps, used as accommodations for refugees, provided a spectrally distinct target. Pure blue tarp pixel spectra were selected from the WorldView-2 scene and input as a reference into ENVI's Spectral Angle Mapper (SAM) classification routine, together with a water-shadow mask to prevent false positives. The resulting blue tarp shape file was input into the ArcGIS Point Density tool, a feature of the Spatial Analyst toolbox. The final distribution map shows the density of blue tarps in Port-au-Prince and can be used to roughly delineate camps of refugees. Analogous, a debris density map was generated after separating the debris elevation class. The combination of this debris density map with the road network allowed to construct an intact road network of Port-au-Prince within the ArcGIS Network Analyst. Moderate density debris was used as a cost-increase barrier feature of the network dataset, and high density debris was used as a total obstruction barrier feature. Based on this information, two hypothetical routing scenarios were analyzed. One involved routing a ground team between two different refugee concentration zones. For the other, potential helicopter landing zones were computed from the LiDAR-derived products and added as facility features to the Network Analyst. Routes from the helicopter landing zones to refugee concentration access points were solved using closest facility logic, again making use of the obstructed network.

Compartmentalized Low-Rank Recovery for High-Resolution Lipid Unsuppressed MRSI

PubMed Central

Bhattacharya, Ipshita; Jacob, Mathews

2017-01-01

Purpose To introduce a novel algorithm for the recovery of high-resolution magnetic resonance spectroscopic imaging (MRSI) data with minimal lipid leakage artifacts, from dual-density spiral acquisition. Methods The reconstruction of MRSI data from dual-density spiral data is formulated as a compartmental low-rank recovery problem. The MRSI dataset is modeled as the sum of metabolite and lipid signals, each of which is support limited to the brain and extracranial regions, respectively, in addition to being orthogonal to each other. The reconstruction problem is formulated as an optimization problem, which is solved using iterative reweighted nuclear norm minimization. Results The comparisons of the scheme against dual-resolution reconstruction algorithm on numerical phantom and in vivo datasets demonstrate the ability of the scheme to provide higher spatial resolution and lower lipid leakage artifacts. The experiments demonstrate the ability of the scheme to recover the metabolite maps, from lipid unsuppressed datasets with echo time (TE)=55 ms. Conclusion The proposed reconstruction method and data acquisition strategy provide an efficient way to achieve high-resolution metabolite maps without lipid suppression. This algorithm would be beneficial for fast metabolic mapping and extension to multislice acquisitions. PMID:27851875

The SAMI Galaxy Survey: Publicly Available Spatially Resolved Emission Line Data Products

NASA Astrophysics Data System (ADS)

Medling, Anne; Green, Andrew W.; Ho, I.-Ting; Groves, Brent; Croom, Scott; SAMI Galaxy Survey Team

2017-01-01

The SAMI Galaxy Survey is collecting optical integral field spectroscopy of up to 3400 nearby (z<0.1) galaxies with a range of stellar masses and in a range of environments. The first public data release contains nearly 800 galaxies from the Galaxy And Mass Assembly (GAMA) Survey. In addition to releasing the reduced data cubes, we also provide emission line fits (flux and kinematic maps of strong emission lines including Halpha and Hbeta, [OII]3726,29, [OIII]4959,5007, [OI]6300, [NII]6548,83, and [SII]6716,31), extinction maps, star formation classification masks, and star formation rate maps. We give an overview of the data available for your favorite emission line science and present a few early science results. For example, a sample of edge-on disk galaxies show enhanced extraplanar emission related to SF-driven outflows, which are correlated with a bursty star formation history and higher star formation rate surface densities. Interestingly, the star formation rate surface densities of these wind hosts are 5-100 times lower than the canonical threshold for driving winds (0.1 MSun/yr/kpc2), indicating that galactic winds may be more important in normal star-forming galaxies than previously thought.

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

Jager, Yetta; Efroymson, Rebecca Ann; Sublette, K.

Quantitative tools are needed to evaluate the ecological effects of increasing petroleum production. In this article, we describe two stochastic models for simulating the spatial distribution of brine spills on a landscape. One model uses general assumptions about the spatial arrangement of spills and their sizes; the second model distributes spills by siting rectangular well complexes and conditioning spill probabilities on the configuration of pipes. We present maps of landscapes with spills produced by the two methods and compare the ability of the models to reproduce a specified spill area. A strength of the models presented here is their abilitymore » to extrapolate from the existing landscape to simulate landscapes with a higher (or lower) density of oil wells.« less

Digital processing techniques and film density calibration for printing image data

USGS Publications Warehouse

Chavez, Pat S.; McSweeney, Joseph A.; Binnie, Douglas R.

1987-01-01

Satellite image data that cover a wide range of environments are being used to make prints that represent a map type product. If a wide distribution of these products is desired, they are printed using lithographic rather than photographic procedures to reduce the cost per print. Problems are encountered in the photo lab if the film products to be used for lithographic printing have the same density range and density curve characteristics as the film used for photographic printing. A method is presented that keeps the film densities within the 1.1 range required for lithographic printing, but generates film products with contrast similar to that in photographic film for the majority of data (80 percent). Also, spatial filters can be used to enhance local detail in dark and bright regions, as well as to sharpen the final image product using edge enhancement techniques.

The growth and breakdown of a vortex-pair in a stably stratified fluid

NASA Astrophysics Data System (ADS)

Advaith, S.; Tinaikar, Aashay; Manu, K. V.; Basu, Saptarshi

2017-11-01

Vortex interaction with density stratification is ubiquitous in nature and applied to various engineering applications. Present study have characterized the spatial and temporal dynamics of the interaction between a vortex and a density stratified interface. The present work is prompted by our research on single tank Thermal Energy Storage (TES) system used in concentrated solar power (CSP) plants where hot and cold fluids are separated by means of density stratification. Rigorous qualitative (High speed Shadowgraph) and quantitative (high speed PIV) studies enable us to have great understanding about vortex formation, propagation, interaction dynamics with density stratified interface, resulted plume characteristics and so on. We have categorized this interaction phenomena in to three different cases based on its nature as non-penetrative, partial penetrative and extensively penetrative. Along with that we have proposed a regime map consisting non-dimensional parameters like Reynolds, Richardson and Atwood numbers which predicts the occurrence above mentioned cases.

Understanding the Influence of Turbulence in Imaging Fourier-Transform Spectrometry of Smokestack Plumes

DTIC Science & Technology

2011-03-01

capability of FTS to estimate plume effluent concentrations by comparing intrusive measurements of aircraft engine exhaust with those from an FTS. A... turbojet engine. Temporal averaging was used to reduce SCAs in the spectra, and spatial maps of temperature and concentration were generated. The time...density function ( PDF ) is the de- fined as the derivative of the CDF, and describes the probability of obtaining a given value of X. For a normally

Spatial pattern of groundwater arsenic occurrence and association with bedrock geology in greater augusta, maine

USGS Publications Warehouse

Yang, Q.; Jung, H.B.; Culbertson, C.W.; Marvinney, R.G.; Loiselle, M.C.; Locke, D.B.; Cheek, H.; Thibodeau, H.; Zheng, Yen

2009-01-01

In New England, groundwater arsenic occurrence has been linked to bedrock geology on regional scales. To ascertain and quantify this linkage at intermediate (100-101 km) scales, 790 groundwater samples from fractured bedrock aquifers in the greater Augusta, Maine area are analyzed, and 31% of the sampled wells have arsenic concentrations >10 ??g/L. The probability of [As] exceeding 10 ??g/L mapped by indicator kriging is highest in Silurian pelite-sandstone and pelite-limestone units (???40%). This probability differs significantly (p < 0.001) from those in the Silurian - Ordovician sandstone (24%), the Devonian granite (15%), and the Ordovician - Cambrian volcanic rocks (9%). The spatial pattern of groundwater arsenic distribution resembles the bedrock map. Thus, bedrock geology is associated with arsenic occurrence in fractured bedrock aquifers of the study area at intermediate scales relevant to water resources planning. The arsenic exceedance rate for each rock unit is considered robust because low, medium, and high arsenic occurrences in four cluster areas (3-20 km2) with a low sampling density of 1-6 wells per km2 are comparable to those with a greater density of 5-42 wells per km2. About 12,000 people (21% of the population) in the greater Augusta area (???1135 km2) are at risk of exposure to >10 ??g/L arsenic in groundwater. ?? 2009 American Chemical Society.

Assessing and modelling ecohydrologic processes at the agricultural field scale

NASA Astrophysics Data System (ADS)

Basso, Bruno

2015-04-01

One of the primary goals of agricultural management is to increase the amount of crop produced per unit of fertilizer and water used. World record corn yields demonstrated that water use efficiency can increase fourfold with improved agronomic management and cultivars able to tolerate high densities. Planting crops with higher plant density can lead to significant yield increases, and increase plant transpiration vs. soil water evaporation. Precision agriculture technologies have been adopted for the last twenty years but seldom have the data collected been converted to information that led farmers to different agronomic management. These methods are intuitively appealing, but yield maps and other spatial layers of data need to be properly analyzed and interpreted to truly become valuable. Current agro-mechanic and geospatial technologies allow us to implement a spatially variable plan for agronomic inputs including seeding rate, cultivars, pesticides, herbicides, fertilizers, and water. Crop models are valuable tools to evaluate the impact of management strategies (e.g., cover crops, tile drains, and genetically-improved cultivars) on yield, soil carbon sequestration, leaching and greenhouse gas emissions. They can help farmers identify adaptation strategies to current and future climate conditions. In this paper I illustrate the key role that precision agriculture technologies (yield mapping technologies, within season soil and crop sensing), crop modeling and weather can play in dealing with the impact of climate variability on soil ecohydrologic processes. Case studies are presented to illustrate this concept.

Spatial Pattern of Groundwater Arsenic Occurrence and Association with Bedrock Geology in Greater Augusta, Maine, USA

PubMed Central

Yang, Qiang; Jung, Hun Bok; Culbertson, Charles W.; Marvinney, Robert G.; Loiselle, Marc C.; Locke, Daniel B.; Cheek, Heidi; Thibodeau, Hilary; Zheng, Yan

2009-01-01

In New England, groundwater arsenic occurrence has been linked to bedrock geology on regional scales. To ascertain and quantify this linkage at intermediate (100-101 km) scales, 790 groundwater samples from fractured bedrock aquifers in the greater Augusta, Maine area are analyzed. 31% of the sampled wells have arsenic >10 μg/L. The probability of [As] exceeding 10 μg/L mapped by indicator kriging is highest in Silurian pelite-sandstone and pelite-limestone units (~40%). This probability differs significantly (p<0.001) from those in the Silurian-Ordovician sandstone (24%), the Devonian granite (15%) and the Ordovician-Cambrian volcanic rocks (9%). The spatial pattern of groundwater arsenic distribution resembles the bedrock map. Thus, bedrock geology is associated with arsenic occurrence in fractured bedrock aquifers of the study area at intermediate scales relevant to water resources planning. The arsenic exceedance rate for each rock unit is considered robust because low, medium and high arsenic occurrences in 4 cluster areas (3-20 km2) with a low sampling density of 1-6 wells per km2 are comparable to those with a greater density of 5-42 wells per km2. About 12,000 people (21% of the population) in the greater Augusta area (~1135 km2) are at risk of exposure to >10 μg/L arsenic in groundwater. PMID:19475939

Spatial pattern of groundwater arsenic occurrence and association with bedrock geology in greater Augusta, Maine.

PubMed

Yang, Qiang; Jung, Hun Bok; Culbertson, Charles W; Marvinney, Robert G; Loiselle, Marc C; Locke, Daniel B; Cheek, Heidi; Thibodeau, Hilary; Zheng, Yan

2009-04-15

In New England, groundwater arsenic occurrence has been linked to bedrock geology on regional scales. To ascertain and quantify this linkage at intermediate (10(0)-10(1) km) scales, 790 groundwater samples from fractured bedrock aquifers in the greater Augusta, Maine area are analyzed, and 31% of the sampled wells have arsenic concentrations >10 microg/L. The probability of [As] exceeding 10 microg/L mapped by indicator kriging is highest in Silurian pelite-sandstone and pelite-limestone units (approximately 40%). This probability differs significantly (p < 0.001) from those in the Silurian-Ordovician sandstone (24%),the Devonian granite (15%), and the Ordovician-Cambrian volcanic rocks (9%). The spatial pattern of groundwater arsenic distribution resembles the bedrock map. Thus, bedrock geology is associated with arsenic occurrence in fractured bedrock aquifers of the study area at intermediate scales relevant to water resources planning. The arsenic exceedance rate for each rock unit is considered robust because low, medium, and high arsenic occurrences in four cluster areas (3-20 km2) with a low sampling density of 1-6 wells per km2 are comparable to those with a greater density of 5-42 wells per km2. About 12,000 people (21% of the population) in the greater Augusta area (approximately 1135 km2) are at risk of exposure to >10 microg/L arsenic in groundwater.

Community mapping of sex work criminalization and violence: impacts on HIV treatment interruptions among marginalized women living with HIV in Vancouver, Canada.

PubMed

Goldenberg, Shira M; Deering, Kathleen; Amram, Ofer; Guillemi, Silvia; Nguyen, Paul; Montaner, Julio; Shannon, Kate

2017-09-01

Despite the high HIV burden faced by sex workers, data on access and retention in antiretroviral therapy (ART) are limited. Using an innovative spatial epidemiological approach, we explored how the social geography of sex work criminalization and violence impacts HIV treatment interruptions among sex workers living with HIV in Vancouver over a 3.5-year period. Drawing upon data from a community-based cohort (AESHA, 2010-2013) and linked external administrative data on ART dispensation, GIS mapping and multivariable logistic regression with generalized estimating equations to prospectively examine the effects of spatial criminalization and violence near women's places of residence on 2-day ART interruptions. Analyses were restricted to 66 ART-exposed women who contributed 208 observations and 83 ART interruption events. In adjusted multivariable models, heightened density of displacement due to policing independently correlated with HIV treatment interruptions (AOR: 1.02, 95%CI: 1.00-1.04); density of legal restrictions (AOR: 1.30, 95%CI: 0.97-1.76) and a combined measure of criminalization/violence (AOR: 1.00, 95%CI: 1.00-1.01) were marginally correlated. The social geography of sex work criminalization may undermine access to essential medicines, including HIV treatment. Interventions to promote 'enabling environments' (e.g. peer-led models, safer living/working spaces) should be explored, alongside policy reforms to ensure uninterrupted treatment access.

Automatically Generated Vegetation Density Maps with LiDAR Survey for Orienteering Purpose

NASA Astrophysics Data System (ADS)

Petrovič, Dušan

2018-05-01

The focus of our research was to automatically generate the most adequate vegetation density maps for orienteering purpose. Application Karttapullatuin was used for automated generation of vegetation density maps, which requires LiDAR data to process an automatically generated map. A part of the orienteering map in the area of Kazlje-Tomaj was used to compare the graphical display of vegetation density. With different settings of parameters in the Karttapullautin application we changed the way how vegetation density of automatically generated map was presented, and tried to match it as much as possible with the orienteering map of Kazlje-Tomaj. Comparing more created maps of vegetation density the most suitable parameter settings to automatically generate maps on other areas were proposed, too.

MAPPING SPATIAL ACCURACY AND ESTIMATING LANDSCAPE INDICATORS FROM THEMATIC LAND COVER MAPS USING FUZZY SET THEORY

EPA Science Inventory

This paper presents a fuzzy set-based method of mapping spatial accuracy of thematic map and computing several ecological indicators while taking into account spatial variation of accuracy associated with different land cover types and other factors (e.g., slope, soil type, etc.)...

Non-destructive imaging of spinor Bose-Einstein condensates

NASA Astrophysics Data System (ADS)

Samson, E.; Vinit, Anshuman; Raman, Chandra

2013-05-01

We present a non-destructive differential imaging technique that enables the observation of the spatial distribution of the magnetization in a spinor Bose-Einstein condensate (BEC) through a Faraday rotation protocol. In our procedure, we utilize a linearly polarized, far-detuned laser beam as our imaging probe, and upon interaction with the condensate, the beam's polarization direction undergoes Faraday rotation. A differential measurement of the orthogonal polarization components of the rotated beam provides a spatial map of the net magnetization density within the BEC. The non-destructive aspect of this method allows for continuous imaging of the condensate. This imaging technique will prove useful in experimental BEC studies, such as spatially resolved magnetometry using ultracold atoms, and non-destructive imaging of non-equilibrium behavior of antiferromagnetic spinor condensates. This work was supported by the DARPA QuASAR program through a grant from ARO.

A catchment-scale model to predict spatial and temporal burden of E. coli on pasture from grazing livestock.

PubMed

Oliver, David M; Bartie, Phil J; Louise Heathwaite, A; Reaney, Sim M; Parnell, Jared A Q; Quilliam, Richard S

2018-03-01

Effective management of diffuse microbial water pollution from agriculture requires a fundamental understanding of how spatial patterns of microbial pollutants, e.g. E. coli, vary over time at the landscape scale. The aim of this study was to apply the Visualising Pathogen &Environmental Risk (ViPER) model, developed to predict E. coli burden on agricultural land, in a spatially distributed manner to two contrasting catchments in order to map and understand changes in E. coli burden contributed to land from grazing livestock. The model was applied to the River Ayr and Lunan Water catchments, with significant correlations observed between area of improved grassland and the maximum total E. coli per 1km 2 grid cell (Ayr: r=0.57; p<0.001, Lunan: r=0.32; p<0.001). There was a significant difference in the predicted maximum E. coli burden between seasons in both catchments, with summer and autumn predicted to accrue higher E. coli contributions relative to spring and winter (P<0.001), driven largely by livestock presence. The ViPER model thus describes, at the landscape scale, spatial nuances in the vulnerability of E. coli loading to land as driven by stocking density and livestock grazing regimes. Resulting risk maps therefore provide the underpinning evidence to inform spatially-targeted decision-making with respect to managing sources of E. coli in agricultural environments. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

The Price of Precision: Large-Scale Mapping of Forest Structure and Biomass Using Airborne Lidar

NASA Astrophysics Data System (ADS)

Dubayah, R.

2015-12-01

Lidar remote sensing provides one of the best means for acquiring detailed information on forest structure. However, its application over large areas has been limited largely because of its expense. Nonetheless, extant data exist over many states in the U.S., funded largely by state and federal consortia and mainly for infrastructure, emergency response, flood plain and coastal mapping. These lidar data are almost always acquired in leaf-off seasons, and until recently, usually with low point count densities. Even with these limitations, they provide unprecedented wall-to-wall mappings that enable development of appropriate methodologies for large-scale deployment of lidar. In this talk we summarize our research and lessons learned in deriving forest structure over regional areas as part of NASA's Carbon Monitoring System (CMS). We focus on two areas: the entire state of Maryland and Sonoma County, California. The Maryland effort used low density, leaf-off data acquired by each county in varying epochs, while the on-going Sonoma work employs state-of-the-art, high density, wall-to-wall, leaf-on lidar data. In each area we combine these lidar coverages with high-resolution multispectral imagery from the National Agricultural Imagery Program (NAIP) and in situ plot data to produce maps of canopy height, tree cover and biomass, and compare our results against FIA plot data and national biomass maps. Our work demonstrates that large-scale mapping of forest structure at high spatial resolution is achievable but products may be complex to produce and validate over large areas. Furthermore, fundamental issues involving statistical approaches, plot types and sizes, geolocation, modeling scales, allometry, and even the definitions of "forest" and "non-forest" must be approached carefully. Ultimately, determining the "price of precision", that is, does the value of wall-to-wall forest structure data justify their expense, should consider not only carbon market applications, but the other ways the underlying lidar data may be used.

Mapping Patterns and Trends in the Spatial Availability of Alcohol Using Low-Level Geographic Data: A Case Study in England 2003-2013.

PubMed

Angus, Colin; Holmes, John; Maheswaran, Ravi; Green, Mark A; Meier, Petra; Brennan, Alan

2017-04-12

Much literature examines the relationship between the spatial availability of alcohol and alcohol-related harm. This study aims to address an important gap in this evidence by using detailed outlet data to examine recent temporal trends in the sociodemographic distribution of spatial availability for different types of alcohol outlet in England. Descriptive analysis of measures of alcohol outlet density and proximity using extremely high resolution market research data stratified by outlet type and quintiles of area-level deprivation from 2003, 2007, 2010 and 2013 was undertaken and hierarchical linear growth models fitted to explore the significance of socioeconomic differences. We find that overall availability of alcohol changed very little from 2003 to 2013 (density +1.6%), but this conceals conflicting trends by outlet type and area-level deprivation. Mean on-trade density has decreased substantially (-2.2 outlets within 1 km (Inter-Quartile Range (IQR) -3-0), although access to restaurants has increased (+1.0 outlets (IQR 0-1)), while off-trade access has risen substantially (+2.4 outlets (IQR 0-3)). Availability is highest in the most deprived areas ( p < 0.0001) although these areas have also seen the greatest falls in on-trade outlet availability ( p < 0.0001). This study underlines the importance of using detailed, low-level geographic data to understand patterns and trends in the spatial availability of alcohol. There are significant variations in these trends by outlet type and deprivation level which may have important implications for health inequalities and public health policy.

Mapping Patterns and Trends in the Spatial Availability of Alcohol Using Low-Level Geographic Data: A Case Study in England 2003–2013

PubMed Central

Angus, Colin; Holmes, John; Maheswaran, Ravi; Green, Mark A.; Meier, Petra; Brennan, Alan

2017-01-01

Much literature examines the relationship between the spatial availability of alcohol and alcohol-related harm. This study aims to address an important gap in this evidence by using detailed outlet data to examine recent temporal trends in the sociodemographic distribution of spatial availability for different types of alcohol outlet in England. Descriptive analysis of measures of alcohol outlet density and proximity using extremely high resolution market research data stratified by outlet type and quintiles of area-level deprivation from 2003, 2007, 2010 and 2013 was undertaken and hierarchical linear growth models fitted to explore the significance of socioeconomic differences. We find that overall availability of alcohol changed very little from 2003 to 2013 (density +1.6%), but this conceals conflicting trends by outlet type and area-level deprivation. Mean on-trade density has decreased substantially (−2.2 outlets within 1 km (Inter-Quartile Range (IQR) −3–0), although access to restaurants has increased (+1.0 outlets (IQR 0–1)), while off-trade access has risen substantially (+2.4 outlets (IQR 0–3)). Availability is highest in the most deprived areas (p < 0.0001) although these areas have also seen the greatest falls in on-trade outlet availability (p < 0.0001). This study underlines the importance of using detailed, low-level geographic data to understand patterns and trends in the spatial availability of alcohol. There are significant variations in these trends by outlet type and deprivation level which may have important implications for health inequalities and public health policy. PMID:28417941

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

Spatial-Temporal Dynamics of Urban Fire Incidents: a Case Study of Nanjing, China

NASA Astrophysics Data System (ADS)

Yao, J.; Zhang, X.

2016-06-01

Fire and rescue service is one of the fundamental public services provided by government in order to protect people, properties and environment from fires and other disasters, and thus promote a safer living environment. Well understanding spatial-temporal dynamics of fire incidents can offer insights for potential determinants of various fire events and enable better fire risk estimation, assisting future allocation of prevention resources and strategic planning of mitigation programs. Using a 12-year (2002-2013) dataset containing the urban fire events in Nanjing, China, this research explores the spatial-temporal dynamics of urban fire incidents. A range of exploratory spatial data analysis (ESDA) approaches and tools, such as spatial kernel density and co-maps, are employed to examine the spatial, temporal and spatial-temporal variations of the fire events. Particular attention has been paid to two types of fire incidents: residential properties and local facilities, due to their relatively higher occurrence frequencies. The results demonstrated that the amount of urban fire has greatly increased in the last decade and spatial-temporal distribution of fire events vary among different incident types, which implies varying impact of potential influencing factors for further investigation.

Reporting of quantitative oxygen mapping in EPR imaging

NASA Astrophysics Data System (ADS)

Subramanian, Sankaran; Devasahayam, Nallathamby; McMillan, Alan; Matsumoto, Shingo; Munasinghe, Jeeva P.; Saito, Keita; Mitchell, James B.; Chandramouli, Gadisetti V. R.; Krishna, Murali C.

2012-01-01

Oxygen maps derived from electron paramagnetic resonance spectral-spatial imaging (EPRI) are based upon the relaxivity of molecular oxygen with paramagnetic spin probes. This technique can be combined with MRI to facilitate mapping of pO 2 values in specific anatomic locations with high precision. The co-registration procedure, which matches the physical and digital dimensions of EPR and MR images, may present the pO 2 map at the higher MRI resolution, exaggerating the spatial resolution of oxygen, making it difficult to precisely distinguish hypoxic regions from normoxic regions. The latter distinction is critical in monitoring the treatment of cancer by radiation and chemotherapy, since it is well-established that hypoxic regions are three or four times more resistant to treatment compared to normoxic regions. The aim of this article is to describe pO 2 maps based on the intrinsic resolution of EPRI. A spectral parameter that affects the intrinsic spatial resolution of EPRI is the full width at half maximum (FWHM) height of the gradient-free EPR absorption line in frequency-encoded imaging. In single point imaging too, the transverse relaxation times (T2∗) limit the resolution since the signal decays by exp(-tp/T2∗) where the delay time after excitation pulse, t p, is related to the resolution. Although the spin densities of two point objects may be resolved at this separation, it is inadequate to evaluate quantitative changes of pO 2 levels since the linewidths are proportionately affected by pO 2. A spatial separation of at least twice this resolution is necessary to correctly identify a change in pO 2 level. In addition, the pO 2 values are blurred by uncertainties arising from spectral dimensions. Blurring due to noise and low resolution modulates the pO 2 levels at the boundaries of hypoxic and normoxic regions resulting in higher apparent pO 2 levels in hypoxic regions. Therefore, specification of intrinsic resolution and pO 2 uncertainties are necessary to interpret digitally processed pO 2 illustrations.

Comparison of different digital elevation models and satellite imagery for lineament analysis: Implications for identification and spatial arrangement of fault zones in crystalline basement rocks of the southern Black Forest (Germany)

NASA Astrophysics Data System (ADS)

Meixner, J.; Grimmer, J. C.; Becker, A.; Schill, E.; Kohl, T.

2018-03-01

GIS-based remote sensing techniques and lineament mapping provide additional information on the spatial arrangement of faults and fractures in large areas with variable outcrop conditions. Due to inherent censoring and truncation bias mapping of lineaments is still a challenging task. In this study we show how statistical evaluations help to improve the reliability of lineament mappings by comparing two digital elevation models (ASTER, LIDAR) and satellite imagery data sets in the seismically active southern Black Forest. A statistical assessment of the orientation, average length, and the total length of mapped lineaments reveals an impact of the different resolutions of the data sets that allow to define maximum (censoring bias) and minimum (truncation bias) observable lineament length for each data set. The increase of the spatial resolution of the digital elevation model from 30 m × 30 m to 5 m × 5 m results in a decrease of total lineament length by about 40% whereby the average lineament lengths decrease by about 60%. Lineament length distributions of both data sets follow a power law distribution as documented elsewhere for fault and fracture systems. Predominant NE-, N-, NNW-, and NW-directions of the lineaments are observed in all data sets and correlate with well-known, mappable large-scale structures in the southern Black Forest. Therefore, mapped lineaments can be correlated with faults and hence display geological significance. Lineament density in the granite-dominated areas is apparently higher than in the gneiss-dominated areas. Application of a slip- and dilation tendency analysis on the fault pattern reveals largest reactivation potentials for WNW-ESE and N-S striking faults as strike-slip faults whereas normal faulting may occur along NW-striking faults within the ambient stress field. Remote sensing techniques in combination with highly resolved digital elevation models and a slip- and dilation tendency analysis thus can be used to quickly get first order results of the spatial arrangement of critically stressed faults in crystalline basement rocks.

Improving risk models for avian influenza: the role of intensive poultry farming and flooded land during the 2004 Thailand epidemic.

