RipleyGUI: software for analyzing spatial patterns in 3D cell distributions
Hansson, Kristin; Jafari-Mamaghani, Mehrdad; Krieger, Patrik
2013-01-01
The true revolution in the age of digital neuroanatomy is the ability to extensively quantify anatomical structures and thus investigate structure-function relationships in great detail. To facilitate the quantification of neuronal cell patterns we have developed RipleyGUI, a MATLAB-based software that can be used to detect patterns in the 3D distribution of cells. RipleyGUI uses Ripley's K-function to analyze spatial distributions. In addition the software contains statistical tools to determine quantitative statistical differences, and tools for spatial transformations that are useful for analyzing non-stationary point patterns. The software has a graphical user interface making it easy to use without programming experience, and an extensive user manual explaining the basic concepts underlying the different statistical tools used to analyze spatial point patterns. The described analysis tool can be used for determining the spatial organization of neurons that is important for a detailed study of structure-function relationships. For example, neocortex that can be subdivided into six layers based on cell density and cell types can also be analyzed in terms of organizational principles distinguishing the layers. PMID:23658544
Mining Co-Location Patterns with Clustering Items from Spatial Data Sets
NASA Astrophysics Data System (ADS)
Zhou, G.; Li, Q.; Deng, G.; Yue, T.; Zhou, X.
2018-05-01
The explosive growth of spatial data and widespread use of spatial databases emphasize the need for the spatial data mining. Co-location patterns discovery is an important branch in spatial data mining. Spatial co-locations represent the subsets of features which are frequently located together in geographic space. However, the appearance of a spatial feature C is often not determined by a single spatial feature A or B but by the two spatial features A and B, that is to say where A and B appear together, C often appears. We note that this co-location pattern is different from the traditional co-location pattern. Thus, this paper presents a new concept called clustering terms, and this co-location pattern is called co-location patterns with clustering items. And the traditional algorithm cannot mine this co-location pattern, so we introduce the related concept in detail and propose a novel algorithm. This algorithm is extended by join-based approach proposed by Huang. Finally, we evaluate the performance of this algorithm.
Spatio-temporal Analysis for New York State SPARCS Data
Chen, Xin; Wang, Yu; Schoenfeld, Elinor; Saltz, Mary; Saltz, Joel; Wang, Fusheng
2017-01-01
Increased accessibility of health data provides unique opportunities to discover spatio-temporal patterns of diseases. For example, New York State SPARCS (Statewide Planning and Research Cooperative System) data collects patient level detail on patient demographics, diagnoses, services, and charges for each hospital inpatient stay and outpatient visit. Such data also provides home addresses for each patient. This paper presents our preliminary work on spatial, temporal, and spatial-temporal analysis of disease patterns for New York State using SPARCS data. We analyzed spatial distribution patterns of typical diseases at ZIP code level. We performed temporal analysis of common diseases based on 12 years’ historical data. We then compared the spatial variations for diseases with different levels of clustering tendency, and studied the evolution history of such spatial patterns. Case studies based on asthma demonstrated that the discovered spatial clusters are consistent with prior studies. We visualized our spatial-temporal patterns as animations through videos. PMID:28815148
Development of a Geometric Spatial Visualization Tool
ERIC Educational Resources Information Center
Ganesh, Bibi; Wilhelm, Jennifer; Sherrod, Sonya
2009-01-01
This paper documents the development of the Geometric Spatial Assessment. We detail the development of this instrument which was designed to identify middle school students' strategies and advancement in understanding of four geometric concept domains (geometric spatial visualization, spatial projection, cardinal directions, and periodic patterns)…
Selective sweeps in growing microbial colonies
NASA Astrophysics Data System (ADS)
Korolev, Kirill S.; Müller, Melanie J. I.; Karahan, Nilay; Murray, Andrew W.; Hallatschek, Oskar; Nelson, David R.
2012-04-01
Evolutionary experiments with microbes are a powerful tool to study mutations and natural selection. These experiments, however, are often limited to the well-mixed environments of a test tube or a chemostat. Since spatial organization can significantly affect evolutionary dynamics, the need is growing for evolutionary experiments in spatially structured environments. The surface of a Petri dish provides such an environment, but a more detailed understanding of microbial growth on Petri dishes is necessary to interpret such experiments. We formulate a simple deterministic reaction-diffusion model, which successfully predicts the spatial patterns created by two competing species during colony expansion. We also derive the shape of these patterns analytically without relying on microscopic details of the model. In particular, we find that the relative fitness of two microbial strains can be estimated from the logarithmic spirals created by selective sweeps. The theory is tested with strains of the budding yeast Saccharomyces cerevisiae for spatial competitions with different initial conditions and for a range of relative fitnesses. The reaction-diffusion model also connects the microscopic parameters like growth rates and diffusion constants with macroscopic spatial patterns and predicts the relationship between fitness in liquid cultures and on Petri dishes, which we confirmed experimentally. Spatial sector patterns therefore provide an alternative fitness assay to the commonly used liquid culture fitness assays.
Spatial pattern and ecological process in the coffee agroforestry system.
Perfecto, Ivette; Vandermeer, John
2008-04-01
The coffee agroforestry system provides an ideal platform for the study of spatial ecology. The uniform pattern of the coffee plants and shade trees allows for the study of pattern generation through intrinsic biological forces rather than extrinsic habitat patchiness. Detailed studies, focusing on a key mutualism between an ant (Azteca instabilis) and a scale insect (Coccus viridis), conducted in a 45-ha plot in a coffee agroforestry system have provided insights into (1) the quantitative evaluation of spatial pattern of the scale insect Coccus viridis on coffee bushes, (2) the mechanisms for the generation of patterns through the combination of local satellite ant nest formation and regional control from natural enemies, and (3) the consequences of the spatial pattern for the stability of predator-prey (host-parasitoid) systems, for a key coccinelid beetle preying on the scale insects and a phorid fly parasitoid parasitizing the ant.
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.
Dynamics of land change in India: a fine-scale spatial analysis
NASA Astrophysics Data System (ADS)
Meiyappan, P.; Roy, P. S.; Sharma, Y.; Jain, A. K.; Ramachandran, R.; Joshi, P. K.
2015-12-01
Land is scarce in India: India occupies 2.4% of worlds land area, but supports over 1/6th of worlds human and livestock population. This high population to land ratio, combined with socioeconomic development and increasing consumption has placed tremendous pressure on India's land resources for food, feed, and fuel. In this talk, we present contemporary (1985 to 2005) spatial estimates of land change in India using national-level analysis of Landsat imageries. Further, we investigate the causes of the spatial patterns of change using two complementary lines of evidence. First, we use statistical models estimated at macro-scale to understand the spatial relationships between land change patterns and their concomitant drivers. This analysis using our newly compiled extensive socioeconomic database at village level (~630,000 units), is 100x higher in spatial resolution compared to existing datasets, and covers over 200 variables. The detailed socioeconomic data enabled the fine-scale spatial analysis with Landsat data. Second, we synthesized information from over 130 survey based case studies on land use drivers in India to complement our macro-scale analysis. The case studies are especially useful to identify unobserved variables (e.g. farmer's attitude towards risk). Ours is the most detailed analysis of contemporary land change in India, both in terms of national extent, and the use of detailed spatial information on land change, socioeconomic factors, and synthesis of case studies.
Abnormalities of Object Visual Processing in Body Dysmorphic Disorder
Feusner, Jamie D.; Hembacher, Emily; Moller, Hayley; Moody, Teena D.
2013-01-01
Background Individuals with body dysmorphic disorder may have perceptual distortions for their appearance. Previous studies suggest imbalances in detailed relative to configural/holistic visual processing when viewing faces. No study has investigated the neural correlates of processing non-symptom-related stimuli. The objective of this study was to determine whether individuals with body dysmorphic disorder have abnormal patterns of brain activation when viewing non-face/non-body object stimuli. Methods Fourteen medication-free participants with DSM-IV body dysmorphic disorder and 14 healthy controls participated. We performed functional magnetic resonance imaging while participants matched photographs of houses that were unaltered, contained only high spatial frequency (high detail) information, or only low spatial frequency (low detail) information. The primary outcome was group differences in blood oxygen level-dependent signal changes. Results The body dysmorphic disorder group showed lesser activity in the parahippocampal gyrus, lingual gyrus, and precuneus for low spatial frequency images. There were greater activations in medial prefrontal regions for high spatial frequency images, although no significant differences when compared to a low-level baseline. Greater symptom severity was associated with lesser activity in dorsal occipital cortex and ventrolateral prefrontal cortex for normal and high spatial frequency images. Conclusions Individuals with body dysmorphic disorder have abnormal brain activation patterns when viewing objects. Hypoactivity in visual association areas for configural and holistic (low detail) elements and abnormal allocation of prefrontal systems for details is consistent with a model of imbalances in global vs. local processing. This may occur not only for appearance but also for general stimuli unrelated to their symptoms. PMID:21557897
Spatial Patterning of Newly-Inserted Material during Bacterial Cell Growth
NASA Astrophysics Data System (ADS)
Ursell, Tristan
2012-02-01
In the life cycle of a bacterium, rudimentary microscopy demonstrates that cell growth and elongation are essential characteristics of cellular reproduction. The peptidoglycan cell wall is the main load-bearing structure that determines both cell shape and overall size. However, simple imaging of cellular growth gives no indication of the spatial patterning nor mechanism by which material is being incorporated into the pre-existing cell wall. We employ a combination of high-resolution pulse-chase fluorescence microscopy, 3D computational microscopy, and detailed mechanistic simulations to explore how spatial patterning results in uniform growth and maintenance of cell shape. We show that growth is happening in discrete bursts randomly distributed over the cell surface, with a well-defined mean size and average rate. We further use these techniques to explore the effects of division and cell wall disrupting antibiotics, like cephalexin and A22, respectively, on the patterning of cell wall growth in E. coli. Finally, we explore the spatial correlation between presence of the bacterial actin-like cytoskeletal protein, MreB, and local cell wall growth. Together these techniques form a powerful method for exploring the detailed dynamics and involvement of antibiotics and cell wall-associated proteins in bacterial cell growth.[4pt] In collaboration with Kerwyn Huang, Stanford University.
Comparing spatial and temporal patterns of river water isotopes across networks
A detailed understanding of the spatial and temporal dynamics of water sources across river networks is central to managing the impacts of climate change. Because the stable isotope composition of precipitation varies geographically, variation in surface-water isotope signatures ...
Anthropogenic heat flux: advisable spatial resolutions when input data are scarce
NASA Astrophysics Data System (ADS)
Gabey, A. M.; Grimmond, C. S. B.; Capel-Timms, I.
2018-02-01
Anthropogenic heat flux (QF) may be significant in cities, especially under low solar irradiance and at night. It is of interest to many practitioners including meteorologists, city planners and climatologists. QF estimates at fine temporal and spatial resolution can be derived from models that use varying amounts of empirical data. This study compares simple and detailed models in a European megacity (London) at 500 m spatial resolution. The simple model (LQF) uses spatially resolved population data and national energy statistics. The detailed model (GQF) additionally uses local energy, road network and workday population data. The Fractions Skill Score (FSS) and bias are used to rate the skill with which the simple model reproduces the spatial patterns and magnitudes of QF, and its sub-components, from the detailed model. LQF skill was consistently good across 90% of the city, away from the centre and major roads. The remaining 10% contained elevated emissions and "hot spots" representing 30-40% of the total city-wide energy. This structure was lost because it requires workday population, spatially resolved building energy consumption and/or road network data. Daily total building and traffic energy consumption estimates from national data were within ± 40% of local values. Progressively coarser spatial resolutions to 5 km improved skill for total QF, but important features (hot spots, transport network) were lost at all resolutions when residential population controlled spatial variations. The results demonstrate that simple QF models should be applied with conservative spatial resolution in cities that, like London, exhibit time-varying energy use patterns.
Application of Geostatistical Simulation to Enhance Satellite Image Products
NASA Technical Reports Server (NTRS)
Hlavka, Christine A.; Dungan, Jennifer L.; Thirulanambi, Rajkumar; Roy, David
2004-01-01
With the deployment of Earth Observing System (EOS) satellites that provide daily, global imagery, there is increasing interest in defining the limitations of the data and derived products due to its coarse spatial resolution. Much of the detail, i.e. small fragments and notches in boundaries, is lost with coarse resolution imagery such as the EOS MODerate-Resolution Imaging Spectroradiometer (MODIS) data. Higher spatial resolution data such as the EOS Advanced Spaceborn Thermal Emission and Reflection Radiometer (ASTER), Landsat and airborne sensor imagery provide more detailed information but are less frequently available. There are, however, both theoretical and analytical evidence that burn scars and other fragmented types of land covers form self-similar or self-affine patterns, that is, patterns that look similar when viewed at widely differing spatial scales. Therefore small features of the patterns should be predictable, at least in a statistical sense, with knowledge about the large features. Recent developments in fractal modeling for characterizing the spatial distribution of undiscovered petroleum deposits are thus applicable to generating simulations of finer resolution satellite image products. We will present example EOS products, analysis to investigate self-similarity, and simulation results.
The geography of spatial synchrony
Jonathan A. Walter; Lawrence W. Sheppard; Thomas L. Anderson; Jude H. Kastens; Ottar N. Bjørnstad; Andrew M. Liebhold; Daniel C. Reuman; Bernd Blasius
2017-01-01
Spatial synchrony, defined as correlated temporal fluctuations among populations, is a fundamental feature of population dynamics, but many aspects of synchrony remain poorly understood. Few studies have examined detailed geographical patterns of synchrony; instead most focus on how synchrony declines with increasing linear distance between locations, making the...
Evaluation of spatial productivity patterns in an annual grassland during an AVIRIS overflight
NASA Technical Reports Server (NTRS)
Gamon, John A.; Field, Christopher B.; Ustin, Susan L.
1992-01-01
In May 1991, coincident with an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) overflight, a ground-based study covering 9 hectares of an annual grassland was completed. There were two goals of this ground study: (1) obtain ecologically and physiologically meaningful data for relating AVIRIS images to canopy structure, biochemistry, and physiology; and (2) evaluate the suitability of the 20-m AVIRIS pixel size for depicting detailed spatial patterns of productivity.
Phase separation driven by density-dependent movement: A novel mechanism for ecological patterns.
Liu, Quan-Xing; Rietkerk, Max; Herman, Peter M J; Piersma, Theunis; Fryxell, John M; van de Koppel, Johan
2016-12-01
Many ecosystems develop strikingly regular spatial patterns because of small-scale interactions between organisms, a process generally referred to as spatial self-organization. Self-organized spatial patterns are important determinants of the functioning of ecosystems, promoting the growth and survival of the involved organisms, and affecting the capacity of the organisms to cope with changing environmental conditions. The predominant explanation for self-organized pattern formation is spatial heterogeneity in establishment, growth and mortality, resulting from the self-organization processes. A number of recent studies, however, have revealed that movement of organisms can be an important driving process creating extensive spatial patterning in many ecosystems. Here, we review studies that detail movement-based pattern formation in contrasting ecological settings. Our review highlights that a common principle, where movement of organisms is density-dependent, explains observed spatial regular patterns in all of these studies. This principle, well known to physics as the Cahn-Hilliard principle of phase separation, has so-far remained unrecognized as a general mechanism for self-organized complexity in ecology. Using the examples presented in this paper, we explain how this movement principle can be discerned in ecological settings, and clarify how to test this mechanism experimentally. Our study highlights that animal movement, both in isolation and in unison with other processes, is an important mechanism for regular pattern formation in ecosystems. Copyright © 2016 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Gaona Garcia, J.; Lewandowski, J.; Bellin, A.
2017-12-01
Groundwater-stream water interactions in rivers determine water balances, but also chemical and biological processes in the streambed at different spatial and temporal scales. Due to the difficult identification and quantification of gaining, neutral and losing conditions, it is necessary to combine techniques with complementary capabilities and scale ranges. We applied this concept to a study site at the River Schlaube, East Brandenburg-Germany, a sand bed stream with intense sediment heterogeneity and complex environmental conditions. In our approach, point techniques such as temperature profiles of the streambed together with vertical hydraulic gradients provide data for the estimation of fluxes between groundwater and surface water with the numerical model 1DTempPro. On behalf of distributed techniques, fiber optic distributed temperature sensing identifies the spatial patterns of neutral, down- and up-welling areas by analysis of the changes in the thermal patterns at the streambed interface under certain flow. The study finally links point and surface temperatures to provide a method for upscaling of fluxes. Point techniques provide point flux estimates with essential depth detail to infer streambed structures while the results hardly represent the spatial distribution of fluxes caused by the heterogeneity of streambed properties. Fiber optics proved capable of providing spatial thermal patterns with enough resolution to observe distinct hyporheic thermal footprints at multiple scales. The relation of thermal footprint patterns and temporal behavior with flux results from point techniques enabled the use of methods for spatial flux estimates. The lack of detailed information of the physical driver's spatial distribution restricts the spatial flux estimation to the application of the T-proxy method, whose highly uncertain results mainly provide coarse spatial flux estimates. The study concludes that the upscaling of groundwater-stream water interactions using thermal measurements with combined point and distributed techniques requires the integration of physical drivers because of the heterogeneity of the flux patterns. Combined experimental and modeling approaches may help to obtain more reliable understanding of groundwater-surface water interactions at multiple scales.
Experimental Investigation of Spatially-Periodic Scalar Patterns in an Inline Mixer
NASA Astrophysics Data System (ADS)
Baskan, Ozge; Speetjens, Michel F. M.; Clercx, Herman J. H.
2015-11-01
Spatially persisting patterns with exponentially decaying intensities form during the downstream evolution of passive scalars in three-dimensional (3D) spatially periodic flows due to the coupled effect of the chaotic nature of the flow and the diffusivity of the material. This has been investigated in many computational and theoretical studies on 3D spatially-periodic flow fields. However, in the limit of zero-diffusivity, the evolution of the scalar fields results in more detailed structures that can only be captured by experiments due to limitations in the computational tools. Our study employs the-state-of-the-art experimental methods to analyze the evolution of 3D advective scalar field in a representative inline mixer, called Quatro static mixer. The experimental setup consists of an optically accessible test section with transparent internal elements, accommodating a pressure-driven pipe flow and equipped with 3D Laser-Induced Fluorescence. The results reveal that the continuous process of stretching and folding of material creates finer structures as the flow progresses, which is an indicator of chaotic advection and the experiments outperform the simulations by revealing far greater level of detail.
Spatially detailed water footprint assessment using the U.S. National Water-Economy Database
NASA Astrophysics Data System (ADS)
Ruddell, B. L.
2015-12-01
The new U.S. National Water-Economy Database (NWED) provides a complete picture of water use and trade in water-derived goods and services in the U.S. economy, by economic sector, at the county and metropolitan area scale. This data product provides for the first time a basis for spatially detailed calculations of water footprints and virtual water trade in the entire U.S.. This talk reviews the general patterns of U.S. water footprint and virtual water trade, at the county scale., and provides an opportunity for the community to discuss applications of this database for water resource policy and economics. The water footprints of irrigated agriculture and energy are specifically addressed, as well as overall patterns of water use in the economy.
NASA Astrophysics Data System (ADS)
Mo, Hong-yuan; Wang, Ying-jie; Yu, Zhuo-yuan
2009-07-01
The Poverty Alleviation Monitoring and Evaluation System (PAMES) is introduced in this paper. The authors present environment platform selection, and details of system design and realization. Different with traditional research of poverty alleviation, this paper develops a new analytical geo-visualization approach to study the distribution and causes of poverty phenomena within Geographic Information System (GIS). Based on the most detailed poverty population data, the spatial location and population statistical indicators of poverty village in Jiangxi province, the distribution characteristics of poverty population are detailed. The research results can provide much poverty alleviation decision support from a spatial-temporal view. It should be better if the administrative unit of poverty-stricken area to be changed from county to village according to spatial distribution pattern of poverty.
NASA Astrophysics Data System (ADS)
Lewis, Q. W.; Rhoads, B. L.
2017-12-01
The merging of rivers at confluences results in complex three-dimensional flow patterns that influence sediment transport, bed morphology, downstream mixing, and physical habitat conditions. The capacity to characterize comprehensively flow at confluences using traditional sensors, such as acoustic Doppler velocimeters and profiles, is limited by the restricted spatial resolution of these sensors and difficulties in measuring velocities simultaneously at many locations within a confluence. This study assesses two-dimensional surficial patterns of flow structure at a small stream confluence in Illinois, USA, using large scale particle image velocimetry (LSPIV) derived from videos captured by unmanned aerial systems (UAS). The method captures surface velocity patterns at high spatial and temporal resolution over multiple scales, ranging from the entire confluence to details of flow within the confluence mixing interface. Flow patterns at high momentum ratio are compared to flow patterns when the two incoming flows have nearly equal momentum flux. Mean surface flow patterns during the two types of events provide details on mean patterns of surface flow in different hydrodynamic regions of the confluence and on changes in these patterns with changing momentum flux ratio. LSPIV data derived from the highest resolution imagery also reveal general characteristics of large-scale vortices that form along the shear layer between the flows during the high-momentum ratio event. The results indicate that the use of LSPIV and UAS is well-suited for capturing in detail mean surface patterns of flow at small confluences, but that characterization of evolving turbulent structures is limited by scale considerations related to structure size, image resolution, and camera instability. Complementary methods, including camera platforms mounted at fixed positions close to the water surface, provide opportunities to accurately characterize evolving turbulent flow structures in confluences.
Probing Atomic Dynamics and Structures Using Optical Patterns
NASA Astrophysics Data System (ADS)
Schmittberger, Bonnie L.; Gauthier, Daniel J.
2015-05-01
Pattern formation is a widely studied phenomenon that can provide fundamental insights into nonlinear systems. Emergent patterns in cold atoms are of particular interest in condensed matter physics and quantum information science because one can relate optical patterns to spatial structures in the atoms. In our experimental system, we study multimode optical patterns generated from a sample of cold, thermal atoms. We observe this nonlinear optical phenomenon at record low input powers due to the highly nonlinear nature of the spatial bunching of atoms in an optical lattice. We present a detailed study of the dynamics of these bunched atoms during optical pattern formation. We show how small changes in the atomic density distribution affect the symmetry of the generated patterns as well as the nature of the nonlinearity that describes the light-atom interaction. We gratefully acknowledge the financial support of the National Science Foundation through Grant #PHY-1206040.
The Signature of Southern Hemisphere Atmospheric Circulation Patterns in Antarctic Precipitation
Thompson, David W. J.; van den Broeke, Michiel R.
2017-01-01
Abstract We provide the first comprehensive analysis of the relationships between large‐scale patterns of Southern Hemisphere climate variability and the detailed structure of Antarctic precipitation. We examine linkages between the high spatial resolution precipitation from a regional atmospheric model and four patterns of large‐scale Southern Hemisphere climate variability: the southern baroclinic annular mode, the southern annular mode, and the two Pacific‐South American teleconnection patterns. Variations in all four patterns influence the spatial configuration of precipitation over Antarctica, consistent with their signatures in high‐latitude meridional moisture fluxes. They impact not only the mean but also the incidence of extreme precipitation events. Current coupled‐climate models are able to reproduce all four patterns of atmospheric variability but struggle to correctly replicate their regional impacts on Antarctic climate. Thus, linking these patterns directly to Antarctic precipitation variability may allow a better estimate of future changes in precipitation than using model output alone. PMID:29398735
Recent variations in seasonality of temperature and precipitation in Canada, 1976-95
NASA Astrophysics Data System (ADS)
Whitfield, Paul H.; Bodtker, Karin; Cannon, Alex J.
2002-11-01
A previously reported analysis of rehabilitated monthly temperature and precipitation time series for several hundred stations across Canada showed generally spatially coherent patterns of variation between two decades (1976-85 and 1986-95). The present work expands that analysis to finer time scales and a greater number of stations. We demonstrate how the finer temporal resolution, at 5 day or 11 day intervals, increases the separation between clusters of recent variations in seasonal patterns of temperature and precipitation. We also expand the analysis by increasing the number of stations from only rehabilitated monthly data sets to rehabilitated daily sets, then to approximately 1500 daily observation stations. This increases the spatial density of data and allows a finer spatial resolution of patterns between the two decades. We also examine the success of clustering partial records, i.e. sites where the data record is incomplete. The intent of this study was to be consistent with previous work and explore how greater temporal and spatial detail in the climate data affects the resolution of patterns of recent climate variations. The variations we report for temperature and precipitation are taking place at different temporal and spatial scales. Further, the spatial patterns are much broader than local climate regions and ecozones, indicating that the differences observed may be the result of variations in atmospheric circulation.
Hong S. He; Wei Li; Brian R. Sturtevant; Jian Yang; Bo Z. Shang; Eric J. Gustafson; David J. Mladenoff
2005-01-01
LANDIS 4.0 is new-generation software that simulates forest landscape change over large spatial and temporal scales. It is used to explore how disturbances, succession, and management interact to determine forest composition and pattern. Also describes software architecture, model assumptions and provides detailed instructions on the use of the model.
Near-Resonant Imaging of Trapped Cold Atomic Samples
You, L.; Lewenstein, Maciej
1996-01-01
We study the formation of diffraction patterns in the near-resonant imaging of trapped cold atomic samples. We show that the spatial imaging can provide detailed information on the trapped atomic clouds. PMID:27805110
Pattern-based, multi-scale segmentation and regionalization of EOSD land cover
NASA Astrophysics Data System (ADS)
Niesterowicz, Jacek; Stepinski, Tomasz F.
2017-10-01
The Earth Observation for Sustainable Development of Forests (EOSD) map is a 25 m resolution thematic map of Canadian forests. Because of its large spatial extent and relatively high resolution the EOSD is difficult to analyze using standard GIS methods. In this paper we propose multi-scale segmentation and regionalization of EOSD as new methods for analyzing EOSD on large spatial scales. Segments, which we refer to as forest land units (FLUs), are delineated as tracts of forest characterized by cohesive patterns of EOSD categories; we delineated from 727 to 91,885 FLUs within the spatial extent of EOSD depending on the selected scale of a pattern. Pattern of EOSD's categories within each FLU is described by 1037 landscape metrics. A shapefile containing boundaries of all FLUs together with an attribute table listing landscape metrics make up an SQL-searchable spatial database providing detailed information on composition and pattern of land cover types in Canadian forest. Shapefile format and extensive attribute table pertaining to the entire legend of EOSD are designed to facilitate broad range of investigations in which assessment of composition and pattern of forest over large areas is needed. We calculated four such databases using different spatial scales of pattern. We illustrate the use of FLU database for producing forest regionalization maps of two Canadian provinces, Quebec and Ontario. Such maps capture the broad scale variability of forest at the spatial scale of the entire province. We also demonstrate how FLU database can be used to map variability of landscape metrics, and thus the character of landscape, over the entire Canada.
Logan, John R.; Martinez, Matthew
2018-01-01
Studies of residential segregation typically focus on its degree without questioning its scale and configuration. We study Southern cities in 1880 to emphasize the salience of these spatial dimensions. Distance-based and sequence indices can reflect spatial patterns but with some limitations, while geocoded 100% population data make possible more informative measures. One improvement is flexibility in spatial scale, ranging from adjacent buildings to whole districts of the city. Another is the ability to map patterns in fine detail. In Southern cities we find qualitatively distinct configurations that include not only black “neighborhoods” as usually imagined, but also backyard housing, alley housing, and side streets that were predominantly black. These configurations represent the sort of symbolic boundaries recognized by urban ethnographers. By mapping residential configurations and interpreting them in light of historical accounts, our intention is to capture meanings that are too often missed by quantitative studies of segregation. PMID:29479108
Spatially structured superinfection and the evolution of disease virulence.
Caraco, Thomas; Glavanakov, Stephan; Li, Shengua; Maniatty, William; Szymanski, Boleslaw K
2006-06-01
When pathogen strains differing in virulence compete for hosts, spatial structuring of disease transmission can govern both evolved levels of virulence and patterns in strain coexistence. We develop a spatially detailed model of superinfection, a form of contest competition between pathogen strains; the probability of superinfection depends explicitly on the difference in levels of virulence. We apply methods of adaptive dynamics to address the interplay of spatial dynamics and evolution. The mean-field approximation predicts evolution to criticality; any small increase in virulence capable of dynamical persistence is favored. Both pair approximation and simulation of the detailed model indicate that spatial structure constrains disease virulence. Increased spatial clustering reduces the maximal virulence capable of single-strain persistence and, more importantly, reduces the convergent-stable virulence level under strain competition. The spatially detailed model predicts that increasing the probability of superinfection, for given difference in virulence, increases the likelihood of between-strain coexistence. When strains differing in virulence can coexist ecologically, our results may suggest policies for managing diseases with localized transmission. Comparing equilibrium densities from the pair approximation, we find that introducing a more virulent strain into a host population infected by a less virulent strain can sometimes reduce total host mortality and increase global host density.
Spatial band-pass filtering aids decoding musical genres from auditory cortex 7T fMRI.
Sengupta, Ayan; Pollmann, Stefan; Hanke, Michael
2018-01-01
Spatial filtering strategies, combined with multivariate decoding analysis of BOLD images, have been used to investigate the nature of the neural signal underlying the discriminability of brain activity patterns evoked by sensory stimulation -- primarily in the visual cortex. Reported evidence indicates that such signals are spatially broadband in nature, and are not primarily comprised of fine-grained activation patterns. However, it is unclear whether this is a general property of the BOLD signal, or whether it is specific to the details of employed analyses and stimuli. Here we performed an analysis of publicly available, high-resolution 7T fMRI on the response BOLD response to musical genres in primary auditory cortex that matches a previously conducted study on decoding visual orientation from V1. The results show that the pattern of decoding accuracies with respect to different types and levels of spatial filtering is comparable to that obtained from V1, despite considerable differences in the respective cortical circuitry.
Shared memories reveal shared structure in neural activity across individuals
Chen, J.; Leong, Y.C.; Honey, C.J.; Yong, C.H.; Norman, K.A.; Hasson, U.
2016-01-01
Our lives revolve around sharing experiences and memories with others. When different people recount the same events, how similar are their underlying neural representations? Participants viewed a fifty-minute movie, then verbally described the events during functional MRI, producing unguided detailed descriptions lasting up to forty minutes. As each person spoke, event-specific spatial patterns were reinstated in default-network, medial-temporal, and high-level visual areas. Individual event patterns were both highly discriminable from one another and similar between people, suggesting consistent spatial organization. In many high-order areas, patterns were more similar between people recalling the same event than between recall and perception, indicating systematic reshaping of percept into memory. These results reveal the existence of a common spatial organization for memories in high-level cortical areas, where encoded information is largely abstracted beyond sensory constraints; and that neural patterns during perception are altered systematically across people into shared memory representations for real-life events. PMID:27918531
Spatiotemporal pattern in somitogenesis: a non-Turing scenario with wave propagation.
Nagahara, Hiroki; Ma, Yue; Takenaka, Yoshiko; Kageyama, Ryoichiro; Yoshikawa, Kenichi
2009-08-01
Living organisms maintain their lives under far-from-equilibrium conditions by creating a rich variety of spatiotemporal structures in a self-organized manner, such as temporal rhythms, switching phenomena, and development of the body. In this paper, we focus on the dynamical process of morphogens in somitogenesis in mice where propagation of the gene expression level plays an essential role in creating the spatially periodic patterns of the vertebral columns. We present a simple discrete reaction-diffusion model which includes neighboring interaction through an activator, but not diffusion of an inhibitor. We can produce stationary periodic patterns by introducing the effect of spatial discreteness to the field. Based on the present model, we discuss the underlying physical principles that are independent of the details of biomolecular reactions. We also discuss the framework of spatial discreteness based on the reaction-diffusion model in relation to a cellular array, by comparison with an actual experimental observation.
Spatial pattern enhances ecosystem functioning in an African savanna.
Pringle, Robert M; Doak, Daniel F; Brody, Alison K; Jocqué, Rudy; Palmer, Todd M
2010-05-25
The finding that regular spatial patterns can emerge in nature from local interactions between organisms has prompted a search for the ecological importance of these patterns. Theoretical models have predicted that patterning may have positive emergent effects on fundamental ecosystem functions, such as productivity. We provide empirical support for this prediction. In dryland ecosystems, termite mounds are often hotspots of plant growth (primary productivity). Using detailed observations and manipulative experiments in an African savanna, we show that these mounds are also local hotspots of animal abundance (secondary and tertiary productivity): insect abundance and biomass decreased with distance from the nearest termite mound, as did the abundance, biomass, and reproductive output of insect-eating predators. Null-model analyses indicated that at the landscape scale, the evenly spaced distribution of termite mounds produced dramatically greater abundance, biomass, and reproductive output of consumers across trophic levels than would be obtained in landscapes with randomly distributed mounds. These emergent properties of spatial pattern arose because the average distance from an arbitrarily chosen point to the nearest feature in a landscape is minimized in landscapes where the features are hyper-dispersed (i.e., uniformly spaced). This suggests that the linkage between patterning and ecosystem functioning will be common to systems spanning the range of human management intensities. The centrality of spatial pattern to system-wide biomass accumulation underscores the need to conserve pattern-generating organisms and mechanisms, and to incorporate landscape patterning in efforts to restore degraded habitats and maximize the delivery of ecosystem services.
Modelling spatial patterns of urban growth in Africa
Linard, Catherine; Tatem, Andrew J.; Gilbert, Marius
2013-01-01
The population of Africa is predicted to double over the next 40 years, driving exceptionally high urban expansion rates that will induce significant socio-economic, environmental and health changes. In order to prepare for these changes, it is important to better understand urban growth dynamics in Africa and better predict the spatial pattern of rural-urban conversions. Previous work on urban expansion has been carried out at the city level or at the global level with a relatively coarse 5–10 km resolution. The main objective of the present paper was to develop a modelling approach at an intermediate scale in order to identify factors that influence spatial patterns of urban expansion in Africa. Boosted Regression Tree models were developed to predict the spatial pattern of rural-urban conversions in every large African city. Urban change data between circa 1990 and circa 2000 available for 20 large cities across Africa were used as training data. Results showed that the urban land in a 1 km neighbourhood and the accessibility to the city centre were the most influential variables. Results obtained were generally more accurate than results obtained using a distance-based urban expansion model and showed that the spatial pattern of small, compact and fast growing cities were easier to simulate than cities with lower population densities and a lower growth rate. The simulation method developed here will allow the production of spatially detailed urban expansion forecasts for 2020 and 2025 for Africa, data that are increasingly required by global change modellers. PMID:25152552
NASA Astrophysics Data System (ADS)
Wolf, N.; Siegmund, A.; del Río, C.; Osses, P.; García, J. L.
2016-06-01
In the coastal Atacama Desert in Northern Chile plant growth is constrained to so-called `fog oases' dominated by monospecific stands of the genus Tillandsia. Adapted to the hyperarid environmental conditions, these plants specialize on the foliar uptake of fog as main water and nutrient source. It is this characteristic that leads to distinctive macro- and micro-scale distribution patterns, reflecting complex geo-ecological gradients, mainly affected by the spatiotemporal occurrence of coastal fog respectively the South Pacific Stratocumulus clouds reaching inlands. The current work employs remote sensing, machine learning and spatial pattern/GIS analysis techniques to acquire detailed information on the presence and state of Tillandsia spp. in the Tarapacá region as a base to better understand the bioclimatic and topographic constraints determining the distribution patterns of Tillandsia spp. Spatial and spectral predictors extracted from WorldView-3 satellite data are used to map present Tillandsia vegetation in the Tarapaca region. Regression models on Vegetation Cover Fraction (VCF) are generated combining satellite-based as well as topographic variables and using aggregated high spatial resolution information on vegetation cover derived from UAV flight campaigns as a reference. The results are a first step towards mapping and modelling the topographic as well as bioclimatic factors explaining the spatial distribution patterns of Tillandsia fog oases in the Atacama, Chile.
Hirshhorn, Marnie; Grady, Cheryl; Rosenbaum, R Shayna; Winocur, Gordon; Moscovitch, Morris
2012-11-01
Functional magnetic resonance imaging (fMRI) was used to compare brain activity during the retrieval of coarse- and fine-grained spatial details and episodic details associated with a familiar environment. Long-time Toronto residents compared pairs of landmarks based on their absolute geographic locations (requiring either coarse or fine discriminations) or based on previous visits to those landmarks (requiring episodic details). An ROI analysis of the hippocampus showed that all three conditions activated the hippocampus bilaterally. Fine-grained spatial judgments recruited an additional region of the right posterior hippocampus, while episodic judgments recruited an additional region of the right anterior hippocampus, and a more extensive region along the length of the left hippocampus. To examine whole-brain patterns of activity, Partial Least Squares (PLS) analysis was used to identify sets of brain regions whose activity covaried with the three conditions. All three comparison judgments recruited the default mode network including the posterior cingulate/retrosplenial cortex, middle frontal gyrus, hippocampus, and precuneus. Fine-grained spatial judgments also recruited additional regions of the precuneus, parahippocampal cortex and the supramarginal gyrus. Episodic judgments recruited the posterior cingulate and medial frontal lobes as well as the angular gyrus. These results are discussed in terms of their implications for theories of hippocampal function and spatial and episodic memory. Copyright © 2012 Elsevier Ltd. All rights reserved.
Clinchy, Michael; Haydon, Daniel T; Smith, Andrew T
2002-04-01
Patch occupancy surveys are commonly used to parameterize metapopulation models. If isolation predicts patch occupancy, this is generally attributed to a balance between distance-dependent recolonization and spatially independent extinctions. We investigated whether similar patterns could also be generated by a process of spatially correlated extinctions following a unique colonization event (analogous to nonequilibrium processes in island biogeography). We simulated effects of spatially correlated extinctions on patterns of patch occupancy among pikas (Ochotona princeps) at Bodie, California, using randomly located extinction disks to represent the likely effects of predation. Our simulations produced similar patterns to those cited as evidence of balanced metapopulation dynamics. Simulations using a variety of disk sizes and patch configurations confirmed that our results are potentially applicable to a broad range of species and sites. Analyses of the observed patterns of patch occupancy at Bodie revealed little evidence of rescue effects and strong evidence that most recolonizations are ephemeral in nature. Persistence will be overestimated if static or declining patterns of patch occupancy are mistakenly attributed to dynamically stable metapopulation processes. Consequently, simple patch occupancy surveys should not be considered as substitutes for detailed experimental tests of hypothesized population processes, particularly when conservation concerns are involved.
NASA Astrophysics Data System (ADS)
Awumah, A.; Mahanti, P.; Robinson, M. S.
2017-12-01
Image fusion is often used in Earth-based remote sensing applications to merge spatial details from a high-resolution panchromatic (Pan) image with the color information from a lower-resolution multi-spectral (MS) image, resulting in a high-resolution multi-spectral image (HRMS). Previously, the performance of six well-known image fusion methods were compared using Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) and Wide Angle Camera (WAC) images (1). Results showed the Intensity-Hue-Saturation (IHS) method provided the best spatial performance, but deteriorated the spectral content. In general, there was a trade-off between spatial enhancement and spectral fidelity from the fusion process; the more spatial details from the Pan fused with the MS image, the more spectrally distorted the final HRMS. In this work, we control the amount of spatial details fused (from the LROC NAC images to WAC images) using a controlled IHS method (2), to investigate the spatial variation in spectral distortion on fresh crater ejecta. In the controlled IHS method (2), the percentage of the Pan component merged with the MS is varied. The percent of spatial detail from the Pan used is determined by a variable whose value may be varied between 1 (no Pan utilized) to infinity (entire Pan utilized). An HRMS color composite image (red=415nm, green=321/415nm, blue=321/360nm (3)) was used to assess performance (via visual inspection and metric-based evaluations) at each tested value of the control parameter (1 to 10—after which spectral distortion saturates—in 0.01 increments) within three regions: crater interiors, ejecta blankets, and the background material surrounding the craters. Increasing the control parameter introduced increased spatial sharpness and spectral distortion in all regions, but to varying degrees. Crater interiors suffered the most color distortion, while ejecta experienced less color distortion. The controlled IHS method is therefore desirable for resolution-enhancement of fresh crater ejecta; larger values of the control parameter may be used to sharpen MS images of ejecta patterns but with less impact to color distortion than in the uncontrolled IHS fusion process. References: (1) Prasun et. al (2016) ISPRS. (2) Choi, Myungjin (2006) IEEE. (3) Denevi et. al (2014) JGR.
Influences of indigenous language on spatial frames of reference in Aboriginal English
NASA Astrophysics Data System (ADS)
Edmonds-Wathen, Cris
2014-06-01
The Aboriginal English spoken by Indigenous children in remote communities in the Northern Territory of Australia is influenced by the home languages spoken by themselves and their families. This affects uses of spatial terms used in mathematics such as `in front' and `behind.' Speakers of the endangered Indigenous Australian language Iwaidja use the intrinsic frame of reference in contexts where speakers of Standard Australian English use the relative frame of reference. Children speaking Aboriginal English show patterns of use that parallel the Iwaidja contexts. This paper presents detailed examples of spatial descriptions in Iwaidja and Aboriginal English that demonstrate the parallel patterns of use. The data comes from a study that investigated how an understanding of spatial frame of reference in Iwaidja could assist teaching mathematics to Indigenous language-speaking students. Implications for teaching mathematics are explored for teachers without previous experience in a remote Indigenous community.
Shrestha, Rehana; Flacke, Johannes; Martinez, Javier; van Maarseveen, Martin
2016-01-01
Differential exposure to multiple environmental burdens and benefits and their distribution across a population with varying vulnerability can contribute heavily to health inequalities. Particularly relevant are areas with high cumulative burdens and high social vulnerability termed as “hotspots”. This paper develops an index-based approach to assess these multiple burdens and benefits in combination with vulnerability factors at detailed intra-urban level. The method is applied to the city of Dortmund, Germany. Using non-spatial and spatial methods we assessed inequalities and identified “hotspot” areas in the city. We found modest inequalities burdening higher vulnerable groups in Dortmund (CI = −0.020 at p < 0.05). At the detailed intra-urban level, however, inequalities showed strong geographical patterns. Large numbers of “hotspots” exist in the northern part of the city compared to the southern part. A holistic assessment, particularly at a detailed local level, considering both environmental burdens and benefits and their distribution across the population with the different vulnerability, is essential to inform environmental justice debates and to mobilize local stakeholders. Locating “hotspot” areas at this detailed spatial level can serve as a basis to develop interventions that target vulnerable groups to ensure a health conducive equal environment. PMID:27409625
Novotny, Josef; Hasman, Jiri
2015-01-01
This paper examines the patterns of the US and Australian immigration geography and the process of regional population diversification and the emergence of new immigrant concentrations at the regional level. It presents a new approach in the context of human migration studies, focusing on spatial relatedness between individual foreign-born groups as revealed from the analysis of their joint spatial concentrations. The approach employs a simple assumption that the more frequently the members of two population groups concentrate in the same locations the higher is the probability that these two groups can be related. Based on detailed data on the spatial distribution of foreign-born groups in US counties (2000–2010) and Australian postal areas (2006–2011) we firstly quantify the spatial relatedness between all pairs of foreign-born groups and model the aggregate patterns of US and Australian immigration systems conceptualized as the undirected networks of foreign-born groups linked by their spatial relatedness. Secondly, adopting a more dynamic perspective, we assume that immigrant groups with higher spatial relatedness to those groups already concentrated in a region are also more likely to settle in this region in future. As the ultimate goal of the paper, we examine the power of spatial relatedness measures in projecting the emergence of new immigrant concentrations in the US and Australian regions. The results corroborate that the spatial relatedness measures can serve as useful instruments in the analysis of the patterns of population structure and prediction of regional population change. More generally, this paper demonstrates that information contained in spatial patterns (relatedness in space) of population composition has yet to be fully utilized in population forecasting. PMID:25966371
NASA Astrophysics Data System (ADS)
Manson, F. J.; Loneragan, N. R.; Phinn, S. R.
2003-07-01
An assessment of the changes in the distribution and extent of mangroves within Moreton Bay, southeast Queensland, Australia, was carried out. Two assessment methods were evaluated: spatial and temporal pattern metrics analysis, and change detection analysis. Currently, about 15,000 ha of mangroves are present in Moreton Bay. These mangroves are important ecosystems, but are subject to disturbance from a number of sources. Over the past 25 years, there has been a loss of more than 3800 ha, as a result of natural losses and mangrove clearing (e.g. for urban and industrial development, agriculture and aquaculture). However, areas of new mangroves have become established over the same time period, offsetting these losses to create a net loss of about 200 ha. These new mangroves have mainly appeared in the southern bay region and the bay islands, particularly on the landward edge of existing mangroves. In addition, spatial patterns and species composition of mangrove patches have changed. The pattern metrics analysis provided an overview of mangrove distribution and change in the form of single metric values, while the change detection analysis gave a more detailed and spatially explicit description of change. An analysis of the effects of spatial scales on the pattern metrics indicated that they were relatively insensitive to scale at spatial resolutions less than 50 m, but that most metrics became sensitive at coarser resolutions, a finding which has implications for mapping of mangroves based on remotely sensed data.
Crombach, Anton; Cicin-Sain, Damjan; Wotton, Karl R; Jaeger, Johannes
2012-01-01
Understanding the function and evolution of developmental regulatory networks requires the characterisation and quantification of spatio-temporal gene expression patterns across a range of systems and species. However, most high-throughput methods to measure the dynamics of gene expression do not preserve the detailed spatial information needed in this context. For this reason, quantification methods based on image bioinformatics have become increasingly important over the past few years. Most available approaches in this field either focus on the detailed and accurate quantification of a small set of gene expression patterns, or attempt high-throughput analysis of spatial expression through binary pattern extraction and large-scale analysis of the resulting datasets. Here we present a robust, "medium-throughput" pipeline to process in situ hybridisation patterns from embryos of different species of flies. It bridges the gap between high-resolution, and high-throughput image processing methods, enabling us to quantify graded expression patterns along the antero-posterior axis of the embryo in an efficient and straightforward manner. Our method is based on a robust enzymatic (colorimetric) in situ hybridisation protocol and rapid data acquisition through wide-field microscopy. Data processing consists of image segmentation, profile extraction, and determination of expression domain boundary positions using a spline approximation. It results in sets of measured boundaries sorted by gene and developmental time point, which are analysed in terms of expression variability or spatio-temporal dynamics. Our method yields integrated time series of spatial gene expression, which can be used to reverse-engineer developmental gene regulatory networks across species. It is easily adaptable to other processes and species, enabling the in silico reconstitution of gene regulatory networks in a wide range of developmental contexts.
The geography of spatial synchrony.
Walter, Jonathan A; Sheppard, Lawrence W; Anderson, Thomas L; Kastens, Jude H; Bjørnstad, Ottar N; Liebhold, Andrew M; Reuman, Daniel C
2017-07-01
Spatial synchrony, defined as correlated temporal fluctuations among populations, is a fundamental feature of population dynamics, but many aspects of synchrony remain poorly understood. Few studies have examined detailed geographical patterns of synchrony; instead most focus on how synchrony declines with increasing linear distance between locations, making the simplifying assumption that distance decay is isotropic. By synthesising and extending prior work, we show how geography of synchrony, a term which we use to refer to detailed spatial variation in patterns of synchrony, can be leveraged to understand ecological processes including identification of drivers of synchrony, a long-standing challenge. We focus on three main objectives: (1) showing conceptually and theoretically four mechanisms that can generate geographies of synchrony; (2) documenting complex and pronounced geographies of synchrony in two important study systems; and (3) demonstrating a variety of methods capable of revealing the geography of synchrony and, through it, underlying organism ecology. For example, we introduce a new type of network, the synchrony network, the structure of which provides ecological insight. By documenting the importance of geographies of synchrony, advancing conceptual frameworks, and demonstrating powerful methods, we aim to help elevate the geography of synchrony into a mainstream area of study and application. © 2017 John Wiley & Sons Ltd/CNRS.
New data for relating land use and urban form to private passenger vehicle miles.
DOT National Transportation Integrated Search
2013-08-01
This research project developed the most extensive and spatially detailed analysis of : annual vehicle miles traveled (VMT) by type of vehicle, place of residence, and land use : pattern. We combined a unique Massachusetts State dataset of annual odo...
Wesolowski, Amy; Stresman, Gillian; Eagle, Nathan; Stevenson, Jennifer; Owaga, Chrispin; Marube, Elizabeth; Bousema, Teun; Drakeley, Christopher; Cox, Jonathan; Buckee, Caroline O.
2014-01-01
Human travel impacts the spread of infectious diseases across spatial and temporal scales, with broad implications for the biological and social sciences. Individual data on travel patterns have been difficult to obtain, particularly in low-income countries. Travel survey data provide detailed demographic information, but sample sizes are often small and travel histories are hard to validate. Mobile phone records can provide vast quantities of spatio-temporal travel data but vary in spatial resolution and explicitly do not include individual information in order to protect the privacy of subscribers. Here we compare and contrast both sources of data over the same time period in a rural area of Kenya. Although both data sets are able to quantify broad travel patterns and distinguish regional differences in travel, each provides different insights that can be combined to form a more detailed picture of travel in low-income settings to understand the spread of infectious diseases. PMID:25022440
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.
Wesolowski, Amy; Stresman, Gillian; Eagle, Nathan; Stevenson, Jennifer; Owaga, Chrispin; Marube, Elizabeth; Bousema, Teun; Drakeley, Christopher; Cox, Jonathan; Buckee, Caroline O
2014-07-14
Human travel impacts the spread of infectious diseases across spatial and temporal scales, with broad implications for the biological and social sciences. Individual data on travel patterns have been difficult to obtain, particularly in low-income countries. Travel survey data provide detailed demographic information, but sample sizes are often small and travel histories are hard to validate. Mobile phone records can provide vast quantities of spatio-temporal travel data but vary in spatial resolution and explicitly do not include individual information in order to protect the privacy of subscribers. Here we compare and contrast both sources of data over the same time period in a rural area of Kenya. Although both data sets are able to quantify broad travel patterns and distinguish regional differences in travel, each provides different insights that can be combined to form a more detailed picture of travel in low-income settings to understand the spread of infectious diseases.
Spatially explicit modeling in ecology: A review
DeAngelis, Donald L.; Yurek, Simeon
2017-01-01
The use of spatially explicit models (SEMs) in ecology has grown enormously in the past two decades. One major advancement has been that fine-scale details of landscapes, and of spatially dependent biological processes, such as dispersal and invasion, can now be simulated with great precision, due to improvements in computer technology. Many areas of modeling have shifted toward a focus on capturing these fine-scale details, to improve mechanistic understanding of ecosystems. However, spatially implicit models (SIMs) have played a dominant role in ecology, and arguments have been made that SIMs, which account for the effects of space without specifying spatial positions, have an advantage of being simpler and more broadly applicable, perhaps contributing more to understanding. We address this debate by comparing SEMs and SIMs in examples from the past few decades of modeling research. We argue that, although SIMs have been the dominant approach in the incorporation of space in theoretical ecology, SEMs have unique advantages for addressing pragmatic questions concerning species populations or communities in specific places, because local conditions, such as spatial heterogeneities, organism behaviors, and other contingencies, produce dynamics and patterns that usually cannot be incorporated into simpler SIMs. SEMs are also able to describe mechanisms at the local scale that can create amplifying positive feedbacks at that scale, creating emergent patterns at larger scales, and therefore are important to basic ecological theory. We review the use of SEMs at the level of populations, interacting populations, food webs, and ecosystems and argue that SEMs are not only essential in pragmatic issues, but must play a role in the understanding of causal relationships on landscapes.
Visual information processing of faces in body dysmorphic disorder.
Feusner, Jamie D; Townsend, Jennifer; Bystritsky, Alexander; Bookheimer, Susan
2007-12-01
Body dysmorphic disorder (BDD) is a severe psychiatric condition in which individuals are preoccupied with perceived appearance defects. Clinical observation suggests that patients with BDD focus on details of their appearance at the expense of configural elements. This study examines abnormalities in visual information processing in BDD that may underlie clinical symptoms. To determine whether patients with BDD have abnormal patterns of brain activation when visually processing others' faces with high, low, or normal spatial frequency information. Case-control study. University hospital. Twelve right-handed, medication-free subjects with BDD and 13 control subjects matched by age, sex, and educational achievement. Intervention Functional magnetic resonance imaging while performing matching tasks of face stimuli. Stimuli were neutral-expression photographs of others' faces that were unaltered, altered to include only high spatial frequency visual information, or altered to include only low spatial frequency visual information. Blood oxygen level-dependent functional magnetic resonance imaging signal changes in the BDD and control groups during tasks with each stimulus type. Subjects with BDD showed greater left hemisphere activity relative to controls, particularly in lateral prefrontal cortex and lateral temporal lobe regions for all face tasks (and dorsal anterior cingulate activity for the low spatial frequency task). Controls recruited left-sided prefrontal and dorsal anterior cingulate activity only for the high spatial frequency task. Subjects with BDD demonstrate fundamental differences from controls in visually processing others' faces. The predominance of left-sided activity for low spatial frequency and normal faces suggests detail encoding and analysis rather than holistic processing, a pattern evident in controls only for high spatial frequency faces. These abnormalities may be associated with apparent perceptual distortions in patients with BDD. The fact that these findings occurred while subjects viewed others' faces suggests differences in visual processing beyond distortions of their own appearance.
NASA Astrophysics Data System (ADS)
Chen, Y.; Zhang, Y.; Gao, J.; Yuan, Y.; Lv, Z.
2018-04-01
Recently, built-up area detection from high-resolution satellite images (HRSI) has attracted increasing attention because HRSI can provide more detailed object information. In this paper, multi-resolution wavelet transform and local spatial autocorrelation statistic are introduced to model the spatial patterns of built-up areas. First, the input image is decomposed into high- and low-frequency subbands by wavelet transform at three levels. Then the high-frequency detail information in three directions (horizontal, vertical and diagonal) are extracted followed by a maximization operation to integrate the information in all directions. Afterward, a cross-scale operation is implemented to fuse different levels of information. Finally, local spatial autocorrelation statistic is introduced to enhance the saliency of built-up features and an adaptive threshold algorithm is used to achieve the detection of built-up areas. Experiments are conducted on ZY-3 and Quickbird panchromatic satellite images, and the results show that the proposed method is very effective for built-up area detection.
Scown, Murray W.; Thoms, Martin C.; DeJager, Nathan R.; Gilvear, David J.; Greenwood, Malcolm T.; Thoms, Martin C.; Wood, Paul J.
2016-01-01
Floodplains can be viewed as complex adaptive systems (Levin, 1998) because they are comprised of many different biophysical components, such as morphological features, soil groups and vegetation communities as well as being sites of key biogeochemical processing (Stanford et al., 2005). Interactions and feedbacks among the biophysical components often result in additional phenomena occuring over a range of scales, often in the absence of any controlling factors (sensu Hallet, 1990). This emergence of new biophysical features and rates of processing can lead to alternative stable states which feed back into floodplain adaptive cycles (cf. Hughes, 1997; Stanford et al., 2005). Interactions between different biophysical components, feedbacks, self emergence and scale are all key properties of complex adaptive systems (Levin, 1998; Phillips, 2003; Murray et al., 2014) and therefore will influence the manner in which we study and view spatial patterns. Measuring the spatial patterns of floodplain biophysical components is a prerequisite to examining and understanding these ecosystems as complex adaptive systems. Elucidating relationships between pattern and process, which are intrinsically linked within floodplains (Ward et al., 2002), is dependent upon an understanding of spatial pattern. This knowledge can help river scientists determine the major drivers, controllers and responses of floodplain structure and function, as well as the consequences of altering those drivers and controllers (Hughes and Cass, 1997; Whited et al., 2007). Interactions and feedbacks between physical, chemical and biological components of floodplain ecosystems create and maintain a structurally diverse and dynamic template (Stanford et al., 2005). This template influences subsequent interactions between components that consequently affect system trajectories within floodplains (sensu Bak et al., 1988). Constructing and evaluating models used to predict floodplain ecosystem responses to natural and anthropogenic disturbances therefore require quantification of spatial pattern (Asselman and Middelkoop, 1995; Walling and He, 1998). Quantifying these patterns also provides insights into the spatial and temporal domains of structuring processes as well as enabling the detection of self-emergent phenomena, environmental constraints or anthropogenic interference (Turner et al., 1990; Holling, 1992; De Jager and Rohweder, 2012). Thus, quantifying spatial pattern is an important building block on which to examine floodplains as complex adaptive systems (Levin, 1998). Approaches to measuring spatial pattern in floodplains must be cognisant of scale, self-emergent phenomena, spatial organisation, and location. Fundamental problems may arise when patterns observed at a site or transect scale are scaled-up to infer processes and patterns over entire floodplain surfaces (Wiens, 2002; Thorp et al., 2008). Likewise, patterns observed over the entire spatial extent of a landscape can mask important variation and detail at finer scales (Riitters et al., 2002). Indeed, different patterns often emerge at different scales (Turner et al., 1990) because of hierarchical structuring processes (O'Neill et al., 1991). Categorising data into discrete, homogeneous and predefined spatial units at a particular scale (e.g. polygons) creates issues and errors associated with scale and subjective classification (McGarigal et al., 2009; Cushman et al., 2010). These include, loss of information within classified ‘patches’, as well as the ability to detect the emergence of new features that do not fit the original classification scheme. Many of these issues arise because floodplains are highly heterogeneous and have complex spatial organizations (Carbonneau et al., 2012; Legleiter, 2013). As a result, the scale and location at which measurements are made can influence the observed spatial patterns; and patterns may not be scale independent or applicable in different geomorp
NASA Astrophysics Data System (ADS)
Pepin, N. C.
2009-12-01
Predictions of current spatial patterns of climate are difficult in areas of complex relief in all parts of the world, because of the interweaving influences of topography, elevation and aspect. These influences vary temporally as a result of the seasonal and diurnal cycles in radiation balance. In periods of negative energy balance, surface decoupling can occur as cold air drainage develops low-level temperature inversions, and the surface temperature regime beneath the inversion becomes divorced from free atmospheric forcing. Both the spatial scale and temporal persistence of this decoupling vary according to latitude, and although the physical processes that influence inversion formation are similar in polar areas and mid-latitude mountains, the contrasting seasonal and diurnal forcings make the end results very different. Examples are contrasted from detailed field temperature measurements (~50 sites per field area) taken over several years in areas of complex relief in the eastern Pyrenees (~42.5 deg N), the Oregon Cascades (also ~42.5 deg N) and Finnish Lapland (70 deg N and above the Arctic circle). In the former two locations decoupling is mostly diurnally driven, and small-scale topography is important in mediating the effects. Summer decoupling is brief and spatially limited, whereas winter decoupling can be more spatially extensive. There are strong relationships between synoptic conditions, as measured by objective flow indices at the 700 mb level (derived from NCEP/NCAR reanalysis fields) and the patterns of decoupling, which allow us to assess the effects of past and potential future circulation change on spatial patterns of future climate warming. In Finnish Lapland the decoupling regime most clearly approaches the mid-latitude pattern around the equinoxes when there are clear day and night periods. In winter and summer however (the polar night and polar day) with the muting of the diurnal cycle, processes are more poorly understood. Winter cold pools can develop and strengthen over days until eventually they extend over and above the topography. Strangely, there are also indistinct relationships with circulation indices at this time. While build-up can take days, destruction is often immediate and is dynamically forced. In summer, localized decoupling occurs on clear nights even though the sun is above the horizon, but micro-scale patterns are different than in mid-latitudes. The above comparison shows that polar areas are very different in their micro-temperature regimes than mid-latitude mountains and in their relationships of these regimes with circulation. Thus we expect detailed spatial patterns of climate change may be very different in the two regions.
Multisubject Learning for Common Spatial Patterns in Motor-Imagery BCI
Devlaminck, Dieter; Wyns, Bart; Grosse-Wentrup, Moritz; Otte, Georges; Santens, Patrick
2011-01-01
Motor-imagery-based brain-computer interfaces (BCIs) commonly use the common spatial pattern filter (CSP) as preprocessing step before feature extraction and classification. The CSP method is a supervised algorithm and therefore needs subject-specific training data for calibration, which is very time consuming to collect. In order to reduce the amount of calibration data that is needed for a new subject, one can apply multitask (from now on called multisubject) machine learning techniques to the preprocessing phase. Here, the goal of multisubject learning is to learn a spatial filter for a new subject based on its own data and that of other subjects. This paper outlines the details of the multitask CSP algorithm and shows results on two data sets. In certain subjects a clear improvement can be seen, especially when the number of training trials is relatively low. PMID:22007194
Spatial variation in extreme winds predicts large wildfire locations in chaparral ecosystems
NASA Astrophysics Data System (ADS)
Moritz, Max A.; Moody, Tadashi J.; Krawchuk, Meg A.; Hughes, Mimi; Hall, Alex
2010-02-01
Fire plays a crucial role in many ecosystems, and a better understanding of different controls on fire activity is needed. Here we analyze spatial variation in fire danger during episodic wind events in coastal southern California, a densely populated Mediterranean-climate region. By reconstructing almost a decade of fire weather patterns through detailed simulations of Santa Ana winds, we produced the first high-resolution map of where these hot, dry winds are consistently most severe and which areas are relatively sheltered. We also analyzed over half a century of mapped fire history in chaparral ecosystems of the region, finding that our models successfully predict where the largest wildfires are most likely to occur. There is a surprising lack of information about extreme wind patterns worldwide, and more quantitative analyses of their spatial variation will be important for effective fire management and sustainable long-term urban development on fire-prone landscapes.
Racial segregation in postbellum Southern cities: The case of Washington, D.C.
Logan, John R.
2018-01-01
BACKGROUND Segregation in Southern cities has been described as a 20th-century development, layered onto an earlier pattern in which whites and blacks (both slaves and free black people) shared the same neighborhoods. Urban historians have pointed out ways in which the Southern postbellum pattern was less benign, but studies relying on census data aggregated by administrative areas – and segregation measures based on this data – have not confirmed their observations. METHODS This study is based mainly on 100% microdata from the 1880 census that has been mapped at the address level in Washington, D.C. This data makes it possible to examine in detail the unique spatial configuration of segregation that is found in this city, especially the pattern of housing in alleys. RESULTS While segregation appears to have been low, as reflected in data by wards and even by much smaller enumeration districts, analyses at a finer spatial scale reveal strongly patterned separation between blacks and whites at this early time. CONTRIBUTION This research provides much new information about segregation in a major Southern city at the end of the 19th century. It also demonstrates the importance of dealing explicitly with issues of both scale and spatial pattern in studies of segregation. PMID:29375269
Spatial filtering precedes motion detection.
Morgan, M J
1992-01-23
When we perceive motion on a television or cinema screen, there must be some process that allows us to track moving objects over time: if not, the result would be a conflicting mass of motion signals in all directions. A possible mechanism, suggested by studies of motion displacement in spatially random patterns, is that low-level motion detectors have a limited spatial range, which ensures that they tend to be stimulated over time by the same object. This model predicts that the direction of displacement of random patterns cannot be detected reliably above a critical absolute displacement value (Dmax) that is independent of the size or density of elements in the display. It has been inferred that Dmax is a measure of the size of motion detectors in the visual pathway. Other studies, however, have shown that Dmax increases with element size, in which case the most likely interpretation is that Dmax depends on the probability of false matches between pattern elements following a displacement. These conflicting accounts are reconciled here by showing that Dmax is indeed determined by the spacing between the elements in the pattern, but only after fine detail has been removed by a physiological prefiltering stage: the filter required to explain the data has a similar size to the receptive field of neurons in the primate magnocellular pathway. The model explains why Dmax can be increased by removing high spatial frequencies from random patterns, and simplifies our view of early motion detection.
NASA Astrophysics Data System (ADS)
Sohn, Hayley; Ackerman, Paul; Smalyukh, Ivan
Three-dimensional (3D) topological solitons arise in field theories ranging from particle physics to condensed matter and cosmology. They are the 3D counterparts of 2D skyrmions (often called ``baby skyrmions''), which attract a great deal of interest in studies of chiral ferromagnets and enable the emerging field of skyrmionics. In chiral nematic liquid crystals, the stability of such solitons is enhanced by the chiral medium's tendency to twist the director field describing the 3D spatial patterns of molecular alignment. However, their experimental realization, control and detailed studies remain limited. We combine experimental realization and numerical modeling of such light-responsive solitonic structures, including elementary torons and hopfions, in confined chiral nematic liquid crystals with photo-tunable cholesteric pitch. We show that the optical tunability of the pitch allows for using low-intensity light to control the soliton stability, dimensions, spatial patterning and dynamics.
Spatial analysis and characteristics of pig farming in Thailand.
Thanapongtharm, Weerapong; Linard, Catherine; Chinson, Pornpiroon; Kasemsuwan, Suwicha; Visser, Marjolein; Gaughan, Andrea E; Epprech, Michael; Robinson, Timothy P; Gilbert, Marius
2016-10-06
In Thailand, pig production intensified significantly during the last decade, with many economic, epidemiological and environmental implications. Strategies toward more sustainable future developments are currently investigated, and these could be informed by a detailed assessment of the main trends in the pig sector, and on how different production systems are geographically distributed. This study had two main objectives. First, we aimed to describe the main trends and geographic patterns of pig production systems in Thailand in terms of pig type (native, breeding, and fattening pigs), farm scales (smallholder and large-scale farming systems) and type of farming systems (farrow-to-finish, nursery, and finishing systems) based on a very detailed 2010 census. Second, we aimed to study the statistical spatial association between these different types of pig farming distribution and a set of spatial variables describing access to feed and markets. Over the last decades, pig population gradually increased, with a continuously increasing number of pigs per holder, suggesting a continuing intensification of the sector. The different pig-production systems showed very contrasted geographical distributions. The spatial distribution of large-scale pig farms corresponds with that of commercial pig breeds, and spatial analysis conducted using Random Forest distribution models indicated that these were concentrated in lowland urban or peri-urban areas, close to means of transportation, facilitating supply to major markets such as provincial capitals and the Bangkok Metropolitan region. Conversely the smallholders were distributed throughout the country, with higher densities located in highland, remote, and rural areas, where they supply local rural markets. A limitation of the study was that pig farming systems were defined from the number of animals per farm, resulting in their possible misclassification, but this should have a limited impact on the main patterns revealed by the analysis. The very contrasted distribution of different pig production systems present opportunities for future regionalization of pig production. More specifically, the detailed geographical analysis of the different production systems will be used to spatially-inform planning decisions for pig farming accounting for the specific health, environment and economical implications of the different pig production systems.
USDA-ARS?s Scientific Manuscript database
During drought, xylem conduits are susceptible to hydraulic dysfunction caused by cavitation and gas embolism. Embolism formation and spread within xylem is dependent on conduit structure and network connectivity, but detailed spatial analysis has been limited due to a lack of non-destructive method...
Berdugo, Miguel; Kéfi, Sonia; Soliveres, Santiago; Maestre, Fernando T
2018-03-01
In the version of this Article originally published, the values of two of the functions used to calculate the multifunctionality index were incorrect, which affected Figs 3,4 of the main article and Supplementary Figs 3,4,5,6,9. Please see the correction notice for full details.
Pattern analysis of eastern spruce budworm Choristoneura fumiferana dispersal
Dean P. Anderson; Brian R. Sturtevant
2011-01-01
Dispersal has been proposed as an important mechanism in the broad-scale synchronisation of insect outbreaks by linking spatially disjunct populations. Evidence suggests that dispersal is influenced by landscape structure, phenology, temperature, and air currents; however, the details remain unclear due to the difficulty of quantifying dispersal. In this study, we used...
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
Damped-driven granular chains: An ideal playground for dark breathers and multibreathers
NASA Astrophysics Data System (ADS)
Chong, C.; Li, F.; Yang, J.; Williams, M. O.; Kevrekidis, I. G.; Kevrekidis, P. G.; Daraio, C.
2014-03-01
By applying an out-of-phase actuation at the boundaries of a uniform chain of granular particles, we demonstrate experimentally that time-periodic and spatially localized structures with a nonzero background (so-called dark breathers) emerge for a wide range of parameter values and initial conditions. We demonstrate a remarkable control over the number of breathers within the multibreather pattern that can be "dialed in" by varying the frequency or amplitude of the actuation. The values of the frequency (or amplitude) where the transition between different multibreather states occurs are predicted accurately by the proposed theoretical model, which is numerically shown to support exact dark breather and multibreather solutions. Moreover, we visualize detailed temporal and spatial profiles of breathers and, especially, of multibreathers using a full-field probing technology and enable a systematic favorable comparison among theory, computation, and experiments. A detailed bifurcation analysis reveals that the dark and multibreather families are connected in a "snaking" pattern, providing a roadmap for the identification of such fundamental states and their bistability in the laboratory.
NASA Astrophysics Data System (ADS)
Heuer, A.; Casper, M. C.; Vohland, M.
2009-04-01
Processes in natural systems and the resulting patterns occur in ecological space and time. To study natural structures and to understand the functional processes it is necessary to identify the relevant spatial and temporal space at which these all occur; or with other words to isolate spatial and temporal patterns. In this contribution we will concentrate on the spatial aspects of agro-ecological data analysis. Data were derived from two agricultural plots, each of about 5 hectares, in the area of Newel, located in Western Palatinate, Germany. The plots had been conventionally cultivated with a crop rotation of winter rape, winter wheat and spring barley. Data about physical and chemical soil properties, vegetation and topography were i) collected by measurements in the field during three vegetation periods (2005-2008) and/or ii) derived from hyperspectral image data, acquired by a HyMap airborne imaging sensor (2005). To detect spatial variability within the plots, we applied three different approaches that examine and describe relationships among data. First, we used variography to get an overview of the data. A comparison of the experimental variograms facilitated to distinguish variables, which seemed to occur in related or dissimilar spatial space. Second, based on data available in raster-format basic cell statistics were conducted, using a geographic information system. Here we could make advantage of the powerful classification and visualization tool, which supported the spatial distribution of patterns. Third, we used an approach that is being used for visualization of complex highly dimensional environmental data, the Kohonen self-organizing map. The self-organizing map (SOM) uses multidimensional data that gets further reduced in dimensionality (2-D) to detect similarities in data sets and correlation between single variables. One of SOM's advantages is its powerful visualization capability. The combination of the three approaches leads to comprehensive and reasonable results, which will be presented in detail. It can be concluded, that the chosen strategy made it possible to complement preliminary findings, to validate the results of a single approach and to clearly delineate spatial patterns.
NASA Astrophysics Data System (ADS)
Blume, T.; Hassler, S. K.; Weiler, M.
2017-12-01
Hydrological science still struggles with the fact that while we wish for spatially continuous images or movies of state variables and fluxes at the landscape scale, most of our direct measurements are point measurements. To date regional measurements resolving landscape scale patterns can only be obtained by remote sensing methods, with the common drawback that they remain near the earth surface and that temporal resolution is generally low. However, distributed monitoring networks at the landscape scale provide the opportunity for detailed and time-continuous pattern exploration. Even though measurements are spatially discontinuous, the large number of sampling points and experimental setups specifically designed for the purpose of landscape pattern investigation open up new avenues of regional hydrological analyses. The CAOS hydrological observatory in Luxembourg offers a unique setup to investigate questions of temporal stability, pattern evolution and persistence of certain states. The experimental setup consists of 45 sensor clusters. These sensor clusters cover three different geologies, two land use classes, five different landscape positions, and contrasting aspects. At each of these sensor clusters three soil moisture/soil temperature profiles, basic climate variables, sapflow, shallow groundwater, and stream water levels were measured continuously for the past 4 years. We will focus on characteristic landscape patterns of various hydrological state variables and fluxes, studying their temporal stability on the one hand and the dependence of patterns on hydrological states on the other hand (e.g. wet vs dry). This is extended to time-continuous pattern analysis based on time series of spatial rank correlation coefficients. Analyses focus on the absolute values of soil moisture, soil temperature, groundwater levels and sapflow, but also investigate the spatial pattern of the daily changes of these variables. The analysis aims at identifying hydrologic signatures of the processes or landscape characteristics acting as major controls. While groundwater, soil water and transpiration are closely linked by the water cycle, they are controlled by different processes and we expect this to be reflected in interlinked but not necessarily congruent patterns and responses.
2014-01-01
Background There have been large-scale outbreaks of hand, foot and mouth disease (HFMD) in Mainland China over the last decade. These events varied greatly across the country. It is necessary to identify the spatial risk factors and spatial distribution patterns of HFMD for public health control and prevention. Climate risk factors associated with HFMD occurrence have been recognized. However, few studies discussed the socio-economic determinants of HFMD risk at a space scale. Methods HFMD records in Mainland China in May 2008 were collected. Both climate and socio-economic factors were selected as potential risk exposures of HFMD. Odds ratio (OR) was used to identify the spatial risk factors. A spatial autologistic regression model was employed to get OR values of each exposures and model the spatial distribution patterns of HFMD risk. Results Results showed that both climate and socio-economic variables were spatial risk factors for HFMD transmission in Mainland China. The statistically significant risk factors are monthly average precipitation (OR = 1.4354), monthly average temperature (OR = 1.379), monthly average wind speed (OR = 1.186), the number of industrial enterprises above designated size (OR = 17.699), the population density (OR = 1.953), and the proportion of student population (OR = 1.286). The spatial autologistic regression model has a good goodness of fit (ROC = 0.817) and prediction accuracy (Correct ratio = 78.45%) of HFMD occurrence. The autologistic regression model also reduces the contribution of the residual term in the ordinary logistic regression model significantly, from 17.25 to 1.25 for the odds ratio. Based on the prediction results of the spatial model, we obtained a map of the probability of HFMD occurrence that shows the spatial distribution pattern and local epidemic risk over Mainland China. Conclusions The autologistic regression model was used to identify spatial risk factors and model spatial risk patterns of HFMD. HFMD occurrences were found to be spatially heterogeneous over the Mainland China, which is related to both the climate and socio-economic variables. The combination of socio-economic and climate exposures can explain the HFMD occurrences more comprehensively and objectively than those with only climate exposures. The modeled probability of HFMD occurrence at the county level reveals not only the spatial trends, but also the local details of epidemic risk, even in the regions where there were no HFMD case records. PMID:24731248
Neural Representation of Spatial Topology in the Rodent Hippocampus
Chen, Zhe; Gomperts, Stephen N.; Yamamoto, Jun; Wilson, Matthew A.
2014-01-01
Pyramidal cells in the rodent hippocampus often exhibit clear spatial tuning in navigation. Although it has been long suggested that pyramidal cell activity may underlie a topological code rather than a topographic code, it remains unclear whether an abstract spatial topology can be encoded in the ensemble spiking activity of hippocampal place cells. Using a statistical approach developed previously, we investigate this question and related issues in greater details. We recorded ensembles of hippocampal neurons as rodents freely foraged in one and two-dimensional spatial environments, and we used a “decode-to-uncover” strategy to examine the temporally structured patterns embedded in the ensemble spiking activity in the absence of observed spatial correlates during periods of rodent navigation or awake immobility. Specifically, the spatial environment was represented by a finite discrete state space. Trajectories across spatial locations (“states”) were associated with consistent hippocampal ensemble spiking patterns, which were characterized by a state transition matrix. From this state transition matrix, we inferred a topology graph that defined the connectivity in the state space. In both one and two-dimensional environments, the extracted behavior patterns from the rodent hippocampal population codes were compared against randomly shuffled spike data. In contrast to a topographic code, our results support the efficiency of topological coding in the presence of sparse sample size and fuzzy space mapping. This computational approach allows us to quantify the variability of ensemble spiking activity, to examine hippocampal population codes during off-line states, and to quantify the topological complexity of the environment. PMID:24102128
Lebedev, Mikhail A; Pimashkin, Alexey; Ossadtchi, Alexei
2018-01-01
According to the currently prevailing theory, hippocampal formation constructs and maintains cognitive spatial maps. Most of the experimental evidence for this theory comes from the studies on navigation in laboratory rats and mice, typically male animals. While these animals exhibit a rich repertoire of behaviors associated with navigation, including locomotion, head movements, whisking, sniffing, raring and scent marking, the contribution of these behavioral patterns to the hippocampal spatially-selective activity has not been sufficiently studied. Instead, many publications have considered animal position in space as the major variable that affects the firing of hippocampal place cells and entorhinal grid cells. Here we argue that future work should focus on a more detailed examination of different behaviors exhibited during navigation to better understand the mechanism of spatial tuning in hippocampal neurons. As an inquiry in this direction, we have analyzed data from two datasets, shared online, containing recordings from rats navigating in square and round arenas. Our analyses revealed patchy navigation patterns, evident from the spatial maps of animal position, velocity and acceleration. Moreover, grid cells available in the datasets exhibited similar periodicity as the navigation parameters. These findings indicate that activity of grid cells could affect navigation parameters and/or vice versa. Additionally, we speculate that scent marks left by navigating animals could contribute to neuronal responses while rats and mice sniff their environment; the act of sniffing could modulate neuronal discharges even in virtual visual environments. Accordingly, we propose that future experiments should contain additional controls for navigation patterns, whisking, sniffing and maps composed of scent marks.
Noise and Dynamical Pattern Selection in Solidification
NASA Technical Reports Server (NTRS)
Kurtze, Douglas A.
1997-01-01
The overall goal of this project was to understand in more detail how a pattern-forming system can adjust its spacing. "Pattern-forming systems," in this context, are nonequilibrium contina whose state is determined by experimentally adjustable control parameter. Below some critical value of the control system then has available to it a range of linearly stable, spatially periodic steady states, each characterized by a spacing which can lie anywhere within some band of values. These systems like directional solidification, where the solidification front is planar when the ratio of growth velocity to thermal gradient is below its critical value, but takes on a cellular shape above critical. They also include systems without interfaces, such as Benard convection, where it is the fluid velocity field which changes from zero to something spatially periodic as the control parameter is increased through its critical value. The basic question to be addressed was that of how the system chooses one of its myriad possible spacings when the control parameter is above critical, and in particular the role of noise in the selection process. Previous work on explosive crystallization had suggested that one spacing in the range should be preferred, in the sense that weak noise should eventually drive the system to that spacing. That work had also suggested a heuristic argument for identifying the preferred spacing. The project had three main objectives: to understand in more detail how a pattern-forming system can adjust its spacing; to investigate how noise drives a system to its preferred spacing; and to extend the heuristic argument for a preferred spacing in explosive crystallization to other pattern-forming systems.
NASA Astrophysics Data System (ADS)
Tzou, J. C.; Ward, M. J.
