Spatially explicit shallow landslide susceptibility mapping over large areas
Dino Bellugi; William E. Dietrich; Jonathan Stock; Jim McKean; Brian Kazian; Paul Hargrove
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...
Development of a large-area Multigap RPC with adequate spatial resolution for muon tomography
NASA Astrophysics Data System (ADS)
Wang, J.; Wang, Y.; Wang, X.; Zeng, M.; Xie, B.; Han, D.; Lyu, P.; Wang, F.; Li, Y.
2016-11-01
We study the performance of a large-area 2-D Multigap Resistive Plate Chamber (MRPC) designed for muon tomography with high spatial resolution. An efficiency up to 98% and a spatial resolution of around 270 μ m are obtained in cosmic ray and X-ray tests. The performance of the MRPC is also investigated for two working gases: standard gas and pure Freon. The result shows that the MRPC working in pure Freon can provide higher efficiency and better spatial resolution.
Lin, Yu-Pin; Chu, Hone-Jay; Wang, Cheng-Long; Yu, Hsiao-Hsuan; Wang, Yung-Chieh
2009-01-01
This study applies variogram analyses of normalized difference vegetation index (NDVI) images derived from SPOT HRV images obtained before and after the ChiChi earthquake in the Chenyulan watershed, Taiwan, as well as images after four large typhoons, to delineate the spatial patterns, spatial structures and spatial variability of landscapes caused by these large disturbances. The conditional Latin hypercube sampling approach was applied to select samples from multiple NDVI images. Kriging and sequential Gaussian simulation with sufficient samples were then used to generate maps of NDVI images. The variography of NDVI image results demonstrate that spatial patterns of disturbed landscapes were successfully delineated by variogram analysis in study areas. The high-magnitude Chi-Chi earthquake created spatial landscape variations in the study area. After the earthquake, the cumulative impacts of typhoons on landscape patterns depended on the magnitudes and paths of typhoons, but were not always evident in the spatiotemporal variability of landscapes in the study area. The statistics and spatial structures of multiple NDVI images were captured by 3,000 samples from 62,500 grids in the NDVI images. Kriging and sequential Gaussian simulation with the 3,000 samples effectively reproduced spatial patterns of NDVI images. However, the proposed approach, which integrates the conditional Latin hypercube sampling approach, variogram, kriging and sequential Gaussian simulation in remotely sensed images, efficiently monitors, samples and maps the effects of large chronological disturbances on spatial characteristics of landscape changes including spatial variability and heterogeneity.
A spatial model to aggregate point-source and nonpoint-source water-quality data for large areas
White, D.A.; Smith, R.A.; Price, C.V.; Alexander, R.B.; Robinson, K.W.
1992-01-01
More objective and consistent methods are needed to assess water quality for large areas. A spatial model, one that capitalizes on the topologic relationships among spatial entities, to aggregate pollution sources from upstream drainage areas is described that can be implemented on land surfaces having heterogeneous water-pollution effects. An infrastructure of stream networks and drainage basins, derived from 1:250,000-scale digital-elevation models, define the hydrologic system in this spatial model. The spatial relationships between point- and nonpoint pollution sources and measurement locations are referenced to the hydrologic infrastructure with the aid of a geographic information system. A maximum-branching algorithm has been developed to simulate the effects of distance from a pollutant source to an arbitrary downstream location, a function traditionally employed in deterministic water quality models. ?? 1992.
NASA Astrophysics Data System (ADS)
Zhu, Yi-Qing; Liang, Wei-Feng; Zhang, Song
2018-01-01
Using multiple-scale mobile gravity data in the Sichuan-Yunnan area, we systematically analyzed the relationships between spatial-temporal gravity changes and the 2014 Ludian, Yunnan Province Ms6.5 earthquake and the 2014 Kangding Ms6.3, 2013 Lushan Ms7.0, and 2008 Wenchuan Ms8.0 earthquakes in Sichuan Province. Our main results are as follows. (1) Before the occurrence of large earthquakes, gravity anomalies occur in a large area around the epicenters. The directions of gravity change gradient belts usually agree roughly with the directions of the main fault zones of the study area. Such gravity changes might reflect the increase of crustal stress, as well as the significant active tectonic movements and surface deformations along fault zones, during the period of gestation of great earthquakes. (2) Continuous significant changes of the multiple-scale gravity fields, as well as greater gravity changes with larger time scales, can be regarded as medium-range precursors of large earthquakes. The subsequent large earthquakes always occur in the area where the gravity changes greatly. (3) The spatial-temporal gravity changes are very useful in determining the epicenter of coming large earthquakes. The large gravity networks are useful to determine the general areas of coming large earthquakes. However, the local gravity networks with high spatial-temporal resolution are suitable for determining the location of epicenters. Therefore, denser gravity observation networks are necessary for better forecasts of the epicenters of large earthquakes. (4) Using gravity changes from mobile observation data, we made medium-range forecasts of the Kangding, Ludian, Lushan, and Wenchuan earthquakes, with especially successful forecasts of the location of their epicenters. Based on the above discussions, we emphasize that medium-/long-term potential for large earthquakes might exist nowadays in some areas with significant gravity anomalies in the study region. Thus, the monitoring should be strengthened.
A spatial age-structured model for describing sea lamprey (Petromyzon marinus) population dynamics
Robinson, Jason M.; Wilberg, Michael J.; Adams, Jean V.; Jones, Michael L.
2013-01-01
The control of invasive sea lampreys (Petromyzon marinus) presents large scale management challenges in the Laurentian Great Lakes. No modeling approach has been developed that describes spatial dynamics of lamprey populations. We developed and validated a spatial and age-structured model and applied it to a sea lamprey population in a large river in the Great Lakes basin. We considered 75 discrete spatial areas, included a stock-recruitment function, spatial recruitment patterns, natural mortality, chemical treatment mortality, and larval metamorphosis. Recruitment was variable, and an upstream shift in recruitment location was observed over time. From 1993–2011 recruitment, larval abundance, and the abundance of metamorphosing individuals decreased by 80, 84, and 86%, respectively. The model successfully identified areas of high larval abundance and showed that areas of low larval density contribute significantly to the population. Estimated treatment mortality was less than expected but had a large population-level impact. The results and general approach of this work have applications for sea lamprey control throughout the Great Lakes and for the restoration and conservation of native lamprey species globally.
Leaf Area Index (LAI) is an important parameter in assessing vegetation structure for characterizing forest canopies over large areas at broad spatial scales using satellite remote sensing data. However, satellite-derived LAI products can be limited by obstructed atmospheric cond...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Xiaoma; Zhou, Yuyu; Asrar, Ghassem R.
Abstract: Urban heat island (UHI), a major concern worldwide, affects human health and energy use. With current and anticipated rapid urbanization, improved understanding of the response of UHI to urbanization is important for impact analysis and developing effective adaptation measures and mitigation strategies. Current studies mainly focus on a single or a few big cities and knowledge on the response of UHI to urbanization for large areas is very limited. Modelling UHI caused by urbanization for large areas that encompass multiple metropolitans remains a major scientific challenge/opportunity. As a major indicator of urbanization, urban area size lends itself well formore » representation in prognostic models to investigate the impacts of urbanization on UHI and the related socioeconomic and environmental effects. However, we have little knowledge on how UHI responds to the increase of urban area size, namely urban expansion, and its spatial and temporal variation over large areas. In this study, we investigated the relationship between surface UHI (SUHI) and urban area size in the climate and ecological context, and its spatial and temporal variations, based on a panel analysis of about 5000 urban areas of 10 km2 or larger, in the conterminous U.S. We found statistically significant positive relationship between SUHI and urban area size, and doubling the urban area size led to a SUHI increase of higher than 0.7 °C. The response of SUHI to the increase of urban area size shows spatial and temporal variations, with stronger SUHI increase in the Northern region of U.S., and during daytime and summer. Urban area size alone can explain as much as 87% of the variance of SUHI among cities studied, but with large spatial and temporal variations. Urban area size shows higher association with SUHI in regions where the thermal characteristics of land cover surrounding the urban are more homogeneous, such as in Eastern U.S., and in the summer months. This study provides a practical approach for large-scale assessment and modeling of the impact of urbanization on SUHI, both spatially and temporally, for developing mitigation/adaptation measures, especially in anticipated warmer climate conditions for the rest of this century.« less
Owen, Sheldon F.; Berl, Jacob L.; Edwards, John W.; Ford, W. Mark; Wood, Petra Bohall
2015-01-01
We studied a raccoon (Procyon lotor) population within a managed central Appalachian hardwood forest in West Virginia to investigate the effects of intensive forest management on raccoon spatial requirements and habitat selection. Raccoon home-range (95% utilization distribution) and core-area (50% utilization distribution) size differed between sexes with males maintaining larger (2×) home ranges and core areas than females. Home-range and core-area size did not differ between seasons for either sex. We used compositional analysis to quantify raccoon selection of six different habitat types at multiple spatial scales. Raccoons selected riparian corridors (riparian management zones [RMZ]) and intact forests (> 70 y old) at the core-area spatial scale. RMZs likely were used by raccoons because they provided abundant denning resources (i.e., large-diameter trees) as well as access to water. Habitat composition associated with raccoon foraging locations indicated selection for intact forests, riparian areas, and regenerating harvest (stands <10 y old). Although raccoons were able to utilize multiple habitat types for foraging resources, a selection of intact forest and RMZs at multiple spatial scales indicates the need of mature forest (with large-diameter trees) for this species in managed forests in the central Appalachians.