PubMed

Van Boeckel, Thomas P; Thanapongtharm, Weerapong; Robinson, Timothy; Biradar, Chandrashekhar M; Xiao, Xiangming; Gilbert, Marius

2012-01-01

Since 1996 when Highly Pathogenic Avian Influenza type H5N1 first emerged in southern China, numerous studies sought risk factors and produced risk maps based on environmental and anthropogenic predictors. However little attention has been paid to the link between the level of intensification of poultry production and the risk of outbreak. This study revised H5N1 risk mapping in Central and Western Thailand during the second wave of the 2004 epidemic. Production structure was quantified using a disaggregation methodology based on the number of poultry per holding. Population densities of extensively- and intensively-raised ducks and chickens were derived both at the sub-district and at the village levels. LandSat images were used to derive another previously neglected potential predictor of HPAI H5N1 risk: the proportion of water in the landscape resulting from floods. We used Monte Carlo simulation of Boosted Regression Trees models of predictor variables to characterize the risk of HPAI H5N1. Maps of mean risk and uncertainty were derived both at the sub-district and the village levels. The overall accuracy of Boosted Regression Trees models was comparable to that of logistic regression approaches. The proportion of area flooded made the highest contribution to predicting the risk of outbreak, followed by the densities of intensively-raised ducks, extensively-raised ducks and human population. Our results showed that as little as 15% of flooded land in villages is sufficient to reach the maximum level of risk associated with this variable. The spatial pattern of predicted risk is similar to previous work: areas at risk are mainly located along the flood plain of the Chao Phraya river and to the south-east of Bangkok. Using high-resolution village-level poultry census data, rather than sub-district data, the spatial accuracy of predictions was enhanced to highlight local variations in risk. Such maps provide useful information to guide intervention.

Improving Risk Models for Avian Influenza: The Role of Intensive Poultry Farming and Flooded Land during the 2004 Thailand Epidemic

PubMed Central

Van Boeckel, Thomas P.; Thanapongtharm, Weerapong; Robinson, Timothy; Biradar, Chandrashekhar M.; Xiao, Xiangming; Gilbert, Marius

2012-01-01

Since 1996 when Highly Pathogenic Avian Influenza type H5N1 first emerged in southern China, numerous studies sought risk factors and produced risk maps based on environmental and anthropogenic predictors. However little attention has been paid to the link between the level of intensification of poultry production and the risk of outbreak. This study revised H5N1 risk mapping in Central and Western Thailand during the second wave of the 2004 epidemic. Production structure was quantified using a disaggregation methodology based on the number of poultry per holding. Population densities of extensively- and intensively-raised ducks and chickens were derived both at the sub-district and at the village levels. LandSat images were used to derive another previously neglected potential predictor of HPAI H5N1 risk: the proportion of water in the landscape resulting from floods. We used Monte Carlo simulation of Boosted Regression Trees models of predictor variables to characterize the risk of HPAI H5N1. Maps of mean risk and uncertainty were derived both at the sub-district and the village levels. The overall accuracy of Boosted Regression Trees models was comparable to that of logistic regression approaches. The proportion of area flooded made the highest contribution to predicting the risk of outbreak, followed by the densities of intensively-raised ducks, extensively-raised ducks and human population. Our results showed that as little as 15% of flooded land in villages is sufficient to reach the maximum level of risk associated with this variable. The spatial pattern of predicted risk is similar to previous work: areas at risk are mainly located along the flood plain of the Chao Phraya river and to the south-east of Bangkok. Using high-resolution village-level poultry census data, rather than sub-district data, the spatial accuracy of predictions was enhanced to highlight local variations in risk. Such maps provide useful information to guide intervention. PMID:23185352

Initial Results from the New Stress Map of Texas Project

NASA Astrophysics Data System (ADS)

Lund Snee, J. E.; Zoback, M. D.

2015-12-01

Modern techniques for characterizing tectonic stress orientation and relative magnitude have been successfully used for more than 35 years. Nevertheless, large areas of North America lack high spatial resolution maps of stress orientation, magnitude, and faulting regime. In Texas, for example, <30 A-C-quality stress orientations are currently registered on the World Stress Map and only 7 of these points also describe the stress regime. Stress data are foundational elements of attempts to characterize tectonic driving forces, understand hazards associated with induced seismicity, and optimize production of oil, gas, and geothermal resources. This year, we launched the Texas Stress Map project to characterize tectonic stress patterns at higher spatial resolution across Texas and nearby areas. Following a successful effort just completed in Oklahoma, we will evaluate borehole breakouts, drilling-induced tensile fractures, shear wave anisotropy, and earthquake data. The principal data source will be FMI (fullbore formation microimager), UBI (ultrasonic borehole imager), cross-dipole sonic, density, and caliper logs provided by private industry. Earthquake moment tensor solutions from the U.S. Geological Survey, Saint Louis University and other sources will also be used. Our initial focus is on the Permian Basin and Barnett Shale petroleum plays due to the availability of data, but we will expand our analysis across the state as the project progresses. In addition, we hope to eventually apply the higher spatial resolution data coverage to understanding tectonic and geodynamic characteristics of the southwestern United States and northeastern Mexico. Here we present early results from our work to constrain stress orientations and faulting regime in and near Texas, and we also provide a roadmap for the ongoing research.

Airborne Laser Altimetry Mapping of the Greenland Ice Sheet: Application to Mass Balance Assessment

NASA Technical Reports Server (NTRS)

Abdalati, W.; Krabill, W.; Frederick, E.; Manizade, S.; Martin, C.; Sonntag, J.; Swift, R.; Thomas, R.; Wright, W.; Yungel, J.

2000-01-01

In 1998 and '99, the Arctic Ice Mapping (AIM) program completed resurveys of lines occupied 5 years earlier revealing elevation changes of the Greenland ice sheet and identifying areas of significant thinning, thickening and balance. In planning these surveys, consideration had to be given to the spatial constraints associated with aircraft operation, the spatial nature of ice sheet behavior, and limited resources, as well as temporal issues, such as seasonal and interannual variability in the context of measurement accuracy. This paper examines the extent to which the sampling and survey strategy is valid for drawing conclusions on the current state of balance of the Greenland ice sheet. The surveys covered the entire ice sheet with an average distance of 21.4 km between each location on the ice sheet and the nearest flight line. For most of the ice sheet, the elevation changes show relatively little spatial variability, and their magnitudes are significantly smaller than the observed elevation change signal. As a result, we conclude that the density of the sampling and the accuracy of the measurements are sufficient to draw meaningful conclusions on the state of balance of the entire ice sheet over the five-year survey period. Outlet glaciers, however, show far more spatial and temporal variability, and each of the major ones is likely to require individual surveys in order to determine its balance.

Using GIS Mapping to Target Public Health Interventions: Examining Birth Outcomes Across GIS Techniques.

PubMed

MacQuillan, E L; Curtis, A B; Baker, K M; Paul, R; Back, Y O

2017-08-01

With advances in spatial analysis techniques, there has been a trend in recent public health research to assess the contribution of area-level factors to health disparity for a number of outcomes, including births. Although it is widely accepted that health disparity is best addressed by targeted, evidence-based and data-driven community efforts, and despite national and local focus in the U.S. to reduce infant mortality and improve maternal-child health, there is little work exploring how choice of scale and specific GIS visualization technique may alter the perception of analyses focused on health disparity in birth outcomes. Retrospective cohort study. Spatial analysis of individual-level vital records data for low birthweight and preterm births born to black women from 2007 to 2012 in one mid-sized Midwest city using different geographic information systems (GIS) visualization techniques [geocoded address records were aggregated at two levels of scale and additionally mapped using kernel density estimation (KDE)]. GIS analyses in this study support our hypothesis that choice of geographic scale (neighborhood or census tract) for aggregated birth data can alter programmatic decision-making. Results indicate that the relative merits of aggregated visualization or the use of KDE technique depend on the scale of intervention. The KDE map proved useful in targeting specific areas for interventions in cities with smaller populations and larger census tracts, where they allow for greater specificity in identifying intervention areas. When public health programmers seek to inform intervention placement in highly populated areas, however, aggregated data at the census tract level may be preferred, since it requires lower investments in terms of time and cartographic skill and, unlike neighborhood, census tracts are standardized in that they become smaller as the population density of an area increases.

Abundance Variations and Flows in Plage Regions Observed with CDS/SOHO

NASA Astrophysics Data System (ADS)

Rank, G.; Bagalá, L. G.; Czaykowska, A.; Haerendel, G.

1999-10-01

We present results from CDS/SOHO observations of the spotless active region NOAA-8208, obtained on 28th April 1998 near disk center. MDI images show a bipolar magnetic configuration. The regions of enhanced He I emission correspond to the areas with strong magnetic flux and also with bright plage areas seen in Ca II and H-alpha images. A high correlation is found between intensity maps of the transition region lines He I (logTmax = 4.3), O III (logTmax = 5.0), and O V (logTmax = 5.4). The line-of-sight velocities of He I reveal a strong downflow in the plage areas. Further, the line-of-sight velocities of He I, O III, and O V are well correlated, showing that the downflow pattern exists up to temperatures of about 0.25 MK. At higher temperatures (Mg VIII at logTmax = 5.8) this flow is not detected, suggesting that material streams into the plage region from sideways in the high transition region. Maps of the electron density in the transition region have been constructed from several line ratios yielding densities of about 9.0 cm-3 in the plage regions, about dex 0.5 cm-3 higher compared to the surrounding. To study the spatial variation of the first ionization potential (FIP) effect, the abundance ratio has been mapped for the ion ratio MgVI/NeVI. The ratio is highly variable on spatial scales down to a few arcsec from photospheric values to enhancements of a factor of 10. The strongest FIP enhancements are not correlated with transition region line emission, but are found outside of the plage regions. Some areas of strong FIP enhancement appear stretched and elongated, suggesting that the material is confined in loop-like structures.

Development and Applications of a Comprehensive Land Use Classification and Map for the US

PubMed Central

Theobald, David M.

2014-01-01

Land cover maps reasonably depict areas that are strongly converted by human activities, but typically are unable to resolve low-density but widespread development patterns. Data products specifically designed to resolve land uses complement land cover datasets and likely improve our ability to understand the extent and complexity of human modification. Methods for developing a comprehensive land use classification system are described, and a map of land use for the conterminous United States is presented to reveal what we are doing on the land. The comprehensive, detailed and high-resolution dataset was developed through spatial analysis of nearly two-dozen publicly-available, national spatial datasets – predominately based on census housing, employment, and infrastructure, as well as land cover from satellite imagery. This effort resulted in 79 land use classes that fit within five main land use groups: built-up, production, recreation, conservation, and water. Key findings from this study are that built-up areas occupy 13.6% of mainland US, but that the majority of this occurs as low-density exurban/rural residential (9.1% of the US), while more intensive built-up land uses occupy 4.5%. For every acre of urban and suburban residential land, there are 0.13 commercial, 0.07 industrial, 0.48 institutional, and 0.29 acres of interstates/highways. This database can be used to address a variety of natural resource applications, and I provide three examples here: an entropy index of the diversity of land uses for smart-growth planning, a power-law scaling of metropolitan area population to developed footprint, and identifying potential conflict areas by delineating the urban interface. PMID:24728210

Charge density wave order in 1D mirror twin boundaries of single-layer MoSe 2

DOE PAGES

Barja, Sara; Wickenburg, Sebastian; Liu, Zhen-Fei; ...

2016-04-18

Here, We provide direct evidence for the existence of isolated, one-dimensional charge density waves at mirror twin boundaries (MTBs) of single-layer semiconducting MoSe 2. Such MTBs have been previously observed by transmission electron microscopy and have been predicted to be metallic in MoSe 2 and MoS 2. Our low-temperature scanning tunnelling microscopy/spectroscopy measurements revealed a substantial bandgap of 100 meV opening at the Fermi energy in the otherwise metallic one-dimensional structures. We found a periodic modulation in the density of states along the MTB, with a wavelength of approximately three lattice constants. In addition to mapping the energy-dependent densitymore » of states, we determined the atomic structure and bonding of the MTB through simultaneous high-resolution non-contact atomic force microscopy. Density functional theory calculations based on the observed structure reproduced both the gap opening and the spatially resolved density of states.« less

Time resolved interferometric study of the plasma plume induced shock wave in confined geometry: Two-dimensional mapping of the ambient and plasma density

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

Choudhury, Kaushik; Singh, R. K.; Kumar, Ajai, E-mail: ajai@ipr.res.in

2016-04-15

An experimental investigation of the laser produced plasma induced shock wave in the presence of confining walls placed along the axial as well as the lateral direction has been performed. A time resolved Mach Zehnder interferometer is set up to track the primary as well as the reflected shock waves and its effect on the evolving plasma plume has been studied. An attempt has been made to discriminate the electronic and medium density contributions towards the changes in the refractive index of the medium. Two dimensional spatial distributions for both ambient medium density and plasma density (electron density) have beenmore » obtained by employing customised inversion technique and algorithm on the recorded interferograms. The observed density pattern of the surrounding medium in the presence of confining walls is correlated with the reflected shock wave propagation in the medium. Further, the shock wave plasma interaction and the subsequent changes in the shape and density of the plasma plume in confined geometry are briefly described.« less

Predicting and mapping soil available water capacity in Korea.

PubMed

Hong, Suk Young; Minasny, Budiman; Han, Kyung Hwa; Kim, Yihyun; Lee, Kyungdo

2013-01-01

The knowledge on the spatial distribution of soil available water capacity at a regional or national extent is essential, as soil water capacity is a component of the water and energy balances in the terrestrial ecosystem. It controls the evapotranspiration rate, and has a major impact on climate. This paper demonstrates a protocol for mapping soil available water capacity in South Korea at a fine scale using data available from surveys. The procedures combined digital soil mapping technology with the available soil map of 1:25,000. We used the modal profile data from the Taxonomical Classification of Korean Soils. The data consist of profile description along with physical and chemical analysis for the modal profiles of the 380 soil series. However not all soil samples have measured bulk density and water content at -10 and -1500 kPa. Thus they need to be predicted using pedotransfer functions. Furthermore, water content at -10 kPa was measured using ground samples. Thus a correction factor is derived to take into account the effect of bulk density. Results showed that Andisols has the highest mean water storage capacity, followed by Entisols and Inceptisols which have loamy texture. The lowest water retention is Entisols which are dominated by sandy materials. Profile available water capacity to a depth of 1 m was calculated and mapped for Korea. The western part of the country shows higher available water capacity than the eastern part which is mountainous and has shallower soils. The highest water storage capacity soils are the Ultisols and Alfisols (mean of 206 and 205 mm, respectively). Validation of the maps showed promising results. The map produced can be used as an indication of soil physical quality of Korean soils.

Multilevel spatiotemporal change-point models for evaluating the effect of an alcohol outlet control policy on changes in neighborhood assaultive violence rates.

PubMed

Xu, Yanjun; Yu, Qingzhao; Scribner, Richard; Theall, Katherine; Scribner, Scott; Simonsen, Neal

2012-06-01

Many previous studies have suggested a link between alcohol outlets and assaultive violence rates. In 1997 the City of New Orleans adopted a series of policies, e.g., increased license fee, additional enforcement staff, and expanded powers for the alcohol license board. The policies were specifically enacted to address the proliferation of problem alcohol outlets believed to be the source of a variety of social problems including assaultive violence. In this research, we evaluate the impact of a city level policy in New Orleans to address the problem alcohol outlets and their influence on assaultive violence. The spatial association between rates of assaultive violence at the census tract level (n=170) over a ten year period raises a challenge in statistical analysis. To meet this challenge we developed a hierarchical change-point model that controls for important covariates of assaultive violence and accounts for unexplained spatial and temporal variability. While our model is somewhat complex, its hierarchical Bayesian analysis is accessible via the WinBUGS software program. Keeping other effects fixed, the implementation of the new city level policy was associated with a decrease in the positive association between census tract level rates of assaultive violence and alcohol outlet density. Comparing several candidate change-point models using the DIC criterion, the positive association began decreasing the year of the policy implementation. The magnitude of the association continued to decrease for roughly two years and then stabilized. We also created maps of the fitted assaultive violence rates in New Orleans, as well as spatial residual maps which, together with Moran's I's, suggest that the spatial variation of the data is well accounted for by our model. We reach the conclusion that the implementation of the policy is associated with a significant decrease in the positive relationship between assaultive violence and the off-sale alcohol outlet density. Copyright © 2012 Elsevier Ltd. All rights reserved.

Spatial variation in mortality risk for haematological malignancies near a petrochemical refinery: a population-based case-control study

PubMed Central

Di Salvo, Francesca; Meneghini, Elisabetta; Vieira, Veronica; Baili, Paolo; Mariottini, Mauro; Baldini, Marco; Micheli, Andrea; Sant, Milena

2015-01-01

Introduction The study investigated the geographic variation of mortality risk for hematological malignancies (HMs) in order to identify potential high-risk areas near an Italian petrochemical refinery. Material and methods A population-based case-control study was conducted and residential histories for 171 cases and 338 sex- and age-matched controls were collected. Confounding factors were obtained from interviews with consenting relatives for 109 HM deaths and 267 controls. To produce risk mortality maps, two different approaches were applied. We mapped (1) adptive kernel density relative risk estimation (KDE) for case-control studies which estimates a spatial relative risk function using the ratio between cases and controls’ densities, and (2) estimated odds ratios for case-control study data using generalized additive models (GAMs) to smooth the effect of location, a proxy for exposure, while adjusting for confounding variables. Results No high-risk areas for HM mortality were identified among all subjects (men and women combined), by applying both approaches. Using the adaptive KDE approach, we found a significant increase in death risk only among women in a large area 2–6 km southeast of the refinery and the application of GAMs also identified a similarly-located significant high-risk area among women only (global p-value<0.025). Potential confounding risk factors we considered in the GAM did not alter the results. Conclusion Both approaches identified a high-risk area close to the refinery among women only. Those spatial methods are useful tools for public policy management to determine priority areas for intervention. Our findings suggest several directions for further research in order to identify other potential environmental exposures that may be assessed in forthcoming studies based on detailed exposure modeling. PMID:26073202

Big Data Geo-Analytical Tool Development for Spatial Analysis Uncertainty Visualization and Quantification Needs

NASA Astrophysics Data System (ADS)

Rose, K.; Bauer, J. R.; Baker, D. V.

2015-12-01

As big data computing capabilities are increasingly paired with spatial analytical tools and approaches, there is a need to ensure uncertainty associated with the datasets used in these analyses is adequately incorporated and portrayed in results. Often the products of spatial analyses, big data and otherwise, are developed using discontinuous, sparse, and often point-driven data to represent continuous phenomena. Results from these analyses are generally presented without clear explanations of the uncertainty associated with the interpolated values. The Variable Grid Method (VGM) offers users with a flexible approach designed for application to a variety of analyses where users there is a need to study, evaluate, and analyze spatial trends and patterns while maintaining connection to and communicating the uncertainty in the underlying spatial datasets. The VGM outputs a simultaneous visualization representative of the spatial data analyses and quantification of underlying uncertainties, which can be calculated using data related to sample density, sample variance, interpolation error, uncertainty calculated from multiple simulations. In this presentation we will show how we are utilizing Hadoop to store and perform spatial analysis through the development of custom Spark and MapReduce applications that incorporate ESRI Hadoop libraries. The team will present custom 'Big Data' geospatial applications that run on the Hadoop cluster and integrate with ESRI ArcMap with the team's probabilistic VGM approach. The VGM-Hadoop tool has been specially built as a multi-step MapReduce application running on the Hadoop cluster for the purpose of data reduction. This reduction is accomplished by generating multi-resolution, non-overlapping, attributed topology that is then further processed using ESRI's geostatistical analyst to convey a probabilistic model of a chosen study region. Finally, we will share our approach for implementation of data reduction and topology generation via custom multi-step Hadoop applications, performance benchmarking comparisons, and Hadoop-centric opportunities for greater parallelization of geospatial operations. The presentation includes examples of the approach being applied to a range of subsurface, geospatial studies (e.g. induced seismicity risk).

Visualization of NO2 emission sources using temporal and spatial pattern analysis in Asia

NASA Astrophysics Data System (ADS)

Schütt, A. M. N.; Kuhlmann, G.; Zhu, Y.; Lipkowitsch, I.; Wenig, M.

2016-12-01

Nitrogen dioxide (NO2) is an indicator for population density and level of development, but the contributions of the different emission sources to the overall concentrations remains mostly unknown. In order to allocate fractions of OMI NO2 to emission types, we investigate several temporal cycles and regional patterns.Our analysis is based on daily maps of tropospheric NO2 vertical column densities (VCDs) from the Ozone Monitoring Instrument (OMI). The data set is mapped to a high resolution grid by a histopolation algorithm. This algorithm is based on a continuous parabolic spline, producing more realistic smooth distributions while reproducing the measured OMI values when integrating over ground pixel areas.In the resulting sequence of zoom in maps, we analyze weekly and annual cycles for cities, countryside and highways in China, Japan and Korea Republic and look for patterns and trends and compare the derived results to emission sources in Middle Europe and North America. Due to increased heating in winter compared to summer and more traffic during the week than on Sundays, we dissociate traffic, heating and power plants and visualized maps with different sources. We will also look into the influence of emission control measures during big events like the Olympic Games 2008 and the World Expo 2010 as a possibility to confirm our classification of NO2 emission sources.

GEMAS: Spatial pattern analysis of Ni by using digital image processing techniques on European agricultural soil data

NASA Astrophysics Data System (ADS)

Jordan, Gyozo; Petrik, Attila; De Vivo, Benedetto; Albanese, Stefano; Demetriades, Alecos; Sadeghi, Martiya

2017-04-01

Several studies have investigated the spatial distribution of chemical elements in topsoil (0-20 cm) within the framework of the EuroGeoSurveys Geochemistry Expert Group's 'Geochemical Mapping of Agricultural and Grazing Land Soil' project . Most of these studies used geostatistical analyses and interpolated concentration maps, Exploratory and Compositional Data and Analysis to identify anomalous patterns. The objective of our investigation is to demonstrate the use of digital image processing techniques for reproducible spatial pattern recognition and quantitative spatial feature characterisation. A single element (Ni) concentration in agricultural topsoil is used to perform the detailed spatial analysis, and to relate these features to possible underlying processes. In this study, simple univariate statistical methods were implemented first, and Tukey's inner-fence criterion was used to delineate statistical outliers. The linear and triangular irregular network (TIN) interpolation was used on the outlier-free Ni data points, which was resampled to a 10*10 km grid. Successive moving average smoothing was applied to generalise the TIN model and to suppress small- and at the same time enhance significant large-scale features of Nickel concentration spatial distribution patterns in European topsoil. The TIN map smoothed with a moving average filter revealed the spatial trends and patterns without losing much detail, and it was used as the input into digital image processing, such as local maxima and minima determination, digital cross sections, gradient magnitude and gradient direction calculation, second derivative profile curvature calculation, edge detection, local variability assessment, lineament density and directional variogram analyses. The detailed image processing analysis revealed several NE-SW, E-W and NW-SE oriented elongated features, which coincide with different spatial parameter classes and alignment with local maxima and minima. The NE-SW oriented linear pattern is the dominant feature to the south of the last glaciation limit. Some of these linear features are parallel to the suture zone of the Iapetus Ocean, while the others follow the Alpine and Carpathian Chains. The highest variability zones of Ni concentration in topsoil are located in the Alps and in the Balkans where mafic and ultramafic rocks outcrop. The predominant NE-SW oriented pattern is also captured by the strong anisotropy in the semi-variograms in this direction. A single major E-W oriented north-facing feature runs along the southern border of the last glaciation zone. This zone also coincides with a series of local maxima in Ni concentration along the glaciofluvial deposits. The NW-SE elongated spatial features are less dominant and are located in the Pyrenees and Scandinavia. This study demonstrates the efficiency of systematic image processing analysis in identifying and characterising spatial geochemical patterns that often remain uncovered by the usual visual map interpretation techniques.

Domestic well locations and populations served in the contiguous U.S.: 1990

USGS Publications Warehouse

Johnson, Tyler; Belitz, Kenneth

2017-01-01

We estimate the location and population served by domestic wells in the contiguous United States in two ways: (1) the “Block Group Method” or BGM, uses data from the 1990 census, and (2) the “Road-Enhanced Method” or REM, refines the locations by using a buffer expansion and shrinkage technique along roadways to define areas where domestic wells exist. The fundamental assumption is that houses (and therefore domestic wells) are located near a named road. The results are presented as two nationally-consistent domestic-well population datasets.While both methods can be considered valid, the REM map is more precise in locating domestic wells; the REM map has a smaller amount of spatial bias (Type 1 and Type 2 errors nearly equal vs biased in Type 1), total error (10.9% vs 23.7%), and distance error (2.0 km vs 2.7 km), when comparing the REM and BGM maps to a calibration map in California. However, the BGM map is more inclusive of all potential locations for domestic wells. Independent domestic well datasets from the USGS, and the States of MN, NV, and TX show that the BGM captures about 5 to 10% more wells than the REM.One key difference between the BGM and the REM is the mapping of low density areas. The REM reduces areas mapped as low density by 57%, concentrating populations into denser regions. Therefore, if one is trying to capture all of the potential areas of domestic-well usage, then the BGM map may be more applicable. If location is more imperative, then the REM map is better at identifying areas of the landscape with the highest probability of finding a domestic well. Depending on the purpose of a study, a combination of both maps can be used.

A comparison of multi-spectral, multi-angular, and multi-temporal remote sensing datasets for fractional shrub canopy mapping in Arctic Alaska

USGS Publications Warehouse

Selkowitz, D.J.

2010-01-01

Shrub cover appears to be increasing across many areas of the Arctic tundra biome, and increasing shrub cover in the Arctic has the potential to significantly impact global carbon budgets and the global climate system. For most of the Arctic, however, there is no existing baseline inventory of shrub canopy cover, as existing maps of Arctic vegetation provide little information about the density of shrub cover at a moderate spatial resolution across the region. Remotely-sensed fractional shrub canopy maps can provide this necessary baseline inventory of shrub cover. In this study, we compare the accuracy of fractional shrub canopy (> 0.5 m tall) maps derived from multi-spectral, multi-angular, and multi-temporal datasets from Landsat imagery at 30 m spatial resolution, Moderate Resolution Imaging SpectroRadiometer (MODIS) imagery at 250 m and 500 m spatial resolution, and MultiAngle Imaging Spectroradiometer (MISR) imagery at 275 m spatial resolution for a 1067 km2 study area in Arctic Alaska. The study area is centered at 69 ??N, ranges in elevation from 130 to 770 m, is composed primarily of rolling topography with gentle slopes less than 10??, and is free of glaciers and perennial snow cover. Shrubs > 0.5 m in height cover 2.9% of the study area and are primarily confined to patches associated with specific landscape features. Reference fractional shrub canopy is determined from in situ shrub canopy measurements and a high spatial resolution IKONOS image swath. Regression tree models are constructed to estimate fractional canopy cover at 250 m using different combinations of input data from Landsat, MODIS, and MISR. Results indicate that multi-spectral data provide substantially more accurate estimates of fractional shrub canopy cover than multi-angular or multi-temporal data. Higher spatial resolution datasets also provide more accurate estimates of fractional shrub canopy cover (aggregated to moderate spatial resolutions) than lower spatial resolution datasets, an expected result for a study area where most shrub cover is concentrated in narrow patches associated with rivers, drainages, and slopes. Including the middle infrared bands available from Landsat and MODIS in the regression tree models (in addition to the four standard visible and near-infrared spectral bands) typically results in a slight boost in accuracy. Including the multi-angular red band data available from MISR in the regression tree models, however, typically boosts accuracy more substantially, resulting in moderate resolution fractional shrub canopy estimates approaching the accuracy of estimates derived from the much higher spatial resolution Landsat sensor. Given the poor availability of snow and cloud-free Landsat scenes in many areas of the Arctic and the promising results demonstrated here by the MISR sensor, MISR may be the best choice for large area fractional shrub canopy mapping in the Alaskan Arctic for the period 2000-2009.

(Semi-)Automated landform mapping of the alpine valley Gradental (Austria) based on LiDAR data

NASA Astrophysics Data System (ADS)

Strasser, T.; Eisank, C.