2018-06-01
Spot patterns, whereby the activator field becomes spatially localized near certain dynamically-evolving discrete spatial locations in a bounded multi-dimensional domain, is a common occurrence for two-component reaction-diffusion (RD) systems in the singular limit of a large diffusivity ratio. In previous studies of 2-D localized spot patterns for various specific well-known RD systems, the domain boundary was assumed to be impermeable to both the activator and inhibitor, and the reaction-kinetics were assumed to be spatially uniform. As an extension of this previous theory, we use formal asymptotic methods to study the existence, stability, and slow dynamics of localized spot patterns for the singularly perturbed 2-D Brusselator RD model when the domain boundary is only partially impermeable, as modeled by an inhomogeneous Robin boundary condition, or when there is an influx of inhibitor across the domain boundary. In our analysis, we will also allow for the effect of a spatially variable bulk feed term in the reaction kinetics. By applying our extended theory to the special case of one-spot patterns and ring patterns of spots inside the unit disk, we provide a detailed analysis of the effect on spot patterns of these three different sources of heterogeneity. In particular, when there is an influx of inhibitor across the boundary of the unit disk, a ring pattern of spots can become pinned to a ring-radius closer to the domain boundary. Under a Robin condition, a quasi-equilibrium ring pattern of spots is shown to exhibit a novel saddle-node bifurcation behavior in terms of either the inhibitor diffusivity, the Robin constant, or the ambient background concentration. A spatially variable bulk feed term, with a concentrated source of "fuel" inside the domain, is shown to yield a saddle-node bifurcation structure of spot equilibria, which leads to qualitatively new spot-pinning behavior. Results from our asymptotic theory are validated from full numerical simulations of the Brusselator model.
Theories of Simplification and Scaling of Spatially Distributed Processes. Chapter 12
NASA Technical Reports Server (NTRS)
Levin, Simon A.; Pacala, Stephen W.
1997-01-01
The problem of scaling is at the heart of ecological theory, the essence of understanding and of the development of a predictive capability. The description of any system depends on the spatial, temporal, and organizational perspective chosen; hence it is essential to understand not only how patterns and dynamics vary with scale, but also how patterns at one scale are manifestations of processes operating at other scales. Evolution has shaped the characteristics of species in ways that result in scale displacement: Each species experiences the environment at its own unique set of spatial and temporal scales and interfaces the biota through unique assemblages of phenotypes. In this way, coexistence becomes possible, and biodiversity is enhanced. By averaging over space, time, and biological interactions, a genotype filters variation at fine scales and selects the arena in which it will face the vicissitudes of nature. Variation at finer scales is then noise, of minor importance to the survival and dynamics of the species, and consequently of minor importance in any attempt at description. In attempting to model ecological interactions in space, contributors throughout this book have struggled with a trade-off between simplification and "realistic" complexity and detail. Although the challenge of simplification is widely recognized in ecology, less appreciated is the intertwining of scaling questions and scaling laws with the process of simplification. In the context of this chapter simplification will in general mean the use of spatial or ensemble means and low-order moments to capture more detailed interactions by integrating over given areas. In this way, one can derive descriptions of the system at different spatial scales, which provides the essentials for the extraction of scaling laws by examination of how system properties vary with scale.
Disturbance History,Spatial Variability, and Patterns of Biodiversity
NASA Astrophysics Data System (ADS)
Bendix, J.; Wiley, J. J.; Commons, M.
2012-12-01
The intermediate disturbance hypothesis predicts that species diversity will be maximized in environments experiencing intermediate intensity disturbance, after an intermediate timespan. Because many landscapes comprise mosaics with complex disturbance histories, the theory implies that each patch in those mosaics should have a distinct level of diversity reflecting combined impact of the magnitude of disturbance and the time since it occurred. We modeled the changing patterns of species richness across a landscape experiencing varied scenarios of simulated disturbance. Model outputs show that individual landscape patches have highly variable species richness through time, with the details reflecting the timing, intensity and sequence of their disturbance history. When the results are mapped across the landscape, the resulting temporal and spatial complexity illustrates both the contingent nature of diversity and the danger of generalizing about the impacts of disturbance.
Effect of spatial organisation behaviour on upscaling the overland flow formation in an arable land
NASA Astrophysics Data System (ADS)
Silasari, Rasmiaditya; Blöschl, Günter
2014-05-01
Overland flow during rainfall events on arable land is important to investigate as it affects the land erosion process and water quality in the river. The formation of overland flow may happen through different ways (i.e. Hortonian overland flow, saturation excess overland flow) which is influenced by the surface and subsurface soil characteristics (i.e. land cover, soil infiltration rate). As the soil characteristics vary throughout the entire catchment, it will form distinct spatial patterns with organised or random behaviour. During the upscaling of hydrological processes from plot to catchment scale, this behaviour will become substantial since organised patterns will result in higher spatial connectivity and thus higher conductivity. However, very few of the existing studies explicitly address this effect of spatial organisations of the patterns in upscaling the hydrological processes to the catchment scale. This study will assess the upscaling of overland flow formation with concerns of spatial organisation behaviour of the patterns by application of direct field observations under natural conditions using video camera and soil moisture sensors and investigation of the underlying processes using a physical-based hydrology model. The study area is a Hydrological Open Air Laboratory (HOAL) located at Petzenkirchen, Lower Austria. It is a 64 ha catchment with land use consisting of arable land (87%), forest (6%), pasture (5%) and paved surfaces (2%). A video camera is installed 7m above the ground on a weather station mast in the middle of the arable land to monitor the overland flow patterns during rainfall events in a 2m x 6m plot scale. Soil moisture sensors with continuous measurement at different depth (5, 10, 20 and 50cm) are installed at points where the field is monitored by the camera. The patterns of overland flow formation and subsurface flow state at the plot scale will be generated using a coupled surface-subsurface flow physical-based hydrology model. The observation data will be assimilated into the model to verify the corresponding processes between surface and subsurface flow during the rainfall events. The patterns of conductivity then will be analyzed at catchment scale using the spatial stochastic analysis based on the classification of soil characteristics of the entire catchment. These patterns of conductivity then will be applied in the model at catchment scale to see how the organisational behaviour can affect the spatial connectivity of the hydrological processes and the results of the catchment response. A detailed modelling of the underlying processes in the physical-based model will allow us to see the direct effect of the spatial connectivity to the occurring surface and subsurface flow. This will improve the analysis of the effect of spatial organisations of the patterns in upscaling the hydrological processes from plot to catchment scale.
Comparing fire spread algorithms using equivalence testing and neutral landscape models
Brian R. Miranda; Brian R. Sturtevant; Jian Yang; Eric J. Gustafson
2009-01-01
We demonstrate a method to evaluate the degree to which a meta-model approximates spatial disturbance processes represented by a more detailed model across a range of landscape conditions, using neutral landscapes and equivalence testing. We illustrate this approach by comparing burn patterns produced by a relatively simple fire spread algorithm with those generated by...
Spatial self-organization in hybrid models of multicellular adhesion
NASA Astrophysics Data System (ADS)
Bonforti, Adriano; Duran-Nebreda, Salva; Montañez, Raúl; Solé, Ricard
2016-10-01
Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically cellular automata or reaction-diffusion systems. A different class of dynamical processes involves the correlated movement of agents over space, which can be mediated through chemotactic movement or minimization of cell-cell interaction energy. A classic example of the latter is given by the formation of spatially segregated assemblies when cells display differential adhesion. Here, we consider a new class of dynamical models, involving cell adhesion among two stochastically exchangeable cell states as a minimal model capable of exhibiting well-defined, ordered spatial patterns. Our results suggest that a whole space of pattern-forming rules is hosted by the combination of physical differential adhesion and the value of probabilities modulating cell phenotypic switching, showing that Turing-like patterns can be obtained without resorting to reaction-diffusion processes. If the model is expanded allowing cells to proliferate and die in an environment where diffusible nutrient and toxic waste are at play, different phases are observed, characterized by regularly spaced patterns. The analysis of the parameter space reveals that certain phases reach higher population levels than other modes of organization. A detailed exploration of the mean-field theory is also presented. Finally, we let populations of cells with different adhesion matrices compete for reproduction, showing that, in our model, structural organization can improve the fitness of a given cell population. The implications of these results for ecological and evolutionary models of pattern formation and the emergence of multicellularity are outlined.
NASA Astrophysics Data System (ADS)
Vaudour, E.; Leclercq, L.; Gilliot, J. M.; Chaignon, B.
2017-06-01
For any wine estate, there is a need to demarcate homogeneous within-vineyard zones ('terroirs') so as to manage grape production, which depends on vine biological condition. Until now, the studies performing digital zoning of terroirs have relied on recent spatial data and scant attention has been paid to ancient geoinformation likely to retrace past biological condition of vines and especially occurrence of vine mortality. Is vine mortality characterized by recurrent and specific patterns and if so, are these patterns related to terroir units and/or past landuse? This study aimed at performing a historical and spatial tracing of vine mortality patterns using a long time-series of aerial survey images (1947-2010), in combination with recent data: soil apparent electrical conductivity EM38 measurements, very high resolution Pléiades satellite images, and a detailed field survey. Within a 6 ha-estate in the Southern Rhone Valley, landuse and planting history were retraced and the map of missing vines frequency was constructed from the whole time series including a 2015-Pléiades panchromatic band. Within-field terroir units were obtained from a support vector machine classifier computed on the spectral bands and NDVI of Pléiades images, EM38 data and morphometric data. Repeated spatial patterns of missing vines were highlighted throughout several plantings, uprootings, and vine replacements, and appeared to match some within-field terroir units, being explained by their specific soil characteristics, vine/soil management choices and the past landuse of the 1940s. Missing vines frequency was spatially correlated with topsoil CaCO3 content, and negatively correlated with topsoil iron, clay, total N, organic C contents and NDVI. A retrospective spatio-temporal assessment of terroir therefore brings a renewed focus on some key parameters for maintaining a sustainable grape production.
Darling, John A; Folino-Rorem, Nadine C
2009-12-01
Discerning patterns of post-establishment spread by invasive species is critically important for the design of effective management strategies and the development of appropriate theoretical models predicting spatial expansion of introduced populations. The globally invasive colonial hydrozoan Cordylophora produces propagules both sexually and vegetatively and is associated with multiple potential dispersal mechanisms, making it a promising system to investigate complex patterns of population structure generated throughout the course of rapid range expansion. Here, we explore genetic patterns associated with the spread of this taxon within the North American Great Lakes basin. We collected intensively from eight harbours in the Chicago area in order to conduct detailed investigation of local population expansion. In addition, we collected from Lakes Michigan, Erie, and Ontario, as well as Lake Cayuga in the Finger Lakes of upstate New York in order to assess genetic structure on a regional scale. Based on data from eight highly polymorphic microsatellite loci we examined the spatial extent of clonal genotypes, assessed levels of neutral genetic diversity, and explored patterns of migration and dispersal at multiple spatial scales through assessment of population level genetic differentiation (pairwise F(ST) and factorial correspondence analysis), Bayesian inference of population structure, and assignment tests on individual genotypes. Results of these analyses indicate that Cordylophora populations in this region spread predominantly through sexually produced propagules, and that while limited natural larval dispersal can drive expansion locally, regional expansion likely relies on anthropogenic dispersal vectors.
Dimsdale-Zucker, Halle R; Ritchey, Maureen; Ekstrom, Arne D; Yonelinas, Andrew P; Ranganath, Charan
2018-01-18
The hippocampus plays a critical role in spatial and episodic memory. Mechanistic models predict that hippocampal subfields have computational specializations that differentially support memory. However, there is little empirical evidence suggesting differences between the subfields, particularly in humans. To clarify how hippocampal subfields support human spatial and episodic memory, we developed a virtual reality paradigm where participants passively navigated through houses (spatial contexts) across a series of videos (episodic contexts). We then used multivariate analyses of high-resolution fMRI data to identify neural representations of contextual information during recollection. Multi-voxel pattern similarity analyses revealed that CA1 represented objects that shared an episodic context as more similar than those from different episodic contexts. CA23DG showed the opposite pattern, differentiating between objects encountered in the same episodic context. The complementary characteristics of these subfields explain how we can parse our experiences into cohesive episodes while retaining the specific details that support vivid recollection.
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.
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
NASA Astrophysics Data System (ADS)
Kariyawasam, T.; Essa, A.; Gong, M.; Sudakov, I.
2017-12-01
Greenhouse gas emissions from tundra lakes are a significant positive feedback to the atmosphere in a changing climate as a pronounced growth of the numbers of tundra lake patterns has been observed in the Arctic region. Detailed knowledge of spatial dynamics of lake patterns in a changing arctic tundra landscape and their geometrical properties is therefore potentially valuable, in order to understand and accurately model the sources of greenhouse gas emissions from boreal permafrost. Our goal is to use a collection of historical topographic maps and satellite imagery of tundra lakes to conduct computational image analyses for examining spatial dynamics of Tundra lake patterns. Our approach is based upon analyzing area-perimeter data of thousands of tundra lakes to compute the fractal dimension to study the tundra lake pattern geometry, which have been used to classify pollen grains by textual patterning (Mander, 2016), vegetation in dryland ecosystems (Mander, 2017) and melt pond patterns (Hohenegger, 2012). By analyzing area - perimeter data for over 900 lakes we find that for both historical topographic maps and current satellite imagery, the fractal dimension D is stable at 1.6 for Tundra lakes with area less than about 100km2. For Tundra lake sizes bigger than 100 km2 fractal dimension takes values close to 2 and less than one indicative of structural changes in Tundra lake pattern geometry. Furthermore the current study did not reveal any percolation transition above some critical threshold in Tundra lake evolution. The results of the study will provide scientists with new data on these aspects of tundra lakes to help characterize the geomorphology of spatial patterns in arctic tundra lakes.
Ezzati, M; Saleh, H; Kammen, D M
2000-01-01
Acute and chronic respiratory diseases, which are causally linked to exposure to indoor air pollution in developing countries, are the leading cause of global morbidity and mortality. Efforts to develop effective intervention strategies and detailed quantification of the exposure-response relationship for indoor particulate matter require accurate estimates of exposure. We used continuous monitoring of indoor air pollution and individual time-activity budget data to construct detailed profiles of exposure for 345 individuals in 55 households in rural Kenya. Data for analysis were from two hundred ten 14-hour days of continuous real-time monitoring of concentrations of particulate matter [less than/equal to] 10 microm in aerodynamic diameter and the location and activities of household members. These data were supplemented by data on the spatial dispersion of pollution and from interviews. Young and adult women had not only the highest absolute exposure to particulate matter (2, 795 and 4,898 microg/m(3) average daily exposure concentrations, respectively) but also the largest exposure relative to that of males in the same age group (2.5 and 4.8 times, respectively). Exposure during brief high-intensity emission episodes accounts for 31-61% of the total exposure of household members who take part in cooking and 0-11% for those who do not. Simple models that neglect the spatial distribution of pollution within the home, intense emission episodes, and activity patterns underestimate exposure by 3-71% for different demographic subgroups, resulting in inaccurate and biased estimations. Health and intervention impact studies should therefore consider in detail the critical role of exposure patterns, including the short periods of intense emission, to avoid spurious assessments of risks and benefits. PMID:11017887
Lee, Soo-Rang; Jo, Yeong-Seok; Park, Chan-Ho; Friedman, Jonathan M.; Olson, Matthew S.
2018-01-01
Understanding the complex influences of landscape and anthropogenic elements that shape the population genetic structure of invasive species provides insight into patterns of colonization and spread. The application of landscape genomics techniques to these questions may offer detailed, previously undocumented insights into factors influencing species invasions. We investigated the spatial pattern of genetic variation and the influences of landscape factors on population similarity in an invasive riparian shrub, saltcedar (Tamarix L.) by analysing 1,997 genomewide SNP markers for 259 individuals from 25 populations collected throughout the southwestern United States. Our results revealed a broad-scale spatial genetic differentiation of saltcedar populations between the Colorado and Rio Grande river basins and identified potential barriers to population similarity along both river systems. River pathways most strongly contributed to population similarity. In contrast, low temperature and dams likely served as barriers to population similarity. We hypothesize that large-scale geographic patterns in genetic diversity resulted from a combination of early introductions from distinct populations, the subsequent influence of natural selection, dispersal barriers and founder effects during range expansion.
NASA Astrophysics Data System (ADS)
Kim, J.; Lin, S. Y.; Tsai, Y.; Singh, S.; Singh, T.
2017-12-01
A large ground deformation which may be caused by a significant groundwater depletion of the Northwest India Aquifer has been successfully observed throughout space geodesy techniques (Tsai et al, 2016). Employing advanced time-series ScanSAR InSAR analysis and Gravity Recovery and Climate Experiment (GRACE) satellites data, it revealed 400-km wide huge ground deformation in and around Haryana. It was further notified that the Ambala city located in northern Haryana district shown the most significant ground subsidence with maximum cumulative deformation up to 0.2 meters within 3 years in contrast to the nearby cities such as Patiala and Chandigarh that did not present similar subsidence. In this study, we investigated the details of "Ambala Anomaly" employing advanced time-series InSAR and spatial analyses together with local geology and anthropogenic contexts and tried to identify the factors causing such a highly unique ground deformation pattern. To explore the pattern and trend of Ambala' subsidence, we integrated the time-series deformation results of both ascending L-band PALSAR-1 (Phased Array type L-band Synthetic Aperture Radar) from 2007/1 to 2011/1 and descending C-band ASAR (Advanced Synthetic Aperture Radar) from 2008/9 to 2010/8 to process the 3D decomposition, expecting to reveal the asymmetric movement of the surface. In addition. The spatial analyses incorporating detected ground deformations and local economical/social factors were then applied for the interpretation of "Ambala Anomaly". The detailed interrelationship of driving factors of the "Ambala Anomaly" and the spatial pattern of corresponding ground subsidence will be further demonstrated. After all, we determined the uniqueness of Ambala subsidence possibly be driven by both anthropogenic behaviors including the rapid growth rate of population and constructing of industrial centers as well as the natural geological characteristics and sediment deposition.
Validating a spatially distributed hydrological model with soil morphology data
NASA Astrophysics Data System (ADS)
Doppler, T.; Honti, M.; Zihlmann, U.; Weisskopf, P.; Stamm, C.
2013-10-01
Spatially distributed hydrological models are popular tools in hydrology and they are claimed to be useful to support management decisions. Despite the high spatial resolution of the computed variables, calibration and validation is often carried out only on discharge time-series at specific locations due to the lack of spatially distributed reference data. Because of this restriction, the predictive power of these models, with regard to predicted spatial patterns, can usually not be judged. An example of spatial predictions in hydrology is the prediction of saturated areas in agricultural catchments. These areas can be important source areas for the transport of agrochemicals to the stream. We set up a spatially distributed model to predict saturated areas in a 1.2 km2 catchment in Switzerland with moderate topography. Around 40% of the catchment area are artificially drained. We measured weather data, discharge and groundwater levels in 11 piezometers for 1.5 yr. For broadening the spatially distributed data sets that can be used for model calibration and validation, we translated soil morphological data available from soil maps into an estimate of the duration of soil saturation in the soil horizons. We used redox-morphology signs for these estimates. This resulted in a data set with high spatial coverage on which the model predictions were validated. In general, these saturation estimates corresponded well to the measured groundwater levels. We worked with a model that would be applicable for management decisions because of its fast calculation speed and rather low data requirements. We simultaneously calibrated the model to the groundwater levels in the piezometers and discharge. The model was able to reproduce the general hydrological behavior of the catchment in terms of discharge and absolute groundwater levels. However, the accuracy of the groundwater level predictions was not high enough to be used for the prediction of saturated areas. The groundwater level dynamics were not adequately reproduced and the predicted spatial patterns of soil saturation did not correspond to the patterns estimated from the soil map. Our results indicate that an accurate prediction of the groundwater level dynamics of the shallow groundwater in our catchment that is subject to artificial drainage would require a more complex model. Especially high spatial resolution and very detailed process representations at the boundary between the unsaturated and the saturated zone are expected to be crucial. The data needed for such a detailed model are not generally available. The high computational demand and the complex model setup would require more resources than the direct identification of saturated areas in the field. This severely hampers the practical use of such models despite their usefulness for scientific purposes.
Insights into the Genetic History of French Cattle from Dense SNP Data on 47 Worldwide Breeds
Gautier, Mathieu; Laloë, Denis; Moazami-Goudarzi, Katayoun
2010-01-01
Background Modern cattle originate from populations of the wild extinct aurochs through a few domestication events which occurred about 8,000 years ago. Newly domesticated populations subsequently spread worldwide following breeder migration routes. The resulting complex historical origins associated with both natural and artificial selection have led to the differentiation of numerous different cattle breeds displaying a broad phenotypic variety over a short period of time. Methodology/Principal Findings This study gives a detailed assessment of cattle genetic diversity based on 1,121 individuals sampled in 47 populations from different parts of the world (with a special focus on French cattle) genotyped for 44,706 autosomal SNPs. The analyzed data set consisted of new genotypes for 296 individuals representing 14 French cattle breeds which were combined to those available from three previously published studies. After characterizing SNP polymorphism in the different populations, we performed a detailed analysis of genetic structure at both the individual and population levels. We further searched for spatial patterns of genetic diversity among 23 European populations, most of them being of French origin, under the recently developed spatial Principal Component analysis framework. Conclusions/Significance Overall, such high throughput genotyping data confirmed a clear partitioning of the cattle genetic diversity into distinct breeds. In addition, patterns of differentiation among the three main groups of populations—the African taurine, the European taurine and zebus—may provide some additional support for three distinct domestication centres. Finally, among the European cattle breeds investigated, spatial patterns of genetic diversity were found in good agreement with the two main migration routes towards France, initially postulated based on archeological evidence. PMID:20927341
Dynamically-downscaled projections of changes in temperature extremes over China
NASA Astrophysics Data System (ADS)
Guo, Junhong; Huang, Guohe; Wang, Xiuquan; Li, Yongping; Lin, Qianguo
2018-02-01
In this study, likely changes in extreme temperatures (including 16 indices) over China in response to global warming throughout the twenty-first century are investigated through the PRECIS regional climate modeling system. The PRECIS experiment is conducted at a spatial resolution of 25 km and is driven by a perturbed-physics ensemble to reflect spatial variations and model uncertainties. Simulations of present climate (1961-1990) are compared with observations to validate the model performance in reproducing historical climate over China. Results indicate that the PRECIS demonstrates reasonable skills in reproducing the spatial patterns of observed extreme temperatures over the most regions of China, especially in the east. Nevertheless, the PRECIS shows a relatively poor performance in simulating the spatial patterns of extreme temperatures in the western mountainous regions, where its driving GCM exhibits more uncertainties due to lack of insufficient observations and results in more errors in climate downscaling. Future spatio-temporal changes of extreme temperature indices are then analyzed for three successive periods (i.e., 2020s, 2050s and 2080s). The projected changes in extreme temperatures by PRECIS are well consistent with the results of the major global climate models in both spatial and temporal patterns. Furthermore, the PRECIS demonstrates a distinct superiority in providing more detailed spatial information of extreme indices. In general, all extreme indices show similar changes in spatial pattern: large changes are projected in the north while small changes are projected in the south. In contrast, the temporal patterns for all indices vary differently over future periods: the warm indices, such as SU, TR, WSDI, TX90p, TN90p and GSL are likely to increase, while the cold indices, such as ID, FD, CSDI, TX10p and TN10p, are likely to decrease with time in response to global warming. Nevertheless, the magnitudes of changes in all indices tend to decrease gradually with time, indicating the projected warming will begin to slow down in the late of this century. In addition, the projected range of changes for all indices would become larger with time, suggesting more uncertainties would be involved in long-term climate projections.
Continuous attractor network models of grid cell firing based on excitatory–inhibitory interactions
Shipston‐Sharman, Oliver; Solanka, Lukas
2016-01-01
Abstract Neurons in the medial entorhinal cortex encode location through spatial firing fields that have a grid‐like organisation. The challenge of identifying mechanisms for grid firing has been addressed through experimental and theoretical investigations of medial entorhinal circuits. Here, we discuss evidence for continuous attractor network models that account for grid firing by synaptic interactions between excitatory and inhibitory cells. These models assume that grid‐like firing patterns are the result of computation of location from velocity inputs, with additional spatial input required to oppose drift in the attractor state. We focus on properties of continuous attractor networks that are revealed by explicitly considering excitatory and inhibitory neurons, their connectivity and their membrane potential dynamics. Models at this level of detail can account for theta‐nested gamma oscillations as well as grid firing, predict spatial firing of interneurons as well as excitatory cells, show how gamma oscillations can be modulated independently from spatial computations, reveal critical roles for neuronal noise, and demonstrate that only a subset of excitatory cells in a network need have grid‐like firing fields. Evaluating experimental data against predictions from detailed network models will be important for establishing the mechanisms mediating grid firing. PMID:27870120
A general modeling framework for describing spatially structured population dynamics
Sample, Christine; Fryxell, John; Bieri, Joanna; Federico, Paula; Earl, Julia; Wiederholt, Ruscena; Mattsson, Brady; Flockhart, Tyler; Nicol, Sam; Diffendorfer, James E.; Thogmartin, Wayne E.; Erickson, Richard A.; Norris, D. Ryan
2017-01-01
Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network-based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life-history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network-based population is modeled with discrete time steps. Using both theoretical and real-world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network-based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance that comparative analyses are colored by model details rather than general principles
X-ray phase-contrast tomography for high-spatial-resolution zebrafish muscle imaging
NASA Astrophysics Data System (ADS)
Vågberg, William; Larsson, Daniel H.; Li, Mei; Arner, Anders; Hertz, Hans M.
2015-11-01
Imaging of muscular structure with cellular or subcellular detail in whole-body animal models is of key importance for understanding muscular disease and assessing interventions. Classical histological methods for high-resolution imaging methods require excision, fixation and staining. Here we show that the three-dimensional muscular structure of unstained whole zebrafish can be imaged with sub-5 μm detail with X-ray phase-contrast tomography. Our method relies on a laboratory propagation-based phase-contrast system tailored for detection of low-contrast 4-6 μm subcellular myofibrils. The method is demonstrated on 20 days post fertilization zebrafish larvae and comparative histology confirms that we resolve individual myofibrils in the whole-body animal. X-ray imaging of healthy zebrafish show the expected structured muscle pattern while specimen with a dystrophin deficiency (sapje) displays an unstructured pattern, typical of Duchenne muscular dystrophy. The method opens up for whole-body imaging with sub-cellular detail also of other types of soft tissue and in different animal models.
Boundary-driven anomalous spirals in oscillatory media
NASA Astrophysics Data System (ADS)
Kessler, David A.; Levine, Herbert
2017-06-01
We study a heretofore ignored class of spiral patterns in oscillatory media as characterized by the complex Landau-Ginzburg model. These spirals emerge from modulating the growth rate as a function of r, thereby turning off the instability at large r. They are uniquely determined by matching to this outer condition, lifting a degeneracy in the set of steady-state solutions of the original equations. Unlike the well-studied spiral which acts as a wave source, has a simple core structure and is insensitive to the details of the boundary on which no-flux conditions are imposed, these new spirals are wave sinks, have non-monotonic wavefront curvature near the core, and can be patterned by the form of the spatial boundary. We predict that these anomalous spirals could be produced in nonlinear optics experiments via spatially modulating the gain of the medium.
NASA Astrophysics Data System (ADS)
Chapman, S. C.; Dods, J.; Gjerloev, J. W.
2017-12-01
Observations of how the solar wind interacts with earth's magnetosphere, and its dynamical response, are increasingly becoming a data analytics challenge. Constellations of satellites observe the solar corona, the upstream solar wind and throughout earth's magnetosphere. These data are multipoint in space and extended in time, so in principle are ideal for study using dynamical networks to characterize the full time evolving spatial pattern. We focus here on analysis of data from the full set of 100+ auroral ground based magnetometer stations that have been collated by SuperMAG. Spatio-temporal patterns of correlation between the magnetometer time series can be used to form a dynamical network [1]. The properties of the network can then be captured by (time dependent) network parameters. This offers the possibility of characterizing detailed spatio-temporal pattern by a few parameters, so that many events can then be compared [2] with each other. Whilst networks are in widespread use in the data analytics of societal and commercial data, there are additional challenges in their application to physical timeseries. Determining whether two nodes (here, ground based magnetometer stations) are connected in a network (seeing the same dynamics) requires normalization w.r.t. the detailed sensitivities and dynamical responses of specific observing stations and seasonal conductivity variations and we have developed methods to achieve this dynamical normalization. The detailed properties of the network capture time dependent spatial correlation in the magnetometer responses and we will show how this can be used to infer a transient current system response to magnetospheric activity. [l] Dods et al, J. Geophys. Res 120, doi:10.1002/2015JA02 (2015). [2] Dods et al, J. Geophys. Res. 122, doi:10.1002/2016JA02 (2017).
NASA Astrophysics Data System (ADS)
Gonzalez-Hidalgo, Jose Carlos; Brunetti, Michele; Martin, De Luis
2010-05-01
Precipitation is one of the most important climate elements directly affecting human society, economic activities and natural systems; at the same time it is the most variable climate element, and its changes can be detected only if a spatially dense network of observations is used. Due to this, the last AR4 report renewed interest in the study of precipitation, and suggests focusing on detailed sub-regional studies, with a preference for those areas where water is a scarce resource with heavy demands placed on it. We have developed the new MOPREDAS database (MOnthly PREcipitation DAtabase of Spain) by exploiting the total amount of data available at Spanish Meteorological Agency (AEMET, formerly INM). These provide a total of 2670 complete and homogeneous series for the period 1946-2005 after exhaustive quality control and reconstruction processes, and at present is the most complete and extensive monthly precipitation dataset uptodated in Spain, including dense information up to 1500 m o.l.s.. MOPREDAS has been created with the aim of analyzing the behaviour of precipitation in the conterminous provinces of Spain, and to validate the downscaling of climate models on a detailed spatial level. To this end, the station data were also interpolated on a regular grid, at 1/10 of degree of resolution, over the whole Spain. Trend analysis (Mann-Kendall text, p <0,10) confirms great spatial and temporal variability in the behaviour of precipitation across Spain between 1946-2005. Except March, June and October, no generalized significant pattern have been found, but subregional areas with homogeneous trend were detected. MOPREDAS shows a global decrease of precipitation in March that affects 68.9% of Spain and 31.8% in June, while in October the area affected by positive trends is 33.7% of land (p<0.10). We detected numerous sub-regional coherent patterns well delineated by topographic factors, and passing unnoticed until now due to inadequate data density. These results suggest that both global and local factors affect the spatial distribution of trends in the Iberian Peninsula, being mountain chains the most significant geographical factor in determining the spatial distribution of monthly trends on a detailed, sub-regional spatial scale.
Understanding the spatial complexity of surface hoar from slope to range scale
NASA Astrophysics Data System (ADS)
Hendrikx, J.
2015-12-01
Surface hoar, once buried, is a common weak layer type in avalanche accidents in continental and intermountain snowpacks around the World. Despite this, there is still limited understanding of the spatial variability in both the formation of, and eventual burial of, surface hoar at spatial scales which are of critical importance to avalanche forecasters. While it is relatively well understood that aspect plays an important role in the spatial location of the formation, and burial of these grain forms, due to the unequal distribution of incoming radiation, this factor alone does not explain the complex and often confusing spatial pattern of these grains forms throughout the landscape at different spatial scales. In this paper we present additional data from a unique data set including over two hundred days of manual observations of surface hoar at sixteen locations on Pioneer Mountain at the Yellowstone Club in southwestern Montana. Using this wealth of observational data located on different aspects, elevations and exposures, coupled with detailed meteorological observations, and detailed slope scale observation, we examine the spatial variability of surface hoar at this scale, and examine the factors that control its spatial distribution. Our results further supports our preliminary work, which shows that small-scale slope conditions, meteorological differences, and local scale lapse rates, can greatly influence the spatial variability of surface hoar, over and above that which aspect alone can explain. These results highlight our incomplete understanding of the processes at both the slope and range scale, and are likely to have implications for both regional and local scale avalanche forecasting in environments where surface hoar cause ongoing instabilities.
Abundant Topological Outliers in Social Media Data and Their Effect on Spatial Analysis.
Westerholt, Rene; Steiger, Enrico; Resch, Bernd; Zipf, Alexander
2016-01-01
Twitter and related social media feeds have become valuable data sources to many fields of research. Numerous researchers have thereby used social media posts for spatial analysis, since many of them contain explicit geographic locations. However, despite its widespread use within applied research, a thorough understanding of the underlying spatial characteristics of these data is still lacking. In this paper, we investigate how topological outliers influence the outcomes of spatial analyses of social media data. These outliers appear when different users contribute heterogeneous information about different phenomena simultaneously from similar locations. As a consequence, various messages representing different spatial phenomena are captured closely to each other, and are at risk to be falsely related in a spatial analysis. Our results reveal indications for corresponding spurious effects when analyzing Twitter data. Further, we show how the outliers distort the range of outcomes of spatial analysis methods. This has significant influence on the power of spatial inferential techniques, and, more generally, on the validity and interpretability of spatial analysis results. We further investigate how the issues caused by topological outliers are composed in detail. We unveil that multiple disturbing effects are acting simultaneously and that these are related to the geographic scales of the involved overlapping patterns. Our results show that at some scale configurations, the disturbances added through overlap are more severe than at others. Further, their behavior turns into a volatile and almost chaotic fluctuation when the scales of the involved patterns become too different. Overall, our results highlight the critical importance of thoroughly considering the specific characteristics of social media data when analyzing them spatially.
NASA Astrophysics Data System (ADS)
Wang, Hui; Wellmann, Florian; Verweij, Elizabeth; von Hebel, Christian; van der Kruk, Jan
2017-04-01
Lateral and vertical spatial heterogeneity of subsurface properties such as soil texture and structure influences the available water and resource supply for crop growth. High-resolution mapping of subsurface structures using non-invasive geo-referenced geophysical measurements, like electromagnetic induction (EMI), enables a characterization of 3D soil structures, which have shown correlations to remote sensing information of the crop states. The benefit of EMI is that it can return 3D subsurface information, however the spatial dimensions are limited due to the labor intensive measurement procedure. Although active and passive sensors mounted on air- or space-borne platforms return 2D images, they have much larger spatial dimensions. Combining both approaches provides us with a potential pathway to extend the detailed 3D geophysical information to a larger area by using remote sensing information. In this study, we aim at extracting and providing insights into the spatial and statistical correlation of the geophysical and remote sensing observations of the soil/vegetation continuum system. To this end, two key points need to be addressed: 1) how to detect and recognize the geometric patterns (i.e., spatial heterogeneity) from multiple data sets, and 2) how to quantitatively describe the statistical correlation between remote sensing information and geophysical measurements. In the current study, the spatial domain is restricted to shallow depths up to 3 meters, and the geostatistical database contains normalized difference vegetation index (NDVI) derived from RapidEye satellite images and apparent electrical conductivities (ECa) measured from multi-receiver EMI sensors for nine depths of exploration ranging from 0-2.7 m. The integrated data sets are mapped into both the physical space (i.e. the spatial domain) and feature space (i.e. a two-dimensional space framed by the NDVI and the ECa data). Hidden Markov Random Fields (HMRF) are employed to model the underlying heterogeneities in spatial domain and finite Gaussian mixture models are adopted to quantitatively describe the statistical patterns in terms of center vectors and covariance matrices in feature space. A recently developed parallel stochastic clustering algorithm is adopted to implement the HMRF models and the Markov chain Monte Carlo based Bayesian inference. Certain spatial patterns such as buried paleo-river channels covered by shallow sediments are investigated as typical examples. The results indicate that the geometric patterns of the subsurface heterogeneity can be represented and quantitatively characterized by HMRF. Furthermore, the statistical patterns of the NDVI and the EMI data from the soil/vegetation-continuum system can be inferred and analyzed in a quantitative manner.
Spatially distributed modeling of soil organic carbon across China with improved accuracy
NASA Astrophysics Data System (ADS)
Li, Qi-quan; Zhang, Hao; Jiang, Xin-ye; Luo, Youlin; Wang, Chang-quan; Yue, Tian-xiang; Li, Bing; Gao, Xue-song
2017-06-01
There is a need for more detailed spatial information on soil organic carbon (SOC) for the accurate estimation of SOC stock and earth system models. As it is effective to use environmental factors as auxiliary variables to improve the prediction accuracy of spatially distributed modeling, a combined method (HASM_EF) was developed to predict the spatial pattern of SOC across China using high accuracy surface modeling (HASM), artificial neural network (ANN), and principal component analysis (PCA) to introduce land uses, soil types, climatic factors, topographic attributes, and vegetation cover as predictors. The performance of HASM_EF was compared with ordinary kriging (OK), OK, and HASM combined, respectively, with land uses and soil types (OK_LS and HASM_LS), and regression kriging combined with land uses and soil types (RK_LS). Results showed that HASM_EF obtained the lowest prediction errors and the ratio of performance to deviation (RPD) presented the relative improvements of 89.91%, 63.77%, 55.86%, and 42.14%, respectively, compared to the other four methods. Furthermore, HASM_EF generated more details and more realistic spatial information on SOC. The improved performance of HASM_EF can be attributed to the introduction of more environmental factors, to explicit consideration of the multicollinearity of selected factors and the spatial nonstationarity and nonlinearity of relationships between SOC and selected factors, and to the performance of HASM and ANN. This method may play a useful tool in providing more precise spatial information on soil parameters for global modeling across large areas.
Trends of Cyclone Characteristics in the Arctic and Their Patterns From Different Reanalysis Data
NASA Astrophysics Data System (ADS)
Zahn, Matthias; Akperov, Mirseid; Rinke, Annette; Feser, Frauke; Mokhov, Igor I.
2018-03-01
Cyclones in the Arctic are detected and tracked in four different reanalysis data sets from 1981 to 2010. In great detail the spatial and seasonal patterns of changes are scrutinized with regards to their frequencies, depths, and sizes. We find common spatial patterns for their occurrences, with centers of main activity over the seas in winter, and more activity over land and over the North Pole in summer. The deep cyclones are more frequent in winter, and the number of weak cyclones peaks in summer. Overall, we find a good agreement of our tracking results across the different reanalyses. Regarding the frequency changes, we find strong decreases in the Barents Sea and along the Russian coast toward the North Pole and increases over most of the central Arctic Ocean and toward the Pacific in winter. Areas of increasing and decreasing frequencies are of similar size in winter. In summer there is a longish region of increase from the Laptev Sea toward Greenland, over the Canadian archipelago, and over some smaller regions west of Novaya Zemlya and over the Russia. The larger part of the Arctic experiences a frequency decrease. All the summer changes are found statistically unrelated to the winter patterns. In addition, the frequency changes are found unrelated to changes in cyclone depth and size. There is generally good agreement across the different reanalyses in the spatial patterns of the trend sign. However, the magnitudes of changes in a particular region may strongly differ across the data.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Barnes, Hannah C.; Houze, Robert A.
To equitably compare the spatial pattern of ice microphysical processes produced by three microphysical parameterizations with each other, observations, and theory, simulations of tropical oceanic mesoscale convective systems (MCSs) in the Weather Research and Forecasting (WRF) model were forced to develop the same mesoscale circulations as observations by assimilating radial velocity data from a Doppler radar. The same general layering of microphysical processes was found in observations and simulations with deposition anywhere above the 0°C level, aggregation at and above the 0°C level, melting at and below the 0°C level, and riming near the 0°C level. Thus, this study ismore » consistent with the layered ice microphysical pattern portrayed in previous conceptual models and indicated by dual-polarization radar data. Spatial variability of riming in the simulations suggests that riming in the midlevel inflow is related to convective-scale vertical velocity perturbations. Finally, this study sheds light on limitations of current generally available bulk microphysical parameterizations. In each parameterization, the layers in which aggregation and riming took place were generally too thick and the frequency of riming was generally too high compared to the observations and theory. Additionally, none of the parameterizations produced similar details in every microphysical spatial pattern. Discrepancies in the patterns of microphysical processes between parameterizations likely factor into creating substantial differences in model reflectivity patterns. It is concluded that improved parameterizations of ice-phase microphysics will be essential to obtain reliable, consistent model simulations of tropical oceanic MCSs.« less
NASA Technical Reports Server (NTRS)
Thomas, Randall W.; Ustin, Susan L.
1987-01-01
A preliminary assessment was made of Airborne Imaging Spectrometer (AIS) data for discriminating and characterizing vegetation in a semiarid environment. May and October AIS data sets were acquired over a large alluvial fan in eastern California, on which were found Great Basin desert shrub communities. Maximum likelihood classification of a principal components representation of the May AIS data enabled discrimination of subtle spatial detail in images relating to vegetation and soil characteristics. The spatial patterns in the May AIS classification were, however, too detailed for complete interpretation with existing ground data. A similar analysis of the October AIS data yielded poor results. Comparison of AIS results with a similar analysis of May Landsat Thematic Mapper data showed that the May AIS data contained approximately three to four times as much spectrally coherent information. When only two shortwave infrared TM bands were used, results were similar to those from AIS data acquired in October.
Characterization of fracture aperture for groundwater flow and transport
NASA Astrophysics Data System (ADS)
Sawada, A.; Sato, H.; Tetsu, K.; Sakamoto, K.
2007-12-01
This paper presents experiments and numerical analyses of flow and transport carried out on natural fractures and transparent replica of fractures. The purpose of this study was to improve the understanding of the role of heterogeneous aperture patterns on channelization of groundwater flow and dispersion in solute transport. The research proceeded as follows: First, a precision plane grinder was applied perpendicular to the fracture plane to characterize the aperture distribution on a natural fracture with 1 mm of increment size. Although both time and labor were intensive, this approach provided a detailed, three dimensional picture of the pattern of fracture aperture. This information was analyzed to provide quantitative measures for the fracture aperture distribution, including JRC (Joint Roughness Coefficient) and fracture contact area ratio. These parameters were used to develop numerical models with corresponding synthetic aperture patterns. The transparent fracture replica and numerical models were then used to study how transport is affected by the aperture spatial pattern. In the transparent replica, transmitted light intensity measured by a CCD camera was used to image channeling and dispersion due to the fracture aperture spatial pattern. The CCD image data was analyzed to obtain the quantitative fracture aperture and tracer concentration data according to Lambert-Beer's law. The experimental results were analyzed using the numerical models. Comparison of the numerical models to the transparent replica provided information about the nature of channeling and dispersion due to aperture spatial patterns. These results support to develop a methodology for defining representative fracture aperture of a simplified parallel fracture model for flow and transport in heterogeneous fractures for contaminant transport analysis.
Annual economic impacts of seasonal influenza on US counties: Spatial heterogeneity and patterns
2012-01-01
Economic impacts of seasonal influenza vary across US counties, but little estimation has been conducted at the county level. This research computed annual economic costs of seasonal influenza for 3143 US counties based on Census 2010, identified inherent spatial patterns, and investigated cost-benefits of vaccination strategies. The computing model modified existing methods for national level estimation, and further emphasized spatial variations between counties, in terms of population size, age structure, influenza activity, and income level. Upon such a model, four vaccination strategies that prioritize different types of counties were simulated and their net returns were examined. The results indicate that the annual economic costs of influenza varied from $13.9 thousand to $957.5 million across US counties, with a median of $2.47 million. Prioritizing vaccines to counties with high influenza attack rates produces the lowest influenza cases and highest net returns. This research fills the current knowledge gap by downscaling the estimation to a county level, and adds spatial variability into studies of influenza economics and interventions. Compared to the national estimates, the presented statistics and maps will offer detailed guidance for local health agencies to fight against influenza. PMID:22594494
Estimation of Global 1km-grid Terrestrial Carbon Exchange Part I: Developing Inputs and Modelling
NASA Astrophysics Data System (ADS)
Sasai, T.; Murakami, K.; Kato, S.; Matsunaga, T.; Saigusa, N.; Hiraki, K.
2015-12-01
Global terrestrial carbon cycle largely depends on a spatial pattern in land cover type, which is heterogeneously-distributed over regional and global scales. However, most studies, which aimed at the estimation of carbon exchanges between ecosystem and atmosphere, remained within several tens of kilometers grid spatial resolution, and the results have not been enough to understand the detailed pattern of carbon exchanges based on ecological community. Improving the sophistication of spatial resolution is obviously necessary to enhance the accuracy of carbon exchanges. Moreover, the improvement may contribute to global warming awareness, policy makers and other social activities. In this study, we show global terrestrial carbon exchanges (net ecosystem production, net primary production, and gross primary production) with 1km-grid resolution. As methodology for computing the exchanges, we 1) developed a global 1km-grid climate and satellite dataset based on the approach in Setoyama and Sasai (2013); 2) used the satellite-driven biosphere model (Biosphere model integrating Eco-physiological And Mechanistic approaches using Satellite data: BEAMS) (Sasai et al., 2005, 2007, 2011); 3) simulated the carbon exchanges by using the new dataset and BEAMS by the use of a supercomputer that includes 1280 CPU and 320 GPGPU cores (GOSAT RCF of NIES). As a result, we could develop a global uniform system for realistically estimating terrestrial carbon exchange, and evaluate net ecosystem production in each community level; leading to obtain highly detailed understanding of terrestrial carbon exchanges.
High Resolution Orientation Imaging Microscopy
2012-05-02
Structure of In-Situ Deformations of Steel , TMS, San Diego, 2011 13. Jay Basinger, David Fullwood, Brent Adams, EBSD Detail Extraction for Greater Spatial...Its use has contributed to the development of new steels , aluminum alloys, high TC superconductors, electronic materials, lead-free solders, optical...Resolution The simulated pattern method has been used to recover lattice tetragonality in high-strength low- alloy steels . Since the level of
A compact electron gun for time-resolved electron diffraction
DOE Office of Scientific and Technical Information (OSTI.GOV)
Robinson, Matthew S.; Lane, Paul D.; Wann, Derek A., E-mail: derek.wann@york.ac.uk
A novel compact time-resolved electron diffractometer has been built with the primary goal of studying the ultrafast molecular dynamics of photoexcited gas-phase molecules. Here, we discuss the design of the electron gun, which is triggered by a Ti:Sapphire laser, before detailing a series of calibration experiments relating to the electron-beam properties. As a further test of the apparatus, initial diffraction patterns have been collected for thin, polycrystalline platinum samples, which have been shown to match theoretical patterns. The data collected demonstrate the focusing effects of the magnetic lens on the electron beam, and how this relates to the spatial resolutionmore » of the diffraction pattern.« less
Estimation of Global 1km-grid Terrestrial Carbon Exchange Part II: Evaluations and Applications
NASA Astrophysics Data System (ADS)
Murakami, K.; Sasai, T.; Kato, S.; Niwa, Y.; Saito, M.; Takagi, H.; Matsunaga, T.; Hiraki, K.; Maksyutov, S. S.; Yokota, T.
2015-12-01
Global terrestrial carbon cycle largely depends on a spatial pattern in land cover type, which is heterogeneously-distributed over regional and global scales. Many studies have been trying to reveal distribution of carbon exchanges between terrestrial ecosystems and atmosphere for understanding global carbon cycle dynamics by using terrestrial biosphere models, satellite data, inventory data, and so on. However, most studies remained within several tens of kilometers grid spatial resolution, and the results have not been enough to understand the detailed pattern of carbon exchanges based on ecological community and to evaluate the carbon stocks by forest ecosystems in each countries. Improving the sophistication of spatial resolution is obviously necessary to enhance the accuracy of carbon exchanges. Moreover, the improvement may contribute to global warming awareness, policy makers and other social activities. We show global terrestrial carbon exchanges (net ecosystem production, net primary production, and gross primary production) with 1km-grid resolution. The methodology for these estimations are shown in the 2015 AGU FM poster "Estimation of Global 1km-grid Terrestrial Carbon Exchange Part I: Developing Inputs and Modelling". In this study, we evaluated the carbon exchanges in various regions with other approaches. We used the satellite-driven biosphere model (BEAMS) as our estimations, GOSAT L4A CO2 flux data, NEP retrieved by NICAM and CarbonTracer2013 flux data, for period from Jun 2001 to Dec 2012. The temporal patterns for this period were indicated similar trends between BEAMS, GOSAT, NICAM, and CT2013 in many sub-continental regions. Then, we estimated the terrestrial carbon exchanges in each countries, and could indicated the temporal patterns of the exchanges in large carbon stock regions.Global terrestrial carbon cycle largely depends on a spatial pattern of land cover type, which is heterogeneously-distributed over regional and global scales. Many studies have been trying to reveal distribution of carbon exchanges between terrestrial ecosystems and atmosphere for understanding global carbon cycle dynamics by using terrestrial biosphere models, satellite data, inventory data, and so on. However, most studies remained within several tens of kilometers grid spatial resolution, and the results have not been enough to understand the detailed pattern of carbon exchanges based on ecological community and to evaluate the carbon stocks by forest ecosystems in each countries. Improving the sophistication of spatial resolution is obviously necessary to enhance the accuracy of carbon exchanges. Moreover, the improvement may contribute to global warming awareness, policy makers and other social activities. We show global terrestrial carbon exchanges (net ecosystem production, net primary production, and gross primary production) with 1km-grid resolution. The methodology for these estimations are shown in the 2015 AGU FM poster "Estimation of Global 1km-grid Terrestrial Carbon Exchange Part I: Developing Inputs and Modelling". In this study, we evaluated the carbon exchanges in various regions with other approaches. We used the satellite-driven biosphere model (BEAMS) as our estimations, GOSAT L4A CO2 flux data, NEP retrieved by NICAM and CarbonTracer2013 flux data, for period from Jun 2001 to Dec 2012. The temporal patterns for this period were indicated similar trends between BEAMS, GOSAT, NICAM, and CT2013 in many sub-continental regions. Then, we estimated the terrestrial carbon exchanges in each countries, and could indicated the temporal patterns of the exchanges in large carbon stock regions.
Fast and low-cost structured light pattern sequence projection.
Wissmann, Patrick; Forster, Frank; Schmitt, Robert
2011-11-21
We present a high-speed and low-cost approach for structured light pattern sequence projection. Using a fast rotating binary spatial light modulator, our method is potentially capable of projection frequencies in the kHz domain, while enabling pattern rasterization as low as 2 μm pixel size and inherently linear grayscale reproduction quantized at 12 bits/pixel or better. Due to the circular arrangement of the projected fringe patterns, we extend the widely used ray-plane triangulation method to ray-cone triangulation and provide a detailed description of the optical calibration procedure. Using the proposed projection concept in conjunction with the recently published coded phase shift (CPS) pattern sequence, we demonstrate high accuracy 3-D measurement at 200 Hz projection frequency and 20 Hz 3-D reconstruction rate. © 2011 Optical Society of America
NASA Astrophysics Data System (ADS)
König, Sara; Worrich, Anja; Wick, Lukas Y.; Miltner, Anja; Kästner, Matthias; Thullner, Martin; Centler, Florian; Banitz, Thomas; Frank, Karin
2016-04-01
Biodegradation of organic compounds in soil is an important microbial ecosystem service. Soil ecosystems are constantly exposed to disturbances of different spatial configurations and frequencies, challenging their ability to recover the biodegradation function. Thus, the response to these disturbances is crucial for the soil systems' biodegradation performance. The influence of spatial aspects of the disturbance regimes on long-term biodegradation dynamics under periodic disturbances has not been examined, yet. We applied a numerical simulation model considering bacterial growth, degradation, and dispersal to analyze the spatiotemporal biodegradation dynamics under disturbances occuring with different frequencies and with different spatial configurations. We found biodegradation performance decreasing in response to periodic disturbances but on average approaching a new quasi steady state. This mean performance of the disturbed systems increases with both, the interval length between disturbance events and the fragmentation of the spatial disturbance patterns. A detailed spatiotemporal analysis of degradation activity reveals that under highly fragmented disturbance patterns, biodegradation still takes place in the entire disturbed area. For moderately fragmented disturbance patterns, parts of the disturbed area become completely inactive. However, areas with high degradation activity emerge at the interface between disturbed and undisturbed areas, allowing the systems to maintain a relatively high degradation performance. Further decreasing the disturbance patterns' fragmentation, fewer interfaces between disturbed and undisturbed area and, thus, fewer active habitats occur, which reduces biodegradation performances. In additional simulations, we found that bacterial dispersal networks, as for example provided by fungal hyphae, usually increase the areas of high degradation activity and, thus, the biodegradation performance in presence of periodic disturbances. However, for some specific regimes with highly fragmented disturbance patterns, dispersal networks can in turn decrease the biodegradation performance. Our results show that spatial aspects of the periodic disturbance regime influence the biodegradation dynamics, indicating the relevance of spatial processes for functional stability. The level of connectivity between disturbed and undisturbed areas is crucial for the local and global dynamics of the ecosystem service biodegradation. Networks enhancing bacterial dispersal may often, but not always, increase the functional stability.
Stochastic Analysis and Probabilistic Downscaling of Soil Moisture
NASA Astrophysics Data System (ADS)
Deshon, J. P.; Niemann, J. D.; Green, T. R.; Jones, A. S.
2017-12-01
Soil moisture is a key variable for rainfall-runoff response estimation, ecological and biogeochemical flux estimation, and biodiversity characterization, each of which is useful for watershed condition assessment. These applications require not only accurate, fine-resolution soil-moisture estimates but also confidence limits on those estimates and soil-moisture patterns that exhibit realistic statistical properties (e.g., variance and spatial correlation structure). The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution (9-40 km) soil moisture from satellite remote sensing or land-surface models to produce fine-resolution (10-30 m) estimates. The model was designed to produce accurate deterministic soil-moisture estimates at multiple points, but the resulting patterns do not reproduce the variance or spatial correlation of observed soil-moisture patterns. The primary objective of this research is to generalize the EMT+VS model to produce a probability density function (pdf) for soil moisture at each fine-resolution location and time. Each pdf has a mean that is equal to the deterministic soil-moisture estimate, and the pdf can be used to quantify the uncertainty in the soil-moisture estimates and to simulate soil-moisture patterns. Different versions of the generalized model are hypothesized based on how uncertainty enters the model, whether the uncertainty is additive or multiplicative, and which distributions describe the uncertainty. These versions are then tested by application to four catchments with detailed soil-moisture observations (Tarrawarra, Satellite Station, Cache la Poudre, and Nerrigundah). The performance of the generalized models is evaluated by comparing the statistical properties of the simulated soil-moisture patterns to those of the observations and the deterministic EMT+VS model. The versions of the generalized EMT+VS model with normally distributed stochastic components produce soil-moisture patterns with more realistic statistical properties than the deterministic model. Additionally, the results suggest that the variance and spatial correlation of the stochastic soil-moisture variations do not vary consistently with the spatial-average soil moisture.
Kittle, Andrew M; Bukombe, John K; Sinclair, Anthony R E; Mduma, Simon A R; Fryxell, John M
2016-01-01
Where apex predators move on the landscape influences ecosystem structure and function and is therefore key to effective landscape-level management and species-specific conservation. However the factors underlying predator distribution patterns within functional ecosystems are poorly understood. Predator movement should be sensitive to the spatial patterns of inter-specific competitors, spatial variation in prey density, and landscape attributes that increase individual prey vulnerability. We investigated the relative role of these fundamental factors on seasonal resource utilization by a globally endangered apex carnivore, the African lion (Panthera leo) in Tanzania's Serengeti National Park. Lion space use was represented by novel landscape-level, modified utilization distributions (termed "localized density distributions") created from telemetry relocations of individual lions from multiple neighbouring prides. Spatial patterns of inter-specific competitors were similarly determined from telemetry re-locations of spotted hyenas (Crocuta crocuta), this system's primary competitor for lions; prey distribution was derived from 18 months of detailed census data; and remote sensing data was used to represent relevant habitat attributes. Lion space use was consistently influenced by landscape attributes that increase individual prey vulnerability to predation. Wet season activity, when available prey were scarce, was concentrated near embankments, which provide ambush opportunities, and dry season activity, when available prey were abundant, near remaining water sources where prey occurrence is predictable. Lion space use patterns were positively associated with areas of high prey biomass, but only in the prey abundant dry season. Finally, at the broad scale of this analysis, lion and hyena space use was positively correlated in the comparatively prey-rich dry season and unrelated in the wet season, suggesting lion movement was unconstrained by the spatial patterns of their main inter-specific competitors. The availability of potential prey and vulnerability of that prey to predation both motivate lion movement decisions, with their relative importance apparently mediated by overall prey abundance. With practical and theoretical implications, these results suggest that while top carnivores are consistently cognizant of how landscape features influence individual prey vulnerability, they also adopt a flexible approach to range use by adjusting spatial behaviour according to fluctuations in local prey abundance.
Abundant Topological Outliers in Social Media Data and Their Effect on Spatial Analysis
Zipf, Alexander
2016-01-01
Twitter and related social media feeds have become valuable data sources to many fields of research. Numerous researchers have thereby used social media posts for spatial analysis, since many of them contain explicit geographic locations. However, despite its widespread use within applied research, a thorough understanding of the underlying spatial characteristics of these data is still lacking. In this paper, we investigate how topological outliers influence the outcomes of spatial analyses of social media data. These outliers appear when different users contribute heterogeneous information about different phenomena simultaneously from similar locations. As a consequence, various messages representing different spatial phenomena are captured closely to each other, and are at risk to be falsely related in a spatial analysis. Our results reveal indications for corresponding spurious effects when analyzing Twitter data. Further, we show how the outliers distort the range of outcomes of spatial analysis methods. This has significant influence on the power of spatial inferential techniques, and, more generally, on the validity and interpretability of spatial analysis results. We further investigate how the issues caused by topological outliers are composed in detail. We unveil that multiple disturbing effects are acting simultaneously and that these are related to the geographic scales of the involved overlapping patterns. Our results show that at some scale configurations, the disturbances added through overlap are more severe than at others. Further, their behavior turns into a volatile and almost chaotic fluctuation when the scales of the involved patterns become too different. Overall, our results highlight the critical importance of thoroughly considering the specific characteristics of social media data when analyzing them spatially. PMID:27611199
Direct visualization of hemolymph flow in the heart of a grasshopper (Schistocerca americana)
Lee, Wah-Keat; Socha, John J
2009-01-01
Background Hemolymph flow patterns in opaque insects have never been directly visualized due to the lack of an appropriate imaging technique. The required spatial and temporal resolutions, together with the lack of contrast between the hemolymph and the surrounding soft tissue, are major challenges. Previously, indirect techniques have been used to infer insect heart motion and hemolymph flow, but such methods fail to reveal fine-scale kinematics of heartbeat and details of intra-heart flow patterns. Results With the use of microbubbles as high contrast tracer particles, we directly visualized hemolymph flow in a grasshopper (Schistocerca americana) using synchrotron x-ray phase-contrast imaging. In-vivo intra-heart flow patterns and the relationship between respiratory (tracheae and air sacs) and circulatory (heart) systems were directly observed for the first time. Conclusion Synchrotron x-ray phase contrast imaging is the only generally applicable technique that has the necessary spatial, temporal resolutions and sensitivity to directly visualize heart dynamics and flow patterns inside opaque animals. This technique has the potential to illuminate many long-standing questions regarding small animal circulation, encompassing topics such as retrograde heart flow in some insects and the development of flow in embryonic vertebrates. PMID:19272159
Zhao, Shuqing; Liu, Shuguang; Yin, Runsheng; Li, Zhengpeng; Deng, Yulin; Tan, Kun; Deng, Xiangzheng; Rothstein, David; Qi, Jiaguo
2010-01-01
Quantifying the spatial and temporal dynamics of carbon stocks in terrestrial ecosystems and carbon fluxes between the terrestrial biosphere and the atmosphere is critical to our understanding of regional patterns of carbon budgets. Here we use the General Ensemble biogeochemical Modeling System to simulate the terrestrial ecosystem carbon dynamics in the Jinsha watershed of China’s upper Yangtze basin from 1975 to 2000, based on unique combinations of spatial and temporal dynamics of major driving forces, such as climate, soil properties, nitrogen deposition, and land use and land cover changes. Our analysis demonstrates that the Jinsha watershed ecosystems acted as a carbon sink during the period of 1975–2000, with an average rate of 0.36 Mg/ha/yr, primarily resulting from regional climate variation and local land use and land cover change. Vegetation biomass accumulation accounted for 90.6% of the sink, while soil organic carbon loss before 1992 led to a lower net gain of carbon in the watershed, and after that soils became a small sink. Ecosystem carbon sink/source patterns showed a high degree of spatial heterogeneity. Carbon sinks were associated with forest areas without disturbances, whereas carbon sources were primarily caused by stand-replacing disturbances. It is critical to adequately represent the detailed fast-changing dynamics of land use activities in regional biogeochemical models to determine the spatial and temporal evolution of regional carbon sink/source patterns.
Morphology and spatial patterns of Macrotermes mounds in the SE Katanga, D.R. Congo
NASA Astrophysics Data System (ADS)
Bazirake Mujinya, Basile; Mees, Florias; Erens, Hans; Baert, Geert; Van Ranst, Eric
2015-04-01
The spatial distribution patterns and morphological characteristics of Macrotermes falciger mounds were investigated in the Lubumbashi area, D.R. Congo. Examination of the spatial patterns of M. falciger mounds on high resolution satellite images reveals a mean areal number density of 2.9 ± 0.4 mounds ha-1. The high relative number of inactive mounds in the region, along with their regular distribution pattern, suggests that current termite mound occurrences are largely palaeostructures. Mound positions in the habitat are consistent with intraspecific competition rather than soil and substrate characteristics as controlling factor. Detailed morphological description of five deep termite-mound profiles (~7 m height/depth) shows that carbonate pedofeatures are present in all studied profiles, in contrast to the control soils. They mainly occur in the form of soft powdery masses, nodules and coatings on ped faces, all clearly pedogenic. Carbonate coatings occur mainly between 1 m above the soil surface and 1 m below that level in all mound profiles. Carbonate nodules do show a different distribution pattern at each site. Furthermore, when the studied profiles are considered to represent a toposequence, the stone layer occurs at greater depth in topographically low areas compared to crest and slope positions, which is mainly conditioned by erosion. The clay content of epigeal mounds increases from the summit to the toe slope, which can be largely related to differences in parent material. The Mn-Fe oxide concentrations occurring in all studied termite mound profiles reflect a seasonally high perched water table beneath the mound, which is more pronounced at the lower slope positions.
Ecosystem classifications based on summer and winter conditions.
Andrew, Margaret E; Nelson, Trisalyn A; Wulder, Michael A; Hobart, George W; Coops, Nicholas C; Farmer, Carson J Q
2013-04-01
Ecosystem classifications map an area into relatively homogenous units for environmental research, monitoring, and management. However, their effectiveness is rarely tested. Here, three classifications are (1) defined and characterized for Canada along summertime productivity (moderate-resolution imaging spectrometer fraction of absorbed photosynthetically active radiation) and wintertime snow conditions (special sensor microwave/imager snow water equivalent), independently and in combination, and (2) comparatively evaluated to determine the ability of each classification to represent the spatial and environmental patterns of alternative schemes, including the Canadian ecozone framework. All classifications depicted similar patterns across Canada, but detailed class distributions differed. Class spatial characteristics varied with environmental conditions within classifications, but were comparable between classifications. There was moderate correspondence between classifications. The strongest association was between productivity classes and ecozones. The classification along both productivity and snow balanced these two sets of variables, yielding intermediate levels of association in all pairwise comparisons. Despite relatively low spatial agreement between classifications, they successfully captured patterns of the environmental conditions underlying alternate schemes (e.g., snow classes explained variation in productivity and vice versa). The performance of ecosystem classifications and the relevance of their input variables depend on the environmental patterns and processes used for applications and evaluation. Productivity or snow regimes, as constructed here, may be desirable when summarizing patterns controlled by summer- or wintertime conditions, respectively, or of climate change responses. General purpose ecosystem classifications should include both sets of drivers. Classifications should be carefully, quantitatively, and comparatively evaluated relative to a particular application prior to their implementation as monitoring and assessment frameworks.
[Scale effect of Nanjing urban green infrastructure network pattern and connectivity analysis.
Yu, Ya Ping; Yin, Hai Wei; Kong, Fan Hua; Wang, Jing Jing; Xu, Wen Bin
2016-07-01
Based on ArcGIS, Erdas, GuidosToolbox, Conefor and other software platforms, using morphological spatial pattern analysis (MSPA) and landscape connectivity analysis methods, this paper quantitatively analysed the scale effect, edge effect and distance effect of the Nanjing urban green infrastructure network pattern in 2013 by setting different pixel sizes (P) and edge widths in MSPA analysis, and setting different dispersal distance thresholds in landscape connectivity analysis. The results showed that the type of landscape acquired based on the MSPA had a clear scale effect and edge effect, and scale effects only slightly affected landscape types, whereas edge effects were more obvious. Different dispersal distances had a great impact on the landscape connectivity, 2 km or 2.5 km dispersal distance was a critical threshold for Nanjing. When selecting the pixel size 30 m of the input data and the edge wide 30 m used in the morphological model, we could get more detailed landscape information of Nanjing UGI network. Based on MSPA and landscape connectivity, analysis of the scale effect, edge effect, and distance effect on the landscape types of the urban green infrastructure (UGI) network was helpful for selecting the appropriate size, edge width, and dispersal distance when developing these networks, and for better understanding the spatial pattern of UGI networks and the effects of scale and distance on the ecology of a UGI network. This would facilitate a more scientifically valid set of design parameters for UGI network spatiotemporal pattern analysis. The results of this study provided an important reference for Nanjing UGI networks and a basis for the analysis of the spatial and temporal patterns of medium-scale UGI landscape networks in other regions.
Do we really use rainfall observations consistent with reality in hydrological modelling?
NASA Astrophysics Data System (ADS)
Ciampalini, Rossano; Follain, Stéphane; Raclot, Damien; Crabit, Armand; Pastor, Amandine; Moussa, Roger; Le Bissonnais, Yves
2017-04-01
Spatial and temporal patterns in rainfall control how water reaches soil surface and interacts with soil properties (i.e., soil wetting, infiltration, saturation). Once a hydrological event is defined by a rainfall with its spatiotemporal variability and by some environmental parameters such as soil properties (including land use, topographic and anthropic features), the evidence shows that each parameter variation produces different, specific outputs (e.g., runoff, flooding etc.). In this study, we focus on the effect of rainfall patterns because, due to the difficulty to dispose of detailed data, their influence in modelling is frequently underestimated or neglected. A rainfall event affects a catchment non uniformly, it is spatially localized and its pattern moves in space and time. The way and the time how the water reaches the soil and saturates it respect to the geometry of the catchment deeply influences soil saturation, runoff, and then sediment delivery. This research, approaching a hypothetical, simple case, aims to stimulate the debate on the reliability of the rainfall quality used in hydrological / soil erosion modelling. We test on a small catchment of the south of France (Roujan, Languedoc Roussillon) the influence of rainfall variability with the use of a HD hybrid hydrological - soil erosion model, combining a cinematic wave with the St. Venant equation and a simplified "bucket" conceptual model for ground water, able to quantify the effect of different spatiotemporal patterns of a very-high-definition synthetic rainfall. Results indicate that rainfall spatiotemporal patterns are crucial simulating an erosive event: differences between spatially uniform rainfalls, as frequently adopted in simulations, and some hypothetical rainfall patterns here applied, reveal that the outcome of a simulated event can be highly underestimated.
Understanding the robustness of Hadley cell response to wide variations in ocean heat transport
NASA Astrophysics Data System (ADS)
Rencurrel, M. C.; Rose, B. E. J.
2017-12-01
One important aspect of our climate system is the relationship between surface climate and the poleward energy transport in the atmosphere and ocean. Previous studies have shown that increases in poleward ocean heat transport (OHT) tend to warm the midlatitudes without strongly affecting tropical SSTs, resulting in a reduction in the equator-to-pole temperature gradient. This "tropical thermostat" effect depends crucially on a slowdown of the Hadley circulation (HC), with consequent changes in surface evaporation, atmospheric water vapor, and cloudiness. Here we extend previous studies by considering a wide range of spatial patterns of OHT, which we impose in a suite of slab-ocean aquaplanet GCM simulations. The forcing patterns are idealized but sample a variety of ocean circulation features. We find that the tropical thermostat and HC slowdown effects are relatively robust across all forcing patterns. A 1 PW increase in the amplitude of the prescribed OHT spatial pattern results in a global mean warming and a roughly 5 x 1010 kg/s decrease in HC mass flux, regardless of the detailed spatial structure of the imposed OHT. While the rate of HC slowdown is relatively robust, the mechanisms driving it are less so. Smaller, equator-to-subtropical scale OHT patterns are associated with greater reduced Gross Moist Stability (GMS) than the larger-scale OHT patterns. As the imposed OHT is limited equatorward, the HC becomes less efficient at transporting energy out of the tropics, implying that GMS has a modulating effect on the dynamical response of the cell. These experiments offer some new insights on the interplay between atmospheric dynamics and the radiative and hydrological aspects of global climate.
Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Data Analysis and Visualization; nternational Research Training Group ``Visualization of Large and Unstructured Data Sets,'' University of Kaiserslautern, Germany; Computational Research Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA
2008-05-12
The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses of the complex gene regulatory networks controlling animal development. We present an integrated visualization and analysis framework that supports user-guided data clustering to aid exploration of these new complex datasets. The interplay of data visualization and clustering-based data classification leads to improved visualization and enables a more detailed analysis than previously possible. We discuss (i) integration of data clustering and visualization into one framework; (ii) application of data clustering to 3D gene expression data; (iii)more » evaluation of the number of clusters k in the context of 3D gene expression clustering; and (iv) improvement of overall analysis quality via dedicated post-processing of clustering results based on visualization. We discuss the use of this framework to objectively define spatial pattern boundaries and temporal profiles of genes and to analyze how mRNA patterns are controlled by their regulatory transcription factors.« less
Resolution for color photography
NASA Astrophysics Data System (ADS)
Hubel, Paul M.; Bautsch, Markus
2006-02-01
Although it is well known that luminance resolution is most important, the ability to accurately render colored details, color textures, and colored fabrics cannot be overlooked. This includes the ability to accurately render single-pixel color details as well as avoiding color aliasing. All consumer digital cameras on the market today record in color and the scenes people are photographing are usually color. Yet almost all resolution measurements made on color cameras are done using a black and white target. In this paper we present several methods for measuring and quantifying color resolution. The first method, detailed in a previous publication, uses a slanted-edge target of two colored surfaces in place of the standard black and white edge pattern. The second method employs the standard black and white targets recommended in the ISO standard, but records these onto the camera through colored filters thus giving modulation between black and one particular color component; red, green, and blue color separation filters are used in this study. The third method, conducted at Stiftung Warentest, an independent consumer organization of Germany, uses a whitelight interferometer to generate fringe pattern targets of varying color and spatial frequency.
Scarpino, Samuel V.; Jansen, Patrick A.; Garzon-Lopez, Carol X.; Winkelhagen, Annemarie J. S.; Bohlman, Stephanie A.; Walsh, Peter D.
2010-01-01
Background The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama. Methodology and Principal Findings Aerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI. Conclusions and Significance We present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI. PMID:21124927
Effects of paddy rice agriculture on the seasonal dynamics of atmospheric methane concentration
NASA Astrophysics Data System (ADS)
Zhang, G.; Xiao, X.; Dong, J.; Zhang, Y.; Xin, F.; Zhou, Y.; Wang, J.; Wu, X.; Moore, B., III
2017-12-01
Methane (CH4) is an important greenhouse gas (GHG) and may account for 20 % of anticipated global warming. The atmospheric CH4 concentration was nearly constant from 1999 to 2006, following with a strong growth resumed since 2007. Previous study attributed the increase in CH4 to agriculture. Specifically, paddy rice agriculture is a significant source of CH4, but large uncertainty still exists on methane emission estimates from rice paddies, largely due to lack of detailed geospatial datasets of rice paddies. In this study, based on a pixel- and phenology-based image analysis system with multi-temporal MODIS imagery (MODIS-RICE), we generated the paddy rice map in 2005 to document the spatiotemporal pattern of paddy rice dynamics in Monsoon Asia, which accounts for more than 90% of the global rice production. Furthermore, we examined the effects of paddy rice agriculture on atmospheric CH4 concentration over Monsoon Asia, by comparing atmospheric CH4 concentration data from SCIAMACHY sensor and the paddy rice maps in 2005. We found a significant spatial consistency between spatial patterns of paddy rice and atmospheric CH4 concentration. Based on the high resolution paddy rice map, different seasonal dynamics of CH4 concentration, including single, double to triple peaks, were found based on the rice paddy distribution information. That suggests paddy rice agriculture contributes substantially to the spatial and seasonal pattern of atmospheric CH4 concentration in Monsoon Asia. This study provides satellite evidence for seasonal cycle of CH4 dynamics at regional scale, and suggests that shifting regime of paddy rice agriculture and cropping intensity could affect the seasonal dynamics and spatial pattern of atmospheric methane concentration.
Spatial and temporal patterns of deforestation in Rio Cajarí Extrative Reserve, Amapá, Brazil.
Funi, Claudia; Paese, Adriana
2012-01-01
The Rio Cajarí Extractive Reserve (RCER) is a sustainable use protected area located in Southern Amapá state, Brazil. This protected area is home to traditional agro-extractive families, but has been increasingly invaded by commercial agriculture producers. In this work, we test the hypothesis that the RCER implementation has distinctly affected spatial patterns of deforestation and rates of bare soil and secondary forest formation by the social groups occupying the protected area and its surrounding area. Detailed maps of vegetation cover and deforestation were elaborated, based on Landsat TM images from 1991, 1998, 2007 and 2008 and Linear Spectral Mixture Models. Based on an extensive fieldwork, patches were classified according to the agents causing deforestation and characterized with ten explanatory variables. A discriminant function analysis was used to identify homogeneous groups based on the data. Results show increased rates and distinct spatial patterns of deforestation by three groups: extractivists, non traditional commercial agriculture producers, and a less representative group constituted of miners, cattle and timber producers. In all analyzed dates, clearings by the extrativist community presented the highest total area and smaller average sizes and were located in close proximity to villages. Deforestation patches by the non-traditional group were exclusively associated with ombrophilous forests; these presented higher average sizes and proximity indexes, and showed increased aggregation and large cluster formation. No significant differences were observed in deforestation patterns by the three groups inside or outside the reserve.
Spatial and Temporal Patterns of Deforestation in Rio Cajarí Extrative Reserve, Amapá, Brazil
Funi, Claudia; Paese, Adriana
2012-01-01
The Rio Cajarí Extractive Reserve (RCER) is a sustainable use protected area located in Southern Amapá state, Brazil. This protected area is home to traditional agro-extractive families, but has been increasingly invaded by commercial agriculture producers. In this work, we test the hypothesis that the RCER implementation has distinctly affected spatial patterns of deforestation and rates of bare soil and secondary forest formation by the social groups occupying the protected area and its surrounding area. Detailed maps of vegetation cover and deforestation were elaborated, based on Landsat TM images from 1991, 1998, 2007 and 2008 and Linear Spectral Mixture Models. Based on an extensive fieldwork, patches were classified according to the agents causing deforestation and characterized with ten explanatory variables. A discriminant function analysis was used to identify homogeneous groups based on the data. Results show increased rates and distinct spatial patterns of deforestation by three groups: extractivists, non traditional commercial agriculture producers, and a less representative group constituted of miners, cattle and timber producers. In all analyzed dates, clearings by the extrativist community presented the highest total area and smaller average sizes and were located in close proximity to villages. Deforestation patches by the non-traditional group were exclusively associated with ombrophilous forests; these presented higher average sizes and proximity indexes, and showed increased aggregation and large cluster formation. No significant differences were observed in deforestation patterns by the three groups inside or outside the reserve. PMID:23284806
Crossover Patterning by the Beam-Film Model: Analysis and Implications
Zhang, Liangran; Liang, Zhangyi; Hutchinson, John; Kleckner, Nancy
2014-01-01
Crossing-over is a central feature of meiosis. Meiotic crossover (CO) sites are spatially patterned along chromosomes. CO-designation at one position disfavors subsequent CO-designation(s) nearby, as described by the classical phenomenon of CO interference. If multiple designations occur, COs tend to be evenly spaced. We have previously proposed a mechanical model by which CO patterning could occur. The central feature of a mechanical mechanism is that communication along the chromosomes, as required for CO interference, can occur by redistribution of mechanical stress. Here we further explore the nature of the beam-film model, its ability to quantitatively explain CO patterns in detail in several organisms, and its implications for three important patterning-related phenomena: CO homeostasis, the fact that the level of zero-CO bivalents can be low (the “obligatory CO”), and the occurrence of non-interfering COs. Relationships to other models are discussed. PMID:24497834
Ice shelf thickness change from 2010 to 2017
NASA Astrophysics Data System (ADS)
Hogg, A.; Shepherd, A.; Gilbert, L.; Muir, A. S.
2017-12-01
Floating ice shelves fringe 74 % of Antarctica's coastline, providing a direct link between the ice sheet and the surrounding oceans. Over the last 25 years, ice shelves have retreated, thinned, and collapsed catastrophically. While change in the mass of floating ice shelves has only a modest steric impact on the rate of sea-level rise, their loss can affect the mass balance of the grounded ice-sheet by influencing the rate of ice flow inland, due to the buttressing effect. Here we use CryoSat-2 altimetry data to map the detailed pattern of ice shelf thickness change in Antarctica. We exploit the dense spatial sampling and repeat coverage provided by the CryoSat-2 synthetic aperture radar interferometric mode (SARIn) to investigate data acquired between 2010 to the present day. We find that ice shelf thinning rates can exhibit large fluctuations over short time periods, and that the improved spatial resolution of CryoSat-2 enables us to resolve the spatial pattern of thinning with ever greater detail in Antarctica. In the Amundsen Sea, ice shelves at the terminus of the Pine Island and Thwaites glaciers have thinned at rates in excess of 5 meters per year for more than two decades. We observe the highest rates of basal melting near to the ice sheet grounding line, reinforcing the importance of high resolution datasets. On the Antarctic Peninsula, in contrast to the 3.8 m per decade of thinning observed since 1992, we measure an increase in the surface elevation of the Larsen-C Ice-Shelf during the CryoSat-2 period.
Alexander, Peter; Rabin, Sam; Anthoni, Peter; Henry, Roslyn; Pugh, Thomas A M; Rounsevell, Mark D A; Arneth, Almut
2018-02-27
Land use contributes to environmental change, but is also influenced by such changes. Climate and atmospheric carbon dioxide (CO 2 ) levels' changes alter agricultural crop productivity, plant water requirements and irrigation water availability. The global food system needs to respond and adapt to these changes, for example, by altering agricultural practices, including the crop types or intensity of management, or shifting cultivated areas within and between countries. As impacts and associated adaptation responses are spatially specific, understanding the land use adaptation to environmental changes requires crop productivity representations that capture spatial variations. The impact of variation in management practices, including fertiliser and irrigation rates, also needs to be considered. To date, models of global land use have selected agricultural expansion or intensification levels using relatively aggregate spatial representations, typically at a regional level, that are not able to characterise the details of these spatially differentiated responses. Here, we show results from a novel global modelling approach using more detailed biophysically derived yield responses to inputs with greater spatial specificity than previously possible. The approach couples a dynamic global vegetative model (LPJ-GUESS) with a new land use and food system model (PLUMv2), with results benchmarked against historical land use change from 1970. Land use outcomes to 2100 were explored, suggesting that increased intensity of climate forcing reduces the inputs required for food production, due to the fertilisation and enhanced water use efficiency effects of elevated atmospheric CO 2 concentrations, but requiring substantial shifts in the global and local patterns of production. The results suggest that adaptation in the global agriculture and food system has substantial capacity to diminish the negative impacts and gain greater benefits from positive outcomes of climate change. Consequently, agricultural expansion and intensification may be lower than found in previous studies where spatial details and processes consideration were more constrained. © 2018 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.