Temporal variation in spatial sources of discharge in a large watershed
We examined how the spatial configuration of source areas for runoff varied over time in a watershed contaminated with mercury in order to understand processes governing material loading to rivers. Source areas within the Fox River watershed (Wisconsin, USA) were mapped for indiv...
Modelling the dependence of contrast sensitivity on grating area and spatial frequency.
Rovamo, J; Luntinen, O; Näsänen, R
1993-12-01
We modelled the human foveal visual system in a detection task as a simple image processor comprising (i) low-pass filtering due to the optical transfer function of the eye, (ii) high-pass filtering of neural origin, (iii) addition of internal neural noise, and (iv) detection by a local matched filter. Its detection efficiency for gratings was constant up to a critical area but then decreased with increasing area. To test the model we measured Michelson contrast sensitivity as a function of grating area at spatial frequencies of 0.125-32 c/deg for simple vertical and circular cosine gratings. In circular gratings luminance was sinusoidally modulated as a function of the radius of the grating field. In agreement with the model, contrast sensitivity at all spatial frequencies increased in proportion to the square-root of grating area at small areas. When grating area exceeded critical area, the increase saturated and contrast sensitivity became independent of area at large grating areas. Spatial integration thus obeyed Piper's law at small grating areas. The critical area of spatial integration, marking the cessation of Piper's law, was constant in solid degrees at low spatial frequencies but inversely proportional to spatial frequency squared at medium and high spatial frequencies. At low spatial frequencies the maximum contrast sensitivity obtainable by spatial integration increased in proportion to spatial frequency but at high spatial frequencies it decreased in proportion to the cube of the increasing spatial frequency. The increase was due to high-pass filtering of neural origin (lateral inhibition) and the decrease was mainly due to the optical transfer function of the eye. Our model explained 95% of the total variance of the contrast sensitivity data.
Spatially explicit identification of changes in ecological conditions over large areas is key to targeting and prioritizing areas for environmental protection and restoration by managers at watershed, basin, and regional scales. A critical limitation to this point has been the d...
Emission measurements from large area sources such as landfills are complicated by their spatial extent and heterogeneous nature. In recent years, an on-site optical remote sensing (ORS) technique for characterizing emissions from area sources was described in an EPA-published p...
Estimating the Spatial Extent of Unsaturated Zones in Heterogeneous River-Aquifer Systems
NASA Astrophysics Data System (ADS)
Schilling, Oliver S.; Irvine, Dylan J.; Hendricks Franssen, Harrie-Jan; Brunner, Philip
2017-12-01
The presence of unsaturated zones at the river-aquifer interface has large implications on numerous hydraulic and chemical processes. However, the hydrological and geological controls that influence the development of unsaturated zones have so far only been analyzed with simplified conceptualizations of flow processes, or homogeneous conceptualizations of the hydraulic conductivity in either the aquifer or the riverbed. We systematically investigated the influence of heterogeneous structures in both the riverbed and the aquifer on the development of unsaturated zones. A stochastic 1-D criterion that takes both riverbed and aquifer heterogeneity into account was developed using a Monte Carlo sampling technique. The approach allows the reliable estimation of the upper bound of the spatial extent of unsaturated areas underneath a riverbed. Through systematic numerical modeling experiments, we furthermore show that horizontal capillary forces can reduce the spatial extent of unsaturated zones under clogged areas. This analysis shows how the spatial structure of clogging layers and aquifers influence the propensity for unsaturated zones to develop: In riverbeds where clogged areas are made up of many small, spatially disconnected patches with a diameter in the order of 1 m, unsaturated areas are less likely to develop compared to riverbeds where large clogged areas exist adjacent to unclogged areas. A combination of the stochastic 1-D criterion with an analysis of the spatial structure of the clogging layers and the potential for resaturation can help develop an appropriate conceptual model and inform the choice of a suitable numerical simulator for river-aquifer systems.
Application of the automated spatial surveillance program to birth defects surveillance data.
Gardner, Bennett R; Strickland, Matthew J; Correa, Adolfo
2007-07-01
Although many birth defects surveillance programs incorporate georeferenced records into their databases, practical methods for routine spatial surveillance are lacking. We present a macroprogram written for the software package R designed for routine exploratory spatial analysis of birth defects data, the Automated Spatial Surveillance Program (ASSP), and present an application of this program using spina bifida prevalence data for metropolitan Atlanta. Birth defects surveillance data were collected by the Metropolitan Atlanta Congenital Defects Program. We generated ASSP maps for two groups of years that correspond roughly to the periods before (1994-1998) and after (1999-2002) folic acid fortification of flour. ASSP maps display census tract-specific spina bifida prevalence, smoothed prevalence contours, and locations of statistically elevated prevalence. We used these maps to identify areas of elevated prevalence for spina bifida. We identified a large area of potential concern in the years following fortification of grains and cereals with folic acid. This area overlapped census tracts containing large numbers of Hispanic residents. The potential utility of ASSP for spatial disease monitoring was demonstrated by the identification of areas of high prevalence of spina bifida and may warrant further study and monitoring. We intend to further develop ASSP so that it becomes practical for routine spatial monitoring of birth defects. (c) 2007 Wiley-Liss, Inc.
Spectral Radiance of a Large-Area Integrating Sphere Source
Walker, James H.; Thompson, Ambler
1995-01-01
The radiance and irradiance calibration of large field-of-view scanning and imaging radiometers for remote sensing and surveillance applications has resulted in the development of novel calibration techniques. One of these techniques is the employment of large-area integrating sphere sources as radiance or irradiance secondary standards. To assist the National Aeronautical and Space Administration’s space based ozone measurement program, a commercially available large-area internally illuminated integrating sphere source’s spectral radiance was characterized in the wavelength region from 230 nm to 400 nm at the National Institute of Standards and Technology. Spectral radiance determinations and spatial mappings of the source indicate that carefully designed large-area integrating sphere sources can be measured with a 1 % to 2 % expanded uncertainty (two standard deviation estimate) in the near ultraviolet with spatial nonuniformities of 0.6 % or smaller across a 20 cm diameter exit aperture. A method is proposed for the calculation of the final radiance uncertainties of the source which includes the field of view of the instrument being calibrated. PMID:29151725
A compact large-format streak tube for imaging lidar
NASA Astrophysics Data System (ADS)
Hui, Dandan; Luo, Duan; Tian, Liping; Lu, Yu; Chen, Ping; Wang, Junfeng; Sai, Xiaofeng; Wen, Wenlong; Wang, Xing; Xin, Liwei; Zhao, Wei; Tian, Jinshou
2018-04-01
The streak tubes with a large effective photocathode area, large effective phosphor screen area, and high photocathode radiant sensitivity are essential for improving the field of view, depth of field, and detectable range of the multiple-slit streak tube imaging lidar. In this paper, a high spatial resolution, large photocathode area, and compact meshless streak tube with a spherically curved cathode and screen is designed and tested. Its spatial resolution reaches 20 lp/mm over the entire Φ28 mm photocathode working area, and the simulated physical temporal resolution is better than 30 ps. The temporal distortion in our large-format streak tube, which is shown to be a non-negligible factor, has a minimum value as the radius of curvature of the photocathode varies. Furthermore, the photocathode radiant sensitivity and radiant power gain reach 41 mA/W and 18.4 at the wavelength of 550 nm, respectively. Most importantly, the external dimensions of our streak tube are no more than Φ60 mm × 110 mm.
Fernández-Guisuraga, José Manuel; Sanz-Ablanedo, Enoc; Suárez-Seoane, Susana; Calvo, Leonor
2018-02-14
This study evaluated the opportunities and challenges of using drones to obtain multispectral orthomosaics at ultra-high resolution that could be useful for monitoring large and heterogeneous burned areas. We conducted a survey using an octocopter equipped with a Parrot SEQUOIA multispectral camera in a 3000 ha framework located within the perimeter of a megafire in Spain. We assessed the quality of both the camera raw imagery and the multispectral orthomosaic obtained, as well as the required processing capability. Additionally, we compared the spatial information provided by the drone orthomosaic at ultra-high spatial resolution with another image provided by the WorldView-2 satellite at high spatial resolution. The drone raw imagery presented some anomalies, such as horizontal banding noise and non-homogeneous radiometry. Camera locations showed a lack of synchrony of the single frequency GPS receiver. The georeferencing process based on ground control points achieved an error lower than 30 cm in X-Y and lower than 55 cm in Z. The drone orthomosaic provided more information in terms of spatial variability in heterogeneous burned areas in comparison with the WorldView-2 satellite imagery. The drone orthomosaic could constitute a viable alternative for the evaluation of post-fire vegetation regeneration in large and heterogeneous burned areas.
2018-01-01
This study evaluated the opportunities and challenges of using drones to obtain multispectral orthomosaics at ultra-high resolution that could be useful for monitoring large and heterogeneous burned areas. We conducted a survey using an octocopter equipped with a Parrot SEQUOIA multispectral camera in a 3000 ha framework located within the perimeter of a megafire in Spain. We assessed the quality of both the camera raw imagery and the multispectral orthomosaic obtained, as well as the required processing capability. Additionally, we compared the spatial information provided by the drone orthomosaic at ultra-high spatial resolution with another image provided by the WorldView-2 satellite at high spatial resolution. The drone raw imagery presented some anomalies, such as horizontal banding noise and non-homogeneous radiometry. Camera locations showed a lack of synchrony of the single frequency GPS receiver. The georeferencing process based on ground control points achieved an error lower than 30 cm in X-Y and lower than 55 cm in Z. The drone orthomosaic provided more information in terms of spatial variability in heterogeneous burned areas in comparison with the WorldView-2 satellite imagery. The drone orthomosaic could constitute a viable alternative for the evaluation of post-fire vegetation regeneration in large and heterogeneous burned areas. PMID:29443914
Coherence area profiling in multi-spatial-mode squeezed states
Lawrie, Benjamin J.; Pooser, Raphael C.; Otterstrom, Nils T.