2012-04-01

Alpine valleys are typically characterised as complex, hierarchical structured systems with rapid landform changes. Detection of landform changes can be supported by automated geomorphological mapping. Especially, the analysis over short time scales require a method for standardised, unbiased geomorphological map reproduction, which is delivered by automated mapping techniques. In general, digital geomorphological mapping is a challenging task, since knowledge about landforms with respect to their natural boundaries as well as their hierarchical and scaling relationships, has to be integrated in an objective way. A combination of very-high spatial resolution data (VHSR) such as LiDAR and new methods like object based image analysis (OBIA) allow for a more standardised production of geomorphological maps. In OBIA the processing units are spatially configured objects that are created by multi-scale segmentation. Therefore, not only spectral information can be used for assigning the objects to geomorphological classes, but also spatial and topological properties can be exploited. In this study we focus on the detection of landforms, especially bedrock sediment deposits (alluvion, debris cone, talus, moraine, rockglacier), as well as glaciers. The study site Gradental [N 46°58'29.1"/ E 12°48'53.8"] is located in the Schobergruppe (Austria, Carinthia) and is characterised by heterogenic geology conditions and high process activity. The area is difficult to access and dominated by steep slopes, thus hindering a fast and detailed geomorphological field mapping. Landforms are identified using aerial and terrestrial LiDAR data (1 m spatial resolution). These DEMs are analysed by an object based hierarchical approach, which is structured in three main steps. The first step is to define occurring landforms by basic land surface parameters (LSPs), topology and hierarchy relations. Based on those definitions a semantic model is created. Secondly, a multi-scale segmentation is performed on a three-band LSP that integrates slope, aspect and plan curvature, which expresses the driving forces of geomorphological processes. In the third step, the generated multi-level object structures are classified in order to produce the geomorphological map. The classification rules are derived from the semantic model. Due to landform type-specific scale dependencies of LSPs, the values of LSPs used in the classification are calculated in a multi-scale manner by constantly enlarging the size of the moving window. In addition, object form properties (density, compactness, rectangular fit) are utilised as additional information for landform characterisation. Validation of classification is performed by intersecting a visually interpreted reference map with the classification output map and calculating accuracy matrices. Validation shows an overall accuracy of 78.25 % and a Kappa of 0.65. The natural borders of landforms can be easily detected by the use of slope, aspect and plan curvature. This study illustrates the potential of OBIA for a more standardised and automated mapping of surface units (landforms, landcover). Therefore, the presented methodology features a prospective automated geomorphological mapping approach for alpine regions.

One-dimensional turbulence modeling for cylindrical and spherical flows: model formulation and application

NASA Astrophysics Data System (ADS)

Lignell, David O.; Lansinger, Victoria B.; Medina, Juan; Klein, Marten; Kerstein, Alan R.; Schmidt, Heiko; Fistler, Marco; Oevermann, Michael

2018-06-01

The one-dimensional turbulence (ODT) model resolves a full range of time and length scales and is computationally efficient. ODT has been applied to a wide range of complex multi-scale flows, such as turbulent combustion. Previous ODT comparisons to experimental data have focused mainly on planar flows. Applications to cylindrical flows, such as round jets, have been based on rough analogies, e.g., by exploiting the fortuitous consistency of the similarity scalings of temporally developing planar jets and spatially developing round jets. To obtain a more systematic treatment, a new formulation of the ODT model in cylindrical and spherical coordinates is presented here. The model is written in terms of a geometric factor so that planar, cylindrical, and spherical configurations are represented in the same way. Temporal and spatial versions of the model are presented. A Lagrangian finite-volume implementation is used with a dynamically adaptive mesh. The adaptive mesh facilitates the implementation of cylindrical and spherical versions of the triplet map, which is used to model turbulent advection (eddy events) in the one-dimensional flow coordinate. In cylindrical and spherical coordinates, geometric stretching of the three triplet map images occurs due to the radial dependence of volume, with the stretching being strongest near the centerline. Two triplet map variants, TMA and TMB, are presented. In TMA, the three map images have the same volume, but different radial segment lengths. In TMB, the three map images have the same radial segment lengths, but different segment volumes. Cylindrical results are presented for temporal pipe flow, a spatial nonreacting jet, and a spatial nonreacting jet flame. These results compare very well to direct numerical simulation for the pipe flow, and to experimental data for the jets. The nonreacting jet treatment overpredicts velocity fluctuations near the centerline, due to the geometric stretching of the triplet maps and its effect on the eddy event rate distribution. TMB performs better than TMA. A hybrid planar-TMB (PTMB) approach is also presented, which further improves the results. TMA, TMB, and PTMB are nearly identical in the pipe flow where the key dynamics occur near the wall away from the centerline. The jet flame illustrates effects of variable density and viscosity, including dilatational effects.

SWAG: Survey of Water and Ammonia in the Galactic Center

NASA Astrophysics Data System (ADS)

Ott, Jürgen; Meier, David S.; Krieger, Nico; Rickert, Matthew

2017-01-01

SWAG (``Survey of Water and Ammonia in the Galactic Center'') is a multi-line interferometric survey toward the Center of the Milky Way conducted with the Australia Telescope Compact Array. The survey region spans the entire ~400 pc Central Molecular Zone and comprises ~42 spectral lines at pc spatial and sub-km/s spectral resolution. In addition, we deeply map continuum intensity, spectral index, and polarization at the frequencies where synchrotron, free-free, and thermal dust sources emit. The observed spectral lines include many transitions of ammonia, which we use to construct maps of molecular gas temperature, opacity and gas formation temperature (see poster by Nico Krieger et al., this volume). Water masers pinpoint the sites of active star formation and other lines are good tracers for density, radiation field, shocks, and ionization. This extremely rich survey forms a perfect basis to construct maps of the physical parameters of the gas in this extreme environment.

Effect of Variation of Silicon Nitride Passivation Layer on Electron Irradiated Aluminum Gallium Nitride/Gallium Nitride HEMT Structures

DTIC Science & Technology

2014-06-19

the AlGaN is unintentionally doped . Figure 2.3. AlGaN/GaN band diagram showing polarization charges. The band diagram in Figure 2.3 shows...intentionally doped as are MESFETS, and the channel gets its electrons from the unintentional doping . There is less Coulomb scattering in the...temperature measurements are often used to provide spatial PL maps of doping and trap densities. Laser excitation (quasi-monochromatic) is

Spatial vent opening probability map of El Hierro Island (Canary Islands, Spain)

NASA Astrophysics Data System (ADS)

Becerril, Laura; Cappello, Annalisa; Galindo, Inés; Neri, Marco; Del Negro, Ciro

2013-04-01

The assessment of the probable spatial distribution of new eruptions is useful to manage and reduce the volcanic risk. It can be achieved in different ways, but it becomes especially hard when dealing with volcanic areas less studied, poorly monitored and characterized by a low frequent activity, as El Hierro. Even though it is the youngest of the Canary Islands, before the 2011 eruption in the "Las Calmas Sea", El Hierro had been the least studied volcanic Island of the Canaries, with more historically devoted attention to La Palma, Tenerife and Lanzarote. We propose a probabilistic method to build the susceptibility map of El Hierro, i.e. the spatial distribution of vent opening for future eruptions, based on the mathematical analysis of the volcano-structural data collected mostly on the Island and, secondly, on the submerged part of the volcano, up to a distance of ~10-20 km from the coast. The volcano-structural data were collected through new fieldwork measurements, bathymetric information, and analysis of geological maps, orthophotos and aerial photographs. They have been divided in different datasets and converted into separate and weighted probability density functions, which were then included in a non-homogeneous Poisson process to produce the volcanic susceptibility map. Future eruptive events on El Hierro is mainly concentrated on the rifts zones, extending also beyond the shoreline. The major probabilities to host new eruptions are located on the distal parts of the South and West rifts, with the highest probability reached in the south-western area of the West rift. High probabilities are also observed in the Northeast and South rifts, and the submarine parts of the rifts. This map represents the first effort to deal with the volcanic hazard at El Hierro and can be a support tool for decision makers in land planning, emergency plans and civil defence actions.

Social values for ecosystem services (SolVES): A GIS application for assessing, mapping, and quantifying the social values of ecosystem services-Documentation and user manual, version 1.0

USGS Publications Warehouse

Sherrouse, Benson C.; Riegle, Jodi L.; Semmens, Darius J.

2010-01-01

In response to the need for incorporating quantified and spatially explicit measures of social values into ecosystem services assessments, the Rocky Mountain Geographic Science Center, in collaboration with Colorado State University, has developed a geographic information system application, Social Values for Ecosystem Services (SolVES). SolVES can be used to assess, map, and quantify the perceived social values of ecosystem services. SolVES derives a quantitative social values metric, the Value Index, from a combination of spatial and nonspatial responses to public attitude and preference surveys. SolVES also generates landscape metrics, such as average elevation and distance to water, calculated from spatial data layers describing the underlying physical environment. Using kernel density calculations and zonal statistics, SolVES derives and maps the 10-point Value Index and reports landscape metrics associated with each index value for social value types such as aesthetics, biodiversity, and recreation. This can be repeated for various survey subgroups as distinguished by their attitudes and preferences regarding public uses of the forests such as motorized recreation and logging for fuels reduction. The Value Index provides a basis of comparison within and among survey subgroups to consider the effect of social contexts on the valuation of ecosystem services. SolVES includes regression coefficients linking the predicted value (the Value Index) to landscape metrics. These coefficients are used to generate predicted social value maps using value transfer techniques for areas where primary survey data are not available. SolVES was developed, and will continue to be enhanced through future versions, as a public domain tool to enable decision makers and researchers to map the social values of ecosystem services and to facilitate discussions among diverse stakeholders regarding tradeoffs between different ecosystem services in a variety of physical and social contexts.

A quantitative estimate of the function of soft-bottom sheltered coastal areas as essential flatfish nursery habitat

NASA Astrophysics Data System (ADS)

Trimoreau, E.; Archambault, B.; Brind'Amour, A.; Lepage, M.; Guitton, J.; Le Pape, O.

2013-11-01

Essential fish habitat suitability (EFHS) models and geographic information system (GIS) were combined to describe nursery habitats for three flatfish species (Solea solea, Pleuronectes platessa, Dicologlossa cuneata) in the Bay of Biscay (Western Europe), using physical parameters known or suspected to influence juvenile flatfish spatial distribution and density (i.e. bathymetry, sediment, estuarine influence and wave exposure). The effects of habitat features on juvenile distribution were first calculated from EFHS models, used to identify the habitats in which juvenile are concentrated. The EFHS model for S. solea confirmed previous findings regarding its preference for shallow soft bottom areas and provided new insights relating to the significant effect of wave exposure on nursery habitat suitability. The two other models extended these conclusions with some discrepancies among species related to their respective niches. Using a GIS, quantitative density maps were produced from EFHS models predictions. The respective areas of the different habitats were determined and their relative contributions (density × area) to the total amount of juveniles were calculated at the scale of stock management, in the Bay of Biscay. Shallow and muddy areas contributed to 70% of total juvenile relative abundance whereas only representing 16% of the coastal area, suggesting that they should be considered as essential habitats for these three flatfish species. For S. solea and P. platessa, wave exposure explained the propensity for sheltered areas, where concentration of juveniles was higher. Distribution maps of P. platessa and D. cuneata juveniles also revealed opposite spatial and temporal trends which were explained by the respective biogeographical distributions of these two species, close to their southern and northern limit respectively, and by their responses to hydroclimatic trends.

Cassini atmospheric chemistry mapper. Volume 1. Investigation and technical plan

NASA Technical Reports Server (NTRS)

Smith, William Hayden; Baines, Kevin Hays; Drossart, Pierre; Fegley, Bruce; Orton, Glenn; Noll, Keith; Reitsema, Harold; Bjoraker, Gordon L.

1990-01-01

The Cassini Atmospheric Chemistry Mapper (ACM) enables a broad range of atmospheric science investigations for Saturn and Titan by providing high spectral and spatial resolution mapping and occultation capabilities at 3 and 5 microns. ACM can directly address the major atmospheric science objectives for Saturn and for Titan, as defined by the Announcement of Opportunity, with pivotal diagnostic measurements not accessible to any other proposed Cassini instrument. ACM determines mixing ratios for atmospheric molecules from spectral line profiles for an important and extensive volume of the atmosphere of Saturn (and Jupiter). Spatial and vertical profiles of disequilibrium species abundances define Saturn's deep atmosphere, its chemistry, and its vertical transport phenomena. ACM spectral maps provide a unique means to interpret atmospheric conditions in the deep (approximately 1000 bar) atmosphere of Saturn. Deep chemistry and vertical transport is inferred from the vertical and horizontal distribution of a series of disequilibrium species. Solar occultations provide a method to bridge the altitude range in Saturn's (and Titan's) atmosphere that is not accessible to radio science, thermal infrared, and UV spectroscopy with temperature measurements to plus or minus 2K from the analysis of molecular line ratios and to attain an high sensitivity for low-abundance chemical species in the very large column densities that may be achieved during occultations for Saturn. For Titan, ACM solar occultations yield very well resolved (1/6 scale height) vertical mixing ratios column abundances for atmospheric molecular constituents. Occultations also provide for detecting abundant species very high in the upper atmosphere, while at greater depths, detecting the isotopes of C and O, constraining the production mechanisms, and/or sources for the above species. ACM measures the vertical and horizontal distribution of aerosols via their opacity at 3 microns and, particularly, at 5 microns. ACM recovers spatially-resolved atmospheric temperatures in Titan's troposphere via 3- and 5-microns spectral transitions. Together, the mixing ratio profiles and the aerosol distributions are utilized to investigate the photochemistry of the stratosphere and consequent formation processes for aerosols. Finally, ring opacities, observed during solar occultations and in reflected sunlight, provide a measurement of the particle size and distribution of ring material. ACM will be the first high spectral resolution mapping spectrometer on an outer planet mission for atmospheric studies while retaining a high resolution spatial mapping capability. ACM, thus, opens an entirely new range of orbital scientific studies of the origin, physio-chemical evolution and structure of the Saturn and Titan atmospheres. ACM provides high angular resolution spectral maps, viewing nadir and near-limb thermal radiation and reflected sunlight; sounds planetary limbs, spatially resolving vertical profiles to several atmospheric scale heights; and measures solar occultations, mapping both atmospheres and rings. ACM's high spectral and spatial resolution mapping capability is achieved with a simplified Fourier Transform spectrometer with a no-moving parts, physically compact design. ACM's simplicity guarantees an inherent stability essential for reliable performance throughout the lengthy Cassini Orbiter mission.

Spatial transferability of habitat suitability models of Nephrops norvegicus among fished areas in the Northeast Atlantic: sufficiently stable for marine resource conservation?

PubMed

Lauria, Valentina; Power, Anne Marie; Lordan, Colm; Weetman, Adrian; Johnson, Mark P

2015-01-01

Knowledge of the spatial distribution and habitat associations of species in relation to the environment is essential for their management and conservation. Habitat suitability models are useful in quantifying species-environment relationships and predicting species distribution patterns. Little is known, however, about the stability and performance of habitat suitability models when projected into new areas (spatial transferability) and how this can inform resource management. The aims of this study were to model habitat suitability of Norway lobster (Nephrops norvegicus) in five fished areas of the Northeast Atlantic (Aran ground, Irish Sea, Celtic Sea, Scotland Inshore and Fladen ground), and to test for spatial transferability of habitat models among multiple regions. Nephrops burrow density was modelled using generalised additive models (GAMs) with predictors selected from four environmental variables (depth, slope, sediment and rugosity). Models were evaluated and tested for spatial transferability among areas. The optimum models (lowest AICc) for different areas always included depth and sediment as predictors. Burrow densities were generally greater at depth and in finer sediments, but relationships for individual areas were sometimes more complex. Aside from an inclusion of depth and sediment, the optimum models differed between fished areas. When it came to tests of spatial transferability, however, most of the models were able to predict Nephrops density in other areas. Furthermore, transferability was not dependent on use of the optimum models since competing models were also able to achieve a similar level of transferability to new areas. A degree of decoupling between model 'fitting' performance and spatial transferability supports the use of simpler models when extrapolating habitat suitability maps to different areas. Differences in the form and performance of models from different areas may supply further information on the processes shaping species' distributions. Spatial transferability of habitat models can be used to support fishery management when the information is scarce but caution needs to be applied when making inference and a multi-area transferability analysis is preferable to bilateral comparisons between areas.

Climate and Human Pressure Constraints Co-Explain Regional Plant Invasion at Different Spatial Scales

PubMed Central

García-Baquero, Gonzalo; Caño, Lidia; Biurrun, Idoia; García-Mijangos, Itziar; Loidi, Javier; Herrera, Mercedes

2016-01-01

Alien species invasion represents a global threat to biodiversity and ecosystems. Explaining invasion patterns in terms of environmental constraints will help us to assess invasion risks and plan control strategies. We aim to identify plant invasion patterns in the Basque Country (Spain), and to determine the effects of climate and human pressure on that pattern. We modeled the regional distribution of 89 invasive plant species using two approaches. First, distance-based Moran’s eigenvector maps were used to partition variation in the invasive species richness, S, into spatial components at broad and fine scales; redundancy analysis was then used to explain those components on the basis of climate and human pressure descriptors. Second, we used generalized additive mixed modeling to fit species-specific responses to the same descriptors. Climate and human pressure descriptors have different effects on S at different spatial scales. Broad-scale spatially structured temperature and precipitation, and fine-scale spatially structured human population density and percentage of natural and semi-natural areas, explained altogether 38.7% of the total variance. The distribution of 84% of the individually tested species was related to either temperature, precipitation or both, and 68% was related to either population density or natural and semi-natural areas, displaying similar responses. The spatial pattern of the invasive species richness is strongly environmentally forced, mainly by climate factors. Since individual species responses were proved to be both similarly constrained in shape and explained variance by the same environmental factors, we conclude that the pattern of invasive species richness results from individual species’ environmental preferences. PMID:27741276

Whole brain analysis of postmortem density changes of grey and white matter on computed tomography by statistical parametric mapping.

PubMed

Nishiyama, Yuichi; Kanayama, Hidekazu; Mori, Hiroshi; Tada, Keiji; Yamamoto, Yasushi; Katsube, Takashi; Takeshita, Haruo; Kawakami, Kazunori; Kitagaki, Hajime

2017-06-01

This study examined the usefulness of statistical parametric mapping (SPM) for investigating postmortem changes on brain computed tomography (CT). This retrospective study included 128 patients (23 - 100 years old) without cerebral abnormalities who underwent unenhanced brain CT before and after death. The antemortem CT (AMCT) scans and postmortem CT (PMCT) scans were spatially normalized using our original brain CT template, and postmortem changes of CT values (in Hounsfield units; HU) were analysed by the SPM technique. Compared with AMCT scans, 58.6 % and 98.4 % of PMCT scans showed loss of the cerebral sulci and an unclear grey matter (GM)-white matter (WM) interface, respectively. SPM analysis revealed a significant decrease in cortical GM density within 70 min after death on PMCT scans, suggesting cytotoxic brain oedema. Furthermore, there was a significant increase in the density of the WM, lenticular nucleus and thalamus more than 120 min after death. The SPM technique demonstrated typical postmortem changes on brain CT scans, and revealed that the unclear GM-WM interface on early PMCT scans is caused by a rapid decrease in cortical GM density combined with a delayed increase in WM density. SPM may be useful for assessment of whole brain postmortem changes. • The original brain CT template achieved successful normalization of brain morphology. • Postmortem changes in the brain were independent of sex. • Cortical GM density decreased rapidly after death. • WM and deep GM densities increased following cortical GM density change. • SPM could be useful for assessment of whole brain postmortem changes.

The Cancer Cluster - An unbound collection of groups

NASA Technical Reports Server (NTRS)

Geller, M. J.; Beers, T. C.; Bothun, G. D.; Huchra, J. P.

1983-01-01

A surface density contour map of the Cancer Cluster derived from galaxy counts in the Zwicky catalog is presented. The contour map shows that the galaxy distribution is clumpy. When this spatial distribution is combined with nearly complete velocity information, the clumps stand out more clearly; there are significant differences in the mean velocities of the clumps which exceed their internal velocity dispersions. The Cancer Cluster is not a proper 'cluster' but is a collection of discrete groups, each with a velocity dispersion of approximately 300 km/s, separating from one another with the cosmological flow. The mass-to-light ratio for galaxies in the main concentration is approximately 320 solar masses/solar luminosities (H sub 0 = 100 km/s Mpc).

A comprehensive population dataset for Afghanistan constructed using GIS-based dasymetric mapping methods

USGS Publications Warehouse

Thompson, Allyson L.; Hubbard, Bernard E.

2014-01-01

This report summarizes the application of dasymetric methods for mapping the distribution of population throughout Afghanistan. Because Afghanistan's population has constantly changed through decades of war and conflict, existing vector and raster GIS datasets (such as point settlement densities and intensities of lights at night) do not adequately reflect the changes. The purposes of this report are (1) to provide historic population data at the provincial and district levels that can be used to chart population growth and migration trends within the country and (2) to provide baseline information that can be used for other types of spatial analyses of Afghanistan, such as resource and hazard assessments; infrastructure and capacity rebuilding; and assisting with international, regional, and local planning.

A method to estimate the effect of deformable image registration uncertainties on daily dose mapping

PubMed Central

Murphy, Martin J.; Salguero, Francisco J.; Siebers, Jeffrey V.; Staub, David; Vaman, Constantin

2012-01-01

Purpose: To develop a statistical sampling procedure for spatially-correlated uncertainties in deformable image registration and then use it to demonstrate their effect on daily dose mapping. Methods: Sequential daily CT studies are acquired to map anatomical variations prior to fractionated external beam radiotherapy. The CTs are deformably registered to the planning CT to obtain displacement vector fields (DVFs). The DVFs are used to accumulate the dose delivered each day onto the planning CT. Each DVF has spatially-correlated uncertainties associated with it. Principal components analysis (PCA) is applied to measured DVF error maps to produce decorrelated principal component modes of the errors. The modes are sampled independently and reconstructed to produce synthetic registration error maps. The synthetic error maps are convolved with dose mapped via deformable registration to model the resulting uncertainty in the dose mapping. The results are compared to the dose mapping uncertainty that would result from uncorrelated DVF errors that vary randomly from voxel to voxel. Results: The error sampling method is shown to produce synthetic DVF error maps that are statistically indistinguishable from the observed error maps. Spatially-correlated DVF uncertainties modeled by our procedure produce patterns of dose mapping error that are different from that due to randomly distributed uncertainties. Conclusions: Deformable image registration uncertainties have complex spatial distributions. The authors have developed and tested a method to decorrelate the spatial uncertainties and make statistical samples of highly correlated error maps. The sample error maps can be used to investigate the effect of DVF uncertainties on daily dose mapping via deformable image registration. An initial demonstration of this methodology shows that dose mapping uncertainties can be sensitive to spatial patterns in the DVF uncertainties. PMID:22320766

ALMA MEASUREMENTS OF THE HNC AND HC{sub 3}N DISTRIBUTIONS IN TITAN'S ATMOSPHERE

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

Cordiner, M. A.; Nixon, C. A.; Serigano, J.

2014-11-10

We present spectrally and spatially resolved maps of HNC and HC{sub 3}N emission from Titan's atmosphere, obtained using the Atacama Large Millimeter/submillimeter Array on 2013 November 17. These maps show anisotropic spatial distributions for both molecules, with resolved emission peaks in Titan's northern and southern hemispheres. The HC{sub 3}N maps indicate enhanced concentrations of this molecule over the poles, consistent with previous studies of Titan's photochemistry and atmospheric circulation. Differences between the spectrally integrated flux distributions of HNC and HC{sub 3}N show that these species are not co-spatial. The observed spectral line shapes are consistent with HNC being concentrated predominantlymore » in the mesosphere and above (at altitudes z ≳ 400 km), whereas HC{sub 3}N is abundant at a broader range of altitudes (z ≈ 70-600 km). From spatial variations in the HC{sub 3}N line profile, the locations of the HC{sub 3}N emission peaks are shown to be variable as a function of altitude. The peaks in the integrated emission from HNC and the line core (upper atmosphere) component of HC{sub 3}N (at z ≳ 300 km) are found to be asymmetric with respect to Titan's polar axis, indicating that the mesosphere may be more longitudinally variable than previously thought. The spatially integrated HNC and HC{sub 3}N spectra are modeled using the NEMESIS planetary atmosphere code and the resulting best-fitting disk-averaged vertical mixing ratio profiles are found to be in reasonable agreement with previous measurements for these species. Vertical column densities of the best-fitting gradient models for HNC and HC{sub 3}N are 1.9 × 10{sup 13} cm{sup –2} and 2.3 × 10{sup 14} cm{sup –2}, respectively.« less

SoilGrids1km — Global Soil Information Based on Automated Mapping

PubMed Central

Hengl, Tomislav; de Jesus, Jorge Mendes; MacMillan, Robert A.; Batjes, Niels H.; Heuvelink, Gerard B. M.; Ribeiro, Eloi; Samuel-Rosa, Alessandro; Kempen, Bas; Leenaars, Johan G. B.; Walsh, Markus G.; Gonzalez, Maria Ruiperez

2014-01-01

Background Soils are widely recognized as a non-renewable natural resource and as biophysical carbon sinks. As such, there is a growing requirement for global soil information. Although several global soil information systems already exist, these tend to suffer from inconsistencies and limited spatial detail. Methodology/Principal Findings We present SoilGrids1km — a global 3D soil information system at 1 km resolution — containing spatial predictions for a selection of soil properties (at six standard depths): soil organic carbon (g kg−1), soil pH, sand, silt and clay fractions (%), bulk density (kg m−3), cation-exchange capacity (cmol+/kg), coarse fragments (%), soil organic carbon stock (t ha−1), depth to bedrock (cm), World Reference Base soil groups, and USDA Soil Taxonomy suborders. Our predictions are based on global spatial prediction models which we fitted, per soil variable, using a compilation of major international soil profile databases (ca. 110,000 soil profiles), and a selection of ca. 75 global environmental covariates representing soil forming factors. Results of regression modeling indicate that the most useful covariates for modeling soils at the global scale are climatic and biomass indices (based on MODIS images), lithology, and taxonomic mapping units derived from conventional soil survey (Harmonized World Soil Database). Prediction accuracies assessed using 5–fold cross-validation were between 23–51%. Conclusions/Significance SoilGrids1km provide an initial set of examples of soil spatial data for input into global models at a resolution and consistency not previously available. Some of the main limitations of the current version of SoilGrids1km are: (1) weak relationships between soil properties/classes and explanatory variables due to scale mismatches, (2) difficulty to obtain covariates that capture soil forming factors, (3) low sampling density and spatial clustering of soil profile locations. However, as the SoilGrids system is highly automated and flexible, increasingly accurate predictions can be generated as new input data become available. SoilGrids1km are available for download via http://soilgrids.org under a Creative Commons Non Commercial license. PMID:25171179

Laser-diagnostic mapping of temperature and soot statistics in a 2-m diameter turbulent pool fire

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

Kearney, Sean P.; Grasser, Thomas W.

We present spatial profiles of temperature and soot-volume-fraction statistics from a sooting 2-m base diameter turbulent pool fire, burning a 10%-toluene / 90%-methanol fuel mixture. Dual-pump coherent anti-Stokes Raman scattering and laser-induced incandescence are utilized to obtain radial profiles of temperature and soot probability density functions (pdf) as well as estimates of temperature/soot joint statistics at three vertical heights above the surface of the methanol/toluene fuel pool. Results are presented both in the fuel vapor-dome region at ¼ base diameter and in the actively burning region at ½ and ¾ diameters above the fuel surface. The spatial evolution of themore » soot and temperature pdfs is discussed and profiles of the temperature and soot mean and rms statistics are provided. Joint temperature/soot statistics are presented as spatially resolved conditional averages across the fire plume, and in terms of a joint pdf obtained by including measurements from multiple spatial locations.« less

Laser-diagnostic mapping of temperature and soot statistics in a 2-m diameter turbulent pool fire

DOE PAGES

Kearney, Sean P.; Grasser, Thomas W.