2014-01-01
Background Congenital heart disease (CHD) is the most common type of major birth defects in Sichuan, the most populous province in China. The detailed etiology of CHD is unknown but some environmental factors are suspected as the cause of this disease. However, the geographical variations in CHD prevalence would be highly valuable in providing a clue on the role of the environment in CHD etiology. Here, we investigate the spatial patterns and geographic differences in CHD prevalence among 0- to 14-year-old children, discuss the possible environmental risk factors that might be associated with CHD prevalence in Sichuan Basin from 2004 to 2009. Methods The hierarchical Bayesian model was used to estimate CHD prevalence at the township level. Spatial autocorrelation statistics were performed, and a hot-spot analysis with different distance thresholds was used to identify the spatial pattern of CHD prevalence. Distribution and clustering maps were drawn using geographic information system tools. Results CHD prevalence was significantly clustered in Sichuan Basin in different spatial scale. Typical hot/cold clusters were identified, and possible CHD causes were discussed. The association between selected hypothetical environmental factors of maternal exposure and CHD prevalence was evaluated. Conclusions The largest hot-spot clustering phenomena and the CHD prevalence clustering trend among 0- to 14-year-old children in the study area showed a plausibly close similarity with those observed in the Tuojiang River Basin. The high ecological risk of heavy metal(Cd, As, and Pb)sediments in the middle and lower streams of the Tuojiang River watershed and ammonia–nitrogen pollution may have contribution to the high prevalence of CHD in this area. PMID:24924350
NASA Astrophysics Data System (ADS)
Zieschang, H. E.; Sievers, A.
1994-08-01
With the mathematical basis for the precise analysis of developmental processes in plants, the patterns of growth in phototropic and gravitropic responses have become better understood. A detailed temporal and spatial quantification of a growth process is an important tool for evaluating hypotheses about the underlying physiological mechanisms. Studies of growth rates and curvature show that the original Cholodny-Went hypothesis cannot explain the complex growth patterns during tropic responses of shoots and roots. In addition, regulating factors other than the lateral redistribution of hormones must be taken into account. Electrophysiological studies on roots led to a modification of the Cholodny-Went hypothesis in that redistributions of bioelectrical activities are observed.
Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains.
Onken, Arno; Liu, Jian K; Karunasekara, P P Chamanthi R; Delis, Ioannis; Gollisch, Tim; Panzeri, Stefano
2016-11-01
Advances in neuronal recording techniques are leading to ever larger numbers of simultaneously monitored neurons. This poses the important analytical challenge of how to capture compactly all sensory information that neural population codes carry in their spatial dimension (differences in stimulus tuning across neurons at different locations), in their temporal dimension (temporal neural response variations), or in their combination (temporally coordinated neural population firing). Here we investigate the utility of tensor factorizations of population spike trains along space and time. These factorizations decompose a dataset of single-trial population spike trains into spatial firing patterns (combinations of neurons firing together), temporal firing patterns (temporal activation of these groups of neurons) and trial-dependent activation coefficients (strength of recruitment of such neural patterns on each trial). We validated various factorization methods on simulated data and on populations of ganglion cells simultaneously recorded in the salamander retina. We found that single-trial tensor space-by-time decompositions provided low-dimensional data-robust representations of spike trains that capture efficiently both their spatial and temporal information about sensory stimuli. Tensor decompositions with orthogonality constraints were the most efficient in extracting sensory information, whereas non-negative tensor decompositions worked well even on non-independent and overlapping spike patterns, and retrieved informative firing patterns expressed by the same population in response to novel stimuli. Our method showed that populations of retinal ganglion cells carried information in their spike timing on the ten-milliseconds-scale about spatial details of natural images. This information could not be recovered from the spike counts of these cells. First-spike latencies carried the majority of information provided by the whole spike train about fine-scale image features, and supplied almost as much information about coarse natural image features as firing rates. Together, these results highlight the importance of spike timing, and particularly of first-spike latencies, in retinal coding.
Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains
Onken, Arno; Liu, Jian K.; Karunasekara, P. P. Chamanthi R.; Delis, Ioannis; Gollisch, Tim; Panzeri, Stefano
2016-01-01
Advances in neuronal recording techniques are leading to ever larger numbers of simultaneously monitored neurons. This poses the important analytical challenge of how to capture compactly all sensory information that neural population codes carry in their spatial dimension (differences in stimulus tuning across neurons at different locations), in their temporal dimension (temporal neural response variations), or in their combination (temporally coordinated neural population firing). Here we investigate the utility of tensor factorizations of population spike trains along space and time. These factorizations decompose a dataset of single-trial population spike trains into spatial firing patterns (combinations of neurons firing together), temporal firing patterns (temporal activation of these groups of neurons) and trial-dependent activation coefficients (strength of recruitment of such neural patterns on each trial). We validated various factorization methods on simulated data and on populations of ganglion cells simultaneously recorded in the salamander retina. We found that single-trial tensor space-by-time decompositions provided low-dimensional data-robust representations of spike trains that capture efficiently both their spatial and temporal information about sensory stimuli. Tensor decompositions with orthogonality constraints were the most efficient in extracting sensory information, whereas non-negative tensor decompositions worked well even on non-independent and overlapping spike patterns, and retrieved informative firing patterns expressed by the same population in response to novel stimuli. Our method showed that populations of retinal ganglion cells carried information in their spike timing on the ten-milliseconds-scale about spatial details of natural images. This information could not be recovered from the spike counts of these cells. First-spike latencies carried the majority of information provided by the whole spike train about fine-scale image features, and supplied almost as much information about coarse natural image features as firing rates. Together, these results highlight the importance of spike timing, and particularly of first-spike latencies, in retinal coding. PMID:27814363
The spatial configuration of ordered polynucleotide chains. II. The poly(rA) helix.
Olson, W K
1975-01-01
Approximate details of the spatial configuration of the ordered single-stranded poly(rA) molecule in dilute solution have been obtained in a combined theoretical analysis of base stacking and chain flexibility. Only those regularly repeating structures which fulfill the criterion of conformational flexibility (based upon all available experimental and theoretical evidence of preferred bond rotations) and which also exhibit the right-handed base stacking pattern observed in nmr investigations of poly(rA) are deemed suitable single-stranded helices. In addition, the helical geometry of the stacked structures is required to be consistent with the experimentally observed dimensions of both completely ordered and partially ordered poly(rA) chains. Only a single category of poly(rA) helices (very similar in all conformational details to the individual chains of the poly(rA) double-stranded X-ray structure) is thus obtained. Other conformationally feasible polynucleotide helices characterized simply by a parallel and overlapping base stacking arrangement are also discussed. PMID:1052529
NASA Astrophysics Data System (ADS)
Lin, Hai; Shuai, J. W.
2010-04-01
A stochastic spatial model based on the Monte Carlo approach is developed to study the dynamics of human immunodeficiency virus (HIV) infection. We aim to propose a more detailed and realistic simulation frame by incorporating many important features of HIV dynamics, which include infections, replications and mutations of viruses, antigen recognitions, activations and proliferations of lymphocytes, and diffusions, encounters and interactions of virions and lymphocytes. Our model successfully reproduces the three-phase pattern observed in HIV infection, and the simulation results for the time distribution from infection to AIDS onset are also in good agreement with the clinical data. The interactions of viruses and the immune system in all the three phases are investigated. We assess the relative importance of various immune system components in the acute phase. The dynamics of how the two important factors, namely the viral diversity and the asymmetric battle between HIV and the immune system, result in AIDS are investigated in detail with the model.
Tree-based approach for exploring marine spatial patterns with raster datasets.
Liao, Xiaohan; Xue, Cunjin; Su, Fenzhen
2017-01-01
From multiple raster datasets to spatial association patterns, the data-mining technique is divided into three subtasks, i.e., raster dataset pretreatment, mining algorithm design, and spatial pattern exploration from the mining results. Comparison with the former two subtasks reveals that the latter remains unresolved. Confronted with the interrelated marine environmental parameters, we propose a Tree-based Approach for eXploring Marine Spatial Patterns with multiple raster datasets called TAXMarSP, which includes two models. One is the Tree-based Cascading Organization Model (TCOM), and the other is the Spatial Neighborhood-based CAlculation Model (SNCAM). TCOM designs the "Spatial node→Pattern node" from top to bottom layers to store the table-formatted frequent patterns. Together with TCOM, SNCAM considers the spatial neighborhood contributions to calculate the pattern-matching degree between the specified marine parameters and the table-formatted frequent patterns and then explores the marine spatial patterns. Using the prevalent quantification Apriori algorithm and a real remote sensing dataset from January 1998 to December 2014, a successful application of TAXMarSP to marine spatial patterns in the Pacific Ocean is described, and the obtained marine spatial patterns present not only the well-known but also new patterns to Earth scientists.
NASA Astrophysics Data System (ADS)
Dąbski, Maciej; Zmarz, Anna; Pabjanek, Piotr; Korczak-Abshire, Małgorzata; Karsznia, Izabela; Chwedorzewska, Katarzyna J.
2017-08-01
High-resolution aerial images allow detailed analyses of periglacial landforms, which is of particular importance in light of climate change and resulting changes in active layer thickness. The aim of this study is to show possibilities of using UAV-based photography to perform spatial analysis of periglacial landforms on the Demay Point peninsula, King George Island, and hence to supplement previous geomorphological studies of the South Shetland Islands. Photogrammetric flights were performed using a PW-ZOOM fixed-winged unmanned aircraft vehicle. Digital elevation models (DEM) and maps of slope and contour lines were prepared in ESRI ArcGIS 10.3 with the Spatial Analyst extension, and three-dimensional visualizations in ESRI ArcScene 10.3 software. Careful interpretation of orthophoto and DEM, allowed us to vectorize polygons of landforms, such as (i) solifluction landforms (solifluction sheets, tongues, and lobes); (ii) scarps, taluses, and a protalus rampart; (iii) patterned ground (hummocks, sorted circles, stripes, nets and labyrinths, and nonsorted nets and stripes); (iv) coastal landforms (cliffs and beaches); (v) landslides and mud flows; and (vi) stone fields and bedrock outcrops. We conclude that geomorphological studies based on commonly accessible aerial and satellite images can underestimate the spatial extent of periglacial landforms and result in incomplete inventories. The PW-ZOOM UAV is well suited to gather detailed geomorphological data and can be used in spatial analysis of periglacial landforms in the Western Antarctic Peninsula region.
Long-term Spatial Distribution Patterns of Protozoa in Connected Microhabitats
NASA Astrophysics Data System (ADS)
Taghon, G. L.; Tuorto, S. J.
2016-02-01
Studies of microbial ecosystems usually assume habitat homogeneity. Recent research, however, indicates that habitat structure varies at millimeter scales and that this patchiness affects abundance and behavior of microbes. In this study, two species of ciliated protozoa were maintained, together, for multiple generations in microfluidic devices consisting of arrays of interconnected microhabitats with differing resource availability. The species differed in their population dynamics and tendency to disperse among microhabitats. Both species coexisted for over 45 days, and their coexistence likely resulted from habitat selection at millimeter scales. We demonstrate that it is not only possible, but imperative, that detailed ecological phenomena of microbial systems be studied at the relevant spatial and temporal scales.
NASA Astrophysics Data System (ADS)
Rice, Joshua S.; Emanuel, Ryan E.; Vose, James M.; Nelson, Stacy A. C.
2015-08-01
Changes in streamflow are an important area of ongoing research in the hydrologic sciences. To better understand spatial patterns in past changes in streamflow, we examined relationships between watershed-scale spatial characteristics and trends in streamflow. Trends in streamflow were identified by analyzing mean daily flow observations between 1940 and 2009 from 967 U.S. Geological Survey stream gages. Results indicated that streamflow across the continental U.S., as a whole, increased while becoming less extreme between 1940 and 2009. However, substantial departures from the continental U.S. (CONUS) scale pattern occurred at the regional scale, including increased annual maxima, decreased annual minima, overall drying trends, and changes in streamflow variability. A subset of watersheds belonging to a reference data set exhibited significantly smaller trend magnitudes than those observed in nonreference watersheds. Boosted regression tree models were applied to examine the influence of watershed characteristics on streamflow trend magnitudes at both the CONUS and regional scale. Geographic location was found to be of particular importance at the CONUS scale while local variability in hydroclimate and topography tended to have a strong influence on regional-scale patterns in streamflow trends. This methodology facilitates detailed, data-driven analyses of how the characteristics of individual watersheds interact with large-scale hydroclimate forces to influence how changes in streamflow manifest.
Snowpack spatial and temporal variability assessment using SMP high-resolution penetrometer
NASA Astrophysics Data System (ADS)
Komarov, Anton; Seliverstov, Yuriy; Sokratov, Sergey; Grebennikov, Pavel
2017-04-01
This research is focused on study of spatial and temporal variability of structure and characteristics of snowpack, quick identification of layers based on hardness and dispersion values received from snow micro penetrometer (SMP). We also discuss the detection of weak layers and definition of their parameters in non-alpine terrain. As long as it is the first SMP tool available in Russia, our intent is to test it in different climate and weather conditions. During two separate snowpack studies in plain and mountain landscapes, we derived density and grain size profiles by comparing snow density and grain size from snowpits and SMP measurements. The first case study was MSU meteorological observatory test site in Moscow. SMP data was obtained by 6 consecutive measurements along 10 m transects with a horizontal resolution of approximately 50 cm. The detailed description of snowpack structure, density, grain size, air and snow temperature was also performed. By comparing this information, the detailed scheme of snowpack evolution was created. The second case study was in Khibiny mountains. One 10-meter-long transect was made. SMP, density, grain size and snow temperature data was obtained with horizontal resolution of approximately 50 cm. The high-definition profile of snowpack density variation was acquired using received data. The analysis of data reveals high spatial and temporal variability in snow density and layer structure in both horizontal and vertical dimensions. It indicates that the spatial variability is exhibiting similar spatial patterns as surface topology. This suggests a strong influence from such factors as wind and liquid water pressure on the temporal and spatial evolution of snow structure. It was also defined, that spatial variation of snowpack characteristics is substantial even within homogeneous plain landscape, while in high-latitude mountain regions it grows significantly.
NASA Astrophysics Data System (ADS)
Dubovyk, Olena; Landmann, Tobias; Erasmus, Barend F. N.; Tewes, Andreas; Schellberg, Jürgen
2015-06-01
Currently there is a lack of knowledge on spatio-temporal patterns of land surface dynamics at medium spatial scale in southern Africa, even though this information is essential for better understanding of ecosystem response to climatic variability and human-induced land transformations. In this study, we analysed vegetation dynamics across a large area in southern Africa using the 14-years (2000-2013) of medium spatial resolution (250 m) MODIS-EVI time-series data. Specifically, we investigated temporal changes in the time series of key phenometrics including overall greenness, peak and timing of annual greenness over the monitoring period and study region. In order to specifically capture spatial and per pixel vegetation changes over time, we calculated trends in these phenometrics using a robust trend analysis method. The results showed that interannual vegetation dynamics followed precipitation patterns with clearly differentiated seasonality. The earliest peak greenness during 2000-2013 occurred at the end of January in the year 2000 and the latest peak greenness was observed at the mid of March in 2012. Specifically spatial patterns of long-term vegetation trends allowed mapping areas of (i) decrease or increase in overall greenness, (ii) decrease or increase of peak greenness, and (iii) shifts in timing of occurrence of peak greenness over the 14-year monitoring period. The observed vegetation decline in the study area was mainly attributed to human-induced factors. The obtained information is useful to guide selection of field sites for detailed vegetation studies and land rehabilitation interventions and serve as an input for a range of land surface models.
Can we infer plant facilitation from remote sensing? A test across global drylands
Xu, Chi; Holmgren, Milena; Van Nes, Egbert H.; Maestre, Fernando T.; Soliveres, Santiago; Berdugo, Miguel; Kéfi, Sonia; Marquet, Pablo A.; Abades, Sebastian; Scheffer, Marten
2016-01-01
Facilitation is a major force shaping the structure and diversity of plant communities in terrestrial ecosystems. Detecting positive plant-plant interactions relies on the combination of field experimentation and the demonstration of spatial association between neighboring plants. This has often restricted the study of facilitation to particular sites, limiting the development of systematic assessments of facilitation over regional and global scales. Here we explore whether the frequency of plant spatial associations detected from high-resolution remotely-sensed images can be used to infer plant facilitation at the community level in drylands around the globe. We correlated the information from remotely-sensed images freely available through Google Earth™ with detailed field assessments, and used a simple individual-based model to generate patch-size distributions using different assumptions about the type and strength of plant-plant interactions. Most of the patterns found from the remotely-sensed images were more right-skewed than the patterns from the null model simulating a random distribution. This suggests that the plants in the studied drylands show stronger spatial clustering than expected by chance. We found that positive plant co-occurrence, as measured in the field, was significantly related to the skewness of vegetation patch-size distribution measured using Google Earth™ images. Our findings suggest that the relative frequency of facilitation may be inferred from spatial pattern signals measured from remotely-sensed images, since facilitation often determines positive co-occurrence among neighboring plants. They pave the road for a systematic global assessment of the role of facilitation in terrestrial ecosystems. PMID:26552256
Moving GIS Research Indoors: Spatiotemporal Analysis of Agricultural Animals
Daigle, Courtney L.; Banerjee, Debasmit; Montgomery, Robert A.; Biswas, Subir; Siegford, Janice M.
2014-01-01
A proof of concept applying wildlife ecology techniques to animal welfare science in intensive agricultural environments was conducted using non-cage laying hens. Studies of wildlife ecology regularly use Geographic Information Systems (GIS) to assess wild animal movement and behavior within environments with relatively unlimited space and finite resources. However, rather than depicting landscapes, a GIS could be developed in animal production environments to provide insight into animal behavior as an indicator of animal welfare. We developed a GIS-based approach for studying agricultural animal behavior in an environment with finite space and unlimited resources. Concurrent data from wireless body-worn location tracking sensor and video-recording systems, which depicted spatially-explicit behavior of hens (135 hens/room) in two identical indoor enclosures, were collected. The spatial configuration of specific hen behaviors, variation in home range patterns, and variation in home range overlap show that individual hens respond to the same environment differently. Such information could catalyze management practice adjustments (e.g., modifying feeder design and/or location). Genetically-similar hens exhibited diverse behavioral and spatial patterns via a proof of concept approach enabling detailed examinations of individual non-cage laying hen behavior and welfare. PMID:25098421
Browne, Mark Anthony; Chapman, M Gee; Thompson, Richard C; Amaral Zettler, Linda A; Jambeck, Jenna; Mallos, Nicholas J
2015-06-16
Floating and stranded marine debris is widespread. Increasing sea levels and altered rainfall, solar radiation, wind speed, waves, and oceanic currents associated with climatic change are likely to transfer more debris from coastal cities into marine and coastal habitats. Marine debris causes economic and ecological impacts, but understanding the scope of these requires quantitative information on spatial patterns and trends in the amounts and types of debris at a global scale. There are very few large-scale programs to measure debris, but many peer-reviewed and published scientific studies of marine debris describe local patterns. Unfortunately, methods of defining debris, sampling, and interpreting patterns in space or time vary considerably among studies, yet if data could be synthesized across studies, a global picture of the problem may be avaliable. We analyzed 104 published scientific papers on marine debris in order to determine how to evaluate this. Although many studies were well designed to answer specific questions, definitions of what constitutes marine debris, the methods used to measure, and the scale of the scope of the studies means that no general picture can emerge from this wealth of data. These problems are detailed to guide future studies and guidelines provided to enable the collection of more comparable data to better manage this growing problem.
Using population genetic analyses to understand seed dispersal patterns
NASA Astrophysics Data System (ADS)
Hamrick, J. L.; Trapnell, Dorset W.
2011-11-01
Neutral genetic markers have been employed in several ways to understand seed dispersal patterns in natural and human modified landscapes. Genetic differentiation among spatially separated populations, using biparentally and maternally inherited genetic markers, allows determination of the relative historical effectiveness of pollen and seed dispersal. Genetic relatedness among individuals, estimated as a function of spatial separation between pairs of individuals, has also been used to indirectly infer seed dispersal distances. Patterns of genetic relatedness among plants in recently colonized populations provide insights into the role of seed dispersal in population colonization and expansion. High genetic relatedness within expanding populations indicates original colonization by a few individuals and population expansion by the recruitment of the original colonists' progeny; low relatedness should occur if population growth results primarily from continuous seed immigration from multiple sources. Parentage analysis procedures can identify maternal parents of dispersed fruits, seeds, or seedlings providing detailed descriptions of contemporary seed dispersal patterns. With standard parent-pair analyses of seeds or seedlings, problems can arise in distinguishing the maternal parent. However, the use of maternal DNA from dispersed fruits or seed coats allows direct identification of maternal individuals and, as a consequence, the distance and patterns of seed dispersal and deposition. Application of combinations of these approaches provides additional insights into the role seed dispersal plays in the genetic connectivity between populations in natural and disturbed landscapes.
NASA Astrophysics Data System (ADS)
Eslami, Parastou; Seo, Jung-Hee; Abd, Thura T.; George, Richard; Lardo, Albert C.; Chen, Marcus Y.; Mittal, Rajat
2015-11-01
Computed tomography angiography (CTA) has emerged as a powerful tool for the assessment of coronary artery disease and other cardiac conditions. Continuous improvements in the spatial and temporal resolution of CT scanners are revealing details regarding the spatially and temporally varying contrast concentration in the vasculature, that were not evident before. These contrast dispersion patterns offer the possibility of extracting useful information about the hemodynamics from the scans. In the current presentation, we will describe experimental studies carried out with CT compatible phantoms of coronary vessels that provide insights into the effect of imaging artifacts on the observed intracoronary contrast gradients. In addition, we will describe a series of computational fluid dynamics studies that explore the dispersion of contrast through the ascending-descending aorta with particular focus on the effect of the aortic curvature on the dispersion patterns. PE is supported by the NIH Graduate Partnership Program. RM and ACL pending patents in CTA based flow diagnostics and have other significant financial interests in these technologies.
Configuration of Pluto's Volatile Ices
NASA Astrophysics Data System (ADS)
Grundy, William M.; Binzel, R. P.; Cook, J. C.; Cruikshank, D. P.; Dalle Ore, C. M.; Earle, A. M.; Ennico, K.; Jennings, D. E.; Howett, C. J. A.; Linscott, I. R.; Lunsford, A. W.; Olkin, C. B.; Parker, A. H.; Parker, J. Wm; Protopapa, S.; Reuter, D. C.; Singer, K. N.; Spencer, J. R.; Stern, S. A.; Tsang, C. C. C.; Verbiscer, A. J.; Weaver, H. A.; Young, L. A.; Berry, K.; Buie, M. W.; Stansberry, J. A.
2015-11-01
We report on near-infrared remote sensing by New Horizons' Ralph instrument (Reuter et al. 2008, Space Sci. Rev. 140, 129-154) of Pluto's N2, CO, and CH4 ices. These especially volatile ices are mobile even at Pluto's cryogenic surface temperatures. Sunlight reflected from these ices becomes imprinted with their characteristic spectral absorption bands. The detailed appearance of these absorption features depends on many aspects of local composition, thermodynamic state, and texture. Multiple-scattering radiative transfer models are used to retrieve quantitative information about these properties and to map how they vary across Pluto's surface. Using parameter maps derived from New Horizons observations, we investigate the striking regional differences in the abundances and scattering properties of Pluto's volatile ices. Comparing these spatial patterns with the underlying geology provides valuable constraints on processes actively modifying the planet's surface, over a variety of spatial scales ranging from global latitudinal patterns to more regional and local processes within and around the feature informally known as Sputnik Planum. This work was supported by the NASA New Horizons Project.
Frequency-domain nonlinear optics in two-dimensionally patterned quasi-phase-matching media.
Phillips, C R; Mayer, B W; Gallmann, L; Keller, U
2016-07-11
Advances in the amplification and manipulation of ultrashort laser pulses have led to revolutions in several areas. Examples include chirped pulse amplification for generating high peak-power lasers, power-scalable amplification techniques, pulse shaping via modulation of spatially-dispersed laser pulses, and efficient frequency-mixing in quasi-phase-matched nonlinear crystals to access new spectral regions. In this work, we introduce and demonstrate a new platform for nonlinear optics which has the potential to combine these separate functionalities (pulse amplification, frequency transfer, and pulse shaping) into a single monolithic device that is bandwidth- and power-scalable. The approach is based on two-dimensional (2D) patterning of quasi-phase-matching (QPM) gratings combined with optical parametric interactions involving spatially dispersed laser pulses. Our proof of principle experiment demonstrates this technique via mid-infrared optical parametric chirped pulse amplification of few-cycle pulses. Additionally, we present a detailed theoretical and numerical analysis of such 2D-QPM devices and how they can be designed.
Status of GeoTASO Trace Gas Data Analysis for the KORUS-AQ Campaign
NASA Astrophysics Data System (ADS)
Janz, S. J.; Nowlan, C. R.; Lamsal, L. N.; Kowalewski, M. G.; Judd, L. M.; Wang, J.
2017-12-01
The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) instrument measures spectrally resolved backscattered solar radiation at high spatial resolution. The instrument completed 30 sorties on board the NASA LaRC UC-12 aircraft during the KORUS-AQ deployment in May-June of 2016. GeoTASO collects spatially resolved spectra with sufficient sensitivity to retrieve column amounts of the trace gas molecules NO2, SO2, H2CO, O3, and C2H2O2 as well as aerosol products. Typical product retrievals are done in 250 m2 bins with multiple overpasses of key ground sites, allowing for detailed spatio-temporal analysis. Flight patterns consisted of both contiguous overlapping grid patterns to simulate satellite observational strategies in support of future geostationary satellite algorithm development, and "race-track" sampling to perform calibration and validation with the in-situ DC-8 platform as well as ground based assets. We will summarize the status of the radiance data set as well as ongoing analysis from our co-Investigators.
Origins and early development of human body knowledge.
Slaughter, Virginia; Heron, Michelle
2004-01-01
As a knowable object, the human body is highly complex. Evidence from several converging lines of research, including psychological studies, neuroimaging and clinical neuropsychology, indicates that human body knowledge is widely distributed in the adult brain, and is instantiated in at least three partially independent levels of representation. Sensorimotor body knowledge is responsible for on-line control and movement of one's own body and may also contribute to the perception of others' moving bodies; visuo-spatial body knowledge specifies detailed structural descriptions of the spatial attributes of the human body; and lexical-semantic body knowledge contains language-based knowledge about the human body. In the first chapter of this Monograph, we outline the evidence for these three hypothesized levels of human body knowledge, then review relevant literature on infants' and young children's human body knowledge in terms of the three-level framework. In Chapters II and III, we report two complimentary series of studies that specifically investigate the emergence of visuo-spatial body knowledge in infancy. Our technique is to compare infants'responses to typical and scrambled human bodies, in order to evaluate when and how infants acquire knowledge about the canonical spatial layout of the human body. Data from a series of visual habituation studies indicate that infants first discriminate scrambled from typical human body picture sat 15 to 18 months of age. Data from object examination studies similarly indicate that infants are sensitive to violations of three-dimensional human body stimuli starting at 15-18 months of age. The overall pattern of data supports several conclusions about the early development of human body knowledge: (a) detailed visuo-spatial knowledge about the human body is first evident in the second year of life, (b) visuo-spatial knowledge of human faces and human bodies are at least partially independent in infancy and (c) infants' initial visuo-spatial human body representations appear to be highly schematic, becoming more detailed and specific with development. In the final chapter, we explore these conclusions and discuss how levels of body knowledge may interact in early development.
NASA Astrophysics Data System (ADS)
Schneider, C.; Buttstädt, M.; Merbitz, H.; Sachsen, T.; Ketzler, G.; Michael, S.; Klemme, M.; Dott, W.; Selle, K.; Hofmeister, H.
2010-09-01
This research initiative CITY 2020+ assesses the risks and opportunities for residents in urban built environments under projected demographic and climate change for the year 2020 and beyond, using the City of Aachen as a case study. CITY 2020+ develops scenarios, options and tools for planning and developing sustainable future city structures. We investigate how urban environment, political structure and residential behavior can best be adapted, with attention to the interactions among structural, political, and sociological configurations and with their consequences on human health. Demographers project that in the EU-25-States by 2050, approximately 30% of the population will be over age 65. Also by 2050, average tem¬peratures are projected to rise by 1 to 2 K. Combined, Europe can expect enhanced thermal stress and higher levels of particulate matter. CITY 2020+ amongst other sub-projects includes research project dealing with (1) a micro-scale assessment of blockages to low-level cold-air drainage flow into the city centre by vegetation and building structures, (2) a detailed analysis of the change of probability density functions related to the occurrence of heat waves during summer and the spatial and temporal structure of the urban heat island (UHI) (3) a meso-scale analysis of particulate matter (PM) concentrations depending on topography, local meteorological conditions and synoptic-scale weather patterns. First results will be presented specifically from sub-projects related to vegetation barriers within cold air drainage, the assessment of the UHI and the temporal and spatial pattern of PM loadings in the city centre. The analysis of the cold air drainage flow is investigated in two consecutive years with a clearing of vegetation stands in the beginning of the second year early in 2010. The spatial pattern of the UHI and its possible enhancement by climate change is addressed employing a unique setup using GPS devices and temperature probes fixed to several public transport units running all across the city. This is accompanied by an analysis of probability density functions (PDF) for heat waves based on recent climate data and climate projections. A dense net of 40 PM measurement sites is operated in order to obtain the spatial pattern of PM concentration as depending on meteorological condition and location. It is lined out how this climate related sub-projects interact with investigations on social networks, governance issues, buildings structure development and health outcome. Related to the later the chemical composition of PM is analyzed in more detail and related to the spatial patterns of health deficiencies. At a later stage City2020+ will propose new strategies based on cooperation from the fields of medicine, geography, sociology, history, civil engineering, and architecture for adapting the city for future needs. The Project CITY 2020+ is part of the interdisciplinary Project House HumTec (Human Sciences and Technology) at RWTH Aachen University funded by the Excellence Initiative of the German federal and state governments through the Deutsche Forschungsgemeinschaft (German Research Foundation, DFG).
Wang, Jiaojiao; Cao, Zhidong; Zeng, Daniel Dajun; Wang, Quanyi; Wang, Xiaoli; Qian, Haikun
2014-01-01
Hand, foot, and mouth disease (HFMD) mostly affects the health of infants and preschool children. Many studies of HFMD in different regions have been published. However, the epidemiological characteristics and space-time patterns of individual-level HFMD cases in a major city such as Beijing are unknown. The objective of this study was to investigate epidemiological features and identify high relative risk space-time HFMD clusters at a fine spatial scale. Detailed information on age, occupation, pathogen and gender was used to analyze the epidemiological features of HFMD epidemics. Data on individual-level HFMD cases were examined using Local Indicators of Spatial Association (LISA) analysis to identify the spatial autocorrelation of HFMD incidence. Spatial filtering combined with scan statistics methods were used to detect HFMD clusters. A total of 157,707 HFMD cases (60.25% were male, 39.75% were female) reported in Beijing from 2008 to 2012 included 1465 severe cases and 33 fatal cases. The annual average incidence rate was 164.3 per 100,000 (ranged from 104.2 in 2008 to 231.5 in 2010). Male incidence was higher than female incidence for the 0 to 14-year age group, and 93.88% were nursery children or lived at home. Areas at a higher relative risk were mainly located in the urban-rural transition zones (the percentage of the population at risk ranged from 33.89% in 2011 to 39.58% in 2012) showing High-High positive spatial association for HFMD incidence. The most likely space-time cluster was located in the mid-east part of the Fangshan district, southwest of Beijing. The spatial-time patterns of Beijing HFMD (2008-2012) showed relatively steady. The population at risk were mainly distributed in the urban-rural transition zones. Epidemiological features of Beijing HFMD were generally consistent with the previous research. The findings generated computational insights useful for disease surveillance, risk assessment and early warning.
FracPaQ: a MATLAB™ Toolbox for the Quantification of Fracture Patterns
NASA Astrophysics Data System (ADS)
Healy, D.; Rizzo, R. E.; Cornwell, D. G.; Timms, N.; Farrell, N. J.; Watkins, H.; Gomez-Rivas, E.; Smith, M.
2016-12-01
The patterns of fractures in deformed rocks are rarely uniform or random. Fracture orientations, sizes, shapes and spatial distributions often exhibit some kind of order. In detail, there may be relationships among the different fracture attributes e.g. small fractures dominated by one orientation, larger fractures by another. These relationships are important because the mechanical (e.g. strength, anisotropy) and transport (e.g. fluids, heat) properties of rock depend on these fracture patterns and fracture attributes. This presentation describes an open source toolbox to quantify fracture patterns, including distributions in fracture attributes and their spatial variation. Software has been developed to quantify fracture patterns from 2-D digital images, such as thin section micrographs, geological maps, outcrop or aerial photographs or satellite images. The toolbox comprises a suite of MATLAB™ scripts based on published quantitative methods for the analysis of fracture attributes: orientations, lengths, intensity, density and connectivity. An estimate of permeability in 2-D is made using a parallel plate model. The software provides an objective and consistent methodology for quantifying fracture patterns and their variations in 2-D across a wide range of length scales. Our current focus for the application of the software is on quantifying the fracture patterns in and around fault zones. There is a large body of published work on the quantification of relatively simple joint patterns, but fault zones present a bigger, and arguably more important, challenge. The method presented is inherently scale independent, and a key task will be to analyse and integrate quantitative fracture pattern data from micro- to macro-scales. Planned future releases will incorporate multi-scale analyses based on a wavelet method to look for scale transitions, and combining fracture traces from multiple 2-D images to derive the statistically equivalent 3-D fracture pattern.
NASA Astrophysics Data System (ADS)
Selvakumar, R.; Ramasamy, SM.
2014-12-01
Flooding is a naturally recurrent phenomenon that causes severe damage to lives and property. Predictions on flood-prone zones are made based on intensity-duration of rainfall, carrying capacity of drainage, and natural or man-made obstructions. Particularly, the lower part of the drainage system and its adjacent geomorphic landforms like floodplains and deltaic plains are considered for analysis, but stagnation in parts of basins that are far away from major riverine systems is less unveiled. Similarly, uncharacteristic flooding in the upper and middle parts of drainage, especially in zones of an anomalous drainage pattern, is also least understood. Even though topographic differences are attributed for such anomalous spatial occurrence of floods, its genetic cause has to be identified for effective management practice. Added to structural and lithological variations, tectonic movements too impart micro-scale terrain undulations. Because active tectonic movements are slow-occurring, long-term geological processes, its resultant topographical variations and drainage anomalies are least correlated with floods. The recent floods of Tamil Nadu also exhibit a unique distribution pattern emphasizing the role of tectonics over it. Hence a detailed geoinformatics-based analysis was carried out to envisage the relationship between spatial distribution of flood and active tectonic elements such as regional arches and deeps, block faults, and graben and drainage anomalies such as deflected drainage, compressed meander, and eyed drainages. The analysis reveals that micro-scale topographic highs and lows imparted by active tectonic movements and its further induced drainage anomalies have substantially controlled the distribution pattern of flood.
Movement patterns of silvertip sharks ( Carcharhinus albimarginatus) on coral reefs
NASA Astrophysics Data System (ADS)
Espinoza, Mario; Heupel, Michelle. R.; Tobin, Andrew J.; Simpfendorfer, Colin A.
2015-09-01
Understanding how sharks use coral reefs is essential for assessing risk of exposure to fisheries, habitat loss, and climate change. Despite a wide Indo-Pacific distribution, little is known about the spatial ecology of silvertip sharks ( Carcharhinus albimarginatus), compromising the ability to effectively manage their populations. We examined the residency and movements of silvertip sharks in the central Great Barrier Reef (GBR). An array of 56 VR2W acoustic receivers was used to monitor shark movements on 17 semi-isolated reefs. Twenty-seven individuals tagged with acoustic transmitters were monitored from 70 to 731 d. Residency index to the study site ranged from 0.05 to 0.97, with a mean residency (±SD) of 0.57 ± 0.26, but most individuals were detected at or near their tagging reef. Clear seasonal patterns were apparent, with fewer individuals detected between September and February. A large proportion of the tagged population (>71 %) moved regularly between reefs. Silvertip sharks were detected less during daytime and exhibited a strong diel pattern in depth use, which may be a strategy for optimizing energetic budgets and foraging opportunities. This study provides the first detailed examination of the spatial ecology and behavior of silvertip sharks on coral reefs. Silvertip sharks remained resident at coral reef habitats over long periods, but our results also suggest this species may have more complex movement patterns and use larger areas of the GBR than common reef shark species. Our findings highlight the need to further understand the movement ecology of silvertip sharks at different spatial and temporal scales, which is critical for developing effective management approaches.
Peixoto, Roberta B.; Machado-Silva, Fausto; Marotta, Humberto; Enrich-Prast, Alex; Bastviken, David
2015-01-01
Inland waters (lakes, rivers and reservoirs) are now understood to contribute large amounts of methane (CH4) to the atmosphere. However, fluxes are poorly constrained and there is a need for improved knowledge on spatiotemporal variability and on ways of optimizing sampling efforts to yield representative emission estimates for different types of aquatic ecosystems. Low-latitude floodplain lakes and wetlands are among the most high-emitting environments, and here we provide a detailed investigation of spatial and day-to-day variability in a shallow floodplain lake in the Pantanal in Brazil over a five-day period. CH4 flux was dominated by frequent and ubiquitous ebullition. A strong but predictable spatial variability (decreasing flux with increasing distance to the shore or to littoral vegetation) was found, and this pattern can be addressed by sampling along transects from the shore to the center. Although no distinct day-to-day variability were found, a significant increase in flux was identified from measurement day 1 to measurement day 5, which was likely attributable to a simultaneous increase in temperature. Our study demonstrates that representative emission assessments requires consideration of spatial variability, but also that spatial variability patterns are predictable for lakes of this type and may therefore be addressed through limited sampling efforts if designed properly (e.g., fewer chambers may be used if organized along transects). Such optimized assessments of spatial variability are beneficial by allowing more of the available sampling resources to focus on assessing temporal variability, thereby improving overall flux assessments. PMID:25860229
Gu, Yingxin; Wylie, Bruce K.
2015-01-01
Accurately estimating aboveground vegetation biomass productivity is essential for local ecosystem assessment and best land management practice. Satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. A 250-m grassland biomass productivity map for the Greater Platte River Basin had been developed based on the relationship between Moderate Resolution Imaging Spectroradiometer (MODIS) GSN and Soil Survey Geographic (SSURGO) annual grassland productivity. However, the 250-m MODIS grassland biomass productivity map does not capture detailed ecological features (or patterns) and may result in only generalized estimation of the regional total productivity. Developing a high or moderate spatial resolution (e.g., 30-m) productivity map to better understand the regional detailed vegetation condition and ecosystem services is preferred. The 30-m Landsat data provide spatial detail for characterizing human-scale processes and have been successfully used for land cover and land change studies. The main goal of this study is to develop a 30-m grassland biomass productivity estimation map for central Nebraska, leveraging 250-m MODIS GSN and 30-m Landsat data. A rule-based piecewise regression GSN model based on MODIS and Landsat (r = 0.91) was developed, and a 30-m MODIS equivalent GSN map was generated. Finally, a 30-m grassland biomass productivity estimation map, which provides spatially detailed ecological features and conditions for central Nebraska, was produced. The resulting 30-m grassland productivity map was generally supported by the SSURGO biomass production map and will be useful for regional ecosystem study and local land management practices.
NASA Astrophysics Data System (ADS)
Martini, Edoardo; Wollschläger, Ute; Kögler, Simon; Behrens, Thorsten; Dietrich, Peter; Reinstorf, Frido; Schmidt, Karsten; Weiler, Markus; Werban, Ulrike; Zacharias, Steffen
2016-04-01
Characterizing the spatial patterns of soil moisture is critical for hydrological and meteorological models, as soil moisture is a key variable that controls matter and energy fluxes and soil-vegetation-atmosphere exchange processes. Deriving detailed process understanding at the hillslope scale is not trivial, because of the temporal variability of local soil moisture dynamics. Nevertheless, it remains a challenge to provide adequate information on the temporal variability of soil moisture and its controlling factors. Recent advances in wireless sensor technology allow monitoring of soil moisture dynamics with high temporal resolution at varying scales. In addition, mobile geophysical methods such as electromagnetic induction (EMI) have been widely used for mapping soil water content at the field scale with high spatial resolution, as being related to soil apparent electrical conductivity (ECa). The objective of this study was to characterize the spatial and temporal pattern of soil moisture at the hillslope scale and to infer the controlling hydrological processes, integrating well established and innovative sensing techniques, as well as new statistical methods. We combined soil hydrological and pedological expertise with geophysical measurements and methods from digital soil mapping for designing a wireless soil moisture monitoring network. For a hillslope site within the Schäfertal catchment (Central Germany), soil water dynamics were observed during 14 months, and soil ECa was mapped on seven occasions whithin this period of time using an EM38-DD device. Using the Spearman rank correlation coefficient, we described the temporal persistence of a dry and a wet characteristic state of soil moisture as well as the switching mechanisms, inferring the local properties that control the observed spatial patterns and the hydrological processes driving the transitions. Based on this, we evaluated the use of EMI for mapping the spatial pattern of soil moisture under different hydrologic conditions and the factors controlling the temporal variability of the ECa-soil moisture relationship. The approach provided valuable insight into the time-varying contribution of local and nonlocal factors to the characteristic spatial patterns of soil moisture and the transition mechanisms. The spatial organization of soil moisture was controlled by different processes in different soil horizons, and the topsoil's moisture did not mirror processes that take place within the soil profile. Results show that, for the Schäfertal hillslope site which is presumed to be representative for non-intensively managed soils with moderate clay content, local soil properties (e.g., soil texture and porosity) are the major control on the spatial pattern of ECa. In contrast, the ECa-soil moisture relationship is small and varies over time indicating that ECa is not a good proxy for soil moisture estimation at the investigated site.Occasionally observed stronger correlations between ECa and soil moisture may be explained by background dependencies of ECa to other state variables such as pore water electrical conductivity. The results will help to improve conceptual understanding for hydrological model studies at similar or smaller scales, and to transfer observation concepts and process understanding to larger or less instrumented sites, as well as to constrain the use of EMI-based ECa data for hydrological applications.
Krüger, Julia; Bohrmann, Johannes
2015-01-16
Bioelectric phenomena have been found to exert influence on various developmental and regenerative processes. Little is known about their possible functions and the cellular mechanisms by which they might act during Drosophila oogenesis. In developing follicles, characteristic extracellular current patterns and membrane-potential changes in oocyte and nurse cells have been observed that partly depend on the exchange of protons, potassium ions and sodium ions. These bioelectric properties have been supposed to be related to various processes during oogenesis, e. g. pH-regulation, osmoregulation, cell communication, cell migration, cell proliferation, cell death, vitellogenesis and follicle growth. Analysing in detail the spatial distribution and activity of the relevant ion-transport mechanisms is expected to elucidate the roles that bioelectric phenomena play during oogenesis. To obtain an overview of bioelectric patterning along the longitudinal and transversal axes of the developing follicle, the spatial distributions of membrane potentials (Vmem), intracellular pH (pHi) and various membrane-channel proteins were studied systematically using fluorescent indicators, fluorescent inhibitors and antisera. During mid-vitellogenic stages 9 to 10B, characteristic, stage-specific Vmem-patterns in the follicle-cell epithelium as well as anteroposterior pHi-gradients in follicle cells and nurse cells were observed. Corresponding distribution patterns of proton pumps (V-ATPases), voltage-dependent L-type Ca(2+)-channels, amiloride-sensitive Na(+)-channels and Na(+),H(+)-exchangers (NHE) and gap-junction proteins (innexin 3) were detected. In particular, six morphologically distinguishable follicle-cell types are characterized on the bioelectric level by differences concerning Vmem and pHi as well as specific compositions of ion channels and carriers. Striking similarities between Vmem-patterns and activity patterns of voltage-dependent Ca(2+)-channels were found, suggesting a mechanism for transducing bioelectric signals into cellular responses. Moreover, gradients of electrical potential and pH were observed within single cells. Our data suggest that spatial patterning of Vmem, pHi and specific membrane-channel proteins results in bioelectric signals that are supposed to play important roles during oogenesis, e. g. by influencing spatial coordinates, regulating migration processes or modifying the cytoskeletal organization. Characteristic stage-specific changes of bioelectric activity in specialized cell types are correlated with various developmental processes.
Land cover mapping at sub-pixel scales
NASA Astrophysics Data System (ADS)
Makido, Yasuyo Kato
One of the biggest drawbacks of land cover mapping from remotely sensed images relates to spatial resolution, which determines the level of spatial details depicted in an image. Fine spatial resolution images from satellite sensors such as IKONOS and QuickBird are now available. However, these images are not suitable for large-area studies, since a single image is very small and therefore it is costly for large area studies. Much research has focused on attempting to extract land cover types at sub-pixel scale, and little research has been conducted concerning the spatial allocation of land cover types within a pixel. This study is devoted to the development of new algorithms for predicting land cover distribution using remote sensory imagery at sub-pixel level. The "pixel-swapping" optimization algorithm, which was proposed by Atkinson for predicting sub-pixel land cover distribution, is investigated in this study. Two limitations of this method, the arbitrary spatial range value and the arbitrary exponential model of spatial autocorrelation, are assessed. Various weighting functions, as alternatives to the exponential model, are evaluated in order to derive the optimum weighting function. Two different simulation models were employed to develop spatially autocorrelated binary class maps. In all tested models, Gaussian, Exponential, and IDW, the pixel swapping method improved classification accuracy compared with the initial random allocation of sub-pixels. However the results suggested that equal weight could be used to increase accuracy and sub-pixel spatial autocorrelation instead of using these more complex models of spatial structure. New algorithms for modeling the spatial distribution of multiple land cover classes at sub-pixel scales are developed and evaluated. Three methods are examined: sequential categorical swapping, simultaneous categorical swapping, and simulated annealing. These three methods are applied to classified Landsat ETM+ data that has been resampled to 210 meters. The result suggested that the simultaneous method can be considered as the optimum method in terms of accuracy performance and computation time. The case study employs remote sensing imagery at the following sites: tropical forests in Brazil and temperate multiple land mosaic in East China. Sub-areas for both sites are used to examine how the characteristics of the landscape affect the ability of the optimum technique. Three types of measurement: Moran's I, mean patch size (MPS), and patch size standard deviation (STDEV), are used to characterize the landscape. All results suggested that this technique could increase the classification accuracy more than traditional hard classification. The methods developed in this study can benefit researchers who employ coarse remote sensing imagery but are interested in detailed landscape information. In many cases, the satellite sensor that provides large spatial coverage has insufficient spatial detail to identify landscape patterns. Application of the super-resolution technique described in this dissertation could potentially solve this problem by providing detailed land cover predictions from the coarse resolution satellite sensor imagery.
NASA Astrophysics Data System (ADS)
Demirel, Mehmet C.; Mai, Juliane; Mendiguren, Gorka; Koch, Julian; Samaniego, Luis; Stisen, Simon
2018-02-01
Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET) are utilised for spatial model calibration tailored to target the pattern performance of the model. The proposed calibration framework combines temporally aggregated observed spatial patterns with a new spatial performance metric and a flexible spatial parameterisation scheme. The mesoscale hydrologic model (mHM) is used to simulate streamflow and AET and has been selected due to its soil parameter distribution approach based on pedo-transfer functions and the build in multi-scale parameter regionalisation. In addition two new spatial parameter distribution options have been incorporated in the model in order to increase the flexibility of root fraction coefficient and potential evapotranspiration correction parameterisations, based on soil type and vegetation density. These parameterisations are utilised as they are most relevant for simulated AET patterns from the hydrologic model. Due to the fundamental challenges encountered when evaluating spatial pattern performance using standard metrics, we developed a simple but highly discriminative spatial metric, i.e. one comprised of three easily interpretable components measuring co-location, variation and distribution of the spatial data. The study shows that with flexible spatial model parameterisation used in combination with the appropriate objective functions, the simulated spatial patterns of actual evapotranspiration become substantially more similar to the satellite-based estimates. Overall 26 parameters are identified for calibration through a sequential screening approach based on a combination of streamflow and spatial pattern metrics. The robustness of the calibrations is tested using an ensemble of nine calibrations based on different seed numbers using the shuffled complex evolution optimiser. The calibration results reveal a limited trade-off between streamflow dynamics and spatial patterns illustrating the benefit of combining separate observation types and objective functions. At the same time, the simulated spatial patterns of AET significantly improved when an objective function based on observed AET patterns and a novel spatial performance metric compared to traditional streamflow-only calibration were included. Since the overall water balance is usually a crucial goal in hydrologic modelling, spatial-pattern-oriented optimisation should always be accompanied by traditional discharge measurements. In such a multi-objective framework, the current study promotes the use of a novel bias-insensitive spatial pattern metric, which exploits the key information contained in the observed patterns while allowing the water balance to be informed by discharge observations.
Caustics and Rogue Waves in an Optical Sea.
Mathis, Amaury; Froehly, Luc; Toenger, Shanti; Dias, Frédéric; Genty, Goëry; Dudley, John M
2015-08-06
There are many examples in physics of systems showing rogue wave behaviour, the generation of high amplitude events at low probability. Although initially studied in oceanography, rogue waves have now been seen in many other domains, with particular recent interest in optics. Although most studies in optics have focussed on how nonlinearity can drive rogue wave emergence, purely linear effects have also been shown to induce extreme wave amplitudes. In this paper, we report a detailed experimental study of linear rogue waves in an optical system, using a spatial light modulator to impose random phase structure on a coherent optical field. After free space propagation, different random intensity patterns are generated, including partially-developed speckle, a broadband caustic network, and an intermediate pattern with characteristics of both speckle and caustic structures. Intensity peaks satisfying statistical criteria for rogue waves are seen especially in the case of the caustic network, and are associated with broader spatial spectra. In addition, the electric field statistics of the intermediate pattern shows properties of an "optical sea" with near-Gaussian statistics in elevation amplitude, and trough-to-crest statistics that are near-Rayleigh distributed but with an extended tail where a number of rogue wave events are observed.
Caustics and Rogue Waves in an Optical Sea
Mathis, Amaury; Froehly, Luc; Toenger, Shanti; Dias, Frédéric; Genty, Goëry; Dudley, John M.
2015-01-01
There are many examples in physics of systems showing rogue wave behaviour, the generation of high amplitude events at low probability. Although initially studied in oceanography, rogue waves have now been seen in many other domains, with particular recent interest in optics. Although most studies in optics have focussed on how nonlinearity can drive rogue wave emergence, purely linear effects have also been shown to induce extreme wave amplitudes. In this paper, we report a detailed experimental study of linear rogue waves in an optical system, using a spatial light modulator to impose random phase structure on a coherent optical field. After free space propagation, different random intensity patterns are generated, including partially-developed speckle, a broadband caustic network, and an intermediate pattern with characteristics of both speckle and caustic structures. Intensity peaks satisfying statistical criteria for rogue waves are seen especially in the case of the caustic network, and are associated with broader spatial spectra. In addition, the electric field statistics of the intermediate pattern shows properties of an “optical sea” with near-Gaussian statistics in elevation amplitude, and trough-to-crest statistics that are near-Rayleigh distributed but with an extended tail where a number of rogue wave events are observed. PMID:26245864
Modeling the spatio-temporal heterogeneity in the PM10-PM2.5 relationship
NASA Astrophysics Data System (ADS)
Chu, Hone-Jay; Huang, Bo; Lin, Chuan-Yao
2015-02-01
This paper explores the spatio-temporal patterns of particulate matter (PM) in Taiwan based on a series of methods. Using fuzzy c-means clustering first, the spatial heterogeneity (six clusters) in the PM data collected between 2005 and 2009 in Taiwan are identified and the industrial and urban areas of Taiwan (southwestern, west central, northwestern, and northern Taiwan) are found to have high PM concentrations. The PM10-PM2.5 relationship is then modeled with global ordinary least squares regression, geographically weighted regression (GWR), and geographically and temporally weighted regression (GTWR). The GTWR and GWR produce consistent results; however, GTWR provides more detailed information of spatio-temporal variations of the PM10-PM2.5 relationship. The results also show that GTWR provides a relatively high goodness of fit and sufficient space-time explanatory power. In particular, the PM2.5 or PM10 varies with time and space, depending on weather conditions and the spatial distribution of land use and emission patterns in local areas. Such information can be used to determine patterns of spatio-temporal heterogeneity in PM that will allow the control of pollutants and the reduction of public exposure.
NASA Astrophysics Data System (ADS)
Gómez Giménez, M.; Della Peruta, R.; de Jong, R.; Keller, A.; Schaepman, M. E.
2015-12-01
Agroecosystems play an important role providing economic and ecosystem services, which directly impact society. Inappropriate land use and unsustainable agricultural management with associated nutrient cycles can jeopardize important soil functions such as food production, livestock feeding and conservation of biodiversity. The objective of this study was to integrate remotely sensed land cover information into a regional Land Management Model (LMM) to improve the assessment of spatial explicit nutrient balances for agroecosystems. Remotely sensed data as well as an optimized parameter set contributed to feed the LMM providing a better spatial allocation of agricultural data aggregated at farm level. The integration of land use information in the land allocation process relied predominantly on three factors: i) spatial resolution, ii) classification accuracy and iii) parcels definition. The best-input parameter combination resulted in two different land cover classifications with overall accuracies of 98%, improving the LMM performance by 16% as compared to using non-spatially explicit input. Firstly, the use of spatial explicit information improved the spatial allocation output resulting in a pattern that better followed parcel boundaries (Figure 1). Second, the high classification accuracies ensured consistency between the datasets used. Third, the use of a suitable spatial unit to define the parcels boundaries influenced the model in terms of computational time and the amount of farmland allocated. We conclude that the combined use of remote sensing (RS) data with the LMM has the potential to provide highly accurate information of spatial explicit nutrient balances that are crucial for policy options concerning sustainable management of agricultural soils. Figure 1. Details of the spatial pattern obtained: a) Using only the farm census data, b) using also land use information. Framed in black in the left image (a), examples of artifacts that disappeared when using land use information (right image, b). Colors represent different ownership.
Spatial-structural analysis of leafless woody riparian vegetation for hydraulic considerations
NASA Astrophysics Data System (ADS)
Weissteiner, Clemens; Jalonen, Johanna; Järvelä, Juha; Rauch, Hans Peter
2013-04-01
Woody riparian vegetation is a vital element of riverine environments. On one hand woody riparian vegetation has to be taken into account from a civil engineering point of view due to boundary shear stress and vegetation drag. On the other hand it has to be considered from a river ecological point of view due to shadowing effects and as a source of organic material for aquatic habitats. In hydrodynamic and hydro-ecological studies the effects of woody riparian vegetation on flow patterns are usually investigated on a very detailed level. On the contrary vegetation elements and their spatial patterns are generally analysed and discussed on the basis of an integral approach measuring for example basal diameters, heights and projected plant areas. For a better understanding of the influence of woody riparian vegetation on turbulent flow and on river ecology, it is essential to record and analyse plant data sets on the same level of quality as for hydrodynamic or hydro-ecologic purposes. As a result of the same scale of the analysis it is possible to incorporate riparian vegetation as a sub-model in the hydraulic analysis. For plant structural components, such as branches on different topological levels it is crucial to record plant geometrical parameters describing the habitus of the plant on branch level. An exact 3D geometrical model of real plants allows for an extraction of various spatial-structural plant parameters. In addition, allometric relationships help to summarize and describe plant traits of riparian vegetation. This paper focuses on the spatial-structural composition of leafless riparia woddy vegetation. Structural and spatial analyses determine detailed geometric properties of the structural components of the plants. Geometrical and topological parameters were recorded with an electro-magnetic scanning device. In total, 23 plants (willows, alders and birches) were analysed in the study. Data were recorded on branch level, which allowed for the development of a 3D geometric plant model. The results are expected to improve knowledge on how the architectural system and allometric relationships of the plants relate to ecological and hydrodynamic properties.
Changes in population and agricultural land in conterminous United States counties, 1790 to 1997
Waisanen, Pamela J.; Bliss, Norman B.
2002-01-01
We have developed a data set of changes in population and agricultural land for the conterminous United States at the county level, resulting in more spatial detail than in previously available compilations. The purpose was to provide data on the timing of land conversion as an input to dynamic models of the carbon cycle, although a wide variety of applications exist for the physical, biological, and social sciences. The spatial data represent the appropriate county boundaries for each census year between 1790 and 1997, and the census attributes are attached to the appropriate spatial region. The resulting time series and maps show the history of population (1790-1990) and the history of agricultural development (1850-1997). The patterns of agricultural development reflect the influences of climate, soil productivity, increases in population size, variations in the general economy, and technological changes in the energy, transportation, and agricultural sectors.
Reichenau, Tim G; Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl
2016-01-01
The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI.
Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl
2016-01-01
The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI. PMID:27391858
Behavioral and Neural Representations of Spatial Directions across Words, Schemas, and Images.
Weisberg, Steven M; Marchette, Steven A; Chatterjee, Anjan
2018-05-23
Modern spatial navigation requires fluency with multiple representational formats, including visual scenes, signs, and words. These formats convey different information. Visual scenes are rich and specific but contain extraneous details. Arrows, as an example of signs, are schematic representations in which the extraneous details are eliminated, but analog spatial properties are preserved. Words eliminate all spatial information and convey spatial directions in a purely abstract form. How does the human brain compute spatial directions within and across these formats? To investigate this question, we conducted two experiments on men and women: a behavioral study that was preregistered and a neuroimaging study using multivoxel pattern analysis of fMRI data to uncover similarities and differences among representational formats. Participants in the behavioral study viewed spatial directions presented as images, schemas, or words (e.g., "left"), and responded to each trial, indicating whether the spatial direction was the same or different as the one viewed previously. They responded more quickly to schemas and words than images, despite the visual complexity of stimuli being matched. Participants in the fMRI study performed the same task but responded only to occasional catch trials. Spatial directions in images were decodable in the intraparietal sulcus bilaterally but were not in schemas and words. Spatial directions were also decodable between all three formats. These results suggest that intraparietal sulcus plays a role in calculating spatial directions in visual scenes, but this neural circuitry may be bypassed when the spatial directions are presented as schemas or words. SIGNIFICANCE STATEMENT Human navigators encounter spatial directions in various formats: words ("turn left"), schematic signs (an arrow showing a left turn), and visual scenes (a road turning left). The brain must transform these spatial directions into a plan for action. Here, we investigate similarities and differences between neural representations of these formats. We found that bilateral intraparietal sulci represent spatial directions in visual scenes and across the three formats. We also found that participants respond quickest to schemas, then words, then images, suggesting that spatial directions in abstract formats are easier to interpret than concrete formats. These results support a model of spatial direction interpretation in which spatial directions are either computed for real world action or computed for efficient visual comparison. Copyright © 2018 the authors 0270-6474/18/384996-12$15.00/0.
Adaptive antenna arrays for satellite communications: Design and testing
NASA Technical Reports Server (NTRS)
Gupta, I. J.; Swarner, W. G.; Walton, E. K.
1985-01-01
When two separate antennas are used with each feedback loop to decorrelate noise, the antennas should be located such that the phase of the interfering signal in the two antennas is the same while the noise in them is uncorrelated. Thus, the antenna patterns and spatial distribution of the auxiliary antennas are quite important and should be carefully selected. The selection and spatial distribution of auxiliary elements is discussed when the main antenna is a center fed reflector antenna. It is shown that offset feeds of the reflector antenna can be used as auxiliary elements of an adaptive array to suppress weak interfering signals. An experimental system is designed to verify the theoretical analysis. The details of the experimental systems are presented.
Communication scheme based on evolutionary spatial 2×2 games
NASA Astrophysics Data System (ADS)
Ziaukas, Pranas; Ragulskis, Tautvydas; Ragulskis, Minvydas
2014-06-01
A visual communication scheme based on evolutionary spatial 2×2 games is proposed in this paper. Self-organizing patterns induced by complex interactions between competing individuals are exploited for hiding and transmitting secret visual information. Properties of the proposed communication scheme are discussed in details. It is shown that the hiding capacity of the system (the minimum size of the detectable primitives and the minimum distance between two primitives) is sufficient for the effective transmission of digital dichotomous images. Also, it is demonstrated that the proposed communication scheme is resilient to time backwards, plain image attacks and is highly sensitive to perturbations of private and public keys. Several computational experiments are used to demonstrate the effectiveness of the proposed communication scheme.
Running Improves Pattern Separation during Novel Object Recognition.
Bolz, Leoni; Heigele, Stefanie; Bischofberger, Josef
2015-10-09
Running increases adult neurogenesis and improves pattern separation in various memory tasks including context fear conditioning or touch-screen based spatial learning. However, it is unknown whether pattern separation is improved in spontaneous behavior, not emotionally biased by positive or negative reinforcement. Here we investigated the effect of voluntary running on pattern separation during novel object recognition in mice using relatively similar or substantially different objects.We show that running increases hippocampal neurogenesis but does not affect object recognition memory with 1.5 h delay after sample phase. By contrast, at 24 h delay, running significantly improves recognition memory for similar objects, whereas highly different objects can be distinguished by both, running and sedentary mice. These data show that physical exercise improves pattern separation, independent of negative or positive reinforcement. In sedentary mice there is a pronounced temporal gradient for remembering object details. In running mice, however, increased neurogenesis improves hippocampal coding and temporally preserves distinction of novel objects from familiar ones.
The effect of lossy image compression on image classification
NASA Technical Reports Server (NTRS)
Paola, Justin D.; Schowengerdt, Robert A.
1995-01-01
We have classified four different images, under various levels of JPEG compression, using the following classification algorithms: minimum-distance, maximum-likelihood, and neural network. The training site accuracy and percent difference from the original classification were tabulated for each image compression level, with maximum-likelihood showing the poorest results. In general, as compression ratio increased, the classification retained its overall appearance, but much of the pixel-to-pixel detail was eliminated. We also examined the effect of compression on spatial pattern detection using a neural network.
COMPARISON OF SPATIAL PATTERNS OF POLLUTANT DISTRIBUTION WITH CMAQ PREDICTIONS
One indication of model performance is the comparison of spatial patterns of pollutants, either as concentration or deposition, predicted by the model with spatial patterns derived from measurements. If the spatial patterns produced by the model are similar to the observations i...
Decoding the spatial signatures of multi-scale climate variability - a climate network perspective
NASA Astrophysics Data System (ADS)
Donner, R. V.; Jajcay, N.; Wiedermann, M.; Ekhtiari, N.; Palus, M.
2017-12-01
During the last years, the application of complex networks as a versatile tool for analyzing complex spatio-temporal data has gained increasing interest. Establishing this approach as a new paradigm in climatology has already provided valuable insights into key spatio-temporal climate variability patterns across scales, including novel perspectives on the dynamics of the El Nino Southern Oscillation or the emergence of extreme precipitation patterns in monsoonal regions. In this work, we report first attempts to employ network analysis for disentangling multi-scale climate variability. Specifically, we introduce the concept of scale-specific climate networks, which comprises a sequence of networks representing the statistical association structure between variations at distinct time scales. For this purpose, we consider global surface air temperature reanalysis data and subject the corresponding time series at each grid point to a complex-valued continuous wavelet transform. From this time-scale decomposition, we obtain three types of signals per grid point and scale - amplitude, phase and reconstructed signal, the statistical similarity of which is then represented by three complex networks associated with each scale. We provide a detailed analysis of the resulting connectivity patterns reflecting the spatial organization of climate variability at each chosen time-scale. Global network characteristics like transitivity or network entropy are shown to provide a new view on the (global average) relevance of different time scales in climate dynamics. Beyond expected trends originating from the increasing smoothness of fluctuations at longer scales, network-based statistics reveal different degrees of fragmentation of spatial co-variability patterns at different scales and zonal shifts among the key players of climate variability from tropically to extra-tropically dominated patterns when moving from inter-annual to decadal scales and beyond. The obtained results demonstrate the potential usefulness of systematically exploiting scale-specific climate networks, whose general patterns are in line with existing climatological knowledge, but provide vast opportunities for further quantifications at local, regional and global scales that are yet to be explored.
Space in the brain: how the hippocampal formation supports spatial cognition
Hartley, Tom; Lever, Colin; Burgess, Neil; O'Keefe, John
2014-01-01
Over the past four decades, research has revealed that cells in the hippocampal formation provide an exquisitely detailed representation of an animal's current location and heading. These findings have provided the foundations for a growing understanding of the mechanisms of spatial cognition in mammals, including humans. We describe the key properties of the major categories of spatial cells: place cells, head direction cells, grid cells and boundary cells, each of which has a characteristic firing pattern that encodes spatial parameters relating to the animal's current position and orientation. These properties also include the theta oscillation, which appears to play a functional role in the representation and processing of spatial information. Reviewing recent work, we identify some themes of current research and introduce approaches to computational modelling that have helped to bridge the different levels of description at which these mechanisms have been investigated. These range from the level of molecular biology and genetics to the behaviour and brain activity of entire organisms. We argue that the neuroscience of spatial cognition is emerging as an exceptionally integrative field which provides an ideal test-bed for theories linking neural coding, learning, memory and cognition. PMID:24366125
Effects of acute insulin-induced hypoglycemia on spatial abilities in adults with type 1 diabetes.
Wright, Rohana J; Frier, Brian M; Deary, Ian J
2009-08-01
OBJECTIVE To examine the effects of acute insulin-induced hypoglycemia on spatial cognitive abilities in adult humans with type 1 diabetes. RESEARCH DESIGN AND METHODS Sixteen adults with type 1 diabetes underwent two counterbalanced experimental sessions: euglycemia (blood glucose 4.5 mmol/l [81 mg/dl]) and hypoglycemia (2.5 mmol/l [45 mg/dl]). Arterialized blood glucose levels were maintained using a hyperinsulinemic glucose clamp technique. During each session, subjects underwent detailed assessment of spatial abilities from the Kit of Factor-Referenced Cognitive Tests and two tests of general cognitive function. RESULTS Spatial ability performance deteriorated significantly during hypoglycemia. Results for the Hidden Patterns, Card Rotations, Paper Folding, and Maze Tracing tests were all impaired significantly (P < or = 0.001) during hypoglycemia, as were results for the Cube Comparisons Test (P = 0.03). The Map Memory Test was not significantly affected by hypoglycemia. CONCLUSIONS Hypoglycemia is a common side effect of insulin therapy in individuals with type 1 diabetes, and spatial abilities are of critical importance in day-to-day functioning. The deterioration in spatial abilities observed during modest experimental hypoglycemia provides novel information on the cerebral hazards of hypoglycemia that has potential relevance to everyday activities.
NASA Astrophysics Data System (ADS)
Bayat, Bardia; Zahraie, Banafsheh; Taghavi, Farahnaz; Nasseri, Mohsen
2013-08-01
Identification of spatial and spatiotemporal precipitation variations plays an important role in different hydrological applications such as missing data estimation. In this paper, the results of Bayesian maximum entropy (BME) and ordinary kriging (OK) are compared for modeling spatial and spatiotemporal variations of annual precipitation with and without incorporating elevation variations. The study area of this research is Namak Lake watershed located in the central part of Iran with an area of approximately 90,000 km2. The BME and OK methods have been used to model the spatial and spatiotemporal variations of precipitation in this watershed, and their performances have been evaluated using cross-validation statistics. The results of the case study have shown the superiority of BME over OK in both spatial and spatiotemporal modes. The results have shown that BME estimates are less biased and more accurate than OK. The improvements in the BME estimates are mostly related to incorporating hard and soft data in the estimation process, which resulted in more detailed and reliable results. Estimation error variance for BME results is less than OK estimations in the study area in both spatial and spatiotemporal modes.
Lottig, Noah R.; Tan, Pang-Ning; Wagner, Tyler; Cheruvelil, Kendra Spence; Soranno, Patricia A.; Stanley, Emily H.; Scott, Caren E.; Stow, Craig A.; Yuan, Shuai
2017-01-01
Ecology has a rich history of studying ecosystem dynamics across time and space that has been motivated by both practical management needs and the need to develop basic ideas about pattern and process in nature. In situations in which both spatial and temporal observations are available, similarities in temporal behavior among sites (i.e., synchrony) provide a means of understanding underlying processes that create patterns over space and time. We used pattern analysis algorithms and data spanning 22–25 yr from 601 lakes to ask three questions: What are the temporal patterns of lake water clarity at sub‐continental scales? What are the spatial patterns (i.e., geography) of synchrony for lake water clarity? And, what are the drivers of spatial and temporal patterns in lake water clarity? We found that the synchrony of water clarity among lakes is not spatially structured at sub‐continental scales. Our results also provide strong evidence that the drivers related to spatial patterns in water clarity are not related to the temporal patterns of water clarity. This analysis of long‐term patterns of water clarity and possible drivers contributes to understanding of broad‐scale spatial patterns in the geography of synchrony and complex relationships between spatial and temporal patterns across ecosystems.
Spatial and Temporal Patterns of Impervious Cover Relative to Watershed Stream Location
The influence of spatial pattern on ecological processes is a guiding principle of landscape ecology. The guiding principle of spatial pattern was used for a U.S. nationwide assessment of impervious cover (IC). Spatial pattern was measured by comparing IC concentration near strea...
Temperature distribution and heat radiation of patterned surfaces at short wavelengths.
Emig, Thorsten
2017-05-01
We analyze the equilibrium spatial distribution of surface temperatures of patterned surfaces. The surface is exposed to a constant external heat flux and has a fixed internal temperature that is coupled to the outside heat fluxes by finite heat conductivity across the surface. It is assumed that the temperatures are sufficiently high so that the thermal wavelength (a few microns at room temperature) is short compared to all geometric length scales of the surface patterns. Hence the radiosity method can be employed. A recursive multiple scattering method is developed that enables rapid convergence to equilibrium temperatures. While the temperature distributions show distinct dependence on the detailed surface shapes (cuboids and cylinder are studied), we demonstrate robust universal relations between the mean and the standard deviation of the temperature distributions and quantities that characterize overall geometric features of the surface shape.
Temperature distribution and heat radiation of patterned surfaces at short wavelengths
NASA Astrophysics Data System (ADS)
Emig, Thorsten
2017-05-01
We analyze the equilibrium spatial distribution of surface temperatures of patterned surfaces. The surface is exposed to a constant external heat flux and has a fixed internal temperature that is coupled to the outside heat fluxes by finite heat conductivity across the surface. It is assumed that the temperatures are sufficiently high so that the thermal wavelength (a few microns at room temperature) is short compared to all geometric length scales of the surface patterns. Hence the radiosity method can be employed. A recursive multiple scattering method is developed that enables rapid convergence to equilibrium temperatures. While the temperature distributions show distinct dependence on the detailed surface shapes (cuboids and cylinder are studied), we demonstrate robust universal relations between the mean and the standard deviation of the temperature distributions and quantities that characterize overall geometric features of the surface shape.
Identifying forest patterns from space to explore dynamics across the circumpolar boreal
NASA Astrophysics Data System (ADS)
Montesano, P. M.; Neigh, C. S. R.; Feng, M.; Channan, S.; Sexton, J. O.; Wagner, W.; Wooten, M.; Poulter, B.; Wang, L.
2017-12-01
A variety of forest patterns are the result of interactions between broad-scale climate and local-scale site factors and history across the northernmost portion of the circumpolar boreal. Patterns of forest extent, height, and cover help describe forest structure transitions that influence future and reflect past dynamics. Coarse spaceborne observations lack structural detail at forest transitions, which inhibits understanding of these dynamics. We highlight: (1) the use of sub-meter spaceborne stereogrammetry for deriving structure estimates in boreal forests; (2) its potential to complement other spaceborne estimates of forest structure at critical scales; and (3) the potential of these sub-meter and other Landsat-derived structure estimates for improving understanding of broad-scale boreal dynamics such as carbon flux and albedo, capturing the spatial variability of the boreal-tundra biome boundary, and assessing its potential for change.
NASA Astrophysics Data System (ADS)
Wang, Jue
Understanding the influences of climate on productivity remains a major challenge in landscape ecology. Satellite remote sensing of normalized difference vegetation index (NDVI) provides a useful tool to study landscape patterns, based on generalization of local measurements, and to examine relations between climate and variation in productivity. This dissertation examines temporal and spatial relations between NDVI, productivity, and climatic factors over the course of nine years in the central Great Plains. Two general findings emerge: (1) integrated NDVI is a reliable measure of production, as validated with ground-based productivity measurements; and (2) precipitation is the primary factor that determines spatial and temporal patterns of NDVI. NDVI, integrated over appropriate time intervals, is strongly correlated with ground productivity measurements in forests, grasslands, and croplands. Most tree productivity measurements (tree ring size, tree diameter growth, and seed production) are strongly correlated with NDVI integrated for a period during the early growing season; foliage production is most strongly correlated with NDVI integrated over the entire growing season; and tree height growth corresponds with NDVI integrate during the previous growing season. Similarly, productivity measurements for herbaceous plants (grassland biomass and crop yield) are strongly correlated with NDVI. Within the growing season, the temporal pattern of grassland biomass production covaries with NDVI, with a four-week lag time. Across years, grassland biomass production covaries with NDVI integrated from part to all of the current growing season. Corn and wheat yield are most strongly related to NDVI integrated from late June to early August and from late April to mid-May, respectively. Precipitation strongly influences both temporal and spatial patterns of NDVI, while temperature influences NDVI only during the early and late growing season. In terms of temporal patterns, NDVI integrated over the growing season is strongly correlated with precipitation received during the current growing season plus the seven preceding months (fifteen month period); NDVI within the growing season responds to changes in precipitation with a four to eight week lag time; and major precipitation events lead to changes in NDVI with a two to four week lag time. Temperature has a positive correlation with NDVI during the early and late growing season, and a weak negative correlation during the middle of the growing season. In terms of spatial patterns, average precipitation is a strong predictor of the major east-west gradient of NDVI. Deviation from average precipitation explains most of the year-to-year variation in spatial patterns. NDVI and precipitation deviations from average covary (both positive or both negative) for 60--95% of the total land area in Kansas. Minimum and average temperatures are positively correlated with NDVI, but temperature deviation from average is generally not correlated with NDVI deviation from average. The strong relationships between NDVI and productivity, and between precipitation and NDVI, along with detailed analysis of the temporal and spatial patterns for our study region, provides the basis for prediction of productivity at landscape scales under different climate regimes.
Tudesque, Loïc; Tisseuil, Clément; Lek, Sovan
2014-01-01
The scale dependence of ecological phenomena remains a central issue in ecology. Particularly in aquatic ecology, the consideration of the accurate spatial scale in assessing the effects of landscape factors on stream condition is critical. In this context, our study aimed at assessing the relationships between multi-spatial scale land cover patterns and a variety of water quality and diatom metrics measured at the stream reach level. This investigation was conducted in a major European river system, the Adour-Garonne river basin, characterized by a wide range of ecological conditions. Redundancy analysis (RDA) and variance partitioning techniques were used to disentangle the different relationships between land cover, water-chemistry and diatom metrics. Our results revealed a top-down "cascade effect" indirectly linking diatom metrics to land cover patterns through water physico-chemistry, which occurred at the largest spatial scales. In general, the strength of the relationships between land cover, physico-chemistry, and diatoms was shown to increase with the spatial scale, from the local to the basin scale, emphasizing the importance of continuous processes of accumulation throughout the river gradient. Unexpectedly, we established that the influence of land cover on the diatom metric was of primary importance both at the basin and local scale, as a result of discontinuous but not necessarily antagonist processes. The most detailed spatial grain of the Corine land cover classification appeared as the most relevant spatial grain to relate land cover to water chemistry and diatoms. Our findings provide suitable information to improve the implementation of effective diatom-based monitoring programs, especially within the scope of the European Water Framework Directive. © 2013 Elsevier B.V. All rights reserved.
Hydrogeological controls on spatial patterns of groundwater discharge in peatlands
NASA Astrophysics Data System (ADS)
Hare, Danielle K.; Boutt, David F.; Clement, William P.; Hatch, Christine E.; Davenport, Glorianna; Hackman, Alex
2017-11-01
Peatland environments provide important ecosystem services including water and carbon storage, nutrient processing and retention, and wildlife habitat. However, these systems and the services they provide have been degraded through historical anthropogenic agricultural conversion and dewatering practices. Effective wetland restoration requires incorporating site hydrology and understanding groundwater discharge spatial patterns. Groundwater discharge maintains wetland ecosystems by providing relatively stable hydrologic conditions, nutrient inputs, and thermal buffering important for ecological structure and function; however, a comprehensive site-specific evaluation is rarely feasible for such resource-constrained projects. An improved process-based understanding of groundwater discharge in peatlands may help guide ecological restoration design without the need for invasive methodologies and detailed site-specific investigation. Here we examine a kettle-hole peatland in southeast Massachusetts historically modified for commercial cranberry farming. During the time of our investigation, a large process-based ecological restoration project was in the assessment and design phases. To gain insight into the drivers of site hydrology, we evaluated the spatial patterning of groundwater discharge and the subsurface structure of the peatland complex using heat-tracing methods and ground-penetrating radar. Our results illustrate that two groundwater discharge processes contribute to the peatland hydrologic system: diffuse lower-flux marginal matrix seepage and discrete higher-flux preferential-flow-path seepage. Both types of groundwater discharge develop through interactions with subsurface peatland basin structure, often where the basin slope is at a high angle to the regional groundwater gradient. These field observations indicate strong correlation between subsurface structures and surficial groundwater discharge. Understanding these general patterns may allow resource managers to more efficiently predict and locate groundwater seepage, confirm these using remote sensing technologies, and incorporate this information into restoration design for these critical ecosystems.