2015-09-12
The presence of multiple bipartite entangled modes in squeezed states generated by four-wave mixing enables ultra-trace sensing, imaging, and metrology applications that are impossible to achieve with single-spatial-mode squeezed states. For Gaussian seed beams, the spatial distribution of these bipartite entangled modes, or coherence areas, across each beam is largely dependent on the spatial modes present in the pump beam, but it has proven difficult to map the distribution of these coherence areas in frequency and space. We demonstrate an accessible method to map the distribution of the coherence areas within these twin beams. In addition, we also show thatmore » the pump shape can impart different noise properties to each coherence area, and that it is possible to select and detect coherence areas with optimal squeezing with this approach.« less
Modeling streams and hydrogeomorphic attributes in Oregon from digital and field data
Sharon E. Clarke; Kelly M. Burnett; Daniel J. Miller
2008-01-01
Managers, regulators, and researchers of aquatic ecosystems are increasingly pressed to consider large areas. However, accurate stream maps with geo-referenced attributes are uncommon over relevant spatial extents. Field inventories provide high-quality data, particularly for habitat characteristics at fine spatial resolutions (e.g., large wood), but are costly and so...
Large-area forest inventory regression modeling: spatial scale considerations
James A. Westfall
2015-01-01
In many forest inventories, statistical models are employed to predict values for attributes that are difficult and/or time-consuming to measure. In some applications, models are applied across a large geographic area, which assumes the relationship between the response variable and predictors is ubiquitously invariable within the area. The extent to which this...
Data Representations for Geographic Information Systems.
ERIC Educational Resources Information Center
Shaffer, Clifford A.
1992-01-01
Surveys the field and literature of geographic information systems (GIS) and spatial data representation as it relates to GIS. Highlights include GIS terms, data types, and operations; vector representations and raster, or grid, representations; spatial indexing; elevation data representations; large spatial databases; and problem areas and future…
Regional forest land cover characterisation using medium spatial resolution satellite data
Huang, Chengquan; Homer, Collin G.; Yang, Limin; Wulder, Michael A.; Franklin, Steven E.
2003-01-01
Increasing demands on forest resources require comprehensive, consistent and up-to-date information on those resources at spatial scales appropriate for management decision-making and for scientific analysis. While such information can be derived using coarse spatial resolution satellite data (e.g. Tucker et al. 1984; Zhu and Evans 1994; Cihlar et al. 1996; Cihlar et al., Chapter 12), many regional applications require more spatial and thematic details than can be derived by using coarse resolution imagery. High spatial resolution satellite data such as IKONOS and Quick Bird images (Aplin et al. 1997), though usable for deriving detailed forest information (Culvenor, Chapter 9), are currently not feasible for wall-to-wall regional applications because of extremely high data cost, huge data volume, and lack of contiguous coverage over large areas. Forest studies over large areas have often been accomplished using data acquired by intermediate spatial resolution sensor systems, including the Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and the Enhanced Thematic Mapper Plus (ETM+) of Landsat, the High Resolution Visible (HRV) of the Systeme Pour l'Observation de la Terre (SPOT), and the Linear Image Self-Scanner (LISS) of the Indian Remote Sensing satellite. These sensor systems are more appropriate for regional applications because they can routinely produce spatially contiguous data over large areas at relatively low cost, and can be used to derive a host of forest attributes (e.g. Cohen et al. 1995; Kimes et al. 1999; Cohen et al. 2001; Huang et al. 2001; Sugumaran 2001). Of the above intermediate spatial resolution satellites, Landsat is perhaps the most widely used in various types of land remote sensing applications, in part because it has provided more extensive spatial and temporal coverage of the globe than any other intermediate resolution satellite. Spatially contiguous Landsat data have been developed for many regions of the globe (e.g. Lunetta and Sturdevant 1993; Fuller et al. 1994b; Skole et al. 1997), and a circa 1990 Landsat image data set covering the entire land area of the globe has also been developed recently (Jones and Smith 2001). An acquisition strategy aimed at acquiring at least one cloud free image per year for the entire land area of the globe has been initiated for Landsat-7 (Arvidson et al. 2001). This will probably ensure the continued dominance of Landsat in the near future.
Remote sensing of exposure to NO2: Satellite versus ground-based measurement in a large urban area
NASA Astrophysics Data System (ADS)
Bechle, Matthew J.; Millet, Dylan B.; Marshall, Julian D.
2013-04-01
Remote sensing may be a useful tool for exploring spatial variability of air pollution exposure within an urban area. To evaluate the extent to which satellite data from the Ozone Monitoring Instrument (OMI) can resolve urban-scale gradients in ground-level nitrogen dioxide (NO2) within a large urban area, we compared estimates of surface NO2 concentrations derived from OMI measurements and US EPA ambient monitoring stations. OMI, aboard NASA's Aura satellite, provides daily afternoon (˜13:30 local time) measurements of NO2 tropospheric column abundance. We used scaling factors (surface-to-column ratios) to relate satellite column measurements to ground-level concentrations. We compared 4138 sets of paired data for 25 monitoring stations in the South Coast Air Basin of California for all of 2005. OMI measurements include more data gaps than the ground monitors (60% versus 5% of available data, respectively), owing to cloud contamination and imposed limits on pixel size. The spatial correlation between OMI columns and corrected in situ measurements is strong (r = 0.93 for annual average data), indicating that the within-urban spatial signature of surface NO2 is well resolved by the satellite sensor. Satellite-based surface estimates employing scaling factors from an urban model provide a reliable measure (annual mean bias: -13%; seasonal mean bias: <1% [spring] to -22% [fall]) of fine-scale surface NO2. We also find that OMI provides good spatial density in the study region (average area [km2] per measurement: 730 for the satellite sensor vs. 1100 for the monitors). Our findings indicate that satellite observations of NO2 from the OMI sensor provide a reliable measure of spatial variability in ground-level NO2 exposure for a large urban area.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Adams, B.W.; et al.
The Large Area Picosecond PhotoDetector (LAPPD) Collaboration was formed in 2009 to develop large-area photodetectors capable of time resolutions measured in pico-seconds, with accompanying sub-millimeter spatial resolution. During the next three and one-half years the Collaboration developed the LAPPD design of 20 x 20 cm modules with gains greater thanmore » $10^7$ and non-uniformity less than $$15\\%$$, time resolution less than 50 psec for single photons and spatial resolution of 700~microns in both lateral dimensions. We describe the R\\&D performed to develop large-area micro-channel plate glass substrates, resistive and secondary-emitting coatings, large-area bialkali photocathodes, and RF-capable hermetic packaging. In addition, the Collaboration developed the necessary electronics for large systems capable of precise timing, built up from a custom low-power 15-GigaSample/sec waveform sampling 6-channel integrated circuit and supported by a two-level modular data acquisition system based on Field-Programmable Gate Arrays for local control, data-sparcification, and triggering. We discuss the formation, organization, and technical successes and short-comings of the Collaboration. The Collaboration ended in December 2012 with a transition from R\\&D to commercialization.« less
NASA Astrophysics Data System (ADS)
Ramsdale, Jason D.; Balme, Matthew R.; Conway, Susan J.; Gallagher, Colman; van Gasselt, Stephan A.; Hauber, Ernst; Orgel, Csilla; Séjourné, Antoine; Skinner, James A.; Costard, Francois; Johnsson, Andreas; Losiak, Anna; Reiss, Dennis; Swirad, Zuzanna M.; Kereszturi, Akos; Smith, Isaac B.; Platz, Thomas
2017-06-01
The increased volume, spatial resolution, and areal coverage of high-resolution images of Mars over the past 15 years have led to an increased quantity and variety of small-scale landform identifications. Though many such landforms are too small to represent individually on regional-scale maps, determining their presence or absence across large areas helps form the observational basis for developing hypotheses on the geological nature and environmental history of a study area. The combination of improved spatial resolution and near-continuous coverage significantly increases the time required to analyse the data. This becomes problematic when attempting regional or global-scale studies of metre and decametre-scale landforms. Here, we describe an approach for mapping small features (from decimetre to kilometre scale) across large areas, formulated for a project to study the northern plains of Mars, and provide context on how this method was developed and how it can be implemented. Rather than ;mapping; with points and polygons, grid-based mapping uses a ;tick box; approach to efficiently record the locations of specific landforms (we use an example suite of glacial landforms; including viscous flow features, the latitude dependant mantle and polygonised ground). A grid of squares (e.g. 20 km by 20 km) is created over the mapping area. Then the basemap data are systematically examined, grid-square by grid-square at full resolution, in order to identify the landforms while recording the presence or absence of selected landforms in each grid-square to determine spatial distributions. The result is a series of grids recording the distribution of all the mapped landforms across the study area. In some ways, these are equivalent to raster images, as they show a continuous distribution-field of the various landforms across a defined (rectangular, in most cases) area. When overlain on context maps, these form a coarse, digital landform map. We find that grid-based mapping provides an efficient solution to the problems of mapping small landforms over large areas, by providing a consistent and standardised approach to spatial data collection. The simplicity of the grid-based mapping approach makes it extremely scalable and workable for group efforts, requiring minimal user experience and producing consistent and repeatable results. The discrete nature of the datasets, simplicity of approach, and divisibility of tasks, open up the possibility for citizen science in which crowdsourcing large grid-based mapping areas could be applied.