2017-08-10

We present spatial profiles of temperature and soot-volume-fraction statistics from a sooting 2-m base diameter turbulent pool fire, burning a 10%-toluene / 90%-methanol fuel mixture. Dual-pump coherent anti-Stokes Raman scattering and laser-induced incandescence are utilized to obtain radial profiles of temperature and soot probability density functions (pdf) as well as estimates of temperature/soot joint statistics at three vertical heights above the surface of the methanol/toluene fuel pool. Results are presented both in the fuel vapor-dome region at ¼ base diameter and in the actively burning region at ½ and ¾ diameters above the fuel surface. The spatial evolution of themore » soot and temperature pdfs is discussed and profiles of the temperature and soot mean and rms statistics are provided. Joint temperature/soot statistics are presented as spatially resolved conditional averages across the fire plume, and in terms of a joint pdf obtained by including measurements from multiple spatial locations.« less

Relationships between human population density and burned area at continental and global scales.

PubMed

Bistinas, Ioannis; Oom, Duarte; Sá, Ana C L; Harrison, Sandy P; Prentice, I Colin; Pereira, José M C

2013-01-01

We explore the large spatial variation in the relationship between population density and burned area, using continental-scale Geographically Weighted Regression (GWR) based on 13 years of satellite-derived burned area maps from the global fire emissions database (GFED) and the human population density from the gridded population of the world (GPW 2005). Significant relationships are observed over 51.5% of the global land area, and the area affected varies from continent to continent: population density has a significant impact on fire over most of Asia and Africa but is important in explaining fire over < 22% of Europe and Australia. Increasing population density is associated with both increased and decreased in fire. The nature of the relationship depends on land-use: increasing population density is associated with increased burned are in rangelands but with decreased burned area in croplands. Overall, the relationship between population density and burned area is non-monotonic: burned area initially increases with population density and then decreases when population density exceeds a threshold. These thresholds vary regionally. Our study contributes to improved understanding of how human activities relate to burned area, and should contribute to a better estimate of atmospheric emissions from biomass burning.

Relationships between Human Population Density and Burned Area at Continental and Global Scales

PubMed Central

Bistinas, Ioannis; Oom, Duarte; Sá, Ana C. L.; Harrison, Sandy P.; Prentice, I. Colin; Pereira, José M. C.

2013-01-01

We explore the large spatial variation in the relationship between population density and burned area, using continental-scale Geographically Weighted Regression (GWR) based on 13 years of satellite-derived burned area maps from the global fire emissions database (GFED) and the human population density from the gridded population of the world (GPW 2005). Significant relationships are observed over 51.5% of the global land area, and the area affected varies from continent to continent: population density has a significant impact on fire over most of Asia and Africa but is important in explaining fire over < 22% of Europe and Australia. Increasing population density is associated with both increased and decreased in fire. The nature of the relationship depends on land-use: increasing population density is associated with increased burned are in rangelands but with decreased burned area in croplands. Overall, the relationship between population density and burned area is non-monotonic: burned area initially increases with population density and then decreases when population density exceeds a threshold. These thresholds vary regionally. Our study contributes to improved understanding of how human activities relate to burned area, and should contribute to a better estimate of atmospheric emissions from biomass burning. PMID:24358108

The SAMI Galaxy Survey: spatially resolving the main sequence of star formation

NASA Astrophysics Data System (ADS)

Medling, Anne M.; Cortese, Luca; Croom, Scott M.; Green, Andrew W.; Groves, Brent; Hampton, Elise; Ho, I.-Ting; Davies, Luke J. M.; Kewley, Lisa J.; Moffett, Amanda J.; Schaefer, Adam L.; Taylor, Edward; Zafar, Tayyaba; Bekki, Kenji; Bland-Hawthorn, Joss; Bloom, Jessica V.; Brough, Sarah; Bryant, Julia J.; Catinella, Barbara; Cecil, Gerald; Colless, Matthew; Couch, Warrick J.; Drinkwater, Michael J.; Driver, Simon P.; Federrath, Christoph; Foster, Caroline; Goldstein, Gregory; Goodwin, Michael; Hopkins, Andrew; Lawrence, J. S.; Leslie, Sarah K.; Lewis, Geraint F.; Lorente, Nuria P. F.; Owers, Matt S.; McDermid, Richard; Richards, Samuel N.; Sharp, Robert; Scott, Nicholas; Sweet, Sarah M.; Taranu, Dan S.; Tescari, Edoardo; Tonini, Chiara; van de Sande, Jesse; Walcher, C. Jakob; Wright, Angus

2018-04-01

We present the ˜800 star formation rate maps for the Sydney-AAO Multi-object Integral field spectrograph (SAMI) Galaxy Survey based on H α emission maps, corrected for dust attenuation via the Balmer decrement, that are included in the SAMI Public Data Release 1. We mask out spaxels contaminated by non-stellar emission using the [O III]/H β, [N II]/H α, [S II]/H α, and [O I]/H α line ratios. Using these maps, we examine the global and resolved star-forming main sequences of SAMI galaxies as a function of morphology, environmental density, and stellar mass. Galaxies further below the star-forming main sequence are more likely to have flatter star formation profiles. Early-type galaxies split into two populations with similar stellar masses and central stellar mass surface densities. The main-sequence population has centrally concentrated star formation similar to late-type galaxies, while galaxies >3σ below the main sequence show significantly reduced star formation most strikingly in the nuclear regions. The split populations support a two-step quenching mechanism, wherein halo mass first cuts off the gas supply and remaining gas continues to form stars until the local stellar mass surface density can stabilize the reduced remaining fuel against further star formation. Across all morphologies, galaxies in denser environments show a decreased specific star formation rate from the outside in, supporting an environmental cause for quenching, such as ram-pressure stripping or galaxy interactions.

Behavior Selection of Mobile Robot Based on Integration of Multimodal Information

NASA Astrophysics Data System (ADS)

Chen, Bin; Kaneko, Masahide

Recently, biologically inspired robots have been developed to acquire the capacity for directing visual attention to salient stimulus generated from the audiovisual environment. On purpose to realize this behavior, a general method is to calculate saliency maps to represent how much the external information attracts the robot's visual attention, where the audiovisual information and robot's motion status should be involved. In this paper, we represent a visual attention model where three modalities, that is, audio information, visual information and robot's motor status are considered, while the previous researches have not considered all of them. Firstly, we introduce a 2-D density map, on which the value denotes how much the robot pays attention to each spatial location. Then we model the attention density using a Bayesian network where the robot's motion statuses are involved. Secondly, the information from both of audio and visual modalities is integrated with the attention density map in integrate-fire neurons. The robot can direct its attention to the locations where the integrate-fire neurons are fired. Finally, the visual attention model is applied to make the robot select the visual information from the environment, and react to the content selected. Experimental results show that it is possible for robots to acquire the visual information related to their behaviors by using the attention model considering motion statuses. The robot can select its behaviors to adapt to the dynamic environment as well as to switch to another task according to the recognition results of visual attention.

A comparison of top-down and bottom-up approaches to benthic habitat mapping to inform offshore wind energy development

NASA Astrophysics Data System (ADS)

LaFrance, Monique; King, John W.; Oakley, Bryan A.; Pratt, Sheldon

2014-07-01

Recent interest in offshore renewable energy within the United States has amplified the need for marine spatial planning to direct management strategies and address competing user demands. To assist this effort in Rhode Island, benthic habitat classification maps were developed for two sites in offshore waters being considered for wind turbine installation. Maps characterizing and representing the distribution and extent of benthic habitats are valuable tools for improving understanding of ecosystem patterns and processes, and promoting scientifically-sound management decisions. This project presented the opportunity to conduct a comparison of the methodologies and resulting map outputs of two classification approaches, “top-down” and “bottom-up” in the two study areas. This comparison was undertaken to improve understanding of mapping methodologies and their applicability, including the bottom-up approach in offshore environments where data density tends to be lower, as well as to provide case studies for scientists and managers to consider for their own areas of interest. Such case studies can offer guidance for future work for assessing methodologies and translating them to other areas. The traditional top-down mapping approach identifies biological community patterns based on communities occurring within geologically defined habitat map units, under the concept that geologic environments contain distinct biological assemblages. Alternatively, the bottom-up approach aims to establish habitat map units centered on biological similarity and then uses statistics to identify relationships with associated environmental parameters and determine habitat boundaries. When applied to the two study areas, both mapping approaches produced habitat classes with distinct macrofaunal assemblages and each established statistically strong and significant biotic-abiotic relationships with geologic features, sediment characteristics, water depth, and/or habitat heterogeneity over various spatial scales. The approaches were also able to integrate various data at differing spatial resolutions. The classification outputs exhibited similar results, including the number of habitat classes generated, the number of species defining the classes, the level of distinction of the biological communities, and dominance by tube-building amphipods. These results indicate that both approaches are able to discern a comparable degree of habitat variability and produce cohesive macrofaunal assemblages. The mapping approaches identify broadly similar benthic habitats at the two study sites and methods were able to distinguish the differing levels of heterogeneity between them. The top-down approach to habitat classification was faster and simpler to accomplish with the data available in this study when compared to the bottom-up approach. Additionally, the top-down approach generated full-coverage habitat classes that are clearly delineated and can easily be interpreted by the map user, which is desirable from a management perspective for providing a more complete assessment of the areas of interest. However, a higher level of biological variability was noted in some of the habitat classes created, indicating that the biological communities present in this area are influenced by factors not captured in the broad-scale geological habitat units used in this approach. The bottom-up approach was valuable in its ability to more clearly define macrofaunal assemblages among habitats, discern finer-scale habitat characteristics, and directly assess the degree of macrofaunal assemblage variability captured by the environmental parameters. From a user perspective, the map is more complex, which may be perceived as a limitation, though likely reflects natural gradations in habitat structure and likely presents a more ecologically realistic portrayal of the study areas. Though more comprehensive, the bottom-up approach in this study was limited by the reliance on full-coverage data to create full-coverage habitat classes. Such classes could only be developed when sediment data was excluded, since this point-sample dataset could not be interpolated due to high spatial heterogeneity of the study areas. Given a higher density of bottom samples, this issue could be rectified. While the top-down approach was more appropriate for this study, both approaches were found to be suitable for mapping and classifying benthic habitats. In the United States, objectives for mapping and classification for renewable energy development have not been well established. Therefore, at this time, the best-suited approach primarily depends on mapping objectives, resource availability, data quality and coverage, and geographical location, as these factors impact the types of data included, the analyses and modeling that can be performed, and the biotic-abiotic relationships identified.

Potential corridors and barriers for plague spread in Central Asia.

PubMed

Wilschut, Liesbeth I; Addink, Elisabeth A; Heesterbeek, Hans; Heier, Lise; Laudisoit, Anne; Begon, Mike; Davis, Stephen; Dubyanskiy, Vladimir M; Burdelov, Leonid A; de Jong, Steven M

2013-10-31

Plague (Yersinia pestis infection) is a vector-borne disease which caused millions of human deaths in the Middle Ages. The hosts of plague are mostly rodents, and the disease is spread by the fleas that feed on them. Currently, the disease still circulates amongst sylvatic rodent populations all over the world, including great gerbil (Rhombomys opimus) populations in Central Asia. Great gerbils are social desert rodents that live in family groups in burrows, which are visible on satellite images. In great gerbil populations an abundance threshold exists, above which plague can spread causing epizootics. The spatial distribution of the host species is thought to influence the plague dynamics, such as the direction of plague spread, however no detailed analysis exists on the possible functional or structural corridors and barriers that are present in this population and landscape. This study aims to fill that gap. Three 20 by 20 km areas with known great gerbil burrow distributions were used to analyse the spatial distribution of the burrows. Object-based image analysis was used to map the landscape at several scales, and was linked to the burrow maps. A novel object-based method was developed - the mean neighbour absolute burrow density difference (MNABDD) - to identify the optimal scale and evaluate the efficacy of using landscape objects as opposed to square cells. Multiple regression using raster maps was used to identify the landscape-ecological variables that explain burrow density best. Functional corridors and barriers were mapped using burrow density thresholds. Cumulative resistance of the burrow distribution to potential disease spread was evaluated using cost distance analysis. A 46-year plague surveillance dataset was used to evaluate whether plague spread was radially symmetric. The burrow distribution was found to be non-random and negatively correlated with Greenness, especially in the floodplain areas. Corridors and barriers showed a mostly NWSE alignment, suggesting easier spreading along this axis. This was confirmed by the analysis of the plague data. Plague spread had a predominantly NWSE direction, which is likely due to the NWSE alignment of corridors and barriers in the burrow distribution and the landscape. This finding may improve predictions of plague in the future and emphasizes the importance of including landscape analysis in wildlife disease studies.

Potential corridors and barriers for plague spread in central Asia

PubMed Central

2013-01-01

Background Plague (Yersinia pestis infection) is a vector-borne disease which caused millions of human deaths in the Middle Ages. The hosts of plague are mostly rodents, and the disease is spread by the fleas that feed on them. Currently, the disease still circulates amongst sylvatic rodent populations all over the world, including great gerbil (Rhombomys opimus) populations in Central Asia. Great gerbils are social desert rodents that live in family groups in burrows, which are visible on satellite images. In great gerbil populations an abundance threshold exists, above which plague can spread causing epizootics. The spatial distribution of the host species is thought to influence the plague dynamics, such as the direction of plague spread, however no detailed analysis exists on the possible functional or structural corridors and barriers that are present in this population and landscape. This study aims to fill that gap. Methods Three 20 by 20 km areas with known great gerbil burrow distributions were used to analyse the spatial distribution of the burrows. Object-based image analysis was used to map the landscape at several scales, and was linked to the burrow maps. A novel object-based method was developed – the mean neighbour absolute burrow density difference (MNABDD) – to identify the optimal scale and evaluate the efficacy of using landscape objects as opposed to square cells. Multiple regression using raster maps was used to identify the landscape-ecological variables that explain burrow density best. Functional corridors and barriers were mapped using burrow density thresholds. Cumulative resistance of the burrow distribution to potential disease spread was evaluated using cost distance analysis. A 46-year plague surveillance dataset was used to evaluate whether plague spread was radially symmetric. Results The burrow distribution was found to be non-random and negatively correlated with Greenness, especially in the floodplain areas. Corridors and barriers showed a mostly NWSE alignment, suggesting easier spreading along this axis. This was confirmed by the analysis of the plague data. Conclusions Plague spread had a predominantly NWSE direction, which is likely due to the NWSE alignment of corridors and barriers in the burrow distribution and the landscape. This finding may improve predictions of plague in the future and emphasizes the importance of including landscape analysis in wildlife disease studies. PMID:24171709

MO-F-CAMPUS-J-04: Tissue Segmentation-Based MR Electron Density Mapping Method for MR-Only Radiation Treatment Planning of Brain

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

Yu, H; Lee, Y; Ruschin, M

2015-06-15

Purpose: Automatically derive electron density of tissues using MR images and generate a pseudo-CT for MR-only treatment planning of brain tumours. Methods: 20 stereotactic radiosurgery (SRS) patients’ T1-weighted MR images and CT images were retrospectively acquired. First, a semi-automated tissue segmentation algorithm was developed to differentiate tissues with similar MR intensities and large differences in electron densities. The method started with approximately 12 slices of manually contoured spatial regions containing sinuses and airways, then air, bone, brain, cerebrospinal fluid (CSF) and eyes were automatically segmented using edge detection and anatomical information including location, shape, tissue uniformity and relative intensity distribution.more » Next, soft tissues - muscle and fat were segmented based on their relative intensity histogram. Finally, intensities of voxels in each segmented tissue were mapped into their electron density range to generate pseudo-CT by linearly fitting their relative intensity histograms. Co-registered CT was used as a ground truth. The bone segmentations of pseudo-CT were compared with those of co-registered CT obtained by using a 300HU threshold. The average distances between voxels on external edges of the skull of pseudo-CT and CT in three axial, coronal and sagittal slices with the largest width of skull were calculated. The mean absolute electron density (in Hounsfield unit) difference of voxels in each segmented tissues was calculated. Results: The average of distances between voxels on external skull from pseudo-CT and CT were 0.6±1.1mm (mean±1SD). The mean absolute electron density differences for bone, brain, CSF, muscle and fat are 78±114 HU, and 21±8 HU, 14±29 HU, 57±37 HU, and 31±63 HU, respectively. Conclusion: The semi-automated MR electron density mapping technique was developed using T1-weighted MR images. The generated pseudo-CT is comparable to that of CT in terms of anatomical position of tissues and similarity of electron density assignment. This method can allow MR-only treatment planning.« less

High-resolution maps of real and illusory tactile activation in primary somatosensory cortex in individual monkeys with functional magnetic resonance imaging and optical imaging.

PubMed

Chen, Li M; Turner, Gregory H; Friedman, Robert M; Zhang, Na; Gore, John C; Roe, Anna W; Avison, Malcolm J

2007-08-22

Although blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) has been widely used to explore human brain function, questions remain regarding the ultimate spatial resolution of positive BOLD fMRI, and indeed the extent to which functional maps revealed by positive BOLD correlate spatially with maps obtained with other high-spatial-resolution mapping techniques commonly used in animals, such as optical imaging of intrinsic signal (OIS) and single-unit electrophysiology. Here, we demonstrate that the positive BOLD signal at 9.4T can reveal the fine topography of individual fingerpads in single-condition activation maps in nonhuman primates. These digit maps are similar to maps obtained from the same animal using intrinsic optical imaging. Furthermore, BOLD fMRI reliably resolved submillimeter spatial shifts in activation in area 3b previously identified with OIS (Chen et al., 2003) as neural correlates of the "funneling illusion." These data demonstrate that at high field, high-spatial-resolution topographic maps can be achieved using the positive BOLD signal, weakening previous notions regarding the spatial specificity of the positive BOLD signal.

King County Nearshore Habitat Mapping Data Report: Picnic Point to Shilshole Bay Marina

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

Woodruff, Dana L.; Farley, Paul J.; Borde, Amy B.

2000-12-31

The objective of this study is to provide accurate, georeferenced maps of benthic habitats to assist in the siting of a new wastewater treatment plant outfall and the assessment of habitats of endangered, threatened, and economically important species. The mapping was conducted in the fall of 1999 using two complementary techniques: side-scan sonar and underwater videography. Products derived from these techniques include geographic information system (GIS) compatible polygon data of substrate type and vegetation cover, including eelgrass and kelp. Additional GIS overlays include underwater video track line data of total macroalgae, selected macroalgal species, fish, and macroinvertebrates. The combined toolsmore » of geo-referenced side-scan sonar and underwater video is a powerful technique for assessing and mapping of nearshore habitat in Puget Sound. Side-scan sonar offers the ability to map eelgrass with high spatial accuracy and resolution, and provides information on patch size, shape, and coverage. It also provides information on substrate change and location of specific targets (e.g., piers, docks, pilings, large boulders, debris piles). The addition of underwater video is a complementary tool providing both groundtruthing for the sonar and additional information on macro fauna and flora. As a groundtruthing technique, the video was able to confirm differences between substrate types, as well as detect subtle spatial changes in substrate. It also verified information related to eelgrass, including the density classification categories and the type of substrate associated with eelgrass, which could not be determined easily with side- scan sonar. Video is also a powerful tool for mapping the location of macroalgae, (including kelp and Ulva), fish and macroinvertebrates. The ability to geo-locate these resources in their functional habitat provides an added layer of information and analytical potential.« less

A Method of Spatial Mapping and Reclassification for High-Spatial-Resolution Remote Sensing Image Classification

PubMed Central

Wang, Guizhou; Liu, Jianbo; He, Guojin

2013-01-01

This paper presents a new classification method for high-spatial-resolution remote sensing images based on a strategic mechanism of spatial mapping and reclassification. The proposed method includes four steps. First, the multispectral image is classified by a traditional pixel-based classification method (support vector machine). Second, the panchromatic image is subdivided by watershed segmentation. Third, the pixel-based multispectral image classification result is mapped to the panchromatic segmentation result based on a spatial mapping mechanism and the area dominant principle. During the mapping process, an area proportion threshold is set, and the regional property is defined as unclassified if the maximum area proportion does not surpass the threshold. Finally, unclassified regions are reclassified based on spectral information using the minimum distance to mean algorithm. Experimental results show that the classification method for high-spatial-resolution remote sensing images based on the spatial mapping mechanism and reclassification strategy can make use of both panchromatic and multispectral information, integrate the pixel- and object-based classification methods, and improve classification accuracy. PMID:24453808

Integration of Heterogenous Digital Surface Models

NASA Astrophysics Data System (ADS)

Boesch, R.; Ginzler, C.

2011-08-01

The application of extended digital surface models often reveals, that despite an acceptable global accuracy for a given dataset, the local accuracy of the model can vary in a wide range. For high resolution applications which cover the spatial extent of a whole country, this can be a major drawback. Within the Swiss National Forest Inventory (NFI), two digital surface models are available, one derived from LiDAR point data and the other from aerial images. Automatic photogrammetric image matching with ADS80 aerial infrared images with 25cm and 50cm resolution is used to generate a surface model (ADS-DSM) with 1m resolution covering whole switzerland (approx. 41000 km2). The spatially corresponding LiDAR dataset has a global point density of 0.5 points per m2 and is mainly used in applications as interpolated grid with 2m resolution (LiDAR-DSM). Although both surface models seem to offer a comparable accuracy from a global view, local analysis shows significant differences. Both datasets have been acquired over several years. Concerning LiDAR-DSM, different flight patterns and inconsistent quality control result in a significantly varying point density. The image acquisition of the ADS-DSM is also stretched over several years and the model generation is hampered by clouds, varying illumination and shadow effects. Nevertheless many classification and feature extraction applications requiring high resolution data depend on the local accuracy of the used surface model, therefore precise knowledge of the local data quality is essential. The commercial photogrammetric software NGATE (part of SOCET SET) generates the image based surface model (ADS-DSM) and delivers also a map with figures of merit (FOM) of the matching process for each calculated height pixel. The FOM-map contains matching codes like high slope, excessive shift or low correlation. For the generation of the LiDAR-DSM only first- and last-pulse data was available. Therefore only the point distribution can be used to derive a local accuracy measure. For the calculation of a robust point distribution measure, a constrained triangulation of local points (within an area of 100m2) has been implemented using the Open Source project CGAL. The area of each triangle is a measure for the spatial distribution of raw points in this local area. Combining the FOM-map with the local evaluation of LiDAR points allows an appropriate local accuracy evaluation of both surface models. The currently implemented strategy ("partial replacement") uses the hypothesis, that the ADS-DSM is superior due to its better global accuracy of 1m. If the local analysis of the FOM-map within the 100m2 area shows significant matching errors, the corresponding area of the triangulated LiDAR points is analyzed. If the point density and distribution is sufficient, the LiDAR-DSM will be used in favor of the ADS-DSM at this location. If the local triangulation reflects low point density or the variance of triangle areas exceeds a threshold, the investigated location will be marked as NODATA area. In a future implementation ("anisotropic fusion") an anisotropic inverse distance weighting (IDW) will be used, which merges both surface models in the point data space by using FOM-map and local triangulation to derive a quality weight for each of the interpolation points. The "partial replacement" implementation and the "fusion" prototype for the anisotropic IDW make use of the Open Source projects CGAL (Computational Geometry Algorithms Library), GDAL (Geospatial Data Abstraction Library) and OpenCV (Open Source Computer Vision).

Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

NASA Astrophysics Data System (ADS)

Belianinov, Alex; Ganesh, Panchapakesan; Lin, Wenzhi; Sales, Brian C.; Sefat, Athena S.; Jesse, Stephen; Pan, Minghu; Kalinin, Sergei V.

2014-12-01

Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe0.55Se0.45 (Tc = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe1-xSex structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified by their electronic signature and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces.

Spatial modeling of cutaneous leishmaniasis in the Andean region of Colombia.

PubMed

Pérez-Flórez, Mauricio; Ocampo, Clara Beatriz; Valderrama-Ardila, Carlos; Alexander, Neal

2016-06-27

The objective of this research was to identify environmental risk factors for cutaneous leishmaniasis (CL) in Colombia and map high-risk municipalities. The study area was the Colombian Andean region, comprising 715 rural and urban municipalities. We used 10 years of CL surveillance: 2000-2009. We used spatial-temporal analysis - conditional autoregressive Poisson random effects modelling - in a Bayesian framework to model the dependence of municipality-level incidence on land use, climate, elevation and population density. Bivariable spatial analysis identified rainforests, forests and secondary vegetation, temperature, and annual precipitation as positively associated with CL incidence. By contrast, livestock agroecosystems and temperature seasonality were negatively associated. Multivariable analysis identified land use - rainforests and agro-livestock - and climate - temperature, rainfall and temperature seasonality - as best predictors of CL. We conclude that climate and land use can be used to identify areas at high risk of CL and that this approach is potentially applicable elsewhere in Latin America.

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.

Space-based Swath Imaging Laser Altimeter for Cryospheric Topographic and Surface Property Mapping

NASA Technical Reports Server (NTRS)

Abshire, James; Harding, David; Shuman, Chris; Sun, Xiaoli; Dabney, Phil; Krainak, Michael; Scambos, Ted

2005-01-01

Uncertainties in the response of the Greenland and Antarctic polar ice sheets to global climatic change inspired the development of ICESat/GLAS as part of NASA's Earth Observing System. ICESat's primary purpose is the measurement of ice sheet surface elevation profiles with sufficient accuracy, spatial density, and temporal coverage so that elevation changes can be derived with an accuracy of <1.5 cm/year for averages of measurements over the ice sheets with areas of 100 x 100 km. The primary means to achieve this elevation change detection is spatial averaging of elevation differences at cross-overs between ascending and descending profiles in areas of low ice surface slope. Additional information is included in the original extended abstract.

Using Landscape Analysis to Test Hypotheses about Drivers of Tick Abundance and Infection Prevalence with Borrelia burgdorferi.

PubMed

Ferrell, A Michelle; Brinkerhoff, R Jory

2018-04-12

Patterns of vector-borne disease risk are changing globally in space and time and elevated disease risk of vector-borne infection can be driven by anthropogenic modification of the environment. Incidence of Lyme disease, caused by the bacterium Borrelia burgdorferi sensu stricto, has risen in a number of locations in North America and this increase may be driven by spatially or numerically expanding populations of the primary tick vector, Ixodes scapularis . We used a model selection approach to identify habitat fragmentation and land-use/land cover variables to test the hypothesis that the amount and configuration of forest cover at spatial scales relevant to deer, the primary hosts of adult ticks, would be the predominant determinants of tick abundance. We expected that land cover heterogeneity and amount of forest edge, a habitat thought to facilitate deer foraging and survival, would be the strongest driver of tick density and that larger spatial scales (5-10 km) would be more important than smaller scales (1 km). We generated metrics of deciduous and mixed forest fragmentation using Fragstats 4.4 implemented in ArcMap 10.3 and found, after adjusting for multicollinearity, that total forest edge within a 5 km buffer had a significant negative effect on tick density and that the proportion of forested land cover within a 10 km buffer was positively associated with density of I. scapularis nymphs. None of the 1 km fragmentation metrics were found to significantly improve the fit of the model. Elevation, previously associated with increased density of I. scapularis nymphs in Virginia, while significantly predictive in univariate analysis, was not an important driver of nymph density relative to fragmentation metrics. Our results suggest that amount of forest cover (i.e., lack of fragmentation) is the most important driver of I. scapularis density in our study system.

A new gridded on-road CO2 emissions inventory for the United States, 1980-2011

NASA Astrophysics Data System (ADS)

Gately, C.; Hutyra, L.; Sue Wing, I.