NASA Astrophysics Data System (ADS)
Lillis, Ashlee; Mooney, T. Aran
2018-06-01
The rich acoustic environment of coral reefs, including the sounds of a variety of fish and invertebrates, is a reflection of the structural complexity and biological diversity of these habitats. Emerging interest in applying passive acoustic monitoring and soundscape analysis to measure coral reef habitat characteristics and track ecological patterns is hindered by a poor understanding of the most common and abundant sound producers on reefs—the snapping shrimp. Here, we sought to address several basic biophysical drivers of reef sound by investigating acoustic activity patterns of snapping shrimp populations on two adjacent coral reefs using a detailed snap detection analysis routine to a high-resolution 2.5-month acoustic dataset from the US Virgin Islands. The reefs exhibited strong diel and lunar periodicity in snap rates and clear spatial differences in snapping levels. Snap rates peaked at dawn and dusk and were higher overall during daytime versus nighttime, a seldom-reported pattern in earlier descriptions of diel snapping shrimp acoustic activity. Small differences between the sites in snap rate rhythms were detected and illustrate how analyses of specific soundscape elements might reveal subtle between-reef variation. Snap rates were highly correlated with environmental variables, including water temperature and light, and were found to be sensitive to changes in oceanographic forcing. This study further establishes snapping shrimp as key players in the coral reef chorus and provides evidence that their acoustic output reflects a combination of environmental conditions, celestial influences, and spatial habitat variation. Effective application of passive acoustic monitoring in coral reef habitats using snap rates or snapping-influenced acoustic metrics will require a mechanistic understanding of the underlying spatial and temporal variation in snapping shrimp sound production across multiple scales.
Simple models for studying complex spatiotemporal patterns of animal behavior
NASA Astrophysics Data System (ADS)
Tyutyunov, Yuri V.; Titova, Lyudmila I.
2017-06-01
Minimal mathematical models able to explain complex patterns of animal behavior are essential parts of simulation systems describing large-scale spatiotemporal dynamics of trophic communities, particularly those with wide-ranging species, such as occur in pelagic environments. We present results obtained with three different modelling approaches: (i) an individual-based model of animal spatial behavior; (ii) a continuous taxis-diffusion-reaction system of partial-difference equations; (iii) a 'hybrid' approach combining the individual-based algorithm of organism movements with explicit description of decay and diffusion of the movement stimuli. Though the models are based on extremely simple rules, they all allow description of spatial movements of animals in a predator-prey system within a closed habitat, reproducing some typical patterns of the pursuit-evasion behavior observed in natural populations. In all three models, at each spatial position the animal movements are determined by local conditions only, so the pattern of collective behavior emerges due to self-organization. The movement velocities of animals are proportional to the density gradients of specific cues emitted by individuals of the antagonistic species (pheromones, exometabolites or mechanical waves of the media, e.g., sound). These cues play a role of taxis stimuli: prey attract predators, while predators repel prey. Depending on the nature and the properties of the movement stimulus we propose using either a simplified individual-based model, a continuous taxis pursuit-evasion system, or a little more detailed 'hybrid' approach that combines simulation of the individual movements with the continuous model describing diffusion and decay of the stimuli in an explicit way. These can be used to improve movement models for many species, including large marine predators.
Regional patterns of total nitrogen concentrations in the National Rivers and Streams Assessment
Omernik, James M.; Paulsen, Steven G.; Griffith, Glenn E.; Weber, Marc H.
2016-01-01
Patterns of nitrogen (N) concentrations in streams sampled by the National Rivers and Streams Assessment (NRSA) were examined semiquantitatively to identify regional differences in stream N levels. The data were categorized and analyzed by watershed size classes to reveal patterns of the concentrations that are consistent with the spatial homogeneity in natural and anthropogenic characteristics associated with regional differences in N levels. Ecoregions and mapped information on human activities including agricultural practices were used to determine the resultant regions. Marked differences in N levels were found among the nine aggregations of ecoregions used to report the results of the NRSA. We identified distinct regional patterns of stream N concentrations within the reporting regions that are associated with the characteristics of specific Level III ecoregions, groups of Level III ecoregions, groups of Level IV ecoregions, certain geographic characteristics within ecoregions, and/or particular watershed size classes. We described each of these regions and illustrated their areal extent and median and range in N concentrations. Understanding the spatial variability of nutrient concentrations in flowing waters and the apparent contributions that human and nonhuman factors have on different sizes of streams and rivers is critical to the development of effective water quality assessment and management plans. This semi-quantitative analysis is also intended to identify areas within which more detailed quantitative work can be conducted to determine specific regional factors associated with variations in stream N concentrations.
Turbulent flame-wall interaction: a DNS study
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, Jackie; Hawkes, Evatt R; Sankaran, Ramanan
2010-01-01
A turbulent flame-wall interaction (FWI) configuration is studied using three-dimensional direct numerical simulation (DNS) and detailed chemical kinetics. The simulations are used to investigate the effects of the wall turbulent boundary layer (i) on the structure of a hydrogen-air premixed flame, (ii) on its near-wall propagation characteristics and (iii) on the spatial and temporal patterns of the convective wall heat flux. Results show that the local flame thickness and propagation speed vary between the core flow and the boundary layer, resulting in a regime change from flamelet near the channel centreline to a thickened flame at the wall. This findingmore » has strong implications for the modelling of turbulent combustion using Reynolds-averaged Navier-Stokes or large-eddy simulation techniques. Moreover, the DNS results suggest that the near-wall coherent turbulent structures play an important role on the convective wall heat transfer by pushing the hot reactive zone towards the cold solid surface. At the wall, exothermic radical recombination reactions become important, and are responsible for approximately 70% of the overall heat release rate at the wall. Spectral analysis of the convective wall heat flux provides an unambiguous picture of its spatial and temporal patterns, previously unobserved, that is directly related to the spatial and temporal characteristic scalings of the coherent near-wall turbulent structures.« less
NASA Astrophysics Data System (ADS)
Navarro, Gabriel; Vicent, Jorge; Caballero, Isabel; Gómez-Enri, Jesús; Morris, Edward P.; Sabater, Neus; Macías, Diego; Bolado-Penagos, Marina; Gomiz, Juan Jesús; Bruno, Miguel; Caldeira, Rui; Vázquez, Águeda
2018-05-01
High Amplitude Internal Waves (HAIWs) are physical processes observed in the Strait of Gibraltar (the narrow channel between the Atlantic Ocean and the Mediterranean Sea). These internal waves are generated over the Camarinal Sill (western side of the strait) during the tidal outflow (toward the Atlantic Ocean) when critical hydraulic conditions are established. HAIWs remain over the sill for up to 4 h until the outflow slackens, being then released (mostly) towards the Mediterranean Sea. These have been previously observed using Synthetic Aperture Radar (SAR), which captures variations in surface water roughness. However, in this work we use high resolution optical remote sensing, with the aim of examining the influence of HAIWs on biogeochemical processes. We used hyperspectral images from the Hyperspectral Imager for the Coastal Ocean (HICO) and high spatial resolution (10 m) images from the MultiSpectral Instrument (MSI) onboard the Sentinel-2A satellite. This work represents the first attempt to examine the relation between internal wave generation and the water constituents of the Camarinal Sill using hyperspectral and high spatial resolution remote sensing images. This enhanced spatial and spectral resolution revealed the detailed biogeochemical patterns associated with the internal waves and suggests local enhancements of productivity associated with internal waves trains.
Brian R Miranda; Brian R Sturtevant; Susan I Stewart; Roger B. Hammer
2012-01-01
Most drivers underlying wildfire are dynamic, but at different spatial and temporal scales. We quantified temporal and spatial trends in wildfire patterns over two spatial extents in northern Wisconsin to identify drivers and their change through time. We used spatial point pattern analysis to quantify the spatial pattern of wildfire occurrences, and linear regression...
Circulation controls of the spatial structure of maximum daily precipitation over Poland
NASA Astrophysics Data System (ADS)
Stach, Alfred
2015-04-01
Among forecasts made on the basis of global and regional climatic models is one of a high probability of an increase in the frequency and intensity of extreme precipitation events. Learning the regularities underlying the recurrence and spatial extent of extreme precipitation is obviously of great importance, both economic and social. The main goal of the study was to analyse regularities underlying spatial and temporal variations in monthly Maximum Daily Precipitation Totals (MDPTs) observed in Poland over the years 1956-1980. These data are specific because apart from being spatially discontinuous, which is typical of precipitation, they are also non-synchronic. The main aim of the study was accomplished via several detailed goals: • identification and typology of the spatial structure of monthly MDPTs, • determination of the character and probable origin of events generating MDPTs, and • quantitative assessment of the contribution of the particular events to the overall MDPT figures. The analysis of the spatial structure of MDPTs was based on 300 models of spatial structure, one for each of the analysed sets of monthly MDPTs. The models were built on the basis of empirical anisotropic semivariograms of normalised data. In spite of their spatial discontinuity and asynchronicity, the MDPT data from Poland display marked regularities in their spatial pattern that yield readily to mathematical modelling. The MDPT field in Poland is usually the sum of the outcomes of three types of processes operating at various spatial scales: local (<10-20 km), regional (50-150 km), and supra-regional (>200 km). The spatial scales are probably connected with a convective/ orographic, a frontal and a 'planetary waves' genesis of high precipitation. Their contributions are highly variable. Generally predominant, however, are high daily precipitation totals with a spatial extent of 50 to 150 km connected with mesoscale phenomena and the migration of atmospheric fronts (35-38%). The spatial extent of areas of high local-scale precipitation usually varies at random, especially in the warm season. At supra-local scales, structures of repetitive size predominate. Eight types of anisotropic structures of monthly MDPTs were distinguished. To identify them, an analysis was made of semivariance surface similarities. The types differ not only in the level and direction of anisotropy, but also in the number and type of elementary components, which is evidence of genetic differences in precipitation. Their appearance shows a significant seasonal variability, so the most probable supposition was that temporal variations in the MDPT pattern were connected with circulation conditions: the type and direction of inflow of air masses. This hypothesis was validated by testing differences in the frequency of occurrence of Grosswetterlagen circulation situations in the months belonging to the distinguished types of the spatial MDPT pattern.
Wilson, Robin; Zu Erbach-Schoenberg, Elisabeth; Albert, Maximilian; Power, Daniel; Tudge, Simon; Gonzalez, Miguel; Guthrie, Sam; Chamberlain, Heather; Brooks, Christopher; Hughes, Christopher; Pitonakova, Lenka; Buckee, Caroline; Lu, Xin; Wetter, Erik; Tatem, Andrew; Bengtsson, Linus
2016-02-24
Sudden impact disasters often result in the displacement of large numbers of people. These movements can occur prior to events, due to early warning messages, or take place post-event due to damages to shelters and livelihoods as well as a result of long-term reconstruction efforts. Displaced populations are especially vulnerable and often in need of support. However, timely and accurate data on the numbers and destinations of displaced populations are extremely challenging to collect across temporal and spatial scales, especially in the aftermath of disasters. Mobile phone call detail records were shown to be a valid data source for estimates of population movements after the 2010 Haiti earthquake, but their potential to provide near real-time ongoing measurements of population displacements immediately after a natural disaster has not been demonstrated. A computational architecture and analytical capacity were rapidly deployed within nine days of the Nepal earthquake of 25th April 2015, to provide spatiotemporally detailed estimates of population displacements from call detail records based on movements of 12 million de-identified mobile phones users. Analysis shows the evolution of population mobility patterns after the earthquake and the patterns of return to affected areas, at a high level of detail. Particularly notable is the movement of an estimated 390,000 people above normal from the Kathmandu valley after the earthquake, with most people moving to surrounding areas and the highly-populated areas in the central southern area of Nepal. This analysis provides an unprecedented level of information about human movement after a natural disaster, provided within a very short timeframe after the earthquake occurred. The patterns revealed using this method are almost impossible to find through other methods, and are of great interest to humanitarian agencies.
Detection and Analysis of Complex Patterns of Ice Dynamics in Antarctica from ICESat Laser Altimetry
NASA Astrophysics Data System (ADS)
Babonis, Gregory Scott
There remains much uncertainty in estimating the amount of Antarctic ice mass change, its dynamic component, and its spatial and temporal patterns. This work remedies the limitations of previous studies by generating the first detailed reconstruction of total and dynamic ice thickness and mass changes across Antarctica, from ICESat satellite altimetry observations in 2003-2009 using the Surface Elevation Reconstruction and Change Detection (SERAC) method. Ice sheet thickness changes are calculated with quantified error estimates for each time when ICESat flew over a ground-track crossover region, at approximately 110,000 locations across the Antarctic Ice Sheet. The time series are partitioned into changes due to surficial processes and ice dynamics. The new results markedly improve the spatial and temporal resolution of surface elevation, volume, and mass change rates for the AIS, and can be sampled at annual temporal resolutions. The results indicate a complex spatiotemporal pattern of dynamic mass loss in Antarctica, especially along individual outlet glaciers, and allow for the quantification of the annual contribution of Antarctic ice loss to sea level rise. Over 5000 individual locations exhibit either strong dynamic ice thickness change patterns, accounting for approximately 500 unique spatial clusters that identify regions likely influenced by subglacial hydrology. The spatial distribution and temporal behavior of these regions reveal the complexity and short-time scale variability in the subglacial hydrological system. From the 500 unique spatial clusters, over 370 represent newly identified, and not previously published, potential subglacial water bodies indicating an active subglacial hydrological system over a much larger region than previously observed. These numerous new observations of dynamic changes provide more than simply a larger set of data. Examination of both regional and local scale dynamic change patterns across Antarctica shows newly discovered connections between the geology and ice sheet dynamics of Antarctica, particularly along the boundary between East and West Antarctica in the Pagano Shear Zone. Additionally, increased dynamic activity is shown to concentrate in regions of Antarctica most likely to experience catastrophic failure and collapse in the future. Further quantification of mass and volume changes demonstrates that the methods described within allow for a true reconciliation between different satellite methods of measuring ice sheet mass and volume balance, and show that Antarctica is losing enough mass between 2003 and 2009 to raise global sea levels 0.1 mm/yr during that time. Additionally, analysis of local patterns of dynamic ice thickness changes shows that there is continued or increased ice loss, since before the ICESat mission period, in many of the coastal sectors of Antarctica.
NASA Astrophysics Data System (ADS)
Dods, Joe; Chapman, Sandra; Gjerloev, Jesper
2016-04-01
Quantitative understanding of the full spatial-temporal pattern of space weather is important in order to estimate the ground impact. Geomagnetic indices such as AE track the peak of a geomagnetic storm or substorm, but cannot capture the full spatial-temporal pattern. Observations by the ~100 ground based magnetometers in the northern hemisphere have the potential to capture the detailed evolution of a given space weather event. We present the first analysis of the full available set of ground based magnetometer observations of substorms using dynamical networks. SuperMAG offers a database containing ground station magnetometer data at a cadence of 1min from 100s stations situated across the globe. We use this data to form dynamic networks which capture spatial dynamics on timescales from the fast reconfiguration seen in the aurora, to that of the substorm cycle. Windowed linear cross-correlation between pairs of magnetometer time series along with a threshold is used to determine which stations are correlated and hence connected in the network. Variations in ground conductivity and differences in the response functions of magnetometers at individual stations are overcome by normalizing to long term averages of the cross-correlation. These results are tested against surrogate data in which phases have been randomised. The network is then a collection of connected points (ground stations); the structure of the network and its variation as a function of time quantify the detailed dynamical processes of the substorm. The network properties can be captured quantitatively in time dependent dimensionless network parameters and we will discuss their behaviour for examples of 'typical' substorms and storms. The network parameters provide a detailed benchmark to compare data with models of substorm dynamics, and can provide new insights on the similarities and differences between substorms and how they correlate with external driving and the internal state of the magnetosphere. We can also investigate the solar wind control of the magnetospheric-ionospheric convection system using dynamical networks. The dynamical networks are first interpolated onto a regular grid. Statistically averaged network responses are then formed for a variety of solar wind conditions, including investigating the network response to southward turnings. [1] Dods, J., S. C. Chapman, and J. W. Gjerloev (2015), Network analysis of geomagnetic substorms using the SuperMAG database of ground-based magnetometer stations, J. Geophys. Res. Space Physics, 120, 7774-7784, doi:10.1002/2015JA021456
a Geometrical Chart of Altered Temporality (and Spatiality)
NASA Astrophysics Data System (ADS)
Saniga, Metod
2005-10-01
The paper presents, to our knowledge, a first fairly comprehensive and mathematically well-underpinned classification of the psychopathology of time (and space). After reviewing the most illustrative first-person accounts of "anomalous/peculiar" experiences of time (and, to a lesser degree, space) we introduce and describe in detail their algebraic geometrical model. The model features six qualitatively different types of the internal structure of time dimension and four types of that of space. As for time, the most pronounced are the ordinary "past-present-future," "present-only" ("eternal/everlasting now") and "no-present" (time "standing still") patterns. Concerning space, the most elementary are the ordinary, i.e., "here-and-there," mode and the "here-only" one ("omnipresence"). We then show what the admissible combinations of temporal and spatial psycho-patterns are and give a rigorous algebraic geometrical classification of them. The predictive power of the model is illustrated by the phenomenon of psychological time-reversal and the experiential difference between time and space. The paper ends with a brief account of some epistemological/ontological questions stemming from the approach.
NASA Astrophysics Data System (ADS)
Langner, Andreas; Miettinen, Jukka; Stibig, Hans-Jurgen
2016-08-01
We use a Normalized Burned Ratio (NBR) differential approach for detecting forest canopy disturbance caused by selective logging in evergreen tropical moist forests of central Cambodia. The general disturbance pattern obtained from Landsat 8 (30 m) imagery is largely compatible to Sentinel-2 (10 m), showing good conformity to high resolution RapidEye reference data. However, the 10 m spatial resolution of Sentinel-2 provides notably higher spatial detail and purer pixel values, increasing the potential for detecting fine and subtle forest canopy changes as indicators for potential forest degradation. We can expect further improvement for detecting short-lived disturbance signals in tropical forest canopies due to an increased revisit frequency (5 days) after the Sentinel-2B launch.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Losey, London M; Andres, Robert Joseph; Marland, Gregg
2006-12-01
Detailed understanding of global carbon cycling requires estimates of CO2 emissions on temporal and spatial scales finer than annual and country. This is the first attempt to derive such estimates for a large, developing, Southern Hemisphere country. Though data on energy use are not complete in terms of time and geography, there are enough data available on the sale or consumption of fuels in Brazil to reasonably approximate the temporal and spatial patterns of fuel use and CO2 emissions. Given the available data, a strong annual cycle in emissions from Brazil is not apparent. CO2 emissions are unevenly distributed withinmore » Brazil as the population density and level of development both vary widely.« less
Spatial pattern of Baccharis platypoda shrub as determined by sex and life stages
NASA Astrophysics Data System (ADS)
Fonseca, Darliana da Costa; de Oliveira, Marcio Leles Romarco; Pereira, Israel Marinho; Gonzaga, Anne Priscila Dias; de Moura, Cristiane Coelho; Machado, Evandro Luiz Mendonça
2017-11-01
Spatial patterns of dioecious species can be determined by their nutritional requirements and intraspecific competition, apart from being a response to environmental heterogeneity. The aim of the study was to evaluate the spatial pattern of populations of a dioecious shrub reporting to sex and reproductive stage patterns of individuals. Sampling was carried out in three areas located in the meridional portion of Serra do Espinhaço, where in individuals of the studied species were mapped. The spatial pattern was determined through O-ring analysis and Ripley's K-function and the distribution of individuals' frequencies was verified through x2 test. Populations in two areas showed an aggregate spatial pattern tending towards random or uniform according to the observed scale. Male and female adults presented an aggregate pattern at smaller scales, while random and uniform patterns were verified above 20 m for individuals of both sexes of the areas A2 and A3. Young individuals presented an aggregate pattern in all areas and spatial independence in relation to adult individuals, especially female plants. The interactions between individuals of both genders presented spatial independence with respect to spatial distribution. Baccharis platypoda showed characteristics in accordance with the spatial distribution of savannic and dioecious species, whereas the population was aggregated tending towards random at greater spatial scales. Young individuals showed an aggregated pattern at different scales compared to adults, without positive association between them. Female and male adult individuals presented similar characteristics, confirming that adult individuals at greater scales are randomly distributed despite their distinct preferences for environments with moisture variation.
Analysis of Spatial Point Patterns in Nuclear Biology
Weston, David J.; Adams, Niall M.; Russell, Richard A.; Stephens, David A.; Freemont, Paul S.
2012-01-01
There is considerable interest in cell biology in determining whether, and to what extent, the spatial arrangement of nuclear objects affects nuclear function. A common approach to address this issue involves analyzing a collection of images produced using some form of fluorescence microscopy. We assume that these images have been successfully pre-processed and a spatial point pattern representation of the objects of interest within the nuclear boundary is available. Typically in these scenarios, the number of objects per nucleus is low, which has consequences on the ability of standard analysis procedures to demonstrate the existence of spatial preference in the pattern. There are broadly two common approaches to look for structure in these spatial point patterns. First a spatial point pattern for each image is analyzed individually, or second a simple normalization is performed and the patterns are aggregated. In this paper we demonstrate using synthetic spatial point patterns drawn from predefined point processes how difficult it is to distinguish a pattern from complete spatial randomness using these techniques and hence how easy it is to miss interesting spatial preferences in the arrangement of nuclear objects. The impact of this problem is also illustrated on data related to the configuration of PML nuclear bodies in mammalian fibroblast cells. PMID:22615822
Charles B. Halpern; Joseph A. Antos; Janine M. Rice; Ryan D. Haugo; Nicole L. Lang
2010-01-01
We combined spatial point pattern analysis, population age structures, and a time-series of stem maps to quantify spatial and temporal patterns of conifer invasion over a 200-yr period in three plots totaling 4 ha. In combination, spatial and temporal patterns of establishment suggest an invasion process shaped by biotic interactions, with facilitation promoting...
Liang, Jia Xin; Li, Xin Ju
2018-02-01
With remote sensing images from 1985, 2000 Lantsat 5 TM and 2015 Lantsat 8 OLI as data sources, we tried to select the suitable research scale and examine the temporal-spatial diffe-rentiation with such scale in the Nansihu Lake wetland by using landscape pattern vulnerability index constructed by sensitivity index and adaptability index, and combined with space statistics such as semivariogram and spatial autocorrelation. The results showed that 1 km × 1 km equidistant grid was the suitable research scale, which could eliminate the influence of spatial heterogeneity induced by random factors. From 1985 to 2015, the landscape pattern vulnerability in the Nansihu Lake wetland deteriorated gradually. The high-risk area of landscape pattern vulnerability dramatically expanded with time. The spatial heterogeneity of landscape pattern vulnerability increased, and the influence of non-structural factors on landscape pattern vulnerability strengthened. Spatial variability affected by spatial autocorrelation slightly weakened. Landscape pattern vulnerability had strong general spatial positive correlation, with the significant form of spatial agglomeration. The positive spatial autocorrelation continued to increase and the phenomenon of spatial concentration was more and more obvious over time. The local autocorrelation mainly based on high-high accumulation zone and low-low accumulation zone had stronger spatial autocorrelation among neighboring space units. The high-high accumulation areas showed the strongest level of significance, and the significant level of low-low accumulation zone increased with time. Natural factors, such as temperature and precipitation, affected water-level and landscape distribution, and thus changed the landscape patterns vulnerability of Nansihu Lake wetland. The dominant driver for the deterioration of landscape patterns vulnerability was human activities, including social economy activity and policy system.
Kim, Jun-Hyun; Gu, Donghwan; Sohn, Wonmin; Kil, Sung-Ho; Kim, Hwanyong; Lee, Dong-Kun
2016-09-02
Rapid urbanization has accelerated land use and land cover changes, and generated the urban heat island effect (UHI). Previous studies have reported positive effects of neighborhood landscapes on mitigating urban surface temperatures. However, the influence of neighborhood landscape spatial patterns on enhancing cooling effects has not yet been fully investigated. The main objective of this study was to assess the relationships between neighborhood landscape spatial patterns and land surface temperatures (LST) by using multi-regression models considering spatial autocorrelation issues. To measure the influence of neighborhood landscape spatial patterns on LST, this study analyzed neighborhood environments of 15,862 single-family houses in Austin, Texas, USA. Using aerial photos, geographic information systems (GIS), and remote sensing, FRAGSTATS was employed to calculate values of several landscape indices used to measure neighborhood landscape spatial patterns. After controlling for the spatial autocorrelation effect, results showed that larger and better-connected landscape spatial patterns were positively correlated with lower LST values in neighborhoods, while more fragmented and isolated neighborhood landscape patterns were negatively related to the reduction of LST.
Kim, Jun-Hyun; Gu, Donghwan; Sohn, Wonmin; Kil, Sung-Ho; Kim, Hwanyong; Lee, Dong-Kun
2016-01-01
Rapid urbanization has accelerated land use and land cover changes, and generated the urban heat island effect (UHI). Previous studies have reported positive effects of neighborhood landscapes on mitigating urban surface temperatures. However, the influence of neighborhood landscape spatial patterns on enhancing cooling effects has not yet been fully investigated. The main objective of this study was to assess the relationships between neighborhood landscape spatial patterns and land surface temperatures (LST) by using multi-regression models considering spatial autocorrelation issues. To measure the influence of neighborhood landscape spatial patterns on LST, this study analyzed neighborhood environments of 15,862 single-family houses in Austin, Texas, USA. Using aerial photos, geographic information systems (GIS), and remote sensing, FRAGSTATS was employed to calculate values of several landscape indices used to measure neighborhood landscape spatial patterns. After controlling for the spatial autocorrelation effect, results showed that larger and better-connected landscape spatial patterns were positively correlated with lower LST values in neighborhoods, while more fragmented and isolated neighborhood landscape patterns were negatively related to the reduction of LST. PMID:27598186
NASA Astrophysics Data System (ADS)
Xiong, C.; Shi, J.; Wang, T.
2017-12-01
Snow and ice is very sensitive to the climate change. Rising air temperature will cause the snowmelt time change. In contrast, the change in snow state will have feedback on climate through snow albedo. The snow melt timing is also correlated with the associated runoff. Ice phenology describes the seasonal cycle of lake ice cover and includes freeze-up and breakup periods and ice cover duration, which is an important weather and climate indicator. It is also important for lake-atmosphere interactions and hydrological and ecological processes. The enhanced resolution (up to 3.125 km) passive microwave data is used to estimate the snowmelt pattern and lake ice phenology on and around Tibetan Plateau. The enhanced resolution makes the estimation of snowmelt and lake ice phenology in more spatial detail compared to previous 25 km gridded passive microwave data. New algorithm based on smooth filters and change point detection was developed to estimate the snowmelt and lake ice freeze-up and break-up timing. Spatial and temporal pattern of snowmelt and lake ice phonology are estimated. This study provides an objective evidence of climate change impact on the cryospheric system on Tibetan Plateau. The results show significant earlier snowmelt and lake ice break-up in some regions.
NASA Astrophysics Data System (ADS)
Li, Yu-Ye; Ding, Xue-Li
2014-12-01
Heterogeneity of the neurons and noise are inevitable in the real neuronal network. In this paper, Gaussian white noise induced spatial patterns including spiral waves and multiple spatial coherence resonances are studied in a network composed of Morris—Lecar neurons with heterogeneity characterized by parameter diversity. The relationship between the resonances and the transitions between ordered spiral waves and disordered spatial patterns are achieved. When parameter diversity is introduced, the maxima of multiple resonances increases first, and then decreases as diversity strength increases, which implies that the coherence degrees induced by noise are enhanced at an intermediate diversity strength. The synchronization degree of spatial patterns including ordered spiral waves and disordered patterns is identified to be a very low level. The results suggest that the nervous system can profit from both heterogeneity and noise, and the multiple spatial coherence resonances are achieved via the emergency of spiral waves instead of synchronization patterns.
Single mode, broad-waveguide ARROW-type semiconductor diode lasers
NASA Astrophysics Data System (ADS)
Al-Muhanna, Abdulrahman Ali
A broad transverse waveguide (low confinement) concept is used to achieve a record-high spatially incoherent cw output power of 11W for InGaAs active devices (λ = 0.97 μm) from 100μm wide-stripe and 2mm-long devices with low internal loss, α1 = 1cm-1, and high characteristic temperatures, T0 = 210K, and T1 = 1800K. A detailed above-threshold analysis reveals that reduction in gain spatial hole burning (GSHB) is possible in ARROW-type structures by using a low transverse confinement factor; consequently, a wider ARROW-core can be utilized. By incorporating both a broad-waveguide concept as well as an asymmetric structure in the transverse direction, and an ARROW-type structure in the lateral direction, a novel single-spatial mode diode laser with improved performance is obtained. Devices with low transverse confinement factor (Γ ~ 1%) and a core-region width of 7.8 μm achieved 510mW single-spatial mode pulsed output power (λ = 0.946 μm) with a full- width at half-maximum (FWHM) of the lateral far-field pattern of 4.7°.
Spatial Patterns of NLCD Land Cover Change Thematic Accuracy (2001 - 2011)
Research on spatial non-stationarity of land cover classification accuracy has been ongoing for over two decades. We extend the understanding of thematic map accuracy spatial patterns by: 1) quantifying spatial patterns of map-reference agreement for class-specific land cover c...
Spatial patterns of close relationships across the lifespan
NASA Astrophysics Data System (ADS)
Jo, Hang-Hyun; Saramäki, Jari; Dunbar, Robin I. M.; Kaski, Kimmo
2014-11-01
The dynamics of close relationships is important for understanding the migration patterns of individual life-courses. The bottom-up approach to this subject by social scientists has been limited by sample size, while the more recent top-down approach using large-scale datasets suffers from a lack of detail about the human individuals. We incorporate the geographic and demographic information of millions of mobile phone users with their communication patterns to study the dynamics of close relationships and its effect in their life-course migration. We demonstrate how the close age- and sex-biased dyadic relationships are correlated with the geographic proximity of the pair of individuals, e.g., young couples tend to live further from each other than old couples. In addition, we find that emotionally closer pairs are living geographically closer to each other. These findings imply that the life-course framework is crucial for understanding the complex dynamics of close relationships and their effect on the migration patterns of human individuals.
Spatial patterns of development drive water use
Sanchez, G.M.; Smith, J.W.; Terando, Adam J.; Sun, G.; Meentemeyer, R.K.
2018-01-01
Water availability is becoming more uncertain as human populations grow, cities expand into rural regions and the climate changes. In this study, we examine the functional relationship between water use and the spatial patterns of developed land across the rapidly growing region of the southeastern United States. We quantified the spatial pattern of developed land within census tract boundaries, including multiple metrics of density and configuration. Through non‐spatial and spatial regression approaches we examined relationships and spatial dependencies between the spatial pattern metrics, socio‐economic and environmental variables and two water use variables: a) domestic water use, and b) total development‐related water use (a combination of public supply, domestic self‐supply and industrial self‐supply). Metrics describing the spatial patterns of development had the highest measure of relative importance (accounting for 53% of model's explanatory power), explaining significantly more variance in water use compared to socio‐economic or environmental variables commonly used to estimate water use. Integrating metrics characterizing the spatial pattern of development into water use models is likely to increase their utility and could facilitate water‐efficient land use planning.
Spatial Patterns of Development Drive Water Use
NASA Astrophysics Data System (ADS)
Sanchez, G. M.; Smith, J. W.; Terando, A.; Sun, G.; Meentemeyer, R. K.
2018-03-01
Water availability is becoming more uncertain as human populations grow, cities expand into rural regions and the climate changes. In this study, we examine the functional relationship between water use and the spatial patterns of developed land across the rapidly growing region of the southeastern United States. We quantified the spatial pattern of developed land within census tract boundaries, including multiple metrics of density and configuration. Through non-spatial and spatial regression approaches we examined relationships and spatial dependencies between the spatial pattern metrics, socio-economic and environmental variables and two water use variables: a) domestic water use, and b) total development-related water use (a combination of public supply, domestic self-supply and industrial self-supply). Metrics describing the spatial patterns of development had the highest measure of relative importance (accounting for 53% of model's explanatory power), explaining significantly more variance in water use compared to socio-economic or environmental variables commonly used to estimate water use. Integrating metrics characterizing the spatial pattern of development into water use models is likely to increase their utility and could facilitate water-efficient land use planning.
FracPaQ: a MATLAB™ toolbox for the quantification of fracture patterns
NASA Astrophysics Data System (ADS)
Healy, David; Rizzo, Roberto; Farrell, Natalie; Watkins, Hannah; Cornwell, David; Gomez-Rivas, Enrique; Timms, Nick
2017-04-01
The patterns of fractures in deformed rocks are rarely uniform or random. Fracture orientations, sizes, shapes and spatial distributions often exhibit some kind of order. In detail, there may be relationships among the different fracture attributes e.g. small fractures dominated by one orientation, larger fractures by another. These relationships are important because the mechanical (e.g. strength, anisotropy) and transport (e.g. fluids, heat) properties of rock depend on these fracture patterns and fracture attributes. This presentation describes an open source toolbox to quantify fracture patterns, including distributions in fracture attributes and their spatial variation. Software has been developed to quantify fracture patterns from 2-D digital images, such as thin section micrographs, geological maps, outcrop or aerial photographs or satellite images. The toolbox comprises a suite of MATLAB™ scripts based on published quantitative methods for the analysis of fracture attributes: orientations, lengths, intensity, density and connectivity. An estimate of permeability in 2-D is made using a parallel plate model. The software provides an objective and consistent methodology for quantifying fracture patterns and their variations in 2-D across a wide range of length scales. Our current focus for the application of the software is on quantifying crack and fracture patterns in and around fault zones. There is a large body of published work on the quantification of relatively simple joint patterns, but fault zones present a bigger, and arguably more important, challenge. The methods presented are inherently scale independent, and a key task will be to analyse and integrate quantitative fracture pattern data from micro- to macro-scales. New features in this release include multi-scale analyses based on a wavelet method to look for scale transitions, support for multi-colour traces in the input file processed as separate fracture sets, and combining fracture traces from multiple 2-D images to derive the statistically equivalent 3-D fracture pattern expressed as a 2nd rank crack tensor.
A framework for the identification of long-term social avoidance in longitudinal datasets
Levengood, Alexis; Foroughirad, Vivienne; Mann, Janet; Krzyszczyk, Ewa
2017-01-01
Animal sociality is of significant interest to evolutionary and behavioural ecologists, with efforts focused on the patterns, causes and fitness outcomes of social preference. However, individual social patterns are the consequence of both attraction to (preference for) and avoidance of conspecifics. Despite this, social avoidance has received far less attention than social preference. Here, we detail the necessary steps to generate a spatially explicit, iterative null model which can be used to identify non-random social avoidance in longitudinal studies of social animals. We specifically identify and detail parameters which will influence the validity of the model. To test the usability of this model, we applied it to two longitudinal studies of social animals (Eastern water dragons (Intellegama lesueurii) and bottlenose dolphins (Tursiops aduncus)) to identify the presence of social avoidances. Using this model allowed us to identify the presence of social avoidances in both species. We hope that the framework presented here inspires interest in addressing this critical gap in our understanding of animal sociality, in turn allowing for a more holistic understanding of social interactions, relationships and structure. PMID:28879006
A framework for the identification of long-term social avoidance in longitudinal datasets.
Strickland, Kasha; Levengood, Alexis; Foroughirad, Vivienne; Mann, Janet; Krzyszczyk, Ewa; Frère, Celine H
2017-08-01
Animal sociality is of significant interest to evolutionary and behavioural ecologists, with efforts focused on the patterns, causes and fitness outcomes of social preference. However, individual social patterns are the consequence of both attraction to (preference for) and avoidance of conspecifics. Despite this, social avoidance has received far less attention than social preference. Here, we detail the necessary steps to generate a spatially explicit, iterative null model which can be used to identify non-random social avoidance in longitudinal studies of social animals. We specifically identify and detail parameters which will influence the validity of the model. To test the usability of this model, we applied it to two longitudinal studies of social animals (Eastern water dragons ( Intellegama lesueurii ) and bottlenose dolphins ( Tursiops aduncus )) to identify the presence of social avoidances. Using this model allowed us to identify the presence of social avoidances in both species. We hope that the framework presented here inspires interest in addressing this critical gap in our understanding of animal sociality, in turn allowing for a more holistic understanding of social interactions, relationships and structure.
Spatial/Temporal Variations of Crime: A Routine Activity Theory Perspective.
de Melo, Silas Nogueira; Pereira, Débora V S; Andresen, Martin A; Matias, Lindon Fonseca
2018-05-01
Temporal and spatial patterns of crime in Campinas, Brazil, are analyzed considering the relevance of routine activity theory in a Latin American context. We use geo-referenced criminal event data, 2010-2013, analyzing spatial patterns using census tracts and temporal patterns considering seasons, months, days, and hours. Our analyses include difference in means tests, count-based regression models, and Kulldorff's scan test. We find that crime in Campinas, Brazil, exhibits both temporal and spatial-temporal patterns. However, the presence of these patterns at the different temporal scales varies by crime type. Specifically, not all crime types have statistically significant temporal patterns at all scales of analysis. As such, routine activity theory works well to explain temporal and spatial-temporal patterns of crime in Campinas, Brazil. However, local knowledge of Brazilian culture is necessary for understanding a portion of these crime patterns.
Yagi, Shunya; Chow, Carmen; Lieblich, Stephanie E; Galea, Liisa A M
2016-01-01
Adult neurogenesis in the dentate gyrus (DG) plays a crucial role for pattern separation, and there are sex differences in the regulation of neurogenesis. Although sex differences, favoring males, in spatial navigation have been reported, it is not known whether there are sex differences in pattern separation. The current study was designed to determine whether there are sex differences in the ability for separating similar or distinct patterns, learning strategy choice, adult neurogenesis, and immediate early gene (IEG) expression in the DG in response to pattern separation training. Male and female Sprague-Dawley rats received a single injection of the DNA synthesis marker, bromodeoxyuridine (BrdU), and were tested for the ability of separating spatial patterns in a spatial pattern separation version of delayed nonmatching to place task using the eight-arm radial arm maze. Twenty-seven days following BrdU injection, rats received a probe trial to determine whether they were idiothetic or spatial strategy users. We found that male spatial strategy users outperformed female spatial strategy users only when separating similar, but not distinct, patterns. Furthermore, male spatial strategy users had greater neurogenesis in response to pattern separation training than all other groups. Interestingly, neurogenesis was positively correlated with performance on similar pattern trials during pattern separation in female spatial strategy users but negatively correlated with performance in male idiothetic strategy users. These results suggest that the survival of new neurons may play an important positive role for pattern separation of similar patterns in females. Furthermore, we found sex and strategy differences in IEG expression in the CA1 and CA3 regions in response to pattern separation. These findings emphasize the importance of studying biological sex on hippocampal function and neural plasticity. © 2015 Wiley Periodicals, Inc.
Variation in Orthologous Shell-Forming Proteins Contribute to Molluscan Shell Diversity
Jackson, Daniel J.; Reim, Laurin; Randow, Clemens; Cerveau, Nicolas; Degnan, Bernard M.; Fleck, Claudia
2017-01-01
Abstract Despite the evolutionary success and ancient heritage of the molluscan shell, little is known about the molecular details of its formation, evolutionary origins, or the interactions between the material properties of the shell and its organic constituents. In contrast to this dearth of information, a growing collection of molluscan shell-forming proteomes and transcriptomes suggest they are comprised of both deeply conserved, and lineage specific elements. Analyses of these sequence data sets have suggested that mechanisms such as exon shuffling, gene co-option, and gene family expansion facilitated the rapid evolution of shell-forming proteomes and supported the diversification of this phylum specific structure. In order to further investigate and test these ideas we have examined the molecular features and spatial expression patterns of two shell-forming genes (Lustrin and ML1A2) and coupled these observations with materials properties measurements of shells from a group of closely related gastropods (abalone). We find that the prominent “GS” domain of Lustrin, a domain believed to confer elastomeric properties to the shell, varies significantly in length between the species we investigated. Furthermore, the spatial expression patterns of Lustrin and ML1A2 also vary significantly between species, suggesting that both protein architecture, and the regulation of spatial gene expression patterns, are important drivers of molluscan shell evolution. Variation in these molecular features might relate to certain materials properties of the shells of these species. These insights reveal an important and underappreciated source of variation within shell-forming proteomes that must contribute to the diversity of molluscan shell phenotypes. PMID:28961798
Kleinmann, Joachim U; Wang, Magnus
2017-09-01
Spatial behavior is of crucial importance for the risk assessment of pesticides and for the assessment of effects of agricultural practice or multiple stressors, because it determines field use, exposition, and recovery. Recently, population models have increasingly been used to understand the mechanisms driving risk and recovery or to conduct landscape-level risk assessments. To include spatial behavior appropriately in population models for use in risk assessments, a new method, "probabilistic walk," was developed, which simulates the detailed daily movement of individuals by taking into account food resources, vegetation cover, and the presence of conspecifics. At each movement step, animals decide where to move next based on probabilities being determined from this information. The model was parameterized to simulate populations of brown hares (Lepus europaeus). A detailed validation of the model demonstrated that it can realistically reproduce various natural patterns of brown hare ecology and behavior. Simulated proportions of time animals spent in fields (PT values) were also comparable to field observations. It is shown that these important parameters for the risk assessment may, however, vary in different landscapes. The results demonstrate the value of using population models to reduce uncertainties in risk assessment and to better understand which factors determine risk in a landscape context. Environ Toxicol Chem 2017;36:2299-2307. © 2017 SETAC. © 2017 SETAC.
Spatial and Temporal Trends of Global Pollination Benefit
Lautenbach, Sven; Seppelt, Ralf; Liebscher, Juliane; Dormann, Carsten F.
2012-01-01
Pollination is a well-studied and at the same time a threatened ecosystem service. A significant part of global crop production depends on or profits from pollination by animals. Using detailed information on global crop yields of 60 pollination dependent or profiting crops, we provide a map of global pollination benefits on a 5′ by 5′ latitude-longitude grid. The current spatial pattern of pollination benefits is only partly correlated with climate variables and the distribution of cropland. The resulting map of pollination benefits identifies hot spots of pollination benefits at sufficient detail to guide political decisions on where to protect pollination services by investing in structural diversity of land use. Additionally, we investigated the vulnerability of the national economies with respect to potential decline of pollination services as the portion of the (agricultural) economy depending on pollination benefits. While the general dependency of the agricultural economy on pollination seems to be stable from 1993 until 2009, we see increases in producer prices for pollination dependent crops, which we interpret as an early warning signal for a conflict between pollination service and other land uses at the global scale. Our spatially explicit analysis of global pollination benefit points to hot spots for the generation of pollination benefits and can serve as a base for further planning of land use, protection sites and agricultural policies for maintaining pollination services. PMID:22563427
DOE Office of Scientific and Technical Information (OSTI.GOV)
Haralalka, Shruti; Abmayr, Susan M., E-mail: sma@stowers.org; Department of Anatomy and Cell Biology, University of Kansas Medical Center, Kansas City, MO 66160
2010-11-01
The body wall musculature of a Drosophila larva is composed of an intricate pattern of 30 segmentally repeated muscle fibers in each abdominal hemisegment. Each muscle fiber has unique spatial and behavioral characteristics that include its location, orientation, epidermal attachment, size and pattern of innervation. Many, if not all, of these properties are dictated by founder cells, which determine the muscle pattern and seed the fusion process. Myofibers are then derived from fusion between a specific founder cell and several fusion competent myoblasts (FCMs) fusing with as few as 3-5 FCMs in the small muscles on the most ventral sidemore » of the embryo and as many as 30 FCMs in the larger muscles on the dorsal side of the embryo. The focus of the present review is the formation of the larval muscles in the developing embryo, summarizing the major issues and players in this process. We have attempted to emphasize experimentally-validated details of the mechanism of myoblast fusion and distinguish these from the theoretically possible details that have not yet been confirmed experimentally. We also direct the interested reader to other recent reviews that discuss myoblast fusion in Drosophila, each with their own perspective on the process . With apologies, we use gene nomenclature as specified by Flybase (http://flybase.org) but provide Table 1 with alternative names and references.« less
Virtual Human Analogs to Rodent Spatial Pattern Separation and Completion Memory Tasks
ERIC Educational Resources Information Center
Paleja, Meera; Girard, Todd A.; Christensen, Bruce K.
2011-01-01
Spatial pattern separation (SPS) and spatial pattern completion (SPC) have played an increasingly important role in computational and rodent literatures as processes underlying associative memory. SPS and SPC are complementary processes, allowing the formation of unique representations and the reconstruction of complete spatial environments based…
Yitbarek, Senay; Vandermeer, John H; Allen, David
2011-10-01
Spatial patterns observed in ecosystems have traditionally been attributed to exogenous processes. Recently, ecologists have found that endogenous processes also have the potential to create spatial patterns. Yet, relatively few studies have attempted to examine the combined effects of exogenous and endogenous processes on the distribution of organisms across spatial and temporal scales. Here we aim to do this, by investigating whether spatial patterns of under-story tree species at a large spatial scale (18 ha) influences the spatial patterns of ground foraging ant species at a much smaller spatial scale (20 m by 20 m). At the regional scale, exogenous processes (under-story tree community) had a strong effect on the spatial patterns in the ground-foraging ant community. We found significantly more Camponotus noveboracensis, Formica subsericae, and Lasius alienus species in black cherry (Prunis serotine Ehrh.) habitats. In witch-hazel (Hamamelis virginiana L.) habitats, we similarly found significantly more Myrmica americana, Formica fusca, and Formica subsericae. At smaller spatial scales, we observed the emergence of mosaic ant patches changing rapidly in space and time. Our study reveals that spatial patterns are the result of both exogenous and endogenous forces, operating at distinct scales.
MPGD for breast cancer prevention: a high resolution and low dose radiation medical imaging
NASA Astrophysics Data System (ADS)
Gutierrez, R. M.; Cerquera, E. A.; Mañana, G.
2012-07-01
Early detection of small calcifications in mammograms is considered the best preventive tool of breast cancer. However, existing digital mammography with relatively low radiation skin exposure has limited accessibility and insufficient spatial resolution for small calcification detection. Micro Pattern Gaseous Detectors (MPGD) and associated technologies, increasingly provide new information useful to generate images of microscopic structures and make more accessible cutting edge technology for medical imaging and many other applications. In this work we foresee and develop an application for the new information provided by a MPGD camera in the form of highly controlled images with high dynamical resolution. We present a new Super Detail Image (S-DI) that efficiently profits of this new information provided by the MPGD camera to obtain very high spatial resolution images. Therefore, the method presented in this work shows that the MPGD camera with SD-I, can produce mammograms with the necessary spatial resolution to detect microcalcifications. It would substantially increase efficiency and accessibility of screening mammography to highly improve breast cancer prevention.
Estimating Vegetation Structure in African Savannas using High Spatial Resolution Imagery
NASA Astrophysics Data System (ADS)
Axelsson, C.; Hanan, N. P.
2016-12-01
High spatial resolution satellite imagery allows for detailed mapping of trees in savanna landscapes, including estimates of woody cover, tree densities, crown sizes, and the spatial pattern of trees. By linking these vegetation parameters to rainfall and soil properties we gain knowledge of how the local environment influences vegetation. A thorough understanding of the underlying ecosystem processes is key to assessing the future productivity and stability of these ecosystems. In this study, we have processed and analyzed hundreds of sites sampled from African savannas across a wide range of rainfall and soil conditions. The vegetation at each site is classified using unsupervised classification with manual assignment into woody, herbaceous and bare cover classes. A crown delineation method further divides the woody areas into individual tree crowns. The results show that rainfall, soil, and topography interactively influence vegetation structure. We see that both total rainfall and rainfall seasonality play important roles and that soil type influences woody cover and the sizes of tree crowns.
Spatial context learning survives interference from working memory load
Vickery, Timothy J.; Sussman, Rachel S.; Jiang, Yuhong V.
2010-01-01
The human visual system is constantly confronted with an overwhelming amount of information, only a subset of which can be processed in complete detail. Attention and implicit learning are two important mechanisms that optimize vision. This study addresses the relationship between these two mechanisms. Specifically we ask: Is implicit learning of spatial context affected by the amount of working memory load devoted to an irrelevant task? We tested observers in visual search tasks where search displays occasionally repeated. Observers became faster searching repeated displays than unrepeated ones, showing contextual cueing. We found that the size of contextual cueing was unaffected by whether observers learned repeated displays under unitary attention or when their attention was divided using working memory manipulations. These results held when working memory was loaded by colors, dot patterns, individual dot locations, or multiple potential targets. We conclude that spatial context learning is robust to interference from manipulations that limit the availability of attention and working memory. PMID:20853996
NASA Astrophysics Data System (ADS)
Schmitt, R. J. P.; Bizzi, S.; Kondolf, G. M.; Rubin, Z.; Castelletti, A.
2016-12-01
Field and laboratory evidence indicates that the spatial distribution of transport in both alluvial and bedrock rivers is an adaptation to sediment supply. Sediment supply, in turn, depends on spatial distribution and properties (e.g., grain sizes and supply rates) of individual sediment sources. Analyzing the distribution of transport capacity in a river network could hence clarify the spatial distribution and properties of sediment sources. Yet, challenges include a) identifying magnitude and spatial distribution of transport capacity for each of multiple grain sizes being simultaneously transported, and b) estimating source grain sizes and supply rates, both at network scales. Herein, we approach the problem of identifying the spatial distribution of sediment sources and the resulting network sediment fluxes in a major, poorly monitored tributary (80,000 km2) of the Mekong. Therefore, we apply the CASCADE modeling framework (Schmitt et al. (2016)). CASCADE calculates transport capacities and sediment fluxes for multiple grainsizes on the network scale based on remotely-sensed morphology and modelled hydrology. CASCADE is run in an inverse Monte Carlo approach for 7500 random initializations of source grain sizes. In all runs, supply of each source is inferred from the minimum downstream transport capacity for the source grain size. Results for each realization are compared to sparse available sedimentary records. Only 1 % of initializations reproduced the sedimentary record. Results for these realizations revealed a spatial pattern in source supply rates, grain sizes, and network sediment fluxes that correlated well with map-derived patterns in lithology and river-morphology. Hence, we propose that observable river hydro-morphology contains information on upstream source properties that can be back-calculated using an inverse modeling approach. Such an approach could be coupled to more detailed models of hillslope processes in future to derive integrated models of hillslope production and fluvial transport processes, which is particularly useful to identify sediment provenance in poorly monitored river basins.
Stochastic population dynamics in spatially extended predator-prey systems
NASA Astrophysics Data System (ADS)
Dobramysl, Ulrich; Mobilia, Mauro; Pleimling, Michel; Täuber, Uwe C.
2018-02-01
Spatially extended population dynamics models that incorporate demographic noise serve as case studies for the crucial role of fluctuations and correlations in biological systems. Numerical and analytic tools from non-equilibrium statistical physics capture the stochastic kinetics of these complex interacting many-particle systems beyond rate equation approximations. Including spatial structure and stochastic noise in models for predator-prey competition invalidates the neutral Lotka-Volterra population cycles. Stochastic models yield long-lived erratic oscillations stemming from a resonant amplification mechanism. Spatially extended predator-prey systems display noise-stabilized activity fronts that generate persistent correlations. Fluctuation-induced renormalizations of the oscillation parameters can be analyzed perturbatively via a Doi-Peliti field theory mapping of the master equation; related tools allow detailed characterization of extinction pathways. The critical steady-state and non-equilibrium relaxation dynamics at the predator extinction threshold are governed by the directed percolation universality class. Spatial predation rate variability results in more localized clusters, enhancing both competing species’ population densities. Affixing variable interaction rates to individual particles and allowing for trait inheritance subject to mutations induces fast evolutionary dynamics for the rate distributions. Stochastic spatial variants of three-species competition with ‘rock-paper-scissors’ interactions metaphorically describe cyclic dominance. These models illustrate intimate connections between population dynamics and evolutionary game theory, underscore the role of fluctuations to drive populations toward extinction, and demonstrate how space can support species diversity. Two-dimensional cyclic three-species May-Leonard models are characterized by the emergence of spiraling patterns whose properties are elucidated by a mapping onto a complex Ginzburg-Landau equation. Multiple-species extensions to general ‘food networks’ can be classified on the mean-field level, providing both fundamental understanding of ensuing cooperativity and profound insight into the rich spatio-temporal features and coarsening kinetics in the corresponding spatially extended systems. Novel space-time patterns emerge as a result of the formation of competing alliances; e.g. coarsening domains that each incorporate rock-paper-scissors competition games.
IPUMS: Detailed global data on population characteristics
NASA Astrophysics Data System (ADS)
Kugler, T.
2017-12-01
Many new and exciting sources of data on human population distributions based on remote sensing, mobile technology, and other mechanisms are becoming available. These new data sources often provide fine scale spatial and/or temporal resolution. However, they typically focus on the location of population, with little or no information on population characteristics. The large and growing collection of data available through the IPUMS family of products complements datasets that provide spatial and temporal detail but little attribute detail by providing the full depth of characteristics covered by population censuses, including demographic, household structure, economic, employment, education, and housing characteristics. IPUMS International provides census microdata for 85 countries. Microdata provide the responses to every census question for each individual in a sample of households. Microdata identify the sub-national geographic unit in which a household is located, but for confidentiality reasons, identified units must include a minimum population, typically 20,000 people. Small-area aggregate data often describe much smaller geographic units, enabling study of detailed spatial patterns of population characteristics. However the structure of aggregate data tables is highly heterogeneous across countries, census years, and even topics within a given census, making these data difficult to work with in any systematic way. A recently funded project will assemble small-area aggregate population and agricultural census data published by national statistical offices. Through preliminary work collecting and cataloging over 10,000 tables, we have identified a small number of structural families that can be used to organize the many different structures. These structural families will form the basis for software tools to document and standardize the tables for ingest into a common database. Both the microdata and aggregate data are made available through IPUMS Terra, facilitating integration with land use, land cover, climate, and other environmental data. These data can be used to address pressing global challenges, such as food and water security, development and deforestation, and environmentally-influenced migration.
Influence of the tilt angle of Percutaneous Aortic Prosthesis on Velocity and Shear Stress Fields
Gomes, Bruno Alvares de Azevedo; Camargo, Gabriel Cordeiro; dos Santos, Jorge Roberto Lopes; Azevedo, Luis Fernando Alzuguir; Nieckele, Ângela Ourivio; Siqueira-Filho, Aristarco Gonçalves; de Oliveira, Glaucia Maria Moraes
2017-01-01
Background Due to the nature of the percutaneous prosthesis deployment process, a variation in its final position is expected. Prosthetic valve placement will define the spatial location of its effective orifice in relation to the aortic annulus. The blood flow pattern in the ascending aorta is related to the aortic remodeling process, and depends on the spatial location of the effective orifice. The hemodynamic effect of small variations in the angle of inclination of the effective orifice has not been studied in detail. Objective To implement an in vitro simulation to characterize the hydrodynamic blood flow pattern associated with small variations in the effective orifice inclination. Methods A three-dimensional aortic phantom was constructed, reproducing the anatomy of one patient submitted to percutaneous aortic valve implantation. Flow analysis was performed by use of the Particle Image Velocimetry technique. The flow pattern in the ascending aorta was characterized for six flow rate levels. In addition, six angles of inclination of the effective orifice were assessed. Results The effective orifice at the -4º and -2º angles directed the main flow towards the anterior wall of the aortic model, inducing asymmetric and high shear stress in that region. However, the effective orifice at the +3º and +5º angles mimics the physiological pattern, centralizing the main flow and promoting a symmetric distribution of shear stress. Conclusion The measurements performed suggest that small changes in the angle of inclination of the percutaneous prosthesis aid in the generation of a physiological hemodynamic pattern, and can contribute to reduce aortic remodeling. PMID:28793046
Spatial Pattern of Standing Timber Value across the Brazilian Amazon
Ahmed, Sadia E.; Ewers, Robert M.
2012-01-01
The Amazon is a globally important system, providing a host of ecosystem services from climate regulation to food sources. It is also home to a quarter of all global diversity. Large swathes of forest are removed each year, and many models have attempted to predict the spatial patterns of this forest loss. The spatial patterns of deforestation are determined largely by the patterns of roads that open access to frontier areas and expansion of the road network in the Amazon is largely determined by profit seeking logging activities. Here we present predictions for the spatial distribution of standing value of timber across the Amazon. We show that the patterns of timber value reflect large-scale ecological gradients, determining the spatial distribution of functional traits of trees which are, in turn, correlated with timber values. We expect that understanding the spatial patterns of timber value across the Amazon will aid predictions of logging movements and thus predictions of potential future road developments. These predictions in turn will be of great use in estimating the spatial patterns of deforestation in this globally important biome. PMID:22590520
Numerical investigation of aggregated fuel spatial pattern impacts on fire behavior
Parsons, Russell A.; Linn, Rodman Ray; Pimont, Francois; ...
2017-06-18
Here, landscape heterogeneity shapes species distributions, interactions, and fluctuations. Historically, in dry forest ecosystems, low canopy cover and heterogeneous fuel patterns often moderated disturbances like fire. Over the last century, however, increases in canopy cover and more homogeneous patterns have contributed to altered fire regimes with higher fire severity. Fire management strategies emphasize increasing within-stand heterogeneity with aggregated fuel patterns to alter potential fire behavior. Yet, little is known about how such patterns may affect fire behavior, or how sensitive fire behavior changes from fuel patterns are to winds and canopy cover. Here, we used a physics-based fire behavior model,more » FIRETEC, to explore the impacts of spatially aggregated fuel patterns on the mean and variability of stand-level fire behavior, and to test sensitivity of these effects to wind and canopy cover. Qualitative and quantitative approaches suggest that spatial fuel patterns can significantly affect fire behavior. Based on our results we propose three hypotheses: (1) aggregated spatial fuel patterns primarily affect fire behavior by increasing variability; (2) this variability should increase with spatial scale of aggregation; and (3) fire behavior sensitivity to spatial pattern effects should be more pronounced under moderate wind and fuel conditions.« less
Numerical investigation of aggregated fuel spatial pattern impacts on fire behavior
DOE Office of Scientific and Technical Information (OSTI.GOV)
Parsons, Russell A.; Linn, Rodman Ray; Pimont, Francois
Here, landscape heterogeneity shapes species distributions, interactions, and fluctuations. Historically, in dry forest ecosystems, low canopy cover and heterogeneous fuel patterns often moderated disturbances like fire. Over the last century, however, increases in canopy cover and more homogeneous patterns have contributed to altered fire regimes with higher fire severity. Fire management strategies emphasize increasing within-stand heterogeneity with aggregated fuel patterns to alter potential fire behavior. Yet, little is known about how such patterns may affect fire behavior, or how sensitive fire behavior changes from fuel patterns are to winds and canopy cover. Here, we used a physics-based fire behavior model,more » FIRETEC, to explore the impacts of spatially aggregated fuel patterns on the mean and variability of stand-level fire behavior, and to test sensitivity of these effects to wind and canopy cover. Qualitative and quantitative approaches suggest that spatial fuel patterns can significantly affect fire behavior. Based on our results we propose three hypotheses: (1) aggregated spatial fuel patterns primarily affect fire behavior by increasing variability; (2) this variability should increase with spatial scale of aggregation; and (3) fire behavior sensitivity to spatial pattern effects should be more pronounced under moderate wind and fuel conditions.« less
Spatial patterns of recreational impact on experimental campsites
David N. Cole; Christopher A. Monz
2004-01-01
Management of camping impacts in protected areas worldwide is limited by inadequate understanding of spatial patterns of impact and attention to spatial management strategies. Spatial patterns of campsite impact were studied in two subalpine plant communities in the Wind River Mountains, Wyoming, USA (a forest and a meadow). Response to chronic disturbance and recovery...
Detecting Spatial Patterns of Natural Hazards from the Wikipedia Knowledge Base
NASA Astrophysics Data System (ADS)
Fan, J.; Stewart, K.
2015-07-01
The Wikipedia database is a data source of immense richness and variety. Included in this database are thousands of geotagged articles, including, for example, almost real-time updates on current and historic natural hazards. This includes usercontributed information about the location of natural hazards, the extent of the disasters, and many details relating to response, impact, and recovery. In this research, a computational framework is proposed to detect spatial patterns of natural hazards from the Wikipedia database by combining topic modeling methods with spatial analysis techniques. The computation is performed on the Neon Cluster, a high performance-computing cluster at the University of Iowa. This work uses wildfires as the exemplar hazard, but this framework is easily generalizable to other types of hazards, such as hurricanes or flooding. Latent Dirichlet Allocation (LDA) modeling is first employed to train the entire English Wikipedia dump, transforming the database dump into a 500-dimension topic model. Over 230,000 geo-tagged articles are then extracted from the Wikipedia database, spatially covering the contiguous United States. The geo-tagged articles are converted into an LDA topic space based on the topic model, with each article being represented as a weighted multidimension topic vector. By treating each article's topic vector as an observed point in geographic space, a probability surface is calculated for each of the topics. In this work, Wikipedia articles about wildfires are extracted from the Wikipedia database, forming a wildfire corpus and creating a basis for the topic vector analysis. The spatial distribution of wildfire outbreaks in the US is estimated by calculating the weighted sum of the topic probability surfaces using a map algebra approach, and mapped using GIS. To provide an evaluation of the approach, the estimation is compared to wildfire hazard potential maps created by the USDA Forest service.
Timsuksai, Pijika; Rambo, A Terry
2016-01-01
Different ethnic groups have evolved distinctive cultural models which guide their interactions with the environment, including their agroecosystems. Although it is probable that variations in the structures of homegardens among separate ethnic groups reflect differences in the cultural models of the farmers, empirical support for this assumption is limited. In this paper the modal horizontal structural patterns of the homegardens of 8 ethnic groups in Northeast Thailand and Vietnam are described. Six of these groups (5 speaking Tai languages and 1 speaking Vietnamese) live in close proximity to each other in separate villages in Northeast Thailand, and 2 of the groups (one Tai-speaking and one Vietnamese-speaking) live in different parts of Vietnam. Detailed information on the horizontal structure of homegardens was collected from samples of households belonging to each group. Although each ethnic group has a somewhat distinctive modal structure, the groups cluster into 2 different types. The Tai speaking Cao Lan, Kalaeng, Lao, Nyaw, and Yoy make up Type I while both of the Vietnamese groups, along with the Tai speaking Phu Thai, belong to Type II. Type I gardens have predominantly organic shapes, indeterminate boundaries, polycentric planting patterns, and multi-species composition within planting areas. Type II homegardens have geometric shapes, sharp boundaries, lineal planting patterns, and mono-species composition of planting areas. That the homegardens of most of the Tai ethnic groups share a relatively similar horizontal structural pattern that is quite different from the pattern shared by both of the Vietnamese groups suggests that the spatial layout of homegardens is strongly influenced by their different cultural models.
2016-01-01
Different ethnic groups have evolved distinctive cultural models which guide their interactions with the environment, including their agroecosystems. Although it is probable that variations in the structures of homegardens among separate ethnic groups reflect differences in the cultural models of the farmers, empirical support for this assumption is limited. In this paper the modal horizontal structural patterns of the homegardens of 8 ethnic groups in Northeast Thailand and Vietnam are described. Six of these groups (5 speaking Tai languages and 1 speaking Vietnamese) live in close proximity to each other in separate villages in Northeast Thailand, and 2 of the groups (one Tai-speaking and one Vietnamese-speaking) live in different parts of Vietnam. Detailed information on the horizontal structure of homegardens was collected from samples of households belonging to each group. Although each ethnic group has a somewhat distinctive modal structure, the groups cluster into 2 different types. The Tai speaking Cao Lan, Kalaeng, Lao, Nyaw, and Yoy make up Type I while both of the Vietnamese groups, along with the Tai speaking Phu Thai, belong to Type II. Type I gardens have predominantly organic shapes, indeterminate boundaries, polycentric planting patterns, and multi-species composition within planting areas. Type II homegardens have geometric shapes, sharp boundaries, lineal planting patterns, and mono-species composition of planting areas. That the homegardens of most of the Tai ethnic groups share a relatively similar horizontal structural pattern that is quite different from the pattern shared by both of the Vietnamese groups suggests that the spatial layout of homegardens is strongly influenced by their different cultural models. PMID:26752564
Mapping sleeping bees within their nest: spatial and temporal analysis of worker honey bee sleep.
Klein, Barrett Anthony; Stiegler, Martin; Klein, Arno; Tautz, Jürgen
2014-01-01
Patterns of behavior within societies have long been visualized and interpreted using maps. Mapping the occurrence of sleep across individuals within a society could offer clues as to functional aspects of sleep. In spite of this, a detailed spatial analysis of sleep has never been conducted on an invertebrate society. We introduce the concept of mapping sleep across an insect society, and provide an empirical example, mapping sleep patterns within colonies of European honey bees (Apis mellifera L.). Honey bees face variables such as temperature and position of resources within their colony's nest that may impact their sleep. We mapped sleep behavior and temperature of worker bees and produced maps of their nest's comb contents as the colony grew and contents changed. By following marked bees, we discovered that individuals slept in many locations, but bees of different worker castes slept in different areas of the nest relative to position of the brood and surrounding temperature. Older worker bees generally slept outside cells, closer to the perimeter of the nest, in colder regions, and away from uncapped brood. Younger worker bees generally slept inside cells and closer to the center of the nest, and spent more time asleep than awake when surrounded by uncapped brood. The average surface temperature of sleeping foragers was lower than the surface temperature of their surroundings, offering a possible indicator of sleep for this caste. We propose mechanisms that could generate caste-dependent sleep patterns and discuss functional significance of these patterns.
Shifting patterns of ENSO variability from a 492-year South Pacific coral core
NASA Astrophysics Data System (ADS)
Tangri, N.; Linsley, B. K.; Mucciarone, D.; Dunbar, R. B.
2017-12-01
Anticipating the impacts of ENSO in a changing climate requires detailed reconstructions of changes in its timing, amplitude, and spatial pattern, as well as attempts to attribute those changes to external forcing or internal variability. A continuous coral δ18O record from American Samoa, in the tropical South Pacific, sheds light on almost five centuries of these changes. We find evidence of internally-driven 50-100 year cycles with broad peaks of high variability punctuated by short transitions of low variability. We see a long, slow trend towards more frequent ENSO events, punctuated by sharp decreases in frequency; the 20th century in particular shows a strong trend towards higher-frequency ENSO. Due to the unique location of American Samoa with respect to ENSO sea surface temperature (SST) anomalies, we infer changes in the spatial pattern of ENSO. American Samoa currently lies on the ENSO 3.4 nodal line - the boomerang shape that separates waters warmed by El Niño from those that cool. Closer examination reveals that SST around American Samoa displays opposing responses to Eastern and Central Pacific ENSO events. However, this has not always been the case; in the late 19th and early 20th century, SST responded similarly to both flavors of ENSO. We interpret this to mean a geographic narrowing towards the equator of the eastern Pacific El Niño SST anomaly pattern in the first half of the 20th century.
Zhuang, Xiaowei; Walsh, Ryan R; Sreenivasan, Karthik; Yang, Zhengshi; Mishra, Virendra; Cordes, Dietmar
2018-05-15
The dynamics of the brain's intrinsic networks have been recently studied using co-activation pattern (CAP) analysis. The CAP method relies on few model assumptions and CAP-based measurements provide quantitative information of network temporal dynamics. One limitation of existing CAP-related methods is that the computed CAPs share considerable spatial overlap that may or may not be functionally distinct relative to specific network dynamics. To more accurately describe network dynamics with spatially distinct CAPs, and to compare network dynamics between different populations, a novel data-driven CAP group analysis method is proposed in this study. In the proposed method, a dominant-CAP (d-CAP) set is synthesized across CAPs from multiple clustering runs for each group with the constraint of low spatial similarities among d-CAPs. Alternating d-CAPs with less overlapping spatial patterns can better capture overall network dynamics. The number of d-CAPs, the temporal fraction and spatial consistency of each d-CAP, and the subject-specific switching probability among all d-CAPs are then calculated for each group and used to compare network dynamics between groups. The spatial dissimilarities among d-CAPs computed with the proposed method were first demonstrated using simulated data. High consistency between simulated ground-truth and computed d-CAPs was achieved, and detailed comparisons between the proposed method and existing CAP-based methods were conducted using simulated data. In an effort to physiologically validate the proposed technique and investigate network dynamics in a relevant brain network disorder, the proposed method was then applied to data from the Parkinson's Progression Markers Initiative (PPMI) database to compare the network dynamics in Parkinson's disease (PD) and normal control (NC) groups. Fewer d-CAPs, skewed distribution of temporal fractions of d-CAPs, and reduced switching probabilities among final d-CAPs were found in most networks in the PD group, as compared to the NC group. Furthermore, an overall negative association between switching probability among d-CAPs and disease severity was observed in most networks in the PD group as well. These results expand upon previous findings from in vivo electrophysiological recording studies in PD. Importantly, this novel analysis also demonstrates that changes in network dynamics can be measured using resting-state fMRI data from subjects with early stage PD. Copyright © 2018 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Fan, Fenglei; Fan, Wei
2014-01-01
A new viewpoint for understanding the urban expansion using impervious surface information, which is obtained using remote sensing imagery is presented. The purpose of this study is to understand and describe the urban expansion pattern with the view of impervious surfaces instead of the conventional view of land use/land cover. Six years' worth of impervious surface data (1990-2009) of Guangzhou are extracted via linear spectral unmixing analysis methods and spatial and temporal characteristics are discussed in detail. The area, density, and gravity centers changes of the impervious surfaces are analyzed to explain internal/external urban expansion. Meanwhile, five landscape indexes, such as patch density, edge density, mean patch size, area-weighted, and fragmentation index, are utilized to describe landscape changes of Guangzhou in past 20 years, which are influenced deeply by the impervious surface expansion. In order to detail landscape changes, two transects corresponding to the two urban expansion directions are designed and five landscape metrics in these two transects are reported. Conclusions can be drawn and shown as following: (1) temporally, the area of impervious surfaces increases from 12,998 to 59,911 ha from 1990 to 2009. The amount of impervious surface varies in different periods. The annual growth rates of impervious surface area during 1990-1995, 1995-1998, and 1998-2000 are 10.16%, 11.61%, and 10.78%, respectively; (2) annual growth rates decrease from 10.78% (1998-2000) to 5.67% (2000-2003). Nevertheless, from 2003-2009, the annual growth rate has a slight increase compared to a former period. The rate is 5.91% (3) spatially, gravity centers of medium and high percentage impervious surfaces migrate slightly; and (4) according to the gradient analysis in the two transects, it can be observed that the high percentage of impervious surface increases gradually in new city districts (from west to east and from south to north).
A Method to Categorize 2-Dimensional Patterns Using Statistics of Spatial Organization.
López-Sauceda, Juan; Rueda-Contreras, Mara D
2017-01-01
We developed a measurement framework of spatial organization to categorize 2-dimensional patterns from 2 multiscalar biological architectures. We propose that underlying shapes of biological entities can be approached using the statistical concept of degrees of freedom, defining it through expansion of area variability in a pattern. To help scope this suggestion, we developed a mathematical argument recognizing the deep foundations of area variability in a polygonal pattern (spatial heterogeneity). This measure uses a parameter called eutacticity . Our measuring platform of spatial heterogeneity can assign particular ranges of distribution of spatial areas for 2 biological architectures: ecological patterns of Namibia fairy circles and epithelial sheets. The spatial organizations of our 2 analyzed biological architectures are demarcated by being in a particular position among spatial order and disorder. We suggest that this theoretical platform can give us some insights about the nature of shapes in biological systems to understand organizational constraints.
NASA Astrophysics Data System (ADS)
Torgersen, C. E.; Fullerton, A.; Lawler, J. J.; Ebersole, J. L.; Leibowitz, S. G.; Steel, E. A.; Beechie, T. J.; Faux, R.
2016-12-01
Understanding spatial patterns in water temperature will be essential for evaluating vulnerability of aquatic biota to future climate and for identifying and protecting diverse thermal habitats. We used high-resolution remotely sensed water temperature data for over 16,000 km of 2nd to 7th-order rivers throughout the Pacific Northwest and California to evaluate spatial patterns of summertime water temperature at multiple spatial scales. We found a diverse and geographically distributed suite of whole-river patterns. About half of rivers warmed asymptotically in a downstream direction, whereas the rest exhibited complex and unique spatial patterns. Patterns were associated with both broad-scale hydroclimatic variables as well as characteristics unique to each basin. Within-river thermal heterogeneity patterns were highly river-specific; across rivers, median size and spacing of cool patches <15 °C were around 250 m. Patches of this size are large enough for juvenile salmon rearing and for resting during migration, and the distance between patches is well within the movement capabilities of both juvenile and adult salmon. We found considerable thermal heterogeneity at fine spatial scales that may be important to fish that would be missed if data were analyzed at coarser scales. We estimated future thermal heterogeneity and concluded that climate change will cause warmer temperatures overall, but that thermal heterogeneity patterns may remain similar in the future for many rivers. We demonstrated considerable spatial complexity in both current and future water temperature, and resolved spatial patterns that could not have been perceived without spatially continuous data.
Quantifying seascape structure: Extending terrestrial spatial pattern metrics to the marine realm
Wedding, L.M.; Christopher, L.A.; Pittman, S.J.; Friedlander, A.M.; Jorgensen, S.
2011-01-01
Spatial pattern metrics have routinely been applied to characterize and quantify structural features of terrestrial landscapes and have demonstrated great utility in landscape ecology and conservation planning. The important role of spatial structure in ecology and management is now commonly recognized, and recent advances in marine remote sensing technology have facilitated the application of spatial pattern metrics to the marine environment. However, it is not yet clear whether concepts, metrics, and statistical techniques developed for terrestrial ecosystems are relevant for marine species and seascapes. To address this gap in our knowledge, we reviewed, synthesized, and evaluated the utility and application of spatial pattern metrics in the marine science literature over the past 30 yr (1980 to 2010). In total, 23 studies characterized seascape structure, of which 17 quantified spatial patterns using a 2-dimensional patch-mosaic model and 5 used a continuously varying 3-dimensional surface model. Most seascape studies followed terrestrial-based studies in their search for ecological patterns and applied or modified existing metrics. Only 1 truly unique metric was found (hydrodynamic aperture applied to Pacific atolls). While there are still relatively few studies using spatial pattern metrics in the marine environment, they have suffered from similar misuse as reported for terrestrial studies, such as the lack of a priori considerations or the problem of collinearity between metrics. Spatial pattern metrics offer great potential for ecological research and environmental management in marine systems, and future studies should focus on (1) the dynamic boundary between the land and sea; (2) quantifying 3-dimensional spatial patterns; and (3) assessing and monitoring seascape change. ?? Inter-Research 2011.
NASA Astrophysics Data System (ADS)
Stisen, S.; Demirel, C.; Koch, J.
2017-12-01
Evaluation of performance is an integral part of model development and calibration as well as it is of paramount importance when communicating modelling results to stakeholders and the scientific community. There exists a comprehensive and well tested toolbox of metrics to assess temporal model performance in the hydrological modelling community. On the contrary, the experience to evaluate spatial performance is not corresponding to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study aims at making a contribution towards advancing spatial pattern oriented model evaluation for distributed hydrological models. This is achieved by introducing a novel spatial performance metric which provides robust pattern performance during model calibration. The promoted SPAtial EFficiency (spaef) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multi-component approach is necessary in order to adequately compare spatial patterns. spaef, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are tested in a spatial pattern oriented model calibration of a catchment model in Denmark. The calibration is constrained by a remote sensing based spatial pattern of evapotranspiration and discharge timeseries at two stations. Our results stress that stand-alone metrics tend to fail to provide holistic pattern information to the optimizer which underlines the importance of multi-component metrics. The three spaef components are independent which allows them to complement each other in a meaningful way. This study promotes the use of bias insensitive metrics which allow comparing variables which are related but may differ in unit in order to optimally exploit spatial observations made available by remote sensing platforms. We see great potential of spaef across environmental disciplines dealing with spatially distributed modelling.
Validating a spatially distributed hydrological model with soil morphology data
NASA Astrophysics Data System (ADS)
Doppler, T.; Honti, M.; Zihlmann, U.; Weisskopf, P.; Stamm, C.
2014-09-01
Spatially distributed models are popular tools in hydrology claimed to be useful to support management decisions. Despite the high spatial resolution of the computed variables, calibration and validation is often carried out only on discharge time series at specific locations due to the lack of spatially distributed reference data. Because of this restriction, the predictive power of these models, with regard to predicted spatial patterns, can usually not be judged. An example of spatial predictions in hydrology is the prediction of saturated areas in agricultural catchments. These areas can be important source areas for inputs of agrochemicals to the stream. We set up a spatially distributed model to predict saturated areas in a 1.2 km2 catchment in Switzerland with moderate topography and artificial drainage. We translated soil morphological data available from soil maps into an estimate of the duration of soil saturation in the soil horizons. This resulted in a data set with high spatial coverage on which the model predictions were validated. In general, these saturation estimates corresponded well to the measured groundwater levels. We worked with a model that would be applicable for management decisions because of its fast calculation speed and rather low data requirements. We simultaneously calibrated the model to observed groundwater levels and discharge. The model was able to reproduce the general hydrological behavior of the catchment in terms of discharge and absolute groundwater levels. However, the the groundwater level predictions were not accurate enough to be used for the prediction of saturated areas. Groundwater level dynamics were not adequately reproduced and the predicted spatial saturation patterns did not correspond to those estimated from the soil map. Our results indicate that an accurate prediction of the groundwater level dynamics of the shallow groundwater in our catchment that is subject to artificial drainage would require a model that better represents processes at the boundary between the unsaturated and the saturated zone. However, data needed for such a more detailed model are not generally available. This severely hampers the practical use of such models despite their usefulness for scientific purposes.
NASA Astrophysics Data System (ADS)
Barron-Gafford, G.; Minor, R. L.; Heard, M. M.; Sutter, L. F.; Yang, J.; Potts, D. L.
2015-12-01
The southwestern U.S. is predicted to experience increasing temperatures and longer periods of inter-storm drought. High temperature and water deficit restrict plant productivity and ecosystem functioning, but the influence of future climate is predicted to be highly heterogeneous because of the complex terrain characteristic of much of the Critical Zone (CZ). Within our Critical Zone Observatory (CZO) in the Southwestern US, we monitor ecosystem-scale carbon and water fluxes using eddy covariance. This whole-ecosystem metric is a powerful integrating measure of ecosystem function over time, but details on spatial heterogeneity resulting from topographic features of the landscape are not captured, nor are interactions among below- and aboveground processes. We supplement eddy covariance monitoring with distributed measures of carbon flux from soil and vegetation across different aspects to quantify the causes and consequences of spatial heterogeneity through time. Given that (i) aspect influences how incoming energy drives evaporative water loss and (ii) seasonality drives temporal patterns of soil moisture recharge, we were able to examine the influence of these processes on CO2 efflux by investigating variation across aspect. We found that aspect was a significant source of spatial heterogeneity in soil CO2 efflux, but the influence varied across seasonal periods. Snow on South-facing aspects melted earlier and yielded higher efflux rates in the spring. However, during summer, North- and South-facing aspects had similar amounts of soil moisture, but soil temperatures were warmer on the North-facing aspect, yielding greater rates of CO2 efflux. Interestingly, aspect did not influence photosynthetic rates. Taken together, we found that physical features of the landscape yielded predictable patterns of levels and phenologies of soil moisture and temperature, but these drivers differentially influenced below- and aboveground sources of carbon exchange. Conducting these spatially distributed measurements are time consuming. Looking forward, we have begun using unmanned aerial vehicles outfitted with thermal and multi-spectral cameras to quantify patterns of water flux, NDVI, needle browning due to moisture stress, and overall phenology in the CZ.