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.
NASA Astrophysics Data System (ADS)
Gui, Jianbao; Guo, Jinchuan; Yang, Qinlao; Liu, Xin; Niu, Hanben
2007-05-01
X-ray phase contrast imaging is a promising new technology today, but the requirements of a digital detector with large area, high spatial resolution and high sensitivity bring forward a large challenge to researchers. This paper is related to the design and theoretical investigation of an x-ray direct conversion digital detector based on mercuric iodide photoconductive layer with the latent charge image readout by photoinduced discharge (PID). Mercuric iodide has been verified having a good imaging performance (high sensitivity, low dark current, low voltage operation and good lag characteristics) compared with the other competitive materials (α-Se,PbI II,CdTe,CdZnTe) and can be easily deposited on large substrates in the manner of polycrystalline. By use of line scanning laser beam and parallel multi-electrode readout make the system have high spatial resolution and fast readout speed suitable for instant general radiography and even rapid sequence radiography.
Clark's nutcracker spatial memory: the importance of large, structural cues.
Bednekoff, Peter A; Balda, Russell P
2014-02-01
Clark's nutcrackers, Nucifraga columbiana, cache and recover stored seeds in high alpine areas including areas where snowfall, wind, and rockslides may frequently obscure or alter cues near the cache site. Previous work in the laboratory has established that Clark's nutcrackers use spatial memory to relocate cached food. Following from aspects of this work, we performed experiments to test the importance of large, structural cues for Clark's nutcracker spatial memory. Birds were no more accurate in recovering caches when more objects were on the floor of a large experimental room nor when this room was subdivided with a set of panels. However, nutcrackers were consistently less accurate in this large room than in a small experimental room. Clark's nutcrackers probably use structural features of experimental rooms as important landmarks during recovery of cached food. This use of large, extremely stable cues may reflect the imperfect reliability of smaller, closer cues in the natural habitat of Clark's nutcrackers. This article is part of a Special Issue entitled: CO3 2013. Copyright © 2013 Elsevier B.V. All rights reserved.
Jones, K.B.; Neale, A.C.; Wade, T.G.; Wickham, J.D.; Cross, C.L.; Edmonds, C.M.; Loveland, Thomas R.; Nash, M.S.; Riitters, K.H.; Smith, E.R.
2001-01-01
Spatially explicit identification of changes in ecological conditions over large areas is key to targeting and prioritizing areas for environmental protection and restoration by managers at watershed, basin, and regional scales. A critical limitation to this point has been the development of methods to conduct such broad-scale assessments. Field-based methods have proven to be too costly and too inconsistent in their application to make estimates of ecological conditions over large areas. New spatial data derived from satellite imagery and other sources, the development of statistical models relating landscape composition and pattern to ecological endpoints, and geographic information systems (GIS) make it possible to evaluate ecological conditions at multiple scales over broad geographic regions. In this study, we demonstrate the application of spatially distributed models for bird habitat quality and nitrogen yield to streams to assess the consequences of landcover change across the mid-Atlantic region between the 1970s and 1990s. Moreover, we present a way to evaluate spatial concordance between models related to different environmental endpoints. Results of this study should help environmental managers in the mid-Atlantic region target those areas in need of conservation and protection.
An invariability-area relationship sheds new light on the spatial scaling of ecological stability.
Wang, Shaopeng; Loreau, Michel; Arnoldi, Jean-Francois; Fang, Jingyun; Rahman, K Abd; Tao, Shengli; de Mazancourt, Claire
2017-05-19
The spatial scaling of stability is key to understanding ecological sustainability across scales and the sensitivity of ecosystems to habitat destruction. Here we propose the invariability-area relationship (IAR) as a novel approach to investigate the spatial scaling of stability. The shape and slope of IAR are largely determined by patterns of spatial synchrony across scales. When synchrony decays exponentially with distance, IARs exhibit three phases, characterized by steeper increases in invariability at both small and large scales. Such triphasic IARs are observed for primary productivity from plot to continental scales. When synchrony decays as a power law with distance, IARs are quasilinear on a log-log scale. Such quasilinear IARs are observed for North American bird biomass at both species and community levels. The IAR provides a quantitative tool to predict the effects of habitat loss on population and ecosystem stability and to detect regime shifts in spatial ecological systems, which are goals of relevance to conservation and policy.
Spatial Representativeness of PM2.5 Concentrations Obtained Using Observations From Network Stations
NASA Astrophysics Data System (ADS)
Shi, Xiaoqin; Zhao, Chuanfeng; Jiang, Jonathan H.; Wang, Chunying; Yang, Xin; Yung, Yuk L.
2018-03-01
Haze has been a focused air pollution phenomenon in China, and its characterization is highly desired. Aerosol properties obtained from a single station are frequently used to represent the haze condition over a large domain, such as tens of kilometers, which could result in high uncertainties due to their spatial variation. Using a high-resolution network observation over an urban city in North China from November 2015 to February 2016, this study examines the spatial representativeness of ground station observations of particulate matter with diameters less than 2.5 μm (PM2.5). We developed a new method to determine the representative area of PM2.5 measurements from limited stations. The key idea is to determine the PM2.5 spatial representative area using its spatial variability and temporal correlation. We also determine stations with large representative area using two grid networks with different resolutions. Based on the high spatial resolution measurements, the representative area of PM2.5 at one station can be determined from the grids with high correlations and small differences of PM2.5. The representative area for a single station in the study period ranges from 0.25 to 16.25 km2 but is less than 3 km2 for more than half of the stations. The representative area varies with locations, and observation at 10 optimal stations would have a good representativeness of those obtained from 169 stations for the 4 month time scale studied. Both evaluations with an empirical orthogonal function analysis and with independent data set corroborate the validity of the results found in this study.
Gray, B.R.; Shi, W.; Houser, J.N.; Rogala, J.T.; Guan, Z.; Cochran-Biederman, J. L.
2011-01-01
Ecological restoration efforts in large rivers generally aim to ameliorate ecological effects associated with large-scale modification of those rivers. This study examined whether the effects of restoration efforts-specifically those of island construction-within a largely open water restoration area of the Upper Mississippi River (UMR) might be seen at the spatial scale of that 3476ha area. The cumulative effects of island construction, when observed over multiple years, were postulated to have made the restoration area increasingly similar to a positive reference area (a proximate area comprising contiguous backwater areas) and increasingly different from two negative reference areas. The negative reference areas represented the Mississippi River main channel in an area proximate to the restoration area and an open water area in a related Mississippi River reach that has seen relatively little restoration effort. Inferences on the effects of restoration were made by comparing constrained and unconstrained models of summer chlorophyll a (CHL), summer inorganic suspended solids (ISS) and counts of benthic mayfly larvae. Constrained models forced trends in means or in both means and sampling variances to become, over time, increasingly similar to those in the positive reference area and increasingly dissimilar to those in the negative reference areas. Trends were estimated over 12- (mayflies) or 14-year sampling periods, and were evaluated using model information criteria. Based on these methods, restoration effects were observed for CHL and mayflies while evidence in favour of restoration effects on ISS was equivocal. These findings suggest that the cumulative effects of island building at relatively large spatial scales within large rivers may be estimated using data from large-scale surveillance monitoring programs. Published in 2010 by John Wiley & Sons, Ltd.
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
Valle, Denis; Lima, Joanna M Tucker
2014-11-20
Most of the malaria burden in the Americas is concentrated in the Brazilian Amazon but a detailed spatial characterization of malaria risk has yet to be undertaken. Utilizing 2004-2008 malaria incidence data collected from six Brazilian Amazon states, large-scale spatial patterns of malaria risk were characterized with a novel Bayesian multi-pathogen geospatial model. Data included 2.4 million malaria cases spread across 3.6 million sq km. Remotely sensed variables (deforestation rate, forest cover, rainfall, dry season length, and proximity to large water bodies), socio-economic variables (rural population size, income, and literacy rate, mortality rate for children age under five, and migration patterns), and GIS variables (proximity to roads, hydro-electric dams and gold mining operations) were incorporated as covariates. Borrowing information across pathogens allowed for better spatial predictions of malaria caused by Plasmodium falciparum, as evidenced by a ten-fold cross-validation. Malaria incidence for both Plasmodium vivax and P. falciparum tended to be higher in areas with greater forest cover. Proximity to gold mining operations was another important risk factor, corroborated by a positive association between migration rates and malaria incidence. Finally, areas with a longer dry season and areas with higher average rural income tended to have higher malaria risk. Risk maps reveal striking spatial heterogeneity in malaria risk across the region, yet these mean disease risk surface maps can be misleading if uncertainty is ignored. By combining mean spatial predictions with their associated uncertainty, several sites were consistently classified as hotspots, suggesting their importance as priority areas for malaria prevention and control. This article provides several contributions. From a methodological perspective, the benefits of jointly modelling multiple pathogens for spatial predictions were illustrated. In addition, maps of mean disease risk were contrasted with that of statistically significant disease clusters, highlighting the critical importance of uncertainty in determining disease hotspots. From an epidemiological perspective, forest cover and proximity to gold mining operations were important large-scale drivers of disease risk in the region. Finally, the hotspot in Western Acre was identified as the area that should receive highest priority from the Brazilian national malaria prevention and control programme.