2013-12-01

On-road transportation is responsible for 28% of all U.S. fossil fuel CO2 emissions. However, mapping vehicle emissions at regional scales is challenging due to data limitations. Existing emission inventories have used spatial proxies such as population and road density to downscale national or state level data, which may introduce errors where the proxy variables and actual emissions are weakly correlated. We have developed a national on-road emissions inventory product based on roadway-level traffic data obtained from the Highway Performance Monitoring System. We produce annual estimates of on-road CO2 emissions at a 1km spatial resolution for the contiguous United States for the years 1980 through 2011. For the year 2011 we also produce an hourly emissions product at the 1km scale using hourly traffic volumes from hundreds of automated traffic counters across the country. National on-road emissions rose at roughly 2% per year from 1980 to 2006, with emissions peaking at 1.71 Tg CO2 in 2007. However, while national emissions have declined 6% since the peak, we observe considerable regional variation in emissions trends post-2007. While many states show stable or declining on-road emissions, several states and metropolitan areas in the Midwest, mountain west and south had emissions increases of 3-10% from 2008 to 2011. Our emissions estimates are consistent with state-reported totals of gasoline and diesel fuel consumption. This is in contrast to on-road CO2 emissions estimated by the Emissions Database of Global Atmospheric Research (EDGAR), which we show to be inconsistent in matching on-road emissions to published fuel consumption at the scale of U.S. states, due to the non-linear relationships between emissions and EDGAR's chosen spatial proxies at these scales. Since our emissions estimates were generated independent of population density and other demographic data, we were able to conduct a panel regression analysis to estimate the relationship between these variables and on-road CO2 at various spatial scales. In the case of Massachusetts we find a non-linear relationship between emissions and population density indicating that increasing density resulted in increased emissions when density is less than 2000 persons-km-2. These results highlight the value of using an emissions inventory with high spatial and temporal resolution. At coarser spatial scales, much of the variation in population density and on-road emissions between towns is lost due to aggregation. The high spatial resolution and broad temporal scope of our CO2 estimates provides a basis for analyses to support emissions monitoring, verification and mitigation policies at regional, state and local scale.

Preschool children use space, rather than counting, to infer the numerical magnitude of digits: Evidence for a spatial mapping principle.

PubMed

Sella, Francesco; Berteletti, Ilaria; Lucangeli, Daniela; Zorzi, Marco

2017-01-01

A milestone in numerical development is the acquisition of counting principles which allow children to exactly determine the numerosity of a given set. Moreover, a canonical left-to-right spatial layout for representing numbers also emerges during preschool. These foundational aspects of numerical competence have been extensively studied, but there is sparse knowledge about the interplay between the acquisition of the cardinality principle and spatial mapping of numbers in early numerical development. The present study investigated how these skills concurrently develop before formal schooling. Preschool children were classified according to their performance in Give-a-Number and Number-to-position tasks. Experiment 1 revealed three qualitatively different groups: (i) children who did not master the cardinality principle and lacked any consistent spatial mapping for digits, (ii) children who mastered the cardinality principle and yet failed in spatial mapping, and (iii) children who mastered the cardinality principle and displayed consistent spatial mapping. This suggests that mastery of the cardinality principle does not entail the emergence of spatial mapping. Experiment 2 confirmed the presence of these three developmental stages and investigated their relation with a digit comparison task. Crucially, only children who displayed a consistent spatial mapping of numbers showed the ability to compare digits by numerical magnitude. A congruent (i.e., numerically ordered) positioning of numbers onto a visual line as well as the concept that moving rightwards (in Western cultures) conveys an increase in numerical magnitude mark the mastery of a spatial mapping principle. Children seem to rely on this spatial organization to achieve a full understanding of the magnitude relations between digits. Copyright © 2016 Elsevier B.V. All rights reserved.

Spatial Supermarket Redlining and Neighborhood Vulnerability: A Case Study of Hartford, Connecticut

PubMed Central

Zhang, Mengyao

2015-01-01

The disinclination of chain supermarkets to locate or pull out existing stores from impoverished neighborhoods is termed as “supermarket redlining”. This paper attempts to map and understand the spatial effects of potential supermarket redlining on food vulnerability in urban disadvantaged neighborhoods of Hartford, Connecticut. Using a combination of statistical and spatial analysis functions, we first, built a Supermarket Redlining Index (SuRI) from five indicators such as sales volume, employee count, accepts food coupons from federally assisted programs, and size and population density of the service area to rank supermarkets in the order of their importance. Second, to understand the effect of redlining, a Supermarket Redlining Impact Model (SuRIM) was built with eleven indicators describing both the socioeconomic and food access vulnerabilities. The interaction of these vulnerabilities would identify the final outcome: neighborhoods where the impact of supermarket redlining would be critical. Results mapped critical areas in the inner-city of Hartford where if a nearby supermarket closes or relocates to a suburb with limited mitigation efforts to gill the grocery gap, a large number of minority, poor, and disadvantaged residents will experience difficulties to access healthy food leading to food insecurity or perhaps a food desert. We also suggest mitigation efforts to reduce the impact of large supermarket closures. PMID:27034615

Spatial Supermarket Redlining and Neighborhood Vulnerability: A Case Study of Hartford, Connecticut.

PubMed

Zhang, Mengyao; Debarchana, Ghosh

2016-02-01

The disinclination of chain supermarkets to locate or pull out existing stores from impoverished neighborhoods is termed as "supermarket redlining". This paper attempts to map and understand the spatial effects of potential supermarket redlining on food vulnerability in urban disadvantaged neighborhoods of Hartford, Connecticut. Using a combination of statistical and spatial analysis functions, we first, built a Supermarket Redlining Index (SuRI) from five indicators such as sales volume, employee count, accepts food coupons from federally assisted programs, and size and population density of the service area to rank supermarkets in the order of their importance. Second, to understand the effect of redlining, a Supermarket Redlining Impact Model (SuRIM) was built with eleven indicators describing both the socioeconomic and food access vulnerabilities. The interaction of these vulnerabilities would identify the final outcome: neighborhoods where the impact of supermarket redlining would be critical. Results mapped critical areas in the inner-city of Hartford where if a nearby supermarket closes or relocates to a suburb with limited mitigation efforts to gill the grocery gap, a large number of minority, poor, and disadvantaged residents will experience difficulties to access healthy food leading to food insecurity or perhaps a food desert. We also suggest mitigation efforts to reduce the impact of large supermarket closures.

Structured illumination diffuse optical tomography for noninvasive functional neuroimaging in mice.

PubMed

Reisman, Matthew D; Markow, Zachary E; Bauer, Adam Q; Culver, Joseph P

2017-04-01

Optical intrinsic signal (OIS) imaging has been a powerful tool for capturing functional brain hemodynamics in rodents. Recent wide field-of-view implementations of OIS have provided efficient maps of functional connectivity from spontaneous brain activity in mice. However, OIS requires scalp retraction and is limited to superficial cortical tissues. Diffuse optical tomography (DOT) techniques provide noninvasive imaging, but previous DOT systems for rodent neuroimaging have been limited either by sparse spatial sampling or by slow speed. Here, we develop a DOT system with asymmetric source-detector sampling that combines the high-density spatial sampling (0.4 mm) detection of a scientific complementary metal-oxide-semiconductor camera with the rapid (2 Hz) imaging of a few ([Formula: see text]) structured illumination (SI) patterns. Analysis techniques are developed to take advantage of the system's flexibility and optimize trade-offs among spatial sampling, imaging speed, and signal-to-noise ratio. An effective source-detector separation for the SI patterns was developed and compared with light intensity for a quantitative assessment of data quality. The light fall-off versus effective distance was also used for in situ empirical optimization of our light model. We demonstrated the feasibility of this technique by noninvasively mapping the functional response in the somatosensory cortex of the mouse following electrical stimulation of the forepaw.

Are fractal dimensions of the spatial distribution of mineral deposits meaningful?

USGS Publications Warehouse

Raines, G.L.

2008-01-01

It has been proposed that the spatial distribution of mineral deposits is bifractal. An implication of this property is that the number of deposits in a permissive area is a function of the shape of the area. This is because the fractal density functions of deposits are dependent on the distance from known deposits. A long thin permissive area with most of the deposits in one end, such as the Alaskan porphyry permissive area, has a major portion of the area far from known deposits and consequently a low density of deposits associated with most of the permissive area. On the other hand, a more equi-dimensioned permissive area, such as the Arizona porphyry permissive area, has a more uniform density of deposits. Another implication of the fractal distribution is that the Poisson assumption typically used for estimating deposit numbers is invalid. Based on datasets of mineral deposits classified by type as inputs, the distributions of many different deposit types are found to have characteristically two fractal dimensions over separate non-overlapping spatial scales in the range of 5-1000 km. In particular, one typically observes a local dimension at spatial scales less than 30-60 km, and a regional dimension at larger spatial scales. The deposit type, geologic setting, and sample size influence the fractal dimensions. The consequence of the geologic setting can be diminished by using deposits classified by type. The crossover point between the two fractal domains is proportional to the median size of the deposit type. A plot of the crossover points for porphyry copper deposits from different geologic domains against median deposit sizes defines linear relationships and identifies regions that are significantly underexplored. Plots of the fractal dimension can also be used to define density functions from which the number of undiscovered deposits can be estimated. This density function is only dependent on the distribution of deposits and is independent of the definition of the permissive area. Density functions for porphyry copper deposits appear to be significantly different for regions in the Andes, Mexico, United States, and western Canada. Consequently, depending on which regional density function is used, quite different estimates of numbers of undiscovered deposits can be obtained. These fractal properties suggest that geologic studies based on mapping at scales of 1:24,000 to 1:100,000 may not recognize processes that are important in the formation of mineral deposits at scales larger than the crossover points at 30-60 km. ?? 2008 International Association for Mathematical Geology.

Expression and Organization of Geographic Spatial Relations Based on Topic Maps

NASA Astrophysics Data System (ADS)

Liang, H. J.; Wang, H.; Cui, T. J.; Guo, J. F.

2017-09-01

Spatial Relation is one of the important components of Geographical Information Science and Spatial Database. There have been lots of researches on Spatial Relation and many different spatial relations have been proposed. The relationships among these spatial relations such as hierarchy and so on are complex and this brings some difficulties to the applications and teaching of these spatial relations. This paper summaries some common spatial relations, extracts the topic types, association types, resource types of these spatial relations using the technology of Topic Maps, and builds many different relationships among these spatial relations. Finally, this paper utilizes Java and Ontopia to build a topic map among these common spatial relations, forms a complex knowledge network of spatial relations, and realizes the effective management and retrieval of spatial relations.

Mapping the Frozen Void

NASA Astrophysics Data System (ADS)

Suutarinen, Aleksi; Fraser, Helen

2013-07-01

Reactions on the surfaces of dust grains play a vital role in the overall chemistry of interstellar matter. These grains become covered by icy layers, which are the largest molecular reservoir in the interstellar medium. Given this, it is surprising that the effect ice has on the overall chain of reactions is poorly characterized. One step on the path of gaining better understanding here is to develop methods of figuring out how much ice is present in these clouds, the links between ice components, and synergy between the ices and gas phase molecules. We do this by examining the absorption spectra of ices on lines of sight towards several stars behind clouds of interstellar matter. From these we can reconstruct spatial maps of the ice distribution on scales of as little as 1000 AU, as a test of the chemical variation within a cloud. By overlapping the ice data with other maps of the same region (gas emission, temperature, density etc) we create combined maps to reveal the astrochemistry of star-forming regions and pre-stellar cores. In this poster we present the continuing results of our ice mapping programme, using data from the AKARI satellite, specifically in slitless spectroscopy observations in the NIR. In this region the key ice features encompass H2O, CO and CO2. The maps illustrate the power of our dedicated AKARI data reduction pipeline, and the novelty of our observing programme. We also detail the next steps' in our ice mapping research. The method is being expanded to include the full 10'x10' AKARI field of view, taking account of image distortion induced by the dispersing optics. These maps are then combined with exiting gas-phase observations and SCUBA maps. The latest attempts at this are shown here. What is clear already is that it is difficult to predict ice abundances from factors such as extinction or gas density alone, and that ice formation and evolution can vary hugely over even very small astronomical scales.

Using Open data in analyzing urban growth: urban density and change detection

NASA Astrophysics Data System (ADS)

murgante, Beniamino; Nolè, Gabriele; Lasaponara, Rosa; Lanorte, Antonio

2013-04-01

In recent years a great attention has been paid to the evolution and the use of spatial data. Internet technologies accelerated such a process, allowing more direct access to spatial information. It is estimated that more than 600 million people have been connected to the Internet at least once to display maps on the web. Consequently, there is an irreversible process which considers geographical dimension as a fundamental attribute for the management of information flows. Furthermore, the great activity produced by open data movement leads to an easier and clearer access to geospatial information. This trend concerns, in a less evident way, also satellite data, which are increasingly accessible through the web. Spatial planning, geography and other regional sciences find it difficult to build knowledge related to spatial transformation. These problems can be significantly reduced due to a large data availability, producing significant opportunities to capture knowledge useful for a better territorial governance. This study has been developed in a heavily anthropized area in southern Italy, Apulia region, using free spatial data and free multispectral and multitemporal satellite data (Apulia region was one of the first regions in Italy to adopt open data policies). The analysis concerns urban growth, which, in recent decades, showed a rapid increase. In a first step the evolution in time and change detection of urban areas has been analyzed paying particular attention to soil consumption. In the second step Kernel Density has been adopted in order to assess development pressures. KDE (Kernel Density Estimation) function is a technique that provides the density of a phenomenon based on point data. A mobile three dimensional surface has been produced from a set of points distributed over a region of space, which weighs the events within its sphere of influence, depending on their distance from the point from which intensity is estimated. It produces, considering as input point data (vector), a density continuous raster as an output. In this case, the intensity of phenomenon will be given by buildings volume. References • Bailey T. C., Gatrell A. C. (1995). Interactive spatial data analysis. Prentice Hall. • Danese M., Lazzari M., Murgante B. (2009). "Geostatistics in Historical Macroseismic Data Analysis" Transactions on Computational Sciences VI, LNCS Vol. 5730, pp. 324-341, Springer-Verlag, Berlin ISSN: 1611-3349, doi:10.1007/978-3-642-10649-1_19 • Nolè G., Danese M., Murgante B., Lasaponara R., Lanorte, A., (2012) "Using Spatial Autocorrelation Techniques and Multi-temporal Satellite Data for Analyzing Urban Sprawl" Lecture Notes in Computer Science vol. 7335, pp. 512-527. Springer-Verlag, Berlin. ISSN: 0302-9743, doi: 10.1007/978-3-642-31137-6_39 • Murgante, B., Las Casas, G., Danese, M., (2012), "Analyzing Neighbourhoods Suitable for Urban Renewal Programs with Autocorrelation Techniques" In Burian J. (Eds.) "Advances in Spatial Planning" InTech — Open Access DOI: 10.5772/33747 ISBN:978-953-51-0377-6 • Lanorte, A., Danese M., Lasaponara R., Murgante B. (2011) "Multiscale mapping of burn area and severity using multisensor satellite data and spatial autocorrelation analysis" International Journal of Applied Earth Observation and Geoinformation, Elsevier, doi:10.1016/j.jag.2011.09.005 • O'Sullivan D., Unwin D., (2002). Geographic Information Analysis. John Wiley & Sons • Yang, X., Lo, C. P.: Using a time series of satellite imagery to detect land use and land cover changes in the Atlanta, Georgia metropolitan area. Int. J. Rem. Sensing 23, pp. 1775--1798 (2002) • Yuan, F., Sawaya, K.,.Loeffelholz, B. C., Bauer, M. E.: Land cover classification and change analysis of the Twin Cities (Minnesota) Metropolitan Area by multitemporal Landsat remote sensing. Rem. Sensing Environ. 98, pp. 317--328 (2005)

Functional connectivity density mapping: comparing multiband and conventional EPI protocols.

PubMed

Cohen, Alexander D; Tomasi, Dardo; Shokri-Kojori, Ehsan; Nencka, Andrew S; Wang, Yang

2018-06-01

Functional connectivity density mapping (FCDM) is a newly developed data-driven technique that quantifies the number of local and global functional connections for each voxel in the brain. In this study, we evaluated reproducibility, sensitivity, and specificity of both local functional connectivity density (lFCD) and global functional connectivity density (gFCD). We compared these metrics using the human connectome project (HCP) compatible high-resolution (2 mm isotropic, TR = 0.8 s) multiband (MB), and more typical, lower resolution (3.5 mm isotropic, TR = 2.0 s) single-band (SB) resting state functional MRI (rs-fMRI) acquisitions. Furthermore, in order to be more clinically feasible, only rs-fMRI scans that lasted seven minutes were tested. Subjects were scanned twice within a two-week span. We found sensitivity and specificity increased and reproducibility either increased or did not change for the MB compared to the SB acquisitions. The MB scans also showed improved gray matter/white matter contrast compared to the SB scans. The lFCD and gFCD patterns were similar across MB and SB scans and confined predominantly to gray matter. We also observed a strong spatial correlation of FCD between MB and SB scans indicating the two acquisitions provide similar information. These findings indicate high-resolution MB acquisitions improve the quality of FCD data, and seven minute rs-fMRI scan can provide robust FCD measurements.

Features of Electron Density Distribution in Delafossite Cualo2

NASA Astrophysics Data System (ADS)

Pogoreltsev, A. I.; Schmidt, S. V.; Gavrilenko, A. N.; Shulgin, D. A.; Korzun, B. V.; Matukhin, V. L.

2015-07-01

We have used pulsed 63,65Cu nuclear quadrupole resonance at room temperature to study the semiconductor compound CuAlO2 with a delafossite crystal structure, and we have determined the quadrupole frequency νQ = 28.12 MHz and the asymmetry parameter η ~ 0, which we used to study the features of the electron density distribution in the vicinity of the quadrupolar nucleus. In order to take into account the influence of correlation effects on the electric field gradient, we carried out ab initio calculations within the density functional theory (DFT) approximation using a set of correlation functionals VWN1RPA, VWN5, PW91LDA, CPW91, and B3LYP1. We mapped the electron density distribution in the vicinity of the quadrupolar copper nucleus for the Cu7Al6o{14/- 1} cluster and we calculated the size of the LUMO-HOMO gap, Δ ~ 3.33 eV. We established the anisotropy of the spatial electron density distribution. Based on analysis of the electron density distribution obtained, we suggest that the bond in CuAlO2 is not purely covalent.

Variation of the fractal dimension anisotropy of two major Cenozoic normal fault systems over space and time around the Snake River Plain, Idaho and SW Montana

NASA Astrophysics Data System (ADS)

Davarpanah, A.; Babaie, H. A.

2012-12-01

The interaction of the thermally induced stress field of the Yellowstone hotspot (YHS) with existing Basin and Range (BR) fault blocks, over the past 17 m.y., has produced a new, spatially and temporally variable system of normal faults around the Snake River Plain (SRP) in Idaho and Wyoming-Montana area. Data about the trace of these new cross faults (CF) and older BR normal faults were acquired from a combination of satellite imageries, DEM, and USGS geological maps and databases at scales of 1:24,000, 1:100,000, 1:250,000, 1:1000, 000, and 1:2,500, 000, and classified based on their azimuth in ArcGIS 10. The box-counting fractal dimension (Db) of the BR fault traces, determined applying the Benoit software, and the anisotropy intensity (ellipticity) of the fractal dimensions, measured with the modified Cantor dust method applying the AMOCADO software, were measured in two large spatial domains (I and II). The Db and anisotropy of the cross faults were studied in five temporal domains (T1-T5) classified based on the geologic age of successive eruptive centers (12 Ma to recent) of the YHS along the eastern SRP. The fractal anisotropy of the CF system in each temporal domain was also spatially determined in the southern part (domain S1), central part (domain S2), and northern part (domain S3) of the SRP. Line (fault trace) density maps for the BR and CF polylines reveal a higher linear density (trace length per unit area) for the BR traces in the spatial domain I, and a higher linear density of the CF traces around the present Yellowstone National Park (S1T5) where most of the seismically active faults are located. Our spatio-temporal analysis reveals that the fractal dimension of the BR system in domain I (Db=1.423) is greater than that in domain II (Db=1.307). It also shows that the anisotropy of the fractal dimension in domain I is less eccentric (axial ratio: 1.242) than that in domain II (1.355), probably reflecting the greater variation in the trend of the BR system in domain I. The CF system in the S1T5 domain has the highest fractal dimension (Db=1.37) and the lowest anisotropy eccentricity (1.23) among the five temporal domains. These values positively correlate with the observed maxima on the fault trace density maps. The major axis of the anisotropy ellipses is consistently perpendicular to the average trend of the normal fault system in each domain, and therefore approximates the orientation of extension for normal faulting in each domain. This fact gives a NE-SW and NW-SE extension direction for the BR system in domains I and II, respectively. The observed NE-SW orientation of the major axes of the anisotropy ellipses in the youngest T4 and T5 temporal domains, oriented perpendicular to the mean trend of the normal faults in the these domains, suggests extension along the NE-SW direction for cross faulting in these areas. The spatial trajectories (form lines) of the minor axes of the anisotropy ellipses, and the mean trend of fault traces in the T4 and T5 temporal domains, define a large parabolic pattern about the axis of the eastern SRP, with its apex at the Yellowstone plateau.

The performance of approximations of farm contiguity compared to contiguity defined using detailed geographical information in two sample areas in Scotland: implications for foot-and-mouth disease modelling.

PubMed

Flood, Jessica S; Porphyre, Thibaud; Tildesley, Michael J; Woolhouse, Mark E J

2013-10-08

When modelling infectious diseases, accurately capturing the pattern of dissemination through space is key to providing optimal recommendations for control. Mathematical models of disease spread in livestock, such as for foot-and-mouth disease (FMD), have done this by incorporating a transmission kernel which describes the decay in transmission rate with increasing Euclidean distance from an infected premises (IP). However, this assumes a homogenous landscape, and is based on the distance between point locations of farms. Indeed, underlying the spatial pattern of spread are the contact networks involved in transmission. Accordingly, area-weighted tessellation around farm point locations has been used to approximate field-contiguity and simulate the effect of contiguous premises (CP) culling for FMD. Here, geographic data were used to determine contiguity based on distance between premises' fields and presence of landscape features for two sample areas in Scotland. Sensitivity, positive predictive value, and the True Skill Statistic (TSS) were calculated to determine how point distance measures and area-weighted tessellation compared to the 'gold standard' of the map-based measures in identifying CPs. In addition, the mean degree and density of the different contact networks were calculated. Utilising point distances <1 km and <5 km as a measure for contiguity resulted in poor discrimination between map-based CPs/non-CPs (TSS 0.279-0.344 and 0.385-0.400, respectively). Point distance <1 km missed a high proportion of map-based CPs; <5 km point distance picked up a high proportion of map-based non-CPs as CPs. Area-weighted tessellation performed best, with reasonable discrimination between map-based CPs/non-CPs (TSS 0.617-0.737) and comparable mean degree and density. Landscape features altered network properties considerably when taken into account. The farming landscape is not homogeneous. Basing contiguity on geographic locations of field boundaries and including landscape features known to affect transmission into FMD models are likely to improve individual farm-level accuracy of spatial predictions in the event of future outbreaks. If a substantial proportion of FMD transmission events are by contiguous spread, and CPs should be assigned an elevated relative transmission rate, the shape of the kernel could be significantly altered since ability to discriminate between map-based CPs and non-CPs is different over different Euclidean distances.

Accuracy assessment of a mobile terrestrial lidar survey at Padre Island National Seashore

USGS Publications Warehouse

Lim, Samsung; Thatcher, Cindy A.; Brock, John C.; Kimbrow, Dustin R.; Danielson, Jeffrey J.; Reynolds, B.J.

2013-01-01

The higher point density and mobility of terrestrial laser scanning (light detection and ranging (lidar)) is desired when extremely detailed elevation data are needed for mapping vertically orientated complex features such as levees, dunes, and cliffs, or when highly accurate data are needed for monitoring geomorphic changes. Mobile terrestrial lidar scanners have the capability for rapid data collection on a larger spatial scale compared with tripod-based terrestrial lidar, but few studies have examined the accuracy of this relatively new mapping technology. For this reason, we conducted a field test at Padre Island National Seashore of a mobile lidar scanner mounted on a sport utility vehicle and integrated with a position and orientation system. The purpose of the study was to assess the vertical and horizontal accuracy of data collected by the mobile terrestrial lidar system, which is georeferenced to the Universal Transverse Mercator coordinate system and the North American Vertical Datum of 1988. To accomplish the study objectives, independent elevation data were collected by conducting a high-accuracy global positioning system survey to establish the coordinates and elevations of 12 targets spaced throughout the 12 km transect. These independent ground control data were compared to the lidar scanner-derived elevations to quantify the accuracy of the mobile lidar system. The performance of the mobile lidar system was also tested at various vehicle speeds and scan density settings (e.g. field of view and linear point spacing) to estimate the optimal parameters for desired point density. After adjustment of the lever arm parameters, the final point cloud accuracy was 0.060 m (east), 0.095 m (north), and 0.053 m (height). The very high density of the resulting point cloud was sufficient to map fine-scale topographic features, such as the complex shape of the sand dunes.

Outcrop-scale fracture trace identification using surface roughness derived from a high-density point cloud

NASA Astrophysics Data System (ADS)

Okyay, U.; Glennie, C. L.; Khan, S.

2017-12-01

Owing to the advent of terrestrial laser scanners (TLS), high-density point cloud data has become increasingly available to the geoscience research community. Research groups have started producing their own point clouds for various applications, gradually shifting their emphasis from obtaining the data towards extracting more and meaningful information from the point clouds. Extracting fracture properties from three-dimensional data in a (semi-)automated manner has been an active area of research in geosciences. Several studies have developed various processing algorithms for extracting only planar surfaces. In comparison, (semi-)automated identification of fracture traces at the outcrop scale, which could be used for mapping fracture distribution have not been investigated frequently. Understanding the spatial distribution and configuration of natural fractures is of particular importance, as they directly influence fluid-flow through the host rock. Surface roughness, typically defined as the deviation of a natural surface from a reference datum, has become an important metric in geoscience research, especially with the increasing density and accuracy of point clouds. In the study presented herein, a surface roughness model was employed to identify fracture traces and their distribution on an ophiolite outcrop in Oman. Surface roughness calculations were performed using orthogonal distance regression over various grid intervals. The results demonstrated that surface roughness could identify outcrop-scale fracture traces from which fracture distribution and density maps can be generated. However, considering outcrop conditions and properties and the purpose of the application, the definition of an adequate grid interval for surface roughness model and selection of threshold values for distribution maps are not straightforward and require user intervention and interpretation.

Large scale IRAM 30 m CO-observations in the giant molecular cloud complex W43

NASA Astrophysics Data System (ADS)

Carlhoff, P.; Nguyen Luong, Q.; Schilke, P.; Motte, F.; Schneider, N.; Beuther, H.; Bontemps, S.; Heitsch, F.; Hill, T.; Kramer, C.; Ossenkopf, V.; Schuller, F.; Simon, R.; Wyrowski, F.