Observed and Modeled Trends in Southern Ocean Sea Ice
NASA Technical Reports Server (NTRS)
Parkinson, Claire L.
2003-01-01
Conceptual models and global climate model (GCM) simulations have both indicated the likelihood of an enhanced sensitivity to climate change in the polar regions, derived from the positive feedbacks brought about by the polar abundance of snow and ice surfaces. Some models further indicate that the changes in the polar regions can have a significant impact globally. For instance, 37% of the temperature sensitivity to a doubling of atmospheric CO2 in simulations with the GCM of the Goddard Institute for Space Studies (GISS) is attributable exclusively to inclusion of sea ice variations in the model calculations. Both sea ice thickness and sea ice extent decrease markedly in the doubled CO, case, thereby allowing the ice feedbacks to occur. Stand-alone sea ice models have shown Southern Ocean hemispherically averaged winter ice-edge retreats of 1.4 deg latitude for each 1 K increase in atmospheric temperatures. Observations, however, show a much more varied Southern Ocean ice cover, both spatially and temporally, than many of the modeled expectations. In fact, the satellite passive-microwave record of Southern Ocean sea ice since late 1978 has revealed overall increases rather than decreases in ice extents, with ice extent trends on the order of 11,000 sq km/year. When broken down spatially, the positive trends are strongest in the Ross Sea, while the trends are negative in the Bellingshausen/Amundsen Seas. Greater spatial detail can be obtained by examining trends in the length of the sea ice season, and those trends show a coherent picture of shortening sea ice seasons throughout almost the entire Bellingshausen and Amundsen Seas to the west of the Antarctic Peninsula and in the far western Weddell Sea immediately to the east of the Peninsula, with lengthening sea ice seasons around much of the rest of the continent. This pattern corresponds well with the spatial pattern of temperature trends, as the Peninsula region is the one region in the Antarctic with a strong record of temperature increases. Still, although the patterns of the temperature and ice changes match fairly well, there is a substantial ways to go before these patterns are understood (and can be modeled) in the full context of global change.
Impact of scale on morphological spatial pattern of forest
Katarzyna Ostapowicz; Peter Vogt; Kurt H. Riitters; Jacek Kozak; Christine Estreguil
2008-01-01
Assessing and monitoring landscape pattern structure from multi-scale land-cover maps can utilize morphological spatial pattern analysis (MSPA), only if various influences of scale are known and taken into account. This paper lays part of the foundation for applying MSPA analysis in landscape monitoring by quantifying scale effects on six classes of spatial patterns...
de Pablo, M A; Ramos, M; Molina, A; Prieto, M
2018-02-15
A new Circumpolar Active Layer Monitoring (CALM) site was established in 2009 at the Limnopolar Lake watershed in Byers Peninsula, Livingston Island, Antarctica, to provide a node in the western Antarctic Peninsula, one of the regions that recorded the highest air temperature increase in the planet during the last decades. The first detailed analysis of the temporal and spatial evolution of the thaw depth at the Limnopolar Lake CALM-S site is presented here, after eight years of monitoring. The average values range between 48 and 29cm, decreasing at a ratio of 16cm/decade. The annual thaw depth observations in the 100×100 m CALM grid are variable (Variability Index of 34 to 51%), although both the Variance Coefficient and the Climate Matrix Analysis Residual point to the internal consistency of the data. Those differences could be explained then by the terrain complexity and node-specific variability due to the ground properties. The interannual variability was about 60% during 2009-2012, increasing to 124% due to the presence of snow in 2013, 2015 and 2016. The snow has been proposed here as one of the most important factors controlling the spatial variability of ground thaw depth, since its values correlate with the snow thickness but also with the ground surface temperature and unconfined compression resistance, as measured in 2010. The topography explains the thaw depth spatial distribution pattern, being related to snowmelt water and its accumulation in low-elevation areas (downslope-flow). Patterned grounds and other surface features correlate well with high thaw depth patterns as well. The edaphic factor (E=0.05842m 2 /°C·day; R 2 =0.63) is in agreement with other permafrost environments, since frozen index (F>0.67) and MAAT (<-2°C) denote a continuous permafrost existence in the area. All these characteristics provided the basis for further comparative analyses between others nearby CALM sites. Copyright © 2017 Elsevier B.V. All rights reserved.
A zone-based approach to identifying urban land uses using nationally-available data
NASA Astrophysics Data System (ADS)
Falcone, James A.
Accurate identification of urban land use is essential for many applications in environmental study, ecological assessment, and urban planning, among other fields. However, because physical surfaces of land cover types are not necessarily related to their use and economic function, differentiating among thematically-detailed urban land uses (single-family residential, multi-family residential, commercial, industrial, etc.) using remotely-sensed imagery is a challenging task, particularly over large areas. Because the process requires an interpretation of tone/color, size, shape, pattern, and neighborhood association elements within a scene, it has traditionally been accomplished via manual interpretation of aerial photography or high-resolution satellite imagery. Although success has been achieved for localized areas using various automated techniques based on high-spatial or high-spectral resolution data, few detailed (Anderson Level II equivalent or greater) urban land use mapping products have successfully been created via automated means for broad (multi-county or larger) areas, and no such product exists today for the United States. In this study I argue that by employing a zone-based approach it is feasible to map thematically-detailed urban land use classes over large areas using appropriate combinations of non-image based predictor data which are nationally and publicly available. The approach presented here uses U.S. Census block groups as the basic unit of geography, and predicts the percent of each of ten land use types---nine of them urban---for each block group based on a number of data sources, to include census data, nationally-available point locations of features from the USGS Geographic Names Information System, historical land cover, and metrics which characterize spatial pattern, context (e.g. distance to city centers or other features), and measures of spatial autocorrelation. The method was demonstrated over a four-county area surrounding the city of Boston. A generalized version of the method (six land use classes) was also developed and cross-validated among additional geographic settings: Atlanta, Los Angeles, and Providence. The results suggest that even with the thematically-detailed ten-class structure, it is feasible to map most urban land uses with reasonable accuracy at the block group scale, and results improve with class aggregation. When classified by predicted majority land use, 79% of block groups correctly matched the actual majority land use with the ten-class models. Six-class models typically performed well for the geographic area they were developed from, however models had mixed performance when transported to other geographic settings. Contextual variables, which characterized a block group's spatial relationship to city centers, transportation routes, and other amenities, were consistently strong predictors of most land uses, a result which corresponds to classic urban land use theory. The method and metrics derived here provide a prototype for mapping urban land uses from readily-available data over broader geographic areas than is generally practiced today using current image-based solutions.
Hierarchical acquisition of visual specificity in spatial contextual cueing.
Lie, Kin-Pou
2015-01-01
Spatial contextual cueing refers to visual search performance's being improved when invariant associations between target locations and distractor spatial configurations are learned incidentally. Using the instance theory of automatization and the reverse hierarchy theory of visual perceptual learning, this study explores the acquisition of visual specificity in spatial contextual cueing. Two experiments in which detailed visual features were irrelevant for distinguishing between spatial contexts found that spatial contextual cueing was visually generic in difficult trials when the trials were not preceded by easy trials (Experiment 1) but that spatial contextual cueing progressed to visual specificity when difficult trials were preceded by easy trials (Experiment 2). These findings support reverse hierarchy theory, which predicts that even when detailed visual features are irrelevant for distinguishing between spatial contexts, spatial contextual cueing can progress to visual specificity if the stimuli remain constant, the task is difficult, and difficult trials are preceded by easy trials. However, these findings are inconsistent with instance theory, which predicts that when detailed visual features are irrelevant for distinguishing between spatial contexts, spatial contextual cueing will not progress to visual specificity. This study concludes that the acquisition of visual specificity in spatial contextual cueing is more plausibly hierarchical, rather than instance-based.
COMPARISON OF SPATIAL PATTERNS OF POLLUTANT DISTRIBUTION WITH CMAQ PREDICTIONS
To evaluate the Models-3/Community Multiscale Air Quality (CMAQ) modeling system in reproducing the spatial patterns of aerosol concentrations over the country on timescales of months and years, the spatial patterns of model output are compared with those derived from observation...
Spatial Patterns in Alternative States and Thresholds: A Missing Link for Management of Landscapes?
USDA-ARS?s Scientific Manuscript database
The detection of threshold dynamics (and other dynamics of interest) would benefit from explicit representations of spatial patterns of disturbance, spatial dependence in responses to disturbance, and the spatial structure of feedbacks in the design of monitoring and management strategies. Spatially...
Analysis of deformation patterns through advanced DINSAR techniques in Istanbul megacity
NASA Astrophysics Data System (ADS)
Balik Sanli, F.; Calò, F.; Abdikan, S.; Pepe, A.; Gorum, T.
2014-09-01
As result of the Turkey's economic growth and heavy migration processes from rural areas, Istanbul has experienced a high urbanization rate, with severe impacts on the environment in terms of natural resources pressure, land-cover changes and uncontrolled sprawl. As a consequence, the city became extremely vulnerable to natural and man-made hazards, inducing ground deformation phenomena that threaten buildings and infrastructures and often cause significant socio-economic losses. Therefore, the detection and monitoring of such deformation patterns is of primary importance for hazard and risk assessment as well as for the design and implementation of effective mitigation strategies. Aim of this work is to analyze the spatial distribution and temporal evolution of deformations affecting the Istanbul metropolitan area, by exploiting advanced Differential SAR Interferometry (DInSAR) techniques. In particular, we apply the Small BAseline Subset (SBAS) approach to a dataset of 43 TerraSAR-X images acquired, between November 2010 and June 2012, along descending orbits with an 11-day revisit time and a 3 m × 3 m spatial resolution. The SBAS processing allowed us to remotely detect and monitor subsidence patterns over all the urban area as well as to provide detailed information at the scale of the single building. Such SBAS measurements, effectively integrated with ground-based monitoring data and thematic maps, allows to explore the relationship between the detected deformation phenomena and urbanization, contributing to improve the urban planning and management.
NASA Astrophysics Data System (ADS)
Liu, Hua
A new synthesis of remote sensing and landscape ecology approaches was developed to establish relationships between the landscape patterns and land surface temperatures (LST) in the city of Indianapolis, Indiana, United States. Land use and land cover (LULC) and LST images were derived from Terra Satellite's Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. An analytical procedure using landscape metrics was developed, applying configuration analysis of landscape patterns and land surface temperature zones. Detailed landscape pattern analyses at the landscape and class scales were conducted using landscape metrics in the City of Indianapolis. The effects of spatial resolution on the identification of the relationship were examined in the same city. The best level of equalization between the LULC and LST maps was determined based on minimum distance analysis in landscape metrics space. The analyses of relationships between the landscape patterns and land surface temperatures, and scaling effects were applied to the spread of West Nile Virus (WNV) in the City of Chicago, Illinois. Results show that urban, forest, and grassland were the main landscape components in Indianapolis. They possessed relatively higher fractal dimensions but lower spatial aggregation levels in April 5, 2004, June 16, 2001, and October 3, 2000, but not in February 6, 2006. Obvious seasonal differences existed with the most distinct landscape pattern detected on February 6, 2006. Urban was the dominant LULC type in high-temperature zones, while water and vegetation mainly fell in low-temperature zones. For each individual date, the metrics of LST zones apparently corresponded to the metrics of LULC types. In the study of scaling-up effect analysis, Patch Percentage, Patch Density, and Landscape Shape index were found to be able to effectively quantify the spatial changes of LULC types and temperature zones at different scales without contradiction. Urban, forest, and grassland in each season were more easily affected by the process in Patch Density and Landscape Shape index. Ninety meters was believed to be the optimal spatial resolution to examine relationships between landscape patterns and LSTs in the City of Indianapolis. In the study of the spread of West Nile Virus in the City of Chicago, WNV was found to have been spread throughout all of Cook County since 2001. Landscape factors, like landscape aggregation index and areas of urban, grass, and water showed a strong correlation with the number of WNV infections. Socioeconomic conditions, like population above 65 years old also showed a strong relationship with the spread of WNV in Cook County. Thermal conditions of water had a lower but still significant correlation to the spread of WNV. This research offers an opportunity to explore the mechanism of interaction between urban landscape patterns and land surface temperatures at different spatial scales, and show the effects of landscape pattern and land surface temperature on the spread of West Nile Virus. This study can be useful for urban planning and environmental management practices in the studied areas. It also contributes to public health management and protection.
Marc-Andre Parisien; Sean A. Parks; Carol Miller; Meg A. Krawchuck; Mark Heathcott; Max A. Moritz
2011-01-01
The spatial pattern of fire observed across boreal landscapes is the outcome of complex interactions among components of the fire environment. We investigated how the naturally occurring patterns of ignitions, fuels, and weather generate spatial pattern of burn probability (BP) in a large and highly fireprone boreal landscape of western Canada, Wood Buffalo National...
Spatial reconstruction of single-cell gene expression data.
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
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
Spatial arrangement of faults and opening-mode fractures
NASA Astrophysics Data System (ADS)
Laubach, S. E.; Lamarche, J.; Gauthier, B. D. M.; Dunne, W. M.; Sanderson, David J.
2018-03-01
Spatial arrangement is a fundamental characteristic of fracture arrays. The pattern of fault and opening-mode fracture positions in space defines structural heterogeneity and anisotropy in a rock volume, governs how faults and fractures affect fluid flow, and impacts our understanding of the initiation, propagation and interactions during the formation of fracture patterns. This special issue highlights recent progress with respect to characterizing and understanding the spatial arrangements of fault and fracture patterns, providing examples over a wide range of scales and structural settings. Five papers describe new methods and improvements of existing techniques to quantify spatial arrangement. One study unravels the time evolution of opening-mode fracture spatial arrangement, which are data needed to compare natural patterns with progressive fracture growth in kinematic and mechanical models. Three papers investigate the role of evolving diagenesis in localizing fractures by mechanical stratigraphy and nine discuss opening-mode fracture spatial arrangement. Two papers show the relevance of complex cluster patterns to unconventional reservoirs through examples of fractures in tight gas sandstone horizontal wells, and a study of fracture arrangement in shale. Four papers demonstrate the roles of folds in fracture localization and the development spatial patterns. One paper models along-fault friction and fluid pressure and their effects on fault-related fracture arrangement. Contributions address deformation band patterns in carbonate rocks and fault size and arrangement above a detachment fault. Three papers describe fault and fracture arrangements in basement terrains, and three document fracture patterns in shale. This collection of papers points toward improvement in field methods, continuing improvements in computer-based data analysis and creation of synthetic fracture patterns, and opportunities for further understanding fault and fracture attributes in the subsurface through coupled spatial, size, and pattern analysis.
Ownership reform and the changing manufacturing landscape in Chinese cities: The case of Wuxi.
Zhou, Lei; Yang, Shan; Wang, Shuguang; Xiong, Liyang
2017-01-01
Since the economic transition, manufacturing in China has undergone profound changes not only in number of enterprises, but also in ownership structure and intra-urban spatial distribution. Investigating the changing manufacturing landscape from the perspective of ownership structure is critical to a deep understanding of the changing role of market and government in re-shaping manufacturing location behavior. Through a case study of Wuxi, a city experiencing comprehensive ownership reform, this paper presents a detailed analysis of the intra-urban spatial shift of manufacturing, identifies the location discrepancies, and examines the underlying forces responsible for the geographical differentiations. Through zone- and district-based analysis, a distinctive trend of decentralization and suburbanization, as well as an uneven distribution of manufacturing, is unveiled. The results of Location Quotient analysis show that the distribution of manufacturing by ownership exhibits distinctive spatial patterns, which is characterized by a historically-based, market-led, and institutionally-created spatial variation. By employing Hot Spot analysis, the role of development zones in attracting manufacturing enterprises of different ownerships is established. Overall, the location behavior of the diversified manufacturing has been increasingly based on the forces of market since the land marketization began. A proactive role played by local governments has also guided the enterprise location decision through spatial planning and regulatory policies.
Kraan, Casper; Aarts, Geert; Van der Meer, Jaap; Piersma, Theunis
2010-06-01
Ongoing statistical sophistication allows a shift from describing species' spatial distributions toward statistically disentangling the possible roles of environmental variables in shaping species distributions. Based on a landscape-scale benthic survey in the Dutch Wadden Sea, we show the merits of spatially explicit generalized estimating equations (GEE). The intertidal macrozoobenthic species, Macoma balthica, Cerastoderma edule, Marenzelleria viridis, Scoloplos armiger, Corophium volutator, and Urothoe poseidonis served as test cases, with median grain-size and inundation time as typical environmental explanatory variables. GEEs outperformed spatially naive generalized linear models (GLMs), and removed much residual spatial structure, indicating the importance of median grain-size and inundation time in shaping landscape-scale species distributions in the intertidal. GEE regression coefficients were smaller than those attained with GLM, and GEE standard errors were larger. The best fitting GEE for each species was used to predict species' density in relation to median grain-size and inundation time. Although no drastic changes were noted compared to previous work that described habitat suitability for benthic fauna in the Wadden Sea, our predictions provided more detailed and unbiased estimates of the determinants of species-environment relationships. We conclude that spatial GEEs offer the necessary methodological advances to further steps toward linking pattern to process.
Ownership reform and the changing manufacturing landscape in Chinese cities: The case of Wuxi
Zhou, Lei; Yang, Shan; Wang, Shuguang
2017-01-01
Since the economic transition, manufacturing in China has undergone profound changes not only in number of enterprises, but also in ownership structure and intra-urban spatial distribution. Investigating the changing manufacturing landscape from the perspective of ownership structure is critical to a deep understanding of the changing role of market and government in re-shaping manufacturing location behavior. Through a case study of Wuxi, a city experiencing comprehensive ownership reform, this paper presents a detailed analysis of the intra-urban spatial shift of manufacturing, identifies the location discrepancies, and examines the underlying forces responsible for the geographical differentiations. Through zone- and district-based analysis, a distinctive trend of decentralization and suburbanization, as well as an uneven distribution of manufacturing, is unveiled. The results of Location Quotient analysis show that the distribution of manufacturing by ownership exhibits distinctive spatial patterns, which is characterized by a historically-based, market-led, and institutionally-created spatial variation. By employing Hot Spot analysis, the role of development zones in attracting manufacturing enterprises of different ownerships is established. Overall, the location behavior of the diversified manufacturing has been increasingly based on the forces of market since the land marketization began. A proactive role played by local governments has also guided the enterprise location decision through spatial planning and regulatory policies. PMID:28278284
Prunier, J G; Colyn, M; Legendre, X; Nimon, K F; Flamand, M C
2015-01-01
Direct gradient analyses in spatial genetics provide unique opportunities to describe the inherent complexity of genetic variation in wildlife species and are the object of many methodological developments. However, multicollinearity among explanatory variables is a systemic issue in multivariate regression analyses and is likely to cause serious difficulties in properly interpreting results of direct gradient analyses, with the risk of erroneous conclusions, misdirected research and inefficient or counterproductive conservation measures. Using simulated data sets along with linear and logistic regressions on distance matrices, we illustrate how commonality analysis (CA), a detailed variance-partitioning procedure that was recently introduced in the field of ecology, can be used to deal with nonindependence among spatial predictors. By decomposing model fit indices into unique and common (or shared) variance components, CA allows identifying the location and magnitude of multicollinearity, revealing spurious correlations and thus thoroughly improving the interpretation of multivariate regressions. Despite a few inherent limitations, especially in the case of resistance model optimization, this review highlights the great potential of CA to account for complex multicollinearity patterns in spatial genetics and identifies future applications and lines of research. We strongly urge spatial geneticists to systematically investigate commonalities when performing direct gradient analyses. © 2014 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Boldina, Inna; Beninger, Peter G.; Le Coz, Maïwen
2014-01-01
Situated at the interface of the microbial and macrofaunal compartments, soft-bottom meiofauna accomplish important ecological functions. However, little is known of their spatial distribution in the benthic environment. To assess the effects of long-term mechanical disturbance on soft-bottom meiofaunal spatial distribution, we compared a site subjected to long-term clam digging to a nearby site untouched by such activities, in Bourgneuf Bay, on the Atlantic coast of France. Six patterned replicate samples were taken at 3, 6, 9, 12, 15, 18, 21 and 24 cm lags, all sampling stations being separated by 5 m. A combined correlogram-variogram approach was used to enhance interpretation of the meiofaunal spatial distribution; in particular, the definition of autocorrelation strength and its statistical significance, as well as the detailed characteristics of the periodic spatial structure of nematode assemblages, and the determination of the maximum distance of their spatial autocorrelation. At both sites, nematodes and copepods clearly exhibited aggregated spatial structure at the meso scale; this structure was attenuated at the impacted site. The nematode spatial distribution showed periodicity at the non-impacted site, but not at the impacted site. This is the first explicit report of a periodic process in meiofaunal spatial distribution. No such cyclic spatial process was observed for the more motile copepods at either site. This first study to indicate the impacts of long-term anthropogenic mechanical perturbation on meiofaunal spatial structure opens the door to a new dimension of mudflat ecology. Since macrofaunal predator search behaviour is known to be strongly influenced by prey spatial structure, the alteration of this structure may have important consequences for ecosystem functioning.
Chen, Jiawen; Xie, Zhong-Ru; Wu, Yinghao
2016-07-01
The ligand-binding of membrane receptors on cell surfaces initiates the dynamic process of cross-membrane signal transduction. It is an indispensable part of the signaling network for cells to communicate with external environments. Recent experiments revealed that molecular components in signal transduction are not randomly mixed, but spatially organized into distinctive patterns. These patterns, such as receptor clustering and ligand oligomerization, lead to very different gene expression profiles. However, little is understood about the molecular mechanisms and functional impacts of this spatial-temporal regulation in cross-membrane signal transduction. In order to tackle this problem, we developed a hybrid computational method that decomposes a model of signaling network into two simulation modules. The physical process of binding between receptors and ligands on cell surfaces are simulated by a diffusion-reaction algorithm, while the downstream biochemical reactions are modeled by stochastic simulation of Gillespie algorithm. These two processes are coupled together by a synchronization framework. Using this method, we tested the dynamics of a simple signaling network in which the ligand binding of cell surface receptors triggers the phosphorylation of protein kinases, and in turn regulates the expression of target genes. We found that spatial aggregation of membrane receptors at cellular interfaces is able to either amplify or inhibit downstream signaling outputs, depending on the details of clustering mechanism. Moreover, by providing higher binding avidity, the co-localization of ligands into multi-valence complex modulates signaling in very different ways that are closely related to the binding affinity between ligand and receptor. We also found that the temporal oscillation of the signaling pathway that is derived from genetic feedback loops can be modified by the spatial clustering of membrane receptors. In summary, our method demonstrates the functional importance of spatial organization in cross-membrane signal transduction. The method can be applied to any specific signaling pathway in cells.
NASA Astrophysics Data System (ADS)
Beltran Torres, Silvana; Petrik, Attila; Zsuzsanna Szabó, Katalin; Jordan, Gyozo; Szabó, Csaba
2017-04-01
In order to estimate the annual dose that the public receive from natural radioactivity, the identification of the potential risk areas is required which, in turn, necessitates understanding the relationship between the spatial distribution of natural radioactivity and the geogenic risk factors (e.g., rock types, dykes, faults, soil conditions, etc.). A detailed spatial analysis of ambient gamma dose equivalent rate was performed in the western side of Velence Mountains, the largest outcropped granitic area in Hungary. In order to assess the role of local geology in the spatial distribution of ambient gamma dose rates, field measurements were carried out at ground level at 300 sites along a 250 m x 250 m regular grid in a total surface of 14.7 km2. Digital image processing methods were applied to identify anomalies, heterogeneities and spatial patterns in the measured gamma dose rates, including local maxima and minima determination, digital cross sections, gradient magnitude and gradient direction, second derivative profile curvature, local variability, lineament density, 2D autocorrelation and directional variogram analyses. Statistical inference showed that different gamma dose rate levels are associated with the rock types (i.e., Carboniferous granite, Pleistocene colluvial, proluvial, deluvial sediments and talus, and Pannonian sand and pebble), with the highest level on the Carboniferous granite including outlying values. Moreover, digital image processing revealed that linear gamma dose rate spatial features are parallel to the SW-NE dyke system and possibly to the NW-SE main fractures. The results of this study underline the importance of understanding the role of geogenic risk factors influencing the ambient gamma dose rate received by public. The study also demonstrates the power of the image processing techniques for the identification of spatial pattern in field-measured geogenic radiation.
Wallet, Grégory; Sauzéon, Hélène; Pala, Prashant Arvind; Larrue, Florian; Zheng, Xia; N'Kaoua, Bernard
2011-01-01
The purpose of this study was to evaluate the effect the visual fidelity of a virtual environment (VE) (undetailed vs. detailed) has on the transfer of spatial knowledge based on the navigation mode (passive vs. active) for three different spatial recall tasks (wayfinding, sketch mapping, and picture sorting). Sixty-four subjects (32 men and 32 women) participated in the experiment. Spatial learning was evaluated by these three tasks in the context of the Bordeaux district. In the wayfinding task, the results indicated that the detailed VE helped subjects to transfer their spatial knowledge from the VE to the real world, irrespective of the navigation mode. In the sketch-mapping task, the detailed VE increased performances compared to the undetailed VE condition, and allowed subjects to benefit from the active navigation. In the sorting task, performances were better in the detailed VE; however, in the undetailed version of the VE, active learning either did not help the subjects or it even deteriorated their performances. These results are discussed in terms of appropriate perceptive-motor and/or spatial representations for each spatial recall task.
Variation in Orthologous Shell-Forming Proteins Contribute to Molluscan Shell Diversity.
Jackson, Daniel J; Reim, Laurin; Randow, Clemens; Cerveau, Nicolas; Degnan, Bernard M; Fleck, Claudia
2017-11-01
Despite the evolutionary success and ancient heritage of the molluscan shell, little is known about the molecular details of its formation, evolutionary origins, or the interactions between the material properties of the shell and its organic constituents. In contrast to this dearth of information, a growing collection of molluscan shell-forming proteomes and transcriptomes suggest they are comprised of both deeply conserved, and lineage specific elements. Analyses of these sequence data sets have suggested that mechanisms such as exon shuffling, gene co-option, and gene family expansion facilitated the rapid evolution of shell-forming proteomes and supported the diversification of this phylum specific structure. In order to further investigate and test these ideas we have examined the molecular features and spatial expression patterns of two shell-forming genes (Lustrin and ML1A2) and coupled these observations with materials properties measurements of shells from a group of closely related gastropods (abalone). We find that the prominent "GS" domain of Lustrin, a domain believed to confer elastomeric properties to the shell, varies significantly in length between the species we investigated. Furthermore, the spatial expression patterns of Lustrin and ML1A2 also vary significantly between species, suggesting that both protein architecture, and the regulation of spatial gene expression patterns, are important drivers of molluscan shell evolution. Variation in these molecular features might relate to certain materials properties of the shells of these species. These insights reveal an important and underappreciated source of variation within shell-forming proteomes that must contribute to the diversity of molluscan shell phenotypes. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
Ji, Kang Hyeun; Herring, Thomas A.; Llenos, Andrea L.
2013-01-01
Long Valley Caldera in eastern California is an active volcanic area and has shown continued unrest in the last three decades. We have monitored surface deformation from Global Positioning System (GPS) data by using a projection method that we call Targeted Projection Operator (TPO). TPO projects residual time series with secular rates and periodic terms removed onto a predefined spatial pattern. We used the 2009–2010 slow deflation as a target spatial pattern. The resulting TPO time series shows a detailed deformation history including the 2007–2009 inflation, the 2009–2010 deflation, and a recent inflation that started in late-2011 and is continuing at the present time (November 2012). The recent inflation event is about four times faster than the previous 2007–2009 event. A Mogi source of the recent event is located beneath the resurgent dome at about 6.6 km depth at a rate of 0.009 km3/yr volume change. TPO is simple and fast and can provide a near real-time continuous monitoring tool without directly looking at all the data from many GPS sites in this potentially eruptive volcanic system.
How big should a mammal be? A macroecological look at mammalian body size over space and time
Smith, Felisa A.; Lyons, S. Kathleen
2011-01-01
Macroecology was developed as a big picture statistical approach to the study of ecology and evolution. By focusing on broadly occurring patterns and processes operating at large spatial and temporal scales rather than on localized and/or fine-scaled details, macroecology aims to uncover general mechanisms operating at organism, population, and ecosystem levels of organization. Macroecological studies typically involve the statistical analysis of fundamental species-level traits, such as body size, area of geographical range, and average density and/or abundance. Here, we briefly review the history of macroecology and use the body size of mammals as a case study to highlight current developments in the field, including the increasing linkage with biogeography and other disciplines. Characterizing the factors underlying the spatial and temporal patterns of body size variation in mammals is a daunting task and moreover, one not readily amenable to traditional statistical analyses. Our results clearly illustrate remarkable regularities in the distribution and variation of mammalian body size across both geographical space and evolutionary time that are related to ecology and trophic dynamics and that would not be apparent without a broader perspective. PMID:21768152
NASA Technical Reports Server (NTRS)
Rundle, John B.
1988-01-01
The idea that earthquakes represent a fluctuation about the long-term motion of plates is expressed mathematically through the fluctuation hypothesis, under which all physical quantities which pertain to the occurance of earthquakes are required to depend on the difference between the present state of slip on the fault and its long-term average. It is shown that under certain circumstances the model fault dynamics undergo a sudden transition from a spatially ordered, temporally disordered state to a spatially disordered, temporally ordered state, and that the latter stages are stable for long intervals of time. For long enough faults, the dynamics are evidently chaotic. The methods developed are then used to construct a detailed model for earthquake dynamics in southern California. The result is a set of slip-time histories for all the major faults, which are similar to data obtained by geological trenching studies. Although there is an element of periodicity to the events, the patterns shift, change and evolve with time. Time scales for pattern evolution seem to be of the order of a thousand years for average recurring intervals of about a hundred years.
Dong, Xiaoli; Grimm, Nancy B.
2017-01-01
Nutrients in freshwater ecosystems are highly variable in space and time. Nevertheless, the variety of processes contributing to nutrient patchiness, and the wide range of spatial and temporal scales at which these processes operate, obfuscate how this spatial heterogeneity is generated. Here, we describe the spatial structure of stream nutrient concentration, quantify the relative importance of the physical template and biological processes, and detect and evaluate the role of self-organization in driving such patterns. We examined nutrient spatial patterns in Sycamore Creek, an intermittent desert stream in Arizona that experienced an ecosystem regime shift [from a gravel/algae-dominated to a vascular plant-dominated (hereafter, “wetland”) system] in 2000 when cattle grazing ceased. We conducted high-resolution nutrient surveys in surface water along a 10-km stream reach over four visits spanning 18 y (1995–2013) that represent different successional stages and prewetland stage vs. postwetland state. As expected, groundwater upwelling had a major influence on nutrient spatial patterns. However, self-organization realized by the mechanism of spatial feedbacks also was significant and intensified over ecosystem succession, as a resource (nitrogen) became increasingly limiting. By late succession, the effects of internal spatial feedbacks and groundwater upwelling were approximately equal in magnitude. Wetland establishment influenced nutrient spatial patterns only indirectly, by modifying the extent of surface water/groundwater exchange. This study illustrates that multiple mechanisms interact in a dynamic way to create spatial heterogeneity in riverine ecosystems, and provides a means to detect spatial self-organization against physical template heterogeneity as a dominant driver of spatial patterns. PMID:28559326
Dong, Xiaoli; Ruhí, Albert; Grimm, Nancy B
2017-06-13
Nutrients in freshwater ecosystems are highly variable in space and time. Nevertheless, the variety of processes contributing to nutrient patchiness, and the wide range of spatial and temporal scales at which these processes operate, obfuscate how this spatial heterogeneity is generated. Here, we describe the spatial structure of stream nutrient concentration, quantify the relative importance of the physical template and biological processes, and detect and evaluate the role of self-organization in driving such patterns. We examined nutrient spatial patterns in Sycamore Creek, an intermittent desert stream in Arizona that experienced an ecosystem regime shift [from a gravel/algae-dominated to a vascular plant-dominated (hereafter, "wetland") system] in 2000 when cattle grazing ceased. We conducted high-resolution nutrient surveys in surface water along a 10-km stream reach over four visits spanning 18 y (1995-2013) that represent different successional stages and prewetland stage vs. postwetland state. As expected, groundwater upwelling had a major influence on nutrient spatial patterns. However, self-organization realized by the mechanism of spatial feedbacks also was significant and intensified over ecosystem succession, as a resource (nitrogen) became increasingly limiting. By late succession, the effects of internal spatial feedbacks and groundwater upwelling were approximately equal in magnitude. Wetland establishment influenced nutrient spatial patterns only indirectly, by modifying the extent of surface water/groundwater exchange. This study illustrates that multiple mechanisms interact in a dynamic way to create spatial heterogeneity in riverine ecosystems, and provides a means to detect spatial self-organization against physical template heterogeneity as a dominant driver of spatial patterns.
Mapping spatial patterns with morphological image processing
Peter Vogt; Kurt H. Riitters; Christine Estreguil; Jacek Kozak; Timothy G. Wade; James D. Wickham
2006-01-01
We use morphological image processing for classifying spatial patterns at the pixel level on binary land-cover maps. Land-cover pattern is classified as 'perforated,' 'edge,' 'patch,' and 'core' with higher spatial precision and thematic accuracy compared to a previous approach based on image convolution, while retaining the...
A Method for Mapping Future Urbanization in the United States
NASA Technical Reports Server (NTRS)
Bounoua, Lahouari; Nigro, Joseph; Thome, Kurtis; Zhang, Ping; Fathi, Najlaa; Lachir, Asia
2018-01-01
Cities are poised to absorb additional people. Their sustainability, or ability to accommodate a population increase without depleting resources or compromising future growth, depends on whether they harness the efficiency gains from urban land management. Population is often projected as a bulk national number without details about spatial distribution. We use Landsat and population data in a methodology to project and map U.S. urbanization for the year 2020 and document its spatial pattern. This methodology is important to spatially disaggregate projected population and assist land managers to monitor land use, assess infrastructure and distribute resources. We found the U.S. west coast urban areas to have the fastest population growth with relatively small land consumption resulting in future decrease in per capita land use. Except for Miami (FL), most other U.S. large urban areas, especially in the Midwest, are growing spatially faster than their population and inadvertently consuming land needed for ecosystem services. In large cities, such as New York, Chicago, Houston and Miami, land development is expected more in suburban zones than urban cores. In contrast, in Los Angeles land development within the city core is greater than in its suburbs.
Van de Voorde, Tim; Vlaeminck, Jeroen; Canters, Frank
2008-01-01
Urban growth and its related environmental problems call for sustainable urban management policies to safeguard the quality of urban environments. Vegetation plays an important part in this as it provides ecological, social, health and economic benefits to a city's inhabitants. Remotely sensed data are of great value to monitor urban green and despite the clear advantages of contemporary high resolution images, the benefits of medium resolution data should not be discarded. The objective of this research was to estimate fractional vegetation cover from a Landsat ETM+ image with sub-pixel classification, and to compare accuracies obtained with multiple stepwise regression analysis, linear spectral unmixing and multi-layer perceptrons (MLP) at the level of meaningful urban spatial entities. Despite the small, but nevertheless statistically significant differences at pixel level between the alternative approaches, the spatial pattern of vegetation cover and estimation errors is clearly distinctive at neighbourhood level. At this spatially aggregated level, a simple regression model appears to attain sufficient accuracy. For mapping at a spatially more detailed level, the MLP seems to be the most appropriate choice. Brightness normalisation only appeared to affect the linear models, especially the linear spectral unmixing. PMID:27879914
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
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.
NASA Technical Reports Server (NTRS)
Bradshaw, G. A.
1995-01-01
There has been an increased interest in the quantification of pattern in ecological systems over the past years. This interest is motivated by the desire to construct valid models which extend across many scales. Spatial methods must quantify pattern, discriminate types of pattern, and relate hierarchical phenomena across scales. Wavelet analysis is introduced as a method to identify spatial structure in ecological transect data. The main advantage of the wavelet transform over other methods is its ability to preserve and display hierarchical information while allowing for pattern decomposition. Two applications of wavelet analysis are illustrated, as a means to: (1) quantify known spatial patterns in Douglas-fir forests at several scales, and (2) construct spatially-explicit hypotheses regarding pattern generating mechanisms. Application of the wavelet variance, derived from the wavelet transform, is developed for forest ecosystem analysis to obtain additional insight into spatially-explicit data. Specifically, the resolution capabilities of the wavelet variance are compared to the semi-variogram and Fourier power spectra for the description of spatial data using a set of one-dimensional stationary and non-stationary processes. The wavelet cross-covariance function is derived from the wavelet transform and introduced as a alternative method for the analysis of multivariate spatial data of understory vegetation and canopy in Douglas-fir forests of the western Cascades of Oregon.
Long-term consistency in spatial patterns of primate seed dispersal.
Heymann, Eckhard W; Culot, Laurence; Knogge, Christoph; Noriega Piña, Tony Enrique; Tirado Herrera, Emérita R; Klapproth, Matthias; Zinner, Dietmar
2017-03-01
Seed dispersal is a key ecological process in tropical forests, with effects on various levels ranging from plant reproductive success to the carbon storage potential of tropical rainforests. On a local and landscape scale, spatial patterns of seed dispersal create the template for the recruitment process and thus influence the population dynamics of plant species. The strength of this influence will depend on the long-term consistency of spatial patterns of seed dispersal. We examined the long-term consistency of spatial patterns of seed dispersal with spatially explicit data on seed dispersal by two neotropical primate species, Leontocebus nigrifrons and Saguinus mystax (Callitrichidae), collected during four independent studies between 1994 and 2013. Using distributions of dispersal probability over distances independent of plant species, cumulative dispersal distances, and kernel density estimates, we show that spatial patterns of seed dispersal are highly consistent over time. For a specific plant species, the legume Parkia panurensis , the convergence of cumulative distributions at a distance of 300 m, and the high probability of dispersal within 100 m from source trees coincide with the dimension of the spatial-genetic structure on the embryo/juvenile (300 m) and adult stage (100 m), respectively, of this plant species. Our results are the first demonstration of long-term consistency of spatial patterns of seed dispersal created by tropical frugivores. Such consistency may translate into idiosyncratic patterns of regeneration.
Optical implementation of neocognitron and its applications to radar signature discrimination
NASA Technical Reports Server (NTRS)
Chao, Tien-Hsin; Stoner, William W.
1991-01-01
A feature-extraction-based optoelectronic neural network is introduced. The system implementation approach applies the principle of the neocognitron paradigm first introduced by Fukushima et al. (1983). A multichannel correlator is used as a building block of a generic single layer of the neocognitron for shift-invariant feature correlation. Multilayer processing is achieved by iteratively feeding back the output of the feature correlator to the input spatial light modulator. Successful pattern recognition with intraclass fault tolerance and interclass discrimination is achieved using this optoelectronic neocognitron. Detailed system analysis is described. Experimental demonstration of radar signature processing is also provided.
Yniguez, A.T.; McManus, J.W.; DeAngelis, D.L.
2008-01-01
The growth patterns of macroalgae in three-dimensional space can provide important information regarding the environments in which they live, and insights into changes that may occur when those environments change due to anthropogenic and/or natural causes. To decipher these patterns and their attendant mechanisms and influencing factors, a spatially explicit model has been developed. The model SPREAD (SPatially-explicit Reef Algae Dynamics), which incorporates the key morphogenetic characteristics of clonality and morphological plasticity, is used to investigate the influences of light, temperature, nutrients and disturbance on the growth and spatial occupancy of dominant macroalgae in the Florida Reef Tract. The model species, Halimeda and Dictyota spp., are modular organisms, with an 'individual' being made up of repeating structures. These species can also propagate asexually through clonal fragmentation. These traits lead to potentially indefinite growth and plastic morphology that can respond to environmental conditions in various ways. The growth of an individual is modeled as the iteration of discrete macroalgal modules whose dynamics are affected by the light, temperature, and nutrient regimes. Fragmentation is included as a source of asexual reproduction and/or mortality. Model outputs are the same metrics that are obtained in the field, thus allowing for easy comparison. The performance of SPREAD was tested through sensitivity analysis and comparison with independent field data from four study sites in the Florida Reef Tract. Halimeda tuna was selected for initial model comparisons because the relatively untangled growth form permits detailed characterization in the field. Differences in the growth patterns of H. tuna were observed among these reefs. SPREAD was able to closely reproduce these variations, and indicate the potential importance of light and nutrient variations in producing these patterns. ?? 2008 Elsevier B.V.
Soil moisture downscaling using a simple thermal based proxy
NASA Astrophysics Data System (ADS)
Peng, Jian; Loew, Alexander; Niesel, Jonathan
2016-04-01
Microwave remote sensing has been largely applied to retrieve soil moisture (SM) from active and passive sensors. The obvious advantage of microwave sensor is that SM can be obtained regardless of atmospheric conditions. However, existing global SM products only provide observations at coarse spatial resolutions, which often hamper their applications in regional hydrological studies. Therefore, various downscaling methods have been proposed to enhance the spatial resolution of satellite soil moisture products. The aim of this study is to investigate the validity and robustness of a simple Vegetation Temperature Condition Index (VTCI) downscaling scheme over different climates and regions. Both polar orbiting (MODIS) and geostationary (MSG SEVIRI) satellite data are used to improve the spatial resolution of the European Space Agency's Water Cycle Multi-mission Observation Strategy and Climate Change Initiative (ESA CCI) soil moisture, which is a merged product based on both active and passive microwave observations. The results from direct validation against soil moisture in-situ measurements, spatial pattern comparison, as well as seasonal and land use analyses show that the downscaling method can significantly improve the spatial details of CCI soil moisture while maintain the accuracy of CCI soil moisture. The application of the scheme with different satellite platforms and over different regions further demonstrate the robustness and effectiveness of the proposed method. Therefore, the VTCI downscaling method has the potential to facilitate relevant hydrological applications that require high spatial and temporal resolution soil moisture.
Spatial modelling of disease using data- and knowledge-driven approaches.
Stevens, Kim B; Pfeiffer, Dirk U
2011-09-01
The purpose of spatial modelling in animal and public health is three-fold: describing existing spatial patterns of risk, attempting to understand the biological mechanisms that lead to disease occurrence and predicting what will happen in the medium to long-term future (temporal prediction) or in different geographical areas (spatial prediction). Traditional methods for temporal and spatial predictions include general and generalized linear models (GLM), generalized additive models (GAM) and Bayesian estimation methods. However, such models require both disease presence and absence data which are not always easy to obtain. Novel spatial modelling methods such as maximum entropy (MAXENT) and the genetic algorithm for rule set production (GARP) require only disease presence data and have been used extensively in the fields of ecology and conservation, to model species distribution and habitat suitability. Other methods, such as multicriteria decision analysis (MCDA), use knowledge of the causal factors of disease occurrence to identify areas potentially suitable for disease. In addition to their less restrictive data requirements, some of these novel methods have been shown to outperform traditional statistical methods in predictive ability (Elith et al., 2006). This review paper provides details of some of these novel methods for mapping disease distribution, highlights their advantages and limitations, and identifies studies which have used the methods to model various aspects of disease distribution. Copyright © 2011. Published by Elsevier Ltd.
Mapping surface temperature variability on a debris-covered glacier with an unmanned aerial vehicle
NASA Astrophysics Data System (ADS)
Kraaijenbrink, P. D. A.; Litt, M.; Shea, J. M.; Treichler, D.; Koch, I.; Immerzeel, W.
2016-12-01
Debris-covered glacier tongues cover about 12% of the glacier surface in high mountain Asia and much of the melt water is generated from those glaciers. A thin layer of supraglacial debris enhances ice melt by lowering the albedo, while thicker debris insulates the ice and reduces melt. Data on debris thickness is therefore an important input for energy balance modelling of these glaciers. Thermal infrared remote sensing can be used to estimate the debris thickness by using an inverse relation between debris surface temperature and thickness. To date this has only been performed using coarse spaceborne thermal imagery, which cannot reveal small scale variation in debris thickness and its influence on the heterogeneous melt patterns on debris-covered glaciers. We deployed an unmanned aerial vehicle mounted with a thermal infrared sensor over the debris-covered Lirung Glacier in Nepal three times in May 2016 to reveal the spatial and temporal variability of surface temperature in high detail. The UAV survey matched a Landsat 8 overpass to be able to make a comparison with spaceborne thermal imagery. The UAV-acquired data is processed using Structure from Motion photogrammetry and georeferenced using DGPS-measured ground control points. Different surface types were distinguished by using data acquired by an additional optical UAV survey in order to correct for differences in surface emissivity. In situ temperature measurements and incoming solar radiation data are used to calibrate the temperature calculations. Debris thicknesses derived are validated by thickness measurements of a ground penetrating radar. Preliminary analysis reveals a spatially highly heterogeneous pattern of surface temperature over Lirung Glacier with a range in temperature of over 40 K. At dawn the debris is relatively cold and its temperature is influenced strongly by the ice underneath. Exposed to the high solar radiation at the high altitude the debris layer heats up very rapidly as sunrise progresses, and the influence of ice on debris surface temperature reduces considerably. Many patterns are revealed that cannot be detected from the Landsat data, both on small spatial and temporal scales. The high detail the UAV-borne thermal imagery provides in time and space has great potential in the research of debris cover and its characteristics.
Tree species exhibit complex patterns of distribution in bottomland hardwood forests
Luben D Dimov; Jim L Chambers; Brian R. Lockhart
2013-01-01
& Context Understanding tree interactions requires an insight into their spatial distribution. & Aims We looked for presence and extent of tree intraspecific spatial point pattern (random, aggregated, or overdispersed) and interspecific spatial point pattern (independent, aggregated, or segregated). & Methods We established twelve 0.64-ha plots in natural...
Spatial image modulation to improve performance of computed tomography imaging spectrometer
NASA Technical Reports Server (NTRS)
Bearman, Gregory H. (Inventor); Wilson, Daniel W. (Inventor); Johnson, William R. (Inventor)
2010-01-01
Computed tomography imaging spectrometers ("CTIS"s) having patterns for imposing spatial structure are provided. The pattern may be imposed either directly on the object scene being imaged or at the field stop aperture. The use of the pattern improves the accuracy of the captured spatial and spectral information.
Mapping the bycatch seascape: multispecies and multi-scale spatial patterns of fisheries bycatch.
Lewison, Rebecca L; Soykan, Candan U; Franklin, Janet
2009-06-01
Fisheries bycatch is a worldwide conservation issue. Despite a growing awareness of bycatch problems in particular ocean regions, there have been few efforts to identify spatial patterns in bycatch events. Furthermore, many studies of fisheries bycatch have been myopic, focusing on a single species or a single region. Using a range of analytical approaches to identify spatial patterns in bycatch data, we demonstrate the utility and applications of area and point pattern analyses to single and multispecies bycatch seascapes of pelagic longline fisheries in the Atlantic and Pacific Oceans. We find clear evidence of spatial clustering within bycatch species in both ocean basins, both in terms of the underlying pattern of the locations of bycatch events relative to fishing locations and for areas of high bycatch rates. Furthermore, we find significant spatial overlap in the pattern of bycatch across species relative to the spatial distribution in fishing effort and target catch. These results point to the importance of considering spatial patterns of both single and multispecies bycatch to meet the ultimate goal of reducing bycatch encounters. These analyses also highlight the importance of considering bycatch relative to target catch as a way of identifying areas where fishing effort reduction may help to reduce multispecies bycatch with minimal impact on target catch.
Controls on subglacial patterns and depositional environments in western Ireland
NASA Astrophysics Data System (ADS)
Knight, J.
2009-12-01
In western Ireland, Late Devensian ice flow dynamics and resultant patterns of landforms and sediments reflect the interplay between internal (glaciological) forcing and external forcing by rapid climate changes centred on the adjacent Atlantic Ocean. This interplay can be best demonstrated where ice from climatically-sensitive mountain source regions flowed into surrounding lowlands, such as the Connemara region of west County Galway, western Ireland. Here, a semi-independent ice cap was present over the Twelve Bens mountains, and interacted with ice from the much larger regional ice sheet from central Ireland. Landform and sediment patterns in the flat lowland region (c. 100 km2 below 30 m asl) to the south of the Twelve Bens reflect elements of this ice interaction. In detail, landform and sediment distributions here are highly complex with marked spatial differences in patterns of sediment availability. Across much of the region, sculpted bedrock forms (whaleback and bedrock drumlin ridges, roches mountonnées, striae) reflect subglacial abrasion across the underlying igneous and metamorphic bedrock that forms a relatively flat and lake-dominated landscape. Glacigenic sediments are found only at or around ice-retreat margins, and within isolated bedrock valleys. Here, diamicton drumlins are relatively uncommon but yet must represent depositional conditions that are not reflected elsewhere in this ice sheet sector where subglacial sediments are generally absent. This paper explores the interrelationship between local and regional ice flows through their impact on spatial patterns of glacial landforms and sediments. The paper presents field data on the characteristics of bedrock forms (erosional) and diamicton drumlins (depositional). Subglacial sediments are described from drumlin outcrops at key sites around Connemara, which helps in the understanding of the evolution of the subglacial environment in response to ice interactions from different source regions.
le Polain de Waroux, O; Cohuet, S; Ndazima, D; Kucharski, A J; Juan-Giner, A; Flasche, S; Tumwesigye, E; Arinaitwe, R; Mwanga-Amumpaire, J; Boum, Y; Nackers, F; Checchi, F; Grais, R F; Edmunds, W J
2018-04-11
Quantification of human interactions relevant to infectious disease transmission through social contact is central to predict disease dynamics, yet data from low-resource settings remain scarce. We undertook a social contact survey in rural Uganda, whereby participants were asked to recall details about the frequency, type, and socio-demographic characteristics of any conversational encounter that lasted for ≥5 min (henceforth defined as 'contacts') during the previous day. An estimate of the number of 'casual contacts' (i.e. < 5 min) was also obtained. In total, 566 individuals were included in the study. On average participants reported having routine contact with 7.2 individuals (range 1-25). Children aged 5-14 years had the highest frequency of contacts and the elderly (≥65 years) the fewest (P < 0.001). A strong age-assortative pattern was seen, particularly outside the household and increasingly so for contacts occurring further away from home. Adults aged 25-64 years tended to travel more often and further than others, and males travelled more frequently than females. Our study provides detailed information on contact patterns and their spatial characteristics in an African setting. It therefore fills an important knowledge gap that will help more accurately predict transmission dynamics and the impact of control strategies in such areas.
Measuring Memory and Attention to Preview in Motion.
Jagacinski, Richard J; Hammond, Gordon M; Rizzi, Emanuele
2017-08-01
Objective Use perceptual-motor responses to perturbations to reveal the spatio-temporal detail of memory for the recent past and attention to preview when participants track a winding roadway. Background Memory of the recently passed roadway can be inferred from feedback control models of the participants' manual movement patterns. Similarly, attention to preview of the upcoming roadway can be inferred from feedforward control models of manual movement patterns. Method Perturbation techniques were used to measure these memory and attention functions. Results In a laboratory tracking task, the bandwidth of lateral roadway deviations was found to primarily influence memory for the past roadway rather than attention to preview. A secondary auditory/verbal/vocal memory task resulted in higher velocity error and acceleration error in the tracking task but did not affect attention to preview. Attention to preview was affected by the frequency pattern of sinusoidal perturbations of the roadway. Conclusion Perturbation techniques permit measurement of the spatio-temporal span of memory and attention to preview that affect tracking a winding roadway. They also provide new ways to explore goal-directed forgetting and spatially distributed attention in the context of movement. More generally, these techniques provide sensitive measures of individual differences in cognitive aspects of action. Application Models of driving behavior and assessment of driving skill may benefit from more detailed spatio-temporal measurement of attention to preview.
[Spatial point patterns of Antarctic krill fishery in the northern Antarctic Peninsula].
Yang, Xiao Ming; Li, Yi Xin; Zhu, Guo Ping
2016-12-01
As a key species in the Antarctic ecosystem, the spatial distribution of Antarctic krill (thereafter krill) often tends to present aggregation characteristics, which therefore reflects the spatial patterns of krill fishing operation. Based on the fishing data collected from Chinese krill fishing vessels, of which vessel A was professional krill fishing vessel and Vessel B was a fishing vessel which shifted between Chilean jack mackerel (Trachurus murphyi) fishing ground and krill fishing ground. In order to explore the characteristics of spatial distribution pattern and their ecological effects of two obvious different fishing fleets under a high and low nominal catch per unit effort (CPUE), from the viewpoint of spatial point pattern, the present study analyzed the spatial distribution characteristics of krill fishery in the northern Antarctic Peninsula from three aspects: (1) the two vessels' point pattern characteristics of higher CPUEs and lower CPUEs at different scales; (2) correlation of the bivariate point patterns between these points of higher CPUE and lower CPUE; and (3) correlation patterns of CPUE. Under the analysis derived from the Ripley's L function and mark correlation function, the results showed that the point patterns of the higher/lo-wer catch available were similar, both showing an aggregation distribution in this study windows at all scale levels. The aggregation intensity of krill fishing was nearly maximum at 15 km spatial scale, and kept stably higher values at the scale of 15-50 km. The aggregation intensity of krill fishery point patterns could be described in order as higher CPUE of vessel A > lower CPUE of vessel B >higher CPUE of vessel B > higher CPUE of vessel B. The relationship of the higher and lo-wer CPUEs of vessel A showed positive correlation at the spatial scale of 0-75 km, and presented stochastic relationship after 75 km scale, whereas vessel B showed positive correlation at all spatial scales. The point events of higher and lower CPUEs were synchronized, showing significant correlations at most of spatial scales because of the dynamics nature and complex of krill aggregation patterns. The distribution of vessel A's CPUEs was positively correlated at scales of 0-44 km, but negatively correlated at the scales of 44-80 km. The distribution of vessel B's CPUEs was negatively correlated at the scales of 50-70 km, but no significant correlations were found at other scales. The CPUE mark point patterns showed a negative correlation, which indicated that intraspecific competition for space and prey was significant. There were significant differences in spatial point pattern distribution between vessel A with higher fishing capacity and vessel B with lower fishing capacity. The results showed that the professional krill fishing vessel is suitable to conduct the analysis of spatial point pattern and scientific fishery survey.
NASA Technical Reports Server (NTRS)
Johnson, Kirk R.; Hickey, Leo J.
1988-01-01
The spatial and temporal distribution of vegetation in the terminal Cretaceous of Western Interior North America was a complex mosaic resulting from the interaction of factors including a shifting coastline, tectonic activity, a mild, possibly deteriorating climate, dinosaur herbivory, local facies effects, and a hypothesized bolide impact. In order to achieve sufficient resolution to analyze this vegetational pattern, over 100 megafloral collecting sites were established, yielding approximately 15,000 specimens, in Upper Cretaceous and lower Paleocene strata in the Williston, Powder River, and Bighorn basins in North Dakota, Montana, and Wyoming. These localities were integrated into a lithostratigraphic framework that is based on detailed local reference sections and constrained by vertebrate and palynomorph biostratigraphy, magnetostratigraphy, and sedimentary facies analysis. A regional biostratigraphy based on well located and identified plant megafossils that can be used to address patterns of floral evolution, ecology, and extinction is the goal of this research. Results of the analyses are discussed.
California coastal processes study: Skylab. [San Pablo and San Francisco Bays
NASA Technical Reports Server (NTRS)
Pirie, D. M.; Steller, D. D. (Principal Investigator)
1975-01-01
The author has identified the following significant results. In San Pablo Bay, the patterns of dredged sediment discharges were plotted over a three month period. It was found that lithogenous particles, kept in suspension by the fresh water from the Sacramento-San Joaquin, were transported downstream to the estuarine area at varying rates depending on the river discharge level. Skylab collected California coastal imagery at limited times and not at constant intervals. Resolution, however, helped compensate for lack of coverage. Increased spatial and spectral resolution provided details not possible utilizing Landsat imagery. The S-192 data was reformatted; band by band image density stretching was utilized to enhance sediment discharge patterns entrainment, boundaries, and eddys. The 26 January 1974 Skylab 4 imagery of San Francisco Bay was taken during an exceptionally high fresh water and suspended sediment discharge period. A three pronged surface sediment pattern was visible where the Sacramento-San Joaquin Rivers entered San Pablo Bay through Carquinez Strait.
Jiang, Xi Zhuo; Feng, Muye; Ventikos, Yiannis; Luo, Kai H
2018-04-10
Flow patterns on surfaces grafted with complex structures play a pivotal role in many engineering and biomedical applications. In this research, large-scale molecular dynamics (MD) simulations are conducted to study the flow over complex surface structures of an endothelial glycocalyx layer. A detailed structure of glycocalyx has been adopted and the flow/glycocalyx system comprises about 5,800,000 atoms. Four cases involving varying external forces and modified glycocalyx configurations are constructed to reveal intricate fluid behaviour. Flow profiles including temporal evolutions and spatial distributions of velocity are illustrated. Moreover, streamline length and vorticity distributions under the four scenarios are compared and discussed to elucidate the effects of external forces and glycocalyx configurations on flow patterns. Results show that sugar chain configurations affect streamline length distributions but their impact on vorticity distributions is statistically insignificant, whilst the influence of the external forces on both streamline length and vorticity distributions are trivial. Finally, a regime diagram for flow over complex surface structures is proposed to categorise flow patterns.
Vincenot, Christian E; Carteni, Fabrizio; Mazzoleni, Stefano; Rietkerk, Max; Giannino, Francesco
2016-01-01
In simulation models of populations or communities, individual plants have often been obfuscated in favor of aggregated vegetation. This simplification comes with a loss of biological detail and a smoothing out of the demographic noise engendered by stochastic individual-scale processes and heterogeneities, which is significant among others when studying the viability of small populations facing challenging fluctuating environmental conditions. This consideration has motivated the development of precise plant-centered models. The accuracy gained in the representation of plant biology has then, however, often been balanced by the disappearance in models of important plant-soil interactions (esp. water dynamics) due to the inability of most individual-based frameworks to simulate complex continuous processes. In this study, we used a hybrid modeling approach, namely integrated System Dynamics (SD)-Individual-based (IB), to illustrate the importance of individual plant dynamics to explain spatial self-organization of vegetation in arid environments. We analyzed the behavior of this model under different parameter sets either related to individual plant properties (such as seed dispersal distance and reproductive age) or the environment (such as intensity and yearly distribution of precipitation events). While the results of this work confirmed the prevailing theory on vegetation patterning, they also revealed the importance therein of plant-level processes that cannot be rendered by reaction-diffusion models. Initial spatial distribution of plants, reproductive age, and average seed dispersal distance, by impacting patch size and vegetation aggregation, affected pattern formation and population survival under climatic variations. Besides, changes in precipitation regime altered the demographic structure and spatial organization of vegetation patches by affecting plants differentially depending on their age and biomass. Water availability influenced non-linearly total biomass density. Remarkably, lower precipitation resulted in lower mean plant age yet higher mean individual biomass. Moreover, seasonal variations in rainfall greater than a threshold (here, ±0.45 mm from the 1.3 mm baseline) decreased mean total biomass and generated limit cycles, which, in the case of large variations, were preceded by chaotic demographic and spatial behavior. In some cases, peculiar spatial patterns (e.g., rings) were also engendered. On a technical note, the shortcomings of the present model and the benefit of hybrid modeling for virtual investigations in plant science are discussed.
The pattern of spatial flood disaster region in DKI Jakarta
NASA Astrophysics Data System (ADS)
Tambunan, M. P.
2017-02-01
The study of disaster flood area was conducted in DKI Jakarta Province, Indonesia. The aim of this research is: to study the spatial distribution of potential and actual of flood area The flood was studied from the geographic point of view using spatial approach, while the study of the location, the distribution, the depth and the duration of flooding was conducted using geomorphologic approach and emphasize on the detailed landform unit as analysis unit. In this study the landforms in DKI Jakarta have been a diversity, as well as spatial and temporal pattern of the actual and potential flood area. Landform at DKI Jakarta has been largely used as built up area for settlement and it facilities, thus affecting the distribution pattern of flooding area. The collection of the physical condition of landform in DKI Jakarta data prone were conducted through interpretation of the topographic map / RBI map and geological map. The flood data were obtained by survey and secondary data from Kimpraswil (Public Work) of DKI Jakarta Province for 3 years (1996, 2002, and 2007). Data of rainfall were obtained from BMKG and land use data were obtained from BPN DKI Jakarta. The analysis of the causal factors and distribution of flooding was made spatially and temporally using geographic information system. This study used survey method with a pragmatic approach. In this study landform as result from the analytical survey was settlement land use as result the synthetic survey. The primary data consist of landform, and the flood characteristic obtained by survey. The samples were using purposive sampling. Landform map was composed by relief, structure and material stone, and process data Landform map was overlay with flood map the flood prone area in DKI Jakarta Province in scale 1:50,000 to show. Descriptive analysis was used the spatial distribute of the flood prone area. The result of the study show that actual of flood prone area in the north, west and east of Jakarta lowland both in beach ridge, coastal alluvial plain, and alluvial plain; while the flood potential area on the slope is found flat and steep at alluvial fan, alluvial plain, beach ridge, and coastal alluvial plain in DKI Jakarta. Based on the result can be concluded that actual flood prone is not distributed on potential flood prone
Vincenot, Christian E.; Carteni, Fabrizio; Mazzoleni, Stefano; Rietkerk, Max; Giannino, Francesco
2016-01-01
In simulation models of populations or communities, individual plants have often been obfuscated in favor of aggregated vegetation. This simplification comes with a loss of biological detail and a smoothing out of the demographic noise engendered by stochastic individual-scale processes and heterogeneities, which is significant among others when studying the viability of small populations facing challenging fluctuating environmental conditions. This consideration has motivated the development of precise plant-centered models. The accuracy gained in the representation of plant biology has then, however, often been balanced by the disappearance in models of important plant-soil interactions (esp. water dynamics) due to the inability of most individual-based frameworks to simulate complex continuous processes. In this study, we used a hybrid modeling approach, namely integrated System Dynamics (SD)—Individual-based (IB), to illustrate the importance of individual plant dynamics to explain spatial self-organization of vegetation in arid environments. We analyzed the behavior of this model under different parameter sets either related to individual plant properties (such as seed dispersal distance and reproductive age) or the environment (such as intensity and yearly distribution of precipitation events). While the results of this work confirmed the prevailing theory on vegetation patterning, they also revealed the importance therein of plant-level processes that cannot be rendered by reaction-diffusion models. Initial spatial distribution of plants, reproductive age, and average seed dispersal distance, by impacting patch size and vegetation aggregation, affected pattern formation and population survival under climatic variations. Besides, changes in precipitation regime altered the demographic structure and spatial organization of vegetation patches by affecting plants differentially depending on their age and biomass. Water availability influenced non-linearly total biomass density. Remarkably, lower precipitation resulted in lower mean plant age yet higher mean individual biomass. Moreover, seasonal variations in rainfall greater than a threshold (here, ±0.45 mm from the 1.3 mm baseline) decreased mean total biomass and generated limit cycles, which, in the case of large variations, were preceded by chaotic demographic and spatial behavior. In some cases, peculiar spatial patterns (e.g., rings) were also engendered. On a technical note, the shortcomings of the present model and the benefit of hybrid modeling for virtual investigations in plant science are discussed. PMID:27252707
FracPaQ: A MATLAB™ toolbox for the quantification of fracture patterns
NASA Astrophysics Data System (ADS)
Healy, David; Rizzo, Roberto E.; Cornwell, David G.; Farrell, Natalie J. C.; Watkins, Hannah; Timms, Nick E.; Gomez-Rivas, Enrique; Smith, Michael
2017-02-01
The patterns of fractures in deformed rocks are rarely uniform or random. Fracture orientations, sizes, and spatial distributions often exhibit some kind of order. In detail, relationships may exist among the different fracture attributes, e.g. small fractures dominated by one orientation, larger fractures by another. These relationships are important because the mechanical (e.g. strength, anisotropy) and transport (e.g. fluids, heat) properties of rock depend on these fracture attributes and patterns. This paper describes FracPaQ, a new open source, cross-platform toolbox to quantify fracture patterns, including distributions in fracture attributes and their spatial variation. Software has been developed to quantify fracture patterns from 2-D digital images, such as thin section micrographs, geological maps, outcrop or aerial photographs or satellite images. The toolbox comprises a suite of MATLAB™ scripts based on previously published quantitative methods for the analysis of fracture attributes: orientations, lengths, intensity, density and connectivity. An estimate of permeability in 2-D is made using a parallel plate model. The software provides an objective and consistent methodology for quantifying fracture patterns and their variations in 2-D across a wide range of length scales, rock types and tectonic settings. The implemented methods presented are inherently scale independent, and a key task where applicable is analysing and integrating quantitative fracture pattern data from micro-to macro-scales. The toolbox was developed in MATLAB™ and the source code is publicly available on GitHub™ and the Mathworks™ FileExchange. The code runs on any computer with MATLAB installed, including PCs with Microsoft Windows, Apple Macs with Mac OS X, and machines running different flavours of Linux. The application, source code and sample input files are available in open repositories in the hope that other developers and researchers will optimise and extend the functionality for the benefit of the wider community.
Downscaling Thermal Infrared Radiance for Subpixel Land Surface Temperature Retrieval
Liu, Desheng; Pu, Ruiliang
2008-01-01
Land surface temperature (LST) retrieved from satellite thermal sensors often consists of mixed temperature components. Retrieving subpixel LST is therefore needed in various environmental and ecological studies. In this paper, we developed two methods for downscaling coarse resolution thermal infrared (TIR) radiance for the purpose of subpixel temperature retrieval. The first method was developed on the basis of a scale-invariant physical model on TIR radiance. The second method was based on a statistical relationship between TIR radiance and land cover fraction at high spatial resolution. The two methods were applied to downscale simulated 990-m ASTER TIR data to 90-m resolution. When validated against the original 90-m ASTER TIR data, the results revealed that both downscaling methods were successful in capturing the general patterns of the original data and resolving considerable spatial details. Further quantitative assessments indicated a strong agreement between the true values and the estimated values by both methods. PMID:27879844
Downscaling Thermal Infrared Radiance for Subpixel Land Surface Temperature Retrieval.
Liu, Desheng; Pu, Ruiliang
2008-04-06
Land surface temperature (LST) retrieved from satellite thermal sensors often consists of mixed temperature components. Retrieving subpixel LST is therefore needed in various environmental and ecological studies. In this paper, we developed two methods for downscaling coarse resolution thermal infrared (TIR) radiance for the purpose of subpixel temperature retrieval. The first method was developed on the basis of a scale-invariant physical model on TIR radiance. The second method was based on a statistical relationship between TIR radiance and land cover fraction at high spatial resolution. The two methods were applied to downscale simulated 990-m ASTER TIR data to 90-m resolution. When validated against the original 90-m ASTER TIR data, the results revealed that both downscaling methods were successful in capturing the general patterns of the original data and resolving considerable spatial details. Further quantitative assessments indicated a strong agreement between the true values and the estimated values by both methods.
Designing exotic many-body states of atomic spin and motion in photonic crystals.
Manzoni, Marco T; Mathey, Ludwig; Chang, Darrick E
2017-03-08
Cold atoms coupled to photonic crystals constitute an exciting platform for exploring quantum many-body physics. For example, such systems offer the potential to realize strong photon-mediated forces between atoms, which depend on the atomic internal (spin) states, and where both the motional and spin degrees of freedom can exhibit long coherence times. An intriguing question then is whether exotic phases could arise, wherein crystalline or other spatial patterns and spin correlations are fundamentally tied together, an effect that is atypical in condensed matter systems. Here, we analyse one realistic model Hamiltonian in detail. We show that this previously unexplored system exhibits a rich phase diagram of emergent orders, including spatially dimerized spin-entangled pairs, a fluid of composite particles comprised of joint spin-phonon excitations, phonon-induced Néel ordering, and a fractional magnetization plateau associated with trimer formation.
Butler, D.R.; Malanson, G.P.; Walsh, S.J.; Fagre, D.B.
2007-01-01
The spatial distribution and pattern of alpine treeline in the American West reflect the overarching influences of geological history, lithology and structure, and geomorphic processes and landforms, and geologic and geomorphic factors—both forms and processes—can control the spatiotemporal response of the ecotone to climate change. These influences occur at spatial scales ranging from the continental scale to fine scale processes and landforms at the slope scale. Past geomorphic influences, particularly Pleistocene glaciation, have also left their impact on treeline, and treelines across the west are still adjusting to post-Pleistocene conditions within Pleistocene-created landforms. Current fine scale processes include solifluction and changes on relict solifluction and digging by animals. These processes should be examined in detail in future studies to facilitate a better understanding of where individual tree seedlings become established as a primary response of the ecotone to climate change.
Mapping Greenland’s mass loss in space and time
Harig, Christopher; Simons, Frederik J.
2012-01-01
The melting of polar ice sheets is a major contributor to global sea-level rise. Early estimates of the mass lost from the Greenland ice cap, based on satellite gravity data collected by the Gravity Recovery and Climate Experiment, have widely varied. Although the continentally and decadally averaged estimated trends have now more or less converged, to this date, there has been little clarity on the detailed spatial distribution of Greenland’s mass loss and how the geographical pattern has varied on relatively shorter time scales. Here, we present a spatially and temporally resolved estimation of the ice mass change over Greenland between April of 2002 and August of 2011. Although the total mass loss trend has remained linear, actively changing areas of mass loss were concentrated on the southeastern and northwestern coasts, with ice mass in the center of Greenland steadily increasing over the decade. PMID:23169646
Finger vein recognition with personalized feature selection.
Xi, Xiaoming; Yang, Gongping; Yin, Yilong; Meng, Xianjing
2013-08-22
Finger veins are a promising biometric pattern for personalized identification in terms of their advantages over existing biometrics. Based on the spatial pyramid representation and the combination of more effective information such as gray, texture and shape, this paper proposes a simple but powerful feature, called Pyramid Histograms of Gray, Texture and Orientation Gradients (PHGTOG). For a finger vein image, PHGTOG can reflect the global spatial layout and local details of gray, texture and shape. To further improve the recognition performance and reduce the computational complexity, we select a personalized subset of features from PHGTOG for each subject by using the sparse weight vector, which is trained by using LASSO and called PFS-PHGTOG. We conduct extensive experiments to demonstrate the promise of the PHGTOG and PFS-PHGTOG, experimental results on our databases show that PHGTOG outperforms the other existing features. Moreover, PFS-PHGTOG can further boost the performance in comparison with PHGTOG.
Finger Vein Recognition with Personalized Feature Selection
Xi, Xiaoming; Yang, Gongping; Yin, Yilong; Meng, Xianjing
2013-01-01
Finger veins are a promising biometric pattern for personalized identification in terms of their advantages over existing biometrics. Based on the spatial pyramid representation and the combination of more effective information such as gray, texture and shape, this paper proposes a simple but powerful feature, called Pyramid Histograms of Gray, Texture and Orientation Gradients (PHGTOG). For a finger vein image, PHGTOG can reflect the global spatial layout and local details of gray, texture and shape. To further improve the recognition performance and reduce the computational complexity, we select a personalized subset of features from PHGTOG for each subject by using the sparse weight vector, which is trained by using LASSO and called PFS-PHGTOG. We conduct extensive experiments to demonstrate the promise of the PHGTOG and PFS-PHGTOG, experimental results on our databases show that PHGTOG outperforms the other existing features. Moreover, PFS-PHGTOG can further boost the performance in comparison with PHGTOG. PMID:23974154
Multiscale assessment of landscape structure in heterogeneous forested area
NASA Astrophysics Data System (ADS)
Simoniello, T.; Pignatti, S.; Carone, M. T.; Fusilli, L.; Lanfredi, M.; Coppola, R.; Santini, F.
2010-05-01
The characterization of landscape structure in space or time is fundamental to infer ecological processes (Ingegnoli, 2002). Landscape pattern arrangements strongly influence forest ecological functioning and biodiversity, as an example landscape fragmentation can induce habitat degradation reducing forest species populations or limiting their recolonization. Such arrangements are spatially correlated and scale-dependent, therefore they have distinctive operational-scales at which they can be best characterized (Wu, 2004). In addition, the detail of the land cover classification can have substantial influences on resulting pattern quantification (Greenberg et al.2001). In order to evaluate the influence of the observational scales and labelling details, we investigated a forested area (Pollino National Park; southern Italy) by analyzing the patch arrangement derived from three remote sensing sensors having different spectral and spatial resolutions. In particular, we elaborated data from the hyperspectral MIVIS (102 bands; ~7m) and Hyperion (220 bands; 30m), and the multispectral Landsat-TM (7 bands; 30m). Moreover, to assess the landscape evolution we investigated the hierarchical structure of the study area (landscape, class, patch) by elaborating two Landsat-TM acquired in 1987 and 1998. Preprocessed data were classified by adopting a supervised procedure based on the Minimum Distance classifier. The obtained labelling correspond to Corine level 5 for the high resolution MIVIS data, to Corine level 4 for Hyperion and to an intermediate level 4-3 for TM data. The analysis was performed by taking into account patch density, diversity and evenness at landscape level; mean patch size and interdispersion at class level; patch structure and perimeter regularity at patch level. The three sensors described a landscape with a quite high level of richness and distribution. The high spectral and spatial resolution of MIVIS data provided the highest diversity level (SHDI = 2.05), even if the results obtained for TM were not so different (1.93), Hyperion showed the lowest value (1.79). The obtained evenness index was similar for all the landscapes (~ 0.72). At class level, the interdispersion increases as the spatial and spectral resolution power decrease. Due to the low labelling detail, TM classes represent an aggregation of MIVIS and Hyperion classes; therefore they result larger and more diffused over the territory favouring higher interspersion values in the computation. The investigation of the patch structure highlighted the highest MIVIS capability in describing the patch articulation; Hyperion and TM showed quite similar situation. The historical analysis based on TM imagery showed a fragmentation process for some forested patches (mainly beeches): an increase of structure complexity (higher FRACT) is coupled with a higher patch number and an extension reduction. On the whole, the obtained results showed that the multispectral Landsat-TM images represent a good data source for supporting studies on landscape structure of forested areas and that for analyzing the articulation of particular species the high spectral resolution needs to be coupled with a high spatial resolution, i.e. Hyperion sampling is not adequate for such a purpose.
Contrasting activity patterns of sympatric and allopatric black and grizzly bears
Schwartz, C.C.; Cain, S.L.; Podruzny, S.; Cherry, S.; Frattaroli, L.
2010-01-01
The distribution of grizzly (Ursus arctos) and American black bears (U. americanus) overlaps in western North America. Few studies have detailed activity patterns where the species are sympatric and no studies contrasted patterns where populations are both sympatric and allopatric. We contrasted activity patterns for sympatric black and grizzly bears and for black bears allopatric to grizzly bears, how human influences altered patterns, and rates of grizzlyblack bear predation. Activity patterns differed between black bear populations, with those sympatric to grizzly bears more day-active. Activity patterns of black bears allopatric with grizzly bears were similar to those of female grizzly bears; both were crepuscular and day-active. Male grizzly bears were crepuscular and night-active. Both species were more night-active and less day-active when ???1 km from roads or developments. In our sympatric study area, 2 of 4 black bear mortalities were due to grizzly bear predation. Our results suggested patterns of activity that allowed for intra- and inter-species avoidance. National park management often results in convergence of locally high human densities in quality bear habitat. Our data provide additional understanding into how bears alter their activity patterns in response to other bears and humans and should help park managers minimize undesirable bearhuman encounters when considering needs for temporal and spatial management of humans and human developments in bear habitats. ?? 2010 The Wildlife Society.
Crop yield response to climate change varies with crop spatial distribution pattern
Leng, Guoyong; Huang, Maoyi
2017-05-03
The linkage between crop yield and climate variability has been confirmed in numerous studies using statistical approaches. A crucial assumption in these studies is that crop spatial distribution pattern is constant over time. Here, we explore how changes in county-level corn spatial distribution pattern modulate the response of its yields to climate change at the state level over the Contiguous United States. Our results show that corn yield response to climate change varies with crop spatial distribution pattern, with distinct impacts on the magnitude and even the direction at the state level. Corn yield is predicted to decrease by 20~40%more » by 2050s when considering crop spatial distribution pattern changes, which is 6~12% less than the estimates with fixed cropping pattern. The beneficial effects are mainly achieved by reducing the negative impacts of daily maximum temperature and strengthening the positive impacts of precipitation. Our results indicate that previous empirical studies could be biased in assessing climate change impacts by ignoring the changes in crop spatial distribution pattern. As a result, this has great implications for understanding the increasing debates on whether climate change will be a net gain or loss for regional agriculture.« less
Crop yield response to climate change varies with crop spatial distribution pattern
DOE Office of Scientific and Technical Information (OSTI.GOV)
Leng, Guoyong; Huang, Maoyi
The linkage between crop yield and climate variability has been confirmed in numerous studies using statistical approaches. A crucial assumption in these studies is that crop spatial distribution pattern is constant over time. Here, we explore how changes in county-level corn spatial distribution pattern modulate the response of its yields to climate change at the state level over the Contiguous United States. Our results show that corn yield response to climate change varies with crop spatial distribution pattern, with distinct impacts on the magnitude and even the direction at the state level. Corn yield is predicted to decrease by 20~40%more » by 2050s when considering crop spatial distribution pattern changes, which is 6~12% less than the estimates with fixed cropping pattern. The beneficial effects are mainly achieved by reducing the negative impacts of daily maximum temperature and strengthening the positive impacts of precipitation. Our results indicate that previous empirical studies could be biased in assessing climate change impacts by ignoring the changes in crop spatial distribution pattern. As a result, this has great implications for understanding the increasing debates on whether climate change will be a net gain or loss for regional agriculture.« less
Incorporating Human Movement Behavior into the Analysis of Spatially Distributed Infrastructure.