Spatial pattern of risk of common raven predation on desert tortoises
Kristan, W. B.; Boarman, W.I.
2003-01-01
Common Ravens (Corvus corax) in the Mojave Desert of California, USA are subsidized by anthropogenic resources. Large numbers of nonbreeding ravens are attracted to human developments and thus are spatially restricted, whereas breeding ravens are distributed more evenly throughout the area. We investigated whether the spatial distribution of risk of predation by ravens to juveniles of the threatened desert tortoise (Gopherus agassizii) was determined by the spatial distribution of (1) nonbreeding ravens at human developments (leading to "spillover" predation) or (2) breeding individuals throughout developed and undeveloped areas (leading to " hyperpredation"). Predation risk, measured using styrofoam models of juvenile desert tortoises, was high near places attracting large numbers of nonbreeding ravens, near successful nests, and far from successful nests when large numbers of nonbreeding ravens were present. Patterns consistent with both "spillover" predation and "hyperpredation" were thus observed, attributed to the nonbreeding and breeding segments of the population, respectively. Furthermore, because locations of successful nests changed almost annually, consistent low-predation refugia for juvenile desert tortoises were nearly nonexistent. Consequently, anthropogenic resources for ravens could indirectly lead to the suppression, decline, or even extinction of desert tortoise populations.
NASA Astrophysics Data System (ADS)
Stumpf, Felix; Goebes, Philipp; Schmidt, Karsten; Schindewolf, Marcus; Schönbrodt-Stitt, Sarah; Wadoux, Alexandre; Xiang, Wei; Scholten, Thomas
2017-04-01
Soil erosion by water outlines a major threat to the Three Gorges Reservoir Area in China. A detailed assessment of soil conservation measures requires a tool that spatially identifies sediment reallocations due to rainfall-runoff events in catchments. We applied EROSION 3D as a physically based soil erosion and deposition model in a small mountainous catchment. Generally, we aim to provide a methodological frame that facilitates the model parametrization in a data scarce environment and to identify sediment sources and deposits. We used digital soil mapping techniques to generate spatially distributed soil property information for parametrization. For model calibration and validation, we continuously monitored the catchment on rainfall, runoff and sediment yield for a period of 12 months. The model performed well for large events (sediment yield>1 Mg) with an averaged individual model error of 7.5%, while small events showed an average error of 36.2%. We focused on the large events to evaluate reallocation patterns. Erosion occurred in 11.1% of the study area with an average erosion rate of 49.9Mgha 1. Erosion mainly occurred on crop rotation areas with a spatial proportion of 69.2% for 'corn-rapeseed' and 69.1% for 'potato-cabbage'. Deposition occurred on 11.0%. Forested areas (9.7%), infrastructure (41.0%), cropland (corn-rapeseed: 13.6%, potatocabbage: 11.3%) and grassland (18.4%) were affected by deposition. Because the vast majority of annual sediment yields (80.3%) were associated to a few large erosive events, the modelling approach provides a useful tool to spatially assess soil erosion control and conservation measures.
The Importance of Large-Diameter Trees to Forest Structural Heterogeneity
Lutz, James A.; Larson, Andrew J.; Freund, James A.; Swanson, Mark E.; Bible, Kenneth J.
2013-01-01
Large-diameter trees dominate the structure, dynamics and function of many temperate and tropical forests. However, their attendant contributions to forest heterogeneity are rarely addressed. We established the Wind River Forest Dynamics Plot, a 25.6 ha permanent plot within which we tagged and mapped all 30,973 woody stems ≥1 cm dbh, all 1,966 snags ≥10 cm dbh, and all shrub patches ≥2 m2. Basal area of the 26 woody species was 62.18 m2/ha, of which 61.60 m2/ha was trees and 0.58 m2/ha was tall shrubs. Large-diameter trees (≥100 cm dbh) comprised 1.5% of stems, 31.8% of basal area, and 17.6% of the heterogeneity of basal area, with basal area dominated by Tsuga heterophylla and Pseudotsuga menziesii. Small-diameter subpopulations of Pseudotsuga menziesii, Tsuga heterophylla and Thuja plicata, as well as all tree species combined, exhibited significant aggregation relative to the null model of complete spatial randomness (CSR) up to 9 m (P≤0.001). Patterns of large-diameter trees were either not different from CSR (Tsuga heterophylla), or exhibited slight aggregation (Pseudotsuga menziesii and Thuja plicata). Significant spatial repulsion between large-diameter and small-diameter Tsuga heterophylla suggests that large-diameter Tsuga heterophylla function as organizers of tree demography over decadal timescales through competitive interactions. Comparison among two forest dynamics plots suggests that forest structural diversity responds to intermediate-scale environmental heterogeneity and disturbances, similar to hypotheses about patterns of species richness, and richness- ecosystem function. Large mapped plots with detailed within-plot environmental spatial covariates will be required to test these hypotheses. PMID:24376579
The importance of large-diameter trees to forest structural heterogeneity.
Lutz, James A; Larson, Andrew J; Freund, James A; Swanson, Mark E; Bible, Kenneth J
2013-01-01
Large-diameter trees dominate the structure, dynamics and function of many temperate and tropical forests. However, their attendant contributions to forest heterogeneity are rarely addressed. We established the Wind River Forest Dynamics Plot, a 25.6 ha permanent plot within which we tagged and mapped all 30,973 woody stems ≥ 1 cm dbh, all 1,966 snags ≥ 10 cm dbh, and all shrub patches ≥ 2 m(2). Basal area of the 26 woody species was 62.18 m(2)/ha, of which 61.60 m(2)/ha was trees and 0.58 m(2)/ha was tall shrubs. Large-diameter trees (≥ 100 cm dbh) comprised 1.5% of stems, 31.8% of basal area, and 17.6% of the heterogeneity of basal area, with basal area dominated by Tsuga heterophylla and Pseudotsuga menziesii. Small-diameter subpopulations of Pseudotsuga menziesii, Tsuga heterophylla and Thuja plicata, as well as all tree species combined, exhibited significant aggregation relative to the null model of complete spatial randomness (CSR) up to 9 m (P ≤ 0.001). Patterns of large-diameter trees were either not different from CSR (Tsuga heterophylla), or exhibited slight aggregation (Pseudotsuga menziesii and Thuja plicata). Significant spatial repulsion between large-diameter and small-diameter Tsuga heterophylla suggests that large-diameter Tsuga heterophylla function as organizers of tree demography over decadal timescales through competitive interactions. Comparison among two forest dynamics plots suggests that forest structural diversity responds to intermediate-scale environmental heterogeneity and disturbances, similar to hypotheses about patterns of species richness, and richness- ecosystem function. Large mapped plots with detailed within-plot environmental spatial covariates will be required to test these hypotheses.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Moriarty, Tom
The NREL cell measurement lab measures the IV parameters of cells of multiple sizes and configurations. A large contributing factor to errors and uncertainty in Jsc, Imax, Pmax and efficiency can be the irradiance spatial nonuniformity. Correcting for this nonuniformity through its precise and frequent measurement can be very time consuming. This paper explains a simple, fast and effective method based on bicubic interpolation for determining and correcting for spatial nonuniformity and verification of the method's efficacy.
Shafer, Sarah L; Bartlein, Patrick J; Gray, Elizabeth M; Pelltier, Richard T
2015-01-01
Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0-58.0°N latitude by 136.6-103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070-2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.
NASA Astrophysics Data System (ADS)
Bayrak, Erdem; Yılmaz, Şeyda; Bayrak, Yusuf
2017-05-01
The temporal and spatial variations of Gutenberg-Richter parameter (b-value) and fractal dimension (DC) during the period 1900-2010 in Western Anatolia was investigated. The study area is divided into 15 different source zones based on their tectonic and seismotectonic regimes. We calculated the temporal variation of b and DC values in each region using Zmap. The temporal variation of these parameters for the prediction of major earthquakes was calculated. The spatial distribution of these parameters is related to the stress levels of the faults. We observed that b and DC values change before the major earthquakes in the 15 seismic regions. To evaluate the spatial distribution of b and DC values, 0.50° × 0.50° grid interval were used. The b-values smaller than 0.70 are related to the Aegean Arc and Eskisehir Fault. The highest values are related to Sultandağı and Sandıklı Faults. Fractal correlation dimension varies from 1.65 to 2.60, which shows that the study area has a higher DC value. The lowest DC values are related to the joining area between Aegean and Cyprus arcs, Burdur-Fethiye fault zone. Some have concluded that b-values drop instantly before large shocks. Others suggested that temporally stable low b value zones identify future large earthquake locations. The results reveal that large earthquakes occur when b decreases and DC increases, suggesting that variation of b and DC can be used as an earthquake precursor. Mapping of b and DC values provide information about the state of stress in the region, i.e. lower b and higher DC values associated with epicentral areas of large earthquakes.