2013-12-01

We aim to fully describe the distribution and location of dense molecular clouds in the giant molecular cloud complex W43. It was previously identified as one of the most massive star-forming regions in our Galaxy. To trace the moderately dense molecular clouds in the W43 region, we initiated W43-HERO, a large program using the IRAM 30 m telescope, which covers a wide dynamic range of scales from 0.3 to 140 pc. We obtained on-the-fly-maps in 13CO (2-1) and C18O (2-1) with a high spectral resolution of 0.1 km s-1 and a spatial resolution of 12''. These maps cover an area of ~1.5 square degrees and include the two main clouds of W43 and the lower density gas surrounding them. A comparison to Galactic models and previous distance calculations confirms the location of W43 near the tangential point of the Scutum arm at approximately 6 kpc from the Sun. The resulting intensity cubes of the observed region are separated into subcubes, which are centered on single clouds and then analyzed in detail. The optical depth, excitation temperature, and H2 column density maps are derived out of the 13CO and C18O data. These results are then compared to those derived from Herschel dust maps. The mass of a typical cloud is several 104 M⊙ while the total mass in the dense molecular gas (>102 cm-3) in W43 is found to be ~1.9 × 106 M⊙. Probability distribution functions obtained from column density maps derived from molecular line data and Herschel imaging show a log-normal distribution for low column densities and a power-law tail for high densities. A flatter slope for the molecular line data probability distribution function may imply that those selectively show the gravitationally collapsing gas. Appendices are available in electronic form at http://www.aanda.orgThe final datacubes (13CO and C18O) for the entire survey are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/560/A24

Ultrafast molecular processes mapped by femtosecond x-ray diffraction

NASA Astrophysics Data System (ADS)

Elsaesser, Thomas

2012-02-01

X-ray diffraction with a femtosecond time resolution allows for mapping photoinduced structural dynamics on the length scale of a chemical bond and in the time domain of atomic and molecular motion. In a pump-probe approach, a femtosecond excitation pulse induces structural changes which are probed by diffracting a femtosecond hard x-ray pulse from the excited sample. The transient angular positions and intensities of diffraction peaks give insight into the momentary atomic or molecular positions and into the distribution of electronic charge density. The simultaneous measurement of changes on different diffraction peaks is essential for determining atom positions and charge density maps with high accuracy. Recent progress in the generation of ultrashort hard x-ray pulses (Cu Kα, wavelength λ=0.154 nm) in laser-driven plasma sources has led to the implementation of the powder diffraction and the rotating crystal method with a time resolution of 100 fs. In this contribution, we report new results from powder diffraction studies of molecular materials. A first series of experiments gives evidence of a so far unknown concerted transfer of electrons and protons in ammonium sulfate [(NH4)2SO4], a centrosymmetric structure. Charge transfer from the sulfate groups results in the sub-100 fs generation of a confined electron channel along the c-axis of the unit cell which is stabilized by transferring protons from the adjacent ammonium groups into the channel. Time-dependent charge density maps display a periodic modulation of the channel's charge density by low-frequency lattice motions with a concerted electron and proton motion between the channel and the initial proton binding site. A second study addresses atomic rearrangements and charge dislocations in the non-centrosymmetric potassium dihydrogen phosphate [KH2PO4, KDP]. Photoexcitation generates coherent low-frequency motions along the LO and TO phonon coordinates, leaving the average atomic positions unchanged. The time-dependent maps of electron density demonstrate a concomitant oscillatory relocation of electronic charge with a spatial amplitude of the order of a chemical bond length, two orders of magnitude larger than the vibrational amplitudes. The coherent phonon motions drive the charge relocation, similar to a soft mode driven phase transition between the ferro- and paraelectric phase of KDP.

Relevance of ERTS to the State of Ohio

NASA Technical Reports Server (NTRS)

Sweet, D. C. (Principal Investigator)

1973-01-01

The author has identified the following significant results. A significant result was the fabrication of an image transfer and comparison device. To avoid problems and high costs encountered in manual drafting methods, Battelle staff members have fabricated an inexpensive, yet effective, technique for transferring ERTS-1 analysis displays from the Spatial Data 32-Color Viewer to maps and/or aircraft imagery. In brief, the image transfer-comparison device consists of a 2-way mirror which functions similar to a zoom transfer scope. However, the device permits multiuser viewing and real time photographic recording (35-mm and Polaroid) of enhanced ERTS-1 imagery superimposed over maps and aircraft photography. Thirty-five mm, 70 mm, and 4 in. x 5 in. photographs are taken of 80% of the TV screen of the Spatial Data Density Slicing Viewer. The resulting black and white and color imagery is then used in transparent overlays, viewgraphs, 35-mm and 70-mm transparencies, and paper prints for reports and publications. Annotations can be added on the TV screen or on the finished product.

Spatially resolved mapping of electrical conductivity across individual domain (grain) boundaries in graphene.

PubMed

Clark, Kendal W; Zhang, X-G; Vlassiouk, Ivan V; He, Guowei; Feenstra, Randall M; Li, An-Ping

2013-09-24

All large-scale graphene films contain extended topological defects dividing graphene into domains or grains. Here, we spatially map electronic transport near specific domain and grain boundaries in both epitaxial graphene grown on SiC and CVD graphene on Cu subsequently transferred to a SiO2 substrate, with one-to-one correspondence to boundary structures. Boundaries coinciding with the substrate step on SiC exhibit a significant potential barrier for electron transport of epitaxial graphene due to the reduced charge transfer from the substrate near the step edge. Moreover, monolayer-bilayer boundaries exhibit a high resistance that can change depending on the height of substrate step coinciding at the boundary. In CVD graphene, the resistance of a grain boundary changes with the width of the disordered transition region between adjacent grains. A quantitative modeling of boundary resistance reveals the increased electron Fermi wave vector within the boundary region, possibly due to boundary induced charge density variation. Understanding how resistance change with domain (grain) boundary structure in graphene is a crucial first step for controlled engineering of defects in large-scale graphene films.

Application of Data-Driven Evidential Belief Functions to Prospectivity Mapping for Aquamarine-Bearing Pegmatites, Lundazi District, Zambia

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

Carranza, E. J. M., E-mail: carranza@itc.nl; Woldai, T.; Chikambwe, E. M.

A case application of data-driven estimation of evidential belief functions (EBFs) is demonstrated to prospectivity mapping in Lundazi district (eastern Zambia). Spatial data used to represent recognition criteria of prospectivity for aquamarine-bearing pegmatites include mapped granites, mapped faults/fractures, mapped shear zones, and radioelement concentration ratios derived from gridded airborne radiometric data. Data-driven estimates EBFs take into account not only (a) spatial association between an evidential map layer and target deposits but also (b) spatial relationships between classes of evidences in an evidential map layer. Data-driven estimates of EBFs can indicate which spatial data provide positive or negative evidence of prospectivity.more » Data-driven estimates of EBFs of only spatial data providing positive evidence of prospectivity were integrated according to Dempster's rule of combination. Map of integrated degrees of belief was used to delineate zones of relative degress of prospectivity for aquamarine-bearing pegmatites. The predictive map has at least 85% prediction rate and at least 79% success rate of delineating training and validation deposits, respectively. The results illustrate usefulness of data-driven estimation of EBFs in GIS-based predictive mapping of mineral prospectivity. The results also show usefulness of EBFs in managing uncertainties associated with evidential maps.« less

Cognitive maps and attention.

PubMed

Hardt, Oliver; Nadel, Lynn

2009-01-01

Cognitive map theory suggested that exploring an environment and attending to a stimulus should lead to its integration into an allocentric environmental representation. We here report that directed attention in the form of exploration serves to gather information needed to determine an optimal spatial strategy, given task demands and characteristics of the environment. Attended environmental features may integrate into spatial representations if they meet the requirements of the optimal spatial strategy: when learning involves a cognitive mapping strategy, cues with high codability (e.g., concrete objects) will be incorporated into a map, but cues with low codability (e.g., abstract paintings) will not. However, instructions encouraging map learning can lead to the incorporation of cues with low codability. On the other hand, if spatial learning is not map-based, abstract cues can and will be used to encode locations. Since exploration appears to determine what strategy to apply and whether or not to encode a cue, recognition memory for environmental features is independent of whether or not a cue is part of a spatial representation. In fact, when abstract cues were used in a way that was not map-based, or when they were not used for spatial navigation at all, they were nevertheless recognized as familiar. Thus, the relation between exploratory activity on the one hand and spatial strategy and memory on the other appears more complex than initially suggested by cognitive map theory.

Intercomparison of four airborne imaging DOAS systems for tropospheric NO2 mapping - First results of the AROMAPEX campaign

NASA Astrophysics Data System (ADS)

Tack, Frederik; Merlaud, Alexis; Meier, Andreas; Ge, Xinrui; Meuleman, Koen; Ruhtz, Thomas; van der Wal, Len; Van Roozendael, Michel; Iordache, Daniel; Schönhardt, Anja; Richter, Andreas; Vlemmix, Tim; de Goeij, Bryan; Ardelean, Magdalena; Boscornea, Andreea; Constantin, Daniel; Shaifangar, Reza; Wagner, Thomas; Lampel, Johannes; Schuettemeyer, Dirk

2017-04-01

The AROMAPEX campaign took place in Berlin in April, 2016, co-funded by the EU (EUFAR) and ESA, with the primary objective to intercompare experimental airborne atmospheric imagers dedicated to the mapping of the spatial distribution of tropospheric nitrogen dioxide (NO2). AROMAPEX is also a preparatory step for forthcoming intercomparison/validation campaigns of satellite air quality sensors, such as TROPOMI (TROPOspheric Monitoring Instrument). The instruments were operated from two planes, performing synchronized flights: APEX (VITO/BIRA-IASB) was operated from DLR's DO-228 D-CFFU plane at 6.1 km altitude while AirMAP (IUP Bremen), and the small, lightweight SWING (BIRA-IASB) and Spectrolite (TNO/TU Delft) instruments were operated from the FUB Cessna 207T D-EAFU at 3 km. Two synchronized flights took place on 21 April, 2016, the only cloud-free day during the campaign, in the morning from 09:34 to 12:01 LT and in the afternoon from 14:24 to 16:39 LT. APEX, AirMAP and SWING have a comparable swath width of 3 km, while Spectrolite has a swath of 450 m due to the fact that the field-of-view had to be reduced from 40° to 8.3° for practical reasons. The spatial resolution is approximately 100 m after spatial aggregation for APEX, AirMAP and Spectrolite (pushbroom scanning), and 300 m for SWING (whiskbroom scanning). The airborne Sunphotometer FUBISS-ASA2 was installed and operated during the ascent and descent of the FUB aircraft to derive aerosol optical depth (AOD). During the overpass of the imagers, simultaneous car mobile-DOAS observations were performed with three systems covering transects from north to south and west to east. The ground-based instrumental set-up was completed by a DOAS instrument, an Aeronet station and a ceilometer installed at the rooftop of FUB, located in the southwest of Berlin. The AROMAPEX experiment builds on the experience gained during the AROMAT campaigns held in September, 2014 and August, 2015 in Romania, and the BUMBA campaigns held in April, 2015 and July, 2016 in Belgium. We present first results of an intercomparison study of both the NO2 slant column densities (SCDs) and vertical column densities (VCDs) retrieved from the APEX, AirMAP, SWING and Spectrolite instruments. Two large NO2 plumes, crossing the city from west to east, were detected by all imaging systems with high consistency. Retrieved NO2 VCDs range between 1.5 x 1015 and 2.4 x 1016 molec cm-2. For the sake of harmonizing the different data sets, efforts are currently ongoing to agree on a common set of parameter settings, gridding algorithm and AMF LUT in the NO2 retrieval approach. Despite these efforts, discrepancies will remain due to a combination of (1) instrumental differences, e.g. SNR, spatial and spectral resolution; (2) algorithmic differences, e.g. DOAS fitting, RTM, a priori input; and (3) observation differences, e.g. flight altitude, overpass time and viewing geometry.

Globally optimal superconducting magnets part I: minimum stored energy (MSE) current density map.

PubMed

Tieng, Quang M; Vegh, Viktor; Brereton, Ian M

2009-01-01

An optimal current density map is crucial in magnet design to provide the initial values within search spaces in an optimization process for determining the final coil arrangement of the magnet. A strategy for obtaining globally optimal current density maps for the purpose of designing magnets with coaxial cylindrical coils in which the stored energy is minimized within a constrained domain is outlined. The current density maps obtained utilising the proposed method suggests that peak current densities occur around the perimeter of the magnet domain, where the adjacent peaks have alternating current directions for the most compact designs. As the dimensions of the domain are increased, the current density maps yield traditional magnet designs of positive current alone. These unique current density maps are obtained by minimizing the stored magnetic energy cost function and therefore suggest magnet coil designs of minimal system energy. Current density maps are provided for a number of different domain arrangements to illustrate the flexibility of the method and the quality of the achievable designs.

Increased stem density and competition may diminish the positive effects of warming at alpine treeline.

PubMed

Wang, Yafeng; Pederson, Neil; Ellison, Aaron M; Buckley, Hannah L; Case, Bradley S; Liang, Eryuan; Julio Camarero, J

2016-07-01

The most widespread response to global warming among alpine treeline ecotones is not an upward shift, but an increase in tree density. However, the impact of increasing density on interactions among trees at treeline is not well understood. Here, we test if treeline densification induced by climatic warming leads to increasing intraspecific competition. We mapped and measured the size and age of Smith fir trees growing in two treelines located in the southeastern Tibetan Plateau. We used spatial point-pattern and codispersion analyses to describe the spatial association and covariation among seedlings, juveniles, and adults grouped in 30-yr age classes from the 1860s to the present. Effects of competition on tree height and regeneration were inferred from bivariate mark-correlations. Since the 1950s, a rapid densification occurred at both sites in response to climatic warming. Competition between adults and juveniles or seedlings at small scales intensified as density increased. Encroachment negatively affected height growth and further reduced recruitment around mature trees. We infer that tree recruitment at the studied treelines was more cold-limited prior to 1950 and shifted to a less temperature-constrained regime in response to climatic warming. Therefore, the ongoing densification and encroachment of alpine treelines could alter the way climate drives their transitions toward subalpine forests. © 2016 by the Ecological Society of America.

A smoothed stochastic earthquake rate model considering seismicity and fault moment release for Europe

NASA Astrophysics Data System (ADS)

Hiemer, S.; Woessner, J.; Basili, R.; Danciu, L.; Giardini, D.; Wiemer, S.

2014-08-01

We present a time-independent gridded earthquake rate forecast for the European region including Turkey. The spatial component of our model is based on kernel density estimation techniques, which we applied to both past earthquake locations and fault moment release on mapped crustal faults and subduction zone interfaces with assigned slip rates. Our forecast relies on the assumption that the locations of past seismicity is a good guide to future seismicity, and that future large-magnitude events occur more likely in the vicinity of known faults. We show that the optimal weighted sum of the corresponding two spatial densities depends on the magnitude range considered. The kernel bandwidths and density weighting function are optimized using retrospective likelihood-based forecast experiments. We computed earthquake activity rates (a- and b-value) of the truncated Gutenberg-Richter distribution separately for crustal and subduction seismicity based on a maximum likelihood approach that considers the spatial and temporal completeness history of the catalogue. The final annual rate of our forecast is purely driven by the maximum likelihood fit of activity rates to the catalogue data, whereas its spatial component incorporates contributions from both earthquake and fault moment-rate densities. Our model constitutes one branch of the earthquake source model logic tree of the 2013 European seismic hazard model released by the EU-FP7 project `Seismic HAzard haRmonization in Europe' (SHARE) and contributes to the assessment of epistemic uncertainties in earthquake activity rates. We performed retrospective and pseudo-prospective likelihood consistency tests to underline the reliability of our model and SHARE's area source model (ASM) using the testing algorithms applied in the collaboratory for the study of earthquake predictability (CSEP). We comparatively tested our model's forecasting skill against the ASM and find a statistically significant better performance for testing periods of 10-20 yr. The testing results suggest that our model is a viable candidate model to serve for long-term forecasting on timescales of years to decades for the European region.

Building-Based Analysis of the Spatial Provision of Urban Parks in Shenzhen, China.

PubMed

Gao, Wenxiu; Lyu, Qiang; Fan, Xiang; Yang, Xiaochun; Liu, Jiangtao; Zhang, Xirui

2017-12-06

Urban parks provide important environmental, social, and economic benefits to people and urban areas. The literature demonstrates that proximity to urban parks is one of the key factors influencing people's willingness to use them. Therefore, the provision of urban parks near residential areas and workplaces is one of the key factors influencing quality of life. This study designed a solution based on the spatial association between urban parks and buildings where people live or work to identify whether people in different buildings have nearby urban parks available for their daily lives. A building density map based on building floor area (BFA) was used to illustrate the spatial distribution of urban parks and five indices were designed to measure the scales, service coverage and potential service loads of urban parks and reveal areas lacking urban park services in an acceptable walking distance. With such solution, we investigated the provision of urban parks in ten districts of Shenzhen in China, which has grown from several small villages to a megacity in only 30 years. The results indicate that the spatial provision of urban parks in Shenzhen is not sufficient since people in about 65% of the buildings cannot access urban parks by walking 10-min. The distribution and service coverage of the existing urban parks is not balanced at the district level. In some districts, the existing urban parks have good numbers of potential users and even have large service loads, while in some districts, the building densities surrounding the existing parks are quite low and at the same time there is no urban parks nearby some high-density areas.

Spatial analysis of deaths from pulmonary tuberculosis in the city of São Luís, Brazil*

PubMed Central

Santos-Neto, Marcelino; Yamamura, Mellina; Garcia, Maria Concebida da Cunha; Popolin, Marcela Paschoal; Silveira, Tatiane Ramos dos Santos; Arcêncio, Ricardo Alexandre

2014-01-01

OBJECTIVE: To characterize deaths from pulmonary tuberculosis, according to sociodemographic and operational variables, in the city of São Luís, Brazil, and to describe their spatial distribution. METHODS: This was an exploratory ecological study based on secondary data from death certificates, obtained from the Brazilian Mortality Database, related to deaths from pulmonary tuberculosis. We included all deaths attributed to pulmonary tuberculosis that occurred in the urban area of São Luís between 2008 and 2012. We performed univariate and bivariate analyses of the sociodemographic and operational variables of the deaths investigated, as well as evaluating the spatial distribution of the events by kernel density estimation. RESULTS: During the study period, there were 193 deaths from pulmonary tuberculosis in São Luís. The median age of the affected individuals was 52 years. Of the 193 individuals who died, 142 (73.60%) were male, 133 (68.91%) were Mulatto, 102 (53.13%) were single, and 64 (33.16%) had completed middle school. There was a significant positive association between not having received medical care prior to death and an autopsy having been performed (p = 0.001). A thematic map by density of points showed that the spatial distribution of those deaths was heterogeneous and that the density was as high as 8.12 deaths/km2. CONCLUSIONS: The sociodemographic and operational characteristics of the deaths from pulmonary tuberculosis evaluated in this study, as well as the identification of priority areas for control and surveillance of the disease, could promote public health policies aimed at reducing health inequities, allowing the optimization of resources, as well as informing decisions regarding the selection of strategies and specific interventions targeting the most vulnerable populations. PMID:25410843

Building-Based Analysis of the Spatial Provision of Urban Parks in Shenzhen, China

PubMed Central

Gao, Wenxiu; Lyu, Qiang; Fan, Xiang; Liu, Jiangtao; Zhang, Xirui

2017-01-01

Urban parks provide important environmental, social, and economic benefits to people and urban areas. The literature demonstrates that proximity to urban parks is one of the key factors influencing people’s willingness to use them. Therefore, the provision of urban parks near residential areas and workplaces is one of the key factors influencing quality of life. This study designed a solution based on the spatial association between urban parks and buildings where people live or work to identify whether people in different buildings have nearby urban parks available for their daily lives. A building density map based on building floor area (BFA) was used to illustrate the spatial distribution of urban parks and five indices were designed to measure the scales, service coverage and potential service loads of urban parks and reveal areas lacking urban park services in an acceptable walking distance. With such solution, we investigated the provision of urban parks in ten districts of Shenzhen in China, which has grown from several small villages to a megacity in only 30 years. The results indicate that the spatial provision of urban parks in Shenzhen is not sufficient since people in about 65% of the buildings cannot access urban parks by walking 10-min. The distribution and service coverage of the existing urban parks is not balanced at the district level. In some districts, the existing urban parks have good numbers of potential users and even have large service loads, while in some districts, the building densities surrounding the existing parks are quite low and at the same time there is no urban parks nearby some high-density areas. PMID:29211046

Spatial analysis of deaths from pulmonary tuberculosis in the city of São Luís, Brazil.

PubMed

Santos-Neto, Marcelino; Yamamura, Mellina; Garcia, Maria Concebida da Cunha; Popolin, Marcela Paschoal; Silveira, Tatiane Ramos Dos Santos; Arcêncio, Ricardo Alexandre

2014-10-01

To characterize deaths from pulmonary tuberculosis, according to sociodemographic and operational variables, in the city of São Luís, Brazil, and to describe their spatial distribution. This was an exploratory ecological study based on secondary data from death certificates, obtained from the Brazilian Mortality Database, related to deaths from pulmonary tuberculosis. We included all deaths attributed to pulmonary tuberculosis that occurred in the urban area of São Luís between 2008 and 2012. We performed univariate and bivariate analyses of the sociodemographic and operational variables of the deaths investigated, as well as evaluating the spatial distribution of the events by kernel density estimation. During the study period, there were 193 deaths from pulmonary tuberculosis in São Luís. The median age of the affected individuals was 52 years. Of the 193 individuals who died, 142 (73.60%) were male, 133 (68.91%) were Mulatto, 102 (53.13%) were single, and 64 (33.16%) had completed middle school. There was a significant positive association between not having received medical care prior to death and an autopsy having been performed (p = 0.001). A thematic map by density of points showed that the spatial distribution of those deaths was heterogeneous and that the density was as high as 8.12 deaths/km2. The sociodemographic and operational characteristics of the deaths from pulmonary tuberculosis evaluated in this study, as well as the identification of priority areas for control and surveillance of the disease, could promote public health policies aimed at reducing health inequities, allowing the optimization of resources, as well as informing decisions regarding the selection of strategies and specific interventions targeting the most vulnerable populations.

Spatial reconstruction of single-cell gene expression data.

PubMed

Satija, Rahul; Farrell, Jeffrey A; Gennert, David; Schier, Alexander F; Regev, Aviv

2015-05-01

Spatial localization is a key determinant of cellular fate and behavior, but methods for spatially resolved, transcriptome-wide gene expression profiling across complex tissues are lacking. RNA staining methods assay only a small number of transcripts, whereas single-cell RNA-seq, which measures global gene expression, separates cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos and generated a transcriptome-wide map of spatial patterning. We confirmed Seurat's accuracy using several experimental approaches, then used the strategy to identify a set of archetypal expression patterns and spatial markers. Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems.

Spatial reconstruction of single-cell gene expression

PubMed Central

Satija, Rahul; Farrell, Jeffrey A.; Gennert, David; Schier, Alexander F.; Regev, Aviv

2015-01-01

Spatial localization is a key determinant of cellular fate and behavior, but spatial RNA assays traditionally rely on staining for a limited number of RNA species. In contrast, single-cell RNA-seq allows for deep profiling of cellular gene expression, but established methods separate cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos, inferring a transcriptome-wide map of spatial patterning. We confirmed Seurat’s accuracy using several experimental approaches, and used it to identify a set of archetypal expression patterns and spatial markers. Additionally, Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems. PMID:25867923

Mapping Topographic Structure in White Matter Pathways with Level Set Trees

PubMed Central

Kent, Brian P.; Rinaldo, Alessandro; Yeh, Fang-Cheng; Verstynen, Timothy

2014-01-01

Fiber tractography on diffusion imaging data offers rich potential for describing white matter pathways in the human brain, but characterizing the spatial organization in these large and complex data sets remains a challenge. We show that level set trees–which provide a concise representation of the hierarchical mode structure of probability density functions–offer a statistically-principled framework for visualizing and analyzing topography in fiber streamlines. Using diffusion spectrum imaging data collected on neurologically healthy controls (N = 30), we mapped white matter pathways from the cortex into the striatum using a deterministic tractography algorithm that estimates fiber bundles as dimensionless streamlines. Level set trees were used for interactive exploration of patterns in the endpoint distributions of the mapped fiber pathways and an efficient segmentation of the pathways that had empirical accuracy comparable to standard nonparametric clustering techniques. We show that level set trees can also be generalized to model pseudo-density functions in order to analyze a broader array of data types, including entire fiber streamlines. Finally, resampling methods show the reliability of the level set tree as a descriptive measure of topographic structure, illustrating its potential as a statistical descriptor in brain imaging analysis. These results highlight the broad applicability of level set trees for visualizing and analyzing high-dimensional data like fiber tractography output. PMID:24714673

A bottom up approach to on-road CO2 emissions estimates: improved spatial accuracy and applications for regional planning.

PubMed

Gately, Conor K; Hutyra, Lucy R; Wing, Ian Sue; Brondfield, Max N

2013-03-05

On-road transportation is responsible for 28% of all U.S. fossil-fuel CO2 emissions. Mapping vehicle emissions at regional scales is challenging due to data limitations. Existing emission inventories use spatial proxies such as population and road density to downscale national or state-level data. Such procedures introduce errors where the proxy variables and actual emissions are weakly correlated, and limit analysis of the relationship between emissions and demographic trends at local scales. We develop an on-road emission inventory product for Massachusetts-based on roadway-level traffic data obtained from the Highway Performance Monitoring System (HPMS). We provide annual estimates of on-road CO2 emissions at a 1 × 1 km grid scale for the years 1980 through 2008. We compared our results with on-road emissions estimates from the Emissions Database for Global Atmospheric Research (EDGAR), with the Vulcan Product, and with estimates derived from state fuel consumption statistics reported by the Federal Highway Administration (FHWA). Our model differs from FHWA estimates by less than 8.5% on average, and is within 5% of Vulcan estimates. We found that EDGAR estimates systematically exceed FHWA by an average of 22.8%. Panel regression analysis of per-mile CO2 emissions on population density at the town scale shows a statistically significant correlation that varies systematically in sign and magnitude as population density increases. Population density has a positive correlation with per-mile CO2 emissions for densities below 2000 persons km(-2), above which increasing density correlates negatively with per-mile emissions.

Social deprivation and population density are not associated with small area risk of amyotrophic lateral sclerosis.

PubMed

Rooney, James P K; Tobin, Katy; Crampsie, Arlene; Vajda, Alice; Heverin, Mark; McLaughlin, Russell; Staines, Anthony; Hardiman, Orla

2015-10-01

Evidence of an association between areal ALS risk and population density has been previously reported. We aim to examine ALS spatial incidence in Ireland using small areas, to compare this analysis with our previous analysis of larger areas and to examine the associations between population density, social deprivation and ALS incidence. Residential area social deprivation has not been previously investigated as a risk factor for ALS. Using the Irish ALS register, we included all cases of ALS diagnosed in Ireland from 1995-2013. 2006 census data was used to calculate age and sex standardised expected cases per small area. Social deprivation was assessed using the pobalHP deprivation index. Bayesian smoothing was used to calculate small area relative risk for ALS, whilst cluster analysis was performed using SaTScan. The effects of population density and social deprivation were tested in two ways: (1) as covariates in the Bayesian spatial model; (2) via post-Bayesian regression. 1701 cases were included. Bayesian smoothed maps of relative risk at small area resolution matched closely to our previous analysis at a larger area resolution. Cluster analysis identified two areas of significant low risk. These areas did not correlate with population density or social deprivation indices. Two areas showing low frequency of ALS have been identified in the Republic of Ireland. These areas do not correlate with population density or residential area social deprivation, indicating that other reasons, such as genetic admixture may account for the observed findings. Copyright © 2015 Elsevier Inc. All rights reserved.

Fast flow-based algorithm for creating density-equalizing map projections

PubMed Central

Gastner, Michael T.; Seguy, Vivien; More, Pratyush

2018-01-01

Cartograms are maps that rescale geographic regions (e.g., countries, districts) such that their areas are proportional to quantitative demographic data (e.g., population size, gross domestic product). Unlike conventional bar or pie charts, cartograms can represent correctly which regions share common borders, resulting in insightful visualizations that can be the basis for further spatial statistical analysis. Computer programs can assist data scientists in preparing cartograms, but developing an algorithm that can quickly transform every coordinate on the map (including points that are not exactly on a border) while generating recognizable images has remained a challenge. Methods that translate the cartographic deformations into physics-inspired equations of motion have become popular, but solving these equations with sufficient accuracy can still take several minutes on current hardware. Here we introduce a flow-based algorithm whose equations of motion are numerically easier to solve compared with previous methods. The equations allow straightforward parallelization so that the calculation takes only a few seconds even for complex and detailed input. Despite the speedup, the proposed algorithm still keeps the advantages of previous techniques: With comparable quantitative measures of shape distortion, it accurately scales all areas, correctly fits the regions together, and generates a map projection for every point. We demonstrate the use of our algorithm with applications to the 2016 US election results, the gross domestic products of Indian states and Chinese provinces, and the spatial distribution of deaths in the London borough of Kensington and Chelsea between 2011 and 2014. PMID:29463721

Inter-nesting habitat-use patterns of loggerhead sea turtles: Enhancing satellite tracking with benthic mapping

USGS Publications Warehouse

Hart, Kristen M.; Zawada, David G.; Fujisaki, Ikuko; Lidz, Barbara H.