Wu, Lihua; Leung, Henry; Jiang, Hao; Zheng, Hong; Ma, Li
2016-01-01
For the first time in human history, the majority of the world's population resides in urban areas. Therefore, city managers are faced with new challenges related to the efficiency, equity and quality of the supply of resources, such as water, food and energy. Infrastructure in a city can be viewed as service points providing resources. These service points function together as a spatially collaborative system to serve an increasing population. To study the spatial collaboration among service points, we propose a shared network according to human's collective movement and resource usage based on data usage detail records (UDRs) from the cellular network in a city in western China. This network is shown to be not scale-free, but exhibits an interesting triangular property governed by two types of nodes with very different link patterns. Surprisingly, this feature is consistent with the urban-rural dualistic context of the city. Another feature of the shared network is that it consists of several spatially separated communities that characterize local people's active zones but do not completely overlap with administrative areas. According to these features, we propose the incorporation of human movement into infrastructure classification. The presence of well-defined spatially separated clusters confirms the effectiveness of this approach. In this paper, our findings reveal the spatial structure inside a city, and the proposed approach provides a new perspective on integrating human movement into the study of a spatially distributed system.
NASA Astrophysics Data System (ADS)
Edwards, Clinton B.; Eynaud, Yoan; Williams, Gareth J.; Pedersen, Nicole E.; Zgliczynski, Brian J.; Gleason, Arthur C. R.; Smith, Jennifer E.; Sandin, Stuart A.
2017-12-01
For sessile organisms such as reef-building corals, differences in the degree of dispersion of individuals across a landscape may result from important differences in life-history strategies or may reflect patterns of habitat availability. Descriptions of spatial patterns can thus be useful not only for the identification of key biological and physical mechanisms structuring an ecosystem, but also by providing the data necessary to generate and test ecological theory. Here, we used an in situ imaging technique to create large-area photomosaics of 16 plots at Palmyra Atoll, central Pacific, each covering 100 m2 of benthic habitat. We mapped the location of 44,008 coral colonies and identified each to the lowest taxonomic level possible. Using metrics of spatial dispersion, we tested for departures from spatial randomness. We also used targeted model fitting to explore candidate processes leading to differences in spatial patterns among taxa. Most taxa were clustered and the degree of clustering varied by taxon. A small number of taxa did not significantly depart from randomness and none revealed evidence of spatial uniformity. Importantly, taxa that readily fragment or tolerate stress through partial mortality were more clustered. With little exception, clustering patterns were consistent with models of fragmentation and dispersal limitation. In some taxa, dispersion was linearly related to abundance, suggesting density dependence of spatial patterning. The spatial patterns of stony corals are non-random and reflect fundamental life-history characteristics of the taxa, suggesting that the reef landscape may, in many cases, have important elements of spatial predictability.
Mapping Sleeping Bees within Their Nest: Spatial and Temporal Analysis of Worker Honey Bee Sleep
Klein, Barrett Anthony; Stiegler, Martin; Klein, Arno; Tautz, Jürgen
2014-01-01
Patterns of behavior within societies have long been visualized and interpreted using maps. Mapping the occurrence of sleep across individuals within a society could offer clues as to functional aspects of sleep. In spite of this, a detailed spatial analysis of sleep has never been conducted on an invertebrate society. We introduce the concept of mapping sleep across an insect society, and provide an empirical example, mapping sleep patterns within colonies of European honey bees (Apis mellifera L.). Honey bees face variables such as temperature and position of resources within their colony's nest that may impact their sleep. We mapped sleep behavior and temperature of worker bees and produced maps of their nest's comb contents as the colony grew and contents changed. By following marked bees, we discovered that individuals slept in many locations, but bees of different worker castes slept in different areas of the nest relative to position of the brood and surrounding temperature. Older worker bees generally slept outside cells, closer to the perimeter of the nest, in colder regions, and away from uncapped brood. Younger worker bees generally slept inside cells and closer to the center of the nest, and spent more time asleep than awake when surrounded by uncapped brood. The average surface temperature of sleeping foragers was lower than the surface temperature of their surroundings, offering a possible indicator of sleep for this caste. We propose mechanisms that could generate caste-dependent sleep patterns and discuss functional significance of these patterns. PMID:25029445
Spatial patterns of development drive water use
G. M. Sanchez; J. W. Smith; A. Terando; G. Sun; R. K. Meentemeyer
2018-01-01
Water availability is becoming more uncertain as human populations grow, cities expand into rural regions and the climate changes. In this study, we examine the functional relationship between water use and the spatial patterns of developed land across the rapidly growing region of the southeastern United States. We quantified the spatial pattern of developed land...
Behavioral states may be associated with distinct spatial patterns in electrocorticogram.
Panagiotides, Heracles; Freeman, Walter J; Holmes, Mark D; Pantazis, Dimitrios
2011-03-01
To determine if behavioral states are associated with unique spatial electrocorticographic (ECoG) patterns, we obtained recordings with a microgrid electrode array applied to the cortical surface of a human subject. The array was constructed with the intent of extracting maximal spatial information by optimizing interelectrode distances. A 34-year-old patient with intractable epilepsy underwent intracranial ECoG monitoring after standard methods failed to reveal localization of seizures. During the 8-day period of invasive recording, in addition to standard clinical electrodes a square 1 × 1 cm microgrid array with 64 electrodes (1.25 mm separation) was placed on the right inferior temporal gyrus. Careful review of video recordings identified four extended naturalistic behaviors: reading, conversing on the telephone, looking at photographs, and face-to-face interactions. ECoG activity recorded with the microgrid that corresponded to these behaviors was collected and ECoG spatial patterns were analyzed. During periods of ECoG selected for analysis, no electrographic seizures or epileptiform patterns were present. Moments of maximal spatial variance are shown to cluster by behavior. Comparisons between conditions using a permutation test reveal significantly different spatial patterns for each behavior. We conclude that ECoG recordings obtained on the cortical surface with optimal high spatial frequency resolution reveal distinct local spatial patterns that reflect different behavioral states, and we predict that similar patterns will be found in many if not most cortical areas on which a microgrid is placed.
Meta-image navigation augmenters for GPS denied mountain navigation of small UAS
NASA Astrophysics Data System (ADS)
Wang, Teng; ćelik, Koray; Somani, Arun K.
2014-06-01
We present a novel approach to use mountain drainage patterns for GPS-Denied navigation of small unmanned aerial systems (UAS) such as the ScanEagle, utilizing a down-looking fixed focus monocular imager. Our proposal allows extension of missions to GPS-denied mountain areas, with no assumption of human-made geographic objects. We leverage the analogy between mountain drainage patterns, human arteriograms, and human fingerprints, to match local drainage patterns to Graphics Processing Unit (GPU) rendered parallax occlusion maps of geo-registered radar returns (GRRR). Details of our actual GPU algorithm is beyond the subject of this paper, and is planned as a future paper. The matching occurs in real-time, while GRRR data is loaded on-board the aircraft pre-mission, so as not to require a scanning aperture radar during the mission. For recognition purposes, we represent a given mountain area with a set of spatially distributed mountain minutiae, i.e., details found in the drainage patterns, so that conventional minutiae-based fingerprint matching approaches can be used to match real-time camera image against template images in the training set. We use medical arteriography processing techniques to extract the patterns. The minutiae-based representation of mountains is achieved by first exposing mountain ridges and valleys with a series of filters and then extracting mountain minutiae from these ridges/valleys. Our results are experimentally validated on actual terrain data and show the effectiveness of minutiae-based mountain representation method. Furthermore, we study how to select landmarks for UAS navigation based on the proposed mountain representation and give a set of examples to show its feasibility. This research was in part funded by Rockwell Collins Inc.
An integrated theory of attention and decision making in visual signal detection.
Smith, Philip L; Ratcliff, Roger
2009-04-01
The simplest attentional task, detecting a cued stimulus in an otherwise empty visual field, produces complex patterns of performance. Attentional cues interact with backward masks and with spatial uncertainty, and there is a dissociation in the effects of these variables on accuracy and on response time. A computational theory of performance in this task is described. The theory links visual encoding, masking, spatial attention, visual short-term memory (VSTM), and perceptual decision making in an integrated dynamic framework. The theory assumes that decisions are made by a diffusion process driven by a neurally plausible, shunting VSTM. The VSTM trace encodes the transient outputs of early visual filters in a durable form that is preserved for the time needed to make a decision. Attention increases the efficiency of VSTM encoding, either by increasing the rate of trace formation or by reducing the delay before trace formation begins. The theory provides a detailed, quantitative account of attentional effects in spatial cuing tasks at the level of response accuracy and the response time distributions. (c) 2009 APA, all rights reserved
NASA Astrophysics Data System (ADS)
Bergström, Per; Lindegarth, Susanne; Lindegarth, Mats
2013-10-01
Human pressures on coastal seas are increasing and methods for sustainable management, including spatial planning and mitigative actions, are therefore needed. In coastal areas worldwide, the development of mussel farming as an economically and ecologically sustainable industry requires geographic information on the growth and potential production capacity. In practice this means that coherent maps of temporally stable spatial patterns of growth need to be available in the planning process and that maps need to be based on mechanistic or empirical models. Therefore, as a first step towards development of models of growth, we assessed empirically the fundamental requirement that there are temporally consistent spatial patterns of growth in the blue mussel, Mytilus edulis. Using a pilot study we designed and dimensioned a transplant experiment, where the spatial consistency in the growth of mussels was evaluated at two resolutions. We found strong temporal and scale-dependent spatial variability in growth but patterns suggested that spatial patterns were uncoupled between growth of shell and that of soft tissue. Spatial patterns of shell growth were complex and largely inconsistent among years. Importantly, however, the growth of soft tissue was qualitatively consistent among years at the scale of km. The results suggest that processes affecting the whole coastal area cause substantial differences in growth of soft tissue among years but that factors varying at the scale of km create strong and persistent spatial patterns of growth, with a potential doubling of productivity by identifying the most suitable locations. We conclude that the observed spatial consistency provides a basis for further development of predictive modelling and mapping of soft tissue growth in these coastal areas. Potential causes of observed patterns, consequences for mussel-farming as a tool for mitigating eutrophication, aspects of precision of modelling and sampling of mussel growth as well as ecological functions in general are discussed.
Nameda, N
1988-01-01
Illumination allows solid object perception to be obtained and depicted by a shading pattern produced by lighting. The shading cue, as one of solid perception cues (Gibson 1979), was investigated in regard to a white corrugated wave shape, using computer graphic device: Tospix-2. The reason the corrugated wave was chosen, is that an alternately bright and dark pattern, produced by shading, can be conveniently analyzed into contained spatial frequencies. This paper reports spatial frequency properties contained in the shading pattern. The shading patterns, input into the computer graphic device, are analyzed by Fourier Transformation by the same device. After the filtration by various spatial frequency low and high pass filters, Inverse Fourier Transformation is carried out for the residual components. The result of the analysis indicates that the third through higher harmonics components are important in regard to presenting a solid reality feeling in solid perception. Sakata (1983) also reported that an edged pattern, superimposed onto a lower sinusoidal pattern, was important in solid perception. The third through higher harmonics components express the changing position of luminance on the pattern, and a slanted plane relating to the light direction. Detection of a solid shape, constructed with flat planes, is assumed to be on the bottom of the perfect curved solid perception mechanism. Apparent evidence for this assumption, in difficult visual conditions, is that a flat paneled solid is seen before the curved solid. This mechanism is explained by two spatial frequency neural network systems, assumed as having correspondence with higher spatial frequency detection and lower spatial frequency detection.
Spatial Patterns of Inshore Marine Soundscapes.
McWilliam, Jamie
2016-01-01
Passive acoustic monitoring was employed to investigate spatial patterns of soundscapes within a marine reserve. High energy level broadband snaps dominated nearly all habitat soundscapes. Snaps, the principal acoustic feature of soundscapes, were primarily responsible for the observed spatial patterns, and soundscapes appeared to retain a level of compositional and configurational stability. In the presence of high-level broadband snaps, soundscape composition was more influenced by geographic location than habitat type. Future research should focus on investigating the spatial patterns of soundscapes across a wider range of coastal and offshore seascapes containing a variety of distinct ecosystems and habitats.
Boundary-induced pattern formation from uniform temporal oscillation
NASA Astrophysics Data System (ADS)
Kohsokabe, Takahiro; Kaneko, Kunihiko
2018-04-01
Pattern dynamics triggered by fixing a boundary is investigated. By considering a reaction-diffusion equation that has a unique spatially uniform and limit cycle attractor under a periodic or Neumann boundary condition, and then by choosing a fixed boundary condition, we found three novel phases depending on the ratio of diffusion constants of activator to inhibitor: transformation of temporally periodic oscillation into a spatially periodic fixed pattern, travelling wave emitted from the boundary, and aperiodic spatiotemporal dynamics. The transformation into a fixed, periodic pattern is analyzed by crossing of local nullclines at each spatial point, shifted by diffusion terms, as is analyzed by using recursive equations, to obtain the spatial pattern as an attractor. The generality of the boundary-induced pattern formation as well as its relevance to biological morphogenesis is discussed.
NASA Astrophysics Data System (ADS)
Tao, Ye; Gu, Huaguang; Ding, Xueli
2017-10-01
Spiral waves were observed in the biological experiment on rat brain cortex with the application of carbachol and bicuculline which can block inhibitory coupling from interneurons to pyramidal neurons. To simulate the experimental spiral waves, a two-dimensional neuronal network composed of pyramidal neurons and inhibitory interneurons was built. By decreasing the percentage of active inhibitory interneurons, the random-like spatial patterns change to spiral waves and to random-like spatial patterns or nearly synchronous behaviors. The spiral waves appear at a low percentage of inhibitory interneurons, which matches the experimental condition that inhibitory couplings of the interneurons were blocked. The spiral waves exhibit a higher order or signal-to-noise ratio (SNR) characterized by spatial structure function than both random-like spatial patterns and nearly synchronous behaviors, which shows that changes of the percentage of active inhibitory interneurons can induce spatial coherence resonance-like behaviors. In addition, the relationship between the coherence degree and the spatial structures of the spiral waves is identified. The results not only present a possible and reasonable interpretation to the spiral waves observed in the biological experiment on the brain cortex with disinhibition, but also reveal that the spiral waves exhibit more ordered degree in spatial patterns.
Integrating spatial and numerical structure in mathematical patterning
NASA Astrophysics Data System (ADS)
Ni’mah, K.; Purwanto; Irawan, E. B.; Hidayanto, E.
2018-03-01
This paper reports a study monitoring the integrating spatial and numerical structure in mathematical patterning skills of 30 students grade 7th of junior high school. The purpose of this research is to clarify the processes by which learners construct new knowledge in mathematical patterning. Findings indicate that: (1) students are unable to organize the structure of spatial and numerical, (2) students were only able to organize the spatial structure, but the numerical structure is still incorrect, (3) students were only able to organize numerical structure, but its spatial structure is still incorrect, (4) students were able to organize both of the spatial and numerical structure.
NASA Astrophysics Data System (ADS)
Castaldo, Raffaele; Gola, Gianluca; Santilano, Alessandro; De Novellis, Vincenzo; Pepe, Susi; Manzo, Mariarosaria; Manzella, Adele; Tizzani, Pietro
2017-04-01
We present a model able to simulate the physical process responsible for the long-term ground deformation of Ischia Island Volcano (Southern Italy) by considering the role of the thermo-rheological properties of the crust. To this aim, we develop and implement in a Finite Element (FE) environment an innovative approach that integrates and homogenizes a large amount of data derived from several and different observation techniques (i.e, geological, geophysical and remote sensing). In detail, the main steps of the proposed approach are: (i) the generation of a 3D geological model of the crust beneath the Island by merging the available geological and geophysical information; (ii) the optimization of a 3D thermal model by exploiting the thermal measurements available in literature; (iii) the definition of the 3D B/D (Brittle/Ductile) transition by using the temperature distribution of the crust and the physical information of the rocks; (iv) the optimization of the ground deformation velocity model (that takes into account the rheological stratification) by considering the spatial and temporal information detected via satellite multi-orbit C-Band SAR (Synthetic Aperture Radar) measurements acquired during the 1992-2010 time period. The achieved results allow investigating the physical process responsible for the observed ground deformation pattern. In particular, they reveal how the rheology modulates the spatial and temporal evolution of long-term subsidence phenomenon, highlighting a coupling effect of the viscosities of the rocks and the gravitational loading of the volcano edifice. Moreover, the achieved results provide a very detailed and realistic image of the subsurface crust of the Ischia Island Volcano in order to study the ongoing deformation phenomena.
NASA Astrophysics Data System (ADS)
Castaldo, R.; Gola, G.; Santilano, A.; De Novellis, V.; Pepe, S.; Manzo, M.; Manzella, A.; Tizzani, P.
2017-09-01
In this paper we develop a model of the ground deformation behaviour occurred at Ischia Island (Southern Italy) in the 1992-2010 time period. The model is employed to investigate the forces and physical parameters of the crust controlling the subsidence of the Island. To this aim, we integrate and homogenize in a Finite Element (FE) environment a large amount of data derived from several and different observation techniques (i.e., geological, geophysical and remote sensing). In detail, the main steps of the multiphysics model are: (i) the generation of a 3D geological model of the crust beneath the Island by merging the available geological and geophysical information; (ii) the optimization of a 3D thermal model by exploiting the thermal measurements available in literature; (iii) the definition of the 3D Brittle/Ductile transition by using the temperature distribution of the crust and the physical information of the rocks; (iv) the optimization of the ground deformation velocity model (that takes into account the rheological stratification) by considering the spatial and temporal information detected via satellite multi-orbit C-Band SAR (Synthetic Aperture Radar) measurements acquired during the 1992-2010 time period. The achieved results allow investigating the physical process responsible for the observed ground deformation pattern. In particular, they reveal how the rheology modulates the spatial and temporal evolution of the long-term subsidence phenomenon, highlighting a coupling effect of the viscosities of the rocks and the gravitational loading of the volcano edifice. Moreover, the achieved results provide a very detailed and realistic velocity field image of the subsurface crust of the Ischia Island Volcano.
The linkages between photosynthesis, productivity, growth and biomass in lowland Amazonian forests.
Malhi, Yadvinder; Doughty, Christopher E; Goldsmith, Gregory R; Metcalfe, Daniel B; Girardin, Cécile A J; Marthews, Toby R; Del Aguila-Pasquel, Jhon; Aragão, Luiz E O C; Araujo-Murakami, Alejandro; Brando, Paulo; da Costa, Antonio C L; Silva-Espejo, Javier E; Farfán Amézquita, Filio; Galbraith, David R; Quesada, Carlos A; Rocha, Wanderley; Salinas-Revilla, Norma; Silvério, Divino; Meir, Patrick; Phillips, Oliver L
2015-06-01
Understanding the relationship between photosynthesis, net primary productivity and growth in forest ecosystems is key to understanding how these ecosystems will respond to global anthropogenic change, yet the linkages among these components are rarely explored in detail. We provide the first comprehensive description of the productivity, respiration and carbon allocation of contrasting lowland Amazonian forests spanning gradients in seasonal water deficit and soil fertility. Using the largest data set assembled to date, ten sites in three countries all studied with a standardized methodology, we find that (i) gross primary productivity (GPP) has a simple relationship with seasonal water deficit, but that (ii) site-to-site variations in GPP have little power in explaining site-to-site spatial variations in net primary productivity (NPP) or growth because of concomitant changes in carbon use efficiency (CUE), and conversely, the woody growth rate of a tropical forest is a very poor proxy for its productivity. Moreover, (iii) spatial patterns of biomass are much more driven by patterns of residence times (i.e. tree mortality rates) than by spatial variation in productivity or tree growth. Current theory and models of tropical forest carbon cycling under projected scenarios of global atmospheric change can benefit from advancing beyond a focus on GPP. By improving our understanding of poorly understood processes such as CUE, NPP allocation and biomass turnover times, we can provide more complete and mechanistic approaches to linking climate and tropical forest carbon cycling. © 2015 John Wiley & Sons Ltd.
Spatial gender-age-period-cohort analysis of pancreatic cancer mortality in Spain (1990–2013)
Etxeberria, Jaione; Goicoa, Tomás; López-Abente, Gonzalo; Riebler, Andrea
2017-01-01
Recently, the interest in studying pancreatic cancer mortality has increased due to its high lethality. In this work a detailed analysis of pancreatic cancer mortality in Spanish provinces was performed using recent data. A set of multivariate spatial gender-age-period-cohort models was considered to look for potential candidates to analyze pancreatic cancer mortality rates. The selected model combines features of APC (age-period-cohort) models with disease mapping approaches. To ensure model identifiability sum-to-zero constraints were applied. A fully Bayesian approach based on integrated nested Laplace approximations (INLA) was considered for model fitting and inference. Sensitivity analyses were also conducted. In general, estimated average rates by age, cohort, and period are higher in males than in females. The higher differences according to age between males and females correspond to the age groups [65, 70), [70, 75), and [75, 80). Regarding the cohort, the greatest difference between men and women is observed for those born between the forties and the sixties. From there on, the younger the birth cohort is, the smaller the difference becomes. Some cohort differences are also identified by regions and age-groups. The spatial pattern indicates a North-South gradient of pancreatic cancer mortality in Spain, the provinces in the North being the ones with the highest effects on mortality during the studied period. Finally, the space-time evolution shows that the space pattern has changed little over time. PMID:28199327
NASA Astrophysics Data System (ADS)
Kaven, J. Ole; Barbour, Andrew J.; Ali, Tabrez
2017-04-01
Continual production of geothermal energy at times leads to significant surface displacement that can be observed in high spatial resolution using InSAR imagery. The surface displacement can be analyzed to resolve volume change within the reservoir revealing the often-complicated patterns of reservoir deformation. Simple point source models of reservoir deformation in a homogeneous elastic or poro-elastic medium can be superimposed to provide spatially varying, kinematic representations of reservoir deformation. In many cases, injection and production data are known in insufficient detail; but, when these are available, the same Green functions can be used to constrain the reservoir deformation. Here we outline how the injection and production data can be used to constrain bounds on the solution by posing the inversion as a quadratic programming with inequality constraints and regularization rather than a conventional least squares solution with regularization. We apply this method to InSAR-derived surface displacements at the Coso and Salton Sea Geothermal Fields in California, using publically available injection and production data. At both geothermal fields the available surface deformation in conjunction with the injection and production data permit robust solutions for the spatially varying reservoir deformation. The reservoir deformation pattern resulting from the constrained quadratic programming solution is more heterogeneous when compared to a conventional least squares solution. The increased heterogeneity is consistent with the known structural controls on heat and fluid transport in each geothermal reservoir.
NASA Astrophysics Data System (ADS)
Baron, J.; Mast, A.; Clow, D. W.; Wetherbee, G. A.
2014-12-01
Ecohydrological systems evolve spontaneously in response to geologic, hydroclimate and biodiversity drivers. The stability and resilience of these systems to multiple disturbances can be addressed over specific temporal extents, potentially embedded within long term transience in response to geologic or climate change. The limits of ecohydrological resilience of system state in terms of vegetation canopy and soil catenae and the space/time distribution of water, carbon and nutrient cycling is determined by a set of critical feedbacks and potential substitutions of plant functional forms in response to disturbance. The ability of forest systems to return to states functionally similar to states prior to major disturbance, or combinations of multiple disturbances, is a critical question given increasing hydroclimate extremes, biological invasions, and human disturbance. Over the past century, forest landscape ecological patterns appear to have the ability to recover from significant disturbance and re-establish similar hydrological and ecological function in humid, biodiverse regions such as the southern Appalachians, and potentially drier forest ecosystems. Understanding and prediction of past and future long term dynamics requires explicit representation of spatial and temporal feedbacks and dependencies between hydrological, ecosystem and geomorphic processes, and the spatial pattern of species or plant functional type (PFT). Comprehensive models of watershed ecohydrological resilience requires careful balance between the level of process and parameter detail between the interacting components, relative to the structure, organization, space and time scales of the landscape.
Understanding high magnitude flood risk: evidence from the past
NASA Astrophysics Data System (ADS)
MacDonald, N.
2009-04-01
The average length of gauged river flow records in the UK is ~25 years, which presents a problem in determining flood risk for high-magnitude flood events. Severe floods have been recorded in many UK catchments during the past 10 years, increasing the uncertainty in conventional flood risk estimates based on river flow records. Current uncertainty in flood risk has implications for society (insurance costs), individuals (personal vulnerability) and water resource managers (flood/drought risk). An alternative approach is required which can improve current understanding of the flood frequency/magnitude relationship. Historical documentary accounts are now recognised as a valuable resource when considering the flood frequency/magnitude relationship, but little consideration has been given to the temporal and spatial distribution of these records. Building on previous research based on British rivers (urban centre): Ouse (York), Trent (Nottingham), Tay (Perth), Severn (Shrewsbury), Dee (Chester), Great Ouse (Cambridge), Sussex Ouse (Lewes), Thames (Oxford), Tweed (Kelso) and Tyne (Hexham), this work considers the spatial and temporal distribution of historical flooding. The selected sites provide a network covering many of the largest river catchments in Britain, based on urban centres with long detailed documentary flood histories. The chronologies offer an opportunity to assess long-term patterns of flooding, indirectly determining periods of climatic variability and potentially increased geomorphic activity. This research represents the first coherent large scale analysis undertaken of historical multi-catchment flood chronologies, providing an unparalleled network of sites, permitting analysis of the spatial and temporal distribution of historical flood patterns on a national scale.
Climate change and fishing: a century of shifting distribution in North Sea cod
Engelhard, Georg H; Righton, David A; Pinnegar, John K
2014-01-01
Globally, spatial distributions of fish stocks are shifting but although the role of climate change in range shifts is increasingly appreciated, little remains known of the likely additional impact that high levels of fishing pressure might have on distribution. For North Sea cod, we show for the first time and in great spatial detail how the stock has shifted its distribution over the past 100 years. We digitized extensive historical fisheries data from paper charts in UK government archives and combined these with contemporary data to a time-series spanning 1913–2012 (excluding both World Wars). New analysis of old data revealed that the current distribution pattern of cod – mostly in the deeper, northern- and north-easternmost parts of the North Sea – is almost opposite to that during most of the Twentieth Century – mainly concentrated in the west, off England and Scotland. Statistical analysis revealed that the deepening, northward shift is likely attributable to warming; however, the eastward shift is best explained by fishing pressure, suggestive of significant depletion of the stock from its previous stronghold, off the coasts of England and Scotland. These spatial patterns were confirmed for the most recent 3½ decades by data from fisheries-independent surveys, which go back to the 1970s. Our results demonstrate the fundamental importance of both climate change and fishing pressure for our understanding of changing distributions of commercially exploited fish. PMID:24375860
Using Social Network Measures in Wildlife Disease Ecology, Epidemiology, and Management
Silk, Matthew J.; Croft, Darren P.; Delahay, Richard J.; Hodgson, David J.; Boots, Mike; Weber, Nicola; McDonald, Robbie A.
2017-01-01
Abstract Contact networks, behavioral interactions, and shared use of space can all have important implications for the spread of disease in animals. Social networks enable the quantification of complex patterns of interactions; therefore, network analysis is becoming increasingly widespread in the study of infectious disease in animals, including wildlife. We present an introductory guide to using social-network-analytical approaches in wildlife disease ecology, epidemiology, and management. We focus on providing detailed practical guidance for the use of basic descriptive network measures by suggesting the research questions to which each technique is best suited and detailing the software available for each. We also discuss how using network approaches can be used beyond the study of social contacts and across a range of spatial and temporal scales. Finally, we integrate these approaches to examine how network analysis can be used to inform the implementation and monitoring of effective disease management strategies. PMID:28596616
Prototype Development of a Geostationary Synthetic Thinned Aperture Radiometer, GeoSTAR
NASA Technical Reports Server (NTRS)
Tanner, Alan B.; Wilson, William J.; Kangaslahti, Pekka P.; Lambrigsten, Bjorn H.; Dinardo, Steven J.; Piepmeier, Jeffrey R.; Ruf, Christopher S.; Rogacki, Steven; Gross, S. M.; Musko, Steve
2004-01-01
Preliminary details of a 2-D synthetic aperture radiometer prototype operating from 50 to 58 GHz will be presented. The instrument is being developed as a laboratory testbed, and the goal of this work is to demonstrate the technologies needed to do atmospheric soundings with high spatial resolution from Geostationary orbit. The concept is to deploy a large sparse aperture Y-array from a geostationary satellite, and to use aperture synthesis to obtain images of the earth without the need for a large mechanically scanned antenna. The laboratory prototype consists of a Y-array of 24 horn antennas, MMIC receivers, and a digital cross-correlation sub-system. System studies are discussed, including an error budget which has been derived from numerical simulations. The error budget defines key requirements, such as null offsets, phase calibration, and antenna pattern knowledge. Details of the instrument design are discussed in the context of these requirements.
Spatial scaling patterns and functional redundancies in a changing boreal lake landscape
Angeler, David G.; Allen, Craig R.; Uden, Daniel R.; Johnson, Richard K.
2015-01-01
Global transformations extend beyond local habitats; therefore, larger-scale approaches are needed to assess community-level responses and resilience to unfolding environmental changes. Using longterm data (1996–2011), we evaluated spatial patterns and functional redundancies in the littoral invertebrate communities of 85 Swedish lakes, with the objective of assessing their potential resilience to environmental change at regional scales (that is, spatial resilience). Multivariate spatial modeling was used to differentiate groups of invertebrate species exhibiting spatial patterns in composition and abundance (that is, deterministic species) from those lacking spatial patterns (that is, stochastic species). We then determined the functional feeding attributes of the deterministic and stochastic invertebrate species, to infer resilience. Between one and three distinct spatial patterns in invertebrate composition and abundance were identified in approximately one-third of the species; the remainder were stochastic. We observed substantial differences in metrics between deterministic and stochastic species. Functional richness and diversity decreased over time in the deterministic group, suggesting a loss of resilience in regional invertebrate communities. However, taxon richness and redundancy increased monotonically in the stochastic group, indicating the capacity of regional invertebrate communities to adapt to change. Our results suggest that a refined picture of spatial resilience emerges if patterns of both the deterministic and stochastic species are accounted for. Spatially extensive monitoring may help increase our mechanistic understanding of community-level responses and resilience to regional environmental change, insights that are critical for developing management and conservation agendas in this current period of rapid environmental transformation.
2011-01-01
Background Geographic Information Systems (GIS) combined with spatial analytical methods could be helpful in examining patterns of drug use. Little attention has been paid to geographic variation of cardiovascular prescription use in Taiwan. The main objective was to use local spatial association statistics to test whether or not the cardiovascular medication-prescribing pattern is homogenous across 352 townships in Taiwan. Methods The statistical methods used were the global measures of Moran's I and Local Indicators of Spatial Association (LISA). While Moran's I provides information on the overall spatial distribution of the data, LISA provides information on types of spatial association at the local level. LISA statistics can also be used to identify influential locations in spatial association analysis. The major classes of prescription cardiovascular drugs were taken from Taiwan's National Health Insurance Research Database (NHIRD), which has a coverage rate of over 97%. The dosage of each prescription was converted into defined daily doses to measure the consumption of each class of drugs. Data were analyzed with ArcGIS and GeoDa at the township level. Results The LISA statistics showed an unusual use of cardiovascular medications in the southern townships with high local variation. Patterns of drug use also showed more low-low spatial clusters (cold spots) than high-high spatial clusters (hot spots), and those low-low associations were clustered in the rural areas. Conclusions The cardiovascular drug prescribing patterns were heterogeneous across Taiwan. In particular, a clear pattern of north-south disparity exists. Such spatial clustering helps prioritize the target areas that require better education concerning drug use. PMID:21609462
Freire, R; Swain, D L; Friend, M A
2012-05-01
We hypothesised that (i) increased feeding motivation will cause sheep to move further apart as a result of individuals trying to find food and (ii) in conditions of high food availability, sheep will move less and show greater social attraction. The effects of both feeding motivation and food availability on spatial distribution was examined in eight groups of food-deprived (high feeding motivation) and satiated (low feeding motivation) sheep in good or poor food resource plots in a 2 × 2 design. Distance travelled was assessed using Global Positioning System collars, grazing time using scan sampling and social cohesion using proximity collars that record the number and duration of encounters within 4 m. Food-deprived sheep in the good-resource plots grazed the most, whereas satiated sheep in the poor-resource plots grazed the least (P = 0.004). Food deprivation had no significant effect on the number or duration of encounters and feeding motivation appeared to have little effect on spatial distribution. Contrary to expectation, sheep had more encounters (P = 0.04) of a longer total duration (P = 0.02) in poor-resource plots than in good-resource plots, indicating that sheep were showing more social cohesion if food was scarce. Our findings suggest that when food is scarce, animals may come together in an attempt to share information on food availability. However, when a highly preferred food is abundant and well dispersed, they may move apart in order to maximise the intake. It is concluded that the particular details of our experiment, namely the even distribution or absence of a highly preferred food, affected spatial distribution patterns as sheep tried to find this food and maximise the intake.
NASA Astrophysics Data System (ADS)
Umar, M.; Rhoads, Bruce L.; Greenberg, Jonathan A.
2018-01-01
Although past work has noted that contrasts in turbidity often are detectable on remotely sensed images of rivers downstream from confluences, no systematic methodology has been developed for assessing mixing over distance of confluent flows with differing surficial suspended sediment concentrations (SSSC). In contrast to field measurements of mixing below confluences, satellite remote-sensing can provide detailed information on spatial distributions of SSSC over long distances. This paper presents a methodology that uses remote-sensing data to estimate spatial patterns of SSSC downstream of confluences along large rivers and to determine changes in the amount of mixing over distance from confluences. The method develops a calibrated Random Forest (RF) model by relating training SSSC data from river gaging stations to derived spectral indices for the pixels corresponding to gaging-station locations. The calibrated model is then used to predict SSSC values for every river pixel in a remotely sensed image, which provides the basis for mapping of spatial variability in SSSCs along the river. The pixel data are used to estimate average surficial values of SSSC at cross sections spaced uniformly along the river. Based on the cross-section data, a mixing metric is computed for each cross section. The spatial pattern of change in this metric over distance can be used to define rates and length scales of surficial mixing of suspended sediment downstream of a confluence. This type of information is useful for exploring the potential influence of various controlling factors on mixing downstream of confluences, for evaluating how mixing in a river system varies over time and space, and for determining how these variations influence water quality and ecological conditions along the river.
Balancing geo-privacy and spatial patterns in epidemiological studies.
Chen, Chien-Chou; Chuang, Jen-Hsiang; Wang, Da-Wei; Wang, Chien-Min; Lin, Bo-Cheng; Chan, Ta-Chien
2017-11-08
To balance the protection of geo-privacy and the accuracy of spatial patterns, we developed a geo-spatial tool (GeoMasker) intended to mask the residential locations of patients or cases in a geographic information system (GIS). To elucidate the effects of geo-masking parameters, we applied 2010 dengue epidemic data from Taiwan testing the tool's performance in an empirical situation. The similarity of pre- and post-spatial patterns was measured by D statistics under a 95% confidence interval. In the empirical study, different magnitudes of anonymisation (estimated Kanonymity ≥10 and 100) were achieved and different degrees of agreement on the pre- and post-patterns were evaluated. The application is beneficial for public health workers and researchers when processing data with individuals' spatial information.
Pattern transitions in spatial epidemics: Mechanisms and emergent properties.
Sun, Gui-Quan; Jusup, Marko; Jin, Zhen; Wang, Yi; Wang, Zhen
2016-12-01
Infectious diseases are a threat to human health and a hindrance to societal development. Consequently, the spread of diseases in both time and space has been widely studied, revealing the different types of spatial patterns. Transitions between patterns are an emergent property in spatial epidemics that can serve as a potential trend indicator of disease spread. Despite the usefulness of such an indicator, attempts to systematize the topic of pattern transitions have been few and far between. We present a mini-review on pattern transitions in spatial epidemics, describing the types of transitions and their underlying mechanisms. We show that pattern transitions relate to the complexity of spatial epidemics by, for example, being accompanied with phenomena such as coherence resonance and cyclic evolution. The results presented herein provide valuable insights into disease prevention and control, and may even be applicable outside epidemiology, including other branches of medical science, ecology, quantitative finance, and elsewhere. Copyright © 2016 Elsevier B.V. All rights reserved.
An exploration of spatial patterns of seasonal diarrhoeal morbidity in Thailand.
McCormick, B J J; Alonso, W J; Miller, M A
2012-07-01
Studies of temporal and spatial patterns of diarrhoeal disease can suggest putative aetiological agents and environmental or socioeconomic drivers. Here, the seasonal patterns of monthly acute diarrhoeal morbidity in Thailand, where diarrhoeal morbidity is increasing, are explored. Climatic data (2003-2006) and Thai Ministry of Health annual reports (2003-2009) were used to construct a spatially weighted panel regression model. Seasonal patterns of diarrhoeal disease were generally bimodal with aetiological agents peaking at different times of the year. There is a strong association between daily mean temperature and precipitation and the incidence of hospitalization due to acute diarrhoea in Thailand leading to a distinct spatial pattern in the seasonal pattern of diarrhoea. Model performance varied across the country in relation to per capita GDP and population density. While climatic factors are likely to drive the general pattern of diarrhoeal disease in Thailand, the seasonality of diarrhoeal disease is dampened in affluent urban populations.
Pe'er, Guy; Zurita, Gustavo A.; Schober, Lucia; Bellocq, Maria I.; Strer, Maximilian; Müller, Michael; Pütz, Sandro
2013-01-01
Landscape simulators are widely applied in landscape ecology for generating landscape patterns. These models can be divided into two categories: pattern-based models that generate spatial patterns irrespective of the processes that shape them, and process-based models that attempt to generate patterns based on the processes that shape them. The latter often tend toward complexity in an attempt to obtain high predictive precision, but are rarely used for generic or theoretical purposes. Here we show that a simple process-based simulator can generate a variety of spatial patterns including realistic ones, typifying landscapes fragmented by anthropogenic activities. The model “G-RaFFe” generates roads and fields to reproduce the processes in which forests are converted into arable lands. For a selected level of habitat cover, three factors dominate its outcomes: the number of roads (accessibility), maximum field size (accounting for land ownership patterns), and maximum field disconnection (which enables field to be detached from roads). We compared the performance of G-RaFFe to three other models: Simmap (neutral model), Qrule (fractal-based) and Dinamica EGO (with 4 model versions differing in complexity). A PCA-based analysis indicated G-RaFFe and Dinamica version 4 (most complex) to perform best in matching realistic spatial patterns, but an alternative analysis which considers model variability identified G-RaFFe and Qrule as performing best. We also found model performance to be affected by habitat cover and the actual land-uses, the latter reflecting on land ownership patterns. We suggest that simple process-based generators such as G-RaFFe can be used to generate spatial patterns as templates for theoretical analyses, as well as for gaining better understanding of the relation between spatial processes and patterns. We suggest caution in applying neutral or fractal-based approaches, since spatial patterns that typify anthropogenic landscapes are often non-fractal in nature. PMID:23724108
Pe'er, Guy; Zurita, Gustavo A; Schober, Lucia; Bellocq, Maria I; Strer, Maximilian; Müller, Michael; Pütz, Sandro
2013-01-01
Landscape simulators are widely applied in landscape ecology for generating landscape patterns. These models can be divided into two categories: pattern-based models that generate spatial patterns irrespective of the processes that shape them, and process-based models that attempt to generate patterns based on the processes that shape them. The latter often tend toward complexity in an attempt to obtain high predictive precision, but are rarely used for generic or theoretical purposes. Here we show that a simple process-based simulator can generate a variety of spatial patterns including realistic ones, typifying landscapes fragmented by anthropogenic activities. The model "G-RaFFe" generates roads and fields to reproduce the processes in which forests are converted into arable lands. For a selected level of habitat cover, three factors dominate its outcomes: the number of roads (accessibility), maximum field size (accounting for land ownership patterns), and maximum field disconnection (which enables field to be detached from roads). We compared the performance of G-RaFFe to three other models: Simmap (neutral model), Qrule (fractal-based) and Dinamica EGO (with 4 model versions differing in complexity). A PCA-based analysis indicated G-RaFFe and Dinamica version 4 (most complex) to perform best in matching realistic spatial patterns, but an alternative analysis which considers model variability identified G-RaFFe and Qrule as performing best. We also found model performance to be affected by habitat cover and the actual land-uses, the latter reflecting on land ownership patterns. We suggest that simple process-based generators such as G-RaFFe can be used to generate spatial patterns as templates for theoretical analyses, as well as for gaining better understanding of the relation between spatial processes and patterns. We suggest caution in applying neutral or fractal-based approaches, since spatial patterns that typify anthropogenic landscapes are often non-fractal in nature.
NASA Astrophysics Data System (ADS)
Grosse, G.; Tillapaugh, M.; Romanovsky, V. E.; Walter, K. M.; Plug, L. J.
2008-12-01
Formation, growth, and drainage of thermokarst lakes in ice-rich permafrost deposits are important factors of landscape dynamics in extent Arctic lowlands. Monitoring of spatial and temporal dynamics of such lakes will allow an assessment of permafrost stability and enhance the capabilities for modelling and quantifying biogeochemical processes related to permafrost degradation in a warming Arctic. In this study we use high-resolution remote sensing and GIS to analyze the development of thermokarst lakes and ponds in two study regions in North Siberia and Northwest Alaska. The sites are 1) the Cherskii region in the Kolyma lowland (Siberia) and 2) the Kitluk River area on the northern Seward Peninsula (Alaska). Both regions are characterized by continuous permafrost, a highly dissected and dynamic thermokarst landscape, uplands of Late Pleistocene permafrost deposits with high excess ice contents, and a large total volume of permafrost-stored carbon. These ice-rich Yedoma or Yedoma-like deposits are highly vulnerable to permafrost degradation forced by climate warming or other surface disturbance. Time series of high- resolution imagery (aerial, Corona, Ikonos, Alos Prism) covering more than 50 years of lake dynamics allow detailed assessments of processes and spatial patterns of thermokarst lake expansion and drainage in continuous permafrost. Time series of high-resolution imagery (aerial, Corona, Ikonos, Alos Prism) covering more than 50 years of lake dynamics allow detailed assessments of processes and spatial patterns of thermokarst lake expansion and drainage in continuous permafrost. Processes identified include thaw slumping, wave undercutting of frozen sediments or peat blocks and subsequent mass wasting, thaw collapse of near-shore zones, sinkhole formation and ice-wedge tunnelling, and gully formation by thermo-erosion. We use GIS-based tools to relate the remote sensing results to field data (ground ice content, topography, lithology, and relative age of landscape units). Results exhibit a very dynamic lake environment at both sites strongly related to landscape history and past cryolithological development. Lake shore erosion rates reach values of more than 1 m per year over the 50 year observation period at some sites. Permafrost degradation processes are identified as a key driver of both lake expansion and drainage.
ERIC Educational Resources Information Center
Hirshhorn, Marnie; Grady, Cheryl; Rosenbaum, R. Shayna; Winocur, Gordon; Moscovitch, Morris
2012-01-01
Functional magnetic resonance imaging (fMRI) was used to compare brain activity during the retrieval of coarse- and fine-grained spatial details and episodic details associated with a familiar environment. Long-time Toronto residents compared pairs of landmarks based on their absolute geographic locations (requiring either coarse or fine…
Liu, Jie; Gao, Meixiang; Liu, Jinwen; Guo, Yuxi; Liu, Dong; Zhu, Xinyu; Wu, Donghui
2018-01-01
Spatial distribution is an important topic in community ecology and a key to understanding the structure and dynamics of populations and communities. However, the available information related to the spatial patterns of soil mite communities in long-term tillage agroecosystems remains insufficient. In this study, we examined the spatial patterns of soil mite communities to explain the spatial relationships between soil mite communities and soil parameters. Soil fauna were sampled three times (August, September and October 2015) at 121 locations arranged regularly within a 400 m × 400 m monitoring plot. Additionally, we estimated the physical and chemical parameters of the same sampling locations. The distribution patterns of the soil mite community and the edaphic parameters were analyzed using a range of geostatistical tools. Moran's I coefficient showed that, during each sampling period, the total abundance of the soil mite communities and the abundance of the dominant mite populations were spatially autocorrelated. The soil mite communities demonstrated clear patchy distribution patterns within the study plot. These patterns were sampling period-specific. Cross-semivariograms showed both negative and positive cross-correlations between soil mite communities and environmental factors. Mantel tests showed a significant and positive relationship between soil mite community and soil organic matter and soil pH only in August. This study demonstrated that in the cornfield, the soil mite distribution exhibited strong or moderate spatial dependence, and the mites formed patches with sizes less than one hundred meters. In addition, in this long-term tillage agroecosystem, soil factors had less influence on the observed pattern of soil mite communities. Further experiments that take into account human activity and spatial factors should be performed to study the factors that drive the spatial distribution of soil microarthropods.
Spatial Pattern of Attacks of the Invasive Woodwasp Sirex noctilio, at Landscape and Stand Scales.
Lantschner, M Victoria; Corley, Juan C
2015-01-01
Invasive insect pests are responsible for important damage to native and plantation forests, when population outbreaks occur. Understanding the spatial pattern of attacks by forest pest populations is essential to improve our understanding of insect population dynamics and for predicting attack risk by invasives or planning pest management strategies. The woodwasp Sirex noctilio is an invasive woodwasp that has become probably the most important pest of pine plantations in the Southern Hemisphere. Our aim was to study the spatial dynamics of S. noctilio populations in Southern Argentina. Specifically we describe: (1) the spatial patterns of S. noctilio outbreaks and their relation with environmental factors at a landscape scale; and (2) characterize the spatial pattern of attacked trees at the stand scale. We surveyed the spatial distribution of S. noctilio outbreaks in three pine plantation landscapes, and we assessed potential associations with topographic variables, habitat characteristics, and distance to other outbreaks. We also looked at the spatial distribution of attacked trees in 20 stands with different levels of infestation, and assessed the relationship of attacks with stand composition and management. We found that the spatial pattern of pine stands with S. noctilio outbreaks at the landscape scale is influenced mainly by the host species present, slope aspect, and distance to other outbreaks. At a stand scale, there is strong aggregation of attacked trees in stands with intermediate infestation levels, and the degree of attacks is influenced by host species and plantation management. We conclude that the pattern of S. noctilio damage at different spatial scales is influenced by a combination of both inherent population dynamics and the underlying patterns of environmental factors. Our results have important implications for the understanding and management of invasive insect outbreaks in forest systems.
Describing spatial pattern in stream networks: A practical approach
Ganio, L.M.; Torgersen, C.E.; Gresswell, R.E.
2005-01-01
The shape and configuration of branched networks influence ecological patterns and processes. Recent investigations of network influences in riverine ecology stress the need to quantify spatial structure not only in a two-dimensional plane, but also in networks. An initial step in understanding data from stream networks is discerning non-random patterns along the network. On the other hand, data collected in the network may be spatially autocorrelated and thus not suitable for traditional statistical analyses. Here we provide a method that uses commercially available software to construct an empirical variogram to describe spatial pattern in the relative abundance of coastal cutthroat trout in headwater stream networks. We describe the mathematical and practical considerations involved in calculating a variogram using a non-Euclidean distance metric to incorporate the network pathway structure in the analysis of spatial variability, and use a non-parametric technique to ascertain if the pattern in the empirical variogram is non-random.
A geostatistical approach for describing spatial pattern in stream networks
Ganio, L.M.; Torgersen, C.E.; Gresswell, R.E.
2005-01-01
The shape and configuration of branched networks influence ecological patterns and processes. Recent investigations of network influences in riverine ecology stress the need to quantify spatial structure not only in a two-dimensional plane, but also in networks. An initial step in understanding data from stream networks is discerning non-random patterns along the network. On the other hand, data collected in the network may be spatially autocorrelated and thus not suitable for traditional statistical analyses. Here we provide a method that uses commercially available software to construct an empirical variogram to describe spatial pattern in the relative abundance of coastal cutthroat trout in headwater stream networks. We describe the mathematical and practical considerations involved in calculating a variogram using a non-Euclidean distance metric to incorporate the network pathway structure in the analysis of spatial variability, and use a non-parametric technique to ascertain if the pattern in the empirical variogram is non-random.
Clay mineralogy in different geomorphic surfaces in sugarcane areas
NASA Astrophysics Data System (ADS)
Camargo, L.; Marques, J., Jr.
2012-04-01
The crystallization of the oxides and hydroxides of iron and aluminum and kaolinite of clay fraction is the result of pedogenetic processes controlled by the relief. These minerals have influence on the physical and chemical attributes of soil and exhibit spatial dependence. The pattern of spatial distribution is influenced by forms of relief as the geomorphic surfaces. In this sense, the studies aimed at understanding the relationship between relief and the distribution pattern of the clay fraction attributes contribute to the delineation of specific areas of management in the field. The objective of this study was to evaluate the spatial distribution of oxides and hydroxides of iron and aluminum and kaolinite of clay fraction and its relationship with the physical and chemical attributes in different geomorphic surfaces. Soil samples were collected in a transect each 25 m (100 samples) and in the sides of the same (200 samples) as well as an area of 500 ha (1 sample each six hectare). Geomorphic surfaces (GS) in the transect were mapped in detail to support mapping the entire area. The soil samples were taken to the laboratory for chemical, physical, and mineralogical analysis, and the pattern of spatial distribution of soil attributes was obtained by statistics and geostatistics. The GS I is considered the oldest surface of the study area, with depositional character, and a slope ranging from 0 to 4%. GS II and III are considered to be eroded, and the surface II plan a gentle slope that extends from the edge of the surface until the beginning of I and III. The crystallographic characteristics of the oxides and hydroxides of iron and aluminum and kaolinite showed spatial dependence and the distribution pattern corresponding to the limits present of the GS in the field. Surfaces I and II showed the best environments to the degree of crystallinity of hematite and the surface III to the greatest degree of crystallinity of goethite agreeing to the pedoenvironment conditions of each surface. The rate goethite/(goethite+hematite) decreases the surface I to III this result is the variation of the source material that has an increase of clay which is characteristic of sandstone rock (Adamantine Formation) in the surface III. The rate kaolinite/(kaolinite+gibbsite) also shows a decrease of the surface I to the surface III. The spatial distribution pattern of mineralogy influenced the pattern of physical and chemical properties. On the surface III (with higher iron and gibbsite) had the best physical condition (lower density, higher porosity and aggregates) and greater phosphorus sorption. In this sense, the identification and mapping of the GSs, allowed a better understanding of cause and effect of the distribution of soils in the area, and the recognition of areas of controlled variability of soil attributes. These areas can be considered specific areas of management, useful for planning and management practices in the culture of sugarcane. Besides, suggesting criteria for the recognition of map units that would be equivalent to the future series of soils of the Brazilian System of Soil Classification.
Houston-Galveston Bay area, Texas, from space; a new tool for mapping land subsidence
Stork, Sylvia V.; Sneed, Michelle
2002-01-01
Interferometric Synthetic Aperture Radar (InSAR) is a powerful new tool that uses radar signals to measure displacement (subsidence and uplift) of the Earth's crust at an unprecedented level of spatial detail and high degree of measurement resolution.The Houston-Galveston Bay area, possibly more than any other metropolitan area in the United States, has been adversely affected by land subsidence. Extensive subsidence, caused mainly by ground-water pumping but also by oil and gas extraction, has increased the frequency of flooding, caused extensive damage to industrial and transportation infrastructure, motivated major investments in levees, reservoirs, and surfacewater distribution facilities, and caused substantial loss of wetland habitat. Ongoing patterns of subsidence in the Houston area have been carefully monitored using borehole extensometers, Global Positioning System (GPS) and conventional spirit-leveling surveys, and more recently, an emerging technology—Interferometric Synthetic Aperture Radar (InSAR)—which enables development of spatially-detailed maps of land-surface displacement over broad areas. This report, prepared by the U.S. Geological Survey (USGS) in cooperation with the U.S. Fish and Wildlife Service, briefly summarizes the history of subsidence in the area and the local consequences of subsidence and describes the use of InSAR as one of several tools in an integrated subsidence-monitoring program in the area.
NASA Astrophysics Data System (ADS)
Wang, J.; Cai, X.
2007-12-01
A water resources system can be defined as a large-scale spatial system, within which distributed ecological system interacts with the stream network and ground water system. Water resources management, the causative factors and hence the solutions to be developed have a significant spatial dimension. This motivates a modeling analysis of water resources management within a spatial analytical framework, where data is usually geo- referenced and in the form of a map. One of the important functions of Geographic information systems (GIS) is to identify spatial patterns of environmental variables. The role of spatial patterns in water resources management has been well established in the literature particularly regarding how to design better spatial patterns for satisfying the designated objectives of water resources management. Evolutionary algorithms (EA) have been demonstrated to be successful in solving complex optimization models for water resources management due to its flexibility to incorporate complex simulation models in the optimal search procedure. The idea of combining GIS and EA motivates the development and application of spatial evolutionary algorithms (SEA). SEA assimilates spatial information into EA, and even changes the representation and operators of EA. In an EA used for water resources management, the mathematical optimization model should be modified to account the spatial patterns; however, spatial patterns are usually implicit, and it is difficult to impose appropriate patterns to spatial data. Also it is difficult to express complex spatial patterns by explicit constraints included in the EA. The GIS can help identify the spatial linkages and correlations based on the spatial knowledge of the problem. These linkages are incorporated in the fitness function for the preference of the compatible vegetation distribution. Unlike a regular GA for spatial models, the SEA employs a special hierarchical hyper-population and spatial genetic operators to represent spatial variables in a more efficient way. The hyper-population consists of a set of populations, which correspond to the spatial distributions of the individual agents (organisms). Furthermore spatial crossover and mutation operators are designed in accordance with the tree representation and then applied to both organisms and populations. This study applies the SEA to a specific problem of water resources management- maximizing the riparian vegetation coverage in accordance with the distributed groundwater system in an arid region. The vegetation coverage is impacted greatly by the nonlinear feedbacks and interactions between vegetation and groundwater and the spatial variability of groundwater. The SEA is applied to search for an optimal vegetation configuration compatible to the groundwater flow. The results from this example demonstrate the effectiveness of the SEA. Extension of the algorithm for other water resources management problems is discussed.
Point pattern analysis of FIA data
Chris Woodall
2002-01-01
Point pattern analysis is a branch of spatial statistics that quantifies the spatial distribution of points in two-dimensional space. Point pattern analysis was conducted on stand stem-maps from FIA fixed-radius plots to explore point pattern analysis techniques and to determine the ability of pattern descriptions to describe stand attributes. Results indicate that the...
Jeffrey R. Garnas; David R. Houston; Mark J. Twery; Matthew P. Ayres; Celia Evans
2013-01-01
Spatial pattern in the distribution and abundance of organisms is an emergent property of collective rates of reproduction, survival and movement of individuals in a heterogeneous environment. The form, intensity and scale of spatial patterning can be used to test hypotheses regarding the relative importance of candidate processes to population dynamics. Using 84 plots...
Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data
Liu, Yu; Sui, Zhengwei; Kang, Chaogui; Gao, Yong
2014-01-01
The article revisits spatial interaction and distance decay from the perspective of human mobility patterns and spatially-embedded networks based on an empirical data set. We extract nationwide inter-urban movements in China from a check-in data set that covers half a million individuals within 370 cities to analyze the underlying patterns of trips and spatial interactions. By fitting the gravity model, we find that the observed spatial interactions are governed by a power law distance decay effect. The obtained gravity model also closely reproduces the exponential trip displacement distribution. The movement of an individual, however, may not obey the same distance decay effect, leading to an ecological fallacy. We also construct a spatial network where the edge weights denote the interaction strengths. The communities detected from the network are spatially cohesive and roughly consistent with province boundaries. We attribute this pattern to different distance decay parameters between intra-province and inter-province trips. PMID:24465849
Uncovering patterns of inter-urban trip and spatial interaction from social media check-in data.
Liu, Yu; Sui, Zhengwei; Kang, Chaogui; Gao, Yong
2014-01-01
The article revisits spatial interaction and distance decay from the perspective of human mobility patterns and spatially-embedded networks based on an empirical data set. We extract nationwide inter-urban movements in China from a check-in data set that covers half a million individuals within 370 cities to analyze the underlying patterns of trips and spatial interactions. By fitting the gravity model, we find that the observed spatial interactions are governed by a power law distance decay effect. The obtained gravity model also closely reproduces the exponential trip displacement distribution. The movement of an individual, however, may not obey the same distance decay effect, leading to an ecological fallacy. We also construct a spatial network where the edge weights denote the interaction strengths. The communities detected from the network are spatially cohesive and roughly consistent with province boundaries. We attribute this pattern to different distance decay parameters between intra-province and inter-province trips.
NASA Technical Reports Server (NTRS)
Randel, William J.; Newman, Paul A.
1988-01-01
A high degree of correlation between the recent decline in Antarctic total ozone and cooling of the stratosphere during Austral spring has been noted in several recent studies (e.g., Sekiguchi, 1986; Angel, 1986). This study analyzes the observed temperature trends in detail, focusing on the spatial and temporal aspects of the observed cooling. Ozone losses and stratospheric cooling can be correlated for several reasons: (1) ozone losses (from an unspecified cause) will directly reduce temperatures due to decreased solar ultraviolet absorption (Shine, 1986), and/or (2) changes in both ozone and temperature structure due to modification of stratospheric circulation patterns (Mahlman and Fels, 1986). In order to scrutinize various ozone depletion scenarios, detailed information on the observed temperature changes is necessary; the goal is to provide such data. The data used are National Meteorological Center (NMC) Climate Analysis Center (CAC) derived temperatures, covering 1000 to 1 mb (0 to 48 km), for the period 1979 to 1987. Discussions on data origin and quality (assessed by extensive comparisons with radiosonde observations), along with other details of these observations, can be found in Newman and Randel (1988).
NASA Astrophysics Data System (ADS)
Demirel, M. C.; Mai, J.; Stisen, S.; Mendiguren González, G.; Koch, J.; Samaniego, L. E.
2016-12-01
Distributed hydrologic models are traditionally calibrated and evaluated against observations of streamflow. Spatially distributed remote sensing observations offer a great opportunity to enhance spatial model calibration schemes. For that it is important to identify the model parameters that can change spatial patterns before the satellite based hydrologic model calibration. Our study is based on two main pillars: first we use spatial sensitivity analysis to identify the key parameters controlling the spatial distribution of actual evapotranspiration (AET). Second, we investigate the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale Hydrologic Model (mHM). This distributed model is selected as it allows for a change in the spatial distribution of key soil parameters through the calibration of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) directly as input. In addition the simulated AET can be estimated at the spatial resolution suitable for comparison to the spatial patterns observed using MODIS data. We introduce a new dynamic scaling function employing remotely sensed vegetation to downscale coarse reference evapotranspiration. In total, 17 parameters of 47 mHM parameters are identified using both sequential screening and Latin hypercube one-at-a-time sampling methods. The spatial patterns are found to be sensitive to the vegetation parameters whereas streamflow dynamics are sensitive to the PTF parameters. The results of multi-objective model calibration show that calibration of mHM against observed streamflow does not reduce the spatial errors in AET while they improve only the streamflow simulations. We will further examine the results of model calibration using only multi spatial objective functions measuring the association between observed AET and simulated AET maps and another case including spatial and streamflow metrics together.
An interpretation of flare-induced and decayless coronal-loop oscillations as interference patterns
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hindman, Bradley W.; Jain, Rekha, E-mail: hindman@solarz.colorado.edu
2014-04-01
We present an alternative model of coronal-loop oscillations, which considers that the waves are trapped in a two-dimensional waveguide formed by the entire arcade of field lines. This differs from the standard one-dimensional model which treats the waves as the resonant oscillations of just the visible bundle of field lines. Within the framework of our two-dimensional model, the two types of oscillations that have been observationally identified, flare-induced waves and 'decayless' oscillations, can both be attributed to MHD fast waves. The two components of the signal differ only because of the duration and spatial extent of the source that createsmore » them. The flare-induced waves are generated by strong localized sources of short duration, while the decayless background can be excited by a continuous, stochastic source. Further, the oscillatory signal arising from a localized, short-duration source can be interpreted as a pattern of interference fringes produced by waves that have traveled diverse routes of various pathlengths through the waveguide. The resulting amplitude of the fringes slowly decays in time with an inverse square root dependence. The details of the interference pattern depend on the shape of the arcade and the spatial variation of the Alfvén speed. The rapid decay of this wave component, which has previously been attributed to physical damping mechanisms that remove energy from resonant oscillations, occurs as a natural consequence of the interference process without the need for local dissipation.« less
Garcia, A G; Godoy, W A C
2017-06-01
Studies of the influence of biological parameters on the spatial distribution of lepidopteran insects can provide useful information for managing agricultural pests, since the larvae of many species cause serious impacts on crops. Computational models to simulate the spatial dynamics of insect populations are increasingly used, because of their efficiency in representing insect movement. In this study, we used a cellular automata model to explore different patterns of population distribution of Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae), when the values of two biological parameters that are able to influence the spatial pattern (larval viability and adult longevity) are varied. We mapped the spatial patterns observed as the parameters varied. Additionally, by using population data for S. frugiperda obtained in different hosts under laboratory conditions, we were able to describe the expected spatial patterns occurring in corn, cotton, millet, and soybean crops based on the parameters varied. The results are discussed from the perspective of insect ecology and pest management. We concluded that computational approaches can be important tools to study the relationship between the biological parameters and spatial distributions of lepidopteran insect pests.
Spatial controls of occurrence and spread of wildfires in the Missouri Ozark Highlands.
Yang, Jian; He, Hong S; Shifley, Stephen R
2008-07-01
Understanding spatial controls on wildfires is important when designing adaptive fire management plans and optimizing fuel treatment locations on a forest landscape. Previous research about this topic focused primarily on spatial controls for fire origin locations alone. Fire spread and behavior were largely overlooked. This paper contrasts the relative importance of biotic, abiotic, and anthropogenic constraints on the spatial pattern of fire occurrence with that on burn probability (i.e., the probability that fire will spread to a particular location). Spatial point pattern analysis and landscape succession fire model (LANDIS) were used to create maps to show the contrast. We quantified spatial controls on both fire occurrence and fire spread in the Midwest Ozark Highlands region, USA. This area exhibits a typical anthropogenic surface fire regime. We found that (1) human accessibility and land ownership were primary limiting factors in shaping clustered fire origin locations; (2) vegetation and topography had a negligible influence on fire occurrence in this anthropogenic regime; (3) burn probability was higher in grassland and open woodland than in closed-canopy forest, even though fire occurrence density was less in these vegetation types; and (4) biotic and abiotic factors were secondary descriptive ingredients for determining the spatial patterns of burn probability. This study demonstrates how fire occurrence and spread interact with landscape patterns to affect the spatial distribution of wildfire risk. The application of spatial point pattern data analysis would also be valuable to researchers working on landscape forest fire models to integrate historical ignition location patterns in fire simulation.
Xie, Li-Na; Guo, Hong-Yu; Gabler, Christopher A.; Li, Qing-Fang; Ma, Cheng-Cang
2015-01-01
Few studies have investigated the influence of water availability on plant population spatial patterns. We studied changes in the spatial patterns of Caragana stenophylla along a climatic drought gradient within the Inner Mongolian Plateau, China. We examined spatial patterns, seed density, “nurse effects” of shrubs on seedlings, transpiration rates and water use efficiency (WUE) of C. stenophylla across semi-arid, arid, and intensively arid zones. Our results showed that patches of C. stenophylla populations shifted from a random to a clumped spatial pattern towards drier environments. Seed density and seedling survival rate of C. stenophylla decreased from the semi-arid zone to the intensively arid zone. Across the three zones, there were more C. stenophylla seeds and seedlings underneath shrub canopies than outside shrub canopies; and in the intensively arid zone, there were almost no seeds or seedlings outside shrub canopies. Transpiration rates of outer-canopy leaves and WUE of both outer-canopy and inner-canopy leaves increased from the semi-arid zone to the intensively arid zone. In the intensively arid zone, transpiration rates and WUE of inner-canopy leaves were significantly lower and higher, respectively, than those of outer-canopy leaves. We conclude that, as drought stress increased, seed density decreased, seed proportions inside shrubs increased, and “nurse effects” of shrubs on seedlings became more important. These factors, combined with water-saving characteristics associated with clumped spatial patterns, are likely driving the changes in C. stenophylla spatial patterns. PMID:25785848
Jeefoo, Phaisarn; Tripathi, Nitin Kumar; Souris, Marc
2011-01-01
In recent years, dengue has become a major international public health concern. In Thailand it is also an important concern as several dengue outbreaks were reported in last decade. This paper presents a GIS approach to analyze the spatial and temporal dynamics of dengue epidemics. The major objective of this study was to examine spatial diffusion patterns and hotspot identification for reported dengue cases. Geospatial diffusion pattern of the 2007 dengue outbreak was investigated. Map of daily cases was generated for the 153 days of the outbreak. Epidemiological data from Chachoengsao province, Thailand (reported dengue cases for the years 1999-2007) was used for this study. To analyze the dynamic space-time pattern of dengue outbreaks, all cases were positioned in space at a village level. After a general statistical analysis (by gender and age group), data was subsequently analyzed for temporal patterns and correlation with climatic data (especially rainfall), spatial patterns and cluster analysis, and spatio-temporal patterns of hotspots during epidemics. The results revealed spatial diffusion patterns during the years 1999-2007 representing spatially clustered patterns with significant differences by village. Villages on the urban fringe reported higher incidences. The space and time of the cases showed outbreak movement and spread patterns that could be related to entomologic and epidemiologic factors. The hotspots showed the spatial trend of dengue diffusion. This study presents useful information related to the dengue outbreak patterns in space and time and may help public health departments to plan strategies to control the spread of disease. The methodology is general for space-time analysis and can be applied for other infectious diseases as well.
NASA Astrophysics Data System (ADS)
Sasai, Takahiro; Obikawa, Hiroki; Murakami, Kazutaka; Kato, Soushi; Matsunaga, Tsuneo; Nemani, Ramakrishna R.
2016-06-01
The terrestrial carbon cycle in Asia is highly uncertain, and it affects our understanding of global warming. One of the important issues is the need for an enhancement of spatial resolution, since local regions in Asia are heterogeneous with regard to meteorology, land form, and land cover type, which greatly impacts the detailed spatial patterns in its ecosystem. Thus, an important goal of this study is to reasonably reproduce the heterogeneous biogeochemical patterns in Asia by enhancing the spatial resolution of the ecosystem model biosphere model integrating eco-physiological and mechanistic approaches using satellite data (BEAMS). We estimated net ecosystem production (NEP) over eastern Asia and examined the spatial differences in the factors controlling NEP by using a 10 km grid-scale approach over two different decades (2001-2010 and 2091-2100). The present and future meteorological inputs were derived from satellite observations and the downscaled Coupled Model Intercomparison Project Phase 5 (CMIP5) data set, respectively. The results showed that the present NEP in whole eastern Asia was carbon source (-214.9 TgC yr-1) and in future scenarios, the greatest positive (76.4 TgC yr-1) and least negative (-95.9 TgC yr-1) NEPs were estimated from the Representative Concentration Pathways (RCP) 6.0 and RCP8.5 scenarios, respectively. Calculated annual NEP in RCP8.5 was mostly positive in the southern part of East Asia and Southeast Asia and negative in northern and central parts of East Asia. Under the RCP scenario with higher greenhouse gases emission (RCP8.5), deciduous needleleaf and mixed forests distributed in the middle and high latitudes served as carbon source. In contrast, evergreen broadleaf forests distributed in low latitudes served as carbon sink. The sensitivity study demonstrated that the spatial tendency of NEP was largely influenced by atmospheric CO2 and temperature.
Woldeit, M L; Korz, V
2010-02-03
A functional connection between theta rhythms, information processing, learning and memory formation is well documented by studies focusing on the impact of theta waves on motor activity, global context or phase coding in spatial learning. In the present study we analyzed theta oscillations during a spatial learning task and assessed which specific behavioral contexts were connected to changes in theta power and to the formation of memory. Therefore, we measured hippocampal dentate gyrus theta modulations in male rats that were allowed to establish a long-term spatial reference memory in a holeboard (fixed pattern of baited holes) in comparison to rats that underwent similar training conditions but could not form a reference memory (randomly baited holes). The first group established a pattern specific learning strategy, while the second developed an arbitrary search strategy, visiting increasingly more holes during training. Theta power was equally influenced during the training course in both groups, but was significantly higher when compared to untrained controls. A detailed behavioral analysis, however, revealed behavior- and context-specific differences within the experimental groups. In spatially trained animals theta power correlated with the amounts of reference memory errors in the context of the inspection of unbaited holes and exploration in which, as suggested by time frequency analyses, also slow wave (delta) power was increased. In contrast, in randomly trained animals positive correlations with working memory errors were found in the context of rearing behavior. These findings indicate a contribution of theta/delta to long-lasting memory formation in spatially trained animals, whereas in pseudo trained animals theta seems to be related to attention in order to establish trial specific short-term working memory. Implications for differences in neuronal plasticity found in earlier studies are discussed. Copyright 2010 IBRO. Published by Elsevier Ltd. All rights reserved.
Mitchell, Richard; Ogilvie, David
2017-01-01
Background The World Health Organisation reports that road traffic accidents (accidents) could become the seventh leading cause of death globally by 2030. Accidents often occur in spatial clusters and, generally, there are more accidents in less advantaged areas. Infrastructure changes, such as new roads, can affect the locations and magnitude of accident clusters but evidence of impact is lacking. A new 5-mile motorway extension was opened in 2011 in Glasgow, Scotland. Previous research found no impact on the number of accidents but did not consider their spatial location or socio-economic setting. We evaluated impacts on these, both locally and city-wide. Methods We used STATS19 data covering the period 2008 to 2014 and describing the location and details of all reported accidents involving a personal injury. Poisson-based continuous scan statistics were used to detect spatial clusters of accidents and any change in these over time. Change in the socio-economic distribution of accident cluster locations during the study period was also assessed. Results In each year accidents were strongly clustered, with statistically significant clusters more likely to occur in socio-economically deprived areas. There was no significant shift in the magnitude or location of accident clusters during motorway construction or following opening, either locally or city-wide. There was also no impact on the socio-economic patterning of accident cluster locations. Conclusions Although urban infrastructure changes occur constantly, all around the world, this is the first study to evaluate the impact of such changes on road accident clusters. Despite expectations to the contrary from both proponents and opponents of the M74 extension, we found no beneficial or adverse change in the socio-spatial distribution of accidents associated with its construction, opening or operation. Our approach and findings can help inform urban planning internationally. PMID:28880956
Park, Seong-Beom; Lee, Inah
2016-08-01
Place cells in the hippocampus fire at specific positions in space, and distal cues in the environment play critical roles in determining the spatial firing patterns of place cells. Many studies have shown that place fields are influenced by distal cues in foraging animals. However, it is largely unknown whether distal-cue-dependent changes in place fields appear in different ways in a memory task if distal cues bear direct significance to achieving goals. We investigated this possibility in this study. Rats were trained to choose different spatial positions in a radial arm in association with distal cue configurations formed by visual cue sets attached to movable curtains around the apparatus. The animals were initially trained to associate readily discernible distal cue configurations (0° vs. 80° angular separation between distal cue sets) with different food-well positions and then later experienced ambiguous cue configurations (14° and 66°) intermixed with the original cue configurations. Rats showed no difficulty in transferring the associated memory formed for the original cue configurations when similar cue configurations were presented. Place field positions remained at the same locations across different cue configurations, whereas stability and coherence of spatial firing patterns were significantly disrupted when ambiguous cue configurations were introduced. Furthermore, the spatial representation was extended backward and skewed more negatively at the population level when processing ambiguous cue configurations, compared with when processing the original cue configurations only. This effect was more salient for large cue-separation conditions than for small cue-separation conditions. No significant rate remapping was observed across distal cue configurations. These findings suggest that place cells in the hippocampus dynamically change their detailed firing characteristics in response to a modified cue environment and that some of the firing properties previously reported in a foraging task might carry more functional weight than others when tested in a distal-cue-dependent memory task. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Olsen, Jonathan R; Mitchell, Richard; Ogilvie, David
2017-01-01
The World Health Organisation reports that road traffic accidents (accidents) could become the seventh leading cause of death globally by 2030. Accidents often occur in spatial clusters and, generally, there are more accidents in less advantaged areas. Infrastructure changes, such as new roads, can affect the locations and magnitude of accident clusters but evidence of impact is lacking. A new 5-mile motorway extension was opened in 2011 in Glasgow, Scotland. Previous research found no impact on the number of accidents but did not consider their spatial location or socio-economic setting. We evaluated impacts on these, both locally and city-wide. We used STATS19 data covering the period 2008 to 2014 and describing the location and details of all reported accidents involving a personal injury. Poisson-based continuous scan statistics were used to detect spatial clusters of accidents and any change in these over time. Change in the socio-economic distribution of accident cluster locations during the study period was also assessed. In each year accidents were strongly clustered, with statistically significant clusters more likely to occur in socio-economically deprived areas. There was no significant shift in the magnitude or location of accident clusters during motorway construction or following opening, either locally or city-wide. There was also no impact on the socio-economic patterning of accident cluster locations. Although urban infrastructure changes occur constantly, all around the world, this is the first study to evaluate the impact of such changes on road accident clusters. Despite expectations to the contrary from both proponents and opponents of the M74 extension, we found no beneficial or adverse change in the socio-spatial distribution of accidents associated with its construction, opening or operation. Our approach and findings can help inform urban planning internationally.
Nanoscale Spatial Organization of Prokaryotic Cells Studied by Super-Resolution Optical Microscopy
NASA Astrophysics Data System (ADS)
McEvoy, Andrea Lynn
All cells spatially organize their interiors, and this arrangement is necessary for cell viability. Until recently, it was believed that only eukaryotic cells spatially segregate their components. However, it is becoming increasingly clear that bacteria also assemble their proteins into complex patterns. In eukaryotic cells, spatial organization arises from membrane bound organelles as well as motor transport proteins which can move cargos within the cell. To date, there are no known motor transport proteins in bacteria and most microbes lack membrane bound organelles, so it remains a mystery how bacterial spatial organization emerges. In hind-sight it is not surprising that bacteria also exhibit complex spatial organization considering much of what we have learned about the basic processes that take place in all cells, such as transcription and translation was first discovered in prokaryotic cells. Perhaps the fundamental principles that govern spatial organization in prokaryotic cells may be applicable in eukaryotic cells as well. In addition, bacteria are attractive model organism for spatial organization studies because they are genetically tractable, grow quickly and much biochemical and structural data is known about them. A powerful tool for observing spatial organization in cells is the fluorescence microscope. By specifically tagging a protein of interest with a fluorescent probe, it is possible to examine how proteins organize and dynamically assemble inside cells. A significant disadvantage of this technology is its spatial resolution (approximately 250 nm laterally and 500 nm axially). This limitation on resolution causes closely spaced proteins to look blurred making it difficult to observe the fine structure within the complexes. This resolution limit is especially problematic within small cells such as bacteria. With the recent invention of new optical microscopies, we now can surpass the existing limits of fluorescence imaging. In some cases, we can now see individual proteins inside of large complexes or observe structures with ten times the resolution of conventional imaging. These techniques are known as super-resolution microscopes. In this dissertation, I use super-resolution microscopes to understand how a model microbe, Escherichia coli, assembles complex protein structures. I focus on two spatially organized systems, the chemotaxis network and the cell division machinery. These assembly mechanisms could be general mechanisms for protein assembly in all organisms. I also characterize new fluorescent probes for use in multiple super-resolution imaging modalities and discuss the practicalities of using different super-resolution microscopes. The chemotaxis network in E. coli is the best understood signal transduction network in biology. Chemotaxis receptors cluster into complexes of thousands of proteins located at the cell poles and are used to move bacteria towards favorable stimuli in the environment. In these dense clusters, the receptors can bind each other and communicate to filter out noise and amplify weak signals. It is surprising that chemotaxis receptors are spatially segregated and the mechanism for polar localization of these complexes remains unclear. Using data from PALM images, we develop a model to understand how bacteria organize their receptors into large clusters. The model, stochastic cluster nucleation, is surprising in that is generates micron-scale periodic patterns without the need for accessory proteins to provide scaffolding or active transport. This model may be a general mechanism that cells utilize to organize small and large complexes of proteins. During cell division, E. coli must elongate, replicate its DNA and position its components properly prior to binary fission. Prior to septum formation, a ubiquitous protein called FtsZ, assembles into a ring at mid-cell (Z-ring) which constricts during cell division and recruits the remaining proteins necessary for cytokinesis. Though many details have been revealed about FtsZ, the detailed in vivo structure of the Z-ring is not well understood, and many questions remain about how ring constriction occurs. Using multiple super-resolution imaging modalities, in combination with conventional time-lapse fluorescence imaging, we show that the Z-ring does not form a long uniform filament around the circumference of the bacterium. We detail how this structure changes during division and how removal of proteins that help to position FtsZ affects the Z-ring as it proceeds through cytokinesis. Ultimately we present a simple model for Z-ring constriction during division.
Multispectral computational ghost imaging with multiplexed illumination
NASA Astrophysics Data System (ADS)
Huang, Jian; Shi, Dongfeng
2017-07-01
Computational ghost imaging has attracted wide attention from researchers in many fields over the last two decades. Multispectral imaging as one application of computational ghost imaging possesses spatial and spectral resolving abilities, and is very useful for surveying scenes and extracting detailed information. Existing multispectral imagers mostly utilize narrow band filters or dispersive optical devices to separate light of different wavelengths, and then use multiple bucket detectors or an array detector to record them separately. Here, we propose a novel multispectral ghost imaging method that uses one single bucket detector with multiplexed illumination to produce a colored image. The multiplexed illumination patterns are produced by three binary encoded matrices (corresponding to the red, green and blue colored information, respectively) and random patterns. The results of the simulation and experiment have verified that our method can be effective in recovering the colored object. Multispectral images are produced simultaneously by one single-pixel detector, which significantly reduces the amount of data acquisition.
Electric-field-stimulated protein mechanics
Hekstra, Doeke R.; White, K. Ian; Socolich, Michael A.; Henning, Robert W.; Šrajer, Vukica; Ranganathan, Rama
2017-01-01
The internal mechanics of proteins—the coordinated motions of amino acids and the pattern of forces constraining these motions—connects protein structure to function. Here we describe a new method combining the application of strong electric field pulses to protein crystals with time-resolved X-ray crystallography to observe conformational changes in spatial and temporal detail. Using a human PDZ domain (LNX2PDZ2) as a model system, we show that protein crystals tolerate electric field pulses strong enough to drive concerted motions on the sub-microsecond timescale. The induced motions are subtle, involve diverse physical mechanisms, and occur throughout the protein structure. The global pattern of electric-field-induced motions is consistent with both local and allosteric conformational changes naturally induced by ligand binding, including at conserved functional sites in the PDZ domain family. This work lays the foundation for comprehensive experimental study of the mechanical basis of protein function. PMID:27926732
Spatiotemporal polarization modulation microscopy with a microretarder array
NASA Astrophysics Data System (ADS)
Ding, Changqin; Ulcickas, James R. W.; Simpson, Garth J.