Maruyama, Toshisuke
2007-01-01
To estimate the amount of evapotranspiration in a river basin, the “short period water balance method” was formulated. Then, by introducing the “complementary relationship method,” the amount of evapotranspiration was estimated seasonally, and with reasonable accuracy, for both small and large areas. Moreover, to accurately estimate river discharge in the low water season, the “weighted statistical unit hydrograph method” was proposed and a procedure for the calculation of the unit hydrograph was developed. Also, a new model, based on the “equivalent roughness method,” was successfully developed for the estimation of flood runoff from newly reclaimed farmlands. Based on the results of this research, a “composite reservoir model” was formulated to analyze the repeated use of irrigation water in large spatial areas. The application of this model to a number of watershed areas provided useful information with regard to the realities of water demand-supply systems in watersheds predominately dedicated to paddy fields, in Japan. PMID:24367144
Coincident scales of forest feedback on climate and conservation in a diversity hot spot
Webb, Thomas J; Gaston, Kevin J; Hannah, Lee; Ian Woodward, F
2005-01-01
The dynamic relationship between vegetation and climate is now widely acknowledged. Climate influences the distribution of vegetation; and through a number of feedback mechanisms vegetation affects climate. This implies that land-use changes such as deforestation will have climatic consequences. However, the spatial scales at which such feedbacks occur remain largely unknown. Here, we use a large database of precipitation and tree cover records for an area of the biodiversity-rich Atlantic forest region in south eastern Brazil to investigate the forest–rainfall feedback at a range of spatial scales from ca 101–104 km2. We show that the strength of the feedback increases up to scales of at least 103 km2, with the climate at a particular locality influenced by the pattern of landcover extending over a large area. Thus, smaller forest fragments, even if well protected, may suffer degradation due to the climate responding to land-use change in the surrounding area. Atlantic forest vertebrate taxa also require large areas of forest to support viable populations. Areas of forest of ca 103 km2 would be large enough to support such populations at the same time as minimizing the risk of climatic feedbacks resulting from deforestation. PMID:16608697
Coincident scales of forest feedback on climate and conservation in a diversity hot spot.
Webb, Thomas J; Gaston, Kevin J; Hannah, Lee; Ian Woodward, F
2006-03-22
The dynamic relationship between vegetation and climate is now widely acknowledged. Climate influences the distribution of vegetation; and through a number of feedback mechanisms vegetation affects climate. This implies that land-use changes such as deforestation will have climatic consequences. However, the spatial scales at which such feedbacks occur remain largely unknown. Here, we use a large database of precipitation and tree cover records for an area of the biodiversity-rich Atlantic forest region in south eastern Brazil to investigate the forest-rainfall feedback at a range of spatial scales from ca 10(1)-10(4) km2. We show that the strength of the feedback increases up to scales of at least 10(3) km2, with the climate at a particular locality influenced by the pattern of landcover extending over a large area. Thus, smaller forest fragments, even if well protected, may suffer degradation due to the climate responding to land-use change in the surrounding area. Atlantic forest vertebrate taxa also require large areas of forest to support viable populations. Areas of forest of ca 10(3) km2 would be large enough to support such populations at the same time as minimizing the risk of climatic feedbacks resulting from deforestation.
NASA Astrophysics Data System (ADS)
Deo, R. K.; Domke, G. M.; Russell, M.; Woodall, C. W.
2017-12-01
Landsat data have been widely used to support strategic forest inventory and management decisions despite the limited success of passive optical remote sensing for accurate estimation of aboveground biomass (AGB). The archive of publicly available Landsat data, available at 30-m spatial resolutions since 1984, has been a valuable resource for cost-effective large-area estimation of AGB to inform national requirements such as for the US national greenhouse gas inventory (NGHGI). In addition, other optical satellite data such as MODIS imagery of wider spatial coverage and higher temporal resolution are enriching the domain of spatial predictors for regional scale mapping of AGB. Because NGHGIs require national scale AGB information and there are tradeoffs in the prediction accuracy versus operational efficiency of Landsat, this study evaluated the impact of various resolutions of Landsat predictors on the accuracy of regional AGB models across three different sites in the eastern USA: Maine, Pennsylvania-New Jersey, and South Carolina. We used recent national forest inventory (NFI) data with numerous Landsat-derived predictors at ten different spatial resolutions ranging from 30 to 1000 m to understand the optimal spatial resolution of the optical data for enhanced spatial inventory of AGB for NGHGI reporting. Ten generic spatial models at different spatial resolutions were developed for all sites and large-area estimates were evaluated (i) at the county-level against the independent designed-based estimates via the US NFI Evalidator tool and (ii) within a large number of strips ( 1 km wide) predicted via LiDAR metrics at a high spatial resolution. The county-level estimates by the Evalidator and Landsat models were statistically equivalent and produced coefficients of determination (R2) above 0.85 that varied with sites and resolution of predictors. The mean and standard deviation of county-level estimates followed increasing and decreasing trends, respectively, with models of decreasing resolutions. The Landsat-based total AGB estimates within the strips against the total AGB obtained using LiDAR metrics did not differ significantly and were within ±15 Mg/ha for each of the sites. We conclude that the optical satellite data at resolutions up to 1000 m provide acceptable accuracy for the US' NGHGI.
Field Evaluation of Four Spatial Repellent Devices Against Arkansas Rice-Land Mosquitoes
2014-03-01
FIELD EVALUATION OF FOUR SPATIAL REPELLENT DEVICES AGAINST ARKANSAS RICE-LAND MOSQUITOES DAVID A. DAME,1 MAX V. MEISCH,2 CAROLYN N. LEWIS,2 DANIEL L... mosquitoes to locate a host. There are many commercially available spatial repellent products currently on the market. These products include...a large rice growing area where late-spring and summer agricultural irriga- tion generates dense mosquito populations. Spatial repellent devices
NASA Astrophysics Data System (ADS)
Reid, Lucas; Kittlaus, Steffen; Scherer, Ulrike
2015-04-01
For large areas without highly detailed data the empirical Universal Soil Loss Equation (USLE) is widely used to quantify soil loss. The problem though is usually the quantification of actual sediment influx into the rivers. As the USLE provides long-term mean soil loss rates, it is often combined with spatially lumped models to estimate the sediment delivery ratio (SDR). But it gets difficult with spatially lumped approaches in large catchment areas where the geographical properties have a wide variance. In this study we developed a simple but spatially distributed approach to quantify the sediment delivery ratio by considering the characteristics of the flow paths in the catchments. The sediment delivery ratio was determined using an empirical approach considering the slope, morphology and land use properties along the flow path as an estimation of travel time of the eroded particles. The model was tested against suspended solids measurements in selected sub-basins of the River Inn catchment area in Germany and Austria, ranging from the high alpine south to the Molasse basin in the northern part.
Matthew Rollins; Tom Swetnam; Penelope Morgan
2000-01-01
Twentieth century fire patterns were analyzed for two large, disparate wilderness areas in the Rocky Mountains. Spatial and temporal patterns of fires were represented as GIS-based digital fire atlases compiled from archival Forest Service data. We find that spatial and temporal fire patterns are related to landscape features and changes in land use. The rate and...
During the last decade, a number of initiatives have been undertaken to create systematic national and global data sets of processed satellite imagery. An important application of these data is the derivation of large area (i.e. multi-scene) land cover products. Such products, ho...
NASA Astrophysics Data System (ADS)
Wen, Sy-Bor; Bhaskar, Arun; Zhang, Hongjie
2018-07-01
A scanning digital lithography system using computer controlled digital spatial light modulator, spatial filter, infinity correct optical microscope and high precision translation stage is proposed and examined. Through utilizing the spatial filter to limit orders of diffraction modes for light delivered from the spatial light modulator, we are able to achieve diffraction limited deep submicron spatial resolution with the scanning digital lithography system by using standard one inch level optical components with reasonable prices. Raster scanning of this scanning digital lithography system using a high speed high precision x-y translation stage and piezo mount to real time adjust the focal position of objective lens allows us to achieve large area sub-micron resolved patterning with high speed (compared with e-beam lithography). It is determined in this study that to achieve high quality stitching of lithography patterns with raster scanning, a high-resolution rotation stage will be required to ensure the x and y directions of the projected pattern are in the same x and y translation directions of the nanometer precision x-y translation stage.
Where have all the people gone? Enhancing global conservation using night lights and social media.
Levin, Noam; Kark, Salit; Crandall, David
2015-12-01
Conservation prioritization at large scales is complex, combining biological, environmental, and social factors. While conservation scientists now more often aim to incorporate human-related factors, a critical yet unquantified challenge remains: to identify which areas people use for recreation outside urban centers. To address this gap in applied ecology and conservation, we developed a novel approach for quantifying human presence beyond populated areas by combining social media "big data" and remote sensing tools. We used data from the Flickr photo-sharing website as a surrogate for identifying spatial variation in visitation globally, and complemented this estimate with spatially explicit information on stable night lights between 2004 and 2012, used as a proxy for identifying urban and industrial centers. Natural and seminatural areas attracting visitors were defined as areas both highly photographed and non-lit. The number of Flickr photographers within protected areas was found to be a reliable surrogate for estimating visitor numbers as confirmed by local authority censuses (r = 0.8). Half of all visitors' photos taken in protected areas originated from under 1% of all protected areas on Earth (250 of -27 000). The most photographed protected areas globally included Yosemite and Yellowstone National Parks (USA), and the Lake and Peak Districts (UK). Factors explaining the spatial variation in protected areas Flickr photo coverage included their type (e.g., UNESCO World Heritage sites have higher visitation) and accessibility to roads and trails. Using this approach, we identified photography hotspots, which draw many visitors and are also unlit (i.e., are located outside urban centers), but currently remain largely unprotected, such as Brazil's Pantanal and Bolivia's Salar de Uyuni. The integrated big data approach developed here demonstrates the benefits of combining remote sensing sources and novel geo-tagged and crowd-sourced information from social media in future efforts to identify spatial conservation gaps and pressures in real time, and their spatial and temporal variation globally.