2010-01-01

The loggerhead sea turtle Caretta caretta faces declining nest numbers and bycatches from commercial longline fishing in the southeastern USA. Understanding spatial and temporal habitat-use patterns of these turtles, especially reproductive females in the neritic zone, is critical for guiding management decisions. To assess marine turtle habitat use within the Dry Tortugas National Park (DRTO), we used satellite telemetry to identify core-use areas for 7 loggerhead females inter-nesting and tracked in 2008 and 2009. This effort represents the first tracking of DRTO loggerheads, a distinct subpopulation that is 1 of 7 recently proposed for upgrading from threatened to endangered under the US Endangered Species Act. We also used a rapid, high-resolution, digital imaging system to map benthic habitats in turtle core-use areas (i.e. 50% kernel density zones). Loggerhead females were seasonal residents of DRTO for 19 to 51 d, and individual inter-nesting habitats were located within 1.9 km (2008) and 2.3 km (2009) of the nesting beach and tagging site. The core area common to all tagged turtles was 4.2 km2 in size and spanned a depth range of 7.6 to 11.5 m. Mapping results revealed the diversity and distributions of benthic cover available in the core-use area, as well as a heavily used corridor to/from the nesting beach. This combined tagging-mapping approach shows potential for planning and improving the effectiveness of marine protected areas and for developing spatially explicit conservation plans.

Seismo-ionospheric anomalies in total electron content of the GIM and electron density of DEMETER before the 27 February 2010 M8.8 Chile earthquake

NASA Astrophysics Data System (ADS)

Ho, Yi-Ying; Jhuang, Hau-Kun; Su, Yung-Chih; Liu, Jann-Yenq

2013-06-01

In this paper we examine the pre-earthquake ionospheric anomalies by the total electron content (TEC) extracted from GIM (global ionospheric map) and the electron density (Ne) observed by the DEMETER (Detection of Electro-Magnetic Emissions Transmitted from Earthquake Regions) satellite during the 2010 M8.8 Chile earthquake. Temporal variations show the nighttime TEC and Ne simultaneously increase 9-19 days before the earthquake. A cross-comparison of data recorded during the period of 1 February to 3 March in 2006-2010 confirms the above temporal anomalies specifically appear in 2010. The spatial analyses show that the anomalies tend to appear over the epicenter.

Vortex energy landscape from real space imaging analysis of YBa2Cu3O7 with different defect structures

NASA Astrophysics Data System (ADS)

Luccas, R. F.; Granados, X.; Obradors, X.; Puig, T.

2014-10-01

A methodology based on real space vortex image analysis is presented able to estimate semi-quantitatively the relevant energy densities of an arbitrary array of vortices, map the interaction energy distributions and evaluate the pinning energy associated to particular defects. The combined study using nanostructuration tools, a vortex visualization technique and the energy method is seen as an opportunity to estimate vortex pinning potentials strengths. Particularly, spatial distributions of vortex energy densities induced by surface nanoindented scratches are evaluated and compared to those of twin boundaries. This comparative study underlines the remarkable role of surface nanoscratches in pinning vortices and its potentiality in the design of novel devices for pinning and guiding vortex motion.

Ultrafast Phase Mapping of Thin-Sections from An Apollo 16 Drive Tube - a New Visualisation of Lunar Regolith

NASA Technical Reports Server (NTRS)

Botha, Pieter; Butcher, Alan R.; Horsch, Hana; Rickman, Doug; Wentworth, Susan J.; Schrader, Christian M.; Stoeser, Doug; Benedictus, Aukje; Gottlieb, Paul; McKay, David

2008-01-01

Polished thin-sections of samples extracted from Apollo drive tubes provide unique insights into the structure of the Moon's regolith at various landing sites. In particular, they allow the mineralogy and texture of the regolith to be studied as a function of depth. Much has been written about such thin-sections based on optical, SEM and EPMA studies, in terms of their essential petrographic features, but there has been little attempt to quantify these aspects from a spatial perspective. In this study, we report the findings of experimental analysis of two thin-sections (64002, 6019, depth range 5.0 - 8.0 cm & 64001, 6031, depth range 50.0 - 53.1 cm), from a single Apollo 16 drive tube using QEMSCAN . A key feature of the method is phase identification by ultrafast energy dispersive x-ray mapping on a pixel-by-pixel basis. By selecting pixel resolutions ranging from 1 - 5 microns, typically 8,500,000 individual measurement points can be collected on a thin-section. The results we present include false colour digital images of both thin-sections. From these images, information such as phase proportions (major, minor and trace phases), particle textures, packing densities, and particle geometries, has been quantified. Parameters such as porosity and average phase density, which are of geomechanical interest, can also be calculated automatically. This study is part of an on-going investigation into spatial variation of lunar regolith and NASA's ISRU Lunar Simulant Development Project.

Spatial cluster analysis of nanoscopically mapped serotonin receptors for classification of fixed brain tissue

NASA Astrophysics Data System (ADS)

Sams, Michael; Silye, Rene; Göhring, Janett; Muresan, Leila; Schilcher, Kurt; Jacak, Jaroslaw

2014-01-01

We present a cluster spatial analysis method using nanoscopic dSTORM images to determine changes in protein cluster distributions within brain tissue. Such methods are suitable to investigate human brain tissue and will help to achieve a deeper understanding of brain disease along with aiding drug development. Human brain tissue samples are usually treated postmortem via standard fixation protocols, which are established in clinical laboratories. Therefore, our localization microscopy-based method was adapted to characterize protein density and protein cluster localization in samples fixed using different protocols followed by common fluorescent immunohistochemistry techniques. The localization microscopy allows nanoscopic mapping of serotonin 5-HT1A receptor groups within a two-dimensional image of a brain tissue slice. These nanoscopically mapped proteins can be confined to clusters by applying the proposed statistical spatial analysis. Selected features of such clusters were subsequently used to characterize and classify the tissue. Samples were obtained from different types of patients, fixed with different preparation methods, and finally stored in a human tissue bank. To verify the proposed method, samples of a cryopreserved healthy brain have been compared with epitope-retrieved and paraffin-fixed tissues. Furthermore, samples of healthy brain tissues were compared with data obtained from patients suffering from mental illnesses (e.g., major depressive disorder). Our work demonstrates the applicability of localization microscopy and image analysis methods for comparison and classification of human brain tissues at a nanoscopic level. Furthermore, the presented workflow marks a unique technological advance in the characterization of protein distributions in brain tissue sections.

Evaluation of normal swallowing functions by using dynamic high-density surface electromyography maps.

PubMed

Zhu, Mingxing; Yu, Bin; Yang, Wanzhang; Jiang, Yanbing; Lu, Lin; Huang, Zhen; Chen, Shixiong; Li, Guanglin

2017-11-21

Swallowing is a continuous process with substantive interdependencies among different muscles, and it plays a significant role in our daily life. The aim of this study was to propose a novel technique based on high-density surface electromyography (HD sEMG) for the evaluation of normal swallowing functions. A total of 96 electrodes were placed on the front neck to acquire myoelectric signals from 12 healthy subjects while they were performing different swallowing tasks. HD sEMG energy maps were constructed based on the root mean square values to visualize muscular activities during swallowing. The effects of different volumes, viscosities, and head postures on the normal swallowing process were systemically investigated by using the energy maps. The results showed that the HD sEMG energy maps could provide detailed spatial and temporal properties of the muscle electrical activity, and visualize the muscle contractions that closely related to the swallowing function. The energy maps also showed that the swallowing time and effort was also explicitly affected by the volume and viscosity of the bolus. The concentration of the muscular activities shifted to the opposite side when the subjects turned their head to either side. The proposed method could provide an alternative method to physiologically evaluate the dynamic characteristics of normal swallowing and had the advantage of providing a full picture of how different muscle activities cooperate in time and location. The findings from this study suggested that the HD sEMG technique might be a useful tool for fast screening and objective assessment of swallowing disorders or dysphagia.

Fourier-space combination of Planck and Herschel images

NASA Astrophysics Data System (ADS)

Abreu-Vicente, J.; Stutz, A.; Henning, Th.; Keto, E.; Ballesteros-Paredes, J.; Robitaille, T.

2017-08-01

Context. Herschel has revolutionized our ability to measure column densities (NH) and temperatures (T) of molecular clouds thanks to its far infrared multiwavelength coverage. However, the lack of a well defined background intensity level in the Herschel data limits the accuracy of the NH and T maps. Aims: We aim to provide a method that corrects the missing Herschel background intensity levels using the Planck model for foreground Galactic thermal dust emission. For the Herschel/PACS data, both the constant-offset as well as the spatial dependence of the missing background must be addressed. For the Herschel/SPIRE data, the constant-offset correction has already been applied to the archival data so we are primarily concerned with the spatial dependence, which is most important at 250 μm. Methods: We present a Fourier method that combines the publicly available Planck model on large angular scales with the Herschel images on smaller angular scales. Results: We have applied our method to two regions spanning a range of Galactic environments: Perseus and the Galactic plane region around l = 11deg (HiGal-11). We post-processed the combined dust continuum emission images to generate column density and temperature maps. We compared these to previously adopted constant-offset corrections. We find significant differences (≳20%) over significant ( 15%) areas of the maps, at low column densities (NH ≲ 1022 cm-2) and relatively high temperatures (T ≳ 20 K). We have also applied our method to synthetic observations of a simulated molecular cloud to validate our method. Conclusions: Our method successfully corrects the Herschel images, including both the constant-offset intensity level and the scale-dependent background variations measured by Planck. Our method improves the previous constant-offset corrections, which did not account for variations in the background emission levels. The image FITS files used in this paper are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/604/A65

High-resolution airborne imaging DOAS measurements of NO2 above Bucharest during AROMAT

NASA Astrophysics Data System (ADS)

Meier, Andreas Carlos; Schönhardt, Anja; Bösch, Tim; Richter, Andreas; Seyler, André; Ruhtz, Thomas; Constantin, Daniel-Eduard; Shaiganfar, Reza; Wagner, Thomas; Merlaud, Alexis; Van Roozendael, Michel; Belegante, Livio; Nicolae, Doina; Georgescu, Lucian; Burrows, John Philip

2017-05-01

In this study we report on airborne imaging DOAS measurements of NO2 from two flights performed in Bucharest during the AROMAT campaign (Airborne ROmanian Measurements of Aerosols and Trace gases) in September 2014. These measurements were performed with the Airborne imaging Differential Optical Absorption Spectroscopy (DOAS) instrument for Measurements of Atmospheric Pollution (AirMAP) and provide nearly gapless maps of column densities of NO2 below the aircraft with a high spatial resolution of better than 100 m. The air mass factors, which are needed to convert the measured differential slant column densities (dSCDs) to vertical column densities (VCDs), have a strong dependence on the surface reflectance, which has to be accounted for in the retrieval. This is especially important for measurements above urban areas, where the surface properties vary strongly. As the instrument is not radiometrically calibrated, we have developed a method to derive the surface reflectance from intensities measured by AirMAP. This method is based on radiative transfer calculation with SCIATRAN and a reference area for which the surface reflectance is known. While surface properties are clearly apparent in the NO2 dSCD results, this effect is successfully corrected for in the VCD results. Furthermore, we investigate the influence of aerosols on the retrieval for a variety of aerosol profiles that were measured in the context of the AROMAT campaigns. The results of two research flights are presented, which reveal distinct horizontal distribution patterns and strong spatial gradients of NO2 across the city. Pollution levels range from background values in the outskirts located upwind of the city to about 4 × 1016 molec cm-2 in the polluted city center. Validation against two co-located mobile car-DOAS measurements yields good agreement between the datasets, with correlation coefficients of R = 0.94 and R = 0.85, respectively. Estimations on the NOx emission rate of Bucharest for the two flights yield emission rates of 15.1 ± 9.4 and 13.6 ± 8.4 mol s-1, respectively.

Temporal and Spatial Analysis of Monogenetic Volcanic Fields

NASA Astrophysics Data System (ADS)

Kiyosugi, Koji

Achieving an understanding of the nature of monogenetic volcanic fields depends on identification of the spatial and temporal patterns of volcanism in these fields, and their relationships to structures mapped in the shallow crust and inferred in the deep crust and mantle through interpretation of geochemical, radiometric and geophysical data. We investigate the spatial and temporal distributions of volcanism in the Abu Monogenetic Volcano Group, Southwest Japan. E-W elongated volcano distribution, which is identified by a nonparametric kernel method, is found to be consistent with the spatial extent of P-wave velocity anomalies in the lower crust and upper mantle, supporting the idea that the spatial density map of volcanic vents reflects the geometry of a mantle diapir. Estimated basalt supply to the lower crust is constant. This observation and the spatial distribution of volcanic vents suggest stability of magma productivity and essentially constant two-dimensional size of the source mantle diapir. We mapped conduits, dike segments, and sills in the San Rafael sub-volcanic field, Utah, where the shallowest part of a Pliocene magmatic system is exceptionally well exposed. The distribution of conduits matches the major features of dike distribution, including development of clusters and distribution of outliers. The comparison of San Rafael conduit distribution and the distributions of volcanoes in several recently active volcanic fields supports the use of statistical models, such as nonparametric kernel methods, in probabilistic hazard assessment for distributed volcanism. We developed a new recurrence rate calculation method that uses a Monte Carlo procedure to better reflect and understand the impact of uncertainties of radiometric age determinations on uncertainty of recurrence rate estimates for volcanic activity in the Abu, Yucca Mountain Region, and Izu-Tobu volcanic fields. Results suggest that the recurrence rates of volcanic fields can change by more than one order of magnitude on time scales of several hundred thousand to several million years. This suggests that magma generation rate beneath volcanic fields may change over these time scales. Also, recurrence rate varies more than one order of magnitude between these volcanic fields, consistent with the idea that distributed volcanism may be influenced by both the rate of magma generation and the potential for dike interaction during ascent.

Assessing spatial uncertainty in reservoir characterization for carbon sequestration planning using public well-log data: A case study

USGS Publications Warehouse

Venteris, E.R.; Carter, K.M.

2009-01-01

Mapping and characterization of potential geologic reservoirs are key components in planning carbon dioxide (CO2) injection projects. The geometry of target and confining layers is vital to ensure that the injected CO2 remains in a supercritical state and is confined to the target layer. Also, maps of injection volume (porosity) are necessary to estimate sequestration capacity at undrilled locations. Our study uses publicly filed geophysical logs and geostatistical modeling methods to investigate the reliability of spatial prediction for oil and gas plays in the Medina Group (sandstone and shale facies) in northwestern Pennsylvania. Specifically, the modeling focused on two targets: the Grimsby Formation and Whirlpool Sandstone. For each layer, thousands of data points were available to model structure and thickness but only hundreds were available to support volumetric modeling because of the rarity of density-porosity logs in the public records. Geostatistical analysis based on this data resulted in accurate structure models, less accurate isopach models, and inconsistent models of pore volume. Of the two layers studied, only the Whirlpool Sandstone data provided for a useful spatial model of pore volume. Where reliable models for spatial prediction are absent, the best predictor available for unsampled locations is the mean value of the data, and potential sequestration sites should be planned as close as possible to existing wells with volumetric data. ?? 2009. The American Association of Petroleum Geologists/Division of Environmental Geosciences. All rights reserved.

Spatiotemporal Distribution of Chinavia hilaris (Hemiptera: Pentatomidae) in Corn Farmscapes

PubMed Central

Cottrell, Ted E.; Tillman, P. Glynn

2015-01-01

The green stink bug, Chinavia hilaris (Say) (Hemiptera: Pentatomidae), is a pest of cotton in the southeastern United States but little is known concerning its spatiotemporal distribution in corn cropping systems. Therefore, the spatiotemporal distribution of C. hilaris in farmscapes, when corn was adjacent to cotton, peanut, or both, was examined weekly. The spatial patterns of C. hilaris counts were analyzed using Spatial Analysis by Distance Indices methodology. Interpolated maps of C. hilaris density were used to visualize abundance and distribution of C. hilaris in crops in corn–peanut–cotton farmscapes. This stink bug was detected in six of seven corn–cotton farmscapes, four of six corn–peanut farmscapes, and in both corn–peanut–cotton farmscapes. The frequency of C. hilaris in cotton (89.47%) was significantly higher than in peanut (7.02%) or corn (3.51%). This stink bug fed on noncrop hosts that grew in field borders adjacent to crops. The spatial distribution of C. hilaris in crops and the capture of C. hilaris adults and nymphs in pheromone-baited traps near noncrop hosts indicated that these hosts were sources of this stink bug dispersing into crops, primarily cotton. Significant aggregated spatial distributions were detected in cotton on some dates within corn–peanut–cotton farmscapes. Maps of local clustering indices depicted small patches of C. hilaris in cotton or cotton–sorghum at the peanut–cotton interface. Factors affecting the spatiotemporal dynamics of C. hilaris in corn farmscapes are discussed. PMID:25843581

Network-based spatial clustering technique for exploring features in regional industry

NASA Astrophysics Data System (ADS)

Chou, Tien-Yin; Huang, Pi-Hui; Yang, Lung-Shih; Lin, Wen-Tzu

2008-10-01

In the past researches, industrial cluster mainly focused on single or particular industry and less on spatial industrial structure and mutual relations. Industrial cluster could generate three kinds of spillover effects, including knowledge, labor market pooling, and input sharing. In addition, industrial cluster indeed benefits industry development. To fully control the status and characteristics of district industrial cluster can facilitate to improve the competitive ascendancy of district industry. The related researches on industrial spatial cluster were of great significance for setting up industrial policies and promoting district economic development. In this study, an improved model, GeoSOM, that combines DBSCAN (Density-Based Spatial Clustering of Applications with Noise) and SOM (Self-Organizing Map) was developed for analyzing industrial cluster. Different from former distance-based algorithm for industrial cluster, the proposed GeoSOM model can calculate spatial characteristics between firms based on DBSCAN algorithm and evaluate the similarity between firms based on SOM clustering analysis. The demonstrative data sets, the manufacturers around Taichung County in Taiwan, were analyzed for verifying the practicability of the proposed model. The analyzed results indicate that GeoSOM is suitable for evaluating spatial industrial cluster.

Regional patterns of earthquake-triggered landslides and their relation to ground motion

NASA Astrophysics Data System (ADS)

Meunier, Patrick; Hovius, Niels; Haines, A. John

2007-10-01

We have documented patterns of landsliding associated with large earthquakes on three thrust faults: the Northridge earthquake in California, Chi-Chi earthquake in Taiwan, and two earthquakes on the Ramu-Markham fault bounding the Finisterre Mountains of Papua New Guinea. In each case, landslide densities are shown to be greatest in the area of strongest ground acceleration and to decay with distance from the epicenter. In California and Taiwan, the density of co-seismic landslides is linearly and highly correlated with both the vertical and horizontal components of measured peak ground acceleration. Based on this observation, we derive an expression for the spatial variation of landslide density analogous with regional seismic attenuation laws. In its general form, this expression applies to our three examples, and we determine best fit values for individual cases. Our findings open a window on the construction of shake maps from geomorphic observations for earthquakes in non-instrumented regions.

Cosmology with void-galaxy correlations.

PubMed

Hamaus, Nico; Wandelt, Benjamin D; Sutter, P M; Lavaux, Guilhem; Warren, Michael S

2014-01-31

Galaxy bias, the unknown relationship between the clustering of galaxies and the underlying dark matter density field is a major hurdle for cosmological inference from large-scale structure. While traditional analyses focus on the absolute clustering amplitude of high-density regions mapped out by galaxy surveys, we propose a relative measurement that compares those to the underdense regions, cosmic voids. On the basis of realistic mock catalogs we demonstrate that cross correlating galaxies and voids opens up the possibility to calibrate galaxy bias and to define a static ruler thanks to the observable geometric nature of voids. We illustrate how the clustering of voids is related to mass compensation and show that volume-exclusion significantly reduces the degree of stochasticity in their spatial distribution. Extracting the spherically averaged distribution of galaxies inside voids from their cross correlations reveals a remarkable concordance with the mass-density profile of voids.

Surface Current Density Mapping for Identification of Gastric Slow Wave Propagation

PubMed Central

Bradshaw, L. A.; Cheng, L. K.; Richards, W. O.; Pullan, A. J.

2009-01-01

The magnetogastrogram records clinically relevant parameters of the electrical slow wave of the stomach noninvasively. Besides slow wave frequency, gastric slow wave propagation velocity is a potentially useful clinical indicator of the state of health of gastric tissue, but it is a difficult parameter to determine from noninvasive bioelectric or biomagnetic measurements. We present a method for computing the surface current density (SCD) from multichannel magnetogastrogram recordings that allows computation of the propagation velocity of the gastric slow wave. A moving dipole source model with hypothetical as well as realistic biomagnetometer parameters demonstrates that while a relatively sparse array of magnetometer sensors is sufficient to compute a single average propagation velocity, more detailed information about spatial variations in propagation velocity requires higher density magnetometer arrays. Finally, the method is validated with simultaneous MGG and serosal EMG measurements in a porcine subject. PMID:19403355

Laser absorption spectroscopy for measurement of He metastable atoms of a microhollow cathode plasma

NASA Astrophysics Data System (ADS)

Ueno, Keisuke; Kamebuchi, Kenta; Kakutani, Jiro; Matsuoka, Leo; Namba, Shinichi; Fujii, Keisuke; Shikama, Taiichi; Hasuo, Masahiro

2018-01-01

We generated a 0.3-mm-diameter DC, hollow-cathode helium discharge in a gas pressure range of 10-80 kPa. In discharge plasmas, we measured position-dependent laser absorption spectra for helium 23S1-23P0 transition with a spatial resolution of 55 µm. From the results of the analysis of the measured spectra using Voigt functions and including both the Doppler and collision broadening, we produced two-dimensional maps of the metastable 23S1 atomic densities and gas temperatures of the plasmas. We found that, at all pressures, the gas temperatures were approximately uniform in space with values in the range of 400-1500 K and the 23S1 atomic densities were ˜1019 m-3. We also found that the two-dimensional density distribution profiles became ring-shaped at high gas pressures, which is qualitatively consistent with the two-dimensional fluid simulation results.

Image and in situ data integration to derive sawgrass density for surface flow modelling in the Everglades, Florida, USA

USGS Publications Warehouse

Jones, J.W.

2000-01-01

The US Geological Survey is building models of the Florida Everglades to be used in managing south Florida surface water flows for habitat restoration and maintenance. Because of the low gradients in the Everglades, vegetation structural characteristics are very important and greatly influence surface water flow and distribution. Vegetation density is being evaluated as an index of surface resistance to flow. Digital multispectral videography (DMSV) has been captured over several sites just before field collection of vegetation data. Linear regression has been used to establish a relationship between normalized difference vegetation index (NDVI) values computed from the DMSV and field-collected biomass and density estimates. Spatial analysis applied to the DMSV data indicates that thematic mapper (TM) resolution is at the limit required to capture land surface heterogeneity. The TM data collected close to the time of the DMSV will be used to derive a regional sawgrass density map.

Image and in situ data integration to derive sawgrass density for surface flow modelling in the Everglades, Florida, USA

USGS Publications Warehouse

Jones, J.W.

2001-01-01

The US Geological Survey is building models of the Florida Everglades to be used in managing south Florida surface water flows for habitat restoration and maintenance. Because of the low gradients in the Everglades, vegetation structural characteristics are very important and greatly influence surface water flow and distribution. Vegetation density is being evaluated as an index of surface resistance to flow. Digital multispectral videography (DMSV) has been captured over several sites just before field collection of vegetation data. Linear regression has been used to establish a relationship between normalized difference vegetation index (NDVI) values computed from the DMSV and field-collected biomass and density estimates. Spatial analysis applied to the DMSV data indicates that thematic mapper (TM) resolution is at the limit required to capture land surface heterogeneity. The TM data collected close to the time of the DMSV will be used to derive a regional sawgrass density map.

Integrating GIS with AHP and Fuzzy Logic to generate hand, foot and mouth disease hazard zonation (HFMD-HZ) model in Thailand

NASA Astrophysics Data System (ADS)

Samphutthanon, R.; Tripathi, N. K.; Ninsawat, S.; Duboz, R.

2014-12-01

The main objective of this research was the development of an HFMD hazard zonation (HFMD-HZ) model by applying AHP and Fuzzy Logic AHP methodologies for weighting each spatial factor such as disease incidence, socio-economic and physical factors. The outputs of AHP and FAHP were input into a Geographic Information Systems (GIS) process for spatial analysis. 14 criteria were selected for analysis as important factors: disease incidence over 10 years from 2003 to 2012, population density, road density, land use and physical features. The results showed a consistency ratio (CR) value for these main criteria of 0.075427 for AHP, the CR for FAHP results was 0.092436. As both remained below the threshold of 0.1, the CR value were acceptable. After linking to actual geospatial data (disease incidence 2013) through spatial analysis by GIS for validation, the results of the FAHP approach were found to match more accurately than those of the AHP approach. The zones with the highest hazard of HFMD outbreaks were located in two main areas in central Muang Chiang Mai district including suburbs and Muang Chiang Rai district including the vicinity. The produced hazardous maps may be useful for organizing HFMD protection plans.

An Evaluation of Population Density Mapping and Built up Area Estimates in Sri Lanka Using Multiple Methodologies

NASA Astrophysics Data System (ADS)

Engstrom, R.; Soundararajan, V.; Newhouse, D.

2017-12-01

In this study we examine how well multiple population density and built up estimates that utilize satellite data compare in Sri Lanka. The population relationship is examined at the Gram Niladhari (GN) level, the lowest administrative unit in Sri Lanka from the 2011 census. For this study we have two spatial domains, the whole country and a 3,500km2 sub-sample, for which we have complete high spatial resolution imagery coverage. For both the entire country and the sub-sample we examine how consistent are the existing publicly available measures of population constructed from satellite imagery at predicting population density? For just the sub-sample we examine how well do a suite of values derived from high spatial resolution satellite imagery predict population density and how does our built up area estimate compare to other publicly available estimates. Population measures were obtained from the Sri Lankan census, and were downloaded from Facebook, WorldPoP, GPW, and Landscan. Percentage built-up area at the GN level was calculated from three sources: Facebook, Global Urban Footprint (GUF), and the Global Human Settlement Layer (GHSL). For the sub-sample we have derived a variety of indicators from the high spatial resolution imagery. Using deep learning convolutional neural networks, an object oriented, and a non-overlapping block, spatial feature approach. Variables calculated include: cars, shadows (a proxy for building height), built up area, and buildings, roof types, roads, type of agriculture, NDVI, Pantex, and Histogram of Oriented Gradients (HOG) and others. Results indicate that population estimates are accurate at the higher, DS Division level but not necessarily at the GN level. Estimates from Facebook correlated well with census population (GN correlation of 0.91) but measures from GPW and WorldPop are more weakly correlated (0.64 and 0.34). Estimates of built-up area appear to be reliable. In the 32 DSD-subsample, Facebook's built- up area measure is highly correlated with our built-up measure (correlation of 0.9). Preliminary regression results based on variables selected from Lasso-regressions indicate that satellite indicators have exceptionally strong predictive power in predicting GN level population level and density with an out of sample r-squared of 0.75 and 0.72 respectively.

Fine-scale habitat use of reintroduced black-footed ferrets on prairie dog colonies in New Mexico

USGS Publications Warehouse

Chipault, Jennifer G.; Biggins, Dean E.; Detling, James K.; Long, Dustin H.; Reich, Robin M.

2012-01-01

Black-footed ferrets (Mustela nigripes) are among the most endangered animals in North America. Reintroductions of captive-born ferrets onto prairie dog (Cynomys spp.) colonies are crucial to the conservation of the species. In September 2007, captive-born ferrets were released on a black-tailed prairie dog (Cynomys ludovicianus) colony at the Vermejo Park Ranch, New Mexico. Ferret kits experimentally released in areas of comparatively low and high prairie dog burrow densities were located via spotlight surveys. Some maturing ferret kits were subsequently translocated to areas of low and high burrow densities on nearby prairie dog colonies. For 2 months, fine-scale habitat use was quantified by mapping all burrow openings within a 30-m radius of each ferret location. Spatial statistics accounted for autocorrelation in the burrow densities in areas used by ferrets. It was hypothesized that ferrets would select areas of high burrow densities within colonies; however, burrow densities in areas used by ferrets were generally similar to the available burrow densities. Because ferrets used areas with burrow densities similar to densities available at the colony level and because of the potential energetic benefits for ferrets using areas with high burrow densities, releasing ferrets on colonies with high burrow densities might increase reintroduction success.