2018-02-01
A patterned microretarder array positioned in the rear conjugate plane of a microscope enables rapid polarizationdependent nonlinear optical microscopy. The pattern introduced to the array results in periodic modulation of the polarization-state of the incident light as a function of position within the field of view with no moving parts or active control. Introduction of a single stationary optical element and a fixed polarizer into the beam of a nonlinear optical microscope enabled nonlinear optical tensor recovery, which informs on local structure and orientation. Excellent agreement was observed between the measured and predicted second harmonic generation (SHG) of z-cut quartz, selected as a test system with well-established nonlinear optical properties. Subsequent studies of spatially varying samples further support the general applicability of this relatively simple strategy for detailed polarization analysis in both conventional and nonlinear optical imaging of structurally diverse samples.
NASA Technical Reports Server (NTRS)
Choudhari, Meelan; Hall, Philip; Streett, Craig
1992-01-01
The generation of long-wavelength, viscous-inviscid interactive Goertler vortices is studied in the linear regime by numerically solving the time-dependent governing equations. It is found that time-dependent surface deformations, which assume a fixed nonzero shape at large times, generate steady Goertler vortices that amplify in the downstream direction. Thus, the Goertler instability in this regime is shown to be convective in nature, contrary to the earlier findings of Ruban and Savenkov. The disturbance pattern created by steady and streamwise-elongated surface obstacles on a concave surface is examined in detail, and also contrasted with the flow pattern due to roughness elements with aspect ratio of order unity on flat surfaces. Finally, the applicability of the Briggs-Bers criterion to unstable physical systems of this type is questioned by providing a counterexample in the form of the inviscid limit of interactive Goertler vortices.
Climate change alters diffusion of forest pest: A model study
NASA Astrophysics Data System (ADS)
Jo, Woo Seong; Kim, Hwang-Yong; Kim, Beom Jun
2017-01-01
Population dynamics with spatial information is applied to understand the spread of pests. We introduce a model describing how pests spread in discrete space. The number of pest descendants at each site is controlled by local information such as temperature, precipitation, and the density of pine trees. Our simulation leads to a pest spreading pattern comparable to the real data for pine needle gall midge in the past. We also simulate the model in two different climate conditions based on two different representative concentration pathways scenarios for the future. We observe that after an initial stage of a slow spread of pests, a sudden change in the spreading speed occurs, which is soon followed by a large-scale outbreak. We found that a future climate change causes the outbreak point to occur earlier and that the detailed spatio-temporal pattern of the spread depends on the source position from which the initial pest infection starts.
Mamiya, Hiroshi; Moodie, Erica E M; Buckeridge, David L
2017-01-01
Unhealthy eating is the most important preventable cause of global death and disability. Effective development and evaluation of preventive initiatives and the identification of disparities in dietary patterns require surveillance of nutrition at a community level. However, nutrition monitoring currently relies on dietary surveys, which cannot efficiently assess food selection at high spatial resolution. However, marketing companies continuously collect and centralize digital grocery transaction data from a geographically representative sample of chain retail food outlets through scanner technologies. We used these data to develop a model to predict store-level sales of carbonated soft drinks, which was applied to all chain food outlets in Montreal, Canada. The resulting map of purchase patterns provides a foundation for developing novel, high-resolution nutrition indicators that reflect dietary preferences at a community level. These detailed nutrition portraits will allow health agencies to tailor healthy eating interventions and promotion programs precisely to meet specific community needs.
NASA Astrophysics Data System (ADS)
WANG, J.; Kim, J.
2014-12-01
In this study, sensitivity of pollutant dispersion on turbulent Schmidt number (Sct) was investigated in a street canyon using a computational fluid dynamics (CFD) model. For this, numerical simulations with systematically varied Sct were performed and the CFD model results were validated against a wind‒tunnel measurement data. The results showed that root mean square error (RMSE) was quite dependent on Sct and dispersion patterns of non‒reactive scalar pollutant with different Sct were quite different among the simulation results. The RMSE was lowest in the case of Sct = 0.35 and the apparent dispersion pattern was most similar to the wind‒tunnel data in the case of Sct = 0.35. Also, numerical simulations using spatially weighted Sct were additionally performed in order for the best reproduction of the wind‒tunnel data. Detailed method and procedure to find the best reproduction will be presented.
NASA Technical Reports Server (NTRS)
Chao, Tien-Hsin; Stoner, William W.
1993-01-01
An optical neural network based on the neocognitron paradigm is introduced. A novel aspect of the architecture design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by feeding back the ouput of the feature correlator interatively to the input spatial light modulator and by updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intraclass fault tolerance and interclass discrimination is achieved. A detailed system description is provided. Experimental demonstrations of a two-layer neural network for space-object discrimination is also presented.
Automatic target recognition using a feature-based optical neural network
NASA Technical Reports Server (NTRS)
Chao, Tien-Hsin
1992-01-01
An optical neural network based upon the Neocognitron paradigm (K. Fukushima et al. 1983) is introduced. A novel aspect of the architectural design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by iteratively feeding back the output of the feature correlator to the input spatial light modulator and updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intra-class fault tolerance and inter-class discrimination is achieved. A detailed system description is provided. Experimental demonstration of a two-layer neural network for space objects discrimination is also presented.
Macroecological factors shape local-scale spatial patterns in agriculturalist settlements.
Tao, Tingting; Abades, Sebastián; Teng, Shuqing; Huang, Zheng Y X; Reino, Luís; Chen, Bin J W; Zhang, Yong; Xu, Chi; Svenning, Jens-Christian
2017-11-15
Macro-scale patterns of human systems ranging from population distribution to linguistic diversity have attracted recent attention, giving rise to the suggestion that macroecological rules shape the assembly of human societies. However, in which aspects the geography of our own species is shaped by macroecological factors remains poorly understood. Here, we provide a first demonstration that macroecological factors shape strong local-scale spatial patterns in human settlement systems, through an analysis of spatial patterns in agriculturalist settlements in eastern mainland China based on high-resolution Google Earth images. We used spatial point pattern analysis to show that settlement spatial patterns are characterized by over-dispersion at fine spatial scales (0.05-1.4 km), consistent with territory segregation, and clumping at coarser spatial scales beyond the over-dispersion signals, indicating territorial clustering. Statistical modelling shows that, at macroscales, potential evapotranspiration and topographic heterogeneity have negative effects on territory size, but positive effects on territorial clustering. These relationships are in line with predictions from territory theory for hunter-gatherers as well as for many animal species. Our results help to disentangle the complex interactions between intrinsic spatial processes in agriculturalist societies and external forcing by macroecological factors. While one may speculate that humans can escape ecological constraints because of unique abilities for environmental modification and globalized resource transportation, our work highlights that universal macroecological principles still shape the geography of current human agricultural societies. © 2017 The Author(s).
Yao, Lei; Chen, Liding; Wei, Wei
2017-01-01
In the context of global urbanization, urban flood risk in many cities has become a serious environmental issue, threatening the health of residents and the environment. A number of hydrological studies have linked urban flooding issues closely to the spectrum of spatial patterns of urbanization, but relatively little attention has been given to small-scale catchments within the realm of urban systems. This study aims to explore the hydrological effects of small-scaled urbanized catchments assigned with various landscape patterns. Twelve typical residential catchments in Beijing were selected as the study areas. Total Impervious Area (TIA), Directly Connected Impervious Area (DCIA), and a drainage index were used as the catchment spatial metrics. Three scenarios were designed as different spatial arrangement of catchment imperviousness. Runoff variables including total and peak runoff depth (Qt and Qp) were simulated by using Strom Water Management Model (SWMM). The relationship between catchment spatial patterns and runoff variables were determined, and the results demonstrated that, spatial patterns have inherent influences on flood risks in small urbanized catchments. Specifically: (1) imperviousness acts as an effective indicator in affecting both Qt and Qp; (2) reducing the number of rainwater inlets appropriately will benefit the catchment peak flow mitigation; (3) different spatial concentrations of impervious surfaces have inherent influences on Qp. These findings provide insights into the role of urban spatial patterns in driving rainfall-runoff processes in small urbanized catchments, which is essential for urban planning and flood management. PMID:28264521
Yao, Lei; Chen, Liding; Wei, Wei
2017-02-28
In the context of global urbanization, urban flood risk in many cities has become a serious environmental issue, threatening the health of residents and the environment. A number of hydrological studies have linked urban flooding issues closely to the spectrum of spatial patterns of urbanization, but relatively little attention has been given to small-scale catchments within the realm of urban systems. This study aims to explore the hydrological effects of small-scaled urbanized catchments assigned with various landscape patterns. Twelve typical residential catchments in Beijing were selected as the study areas. Total Impervious Area ( TIA ), Directly Connected Impervious Area ( DCIA ), and a drainage index were used as the catchment spatial metrics. Three scenarios were designed as different spatial arrangement of catchment imperviousness. Runoff variables including total and peak runoff depth ( Q t and Q p ) were simulated by using Strom Water Management Model (SWMM). The relationship between catchment spatial patterns and runoff variables were determined, and the results demonstrated that, spatial patterns have inherent influences on flood risks in small urbanized catchments. Specifically: (1) imperviousness acts as an effective indicator in affecting both Q t and Q p ; (2) reducing the number of rainwater inlets appropriately will benefit the catchment peak flow mitigation; (3) different spatial concentrations of impervious surfaces have inherent influences on Q p . These findings provide insights into the role of urban spatial patterns in driving rainfall-runoff processes in small urbanized catchments, which is essential for urban planning and flood management.
Calibration of a distributed hydrologic model using observed spatial patterns from MODIS data
NASA Astrophysics Data System (ADS)
Demirel, Mehmet C.; González, Gorka M.; Mai, Juliane; Stisen, Simon
2016-04-01
Distributed hydrologic models are typically calibrated against streamflow observations at the outlet of the basin. Along with these observations from gauging stations, satellite based estimates offer independent evaluation data such as remotely sensed actual evapotranspiration (aET) and land surface temperature. The primary objective of the study is to compare model calibrations against traditional downstream discharge measurements with calibrations against simulated spatial patterns and combinations of both types of observations. While the discharge based model calibration typically improves the temporal dynamics of the model, it seems to give rise to minimum improvement of the simulated spatial patterns. In contrast, objective functions specifically targeting the spatial pattern performance could potentially increase the spatial model performance. However, most modeling studies, including the model formulations and parameterization, are not designed to actually change the simulated spatial pattern during calibration. This study investigates the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale hydrologic model (mHM). This model is selected as it allows for a change in the spatial distribution of key soil parameters through the optimization of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) values directly as input. In addition the simulated aET can be estimated at a spatial resolution suitable for comparison to the spatial patterns observed with MODIS data. To increase our control on spatial calibration we introduced three additional parameters to the model. These new parameters are part of an empirical equation to the calculate crop coefficient (Kc) from daily LAI maps and used to update potential evapotranspiration (PET) as model inputs. This is done instead of correcting/updating PET with just a uniform (or aspect driven) factor used in the mHM model (version 5.3). We selected the 20 most important parameters out of 53 mHM parameters based on a comprehensive sensitivity analysis (Cuntz et al., 2015). We calibrated 1km-daily mHM for the Skjern basin in Denmark using the Shuffled Complex Evolution (SCE) algorithm and inputs at different spatial scales i.e. meteorological data at 10km and morphological data at 250 meters. We used correlation coefficients between observed monthly (summer months only) MODIS data calculated from cloud free days over the calibration period from 2001 to 2008 and simulated aET from mHM over the same period. Similarly other metrics, e.g mapcurves and fraction skill-score, are also included in our objective function to assess the co-location of the grid-cells. The preliminary results show that multi-objective calibration of mHM against observed streamflow and spatial patterns together does not significantly reduce the spatial errors in aET while it improves the streamflow simulations. This is a strong signal for further investigation of the multi parameter regionalization affecting spatial aET patterns and weighting the spatial metrics in the objective function relative to the streamflow metrics.
Brakebill, J.W.; Preston, S.D.
2003-01-01
The U.S. Geological Survey has developed a methodology for statistically relating nutrient sources and land-surface characteristics to nutrient loads of streams. The methodology is referred to as SPAtially Referenced Regressions On Watershed attributes (SPARROW), and relates measured stream nutrient loads to nutrient sources using nonlinear statistical regression models. A spatially detailed digital hydrologic network of stream reaches, stream-reach characteristics such as mean streamflow, water velocity, reach length, and travel time, and their associated watersheds supports the regression models. This network serves as the primary framework for spatially referencing potential nutrient source information such as atmospheric deposition, septic systems, point-sources, land use, land cover, and agricultural sources and land-surface characteristics such as land use, land cover, average-annual precipitation and temperature, slope, and soil permeability. In the Chesapeake Bay watershed that covers parts of Delaware, Maryland, Pennsylvania, New York, Virginia, West Virginia, and Washington D.C., SPARROW was used to generate models estimating loads of total nitrogen and total phosphorus representing 1987 and 1992 land-surface conditions. The 1987 models used a hydrologic network derived from an enhanced version of the U.S. Environmental Protection Agency's digital River Reach File, and course resolution Digital Elevation Models (DEMs). A new hydrologic network was created to support the 1992 models by generating stream reaches representing surface-water pathways defined by flow direction and flow accumulation algorithms from higher resolution DEMs. On a reach-by-reach basis, stream reach characteristics essential to the modeling were transferred to the newly generated pathways or reaches from the enhanced River Reach File used to support the 1987 models. To complete the new network, watersheds for each reach were generated using the direction of surface-water flow derived from the DEMs. This network improves upon existing digital stream data by increasing the level of spatial detail and providing consistency between the reach locations and topography. The hydrologic network also aids in illustrating the spatial patterns of predicted nutrient loads and sources contributed locally to each stream, and the percentages of nutrient load that reach Chesapeake Bay.
Optimization of landscape pattern [Chapter 8
John Hof; Curtis Flather
2007-01-01
A fundamental assumption in landscape ecology is that spatial patterns have significant influences on the flows of materials, energy, and information while processes create, modify, and maintain spatial patterns. Thus, it is of paramount importance in both theory and practice to address the questions of landscape pattern optimization ... For example, can landscape...
Buckley, Hannah L; Rafat, Arash; Ridden, Johnathon D; Cruickshank, Robert H; Ridgway, Hayley J; Paterson, Adrian M
2014-01-01
The role of species' interactions in structuring biological communities remains unclear. Mutualistic symbioses, involving close positive interactions between two distinct organismal lineages, provide an excellent means to explore the roles of both evolutionary and ecological processes in determining how positive interactions affect community structure. In this study, we investigate patterns of co-diversification between fungi and algae for a range of New Zealand lichens at the community, genus, and species levels and explore explanations for possible patterns related to spatial scale and pattern, taxonomic diversity of the lichens considered, and the level sampling replication. We assembled six independent datasets to compare patterns in phylogenetic congruence with varied spatial extent of sampling, taxonomic diversity and level of specimen replication. For each dataset, we used the DNA sequences from the ITS regions of both the fungal and algal genomes from lichen specimens to produce genetic distance matrices. Phylogenetic congruence between fungi and algae was quantified using distance-based redundancy analysis and we used geographic distance matrices in Moran's eigenvector mapping and variance partitioning to evaluate the effects of spatial variation on the quantification of phylogenetic congruence. Phylogenetic congruence was highly significant for all datasets and a large proportion of variance in both algal and fungal genetic distances was explained by partner genetic variation. Spatial variables, primarily at large and intermediate scales, were also important for explaining genetic diversity patterns in all datasets. Interestingly, spatial structuring was stronger for fungal than algal genetic variation. As the spatial extent of the samples increased, so too did the proportion of explained variation that was shared between the spatial variables and the partners' genetic variation. Different lichen taxa showed some variation in their phylogenetic congruence and spatial genetic patterns and where greater sample replication was used, the amount of variation explained by partner genetic variation increased. Our results suggest that the phylogenetic congruence pattern, at least at small spatial scales, is likely due to reciprocal co-adaptation or co-dispersal. However, the detection of these patterns varies among different lichen taxa, across spatial scales and with different levels of sample replication. This work provides insight into the complexities faced in determining how evolutionary and ecological processes may interact to generate diversity in symbiotic association patterns at the population and community levels. Further, it highlights the critical importance of considering sample replication, taxonomic diversity and spatial scale in designing studies of co-diversification.
Mundo, Ignacio A; Wiegand, Thorsten; Kanagaraj, Rajapandian; Kitzberger, Thomas
2013-07-15
Fire management requires an understanding of the spatial characteristics of fire ignition patterns and how anthropogenic and natural factors influence ignition patterns across space. In this study we take advantage of a recent fire ignition database (855 points) to conduct a comprehensive analysis of the spatial pattern of fire ignitions in the western area of Neuquén province (57,649 km(2)), Argentina, for the 1992-2008 period. The objectives of our study were to better understand the spatial pattern and the environmental drivers of the fire ignitions, with the ultimate aim of supporting fire management. We conducted our analyses on three different levels: statistical "habitat" modelling of fire ignition (natural, anthropogenic, and all causes) based on an information theoretic approach to test several competing hypotheses on environmental drivers (i.e. topographic, climatic, anthropogenic, land cover, and their combinations); spatial point pattern analysis to quantify additional spatial autocorrelation in the ignition patterns; and quantification of potential spatial associations between fires of different causes relative to towns using a novel implementation of the independence null model. Anthropogenic fire ignitions were best predicted by the most complex habitat model including all groups of variables, whereas natural ignitions were best predicted by topographic, climatic and land-cover variables. The spatial pattern of all ignitions showed considerable clustering at intermediate distances (<40 km) not captured by the probability of fire ignitions predicted by the habitat model. There was a strong (linear) and highly significant increase in the density of fire ignitions with decreasing distance to towns (<5 km), but fire ignitions of natural and anthropogenic causes were statistically independent. A two-dimensional habitat model that quantifies differences between ignition probabilities of natural and anthropogenic causes allows fire managers to delineate target areas for consideration of major preventive treatments, strategic placement of fuel treatments, and forecasting of fire ignition. The techniques presented here can be widely applied to situations where a spatial point pattern is jointly influenced by extrinsic environmental factors and intrinsic point interactions. Copyright © 2013 Elsevier Ltd. All rights reserved.
Finer parcellation reveals detailed correlational structure of resting-state fMRI signals.
Dornas, João V; Braun, Jochen
2018-01-15
Even in resting state, the human brain generates functional signals (fMRI) with complex correlational structure. To simplify this structure, it is common to parcellate a standard brain into coarse chunks. Finer parcellations are considered less reproducible and informative, due to anatomical and functional variability of individual brains. Grouping signals with similar local correlation profiles, restricted to each anatomical region (Tzourio-Mazoyer et al., 2002), we divide a standard brain into 758 'functional clusters' averaging 1.7cm 3 gray matter volume ('MD758' parcellation). We compare 758 'spatial clusters' of similar size ('S758'). 'Functional clusters' are spatially contiguous and cluster quality (integration and segregation of temporal variance) is far superior to 'spatial clusters', comparable to multi-modal parcellations of half the resolution (Craddock et al., 2012; Glasser et al., 2016). Moreover, 'functional clusters' capture many long-range functional correlations, with O(10 5 ) reproducibly correlated cluster pairs in different anatomical regions. The pattern of functional correlations closely mirrors long-range anatomical connectivity established by fibre tracking. MD758 is comparable to coarser parcellations (Craddock et al., 2012; Glasser et al., 2016) in terms of cluster quality, correlational structure (54% relative mutual entropy vs 60% and 61%), and sparseness (35% significant pairwise correlations vs 36% and 44%). We describe and evaluate a simple path to finer functional parcellations of the human brain. Detailed correlational structure is surprisingly consistent between individuals, opening new possibilities for comparing functional correlations between cognitive conditions, states of health, or pharmacological interventions. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.
Younger Dryas equilibrium line altitudes and precipitation patterns in the Alps
NASA Astrophysics Data System (ADS)
Kerschner, Hanns; Moran, Andrew; Ivy-Ochs, Susan
2016-04-01
Moraine systems of the "Egesen Stadial" are widespread and easily identifiable features in the Alps. Absolute dating with terrestrial cosmogenic radionuclides shows that the maximum extent was reached during the early Younger Dryas (YD), probably as a reaction to the intense climatic downturn subsequent to Lateglacial Interstadial. In recent years, several new studies and the availability of high-quality laser-scan hillshades and orthophotos allowed a significant extension of the database of YD glaciers as "palaeoprecipitation gauges" to large hitherto unmapped regions in the Austrian and Swiss Alps. The equilibrium line altitude (ELA) of the glaciers and its lowering relative to the Little Ice Age ELA (dELA) shows a distinct and systematic spatial pattern. Along the northern slope of the Alps, dELAs are usually large (around 400 m and perhaps even more), while dELAs range around 200 m in the well sheltered areas of the central Alps, e.g. in the Engadine and in western Tyrol. Both stochastic glacier-climate models (e.g. Ohmura et al. 1992) and the heat- and mass balance equation (Kuhn 1981) allow the reconstruction of precipitation change under the assumption of a spatially constant summer temperature depression, which in turn can be estimated from biological proxies. This allows to draw the spatial pattern of precipitation change with considerable detail. Precipitation change is clearly controlled by the local relief like high mountain chains, deeply incised and long valleys and mountain passes. Generally the contrast between the northern fringe of the Alps and the interior was more pronounced than today. Climate in the Northern and and Northwestern Alps was rather wet with precipitation totals eventually exceeding modern annual sums. The central Alps received 20 - 30% less precipitation than today, mainly due to reduced winter precipitation. In the southern Alps, still scarce spatial information points to precipitation sums which were approximately similar to modern values. As winter precipitation was probably much smaller than today, seasonal contrasts were more pronounced. In total, the pattern of YD precipitation change is remarkably similar to precipitation patterns caused by westerly and northwesterly cyclonic airflow during the present-day hydrologic winter (October - March). Kerschner, H., G. Kaser, R. Sailer (2000): Alpine Younger Dryas glaciers as paleo-precipitation gauges. Annals of Glaciology 31, 80-84. Kerschner, H. and S. Ivy-Ochs (2007): Palaeoclimate from glaciers: Examples from the Eastern Alps during the Alpine Lateglacial and early Holocene. Global and Planetary Change 60, 58-71.
NASA Astrophysics Data System (ADS)
Jackson, Bethanna; Trodahl, Martha; Maxwell, Deborah; Easton, Stuart
2016-04-01
This talk discusses recent progress in adapting the Land Utilisation and Capability Indicator (LUCI) framework to take account of the impact of detailed farm management on greenhouse gas emissions and on water, sediment and nutrient delivery to waterways. LUCI is a land management decision support framework which examines the impact of current and potential interventions on a variety of outcomes, including flood mitigation, water supply, greenhouse gas emissions, biodiversity, erosion, sediment and nutrient delivery to waterways, and agricultural production. The potential of the landscape to provide benefits is a function of both the biophysical properties of individual landscape elements and their configuration. Both are respected in LUCI where possible. For example, the hydrology, sediment and chemical routing algorithms are based on physical principles of hillslope flow, taking information on the storage and permeability capacity of elements within the landscape from soil and land use data and honoring physical thresholds, mass and energy balance constraints. LUCI discretizes hydrological response units within the landscape according to similarity of their hydraulic properties and preserves spatially explicit topographical routing. Implications of keeping the "status quo" or potential scenarios of land management change can then be evaluated under different meteorological or climatic events (e.g. flood return periods, rainfall events, droughts), cascading water through the hydrological response units using a "fill and spill" approach. These and other component algorithms are designed to be fast-running while maintaining physical consistency and fine spatial detail. This allows it to operate from subfield level scale to catchment, or even national scale, simultaneously. It analyses and communicates the spatial pattern of individual provision and tradeoffs/synergies between desired outcomes at detailed resolutions and provides suggestions on where management change could be most efficiently targeted to meet water quality targets while maintaining production. Historically, LUCI has inferred land management from nationally available land cover categorisations, so lacked the capacity to discriminate between differences in more detailed management (tillage information, type of irrigation system, stocking numbers and type, etc). However, recently a collaboration with a farmer cooperative has commenced. LUCI is being further developed to take in a range of more detailed management information, which can be entered directly to LUCI or easily integrated via existing farm management files. Example output using a variety of management scenarios and ongoing "validation" of LUCI's performance at the farm scale will be presented using New Zealand crop, beef and dairy farms as case studies.
Quadratic spatial soliton interactions
NASA Astrophysics Data System (ADS)
Jankovic, Ladislav
Quadratic spatial soliton interactions were investigated in this Dissertation. The first part deals with characterizing the principal features of multi-soliton generation and soliton self-reflection. The second deals with two beam processes leading to soliton interactions and collisions. These subjects were investigated both theoretically and experimentally. The experiments were performed by using potassium niobate (KNBO 3) and periodically poled potassium titanyl phosphate (KTP) crystals. These particular crystals were desirable for these experiments because of their large nonlinear coefficients and, more importantly, because the experiments could be performed under non-critical-phase-matching (NCPM) conditions. The single soliton generation measurements, performed on KNBO3 by launching the fundamental component only, showed a broad angular acceptance bandwidth which was important for the soliton collisions performed later. Furthermore, at high input intensities multi-soliton generation was observed for the first time. The influence on the multi-soliton patterns generated of the input intensity and beam symmetry was investigated. The combined experimental and theoretical efforts indicated that spatial and temporal noise on the input laser beam induced multi-soliton patterns. Another research direction pursued was intensity dependent soliton routing by using of a specially engineered quadratically nonlinear interface within a periodically poled KTP sample. This was the first time demonstration of the self-reflection phenomenon in a system with a quadratic nonlinearity. The feature investigated is believed to have a great potential for soliton routing and manipulation by engineered structures. A detailed investigation was conducted on two soliton interaction and collision processes. Birth of an additional soliton resulting from a two soliton collision was observed and characterized for the special case of a non-planar geometry. A small amount of spiraling, up to 30 degrees rotation, was measured in the experiments performed. The parameters relevant for characterizing soliton collision processes were also studied in detail. Measurements were performed for various collision angles (from 0.2 to 4 degrees), phase mismatch, relative phase between the solitons and the distance to the collision point within the sample (which affects soliton formation). Both the individual and combined effects of these collision variables were investigated. Based on the research conducted, several all-optical switching scenarios were proposed.
A Comparative Study of the Traditional Houses Kaili and Bugis-Makassar in Indonesia
NASA Astrophysics Data System (ADS)
Suharto, M. F.; Kawet, R. S. S. I.; Tumanduk, M. S. S. S.
2018-02-01
In this study, I compared the physical elements of two Indonesian traditional houses between a Kaili tribe (Central Sulawesi) and a Bugis-Makassar tribe (South Sulawesi). If we viewed of the name, meaning and function from both traditional houses have similarities, namely the Souraja/Saoraja house (House of the King), however, observed more detail the physical elements of architecture also show the differences. The spatial, physical and stylistic systems (N. John Habraken’s theory) were applied to analyze their differences and the similarities of the physical elements of architecture on those two traditional houses. The results of the analysis identified that the physical elements of architecture such as the orientation, the function and distribution of rooms (the spatial system), the constructions and materials of floor, wall and roof (the physical system) and the opening types of the door and window as well as ornaments used showed similarities. Meanwhile the physical elements of architecture such as the arrangement of columns, form and spatial pattern as well as the placement of the stairs (the spatial system), the constructions and materials of foundation, column and beam (the physical system) as well as the form of the roof and façade found differences of both traditional houses.
NASA Astrophysics Data System (ADS)
Son, Geunsoo; Kim, Dongsu; Kim, YoungDo; Lyu, Siwan; Kim, Seojun
2017-04-01
River confluences are zones where two rivers with different geomorphic and hydraulic characteristics amalgamate, resulting in rapid change in terms of flow regime, sediment entrainment and hydraulic geometry. In these confluence zones, the flow structure is basically complicated responded with concurrent mixing of physical and chemical aquatic properties, and continuous channel morphology could be changed due to erosion and sedimentation. In addition, the confluences are regions in which two rivers join and play an important role in river ecology. In order to characterize the mixing process of confluence for understanding the impacts of a river on the other river, therefore, it has been crucial to analyze the spatial mixing patterns for main streams depending on various inflow conditions of tributaries. However, most conventional studies have mostly relied upon hydraulic or water quality numerical models for understanding mixing pattern analysis of confluences, due to the difficulties to acquire a wide spatial range of in-situ data especially for characterizing this kind of mixing process. Even with intensive in-situ measurements, those researches tended to focus mainly on the hydraulic characteristics such as the flow and morphological complexity of confluence, so that very few studies comprehensively included sediment variation with flow at the same time. In this study, subsequently, flow and sediment mixing characteristics were concurrently investigated in the confluence between Nakdong and Nam river in South Korea, where it has been frequently questioned to determine how Nam river affects Nakdong river that recently have suffered various environmental problems such as green algae bloom and erosion/deposition in the confluence. We basically examined the mixing characteristics of confluence by using acoustic Doppler current profilers (ADCPs) which were used to measure hydraulic factors such as flow rate and depth, as well as measuring the suspended sediment concentration by using acoustic backscatter. Cross-sectional ADCP measurements in a confluence were collected with high spatial resolution in order to analyze the details of spatial distribution in the perspective of the three-dimensional mixing patterns of flow and sediment, where backscatters (or SNR) measured from ADCPs were used to track sediment mixing assuming that it could be a surrogate to estimate the suspended sediment concentration. Raw backscatter data were corrected by considering the beam spreading and absorption by water. Also, an optical Laser diffraction instrument (LISST) was used to verify the method of acoustic backscatter and to collect the particle size distribution of main stream and tributary. In addition, image-based spatial distributions of sediment mixture in the confluence were monitored in various flow conditions by using an unmanned aerial vehicle (UAV), which were compared with the spatial distribution of acoustic backscatter. As results, we found that when acoustic backscatter and flow measurements by ADCPs were well processed, they could be proper indicators to identify the spatial patterns of the three-dimensional mixing process between two rivers.
Lehtomäki, Joona; Tuominen, Sakari; Toivonen, Tuuli; Leinonen, Antti
2015-01-01
The boreal region is facing intensifying resource extraction pressure, but the lack of comprehensive biodiversity data makes operative forest conservation planning difficult. Many countries have implemented forest inventory schemes and are making extensive and up-to-date forest databases increasingly available. Some of the more detailed inventory databases, however, remain proprietary and unavailable for conservation planning. Here, we investigate how well different open and proprietary forest inventory data sets suit the purpose of conservation prioritization in Finland. We also explore how much priorities are affected by using the less accurate but open data. First, we construct a set of indices for forest conservation value based on quantitative information commonly found in forest inventories. These include the maturity of the trees, tree species composition, and site fertility. Secondly, using these data and accounting for connectivity between forest types, we investigate the patterns in conservation priority. For prioritization, we use Zonation, a method and software for spatial conservation prioritization. We then validate the prioritizations by comparing them to known areas of high conservation value. We show that the overall priority patterns are relatively consistent across different data sources and analysis options. However, the coarse data cannot be used to accurately identify the high-priority areas as it misses much of the fine-scale variation in forest structures. We conclude that, while inventory data collected for forestry purposes may be useful for forest conservation purposes, it needs to be detailed enough to be able to account for more fine-scaled features of high conservation value. These results underline the importance of making detailed inventory data publicly available. Finally, we discuss how the prioritization methodology we used could be integrated into operative forest management, especially in countries in the boreal zone. PMID:26317227
Lehtomäki, Joona; Tuominen, Sakari; Toivonen, Tuuli; Leinonen, Antti
2015-01-01
The boreal region is facing intensifying resource extraction pressure, but the lack of comprehensive biodiversity data makes operative forest conservation planning difficult. Many countries have implemented forest inventory schemes and are making extensive and up-to-date forest databases increasingly available. Some of the more detailed inventory databases, however, remain proprietary and unavailable for conservation planning. Here, we investigate how well different open and proprietary forest inventory data sets suit the purpose of conservation prioritization in Finland. We also explore how much priorities are affected by using the less accurate but open data. First, we construct a set of indices for forest conservation value based on quantitative information commonly found in forest inventories. These include the maturity of the trees, tree species composition, and site fertility. Secondly, using these data and accounting for connectivity between forest types, we investigate the patterns in conservation priority. For prioritization, we use Zonation, a method and software for spatial conservation prioritization. We then validate the prioritizations by comparing them to known areas of high conservation value. We show that the overall priority patterns are relatively consistent across different data sources and analysis options. However, the coarse data cannot be used to accurately identify the high-priority areas as it misses much of the fine-scale variation in forest structures. We conclude that, while inventory data collected for forestry purposes may be useful for forest conservation purposes, it needs to be detailed enough to be able to account for more fine-scaled features of high conservation value. These results underline the importance of making detailed inventory data publicly available. Finally, we discuss how the prioritization methodology we used could be integrated into operative forest management, especially in countries in the boreal zone.
Grid cell hexagonal patterns formed by fast self-organized learning within entorhinal cortex.
Mhatre, Himanshu; Gorchetchnikov, Anatoli; Grossberg, Stephen
2012-02-01
Grid cells in the dorsal segment of the medial entorhinal cortex (dMEC) show remarkable hexagonal activity patterns, at multiple spatial scales, during spatial navigation. It has previously been shown how a self-organizing map can convert firing patterns across entorhinal grid cells into hippocampal place cells that are capable of representing much larger spatial scales. Can grid cell firing fields also arise during navigation through learning within a self-organizing map? This article describes a simple and general mathematical property of the trigonometry of spatial navigation which favors hexagonal patterns. The article also develops a neural model that can learn to exploit this trigonometric relationship. This GRIDSmap self-organizing map model converts path integration signals into hexagonal grid cell patterns of multiple scales. GRIDSmap creates only grid cell firing patterns with the observed hexagonal structure, predicts how these hexagonal patterns can be learned from experience, and can process biologically plausible neural input and output signals during navigation. These results support an emerging unified computational framework based on a hierarchy of self-organizing maps for explaining how entorhinal-hippocampal interactions support spatial navigation. Copyright © 2010 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Koch, Julian; Cüneyd Demirel, Mehmet; Stisen, Simon
2018-05-01
The process of model evaluation is not only an integral part of model development and calibration but also of paramount importance when communicating modelling results to the scientific community and stakeholders. The modelling community has a large and well-tested toolbox of metrics to evaluate temporal model performance. In contrast, spatial performance evaluation does not correspond to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study makes a contribution towards advancing spatial-pattern-oriented model calibration by rigorously testing a multiple-component performance metric. The promoted SPAtial EFficiency (SPAEF) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multiple-component approach is found to be advantageous in order to achieve the complex task of comparing spatial patterns. SPAEF, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are applied in a spatial-pattern-oriented model calibration of a catchment model in Denmark. Results suggest the importance of multiple-component metrics because stand-alone metrics tend to fail to provide holistic pattern information. The three SPAEF components are found to be independent, which allows them to complement each other in a meaningful way. In order to optimally exploit spatial observations made available by remote sensing platforms, this study suggests applying bias insensitive metrics which further allow for a comparison of variables which are related but may differ in unit. This study applies SPAEF in the hydrological context using the mesoscale Hydrologic Model (mHM; version 5.8), but we see great potential across disciplines related to spatially distributed earth system modelling.
Curtis, Andrew; Ye, Xinyue; Hachey, Kevin; Bourdeaux, Margaret; Norris, Alison
2015-10-16
Although it is widely acknowledged that areas of conflict are associated with a high health burden, from a geospatial perspective it is difficult to establish these patterns at fine scales because of a lack of data. The release of the "WikiLeaks" Afghan War Diary (AWD) provides an interesting opportunity to advance analysis and theory into this interrelationship. This paper will apply two different space time analyses to identify patterns of improvised explosive devices (IED) detonations for the period of 2004 to 2009 in Afghanistan. There is considerable spatial and temporal heterogeneity in IED explosions, with concentrations often following transportation links. The results are framed in terms of a resource for subsequent analyses to other existing health research in Afghanistan. To facilitate this, in our discussion we present a Google Earth file of overlapping rates that can be distributed to any researcher interested in combining his/her fine scale health data with a similarly granular layer of violence. The release of the AWD presents a previously unavailable opportunity to consider how spatially detailed data about violence can be incorporated into understanding, and predicting, health related spillover effects. The AWD can enrich previous research conducted on Afghanistan, and provide a justification for future "official" data sharing at appropriately fine scales.
Hierarchical streamline bundles.
Yu, Hongfeng; Wang, Chaoli; Shene, Ching-Kuang; Chen, Jacqueline H
2012-08-01
Effective 3D streamline placement and visualization play an essential role in many science and engineering disciplines. The main challenge for effective streamline visualization lies in seed placement, i.e., where to drop seeds and how many seeds should be placed. Seeding too many or too few streamlines may not reveal flow features and patterns either because it easily leads to visual clutter in rendering or it conveys little information about the flow field. Not only does the number of streamlines placed matter, their spatial relationships also play a key role in understanding the flow field. Therefore, effective flow visualization requires the streamlines to be placed in the right place and in the right amount. This paper introduces hierarchical streamline bundles, a novel approach to simplifying and visualizing 3D flow fields defined on regular grids. By placing seeds and generating streamlines according to flow saliency, we produce a set of streamlines that captures important flow features near critical points without enforcing the dense seeding condition. We group spatially neighboring and geometrically similar streamlines to construct a hierarchy from which we extract streamline bundles at different levels of detail. Streamline bundles highlight multiscale flow features and patterns through clustered yet not cluttered display. This selective visualization strategy effectively reduces visual clutter while accentuating visual foci, and therefore is able to convey the desired insight into the flow data.
Impact of topography on the diurnal cycle of summertime moist convection in idealized simulations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hassanzadeh, Hanieh; Schmidli, Jürg; Langhans, Wolfgang
The impact of an isolated mesoscale mountain on the diurnal cycle of moist convection and its spatial variation is investigated. Convection-resolving simulations of flow over 3D Gaussian-shaped mountains are performed for a conditionally unstable atmosphere under diurnal radiative forcing. The results show considerable spatial variability in terms of timing and amount of convective precipitation. This variability relates to different physical mechanisms responsible for convection initiation in different parts of the domain. During the late morning, the mass convergence from the radiatively driven diurnal upslope flow confronting the large-scale incident background flow triggers strong convective precipitation over the mountain lee slope.more » As a consequence, instabilities in the boundary layer are swept out by the emerging cold pool in the vicinity of the mountain, and some parts over the mountain near-field receive less rainfall than the far-field. Over the latter, an unperturbed boundary-layer growth allows for sporadic convective initiation. Still, secondary convection triggered over the leading edge of the cold pool spreads some precipitation over the downstream near-field. Detailed analysis of our control simulation provides further explanation of this frequently observed precipitation pattern over mountains and adjacent plains. Sensitivity experiments indicate a significant influence of the mountain height on the precipitation pattern over the domain.« less
Structure-from-motion approach for characterization of bioerosion patterns using UAV imagery.
Genchi, Sibila A; Vitale, Alejandro J; Perillo, Gerardo M E; Delrieux, Claudio A
2015-02-04
The aim of this work is to evaluate the applicability of the 3D model obtained through Structure-from-Motion (SFM) from unmanned aerial vehicle (UAV) imagery, in order to characterize bioerosion patterns (i.e., cavities for roosting and nesting) caused by burrowing parrots on a cliff in Bahía Blanca, Argentina. The combined use of SFM-UAV technology was successfully applied for the 3D point cloud model reconstruction. The local point density, obtained by means of a sphere of radius equal to 0.5 m, reached a mean value of 9749, allowing to build a high-resolution model (0.013 m) for resolving fine spatial details in topography. To test the model, we compared it with another point cloud dataset which was created using a low cost do-it-yourself terrestrial laser scanner; the results showed that our georeferenced model had a good accuracy. In addition, an innovative method for the detection of the bioerosion features was implemented, through the processing of data provided by SFM like color and spatial coordinates (particularly the y coordinate). From the 3D model, we also derived topographic calculations such as slope angle and surface roughness, to get associations between the surface topography and bioerosion features.
Impact of topography on the diurnal cycle of summertime moist convection in idealized simulations
Hassanzadeh, Hanieh; Schmidli, Jürg; Langhans, Wolfgang; ...
2015-08-31
The impact of an isolated mesoscale mountain on the diurnal cycle of moist convection and its spatial variation is investigated. Convection-resolving simulations of flow over 3D Gaussian-shaped mountains are performed for a conditionally unstable atmosphere under diurnal radiative forcing. The results show considerable spatial variability in terms of timing and amount of convective precipitation. This variability relates to different physical mechanisms responsible for convection initiation in different parts of the domain. During the late morning, the mass convergence from the radiatively driven diurnal upslope flow confronting the large-scale incident background flow triggers strong convective precipitation over the mountain lee slope.more » As a consequence, instabilities in the boundary layer are swept out by the emerging cold pool in the vicinity of the mountain, and some parts over the mountain near-field receive less rainfall than the far-field. Over the latter, an unperturbed boundary-layer growth allows for sporadic convective initiation. Still, secondary convection triggered over the leading edge of the cold pool spreads some precipitation over the downstream near-field. Detailed analysis of our control simulation provides further explanation of this frequently observed precipitation pattern over mountains and adjacent plains. Sensitivity experiments indicate a significant influence of the mountain height on the precipitation pattern over the domain.« less
Simulation of vehicle acoustics in support of netted sensor research and development
NASA Astrophysics Data System (ADS)
Christou, Carol T.; Jacyna, Garry M.
2005-05-01
The MITRE Corporation has initiated a three-year internally-funded research program in netted sensors, the first-year effort focusing on vehicle detection for border monitoring. An important component is developing an understanding of the complex acoustic structure of vehicle noise to aid in netted sensor-based detection and classification. This presentation will discuss the design of a high-fidelity vehicle acoustic simulator to model the generation and transmission of acoustic energy from a moving vehicle to a collection of sensor nodes. Realistic spatially-dependent automobile sounds are generated from models of the engine cylinder firing rates, muffler and manifold resonances, and speed-dependent tire whine noise. Tire noise is the dominant noise source for vehicle speeds in excess of 30 miles per hour (MPH). As a result, we have developed detailed models that successfully predict the tire noise spectrum as a function of speed, road surface wave-number spectrum, tire geometry, and tire tread pattern. We have also included realistic descriptions of the spatial directivity patterns for the engine harmonics, muffler, and tire whine noise components. The acoustic waveforms are propagated to each sensor node using a simple phase-dispersive multi-path model. A brief description of the models and their corresponding outputs is provided.
NASA Astrophysics Data System (ADS)
Jackson, D.; Delgado-Fernandez, I.; Lynch, K.; Baas, A. C.; Cooper, J. A.; Beyers, M.
2010-12-01
The input of aeolian sediment into foredune systems from beaches represents a key component of sediment budget analysis along many soft sedimentary coastlines. Where there are significant offshore wind components in local wind regimes this is normally excluded from analysis. However, recent work has shown that if the topography of the foredune is favourable then this offshore component is steered or undergoes flow reversal through leeside eddying to give onshore transport events at the back beach under offshore flow conditions. At particular distances from the foredune crest flow reattaches to the surface to continue its incident offshore direction. The location of this reattachment point has important implications for aeolian transport of sand on the back beach and foredune toe locations. This study reports initial results where the positioning of the reattachment point is mobile and is driven by incident wind velocity (at the foredune crest) and the actual undulations of the foredune crest’s topography, dictating heterogeneous flow behaviour at the beach. Using detailed field measurements (25 Hz, three-dimensional sonic anemometry) and computational fluid dynamic modelling, a temporal and spatial pattern of reattachment positions are described. Implications for aeolian transport and dune evolution are also examined.
Structure-from-Motion Approach for Characterization of Bioerosion Patterns Using UAV Imagery
Genchi, Sibila A.; Vitale, Alejandro J.; Perillo, Gerardo M. E.; Delrieux, Claudio A.
2015-01-01
The aim of this work is to evaluate the applicability of the 3D model obtained through Structure-from-Motion (SFM) from unmanned aerial vehicle (UAV) imagery, in order to characterize bioerosion patterns (i.e., cavities for roosting and nesting) caused by burrowing parrots on a cliff in Bahía Blanca, Argentina. The combined use of SFM-UAV technology was successfully applied for the 3D point cloud model reconstruction. The local point density, obtained by means of a sphere of radius equal to 0.5 m, reached a mean value of 9749, allowing to build a high-resolution model (0.013 m) for resolving fine spatial details in topography. To test the model, we compared it with another point cloud dataset which was created using a low cost do-it-yourself terrestrial laser scanner; the results showed that our georeferenced model had a good accuracy. In addition, an innovative method for the detection of the bioerosion features was implemented, through the processing of data provided by SFM like color and spatial coordinates (particularly the y coordinate). From the 3D model, we also derived topographic calculations such as slope angle and surface roughness, to get associations between the surface topography and bioerosion features. PMID:25658392
Temporal and spatial transcriptomic and microRNA dynamics of CAM photosynthesis in pineapple.
Wai, Ching M; VanBuren, Robert; Zhang, Jisen; Huang, Lixian; Miao, Wenjing; Edger, Patrick P; Yim, Won C; Priest, Henry D; Meyers, Blake C; Mockler, Todd; Smith, J Andrew C; Cushman, John C; Ming, Ray
2017-10-01
The altered carbon assimilation pathway of crassulacean acid metabolism (CAM) photosynthesis results in an up to 80% higher water-use efficiency than C 3 photosynthesis in plants making it a potentially useful pathway for engineering crop plants with improved drought tolerance. Here we surveyed detailed temporal (diel time course) and spatial (across a leaf gradient) gene and microRNA (miRNA) expression patterns in the obligate CAM plant pineapple [Ananas comosus (L.) Merr.]. The high-resolution transcriptome atlas allowed us to distinguish between CAM-related and non-CAM gene copies. A differential gene co-expression network across green and white leaf diel datasets identified genes with circadian oscillation, CAM-related functions, and source-sink relations. Gene co-expression clusters containing CAM pathway genes are enriched with clock-associated cis-elements, suggesting circadian regulation of CAM. About 20% of pineapple microRNAs have diel expression patterns, with several that target key CAM-related genes. Expression and physiology data provide a model for CAM-specific carbohydrate flux and long-distance hexose transport. Together these resources provide a list of candidate genes for targeted engineering of CAM into C 3 photosynthesis crop species. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.
Single beam write and/or replay of spatial heterodyne holograms
Thomas, Clarence E.; Hanson, Gregory R.
2007-11-20
A method of writing a spatially heterodyne hologram having spatially heterodyne fringes includes: passing a single write beam through a spatial light modulator that digitally modulates said single write beam; and focusing the single write beam at a focal plane of a lens to impose a holographic diffraction grating pattern on the photorefractive crystal, the holographic diffraction grating pattern including the spatially heterodyne hologram having spatially heterodyne fringes, wherein only said single write beam is incident on said photorefractive crystal without a reference beam. A method of replaying a spatially heterodyne hologram having spatially heterodyne fringes at a replay angle includes: illuminating a photorefractive crystal having a holographic diffraction grating with a beam from a laser at an illumination angle, the holographic diffraction grating pattern including the spatially heterodyne hologram having spatially heterodyne fringes, wherein a difference between said illumination angle and said replay angle defines a diffraction angle .alpha. that is a function of a plane wave mathematically added to original object wave phase and amplitude data of said spatially heterodyne hologram having spatially heterodyne fringes.
Spatial patterns and climate drivers of carbon fluxes in terrestrial ecosystems of China.
Yu, Gui-Rui; Zhu, Xian-Jin; Fu, Yu-Ling; He, Hong-Lin; Wang, Qiu-Feng; Wen, Xue-Fa; Li, Xuan-Ran; Zhang, Lei-Ming; Zhang, Li; Su, Wen; Li, Sheng-Gong; Sun, Xiao-Min; Zhang, Yi-Ping; Zhang, Jun-Hui; Yan, Jun-Hua; Wang, Hui-Min; Zhou, Guang-Sheng; Jia, Bing-Rui; Xiang, Wen-Hua; Li, Ying-Nian; Zhao, Liang; Wang, Yan-Fen; Shi, Pei-Li; Chen, Shi-Ping; Xin, Xiao-Ping; Zhao, Feng-Hua; Wang, Yu-Ying; Tong, Cheng-Li
2013-03-01
Understanding the dynamics and underlying mechanism of carbon exchange between terrestrial ecosystems and the atmosphere is one of the key issues in global change research. In this study, we quantified the carbon fluxes in different terrestrial ecosystems in China, and analyzed their spatial variation and environmental drivers based on the long-term observation data of ChinaFLUX sites and the published data from other flux sites in China. The results indicate that gross ecosystem productivity (GEP), ecosystem respiration (ER), and net ecosystem productivity (NEP) of terrestrial ecosystems in China showed a significantly latitudinal pattern, declining linearly with the increase of latitude. However, GEP, ER, and NEP did not present a clear longitudinal pattern. The carbon sink functional areas of terrestrial ecosystems in China were mainly located in the subtropical and temperate forests, coastal wetlands in eastern China, the temperate meadow steppe in the northeast China, and the alpine meadow in eastern edge of Qinghai-Tibetan Plateau. The forest ecosystems had stronger carbon sink than grassland ecosystems. The spatial patterns of GEP and ER in China were mainly determined by mean annual precipitation (MAP) and mean annual temperature (MAT), whereas the spatial variation in NEP was largely explained by MAT. The combined effects of MAT and MAP explained 79%, 62%, and 66% of the spatial variations in GEP, ER, and NEP, respectively. The GEP, ER, and NEP in different ecosystems in China exhibited 'positive coupling correlation' in their spatial patterns. Both ER and NEP were significantly correlated with GEP, with 68% of the per-unit GEP contributed to ER and 29% to NEP. MAT and MAP affected the spatial patterns of ER and NEP mainly by their direct effects on the spatial pattern of GEP. © 2012 Blackwell Publishing Ltd.
Integrating the statistical analysis of spatial data in ecology
A. M. Liebhold; J. Gurevitch
2002-01-01
In many areas of ecology there is an increasing emphasis on spatial relationships. Often ecologists are interested in new ways of analyzing data with the objective of quantifying spatial patterns, and in designing surveys and experiments in light of the recognition that there may be underlying spatial pattern in biotic responses. In doing so, ecologists have adopted a...
H. H. Welsh; C. A. Wheeler; A. J. Lind
2010-01-01
Spatial patterns of animals have important implications for population dynamics and can reveal other key aspects of a species' ecology. Movements and the resulting spatial arrangements have fitness and genetic consequences for both individuals and populations. We studied the spatial and dispersal patterns of the Oregon Gartersnake, Thamnophis atratus...
Spatial scaling of non-native fish richness across the United States
Qinfeng Guo; Julian D. Olden
2014-01-01
A major goal and challenge of invasion ecology is to describe and interpret spatial and temporal patterns of species invasions. Here, we examined fish invasion patterns at four spatially structured and hierarchically nested scales across the contiguous United States (i.e., from large to small: region, basin, watershed, and sub-watershed). All spatial relationships in...
NASA Astrophysics Data System (ADS)
Golmohammadi, A.; Jafarpour, B.; M Khaninezhad, M. R.
2017-12-01
Calibration of heterogeneous subsurface flow models leads to ill-posed nonlinear inverse problems, where too many unknown parameters are estimated from limited response measurements. When the underlying parameters form complex (non-Gaussian) structured spatial connectivity patterns, classical variogram-based geostatistical techniques cannot describe the underlying connectivity patterns. Modern pattern-based geostatistical methods that incorporate higher-order spatial statistics are more suitable for describing such complex spatial patterns. Moreover, when the underlying unknown parameters are discrete (geologic facies distribution), conventional model calibration techniques that are designed for continuous parameters cannot be applied directly. In this paper, we introduce a novel pattern-based model calibration method to reconstruct discrete and spatially complex facies distributions from dynamic flow response data. To reproduce complex connectivity patterns during model calibration, we impose a feasibility constraint to ensure that the solution follows the expected higher-order spatial statistics. For model calibration, we adopt a regularized least-squares formulation, involving data mismatch, pattern connectivity, and feasibility constraint terms. Using an alternating directions optimization algorithm, the regularized objective function is divided into a continuous model calibration problem, followed by mapping the solution onto the feasible set. The feasibility constraint to honor the expected spatial statistics is implemented using a supervised machine learning algorithm. The two steps of the model calibration formulation are repeated until the convergence criterion is met. Several numerical examples are used to evaluate the performance of the developed method.
Bedford, D.R.; Small, E.E.
2008-01-01
Spatial patterns of soil properties are linked to patchy vegetation in arid and semi-arid landscapes. The patterns of soil properties are generally assumed to be linked to the ecohydrological functioning of patchy dryland vegetation ecosystems. We studied the effects of vegetation canopy, its spatial pattern, and landforms on soil properties affecting overland flow and infiltration in shrublands at the Sevilleta National Wildlife Refuge/LTER in central New Mexico, USA. We studied the patterns of microtopography and saturated conductivity (Ksat), and generally found it to be affected by vegetation canopy and pattern, as well as landform type. On gently sloping alluvial fans, both microtopography and Ksat are high under vegetation canopy and decay with distance from plant center. On steeper hillslope landforms, only microtopography was significantly higher under vegetation canopy, while there was no significant difference in Ksat between vegetation and interspaces. Using geostatistics, we found that the spatial pattern of soil properties was determined by the spatial pattern of vegetation. Most importantly, the effects of vegetation were present in the unvegetated interspaces 2-4 times the extent of vegetation canopy, on the order of 2-3??m. Our results have implications for the understanding the ecohydrologic function of semi-arid ecosystems as well as the parameterization of hydrologic models. ?? 2007 Elsevier B.V. All rights reserved.
Phenomapping of rangelands in South Africa using time series of RapidEye data
NASA Astrophysics Data System (ADS)
Parplies, André; Dubovyk, Olena; Tewes, Andreas; Mund, Jan-Peter; Schellberg, Jürgen
2016-12-01
Phenomapping is an approach which allows the derivation of spatial patterns of vegetation phenology and rangeland productivity based on time series of vegetation indices. In our study, we propose a new spatial mapping approach which combines phenometrics derived from high resolution (HR) satellite time series with spatial logistic regression modeling to discriminate land management systems in rangelands. From the RapidEye time series for selected rangelands in South Africa, we calculated bi-weekly noise reduced Normalized Difference Vegetation Index (NDVI) images. For the growing season of 20112012, we further derived principal phenology metrics such as start, end and length of growing season and related phenological variables such as amplitude, left derivative and small integral of the NDVI curve. We then mapped these phenometrics across two different tenure systems, communal and commercial, at the very detailed spatial resolution of 5 m. The result of a binary logistic regression (BLR) has shown that the amplitude and the left derivative of the NDVI curve were statistically significant. These indicators are useful to discriminate commercial from communal rangeland systems. We conclude that phenomapping combined with spatial modeling is a powerful tool that allows efficient aggregation of phenology and productivity metrics for spatially explicit analysis of the relationships of crop phenology with site conditions and management. This approach has particular potential for disaggregated and patchy environments such as in farming systems in semi-arid South Africa, where phenology varies considerably among and within years. Further, we see a strong perspective for phenomapping to support spatially explicit modelling of vegetation.
NASA Astrophysics Data System (ADS)
Erfanifard, Y.; Rezayan, F.
2014-10-01
Vegetation heterogeneity biases second-order summary statistics, e.g., Ripley's K-function, applied for spatial pattern analysis in ecology. Second-order investigation based on Ripley's K-function and related statistics (i.e., L- and pair correlation function g) is widely used in ecology to develop hypothesis on underlying processes by characterizing spatial patterns of vegetation. The aim of this study was to demonstrate effects of underlying heterogeneity of wild pistachio (Pistacia atlantica Desf.) trees on the second-order summary statistics of point pattern analysis in a part of Zagros woodlands, Iran. The spatial distribution of 431 wild pistachio trees was accurately mapped in a 40 ha stand in the Wild Pistachio & Almond Research Site, Fars province, Iran. Three commonly used second-order summary statistics (i.e., K-, L-, and g-functions) were applied to analyse their spatial pattern. The two-sample Kolmogorov-Smirnov goodness-of-fit test showed that the observed pattern significantly followed an inhomogeneous Poisson process null model in the study region. The results also showed that heterogeneous pattern of wild pistachio trees biased the homogeneous form of K-, L-, and g-functions, demonstrating a stronger aggregation of the trees at the scales of 0-50 m than actually existed and an aggregation at scales of 150-200 m, while regularly distributed. Consequently, we showed that heterogeneity of point patterns may bias the results of homogeneous second-order summary statistics and we also suggested applying inhomogeneous summary statistics with related null models for spatial pattern analysis of heterogeneous vegetations.
NASA Astrophysics Data System (ADS)
Iisaka, Joji; Sakurai-Amano, Takako
1994-08-01
This paper describes an integrated approach to terrain feature detection and several methods to estimate spatial information from SAR (synthetic aperture radar) imagery. Spatial information of image features as well as spatial association are key elements in terrain feature detection. After applying a small feature preserving despeckling operation, spatial information such as edginess, texture (smoothness), region-likeliness and line-likeness of objects, target sizes, and target shapes were estimated. Then a trapezoid shape fuzzy membership function was assigned to each spatial feature attribute. Fuzzy classification logic was employed to detect terrain features. Terrain features such as urban areas, mountain ridges, lakes and other water bodies as well as vegetated areas were successfully identified from a sub-image of a JERS-1 SAR image. In the course of shape analysis, a quantitative method was developed to classify spatial patterns by expanding a spatial pattern through the use of a series of pattern primitives.
Spatial Organization In Europe of Decadal and Interdecadal Fluctuations In Annual Rainfall
NASA Astrophysics Data System (ADS)
Lucero, O. A.; Rodriguez, N. C.
In this research the spatial patterns of decadal and bidecadal fluctuations in annual rainfall in Europe are identified. Filtering of time series of anomaly of annual rainfall is carried out using the Morlet wavelet technique. Reconstruction is achieved by sum- ming the contributions from bands of wavelet timescales; the decadal band and the bidecadal band are composed of contributions from the band of (10- to 17-year] and (17- to 27- year] timescales respectively. Results indicate that 1) the spatial organi- zation of decadal and bidecadal components of annual rainfall are standing wave-like organized patterns. Three standing decadal fluctuations zonally aligned formed the spatial pattern from 1900 until 1931; thereafter the pattern changed into a NW-SE orientation. The decadal band shows an average 12-year period. 2) The spatial orga- nization of bidecadal component was composed of three standing fluctuations since 1903 to 1986. After 1987 two standing bidecadal fluctuations were located on Europe. The orientation of bidecadal fluctuations changed during the period under study. Until 1913 the spatial pattern of the bidecadal component was zonally aligned. Since 1913 until 1986 the three bidecadal fluctuations composing the spatial pattern were aligned SW U NE; starting 1987 the spatial pattern is composed of two standing fluctuations zonally aligned. The bidecadal spatial pattern shows an average period of 20- to 22- year length. 3) At decadal and bidecadal timescales, the first principal component of the spatial field of anomaly of annual rainfall and the NAO index are connected. The upper positive third (lower negative third) of values of first principal component are indicative of extensive area with positive (negative) anomaly of annual rainfall. 4) At decadal timescale the relative phase between the first PC and the NAO index changes through the period under study; these changes define three regimes: 1) Dur- ing the regime covering the period 1900 (start of period under study) to about 1945, at the time of peak values of decadal NAO-index it takes place a transition between extremes (a neutral state) of the decadal rainfall spatial pattern (first PC takes small absolute values). Besides, for positive (negative) peak value of NAO index the spatial pattern of annual rainfall is evolving toward an area of predominantly positive (nega- tive) anomaly. 2) The second regime starts about 1946 and reaches up to early 1980s. At the time of negative (positive) peak of decadal NAO there is a prevailing spatial pattern of positive (negative) anomaly of decadal rainfall. 3) The third regime starts 1 about late 1970s and reaches to the end of the period under study (in 1996). There is a change of relative phase within this period in late 1980s. In this regime a spatial pattern of prevailing positive or negative anomaly of decadal rainfall takes place dur- ing values of decadal NAO close to zero. 5) At bidecadal timescale the relative phase between the first PC and the NAO index remains almost constant through the period under study. The first PC of the transformed bidecadal component of annual rainfall anomaly attains its positive (negative) peak about three years before the bidecadal component of NAO reaches its negative (positive) peak. 2
NASA Astrophysics Data System (ADS)
Saavedra, Francisco; Hensen, Isabell; Apaza Quevedo, Amira; Neuschulz, Eike Lena; Schleuning, Matthias
2017-11-01
Spatial patterns of seed dispersal and recruitment of fleshy-fruited plants in tropical forests are supposed to be driven by the activity of animal seed dispersers, but the spatial patterns of seed dispersal, seedlings and saplings have rarely been analyzed simultaneously. We studied seed deposition and recruitment patterns of three Clusia species in a tropical montane forest of the Bolivian Andes and tested whether these patterns changed between habitat types (forest edge vs. forest interior), distance to the fruiting tree and consecutive recruitment stages of the seedlings. We recorded the number of seeds deposited in seed traps to assess the local seed-deposition pattern and the abundance and distribution of seedlings and saplings to evaluate the spatial pattern of recruitment. More seeds were removed and deposited at the forest edge than in the interior. The number of deposited seeds decreased with distance from the fruiting tree and was spatially clustered in both habitat types. The density of 1-yr-old seedlings and saplings was higher at forest edges, whereas the density of 2-yr-old seedlings was similar in both habitat types. While seedlings were almost randomly distributed, seeds and saplings were spatially clustered in both habitat types. Our findings demonstrate systematic changes in spatial patterns of recruits across the plant regeneration cycle and suggest that the differential effects of biotic and abiotic factors determine plant recruitment at the edges and in the interior of tropical montane forests. These differences in the spatial distribution of individuals across recruitment stages may have strong effects on plant community dynamics and influence plant species coexistence in disturbed tropical forests.
Spatial patterns in vegetation fires in the Indian region.
Vadrevu, Krishna Prasad; Badarinath, K V S; Anuradha, Eaturu
2008-12-01
In this study, we used fire count datasets derived from Along Track Scanning Radiometer (ATSR) satellite to characterize spatial patterns in fire occurrences across highly diverse geographical, vegetation and topographic gradients in the Indian region. For characterizing the spatial patterns of fire occurrences, observed fire point patterns were tested against the hypothesis of a complete spatial random (CSR) pattern using three different techniques, the quadrat analysis, nearest neighbor analysis and Ripley's K function. Hierarchical nearest neighboring technique was used to depict the 'hotspots' of fire incidents. Of the different states, highest fire counts were recorded in Madhya Pradesh (14.77%) followed by Gujarat (10.86%), Maharastra (9.92%), Mizoram (7.66%), Jharkhand (6.41%), etc. With respect to the vegetation categories, highest number of fires were recorded in agricultural regions (40.26%) followed by tropical moist deciduous vegetation (12.72), dry deciduous vegetation (11.40%), abandoned slash and burn secondary forests (9.04%), tropical montane forests (8.07%) followed by others. Analysis of fire counts based on elevation and slope range suggested that maximum number of fires occurred in low and medium elevation types and in very low to low-slope categories. Results from three different spatial techniques for spatial pattern suggested clustered pattern in fire events compared to CSR. Most importantly, results from Ripley's K statistic suggested that fire events are highly clustered at a lag-distance of 125 miles. Hierarchical nearest neighboring clustering technique identified significant clusters of fire 'hotspots' in different states in northeast and central India. The implications of these results in fire management and mitigation were discussed. Also, this study highlights the potential of spatial point pattern statistics in environmental monitoring and assessment studies with special reference to fire events in the Indian region.
Predictor variable resolution governs modeled soil types
USDA-ARS?s Scientific Manuscript database
Soil mapping identifies different soil types by compressing a unique suite of spatial patterns and processes across multiple spatial scales. It can be quite difficult to quantify spatial patterns of soil properties with remotely sensed predictor variables. More specifically, matching the right scale...
A search for model parsimony in a real time flood forecasting system
NASA Astrophysics Data System (ADS)
Grossi, G.; Balistrocchi, M.
2009-04-01
As regards the hydrological simulation of flood events, a physically based distributed approach is the most appealing one, especially in those areas where the spatial variability of the soil hydraulic properties as well as of the meteorological forcing cannot be left apart, such as in mountainous regions. On the other hand, dealing with real time flood forecasting systems, less detailed models requiring a minor number of parameters may be more convenient, reducing both the computational costs and the calibration uncertainty. In fact in this case a precise quantification of the entire hydrograph pattern is not necessary, while the expected output of a real time flood forecasting system is just an estimate of the peak discharge, the time to peak and in some cases the flood volume. In this perspective a parsimonious model has to be found in order to increase the efficiency of the system. A suitable case study was identified in the northern Apennines: the Taro river is a right tributary to the Po river and drains about 2000 km2 of mountains, hills and floodplain, equally distributed . The hydrometeorological monitoring of this medium sized watershed is managed by ARPA Emilia Romagna through a dense network of uptodate gauges (about 30 rain gauges and 10 hydrometers). Detailed maps of the surface elevation, land use and soil texture characteristics are also available. Five flood events were recorded by the new monitoring network in the years 2003-2007: during these events the peak discharge was higher than 1000 m3/s, which is actually quite a high value when compared to the mean discharge rate of about 30 m3/s. The rainfall spatial patterns of such storms were analyzed in previous works by means of geostatistical tools and a typical semivariogram was defined, with the aim of establishing a typical storm structure leading to flood events in the Taro river. The available information was implemented into a distributed flood event model with a spatial resolution of 90m; then the hydrologic detail was reduced by progressively assuming a uniform rainfall field and constant soil properties. A semi-distributed model, obtained by subdividing the catchment into three sub-catchment, and a lumped model were also applied to simulate the selected flood events. Errors were quantified in terms of the peak discharge ratio, the flood volume and the time to peak by comparing the simulated hydrographs to the observed ones.
Jamie M. Lydersen; Malcolm P. North; Eric E. Knapp; Brandon M. Collins
2013-01-01
Fire suppression and past logging have dramatically altered forest conditions in many areas, but changes to within-stand tree spatial patterns over time are not as well understood. The few studies available suggest that variability in tree spatial patterns is an important structural feature of forests with intact frequent fire regimes that should be incorporated in...
Magnetic Excitations of Stripes
NASA Astrophysics Data System (ADS)
Yao, Daoxin; Carlson, Erica; Campbell, David
2005-03-01
Competing tendencies in electronic systems with strong correlations can lead to spontaneous nanoscale structure, pattern formation, and even long-range spatial order. There has been continued interest in various ``stripe'' phases of electrons, as well as more recent interest in possible ``checkerboard'' patterns. New experimental techniques allow for the extraction of detailed and reproducible neutron scattering spectra in copper oxide superconductors and related nickelate compounds. We discuss the magnetic excitations of well-ordered stripe phases, including the high energy magnetic excitations of recent interest and possible connections to the ``resonance peak'' in cuprate superconductors. Using a suitably parametrized Heisenberg model and spin wave theory, we study a variety of possible stripe configurations, including vertical, diagonal, staircase, and zigzag stripes. We calculate the expected neutron scattering intensities as a function of energy and momentum. Constant energy cuts at high energy often reveal a square-like scattering pattern, and occasionally a circular pattern. Bond-centered stripes have weight gathered near (pi,pi) at low energy, indicating that only part of the spin wave cone is expected to be resolvable experimentally. In addition, we present a litmus test for experimentally distinguishing bond-centered stripes from site-centered stripes using low energy data.
Recurrence Methods for the Identification of Morphogenetic Patterns
Facchini, Angelo; Mocenni, Chiara
2013-01-01
This paper addresses the problem of identifying the parameters involved in the formation of spatial patterns in nonlinear two dimensional systems. To this aim, we perform numerical experiments on a prototypical model generating morphogenetic Turing patterns, by changing both the spatial frequency and shape of the patterns. The features of the patterns and their relationship with the model parameters are characterized by means of the Generalized Recurrence Quantification measures. We show that the recurrence measures Determinism and Recurrence Entropy, as well as the distribution of the line lengths, allow for a full characterization of the patterns in terms of power law decay with respect to the parameters involved in the determination of their spatial frequency and shape. A comparison with the standard two dimensional Fourier transform is performed and the results show a better performance of the recurrence indicators in identifying a reliable connection with the spatial frequency of the patterns. Finally, in order to evaluate the robustness of the estimation of the power low decay, extensive simulations have been performed by adding different levels of noise to the patterns. PMID:24066062
[Spatial analysis of mortality from cardiovascular diseases in Madrid City, Spain].
Gómez-Barroso, Diana; Prieto-Flores, María-Eugenia; Mellado San Gabino, Ana; Moreno Jiménez, Antonio
2015-01-01
Cardiovascular disease is the leading cause of death worldwide, but its spatial distribution is not homogeneous. The objective of this study is to analyze the spatial pattern of mortality from these diseases for men and women, in the populated urban area (AUP) of the municipality of Madrid, and to identify spatial aggregations. An ecological study was carried out by census tract, for men and women in 2010. Standardized Mortality Ratio (SMR), Relative Risk Smoothing (RRS) and Posterior Probability (PP) were calculated to consider the spatial pattern of the disease. To identify spatial clusters the Moran index (Moran I) and the Local Index of Spatial Autocorrelation (LISA) were used. The results were mapped. SMR higher than 1.1 was observed mainly in central areas among men and in peripheral areas among women. The PP that RRS was higher than 1 surpassed 0.8 in the center and in the periphery, in both men and women. Moran's I was 0.04 for men and 0.03 for women (p <0.05 in both cases). Sex differences were observed in the spatial distribution of mortality cases. RME RRS and PP maps showed a heterogeneous pattern in men, whereas in women a clearer pattern was detected, with a relatively higher risk in peripheral areas of the AUP. The LISA method showed similar patterns to those previously observed.
NASA Astrophysics Data System (ADS)
Korres, W.; Reichenau, T. G.; Schneider, K.
2013-08-01
Soil moisture is a key variable in hydrology, meteorology and agriculture. Soil moisture, and surface soil moisture in particular, is highly variable in space and time. Its spatial and temporal patterns in agricultural landscapes are affected by multiple natural (precipitation, soil, topography, etc.) and agro-economic (soil management, fertilization, etc.) factors, making it difficult to identify unequivocal cause and effect relationships between soil moisture and its driving variables. The goal of this study is to characterize and analyze the spatial and temporal patterns of surface soil moisture (top 20 cm) in an intensively used agricultural landscape (1100 km2 northern part of the Rur catchment, Western Germany) and to determine the dominant factors and underlying processes controlling these patterns. A second goal is to analyze the scaling behavior of surface soil moisture patterns in order to investigate how spatial scale affects spatial patterns. To achieve these goals, a dynamically coupled, process-based and spatially distributed ecohydrological model was used to analyze the key processes as well as their interactions and feedbacks. The model was validated for two growing seasons for the three main crops in the investigation area: Winter wheat, sugar beet, and maize. This yielded RMSE values for surface soil moisture between 1.8 and 7.8 vol.% and average RMSE values for all three crops of 0.27 kg m-2 for total aboveground biomass and 0.93 for green LAI. Large deviations of measured and modeled soil moisture can be explained by a change of the infiltration properties towards the end of the growing season, especially in maize fields. The validated model was used to generate daily surface soil moisture maps, serving as a basis for an autocorrelation analysis of spatial patterns and scale. Outside of the growing season, surface soil moisture patterns at all spatial scales depend mainly upon soil properties. Within the main growing season, larger scale patterns that are induced by soil properties are superimposed by the small scale land use pattern and the resulting small scale variability of evapotranspiration. However, this influence decreases at larger spatial scales. Most precipitation events cause temporarily higher surface soil moisture autocorrelation lengths at all spatial scales for a short time even beyond the autocorrelation lengths induced by soil properties. The relation of daily spatial variance to the spatial scale of the analysis fits a power law scaling function, with negative values of the scaling exponent, indicating a decrease in spatial variability with increasing spatial resolution. High evapotranspiration rates cause an increase in the small scale soil moisture variability, thus leading to large negative values of the scaling exponent. Utilizing a multiple regression analysis, we found that 53% of the variance of the scaling exponent can be explained by a combination of an independent LAI parameter and the antecedent precipitation.
Maestre, F.T.; Castillo-Monroy, A. P.; Bowker, M.A.; Ochoa-Hueso, R.
2012-01-01
1. Recent studies have suggested that the simultaneous maintenance of multiple ecosystem functions (multifunctionality) is positively supported by species richness. However, little is known regarding the relative importance of other community attributes (e.g. spatial pattern, species evenness) as drivers of multifunctionality. 2. We conducted two microcosm experiments using model biological soil crust communities dominated by lichens to: (i) evaluate the joint effects and relative importance of changes in species composition, spatial pattern (clumped and random distribution of lichens), evenness (maximal and low evenness) and richness (from two to eight species) on soil functions related to nutrient cycling (β-glucosidase, urease and acid phosphatase enzymes, in situ N availability, total N, organic C, and N fixation), and (ii) assess how these community attributes affect multifunctionality. 3. Species richness, composition and spatial pattern affected multiple ecosystem functions (e.g. organic C, total N, N availability, β-glucosidase activity), albeit the magnitude and direction of their effects varied with the particular function, experiment and soil depth considered. Changes in species composition had effects on organic C, total N and the activity of β-glucosidase. Significant species richness × evenness and spatial pattern × evenness interactions were found when analysing functions such as organic C, total N and the activity of phosphatase. 4. The probability of sustaining multiple ecosystem functions increased with species richness, but this effect was largely modulated by attributes such as species evenness, composition and spatial pattern. Overall, we found that model communities with high species richness, random spatial pattern and low evenness increased multifunctionality. 5. Synthesis. Our results illustrate how different community attributes have a diverse impact on ecosystem functions related to nutrient cycling, and provide new experimental evidence illustrating the importance of the spatial pattern of organisms on ecosystem functioning. They also indicate that species richness is not the only biotic driver of multifunctionality, and that particular combinations of community attributes may be required to maximize it.
Self-organizing human cardiac microchambers mediated by geometric confinement
NASA Astrophysics Data System (ADS)
Ma, Zhen; Wang, Jason; Loskill, Peter; Huebsch, Nathaniel; Koo, Sangmo; Svedlund, Felicia L.; Marks, Natalie C.; Hua, Ethan W.; Grigoropoulos, Costas P.; Conklin, Bruce R.; Healy, Kevin E.
2015-07-01
Tissue morphogenesis and organ formation are the consequences of biochemical and biophysical cues that lead to cellular spatial patterning in development. To model such events in vitro, we use PEG-patterned substrates to geometrically confine human pluripotent stem cell colonies and spatially present mechanical stress. Modulation of the WNT/β-catenin pathway promotes spatial patterning via geometric confinement of the cell condensation process during epithelial-mesenchymal transition, forcing cells at the perimeter to express an OCT4+ annulus, which is coincident with a region of higher cell density and E-cadherin expression. The biochemical and biophysical cues synergistically induce self-organizing lineage specification and creation of a beating human cardiac microchamber confined by the pattern geometry. These highly defined human cardiac microchambers can be used to study aspects of embryonic spatial patterning, early cardiac development and drug-induced developmental toxicity.
Tempo-spatial analysis of Fennoscandian intraplate seismicity
NASA Astrophysics Data System (ADS)
Roberts, Roland; Lund, Björn
2017-04-01
Coupled spatial-temporal patterns of the occurrence of earthquakes in Fennoscandia are analysed using non-parametric methods. The occurrence of larger events is unambiguously and very strongly temporally clustered, with major implications for the assessment of seismic hazard in areas such as Fennoscandia. In addition, there is a clear pattern of geographical migration of activity. Data from the Swedish National Seismic Network and a collated international catalogue are analysed. Results show consistent patterns on different spatial and temporal scales. We are currently investigating these patterns in order to assess the statistical significance of the tempo-spatial patterns, and to what extent these may be consistent with stress transfer mechanism such as coulomb stress and pore fluid migration. Indications are that some further mechanism is necessary in order to explain the data, perhaps related to post-glacial uplift, which is up to 1cm/year.
Attempting to physically explain space-time correlation of extremes
NASA Astrophysics Data System (ADS)
Bernardara, Pietro; Gailhard, Joel
2010-05-01
Spatial and temporal clustering of hydro-meteorological extreme events is scientific evidence. Moreover, the statistical parameters characterizing their local frequencies of occurrence show clear spatial patterns. Thus, in order to robustly assess the hydro-meteorological hazard, statistical models need to be able to take into account spatial and temporal dependencies. Statistical models considering long term correlation for quantifying and qualifying temporal and spatial dependencies are available, such as multifractal approach. Furthermore, the development of regional frequency analysis techniques allows estimating the frequency of occurrence of extreme events taking into account spatial patterns on the extreme quantiles behaviour. However, in order to understand the origin of spatio-temporal clustering, an attempt to find physical explanation should be done. Here, some statistical evidences of spatio-temporal correlation and spatial patterns of extreme behaviour are given on a large database of more than 400 rainfall and discharge series in France. In particular, the spatial distribution of multifractal and Generalized Pareto distribution parameters shows evident correlation patterns in the behaviour of frequency of occurrence of extremes. It is then shown that the identification of atmospheric circulation pattern (weather types) can physically explain the temporal clustering of extreme rainfall events (seasonality) and the spatial pattern of the frequency of occurrence. Moreover, coupling this information with the hydrological modelization of a watershed (as in the Schadex approach) an explanation of spatio-temporal distribution of extreme discharge can also be provided. We finally show that a hydro-meteorological approach (as the Schadex approach) can explain and take into account space and time dependencies of hydro-meteorological extreme events.
J. Rojas-Sandoval; E. J. Melendez-Ackerman; NO-VALUE
2013-01-01
Aims The spatial distribution of biotic and abiotic factors may play a dominant role in determining the distribution and abundance of plants in arid and semiarid environments. In this study, we evaluated how spatial patterns of microhabitat variables and the degree of spatial dependence of these variables influence the distribution and abundance of the endangered...
Peña, Daniel; Contreras, María José; Shih, Pei Chun; Santacreu, José
2008-05-01
When individuals perform spatial tasks, individual differences emerge in accuracy and speed as well as in the response patterns used to cope with the task. The purpose of this study is to identify, through empirical criteria, the different response patterns or strategies used by individuals when performing the dynamic spatial task presented in the Spatial Orientation Dynamic Test-Revised (SODT-R). Results show that participants can be classified according to their response patterns. Three different ways of solving a task are described, and their relation to (a) performance factors (response latency, response frequency, and invested time) and (b) ability tests (analytical reasoning, verbal reasoning, and spatial estimation) are investigated. Sex differences in response patterns and performance are also analyzed. It is found that the frequency with which men and women employ each one of the strategies described here, is different and statistically significant. Thus, employed strategy plays an important role when interpreting sex differences on dynamic spatial tasks.