Spatial heterogeneity of leaf area index across scales from simulation and remote sensing
NASA Astrophysics Data System (ADS)
Reichenau, Tim G.; Korres, Wolfgang; Montzka, Carsten; Schneider, Karl
2016-04-01
Leaf area index (LAI, single sided leaf area per ground area) influences mass and energy exchange of vegetated surfaces. Therefore LAI is an input variable for many land surface schemes of coupled large scale models, which do not simulate LAI. Since these models typically run on rather coarse resolution grids, LAI is often inferred from coarse resolution remote sensing. However, especially in agriculturally used areas, a grid cell of these products often covers more than a single land-use. In that case, the given LAI does not apply to any single land-use. Therefore, the overall spatial heterogeneity in these datasets differs from that on resolutions high enough to distinguish areas with differing land-use. Detailed process-based plant growth models simulate LAI for separate plant functional types or specific species. However, limited availability of observations causes reduced spatial heterogeneity of model input data (soil, weather, land-use). Since LAI is strongly heterogeneous in space and time and since processes depend on LAI in a nonlinear way, a correct representation of LAI spatial heterogeneity is also desirable on coarse resolutions. The current study assesses this issue by comparing the spatial heterogeneity of LAI from remote sensing (RapidEye) and process-based simulations (DANUBIA simulation system) across scales. Spatial heterogeneity is assessed by analyzing LAI frequency distributions (spatial variability) and semivariograms (spatial structure). Test case is the arable land in the fertile loess plain of the Rur catchment near the Germany-Netherlands border.
Spatial interactions among ecosystem services in an urbanizing agricultural watershed
Qiu, Jiangxiao; Turner, Monica G.
2013-01-01
Understanding spatial distributions, synergies, and tradeoffs of multiple ecosystem services (benefits people derive from ecosystems) remains challenging. We analyzed the supply of 10 ecosystem services for 2006 across a large urbanizing agricultural watershed in the Upper Midwest of the United States, and asked the following: (i) Where are areas of high and low supply of individual ecosystem services, and are these areas spatially concordant across services? (ii) Where on the landscape are the strongest tradeoffs and synergies among ecosystem services located? (iii) For ecosystem service pairs that experience tradeoffs, what distinguishes locations that are “win–win” exceptions from other locations? Spatial patterns of high supply for multiple ecosystem services often were not coincident; locations where six or more services were produced at high levels (upper 20th percentile) occupied only 3.3% of the landscape. Most relationships among ecosystem services were synergies, but tradeoffs occurred between crop production and water quality. Ecosystem services related to water quality and quantity separated into three different groups, indicating that management to sustain freshwater services along with other ecosystem services will not be simple. Despite overall tradeoffs between crop production and water quality, some locations were positive for both, suggesting that tradeoffs are not inevitable everywhere and might be ameliorated in some locations. Overall, we found that different areas of the landscape supplied different suites of ecosystem services, and their lack of spatial concordance suggests the importance of managing over large areas to sustain multiple ecosystem services. PMID:23818612
Spatial interactions among ecosystem services in an urbanizing agricultural watershed.
Qiu, Jiangxiao; Turner, Monica G
2013-07-16
Understanding spatial distributions, synergies, and tradeoffs of multiple ecosystem services (benefits people derive from ecosystems) remains challenging. We analyzed the supply of 10 ecosystem services for 2006 across a large urbanizing agricultural watershed in the Upper Midwest of the United States, and asked the following: (i) Where are areas of high and low supply of individual ecosystem services, and are these areas spatially concordant across services? (ii) Where on the landscape are the strongest tradeoffs and synergies among ecosystem services located? (iii) For ecosystem service pairs that experience tradeoffs, what distinguishes locations that are "win-win" exceptions from other locations? Spatial patterns of high supply for multiple ecosystem services often were not coincident; locations where six or more services were produced at high levels (upper 20th percentile) occupied only 3.3% of the landscape. Most relationships among ecosystem services were synergies, but tradeoffs occurred between crop production and water quality. Ecosystem services related to water quality and quantity separated into three different groups, indicating that management to sustain freshwater services along with other ecosystem services will not be simple. Despite overall tradeoffs between crop production and water quality, some locations were positive for both, suggesting that tradeoffs are not inevitable everywhere and might be ameliorated in some locations. Overall, we found that different areas of the landscape supplied different suites of ecosystem services, and their lack of spatial concordance suggests the importance of managing over large areas to sustain multiple ecosystem services.
Accuracy comparison in mapping water bodies using Landsat images and Google Earth Images
NASA Astrophysics Data System (ADS)
Zhou, Z.; Zhou, X.
2016-12-01
A lot of research has been done for the extraction of water bodies with multiple satellite images. The Water Indexes with the use of multi-spectral images are the mostly used methods for the water bodies' extraction. In order to extract area of water bodies from satellite images, accuracy may depend on the spatial resolution of images and relative size of the water bodies. To quantify the impact of spatial resolution and size (major and minor lengths) of the water bodies on the accuracy of water area extraction, we use Georgetown Lake, Montana and coalbed methane (CBM) water retention ponds in the Montana Powder River Basin as test sites to evaluate the impact of spatial resolution and the size of water bodies on water area extraction. Data sources used include Landsat images and Google Earth images covering both large water bodies and small ponds. Firstly we used water indices to extract water coverage from Landsat images for both large lake and small ponds. Secondly we used a newly developed visible-index method to extract water coverage from Google Earth images covering both large lake and small ponds. Thirdly, we used the image fusion method in which the Google Earth Images are fused with multi-spectral Landsat images to obtain multi-spectral images of the same high spatial resolution as the Google earth images. The actual area of the lake and ponds are measured using GPS surveys. Results will be compared and the optimal method will be selected for water body extraction.
Harrison, Charlotte; Jackson, Jade; Oh, Seung-Mock; Zeringyte, Vaida
2016-01-01
Multivariate pattern analysis of functional magnetic resonance imaging (fMRI) data is widely used, yet the spatial scales and origin of neurovascular signals underlying such analyses remain unclear. We compared decoding performance for stimulus orientation and eye of origin from fMRI measurements in human visual cortex with predictions based on the columnar organization of each feature and estimated the spatial scales of patterns driving decoding. Both orientation and eye of origin could be decoded significantly above chance in early visual areas (V1–V3). Contrary to predictions based on a columnar origin of response biases, decoding performance for eye of origin in V2 and V3 was not significantly lower than that in V1, nor did decoding performance for orientation and eye of origin differ significantly. Instead, response biases for both features showed large-scale organization, evident as a radial bias for orientation, and a nasotemporal bias for eye preference. To determine whether these patterns could drive classification, we quantified the effect on classification performance of binning voxels according to visual field position. Consistent with large-scale biases driving classification, binning by polar angle yielded significantly better decoding performance for orientation than random binning in V1–V3. Similarly, binning by hemifield significantly improved decoding performance for eye of origin. Patterns of orientation and eye preference bias in V2 and V3 showed a substantial degree of spatial correlation with the corresponding patterns in V1, suggesting that response biases in these areas originate in V1. Together, these findings indicate that multivariate classification results need not reflect the underlying columnar organization of neuronal response selectivities in early visual areas. NEW & NOTEWORTHY Large-scale response biases can account for decoding of orientation and eye of origin in human early visual areas V1–V3. For eye of origin this pattern is a nasotemporal bias; for orientation it is a radial bias. Differences in decoding performance across areas and stimulus features are not well predicted by differences in columnar-scale organization of each feature. Large-scale biases in extrastriate areas are spatially correlated with those in V1, suggesting biases originate in primary visual cortex. PMID:27903637
NASA Technical Reports Server (NTRS)
Horvath, R. (Principal Investigator); Cicone, R.; Crist, E.; Kauth, R. J.; Lambeck, P.; Malila, W. A.; Richardson, W.
1979-01-01
The author has identified the following significant results. An outgrowth of research and development activities in support of LACIE was a multicrop area estimation procedure, Procedure M. This procedure was a flexible, modular system that could be operated within the LACIE framework. Its distinctive features were refined preprocessing (including spatially varying correction for atmospheric haze), definition of field like spatial features for labeling, spectral stratification, and unbiased selection of samples to label and crop area estimation without conventional maximum likelihood classification.
Measuring Te inclusion uniformity over large areas for CdTe/CZT imaging and spectrometry sensors
NASA Astrophysics Data System (ADS)
Bolke, Joe; O'Brien, Kathryn; Wall, Peter; Spicer, Mike; Gélinas, Guillaume; Beaudry, Jean-Nicolas; Alexander, W. Brock
2017-09-01
CdTe and CZT materials are technologies for gamma and x-ray imaging for applications in industry, homeland security, defense, space, medical, and astrophysics. There remain challenges in uniformity over large detector areas (50 75 mm) due to a combination of material purity, handling, growth process, grown in defects, doping/compensation, and metal contacts/surface states. The influence of these various factors has yet to be explored at the large substrate level required for devices with higher resolution both spatially and spectroscopically. In this study, we looked at how the crystal growth processes affect the size and density distributions of microscopic Te inclusion defects. We were able to grow single crystals as large as 75 mm in diameter and spatially characterize three-dimensional defects and map the uniformity using IR microscopy. We report on the pattern of observed defects within wafers and its relation to instabilities at the crystal growth interface.