Image enhancement by non-linear extrapolation in frequency space

NASA Technical Reports Server (NTRS)

Anderson, Charles H. (Inventor); Greenspan, Hayit K. (Inventor)

1998-01-01

An input image is enhanced to include spatial frequency components having frequencies higher than those in an input image. To this end, an edge map is generated from the input image using a high band pass filtering technique. An enhancing map is subsequently generated from the edge map, with the enhanced map having spatial frequencies exceeding an initial maximum spatial frequency of the input image. The enhanced map is generated by applying a non-linear operator to the edge map in a manner which preserves the phase transitions of the edges of the input image. The enhanced map is added to the input image to achieve a resulting image having spatial frequencies greater than those in the input image. Simplicity of computations and ease of implementation allow for image sharpening after enlargement and for real-time applications such as videophones, advanced definition television, zooming, and restoration of old motion pictures.

Mapping standing dead trees (snags) in the aftermath of the 2013 Rim Fire using airborne LiDAR data.

NASA Astrophysics Data System (ADS)

Casas Planes, Á.; Garcia-Alonso, M.; Koltunov, A.; Ustin, S.; Falk, M.; Ramirez, C.; Siegel, R.

2014-12-01

Abundance and spatial distribution of standing dead trees (snags) are key indicators of forest biodiversity and ecosystem health and represent a critical component of habitat for various wildlife species, including the great grey owl and the black-backed woodpecker. In this work we assess the potential of light detection and ranging (LiDAR) to discriminate snags from the live trees and map their distribution. The study area encompasses the burn perimeter of the Rim Fire, the third largest wildfire in California's recorded history (~104.000 ha) and represents a heterogeneous mosaic of mixed conifer forests, hardwood, and meadows. The snags mapping procedure is based on a 3D single tree detection using a Watershed algorithm and the extraction of height and intensity metrics within each segment. Variables selected using Gaussian processes form a feature space for a classifier to distinguish between dead trees and live trees. Finally, snag density and snag diameter classes that are relevant for avian species are mapped. This work shows the use of LiDAR metrics to quantify ecological variables related to the vertical heterogeneity of the forest canopy that are important in the identification of snags, for example, fractional cover. We observed that intensity-related variables are critical to the successful identification of snags and their distribution. Our study highlights the importance of high-density LiDAR for characterizing the forest structural variables that contribute to the assessment of wildlife habitat suitability.

Comparison of spatial association approaches for landscape mapping of soil organic carbon stocks

NASA Astrophysics Data System (ADS)

Miller, B. A.; Koszinski, S.; Wehrhan, M.; Sommer, M.

2015-03-01

The distribution of soil organic carbon (SOC) can be variable at small analysis scales, but consideration of its role in regional and global issues demands the mapping of large extents. There are many different strategies for mapping SOC, among which is to model the variables needed to calculate the SOC stock indirectly or to model the SOC stock directly. The purpose of this research is to compare direct and indirect approaches to mapping SOC stocks from rule-based, multiple linear regression models applied at the landscape scale via spatial association. The final products for both strategies are high-resolution maps of SOC stocks (kg m-2), covering an area of 122 km2, with accompanying maps of estimated error. For the direct modelling approach, the estimated error map was based on the internal error estimations from the model rules. For the indirect approach, the estimated error map was produced by spatially combining the error estimates of component models via standard error propagation equations. We compared these two strategies for mapping SOC stocks on the basis of the qualities of the resulting maps as well as the magnitude and distribution of the estimated error. The direct approach produced a map with less spatial variation than the map produced by the indirect approach. The increased spatial variation represented by the indirect approach improved R2 values for the topsoil and subsoil stocks. Although the indirect approach had a lower mean estimated error for the topsoil stock, the mean estimated error for the total SOC stock (topsoil + subsoil) was lower for the direct approach. For these reasons, we recommend the direct approach to modelling SOC stocks be considered a more conservative estimate of the SOC stocks' spatial distribution.

Comparison of spatial association approaches for landscape mapping of soil organic carbon stocks

NASA Astrophysics Data System (ADS)

Miller, B. A.; Koszinski, S.; Wehrhan, M.; Sommer, M.

2014-11-01

The distribution of soil organic carbon (SOC) can be variable at small analysis scales, but consideration of its role in regional and global issues demands the mapping of large extents. There are many different strategies for mapping SOC, among which are to model the variables needed to calculate the SOC stock indirectly or to model the SOC stock directly. The purpose of this research is to compare direct and indirect approaches to mapping SOC stocks from rule-based, multiple linear regression models applied at the landscape scale via spatial association. The final products for both strategies are high-resolution maps of SOC stocks (kg m-2), covering an area of 122 km2, with accompanying maps of estimated error. For the direct modelling approach, the estimated error map was based on the internal error estimations from the model rules. For the indirect approach, the estimated error map was produced by spatially combining the error estimates of component models via standard error propagation equations. We compared these two strategies for mapping SOC stocks on the basis of the qualities of the resulting maps as well as the magnitude and distribution of the estimated error. The direct approach produced a map with less spatial variation than the map produced by the indirect approach. The increased spatial variation represented by the indirect approach improved R2 values for the topsoil and subsoil stocks. Although the indirect approach had a lower mean estimated error for the topsoil stock, the mean estimated error for the total SOC stock (topsoil + subsoil) was lower for the direct approach. For these reasons, we recommend the direct approach to modelling SOC stocks be considered a more conservative estimate of the SOC stocks' spatial distribution.

The spatial distribution of pet dogs and pet cats on the island of Ireland

PubMed Central

2011-01-01

Background There is considerable international research regarding the link between human demographics and pet ownership. In several international studies, pet ownership was associated with household demographics including: the presence of children in the household, urban/rural location, level of education and age/family structure. What is lacking across all these studies, however, is an understanding of how these pets are spatially distributed throughout the regions under study. This paper describes the spatial distribution of pet dog and pet cat owning households on the island of Ireland. Results In 2006, there were an estimated 640,620 pet dog owning households and 215,542 pet cat owning households in Ireland. These estimates are derived from logistic regression modelling, based on household composition to determine pet dog ownership and the type of house to determine pet cat ownership. Results are presented using chloropleth maps. There is a higher density of pet dog owning households in the east of Ireland and in the cities than the west of Ireland and rural areas. However, in urban districts there are a lower proportion of households owning pet dogs than in rural districts. There are more households with cats in the urban areas, but the proportion of households with cats is greater in rural areas. Conclusions The difference in spatial distribution of dog ownership is a reflection of a generally higher density of households in the east of Ireland and in major cities. The higher proportion of ownership in the west is understandable given the higher proportion of farmers and rural dwellings in this area. Spatial representation allows us to visualise the impact of human household distribution on the density of both pet dogs and pet cats on the island of Ireland. This information can be used when analysing risk of disease spread, for market research and for instigating veterinary care. PMID:21663606

The spatial distribution of pet dogs and pet cats on the island of Ireland.

PubMed

Downes, Martin J; Clegg, Tracy A; Collins, Daniel M; McGrath, Guy; More, Simon J

2011-06-10

There is considerable international research regarding the link between human demographics and pet ownership. In several international studies, pet ownership was associated with household demographics including: the presence of children in the household, urban/rural location, level of education and age/family structure. What is lacking across all these studies, however, is an understanding of how these pets are spatially distributed throughout the regions under study. This paper describes the spatial distribution of pet dog and pet cat owning households on the island of Ireland. In 2006, there were an estimated 640,620 pet dog owning households and 215,542 pet cat owning households in Ireland. These estimates are derived from logistic regression modelling, based on household composition to determine pet dog ownership and the type of house to determine pet cat ownership. Results are presented using chloropleth maps. There is a higher density of pet dog owning households in the east of Ireland and in the cities than the west of Ireland and rural areas. However, in urban districts there are a lower proportion of households owning pet dogs than in rural districts. There are more households with cats in the urban areas, but the proportion of households with cats is greater in rural areas. The difference in spatial distribution of dog ownership is a reflection of a generally higher density of households in the east of Ireland and in major cities. The higher proportion of ownership in the west is understandable given the higher proportion of farmers and rural dwellings in this area. Spatial representation allows us to visualise the impact of human household distribution on the density of both pet dogs and pet cats on the island of Ireland. This information can be used when analysing risk of disease spread, for market research and for instigating veterinary care.

The Effect of Rainfall Measurement Technique and Its Spatiotemporal Resolution on Discharge Predictions in the Netherlands

NASA Astrophysics Data System (ADS)

Uijlenhoet, R.; Brauer, C.; Overeem, A.; Sassi, M.; Rios Gaona, M. F.

2014-12-01

Several rainfall measurement techniques are available for hydrological applications, each with its own spatial and temporal resolution. We investigated the effect of these spatiotemporal resolutions on discharge simulations in lowland catchments by forcing a novel rainfall-runoff model (WALRUS) with rainfall data from gauges, radars and microwave links. The hydrological model used for this analysis is the recently developed Wageningen Lowland Runoff Simulator (WALRUS). WALRUS is a rainfall-runoff model accounting for hydrological processes relevant to areas with shallow groundwater (e.g. groundwater-surface water feedback). Here, we used WALRUS for case studies in a freely draining lowland catchment and a polder with controlled water levels. We used rain gauge networks with automatic (hourly resolution but low spatial density) and manual gauges (high spatial density but daily resolution). Operational (real-time) and climatological (gauge-adjusted) C-band radar products and country-wide rainfall maps derived from microwave link data from a cellular telecommunication network were also used. Discharges simulated with these different inputs were compared to observations. We also investigated the effect of spatiotemporal resolution with a high-resolution X-band radar data set for catchments with different sizes. Uncertainty in rainfall forcing is a major source of uncertainty in discharge predictions, both with lumped and with distributed models. For lumped rainfall-runoff models, the main source of input uncertainty is associated with the way in which (effective) catchment-average rainfall is estimated. When catchments are divided into sub-catchments, rainfall spatial variability can become more important, especially during convective rainfall events, leading to spatially varying catchment wetness and spatially varying contribution of quick flow routes. Improving rainfall measurements and their spatiotemporal resolution can improve the performance of rainfall-runoff models, indicating their potential for reducing flood damage through real-time control.

Visualization of spatial patterns and temporal trends for aerial surveillance of illegal oil discharges in western Canadian marine waters.

PubMed

Serra-Sogas, Norma; O'Hara, Patrick D; Canessa, Rosaline; Keller, Peter; Pelot, Ronald

2008-05-01

This paper examines the use of exploratory spatial analysis for identifying hotspots of shipping-based oil pollution in the Pacific Region of Canada's Exclusive Economic Zone. It makes use of data collected from fiscal years 1997/1998 to 2005/2006 by the National Aerial Surveillance Program, the primary tool for monitoring and enforcing the provisions imposed by MARPOL 73/78. First, we present oil spill data as points in a "dot map" relative to coastlines, harbors and the aerial surveillance distribution. Then, we explore the intensity of oil spill events using the Quadrat Count method, and the Kernel Density Estimation methods with both fixed and adaptive bandwidths. We found that oil spill hotspots where more clearly defined using Kernel Density Estimation with an adaptive bandwidth, probably because of the "clustered" distribution of oil spill occurrences. Finally, we discuss the importance of standardizing oil spill data by controlling for surveillance effort to provide a better understanding of the distribution of illegal oil spills, and how these results can ultimately benefit a monitoring program.

Atomic oxygen between 80 and 120 km: Evidence for a rapid spatial variation in vertical transport near the ionosphere

NASA Technical Reports Server (NTRS)

Donahue, T. M.; Wasser, B.

1977-01-01

Analysis of OGO-6 OI green line photometer results was carried out for 8 cases when the alignment of the spacecraft was such that local emission rates could be determined below the altitude of maximum emission and down to about 80 km. Results show a variation on a scale of 6 deg to 8 deg in latitude between regions where the emission rate increases rapidly between 90 and 95 km and regions where it increases slowly from 80 km to 95 km. Latitude-altitude maps of iso-emissivity contours and iso-density contours for oxygen concentration are presented. The latter are computed under 3 assumptions concerning excitation mechanisms. Comparisons of the spatial variations of oxygen density with the results of a time dependent theory suggest the regions of strong downward transport alternate on a scale of about 1000 km with regions of weak transport near 90 km. In the first case conversion of O to O3 at night appears to be overwhelmed by downward transport of O.

Crustal thickness of Antarctica estimated using data from gravimetric satellites

NASA Astrophysics Data System (ADS)

Llubes, Muriel; Seoane, Lucia; Bruinsma, Sean; Rémy, Frédérique

2018-04-01

Computing a better crustal thickness model is still a necessary improvement in Antarctica. In this remote continent where almost all the bedrock is covered by the ice sheet, seismic investigations do not reach a sufficient spatial resolution for geological and geophysical purposes. Here, we present a global map of Antarctic crustal thickness computed from space gravity observations. The DIR5 gravity field model, built from GOCE and GRACE gravimetric data, is inverted with the Parker-Oldenburg iterative algorithm. The BEDMAP products are used to estimate the gravity effect of the ice and the rocky surface. Our result is compared to crustal thickness calculated from seismological studies and the CRUST1.0 and AN1 models. Although the CRUST1.0 model shows a very good agreement with ours, its spatial resolution is larger than the one we obtain with gravimetric data. Finally, we compute a model in which the crust-mantle density contrast is adjusted to fit the Moho depth from the CRUST1.0 model. In East Antarctica, the resulting density contrast clearly shows higher values than in West Antarctica.

Identification of irrigated crop types from ERTS-1 density contour maps and color infrared aerial photography. [Wyoming

NASA Technical Reports Server (NTRS)

Marrs, R. W.; Evans, M. A.

1974-01-01

The author has identified the following significant results. The crop types of a Great Plains study area were mapped from color infrared aerial photography. Each field was positively identified from field checks in the area. Enlarged (50x) density contour maps were constructed from three ERTS-1 images taken in the summer of 1973. The map interpreted from the aerial photography was compared to the density contour maps and the accuracy of the ERTS-1 density contour map interpretations were determined. Changes in the vegetation during the growing season and harvest periods were detectable on the ERTS-1 imagery. Density contouring aids in the detection of such charges.

Method for removing atomic-model bias in macromolecular crystallography

DOEpatents

Terwilliger, Thomas C [Santa Fe, NM

2006-08-01

Structure factor bias in an electron density map for an unknown crystallographic structure is minimized by using information in a first electron density map to elicit expected structure factor information. Observed structure factor amplitudes are combined with a starting set of crystallographic phases to form a first set of structure factors. A first electron density map is then derived and features of the first electron density map are identified to obtain expected distributions of electron density. Crystallographic phase probability distributions are established for possible crystallographic phases of reflection k, and the process is repeated as k is indexed through all of the plurality of reflections. An updated electron density map is derived from the crystallographic phase probability distributions for each one of the reflections. The entire process is then iterated to obtain a final set of crystallographic phases with minimum bias from known electron density maps.

Spatial analysis of crime incidence and adolescent physical activity.

PubMed

Robinson, Alyssa I; Carnes, Fei; Oreskovic, Nicolas M

2016-04-01

Adolescents do not achieve recommended levels of physical activity. Crime is believed to be a barrier to physical activity among youth, but findings are inconsistent. This study compares the spatial distribution of crime incidences and moderate-to-vigorous physical activity (MVPA) among adolescents in Massachusetts between 2011 and 2012, and examines the correlation between crime and MVPA. Eighty adolescents provided objective physical activity (accelerometer) and location (Global Positioning Systems) data. Crime report data were obtained from the city police department. Data were mapped using geographic information systems, and crime and MVPA densities were calculated using kernel density estimations. Spearman's correlation tested for associations between crime and MVPA. Overall, 1694 reported crimes and 16,702min of MVPA were included in analyses. A strong positive correlation was present between crime and adolescent MVPA (ρ=0.72, p<0.0001). Crime remained positively associated with MVPA in locations falling within the lowest quartile (ρ=0.43, p<0.0001) and highest quartile (ρ=0.32, p<0.0001) of crime density. This study found a strong positive association between crime and adolescent MVPA, despite research suggesting the opposite relationship. This counterintuitive finding may be explained by the logic of a common destination: neighborhood spaces which are desirable destinations and promote physical activity may likewise attract crime. Copyright © 2016 Elsevier Inc. All rights reserved.

Spatial Analysis of Crime Incidence and Adolescent Physical Activity

PubMed Central

Robinson, Alyssa I.; Carnes, Fei

2016-01-01

Adolescents do not achieve recommended levels of physical activity. Crime is believed to be a barrier to physical activity among youth, but findings are inconsistent. This study compares the spatial distribution of crime incidences and moderate-to-vigorous physical activity (MVPA) among adolescents in Massachusetts between 2011 and 2012, and examines the correlation between crime and MVPA. Eighty adolescents provided objective physical activity (accelerometer) and location (Global Positioning Systems) data. Crime report data were obtained from the city police department. Data were mapped using geographic information systems, and crime and MVPA densities were calculated using kernel density estimations. Spearman’s correlation tested for associations between crime and MVPA. Overall, 1,694 reported crimes and 16,702 minutes of MVPA were included in analyses. A strong positive correlation was present between crime and adolescent MVPA (ρ=0.72, p<0.0001). Crime remained positively associated with MVPA in locations falling within the lowest quartile (ρ=0.43, p<0.0001) and highest quartile (ρ=0.32, p<0.0001) of crime density. This study found a strong positive association between crime and adolescent MVPA, despite research suggesting the opposite relationship. This counterintuitive finding may be explained by the logic of a common destination: neighborhood spaces which are desirable destinations and promote physical activity may likewise attract crime. PMID:26820115

Functional Equivalence of Spatial Images from Touch and Vision: Evidence from Spatial Updating in Blind and Sighted Individuals

PubMed Central

Giudice, Nicholas A.; Betty, Maryann R.; Loomis, Jack M.

2012-01-01

This research examines whether visual and haptic map learning yield functionally equivalent spatial images in working memory, as evidenced by similar encoding bias and updating performance. In three experiments, participants learned four-point routes either by seeing or feeling the maps. At test, blindfolded participants made spatial judgments about the maps from imagined perspectives that were either aligned or misaligned with the maps as represented in working memory. Results from Experiments 1 and 2 revealed a highly similar pattern of latencies and errors between visual and haptic conditions. These findings extend the well known alignment biases for visual map learning to haptic map learning, provide further evidence of haptic updating, and most importantly, show that learning from the two modalities yields very similar performance across all conditions. Experiment 3 found the same encoding biases and updating performance with blind individuals, demonstrating that functional equivalence cannot be due to visual recoding and is consistent with an amodal hypothesis of spatial images. PMID:21299331

Demonstration of Hadoop-GIS: A Spatial Data Warehousing System Over MapReduce.

PubMed

Aji, Ablimit; Sun, Xiling; Vo, Hoang; Liu, Qioaling; Lee, Rubao; Zhang, Xiaodong; Saltz, Joel; Wang, Fusheng

2013-11-01

The proliferation of GPS-enabled devices, and the rapid improvement of scientific instruments have resulted in massive amounts of spatial data in the last decade. Support of high performance spatial queries on large volumes data has become increasingly important in numerous fields, which requires a scalable and efficient spatial data warehousing solution as existing approaches exhibit scalability limitations and efficiency bottlenecks for large scale spatial applications. In this demonstration, we present Hadoop-GIS - a scalable and high performance spatial query system over MapReduce. Hadoop-GIS provides an efficient spatial query engine to process spatial queries, data and space based partitioning, and query pipelines that parallelize queries implicitly on MapReduce. Hadoop-GIS also provides an expressive, SQL-like spatial query language for workload specification. We will demonstrate how spatial queries are expressed in spatially extended SQL queries, and submitted through a command line/web interface for execution. Parallel to our system demonstration, we explain the system architecture and details on how queries are translated to MapReduce operators, optimized, and executed on Hadoop. In addition, we will showcase how the system can be used to support two representative real world use cases: large scale pathology analytical imaging, and geo-spatial data warehousing.

Spatiotemporal patterns of duck nest density and predation risk: a multi-scale analysis of 18 years and more than 10,000 nests

USGS Publications Warehouse

Ringelman, Kevin M.; Eadie, John M.; Ackerman, Joshua T.; Sih, Andrew; Loughman, Daniel L.; Yarris, Gregory S.; Oldenburger, Shaun L.; McLandress, M. Robert

2017-01-01

Many avian species are behaviorally-plastic in selecting nest sites, and may shift to new locations or habitats following an unsuccessful breeding attempt. If there is predictable spatial variation in predation risk, the process of many individuals using prior experience to adaptively change nest sites may scale up to create shifting patterns of nest density at a population level. We used 18 years of waterfowl nesting data to assess whether there were areas of consistently high or low predation risk, and whether low-risk areas increased, and high-risk areas decreased in nest density the following year. We created kernel density maps of successful and unsuccessful nests in consecutive years and found no correlation in predation risk and no evidence for adaptive shifts, although nest density was correlated between years. We also examined between-year correlations in nest density and nest success at three smaller spatial scales: individual nesting fields (10–28 ha), 16-ha grid cells and 4-ha grid cells. Here, results were similar across all scales: we found no evidence for year-to-year correlation in nest success but found strong evidence that nest density was correlated between years, and areas of high nest success increased in nest density the following year. Prior research in this system has demonstrated that areas of high nest density have higher nest success, and taken together, our results suggest that ducks may adaptively select nest sites based on the local density of conspecifics, rather than the physical location of last year's nest. In unpredictable environments, current cues, such as the presence of active conspecific nests, may be especially useful in selecting nest sites. The cues birds use to select breeding locations and successfully avoid predators deserve continued attention, especially in systems of conservation concern.

Attention modulates spatial priority maps in the human occipital, parietal and frontal cortices

PubMed Central

Sprague, Thomas C.; Serences, John T.

2014-01-01

Computational theories propose that attention modulates the topographical landscape of spatial ‘priority’ maps in regions of visual cortex so that the location of an important object is associated with higher activation levels. While single-unit recording studies have demonstrated attention-related increases in the gain of neural responses and changes in the size of spatial receptive fields, the net effect of these modulations on the topography of region-level priority maps has not been investigated. Here, we used fMRI and a multivariate encoding model to reconstruct spatial representations of attended and ignored stimuli using activation patterns across entire visual areas. These reconstructed spatial representations reveal the influence of attention on the amplitude and size of stimulus representations within putative priority maps across the visual hierarchy. Our results suggest that attention increases the amplitude of stimulus representations in these spatial maps, particularly in higher visual areas, but does not substantively change their size. PMID:24212672

MAVEN/IUVS Apoapse Observations of the Martian FUV Dayglow

NASA Astrophysics Data System (ADS)

Correira, J.; Evans, J. S.; Stevens, M. H.; Schneider, N. M.; Stewart, I. F.; Deighan, J.; Jain, S.; Chaffin, M.; Crismani, M. M. J.; McClintock, B.; Holsclaw, G.; Lefèvre, F.; Lo, D.; Stiepen, A.; Clarke, J. T.; Mahaffy, P. R.; Bougher, S. W.; Bell, J. M.; Jakosky, B. M.

2015-12-01

We present FUV data (115 - 190 nm) from MAVEN/IUVS apoapse mode observations for the Oct 2014 through Feb 2015 time period. During apoapse mode the highly elliptical orbit of MAVEN allows for up to four apoapse disk images by IUVS per day. Maps of FUV feature intensities and intensity ratios as well as derived CO/CO2 and O/CO2 column density ratios will be shown. Column density ratios are derived from lookup tables created using the Atmospheric Ultraviolet Radiance Integrated Code [Strickland et al., 1999] in conjunction with observed intensity ratios. Column density ratios provide a measure of composition changes in the Martian atmosphere. Due to MAVEN's orbital geometry the observations from this time period focus on the southern hemisphere. The broad view provided by apoapse observations allows for the investigation of spatial and temporal variations (both long term and local time) of the atmospheric composition (via the column density ratios). IUVS FUV intensities and derived column density ratios will also be compared with model results from Mars Global Ionosphere/Thermosphere Model (MGITM) and the Mars Climate Database (MCD).

Laser ultrasonics for bulk-density distribution measurement on green ceramic tiles

NASA Astrophysics Data System (ADS)

Revel, G. M.; Cavuto, A.; Pandarese, G.

2016-10-01

In this paper a Laser Ultrasonics (LUT) system is developed and applied to measure bulk density distribution of green ceramic tiles, which are porous materials with low heat conductivity. Bulk density of green ceramic bodies is a fundamental parameter to be kept under control in the industrial production of ceramic tiles. The LUT system proposed is based on a Nd:YAG pulsed laser for excitation and an air-coupled electro-capacitive transducer for detection. The paper reports experimental apparent bulk-density measurements on white ceramic bodies after a calibration procedures. The performances observed are better than those previously achieved by authors using air-coupled ultrasonic probes for both emission and detection, allowing to reduce average uncertainty down to about ±6 kg/m3 (±0.3%), thanks to the increase in excitation efficiency and lateral resolution, while maintaining potential flexibility for on-line application. The laser ultrasonic procedure proposed is available for both on-line and off-line application. In this last case it is possible to obtain bulk density maps with high spatial resolution by a 2D scan without interrupting the production process.

Spatial and Temporal Mapping of the Evolution of the Miami-Fort Lauderdale-West Palm Beach Metropolitan Statistical Area (MSA)

NASA Astrophysics Data System (ADS)

Rochelo, Mark

Urbanization is a fundamental reality in the developed and developing countries around the world creating large concentrations of the population centering on cities and urban centers. Cities can offer many opportunities for those residing there, including infrastructure, health services, rescue services and more. The living space density of cities allows for the opportunity of more effective and environmentally friendly housing, transportation and resources. Cities play a vital role in generating economic production as entities by themselves and as a part of larger urban complex. The benefits can provide for extraordinary amount of people, but only if proper planning and consideration is undertaken. Global urbanization is a progressive evolution, unique in spatial location while consistent to an overall growth pattern and trend. Remotely sensing these patterns from the last forty years of space borne satellites to understand how urbanization has developed is important to understanding past growth as well as planning for the future. Imagery from the Landsat sensor program provides the temporal component, it was the first satellite launched in 1972, providing appropriate spatial resolution needed to cover a large metropolitan statistical area to monitor urban growth and change on a large scale. This research maps the urban spatial and population growth over the Miami - Fort Lauderdale - West Palm Beach Metropolitan Statistical Area (MSA) covering Miami-Dade, Broward, and Palm Beach counties in Southeast Florida from 1974 to 2010 using Landsat imagery. Supervised Maximum Likelihood classification was performed with a combination of spectral and textural training fields employed in ERDAS Image 2014 to classify the images into urban and non-urban areas. Dasymetric mapping of the classification results were combined with census tract data then created a coherent depiction of the Miami - Fort Lauderdale - West Palm Beach MSA. Static maps and animated files were created from the final datasets for enhanced visualizations and understanding of the MSA evolution from 60-meter resolution remotely sensed Landsat images. The simplified methodology will create a database for urban planning and population growth as well as future work in this area.

One perspective on spatial variability in geologic mapping

USGS Publications Warehouse

Markewich, H.W.; Cooper, S.C.

1991-01-01

This paper discusses some of the differences between geologic mapping and soil mapping, and how the resultant maps are interpreted. The role of spatial variability in geologic mapping is addressed only indirectly because in geologic mapping there have been few attempts at quantification of spatial differences. This is largely because geologic maps deal with temporal as well as spatial variability and consider time, age, and origin, as well as composition and geometry. Both soil scientists and geologists use spatial variability to delineate mappable units; however, the classification systems from which these mappable units are defined differ greatly. Mappable soil units are derived from systematic, well-defined, highly structured sets of taxonomic criteria; whereas mappable geologic units are based on a more arbitrary heirarchy of categories that integrate many features without strict values or definitions. Soil taxonomy is a sorting tool used to reduce heterogeneity between soil units. Thus at the series level, soils in any one series are relatively homogeneous because their range of properties is small and well-defined. Soil maps show the distribution of soils on the land surface. Within a map area, soils, which are often less than 2 m thick, show a direct correlation to topography and to active surface processes as well as to parent material.