Pixelated camouflage patterns from the perspective of hyperspectral imaging
NASA Astrophysics Data System (ADS)
Racek, František; Jobánek, Adam; Baláž, Teodor; Krejčí, Jaroslav
2016-10-01
Pixelated camouflage patterns fulfill the role of both principles the matching and the disrupting that are exploited for blending the target into the background. It means that pixelated pattern should respect natural background in spectral and spatial characteristics embodied in micro and macro patterns. The HS imaging plays the similar, however the reverse role in the field of reconnaissance systems. The HS camera fundamentally records and extracts both the spectral and spatial information belonging to the recorded scenery. Therefore, the article deals with problems of hyperspectral (HS) imaging and subsequent processing of HS images of pixelated camouflage patterns which are among others characterized by their specific spatial frequency heterogeneity.
Patterns and Potential Drivers of Dramatic Changes in Tibetan Lakes, 1972–2010
Li, Yingkui; Liao, Jingjuan; Guo, Huadong; Liu, Zewen; Shen, Guozhuang
2014-01-01
Most glaciers in the Himalayas and the Tibetan Plateau are retreating, and glacier melt has been emphasized as the dominant driver for recent lake expansions on the Tibetan Plateau. By investigating detailed changes in lake extents and levels across the Tibetan Plateau from Landsat/ICESat data, we found a pattern of dramatic lake changes from 1970 to 2010 (especially after 2000) with a southwest-northeast transition from shrinking, to stable, to rapidly expanding. This pattern is in distinct contrast to the spatial characteristics of glacier retreat, suggesting limited influence of glacier melt on lake dynamics. The plateau-wide pattern of lake change is related to precipitation variation and consistent with the pattern of permafrost degradation induced by rising temperature. More than 79% of lakes we observed on the central-northern plateau (with continuous permafrost) are rapidly expanding, even without glacial contributions, while lakes fed by retreating glaciers in southern regions (with isolated permafrost) are relatively stable or shrinking. Our study shows the limited role of glacier melt and highlights the potentially important contribution of permafrost degradation in predicting future water availability in this region, where understanding these processes is of critical importance to drinking water, agriculture, and hydropower supply of densely populated areas in South and East Asia. PMID:25372787
Patterns and potential drivers of dramatic changes in Tibetan lakes, 1972-2010.
Li, Yingkui; Liao, Jingjuan; Guo, Huadong; Liu, Zewen; Shen, Guozhuang
2014-01-01
Most glaciers in the Himalayas and the Tibetan Plateau are retreating, and glacier melt has been emphasized as the dominant driver for recent lake expansions on the Tibetan Plateau. By investigating detailed changes in lake extents and levels across the Tibetan Plateau from Landsat/ICESat data, we found a pattern of dramatic lake changes from 1970 to 2010 (especially after 2000) with a southwest-northeast transition from shrinking, to stable, to rapidly expanding. This pattern is in distinct contrast to the spatial characteristics of glacier retreat, suggesting limited influence of glacier melt on lake dynamics. The plateau-wide pattern of lake change is related to precipitation variation and consistent with the pattern of permafrost degradation induced by rising temperature. More than 79% of lakes we observed on the central-northern plateau (with continuous permafrost) are rapidly expanding, even without glacial contributions, while lakes fed by retreating glaciers in southern regions (with isolated permafrost) are relatively stable or shrinking. Our study shows the limited role of glacier melt and highlights the potentially important contribution of permafrost degradation in predicting future water availability in this region, where understanding these processes is of critical importance to drinking water, agriculture, and hydropower supply of densely populated areas in South and East Asia.
Seismotectonics of the 2014 Chiang Rai, Thailand, earthquake sequence
NASA Astrophysics Data System (ADS)
Pananont, P.; Herman, M. W.; Pornsopin, P.; Furlong, K. P.; Habangkaem, S.; Waldhauser, F.; Wongwai, W.; Limpisawad, S.; Warnitchai, P.; Kosuwan, S.; Wechbunthung, B.
2017-08-01
On 5 May 2014, a
Cooperation in Harsh Environments and the Emergence of Spatial Patterns.
Smaldino, Paul E
2013-11-01
This paper concerns the confluence of two important areas of research in mathematical biology: spatial pattern formation and cooperative dilemmas. Mechanisms through which social organisms form spatial patterns are not fully understood. Prior work connecting cooperation and pattern formation has often included unrealistic assumptions that shed doubt on the applicability of those models toward understanding real biological patterns. I investigated a more biologically realistic model of cooperation among social actors. The environment is harsh, so that interactions with cooperators are strictly needed to survive. Harshness is implemented via a constant energy deduction. I show that this model can generate spatial patterns similar to those seen in many naturally-occuring systems. Moreover, for each payoff matrix there is an associated critical value of the energy deduction that separates two distinct dynamical processes. In low-harshness environments, the growth of cooperator clusters is impeded by defectors, but these clusters gradually expand to form dense dendritic patterns. In very harsh environments, cooperators expand rapidly but defectors can subsequently make inroads to form reticulated patterns. The resulting web-like patterns are reminiscent of transportation networks observed in slime mold colonies and other biological systems.
Structural graph-based morphometry: A multiscale searchlight framework based on sulcal pits.
Takerkart, Sylvain; Auzias, Guillaume; Brun, Lucile; Coulon, Olivier
2017-01-01
Studying the topography of the cortex has proved valuable in order to characterize populations of subjects. In particular, the recent interest towards the deepest parts of the cortical sulci - the so-called sulcal pits - has opened new avenues in that regard. In this paper, we introduce the first fully automatic brain morphometry method based on the study of the spatial organization of sulcal pits - Structural Graph-Based Morphometry (SGBM). Our framework uses attributed graphs to model local patterns of sulcal pits, and further relies on three original contributions. First, a graph kernel is defined to provide a new similarity measure between pit-graphs, with few parameters that can be efficiently estimated from the data. Secondly, we present the first searchlight scheme dedicated to brain morphometry, yielding dense information maps covering the full cortical surface. Finally, a multi-scale inference strategy is designed to jointly analyze the searchlight information maps obtained at different spatial scales. We demonstrate the effectiveness of our framework by studying gender differences and cortical asymmetries: we show that SGBM can both localize informative regions and estimate their spatial scales, while providing results which are consistent with the literature. Thanks to the modular design of our kernel and the vast array of available kernel methods, SGBM can easily be extended to include a more detailed description of the sulcal patterns and solve different statistical problems. Therefore, we suggest that our SGBM framework should be useful for both reaching a better understanding of the normal brain and defining imaging biomarkers in clinical settings. Copyright © 2016 Elsevier B.V. All rights reserved.
Spatially explicit shallow landslide susceptibility mapping over large areas
Bellugi, Dino; Dietrich, William E.; Stock, Jonathan D.; McKean, Jim; Kazian, Brian; Hargrove, Paul
2011-01-01
Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so it has generated downscaled precipitation maps for the storm. To predict the corresponding pattern of shallow landslide susceptibility across the state, we have used the model Shalstab (a coupled steady state runoff and infinite slope stability model) which susceptibility spatially explicit estimates of relative potential instability. Such slope stability models that include the effects of subsurface runoff on potentially destabilizing pore pressure evolution require water routing and hence the definition of upslope drainage area to each potential cell. To calculate drainage area efficiently over a large area we developed a parallel framework to scale-up Shalstab and specifically introduce a new efficient parallel drainage area algorithm which produces seamless results. The single seamless shallow landslide susceptibility map for all of California was accomplished in a short run time, and indicates that much larger areas can be efficiently modelled. As landslide maps generally over predict the extent of instability for any given storm. Local empirical data on the fraction of predicted unstable cells that failed for observed rainfall intensity can be used to specify the likely extent of hazard for a given storm. This suggests that campaigns to collect local precipitation data and detailed shallow landslide location maps after major storms could be used to calibrate models and improve their use in hazard assessment for individual storms.
Inverse methods for estimating primary input signals from time-averaged isotope profiles
NASA Astrophysics Data System (ADS)
Passey, Benjamin H.; Cerling, Thure E.; Schuster, Gerard T.; Robinson, Todd F.; Roeder, Beverly L.; Krueger, Stephen K.
2005-08-01
Mammalian teeth are invaluable archives of ancient seasonality because they record along their growth axes an isotopic record of temporal change in environment, plant diet, and animal behavior. A major problem with the intra-tooth method is that intra-tooth isotope profiles can be extremely time-averaged compared to the actual pattern of isotopic variation experienced by the animal during tooth formation. This time-averaging is a result of the temporal and spatial characteristics of amelogenesis (tooth enamel formation), and also results from laboratory sampling. This paper develops and evaluates an inverse method for reconstructing original input signals from time-averaged intra-tooth isotope profiles. The method requires that the temporal and spatial patterns of amelogenesis are known for the specific tooth and uses a minimum length solution of the linear system Am = d, where d is the measured isotopic profile, A is a matrix describing temporal and spatial averaging during amelogenesis and sampling, and m is the input vector that is sought. Accuracy is dependent on several factors, including the total measurement error and the isotopic structure of the measured profile. The method is shown to accurately reconstruct known input signals for synthetic tooth enamel profiles and the known input signal for a rabbit that underwent controlled dietary changes. Application to carbon isotope profiles of modern hippopotamus canines reveals detailed dietary histories that are not apparent from the measured data alone. Inverse methods show promise as an effective means of dealing with the time-averaging problem in studies of intra-tooth isotopic variation.
Bischel, Alexander; Stratis, Andreas; Bosmans, Hilde; Jacobs, Reinhilde; Gassner, Eva-Maria; Puelacher, Wolfgang; Pauwels, Ruben
2017-01-01
Objectives: The objective of this study was to determine how iterative reconstruction technology (IRT) influences contrast and spatial resolution in ultralow-dose dentomaxillofacial CT imaging. Methods: A polymethyl methacrylate phantom with various inserts was scanned using a reference protocol (RP) at CT dose index volume 36.56 mGy, a sinus protocol at 18.28 mGy and ultralow-dose protocols (LD) at 4.17 mGy, 2.36 mGy, 0.99 mGy and 0.53 mGy. All data sets were reconstructed using filtered back projection (FBP) and the following IRTs: adaptive statistical iterative reconstructions (ASIRs) (ASIR-50, ASIR-100) and model-based iterative reconstruction (MBIR). Inserts containing line-pair patterns and contrast detail patterns for three different materials were scored by three observers. Observer agreement was analyzed using Cohen's kappa and difference in performance between the protocols and reconstruction was analyzed with Dunn's test at α = 0.05. Results: Interobserver agreement was acceptable with a mean kappa value of 0.59. Compared with the RP using FBP, similar scores were achieved at 2.36 mGy using MBIR. MIBR reconstructions showed the highest noise suppression as well as good contrast even at the lowest doses. Overall, ASIR reconstructions did not outperform FBP. Conclusions: LD and MBIR at a dose reduction of >90% may show no significant differences in spatial and contrast resolution compared with an RP and FBP. Ultralow-dose CT and IRT should be further explored in clinical studies. PMID:28059562
Climate change and fishing: a century of shifting distribution in North Sea cod.
Engelhard, Georg H; Righton, David A; Pinnegar, John K
2014-08-01
Globally, spatial distributions of fish stocks are shifting but although the role of climate change in range shifts is increasingly appreciated, little remains known of the likely additional impact that high levels of fishing pressure might have on distribution. For North Sea cod, we show for the first time and in great spatial detail how the stock has shifted its distribution over the past 100 years. We digitized extensive historical fisheries data from paper charts in UK government archives and combined these with contemporary data to a time-series spanning 1913-2012 (excluding both World Wars). New analysis of old data revealed that the current distribution pattern of cod - mostly in the deeper, northern- and north-easternmost parts of the North Sea - is almost opposite to that during most of the Twentieth Century - mainly concentrated in the west, off England and Scotland. Statistical analysis revealed that the deepening, northward shift is likely attributable to warming; however, the eastward shift is best explained by fishing pressure, suggestive of significant depletion of the stock from its previous stronghold, off the coasts of England and Scotland. These spatial patterns were confirmed for the most recent 3 1/2 decades by data from fisheries-independent surveys, which go back to the 1970s. Our results demonstrate the fundamental importance of both climate change and fishing pressure for our understanding of changing distributions of commercially exploited fish. © 2013 Crown copyright. Global Change Biology published by John Wiley & Sons Ltd. This article is published with the permission of the Controller of HMSO and the Queen's Printer for Scotland.
García, José R.; Singh, Ankur; García, Andrés J.
2016-01-01
In the pursuit to develop enhanced technologies for cellular bioassays as well as understand single cell interactions with its underlying substrate, the field of biotechnology has extensively utilized lithographic techniques to spatially pattern proteins onto surfaces in user-defined geometries. Microcontact printing (μCP) remains an incredibly useful patterning method due to its inexpensive nature, scalability, and the lack of considerable use of specialized clean room equipment. However, as new technologies emerge that necessitate various nano-sized areas of deposited proteins, traditional microcontact printing methods may not be able to supply users with the needed resolution size. Recently, our group developed a modified “subtractive microcontact printing” method which still retains many of the benefits offered by conventional μCP. Using this technique, we have been able to reach resolution sizes of fibronectin as small as 250 nm in largely spaced arrays for cell culture. In this communication, we present a detailed description of our subtractive μCP procedure that expands on many of the little tips and tricks that together make this procedure an easy and effective method for controlling protein patterning. PMID:24439290
Behavioural and physiological mechanisms of polarized light sensitivity in birds.
Muheim, Rachel
2011-03-12
Polarized light (PL) sensitivity is relatively well studied in a large number of invertebrates and some fish species, but in most other vertebrate classes, including birds, the behavioural and physiological mechanism of PL sensitivity remains one of the big mysteries in sensory biology. Many organisms use the skylight polarization pattern as part of a sun compass for orientation, navigation and in spatial orientation tasks. In birds, the available evidence for an involvement of the skylight polarization pattern in sun-compass orientation is very weak. Instead, cue-conflict and cue-calibration experiments have shown that the skylight polarization pattern near the horizon at sunrise and sunset provides birds with a seasonally and latitudinally independent compass calibration reference. Despite convincing evidence that birds use PL cues for orientation, direct experimental evidence for PL sensitivity is still lacking. Avian double cones have been proposed as putative PL receptors, but detailed anatomical and physiological evidence will be needed to conclusively describe the avian PL receptor. Intriguing parallels between the functional and physiological properties of PL reception and light-dependent magnetoreception could point to a common receptor system.
Behavioural and physiological mechanisms of polarized light sensitivity in birds
Muheim, Rachel
2011-01-01
Polarized light (PL) sensitivity is relatively well studied in a large number of invertebrates and some fish species, but in most other vertebrate classes, including birds, the behavioural and physiological mechanism of PL sensitivity remains one of the big mysteries in sensory biology. Many organisms use the skylight polarization pattern as part of a sun compass for orientation, navigation and in spatial orientation tasks. In birds, the available evidence for an involvement of the skylight polarization pattern in sun-compass orientation is very weak. Instead, cue-conflict and cue-calibration experiments have shown that the skylight polarization pattern near the horizon at sunrise and sunset provides birds with a seasonally and latitudinally independent compass calibration reference. Despite convincing evidence that birds use PL cues for orientation, direct experimental evidence for PL sensitivity is still lacking. Avian double cones have been proposed as putative PL receptors, but detailed anatomical and physiological evidence will be needed to conclusively describe the avian PL receptor. Intriguing parallels between the functional and physiological properties of PL reception and light-dependent magnetoreception could point to a common receptor system. PMID:21282180
Galloway, D.L.; Hudnut, K.W.; Ingebritsen, S.E.; Phillips, S.P.; Peltzer, G.; Rogez, F.; Rosen, P.A.
1998-01-01
Interferometric synthetic aperture radar (InSAR) has great potential to detect and quantify land subsidence caused by aquifer system compaction. InSAR maps with high spatial detail and resolution of range displacement (±10 mm in change of land surface elevation) were developed for a groundwater basin (∼103 km2) in Antelope Valley, California, using radar data collected from the ERS-1 satellite. These data allow comprehensive comparison between recent (1993–1995) subsidence patterns and those detected historically (1926–1992) by more traditional methods. The changed subsidence patterns are generally compatible with recent shifts in land and water use. The InSAR-detected patterns are generally consistent with predictions based on a coupled model of groundwater flow and aquifer system compaction. The minor inconsistencies may reflect our imperfect knowledge of the distribution and properties of compressible sediments. When used in conjunction with coincident measurements of groundwater levels and other geologic information, InSAR data may be useful for constraining parameter estimates in simulations of aquifer system compaction.
Mechanisms for pattern specificity of deep-brain stimulation in Parkinson’s disease
Mato, Germán; Dellavale, Damián
2017-01-01
Deep brain stimulation (DBS) has become a widely used technique for treating advanced stages of neurological and psychiatric illness. In the case of motor disorders related to basal ganglia (BG) dysfunction, several mechanisms of action for the DBS therapy have been identified which might be involved simultaneously or in sequence. However, the identification of a common key mechanism underlying the clinical relevant DBS configurations has remained elusive due to the inherent complexity related to the interaction between the electrical stimulation and the neural tissue, and the intricate circuital structure of the BG-thalamocortical network. In this work, it is shown that the clinically relevant range for both, the frequency and intensity of the electrical stimulation pattern, is an emergent property of the BG anatomy at the system-level that can be addressed using mean-field descriptive models of the BG network. Moreover, it is shown that the activity resetting mechanism elicited by electrical stimulation provides a natural explanation to the ineffectiveness of irregular (i.e., aperiodic) stimulation patterns, which has been commonly observed in previously reported pathophysiology models of Parkinson’s disease. Using analytical and numerical techniques, these results have been reproduced in both cases: 1) a reduced mean-field model that can be thought as an elementary building block capable to capture the underlying fundamentals of the relevant loops constituting the BG-thalamocortical network, and 2) a detailed model constituted by the direct and hyperdirect loops including one-dimensional spatial structure of the BG nuclei. We found that the optimal ranges for the essential parameters of the stimulation patterns can be understood without taking into account biophysical details of the relevant structures. PMID:28813460
Li, Shoucheng; Liu, Wenquan; Cheng, Xu; Ellis, Erle C
2005-10-01
To realize the landscape programming of agro-ecosystem management, landscape-stratification can provide us the best understanding of landscape ecosystem at very detailed scales. For this purpose, the village landscapes in densely populated Jintang and Jianyang Counties of Sichuan Basin hilly region were mapped from high resolution (1 m) IKONOS satellite imagery by using a standardized 4 level ecological landscape classification and mapping system in a regionally-representative sample of five 500 x 500 m2 landscape quadrats (sample plots). Based on these maps, the spatial patterns were analyzed by landscape indicators, which demonstrated a large variety of landscape types or ecotopes across the village landscape of this region, with diversity indexes ranging from 1.08 to 2.26 at different levels of the landscape classification system. The richness indices ranged from 42.2% to 58.6 %, except that for the landcover at 85 %. About 12.5 % of the ecotopes were distributed in the same way in each landscape sample, and the remaining 87.5% were distributed differently. The landscape fragmentation indices varied from 2.93 to 4.27 across sample plots, and from 2.86 to 5.63 across classification levels. The population density and the road and hamlet areas had strong linear correlations with some landscape indicators, and especially, the correlation coefficients of hamlet areas with fractal indexes and fragmental dimensions were 0.957* and 0.991**, respectively. The differences in most landscape pattern indices across sample plots and landscape classes were statistically significant, indicating that cross-scale mapping and classification of village landscapes could provide more detailed information on landscape patterns than those from a single level of classification.
ABOVE- AND BELOWGROUND CONTROLS ON FOREST TREE GROWTH, MORTALITY AND SPATIAL PATTERN
We investigated the relative importance of above- and belowground competition in controlling growth, mortality and spatial patterns of trees in a nitrogen-limited, old-growth forest in western Oregon. To assess the effects of competition for light, we applied a spatially-explici...
Vergés, Adriana; Vanderklift, Mathew A.; Doropoulos, Christopher; Hyndes, Glenn A.
2011-01-01
Background Patterns of herbivory can alter the spatial structure of ecosystems, with important consequences for ecosystem functions and biodiversity. While the factors that drive spatial patterns in herbivory in terrestrial systems are well established, comparatively less is known about what influences the distribution of herbivory in coral reefs. Methodology and Principal Findings We quantified spatial patterns of macroalgal consumption in a cross-section of Ningaloo Reef (Western Australia). We used a combination of descriptive and experimental approaches to assess the influence of multiple macroalgal traits and structural complexity in establishing the observed spatial patterns in macroalgal herbivory, and to identify potential feedback mechanisms between herbivory and macroalgal nutritional quality. Spatial patterns in macroalgal consumption were best explained by differences in structural complexity among habitats. The biomass of herbivorous fish, and rates of herbivory were always greater in the structurally-complex coral-dominated outer reef and reef flat habitats, which were also characterised by high biomass of herbivorous fish, low cover and biomass of macroalgae and the presence of unpalatable algae species. Macroalgal consumption decreased to undetectable levels within 75 m of structurally-complex reef habitat, and algae were most abundant in the structurally-simple lagoon habitats, which were also characterised by the presence of the most palatable algae species. In contrast to terrestrial ecosystems, herbivory patterns were not influenced by the distribution, productivity or nutritional quality of resources (macroalgae), and we found no evidence of a positive feedback between macroalgal consumption and the nitrogen content of algae. Significance This study highlights the importance of seascape-scale patterns in structural complexity in determining spatial patterns of macroalgal consumption by fish. Given the importance of herbivory in maintaining the ability of coral reefs to reorganise and retain ecosystem functions following disturbance, structural complexity emerges as a critical feature that is essential for the healthy functioning of these ecosystems. PMID:21347254
Design and implementation of spatial knowledge grid for integrated spatial analysis
NASA Astrophysics Data System (ADS)
Liu, Xiangnan; Guan, Li; Wang, Ping
2006-10-01
Supported by spatial information grid(SIG), the spatial knowledge grid (SKG) for integrated spatial analysis utilizes the middleware technology in constructing the spatial information grid computation environment and spatial information service system, develops spatial entity oriented spatial data organization technology, carries out the profound computation of the spatial structure and spatial process pattern on the basis of Grid GIS infrastructure, spatial data grid and spatial information grid (specialized definition). At the same time, it realizes the complex spatial pattern expression and the spatial function process simulation by taking the spatial intelligent agent as the core to establish space initiative computation. Moreover through the establishment of virtual geographical environment with man-machine interactivity and blending, complex spatial modeling, network cooperation work and spatial community decision knowledge driven are achieved. The framework of SKG is discussed systematically in this paper. Its implement flow and the key technology with examples of overlay analysis are proposed as well.
NASA Astrophysics Data System (ADS)
Alexander, L.; Hupp, C. R.; Forman, R. T.
2002-12-01
Many geodisturbances occur across large spatial scales, spanning entire landscapes and creating ecological phenomena in their wake. Ecological study at large scales poses special problems: (1) large-scale studies require large-scale resources, and (2) sampling is not always feasible at the appropriate scale, and researchers rely on data collected at smaller scales to interpret patterns across broad regions. A criticism of landscape ecology is that findings at small spatial scales are "scaled up" and applied indiscriminately across larger spatial scales. In this research, landscape scaling is addressed through process-pattern relationships between hydrogeomorphic processes and patterns of plant diversity in forested wetlands. The research addresses: (1) whether patterns and relationships between hydrogeomorphic, vegetation, and spatial variables can transcend scale; and (2) whether data collected at small spatial scales can be used to describe patterns and relationships across larger spatial scales. Field measurements of hydrologic, geomorphic, spatial, and vegetation data were collected or calculated for 15- 1-ha sites on forested floodplains of six (6) Chesapeake Bay Coastal Plain streams over a total area of about 20,000 km2. Hydroperiod (day/yr), floodplain surface elevation range (m), discharge (m3/s), stream power (kg-m/s2), sediment deposition (mm/yr), relative position downstream and other variables were used in multivariate analyses to explain differences in species richness, tree diversity (Shannon-Wiener Diversity Index H'), and plant community composition at four spatial scales. Data collected at the plot (400-m2) and site- (c. 1-ha) scales are applied to and tested at the river watershed and regional spatial scales. Results indicate that plant species richness and tree diversity (Shannon-Wiener diversity index H') can be described by hydrogeomorphic conditions at all scales, but are best described at the site scale. Data collected at plot and site scales are tested for spatial heterogeneity across the Chesapeake Bay Coastal Plain using a geostatistical variogram, and multiple regression analysis is used to relate plant diversity, spatial, and hydrogeomorphic variables across Coastal Plain regions and hydrologic regimes. Results indicate that relationships between hydrogeomorphic processes and patterns of plant diversity at finer scales can proxy relationships at coarser scales in some, not all, cases. Findings also suggest that data collected at small scales can be used to describe trends across broader scales under limited conditions.
Landscape patterns from mathematical morphology on maps with contagion
Kurt Riitters; Peter Vogt; Pierre Soille; Christine Estreguil
2009-01-01
The perceived realism of simulated maps with contagion (spatial autocorrelation) has led to their use for comparing landscape pattern metrics and as habitat maps for modeling organism movement across landscapes. The objective of this study was to conduct a neutral model analysis of pattern metrics defined by morphological spatial pattern analysis (MSPA) on maps with...
Waite, I.R.; Carpenter, K.D.
2000-01-01
As part of the U.S. Geological Survey's National Water-Quality Assessment Program, fish were collected from 24 selected stream sites in the Willamette Basin during 1993-1995 to determine the composition of the fish assemblages and their relation to the chemical and physical environment. Variance in fish relative abundance was greater among all sites than among spatially distinct reaches within a site (spatial variation) or among multiple sampled years at a site (temporal variation). Therefore, data from a single reach in an individual year was considered to be a reliable estimator of the fish assemblage structure at a site when the data were normalized by percent relative abundance. Multivariate classification and ordination were used to examine patterns in environmental variables and fish relative abundance over differing spatial scales (among versus within ecoregions). Across all ecoregions (all sites), fish assemblages were primarily structured along environmental gradients of water temperature and stream gradient (coldwater, high-gradient forested sites versus warmwater, low-gradient Willamette Valley sites); this pattern superseded patterns that were ecoregion specific. Water temperature, dissolved oxygen, and physical habitat (e.g., riparian canopy and percent riffles) were associated with patterns of fish assemblages across all ecoregions; however, pesticide and total phosphorus concentrations were more important than physical habitat within the Willamette Valley ecoregion. Consideration of stream site stratification (e.g., stream size, ecoregion, and stream gradient), identification of fish to species level (particularly the sculpin family), and detailed measurement of habitat, diurnal dissolved oxygen, and water temperature were critical in evaluating the composition of fish assemblages in relation to land use. In general, these low-gradient valley streams typical of other agricultural regions had poor riparian systems and showed increases in water temperature, nutrients, and fine grain sediments that were associated with degradation in the native fish assemblages. There was an association of high abundances of introduced species and high percent external abnormalities in medium-sized river sites of mixed land use and high abundances of tolerant species in small streams of predominantly agricultural land use.
[Spatial distribution pattern of Chilo suppressalis analyzed by classical method and geostatistics].
Yuan, Zheming; Fu, Wei; Li, Fangyi
2004-04-01
Two original samples of Chilo suppressalis and their grid, random and sequence samples were analyzed by classical method and geostatistics to characterize the spatial distribution pattern of C. suppressalis. The limitations of spatial distribution analysis with classical method, especially influenced by the original position of grid, were summarized rather completely. On the contrary, geostatistics characterized well the spatial distribution pattern, congregation intensity and spatial heterogeneity of C. suppressalis. According to geostatistics, the population was up to Poisson distribution in low density. As for higher density population, its distribution was up to aggregative, and the aggregation intensity and dependence range were 0.1056 and 193 cm, respectively. Spatial heterogeneity was also found in the higher density population. Its spatial correlativity in line direction was more closely than that in row direction, and the dependence ranges in line and row direction were 115 and 264 cm, respectively.
Atmospheric circulation patterns and spatial climatic variations in Beringia
NASA Astrophysics Data System (ADS)
Mock, Cary J.; Bartlein, Patrick J.; Anderson, Patricia M.
1998-08-01
Analyses of more than 40 years of climatic data reveal intriguing spatial variations in climatic patterns for Beringia (North-eastern Siberia and Alaska), aiding the understanding of the hierarchy of climatic controls that operate at different spatial scales within the Arctic. A synoptic climatology, using a subjective classification methodology on January and July sea level pressure, and July 500 hPa height anomaly patterns, identified 13 major atmospheric circulation patterns (26 pairs consisting of 13 synoptic/temperature and 13 synoptic/precipitation comparisons) that occur over Beringia. Composite anomaly maps of circulation, temperature, and precipitation described the spatial variability of surface climatic responses to circulation. Results indicate that nine synoptic pairs yield homogeneous surface climatic anomaly patterns throughout most of Beringia. However, many of the surface climatic responses illustrate heterogeneous anomaly patterns as a result of variations in circulation controls, such as troughing over East Asia and the Pacific subtropical high superimposed over topography, with small shifts in atmospheric circulation dramatically altering spatial variations of anomaly patterns. Distinctive contrasts in climatic responses, as suggested from ten synoptic pairs, are clearly evident for Western Beringia versus Eastern Beringia. These results offer important implications for scholars interested in assessing late Quaternary climatic change in the region from interannual to millennial timescales.
Songhurst, Anna; Coulson, Tim
2014-03-01
Few universal trends in spatial patterns of wildlife crop-raiding have been found. Variations in wildlife ecology and movements, and human spatial use have been identified as causes of this apparent unpredictability. However, varying spatial patterns of spatial autocorrelation (SA) in human-wildlife conflict (HWC) data could also contribute. We explicitly explore the effects of SA on wildlife crop-raiding data in order to facilitate the design of future HWC studies. We conducted a comparative survey of raided and nonraided fields to determine key drivers of crop-raiding. Data were subsampled at different spatial scales to select independent raiding data points. The model derived from all data was fitted to subsample data sets. Model parameters from these models were compared to determine the effect of SA. Most methods used to account for SA in data attempt to correct for the change in P-values; yet, by subsampling data at broader spatial scales, we identified changes in regression estimates. We consequently advocate reporting both model parameters across a range of spatial scales to help biological interpretation. Patterns of SA vary spatially in our crop-raiding data. Spatial distribution of fields should therefore be considered when choosing the spatial scale for analyses of HWC studies. Robust key drivers of elephant crop-raiding included raiding history of a field and distance of field to a main elephant pathway. Understanding spatial patterns and determining reliable socio-ecological drivers of wildlife crop-raiding is paramount for designing mitigation and land-use planning strategies to reduce HWC. Spatial patterns of HWC are complex, determined by multiple factors acting at more than one scale; therefore, studies need to be designed with an understanding of the effects of SA. Our methods are accessible to a variety of practitioners to assess the effects of SA, thereby improving the reliability of conservation management actions.
Marschallinger, Robert; Golaszewski, Stefan M; Kunz, Alexander B; Kronbichler, Martin; Ladurner, Gunther; Hofmann, Peter; Trinka, Eugen; McCoy, Mark; Kraus, Jörg
2014-01-01
In multiple sclerosis (MS) the individual disease courses are very heterogeneous among patients and biomarkers for setting the diagnosis and the estimation of the prognosis for individual patients would be very helpful. For this purpose, we are developing a multidisciplinary method and workflow for the quantitative, spatial, and spatiotemporal analysis and characterization of MS lesion patterns from MRI with geostatistics. We worked on a small data set involving three synthetic and three real-world MS lesion patterns, covering a wide range of possible MS lesion configurations. After brain normalization, MS lesions were extracted and the resulting binary 3-dimensional models of MS lesion patterns were subject to geostatistical indicator variography in three orthogonal directions. By applying geostatistical indicator variography, we were able to describe the 3-dimensional spatial structure of MS lesion patterns in a standardized manner. Fitting a model function to the empirical variograms, spatial characteristics of the MS lesion patterns could be expressed and quantified by two parameters. An orthogonal plot of these parameters enabled a well-arranged comparison of the involved MS lesion patterns. This method in development is a promising candidate to complement standard image-based statistics by incorporating spatial quantification. The work flow is generic and not limited to analyzing MS lesion patterns. It can be completely automated for the screening of radiological archives. Copyright © 2013 by the American Society of Neuroimaging.
An Innovative Metric to Evaluate Satellite Precipitation's Spatial Distribution
NASA Astrophysics Data System (ADS)
Liu, H.; Chu, W.; Gao, X.; Sorooshian, S.
2011-12-01
Thanks to its capability to cover the mountains, where ground measurement instruments cannot reach, satellites provide a good means of estimating precipitation over mountainous regions. In regions with complex terrains, accurate information on high-resolution spatial distribution of precipitation is critical for many important issues, such as flood/landslide warning, reservoir operation, water system planning, etc. Therefore, in order to be useful in many practical applications, satellite precipitation products should possess high quality in characterizing spatial distribution. However, most existing validation metrics, which are based on point/grid comparison using simple statistics, cannot effectively measure satellite's skill of capturing the spatial patterns of precipitation fields. This deficiency results from the fact that point/grid-wised comparison does not take into account of the spatial coherence of precipitation fields. Furth more, another weakness of many metrics is that they can barely provide information on why satellite products perform well or poor. Motivated by our recent findings of the consistent spatial patterns of the precipitation field over the western U.S., we developed a new metric utilizing EOF analysis and Shannon entropy. The metric can be derived through two steps: 1) capture the dominant spatial patterns of precipitation fields from both satellite products and reference data through EOF analysis, and 2) compute the similarities between the corresponding dominant patterns using mutual information measurement defined with Shannon entropy. Instead of individual point/grid, the new metric treat the entire precipitation field simultaneously, naturally taking advantage of spatial dependence. Since the dominant spatial patterns are shaped by physical processes, the new metric can shed light on why satellite product can or cannot capture the spatial patterns. For demonstration, a experiment was carried out to evaluate a satellite precipitation product, CMORPH, against the U.S. daily precipitation analysis of Climate Prediction Center (CPC) at a daily and .25o scale over the Western U.S.
Does livestock grazing influence spatial patterns of woody plant proliferation?
USDA-ARS?s Scientific Manuscript database
Patterns of woody plant proliferation in grasslands and savannas influence rates of erosion, spread of disturbance, and nutrient pools. Spatial pattern is the outcome of plant dispersal, recruitment, competition/facilitation, and disturbance. We quantified effects of livestock grazing, a widely cit...
Gurunathan, Rajalakshmi; Van Emden, Bernard; Panchanathan, Sethuraman; Kumar, Sudhir
2004-01-01
Background Modern developmental biology relies heavily on the analysis of embryonic gene expression patterns. Investigators manually inspect hundreds or thousands of expression patterns to identify those that are spatially similar and to ultimately infer potential gene interactions. However, the rapid accumulation of gene expression pattern data over the last two decades, facilitated by high-throughput techniques, has produced a need for the development of efficient approaches for direct comparison of images, rather than their textual descriptions, to identify spatially similar expression patterns. Results The effectiveness of the Binary Feature Vector (BFV) and Invariant Moment Vector (IMV) based digital representations of the gene expression patterns in finding biologically meaningful patterns was compared for a small (226 images) and a large (1819 images) dataset. For each dataset, an ordered list of images, with respect to a query image, was generated to identify overlapping and similar gene expression patterns, in a manner comparable to what a developmental biologist might do. The results showed that the BFV representation consistently outperforms the IMV representation in finding biologically meaningful matches when spatial overlap of the gene expression pattern and the genes involved are considered. Furthermore, we explored the value of conducting image-content based searches in a dataset where individual expression components (or domains) of multi-domain expression patterns were also included separately. We found that this technique improves performance of both IMV and BFV based searches. Conclusions We conclude that the BFV representation consistently produces a more extensive and better list of biologically useful patterns than the IMV representation. The high quality of results obtained scales well as the search database becomes larger, which encourages efforts to build automated image query and retrieval systems for spatial gene expression patterns. PMID:15603586
Achieving pattern uniformity in plasmonic lithography by spatial frequency selection
NASA Astrophysics Data System (ADS)
Liang, Gaofeng; Chen, Xi; Zhao, Qing; Guo, L. Jay
2018-01-01
The effects of the surface roughness of thin films and defects on photomasks are investigated in two representative plasmonic lithography systems: thin silver film-based superlens and multilayer-based hyperbolic metamaterial (HMM). Superlens can replicate arbitrary patterns because of its broad evanescent wave passband, which also makes it inherently vulnerable to the roughness of the thin film and imperfections of the mask. On the other hand, the HMM system has spatial frequency filtering characteristics and its pattern formation is based on interference, producing uniform and stable periodic patterns. In this work, we show that the HMM system is more immune to such imperfections due to its function of spatial frequency selection. The analyses are further verified by an interference lithography system incorporating the photoresist layer as an optical waveguide to improve the aspect ratio of the pattern. It is concluded that a system capable of spatial frequency selection is a powerful method to produce deep-subwavelength periodic patterns with high degree of uniformity and fidelity.
Abiotic and biotic controls of spatial pattern at alpine treeline
Malanson, George P.; Xiao, Ningchuan; Alftine, K.J.; Bekker, Mathew; Butler, David R.; Brown, Daniel G.; Cairns, David M.; Fagre, Daniel; Walsh, Stephen J.
2000-01-01
At alpine treeline, trees and krummholz forms affect the environment in ways that increase their growth and reproduction. We assess the way in which these positive feedbacks combine in spatial patterns to alter the environment in the neighborhood of existing plants. The research is significant because areas of alpine tundra are susceptible to encroachment by woody species as climate changes. Moreover, understanding the general processes of plant invasion is important. The importance of spatial pattern has been recognized, but the spatial pattern of positive feedbacks per se has not been explored in depth. We present a linked set of models of vegetation change at an alpine forest-tundra ecotone. Our aim is to create models that are as simple as possible in order to test specific hypotheses. We present results from a model of the resource averaging hypothesis and the positive feedback switch hypothesis of treelines. We compare the patterns generated by the models to patterns observed in fine scale remotely sensed data.
A Multivariate Granger Causality Concept towards Full Brain Functional Connectivity.
Schmidt, Christoph; Pester, Britta; Schmid-Hertel, Nicole; Witte, Herbert; Wismüller, Axel; Leistritz, Lutz
2016-01-01
Detecting changes of spatially high-resolution functional connectivity patterns in the brain is crucial for improving the fundamental understanding of brain function in both health and disease, yet still poses one of the biggest challenges in computational neuroscience. Currently, classical multivariate Granger Causality analyses of directed interactions between single process components in coupled systems are commonly restricted to spatially low- dimensional data, which requires a pre-selection or aggregation of time series as a preprocessing step. In this paper we propose a new fully multivariate Granger Causality approach with embedded dimension reduction that makes it possible to obtain a representation of functional connectivity for spatially high-dimensional data. The resulting functional connectivity networks may consist of several thousand vertices and thus contain more detailed information compared to connectivity networks obtained from approaches based on particular regions of interest. Our large scale Granger Causality approach is applied to synthetic and resting state fMRI data with a focus on how well network community structure, which represents a functional segmentation of the network, is preserved. It is demonstrated that a number of different community detection algorithms, which utilize a variety of algorithmic strategies and exploit topological features differently, reveal meaningful information on the underlying network module structure.
Spatial Modeling for Groundwater Arsenic Levels in North Carolina
Kim, Dohyeong; Miranda, Marie Lynn; Tootoo, Joshua; Bradley, Phil; Gelfand, Alan E.
2013-01-01
To examine environmental and geologic determinants of arsenic in groundwater, detailed geologic data were integrated with well water arsenic concentration data and well construction data for 471 private wells in Orange County, NC, via a geographic information system. For the statistical analysis, the geologic units were simplified into four generalized categories based on rock type and interpreted mode of deposition/emplacement. The geologic transitions from rocks of a primary pyroclastic origin to rocks of volcaniclastic sedimentary origin were designated as polylines. The data were fitted to a left-censored regression model to identify key determinants of arsenic levels in groundwater. A Bayesian spatial random effects model was then developed to capture any spatial patterns in groundwater arsenic residuals into model estimation. Statistical model results indicate (1) wells close to a transition zone or fault are more likely to contain detectible arsenic; (2) welded tuffs and hydrothermal quartz bodies are associated with relatively higher groundwater arsenic concentrations and even higher for those proximal to a pluton; and (3) wells of greater depth are more likely to contain elevated arsenic. This modeling effort informs policy intervention by creating three-dimensional maps of predicted arsenic levels in groundwater for any location and depth in the area. PMID:21528844
Spatial modeling for groundwater arsenic levels in North Carolina.
Kim, Dohyeong; Miranda, Marie Lynn; Tootoo, Joshua; Bradley, Phil; Gelfand, Alan E
2011-06-01
To examine environmental and geologic determinants of arsenic in groundwater, detailed geologic data were integrated with well water arsenic concentration data and well construction data for 471 private wells in Orange County, NC, via a geographic information system. For the statistical analysis, the geologic units were simplified into four generalized categories based on rock type and interpreted mode of deposition/emplacement. The geologic transitions from rocks of a primary pyroclastic origin to rocks of volcaniclastic sedimentary origin were designated as polylines. The data were fitted to a left-censored regression model to identify key determinants of arsenic levels in groundwater. A Bayesian spatial random effects model was then developed to capture any spatial patterns in groundwater arsenic residuals into model estimation. Statistical model results indicate (1) wells close to a transition zone or fault are more likely to contain detectible arsenic; (2) welded tuffs and hydrothermal quartz bodies are associated with relatively higher groundwater arsenic concentrations and even higher for those proximal to a pluton; and (3) wells of greater depth are more likely to contain elevated arsenic. This modeling effort informs policy intervention by creating three-dimensional maps of predicted arsenic levels in groundwater for any location and depth in the area.
HESS Opinions Catchments as meta-organisms - a new blueprint for hydrological modelling
NASA Astrophysics Data System (ADS)
Savenije, Hubert H. G.; Hrachowitz, Markus
2017-02-01
Catchment-scale hydrological models frequently miss essential characteristics of what determines the functioning of catchments. The most important active agent in catchments is the ecosystem. It manipulates and partitions moisture in a way that supports the essential functions of survival and productivity: infiltration of water, retention of moisture, mobilization and retention of nutrients, and drainage. Ecosystems do this in the most efficient way, establishing a continuous, ever-evolving feedback loop with the landscape and climatic drivers. In brief, hydrological systems are alive and have a strong capacity to adjust themselves to prevailing and changing environmental conditions. Although most models take Newtonian theory at heart, as best they can, what they generally miss is Darwinian theory on how an ecosystem evolves and adjusts its environment to maintain crucial hydrological functions. In addition, catchments, such as many other natural systems, do not only evolve over time, but develop features of spatial organization, including surface or sub-surface drainage patterns, as a by-product of this evolution. Models that fail to account for patterns and the associated feedbacks miss a critical element of how systems at the interface of atmosphere, biosphere and pedosphere function. In contrast to what is widely believed, relatively simple, semi-distributed conceptual models have the potential to accommodate organizational features and their temporal evolution in an efficient way, a reason for that being that because their parameters (and their evolution over time) are effective at the modelling scale, and thus integrate natural heterogeneity within the system, they may be directly inferred from observations at the same scale, reducing the need for calibration and related problems. In particular, the emergence of new and more detailed observation systems from space will lead towards a more robust understanding of spatial organization and its evolution. This will further permit the development of relatively simple time-dynamic functional relationships that can meaningfully represent spatial patterns and their evolution over time, even in poorly gauged environments.
The spatial pattern of leaf phenology and its response to climate change in China.
Dai, Junhu; Wang, Huanjiong; Ge, Quansheng
2014-05-01
Leaf phenology has been shown to be one of the most important indicators of the effects of climate change on biological systems. Few such studies have, however, been published detailing the relationship between phenology and climate change in Asian contexts. With the aim of quantifying species' phenological responsiveness to temperature and deepening understandings of spatial patterns of phenological and climate change in China, this study analyzes the first leaf date (FLD) and the leaf coloring date (LCD) from datasets of four woody plant species, Robinia pseudoacacia, Ulmus pumila, Salix babylonica, and Melia azedarach, collected from 1963 to 2009 at 47 Chinese Phenological Observation Network (CPON) stations spread across China (from 21° to 50° N). The results of this study show that changes in temperatures in the range of 39-43 days preceding the date of FLD of these plants affected annual variations in FLD, while annual variations in temperature in the range of 71-85 days preceding LCD of these plants affected the date of LCD. Average temperature sensitivity of FLD and LCD for these plants was -3.93 to 3.30 days °C(-1) and 2.11 to 4.43 days °C⁻¹, respectively. Temperature sensitivity of FLD was found to be stronger at lower latitudes or altitude as well as in more continental climates, while the response of LCD showed no consistent pattern. Within the context of significant warming across China during the study period, FLD was found to have advanced by 5.44 days from 1960 to 2009; over the same period, LCD was found to have been delayed by 4.56 days. These findings indicate that the length of the growing season of the four plant species studied was extended by a total of 10.00 days from 1960 to 2009. They also indicate that phenological response to climate is highly heterogeneous spatially.
Derivation of spatial patterns of soil hydraulic properties based on pedotransfer functions
USDA-ARS?s Scientific Manuscript database
Spatial patterns in soil hydrology are the product of the spatial distribution of soil hydraulic properties. These properties are notorious for the difficulties and high labor costs involved in measuring them. Often, there is a need to resort to estimating these parameters from other, more readily a...
Spatial analysis of rural land development
Seong-Hoon Cho; David H. Newman
2005-01-01
This article examines patterns of rural land development and density using spatial econometric models with the application of Geographical Information System (GIS). The cluster patterns of both development and high-density development indicate that the spatially continuous expansions of development and high-density development exist in relatively remote rural areas....
Stocking rate effects on spatial heterogeneity in vegetation cover in a grazing-resistant grassland
USDA-ARS?s Scientific Manuscript database
Spatial patterns in rangeland vegetation serve as indicators of rangeland condition and are an important component of wildlife habitat. We illustrate the use of very-large-scale aerial photography (VLSA) to quantify spatial patterns in bare soil of the northeastern Colorado shortgrass steppe. Using ...
Grazing intensity and spatial heterogeneity in bare soil in a grazing-resistant grassland
USDA-ARS?s Scientific Manuscript database
Spatial patterns in rangeland vegetation serve as indicators of rangeland condition and are an important component of wildlife habitat. We illustrate the use of very-large-scale aerial photography (VLSA) to quantify spatial patterns in bare soil of the northeastern Colorado shortgrass steppe. Using ...
Sorted bedform pattern evolution: Persistence, destruction and self-organized intermittency
NASA Astrophysics Data System (ADS)
Goldstein, Evan B.; Murray, A. Brad; Coco, Giovanni
2011-12-01
We investigate the long-term evolution of inner continental shelf sorted bedform patterns. Numerical modeling suggests that a range of behaviors are possible, from pattern persistence to spatial-temporal intermittency. Sorted bedform persistence results from a robust sorting feedback that operates when the seabed features a sufficient concentration of coarse material. In the absence of storm events, pattern maturation processes such as defect dynamics and pattern migration tend to cause the burial of coarse material and excavation of fine material, leading to the fining of the active layer. Vertical sorting occurs until a critical state of active layer coarseness is reached. This critical state results in the local cessation of the sorting feedback, leading to a self-organized spatially intermittent pattern, a hallmark of observed sorted bedforms. Bedforms in shallow conditions and those subject to high wave climates may be temporally intermittent features as a result of increased wave orbital velocity during storms. Erosion, or deposition of bimodal sediment, similarly leads to a spatially intermittent pattern, with individual coarse domains exhibiting temporal intermittence. Recurring storm events cause coarsening of the seabed (strengthening the sorting feedback) and the development of large wavelength patterns. Cessation of storm events leads to the superposition of storm (large wavelength) and inter-storm (small wavelength) patterns and spatial heterogeneity of pattern modes.
1988 Wet deposition temporal and spatial patterns in North America
DOE Office of Scientific and Technical Information (OSTI.GOV)
Simpson, J.C.; Olsen, A.R.; Bittner, E.A.
1992-03-01
The focus of this report is on North American wet deposition temporal patterns from 1979 to 1988 and spatial patterns for 1988. It is the third in a series of reports that investigate the patterns of annual precipitation-weighted average concentration and annual deposition for nine ion species: hydrogen, sulfate, nitrate, ammonium, calcium, chloride, sodium, potassium, and magnesium. Mosaic maps, based on surface estimation using kriging, display concentration and deposition spatial patterns of pH, hydrogen, sulfate, nitrate, ammonium, and calcium ion species for 1988 annual, winter, and summer periods. Temporal pattern analyses use a subset of 35 sites over a 10-yearmore » (1979--1988) period and an expanded subset of 137 sites, with greater spatial coverage, over a 7-year (1982--1988) period. The 10-year period represents the longest period with wet deposition monitoring data available that has a sufficient number of sites with data of known quality to allow a descriptive summary of annual temporal patterns. Sen's median trend estimate and Kendall's seasonal tau (KST) test are calculated for each ion species concentration and deposition at each site in both subsets.« less
MATLAB for laser speckle contrast analysis (LASCA): a practice-based approach
NASA Astrophysics Data System (ADS)
Postnikov, Eugene B.; Tsoy, Maria O.; Postnov, Dmitry E.
2018-04-01
Laser Speckle Contrast Analysis (LASCA) is one of the most powerful modern methods for revealing blood dynamics. The experimental design and theory for this method are well established, and the computational recipie is often regarded to be trivial. However, the achieved performance and spatial resolution may considerable differ for different implementations. We comprise a minireview of known approaches to the spatial laser speckle contrast data processing and their realization in MATLAB code providing an explicit correspondence to the mathematical representation, a discussion of available implementations. We also present the algorithm based on the 2D Haar wavelet transform, also supplied with the program code. This new method provides an opportunity to introduce horizontal, vertical and diagonal speckle contrasts; it may be used for processing highly anisotropic images of vascular trees. We provide the comparative analysis of the accuracy of vascular pattern detection and the processing times with a special attention to details of the used MATLAB procedures.
NASA Astrophysics Data System (ADS)
Garchitorena, Andrés; Ngonghala, Calistus N.; Texier, Gaëtan; Landier, Jordi; Eyangoh, Sara; Bonds, Matthew H.; Guégan, Jean-François; Roche, Benjamin
2015-12-01
Buruli Ulcer is a devastating skin disease caused by the pathogen Mycobacterium ulcerans. Emergence and distribution of Buruli ulcer cases is clearly linked to aquatic ecosystems, but the specific route of transmission of M. ulcerans to humans remains unclear. Relying on the most detailed field data in space and time on M. ulcerans and Buruli ulcer available today, we assess the relative contribution of two potential transmission routes -environmental and water bug transmission- to the dynamics of Buruli ulcer in two endemic regions of Cameroon. The temporal dynamics of Buruli ulcer incidence are explained by estimating rates of different routes of transmission in mathematical models. Independently, we also estimate statistical models of the different transmission pathways on the spatial distribution of Buruli ulcer. The results of these two independent approaches are corroborative and suggest that environmental transmission pathways explain the temporal and spatial patterns of Buruli ulcer in our endemic areas better than the water bug transmission.
All-optical electrophysiology in mammalian neurons using engineered microbial rhodopsins
Hochbaum, Daniel R.; Zhao, Yongxin; Farhi, Samouil L.; Klapoetke, Nathan; Werley, Christopher A.; Kapoor, Vikrant; Zou, Peng; Kralj, Joel M.; Maclaurin, Dougal; Smedemark-Margulies, Niklas; Saulnier, Jessica L.; Boulting, Gabriella L.; Straub, Christoph; Cho, Yong Ku; Melkonian, Michael; Wong, Gane Ka-Shu; Harrison, D. Jed; Murthy, Venkatesh N.; Sabatini, Bernardo; Boyden, Edward S.; Campbell, Robert E.; Cohen, Adam E.
2014-01-01
All-optical electrophysiology—spatially resolved simultaneous optical perturbation and measurement of membrane voltage—would open new vistas in neuroscience research. We evolved two archaerhodopsin-based voltage indicators, QuasAr1 and 2, which show improved brightness and voltage sensitivity, microsecond response times, and produce no photocurrent. We engineered a novel channelrhodopsin actuator, CheRiff, which shows improved light sensitivity and kinetics, and spectral orthogonality to the QuasArs. A co-expression vector, Optopatch, enabled crosstalk-free genetically targeted all-optical electrophysiology. In cultured neurons, we combined Optopatch with patterned optical excitation to probe back-propagating action potentials in dendritic spines, synaptic transmission, sub-cellular microsecond-timescale details of action potential propagation, and simultaneous firing of many neurons in a network. Optopatch measurements revealed homeostatic tuning of intrinsic excitability in human stem cell-derived neurons. In brain slice, Optopatch induced and reported action potentials and subthreshold events, with high signal-to-noise ratios. The Optopatch platform enables high-throughput, spatially resolved electrophysiology without use of conventional electrodes. PMID:24952910
Spatial resolution requirements for urban land cover mapping from space
NASA Technical Reports Server (NTRS)
Todd, William J.; Wrigley, Robert C.
1986-01-01
Very low resolution (VLR) satellite data (Advanced Very High Resolution Radiometer, DMSP Operational Linescan System), low resolution (LR) data (Landsat MSS), medium resolution (MR) data (Landsat TM), and high resolution (HR) satellite data (Spot HRV, Large Format Camera) were evaluated and compared for interpretability at differing spatial resolutions. VLR data (500 m - 1.0 km) is useful for Level 1 (urban/rural distinction) mapping at 1:1,000,000 scale. Feature tone/color is utilized to distinguish generalized urban land cover using LR data (80 m) for 1:250,000 scale mapping. Advancing to MR data (30 m) and 1:100,000 scale mapping, confidence in land cover mapping is greatly increased, owing to the element of texture/pattern which is now evident in the imagery. Shape and shadow contribute to detailed Level II/III urban land use mapping possible if the interpreter can use HR (10-15 m) satellite data; mapping scales can be 1:25,000 - 1:50,000.
a Novel Framework for Remote Sensing Image Scene Classification
NASA Astrophysics Data System (ADS)
Jiang, S.; Zhao, H.; Wu, W.; Tan, Q.
2018-04-01
High resolution remote sensing (HRRS) images scene classification aims to label an image with a specific semantic category. HRRS images contain more details of the ground objects and their spatial distribution patterns than low spatial resolution images. Scene classification can bridge the gap between low-level features and high-level semantics. It can be applied in urban planning, target detection and other fields. This paper proposes a novel framework for HRRS images scene classification. This framework combines the convolutional neural network (CNN) and XGBoost, which utilizes CNN as feature extractor and XGBoost as a classifier. Then, this framework is evaluated on two different HRRS images datasets: UC-Merced dataset and NWPU-RESISC45 dataset. Our framework achieved satisfying accuracies on two datasets, which is 95.57 % and 83.35 % respectively. From the experiments result, our framework has been proven to be effective for remote sensing images classification. Furthermore, we believe this framework will be more practical for further HRRS scene classification, since it costs less time on training stage.
NASA Technical Reports Server (NTRS)
Dykstra, J. D.; Sheffield, C. A.; Everett, J. R.
1984-01-01
As with any tool applied to geologic exploration, maximum value results from the innovative integration of optimally processed LANDSAT-4 data with existing pertinent information and perceptive geologic thinking. The synoptic view of the satellite images and the relatively high resolution of the data permits recognization of regional tectonic patterns and their detailed mapping. The refined spatial and spectral characteristics and digital nature surface alterations associated with hydrothermal activity and microseepage of hydrocarbons. In general, as vegetation and soil cover increase, the value of spectral components of TM data decreases with respect to the value of the spatial component of the data. This observation reinforces the experience from working with MSS data that digital processing must be optimized both for the area and for the application.
Frequency clusters in self-excited dust density waves
NASA Astrophysics Data System (ADS)
Menzel, Kristoffer O.; Arp, Oliver; Piel, Alexander
2010-11-01
Self-excited dust density waves were studied under microgravity conditions. Their non-sinusoidal shape and high degrees of modulation suggests that nonlinear effects play an important role in their spatio-temporal dynamics. The resulting complex wave pattern is analyzed in great detail by means of the Hilbert transform, which provides instantaneous wave attributes, such as the phase and the frequency. Our analysis showed that the spatial frequency distribution of the DDWs is usually not constant over the dust cloud. In contrast, the wave field is divided into regions of different but almost constant frequencies [1]. The boundaries of these so-called frequency clusters coincide with the locations of phase defects in the wave field. It is found that the size of the clusters depends on the strength of spatial gradients in the plasma parameters. We attribute the formation of frequency clusters to synchronization phenomena as a consequence of the nonlinear character of the wave.[1] K. O. Menzel, O. Arp, A.Piel, Phys. Rev. Lett. 104, 235002 (2010)
Experimental investigation of the 2D ion beam profile generated by an ESI octopole-QMS system.
Syed, Sarfaraz U A H; Eijkel, Gert B; Kistemaker, Piet; Ellis, Shane; Maher, Simon; Smith, Donald F; Heeren, Ron M A
2014-10-01
In this paper, we have employed an ion imaging approach to investigate the behavior of ions exiting from a quadrupole mass spectrometer (QMS) system that employs a radio frequency octopole ion guide before the QMS. An in-vacuum active pixel detector (Timepix) is employed at the exit of the QMS to image the ion patterns. The detector assembly simultaneously records the ion impact position and number of ions per pixel in every measurement frame. The transmission characteristics of the ion beam exiting the QMS are studied using this imaging detector under different operating conditions. Experimental results confirm that the ion spatial distribution exiting the QMS is heavily influenced by ion injection conditions. Furthermore, ion images from Timepix measurements of protein standards demonstrate the capability to enhance the quality of the mass spectral information and provide a detailed insight in the spatial distribution of different charge states (and hence different m/z) ions exiting the QMS.
Implications of Web Mercator and its Use in Online Mapping
Battersby, Sarah E.; Finn, Michael P.; Usery, E. Lynn; Yamamoto, Kristina H.
2014-01-01
Online interactive maps have become a popular means of communicating with spatial data. In most online mapping systems, Web Mercator has become the dominant projection. While the Mercator projection has a long history of discussion about its inappropriateness for general-purpose mapping, particularly at the global scale, and seems to have been virtually phased out for general-purpose global-scale print maps, it has seen a resurgence in popularity in Web Mercator form. This article theorizes on how Web Mercator came to be widely used for online maps and what this might mean in terms of data display, technical aspects of map generation and distribution, design, and cognition of spatial patterns. The authors emphasize details of where the projection excels and where it does not, as well as some of its advantages and disadvantages for cartographic communication, and conclude with some research directions that may help to develop better solutions to the problem of projections for general-purpose, multi-scale Web mapping.
NASA Astrophysics Data System (ADS)
Kamińska, Anna
2010-01-01
The relationship between karst of chalk and tectonics in the interfluve of the middle Wieprz and Bug Rivers has been already examined by Maruszczak (1966), Harasimiuk (1980) and Dobrowolski (1998). Investigating the connection of the karst formation course and the substratum structure, the direction of the landforms and their spatial pattern were analysed and compared later to the structural pattern. The obvious completion of the collected data is a quantity analysis using statistical methods. This paper deals with the characteristics of such quantity analysis. By using the tools of the directional statistics, the following indexes have been calculated: the mean vector orientation, the length of the vector mean, strength of the vector mean, the Batschelet variance, as well as determined confidence intervals for the mean vector. In order to examine the distribution structure of these forms, the selected methods of the spatial statistics have been used-angular wavelet analysis (Rosenberg 2004) and the semivariogram analysis (Namysłowska-Wilczyńska 2006). On the basis of conducted analyses, it is possible to describe in detail the regularities in spatial distribution of the surface karst forms in the interfluve of the middle Wieprz and Bug Rivers. The orientation analysis reveals an important feature of their direction-along with a rise in the size of surface karst forms, the level of concentration around the mean vector orientation increases. Primary karst forms point out poor concentration along the longitudinal direction whereas complex forms are clearly concentrated along the WNW-ESE direction. Hence, only after clumping of the primary forms into the complex ones, the convergence of the surface karst forms direction with the direction of the main faults in the Meso-Cenozoic complex is visible (after A. Henkiel 1984). The results of the wavelet analysis modified by Rosenberg (2004) have indicated significant directions of the clumping of the surface karst forms. A clear difference in the distribution of these forms in west and east areas is noticed. Whereas the west area is dominated by the W-E, NW-SE, N-S directions, the karst forms in the east are concentrated along the NE-SW direction. The semivariogram analysis has confirmed the importance of the W-E and NE-SW directions. Moreover, this analysis has indicated which areas are characterized by the poor karst forms direction. It is a region where the Kock-Wasylów dislocation zone crosses the Święcica dislocation zone in the north-east part of the analysed area. The south-east region is the second such area. The picture of the spatial pattern one confirms the previous results (Dobrowolski 1998) and refers clearly to the structural pattern of this area. Nevertheless, the analyses mentioned above have shown the dominance of the W-E direction over the NW-SE one. The obtained results of the spatial and direction analyses expand and confirm hitherto information about the relation between the spatial pattern of the karst landforms and the tectonics in the interfluve of the middle Wieprz and Bug Rivers.
Patterns in artisanal coral reef fisheries revealed through local monitoring efforts
Teneva, Lida T.; Ogawa, Tom; Friedlander, Alan M.
2017-01-01
Sustainable fisheries management is key to restoring and maintaining ecological function and benefits to people, but it requires accurate information about patterns of resource use, particularly fishing pressure. In most coral reef fisheries and other data-poor contexts, obtaining such information is challenging and remains an impediment to effective management. We developed the most comprehensive regional view of shore-based fishing effort and catch published to date, to show detailed fishing patterns from across the main Hawaiian Islands (MHI). We reveal these regional patterns through fisher “creel” surveys conducted by local communities, state agencies, academics, and/or environmental organizations, at 18 sites, comprising >10,000 h of monitoring across a range of habitats and human influences throughout the MHI. All creel surveys included in this study except for one were previously published in some form (peer-reviewed articles or gray literature reports). Here, we synthesize these studies to document spatial patterns in nearshore fisheries catch, effort, catch rates (i.e., catch-per-unit-effort (CPUE)), and catch disposition (i.e., use of fish after catch is landed). This effort provides for a description of general regional patterns based on these location-specific studies. Line fishing was by far the dominant gear type employed. The most efficient gear (i.e., highest CPUE) was spear (0.64 kg h−1), followed closely by net (0.61 kg h−1), with CPUE for line (0.16 kg h−1) substantially lower than the other two methods. Creel surveys also documented illegal fishing activity across the studied locations, although these activities were not consistent across sites. Overall, most of the catch was not sold, but rather retained for home consumption or given away to extended family, which suggests that cultural practices and food security may be stronger drivers of fishing effort than commercial exploitation for coral reef fisheries in Hawai‘i. Increased monitoring of spatial patterns in nearshore fisheries can inform targeted management, and can help communities develop a more informed understanding of the drivers of marine resource harvest and the state of the resources, in order to maintain these fisheries for food security, cultural practices, and ecological value. PMID:29226033
Spatial organization of bacterial chromosomes
Wang, Xindan; Rudner, David Z.
2014-01-01
Bacterial chromosomes are organized in stereotypical patterns that are faithfully and robustly regenerated in daughter cells. Two distinct spatial patterns were described almost a decade ago in our most tractable model organisms. In recent years, analysis of chromosome organization in a larger and more diverse set of bacteria and a deeper characterization of chromosome dynamics in the original model systems have provided a broader and more complete picture of both chromosome organization and the activities that generate the observed spatial patterns. Here, we summarize these different patterns highlighting similarities and differences and discuss the protein factors that help establish and maintain them. PMID:25460798
Reiter, Matthew E.; Andersen, David E.
2013-01-01
Quantifying spatial patterns of bird nests and nest fate provides insights into processes influencing a species’ distribution. At Cape Churchill, Manitoba, Canada, recent declines in breeding Eastern Prairie Population Canada geese (Branta canadensis interior) has coincided with increasing populations of nesting lesser snow geese (Chen caerulescens caerulescens) and Ross’s geese (Chen rossii). We conducted a spatial analysis of point patterns using Canada goose nest locations and nest fate, and lesser snow goose nest locations at two study areas in northern Manitoba with different densities and temporal durations of sympatric nesting Canada and lesser snow geese. Specifically, we assessed (1) whether Canada geese exhibited territoriality and at what scale and nest density; and (2) whether spatial patterns of Canada goose nest fate were associated with the density of nesting lesser snow geese as predicted by the protective-association hypothesis. Between 2001 and 2007, our data suggest that Canada geese were territorial at the scale of nearest neighbors, but were aggregated when considering overall density of conspecifics at slightly broader spatial scales. The spatial distribution of nest fates indicated that lesser snow goose nest proximity and density likely influence Canada goose nest fate. Our analyses of spatial point patterns suggested that continued changes in the distribution and abundance of breeding lesser snow geese on the Hudson Bay Lowlands may have impacts on the reproductive performance of Canada geese, and subsequently the spatial distribution of Canada goose nests.
NASA Astrophysics Data System (ADS)
Verma, S.; Gupta, R. D.
2014-11-01
In recent times, Japanese Encephalitis (JE) has emerged as a serious public health problem. In India, JE outbreaks were recently reported in Uttar Pradesh, Gorakhpur. The present study presents an approach to use GIS for analyzing the reported cases of JE in the Gorakhpur district based on spatial analysis to bring out the spatial and temporal dynamics of the JE epidemic. The study investigates spatiotemporal pattern of the occurrence of disease and detection of the JE hotspot. Spatial patterns of the JE disease can provide an understanding of geographical changes. Geospatial distribution of the JE disease outbreak is being investigated since 2005 in this study. The JE incidence data for the years 2005 to 2010 is used. The data is then geo-coded at block level. Spatial analysis is used to evaluate autocorrelation in JE distribution and to test the cases that are clustered or dispersed in space. The Inverse Distance Weighting interpolation technique is used to predict the pattern of JE incidence distribution prevalent across the study area. Moran's I Index (Moran's I) statistics is used to evaluate autocorrelation in spatial distribution. The Getis-Ord Gi*(d) is used to identify the disease areas. The results represent spatial disease patterns from 2005 to 2010, depicting spatially clustered patterns with significant differences between the blocks. It is observed that the blocks on the built up areas reported higher incidences.
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.
NASA Astrophysics Data System (ADS)
Rasam, A. R. A.; Ghazali, R.; Noor, A. M. M.; Mohd, W. M. N. W.; Hamid, J. R. A.; Bazlan, M. J.; Ahmad, N.
2014-02-01
Cholera spatial epidemiology is the study of the spread and control of the disease spatial pattern and epidemics. Previous studies have shown that multi-factorial causation such as human behaviour, ecology and other infectious risk factors influence the disease outbreaks. Thus, understanding spatial pattern and possible interrelationship factors of the outbreaks are crucial to be explored an in-depth study. This study focuses on the integration of geographical information system (GIS) and epidemiological techniques in exploratory analyzing the cholera spatial pattern and distribution in the selected district of Sabah. Spatial Statistic and Pattern tools in ArcGIS and Microsoft Excel software were utilized to map and analyze the reported cholera cases and other data used. Meanwhile, cohort study in epidemiological technique was applied to investigate multiple outcomes of the disease exposure. The general spatial pattern of cholera was highly clustered showed the disease spread easily at a place or person to others especially 1500 meters from the infected person and locations. Although the cholera outbreaks in the districts are not critical, it could be endemic at the crowded areas, unhygienic environment, and close to contaminated water. It was also strongly believed that the coastal water of the study areas has possible relationship with the cholera transmission and phytoplankton bloom since the areas recorded higher cases. GIS demonstrates a vital spatial epidemiological technique in determining the distribution pattern and elucidating the hypotheses generating of the disease. The next research would be applying some advanced geo-analysis methods and other disease risk factors for producing a significant a local scale predictive risk model of the disease in Malaysia.
[Spatial distribution pattern of Pontania dolichura larvae and sampling technique].
Zhang, Feng; Chen, Zhijie; Zhang, Shulian; Zhao, Huiyan
2006-03-01
In this paper, the spatial distribution pattern of Pontania dolichura larvae was analyzed with Taylor's power law, Iwao's distribution function, and six aggregation indexes. The results showed that the spatial distribution pattern of P. dolichura larvae was of aggregated, and the basic component of the distribution was individual colony, with the aggregation intensity increased with density. On branches, the aggregation was caused by the adult behavior of laying eggs and the spatial position of leaves, while on leaves, the aggregation was caused by the spatial position of news leaves in spring when m < 2.37, and by the spatial position of news leaves in spring and the behavior of eclosion and laying eggs when m > 2.37. By using the parameters alpha and beta in Iwao's m * -m regression equation, the optimal and sequential sampling numbers were determined.
Razmjou, Amir; Asadnia, Mohsen; Ghaebi, Omid; Yang, Hao-Cheng; Ebrahimi Warkiani, Majid; Hou, Jingwei; Chen, Vicki
2017-11-01
In this work, spatial patterning of a thin, dense, zeolitic imidazolate framework (ZIF-8) pattern was generated using photolithography and nanoscale (60 nm) dopamine coating. A bioinspired, unique, reversible, two-color iridescent pattern can be easily obtained for potential applications in sensing and photonics.
Spatial/Spectral Identification of Endmembers from AVIRIS Data using Mathematical Morphology
NASA Technical Reports Server (NTRS)
Plaza, Antonio; Martinez, Pablo; Gualtieri, J. Anthony; Perez, Rosa M.
2001-01-01
During the last several years, a number of airborne and satellite hyperspectral sensors have been developed or improved for remote sensing applications. Imaging spectrometry allows the detection of materials, objects and regions in a particular scene with a high degree of accuracy. Hyperspectral data typically consist of hundreds of thousands of spectra, so the analysis of this information is a key issue. Mathematical morphology theory is a widely used nonlinear technique for image analysis and pattern recognition. Although it is especially well suited to segment binary or grayscale images with irregular and complex shapes, its application in the classification/segmentation of multispectral or hyperspectral images has been quite rare. In this paper, we discuss a new completely automated methodology to find endmembers in the hyperspectral data cube using mathematical morphology. The extension of classic morphology to the hyperspectral domain allows us to integrate spectral and spatial information in the analysis process. In Section 3, some basic concepts about mathematical morphology and the technical details of our algorithm are provided. In Section 4, the accuracy of the proposed method is tested by its application to real hyperspectral data obtained from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imaging spectrometer. Some details about these data and reference results, obtained by well-known endmember extraction techniques, are provided in Section 2. Finally, in Section 5 we expose the main conclusions at which we have arrived.
Analysis of spatial autocorrelation patterns of heavy and super-heavy rainfall in Iran
NASA Astrophysics Data System (ADS)
Rousta, Iman; Doostkamian, Mehdi; Haghighi, Esmaeil; Ghafarian Malamiri, Hamid Reza; Yarahmadi, Parvane
2017-09-01
Rainfall is a highly variable climatic element, and rainfall-related changes occur in spatial and temporal dimensions within a regional climate. The purpose of this study is to investigate the spatial autocorrelation changes of Iran's heavy and super-heavy rainfall over the past 40 years. For this purpose, the daily rainfall data of 664 meteorological stations between 1971 and 2011 are used. To analyze the changes in rainfall within a decade, geostatistical techniques like spatial autocorrelation analysis of hot spots, based on the Getis-Ord G i statistic, are employed. Furthermore, programming features in MATLAB, Surfer, and GIS are used. The results indicate that the Caspian coast, the northwest and west of the western foothills of the Zagros Mountains of Iran, the inner regions of Iran, and southern parts of Southeast and Northeast Iran, have the highest likelihood of heavy and super-heavy rainfall. The spatial pattern of heavy rainfall shows that, despite its oscillation in different periods, the maximum positive spatial autocorrelation pattern of heavy rainfall includes areas of the west, northwest and west coast of the Caspian Sea. On the other hand, a negative spatial autocorrelation pattern of heavy rainfall is observed in central Iran and parts of the east, particularly in Zabul. Finally, it is found that patterns of super-heavy rainfall are similar to those of heavy rainfall.
Changes in glacier dynamics in the northern Antarctic Peninsula since 1985
NASA Astrophysics Data System (ADS)
Seehaus, Thorsten; Cook, Alison J.; Silva, Aline B.; Braun, Matthias
2018-02-01
The climatic conditions along the northern Antarctic Peninsula have shown significant changes within the last 50 years. Here we present a comprehensive analysis of temporally and spatially detailed observations of the changes in ice dynamics along both the east and west coastlines of the northern Antarctic Peninsula. Temporal evolutions of glacier area (1985-2015) and ice surface velocity (1992-2014) are derived from a broad multi-mission remote sensing database for 74 glacier basins on the northern Antarctic Peninsula ( < 65° S along the west coast and north of the Seal Nunataks on the east coast). A recession of the glaciers by 238.81 km2 is found for the period 1985-2015, of which the glaciers affected by ice shelf disintegration showed the largest retreat by 208.59 km2. Glaciers on the east coast north of the former Prince Gustav Ice Shelf extent in 1986 receded by only 21.07 km2 (1985-2015) and decelerated by about 58 % on average (1992-2014). A dramatic acceleration after ice shelf disintegration with a subsequent deceleration is observed at most former ice shelf tributaries on the east coast, combined with a significant frontal retreat. In 2014, the flow speed of the former ice shelf tributaries was 26 % higher than before 1996. Along the west coast the average flow speeds of the glaciers increased by 41 %. However, the glaciers on the western Antarctic Peninsula revealed a strong spatial variability of the changes in ice dynamics. By applying a hierarchical cluster analysis, we show that this is associated with the geometric parameters of the individual glacier basins (hypsometric indexes, maximum surface elevation of the basin, flux gate to catchment size ratio). The heterogeneous spatial pattern of ice dynamic evolutions at the northern Antarctic Peninsula shows that temporally and spatially detailed observations as well as further monitoring are necessary to fully understand glacier change in regions with such strong topographic and climatic variances.
Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang
2013-01-01
Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management. PMID:24287859
Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang
2013-11-27
Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management.
Spatial aspects of tree mortality strongly differ between young and old-growth forests.
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.
Prpic, Nikola-Michael; Janssen, Ralf; Wigand, Barbara; Klingler, Martin; Damen, Wim G M
2003-12-01
Leg development in Drosophila has been studied in much detail. However, Drosophila limbs form in the larva as imaginal discs and not during embryogenesis as in most other arthropods. Here, we analyze appendage genes in the spider Cupiennius salei and the beetle Tribolium castaneum. Differences in decapentaplegic (dpp) expression suggest a different mode of distal morphogen signaling suitable for the specific geometry of growing limb buds. Also, expression of the proximal genes homothorax (hth) and extradenticle (exd) is significantly altered: in the spider, exd is restricted to the proximal leg and hth expression extends distally, while in insects, exd is expressed in the entire leg and hth is restricted to proximal parts. This reversal of spatial specificity demonstrates an evolutionary shift, which is nevertheless compatible with a conserved role of this gene pair as instructor of proximal fate. Different expression dynamics of dachshund and Distal-less point to modifications in the regulation of the leg gap gene system. We comment on the significance of this finding for attempts to homologize leg segments in different arthropod classes. Comparison of the expression profiles of H15 and optomotor-blind to the Drosophila patterns suggests modifications also in the dorsal-ventral patterning system of the legs. Together, our results suggest alterations in many components of the leg developmental system, namely proximal-distal and dorsal-ventral patterning, and leg segmentation. Thus, the leg developmental system exhibits a propensity to evolutionary change, which probably forms the basis for the impressive diversity of arthropod leg morphologies.
Nonconstant Positive Steady States and Pattern Formation of 1D Prey-Taxis Systems
NASA Astrophysics Data System (ADS)
Wang, Qi; Song, Yang; Shao, Lingjie
2017-02-01
Prey-taxis is the process that predators move preferentially toward patches with highest density of prey. It is well known to have an important role in biological control and the maintenance of biodiversity. To model the coexistence and spatial distributions of predator and prey species, this paper concerns nonconstant positive steady states of a wide class of prey-taxis systems with general functional responses over 1D domain. Linearized stability of the positive equilibrium is analyzed to show that prey-taxis destabilizes prey-predator homogeneity when prey repulsion (e.g., due to volume-filling effect in predator species or group defense in prey species) is present, and prey-taxis stabilizes the homogeneity otherwise. Then, we investigate the existence and stability of nonconstant positive steady states to the system through rigorous bifurcation analysis. Moreover, we provide detailed and thorough calculations to determine properties such as pitchfork and turning direction of the local branches. Our stability results also provide a stable wave mode selection mechanism for thee reaction-advection-diffusion systems including prey-taxis models considered in this paper. Finally, we provide numerical studies of prey-taxis systems with Holling-Tanner kinetics to illustrate and support our theoretical findings. Our numerical simulations demonstrate that the 2× 2 prey-taxis system is able to model the formation and evolution of various striking patterns, such as spikes, periodic oscillations, and coarsening even when the domain is one-dimensional. These dynamics can model the coexistence and spatial distributions of interacting prey and predator species. We also give some insights on how system parameters influence pattern formation in these models.
The potential of using Landsat time-series to extract tropical dry forest phenology
NASA Astrophysics Data System (ADS)
Zhu, X.; Helmer, E.
2016-12-01
Vegetation phenology is the timing of seasonal developmental stages in plant life cycles. Due to the persistent cloud cover in tropical regions, current studies often use satellite data with high frequency, such as AVHRR and MODIS, to detect vegetation phenology. However, the spatial resolution of these data is from 250 m to 1 km, which does not have enough spatial details and it is difficult to relate to field observations. To produce maps of phenology at a finer spatial resolution, this study explores the feasibility of using Landsat images to detect tropical forest phenology through reconstructing a high-quality, seasonal time-series of images, and tested it in Mona Island, Puerto Rico. First, an automatic method was applied to detect cloud and cloud shadow, and a spatial interpolator was use to retrieve pixels covered by clouds, shadows, and SLC-off gaps. Second, enhanced vegetation index time-series derived from the reconstructed Landsat images were used to detect 11 phenology variables. Detected phenology is consistent with field investigations, and its spatial pattern is consistent with the rainfall distribution on this island. In addition, we may expect that phenology should correlate with forest biophysical attributes, so 47 plots with field measurement of biophysical attributes were used to indirectly validate the phenology product. Results show that phenology variables can explain a lot of variations in biophysical attributes. This study suggests that Landsat time-series has great potential to detect phenology in tropical areas.