The evolving role of science in wilderness to our understanding of ecosystems and landscapes
Norman L. Christensen
2000-01-01
Research in wilderness areas (areas with minimal human activity and of large spatial extent) formed the foundation for ecological models and theories that continue to shape our understanding how ecosystems change through time, how ecological communities are structured and how ecosystems function. By the middle of this century, large expanses of wilderness had become...
Congdon, Peter
2010-01-01
Different indicators of morbidity for chronic disease may not necessarily be available at a disaggregated spatial scale (e.g., for small areas with populations under 10 thousand). Instead certain indicators may only be available at a more highly aggregated spatial scale; for example, deaths may be recorded for small areas, but disease prevalence only at a considerably higher spatial scale. Nevertheless prevalence estimates at small area level are important for assessing health need. An instance is provided by England where deaths and hospital admissions for coronary heart disease are available for small areas known as wards, but prevalence is only available for relatively large health authority areas. To estimate CHD prevalence at small area level in such a situation, a shared random effect method is proposed that pools information regarding spatial morbidity contrasts over different indicators (deaths, hospitalizations, prevalence). The shared random effect approach also incorporates differences between small areas in known risk factors (e.g., income, ethnic structure). A Poisson-multinomial equivalence may be used to ensure small area prevalence estimates sum to the known higher area total. An illustration is provided by data for London using hospital admissions and CHD deaths at ward level, together with CHD prevalence totals for considerably larger local health authority areas. The shared random effect involved a spatially correlated common factor, that accounts for clustering in latent risk factors, and also provides a summary measure of small area CHD morbidity.
Congdon, Peter
2010-01-01
Different indicators of morbidity for chronic disease may not necessarily be available at a disaggregated spatial scale (e.g., for small areas with populations under 10 thousand). Instead certain indicators may only be available at a more highly aggregated spatial scale; for example, deaths may be recorded for small areas, but disease prevalence only at a considerably higher spatial scale. Nevertheless prevalence estimates at small area level are important for assessing health need. An instance is provided by England where deaths and hospital admissions for coronary heart disease are available for small areas known as wards, but prevalence is only available for relatively large health authority areas. To estimate CHD prevalence at small area level in such a situation, a shared random effect method is proposed that pools information regarding spatial morbidity contrasts over different indicators (deaths, hospitalizations, prevalence). The shared random effect approach also incorporates differences between small areas in known risk factors (e.g., income, ethnic structure). A Poisson-multinomial equivalence may be used to ensure small area prevalence estimates sum to the known higher area total. An illustration is provided by data for London using hospital admissions and CHD deaths at ward level, together with CHD prevalence totals for considerably larger local health authority areas. The shared random effect involved a spatially correlated common factor, that accounts for clustering in latent risk factors, and also provides a summary measure of small area CHD morbidity. PMID:20195439
Wu, Yiming; Zhang, Xiujuan; Pan, Huanhuan; Deng, Wei; Zhang, Xiaohong; Zhang, Xiwei; Jie, Jiansheng
2013-01-01
Single-crystalline organic nanowires (NWs) are important building blocks for future low-cost and efficient nano-optoelectronic devices due to their extraordinary properties. However, it remains a critical challenge to achieve large-scale organic NW array assembly and device integration. Herein, we demonstrate a feasible one-step method for large-area patterned growth of cross-aligned single-crystalline organic NW arrays and their in-situ device integration for optical image sensors. The integrated image sensor circuitry contained a 10 × 10 pixel array in an area of 1.3 × 1.3 mm2, showing high spatial resolution, excellent stability and reproducibility. More importantly, 100% of the pixels successfully operated at a high response speed and relatively small pixel-to-pixel variation. The high yield and high spatial resolution of the operational pixels, along with the high integration level of the device, clearly demonstrate the great potential of the one-step organic NW array growth and device construction approach for large-scale optoelectronic device integration. PMID:24287887
NASA Technical Reports Server (NTRS)
Sellers, Piers
2012-01-01
Soil wetness typically shows great spatial variability over the length scales of general circulation model (GCM) grid areas (approx 100 km ), and the functions relating evapotranspiration and photosynthetic rate to local-scale (approx 1 m) soil wetness are highly non-linear. Soil respiration is also highly dependent on very small-scale variations in soil wetness. We therefore expect significant inaccuracies whenever we insert a single grid area-average soil wetness value into a function to calculate any of these rates for the grid area. For the particular case of evapotranspiration., this method - use of a grid-averaged soil wetness value - can also provoke severe oscillations in the evapotranspiration rate and soil wetness under some conditions. A method is presented whereby the probability distribution timction(pdf) for soil wetness within a grid area is represented by binning. and numerical integration of the binned pdf is performed to provide a spatially-integrated wetness stress term for the whole grid area, which then permits calculation of grid area fluxes in a single operation. The method is very accurate when 10 or more bins are used, can deal realistically with spatially variable precipitation, conserves moisture exactly and allows for precise modification of the soil wetness pdf after every time step. The method could also be applied to other ecological problems where small-scale processes must be area-integrated, or upscaled, to estimate fluxes over large areas, for example in treatments of the terrestrial carbon budget or trace gas generation.
Schmidt, Tom L.; Barton, Nicholas H.; Rašić, Gordana; Turley, Andrew P.; Montgomery, Brian L.; Iturbe-Ormaetxe, Inaki; Cook, Peter E.; Ryan, Peter A.; Ritchie, Scott A.; Hoffmann, Ary A.; O’Neill, Scott L.
2017-01-01
Dengue-suppressing Wolbachia strains are promising tools for arbovirus control, particularly as they have the potential to self-spread following local introductions. To test this, we followed the frequency of the transinfected Wolbachia strain wMel through Ae. aegypti in Cairns, Australia, following releases at 3 nonisolated locations within the city in early 2013. Spatial spread was analysed graphically using interpolation and by fitting a statistical model describing the position and width of the wave. For the larger 2 of the 3 releases (covering 0.97 km2 and 0.52 km2), we observed slow but steady spatial spread, at about 100–200 m per year, roughly consistent with theoretical predictions. In contrast, the smallest release (0.11 km2) produced erratic temporal and spatial dynamics, with little evidence of spread after 2 years. This is consistent with the prediction concerning fitness-decreasing Wolbachia transinfections that a minimum release area is needed to achieve stable local establishment and spread in continuous habitats. Our graphical and likelihood analyses produced broadly consistent estimates of wave speed and wave width. Spread at all sites was spatially heterogeneous, suggesting that environmental heterogeneity will affect large-scale Wolbachia transformations of urban mosquito populations. The persistence and spread of Wolbachia in release areas meeting minimum area requirements indicates the promise of successful large-scale population transformation. PMID:28557993
Schmidt, Tom L; Barton, Nicholas H; Rašić, Gordana; Turley, Andrew P; Montgomery, Brian L; Iturbe-Ormaetxe, Inaki; Cook, Peter E; Ryan, Peter A; Ritchie, Scott A; Hoffmann, Ary A; O'Neill, Scott L; Turelli, Michael
2017-05-01
Dengue-suppressing Wolbachia strains are promising tools for arbovirus control, particularly as they have the potential to self-spread following local introductions. To test this, we followed the frequency of the transinfected Wolbachia strain wMel through Ae. aegypti in Cairns, Australia, following releases at 3 nonisolated locations within the city in early 2013. Spatial spread was analysed graphically using interpolation and by fitting a statistical model describing the position and width of the wave. For the larger 2 of the 3 releases (covering 0.97 km2 and 0.52 km2), we observed slow but steady spatial spread, at about 100-200 m per year, roughly consistent with theoretical predictions. In contrast, the smallest release (0.11 km2) produced erratic temporal and spatial dynamics, with little evidence of spread after 2 years. This is consistent with the prediction concerning fitness-decreasing Wolbachia transinfections that a minimum release area is needed to achieve stable local establishment and spread in continuous habitats. Our graphical and likelihood analyses produced broadly consistent estimates of wave speed and wave width. Spread at all sites was spatially heterogeneous, suggesting that environmental heterogeneity will affect large-scale Wolbachia transformations of urban mosquito populations. The persistence and spread of Wolbachia in release areas meeting minimum area requirements indicates the promise of successful large-scale population transformation.
Improved understanding of air emissions from large area sources such as landfills, waste water ponds, open-source processing, and agricultural operations is a topic of increasing environmental importance. In many cases, the size of the area source, coupled with spatial-heteroge...
Garcia, A G; Araujo, M R; Uramoto, K; Walder, J M M; Zucchi, R A
2017-12-08
Fruit flies are among the most damaging insect pests of commercial fruit in Brazil. It is important to understand the landscape elements that may favor these flies. In the present study, spatial data from surveys of species of Anastrepha Schiner (Diptera: Tephritidae) in an urban area with forest fragments were analyzed, using geostatistics and Geographic Information System (GIS) to map the diversity of insects and evaluate how the forest fragments drive the spatial patterns. The results indicated a high diversity of species associated with large fragments, and a trend toward lower diversity in the more urbanized area, as the fragment sizes decreased. We concluded that the diversity of Anastrepha species is directly and positively related to large and continuous forest fragments in urbanized areas, and that combining geostatistics and GIS is a promising method for use in insect-pest management and sampling involving fruit flies. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Spatial statistical analysis of tree deaths using airborne digital imagery
NASA Astrophysics Data System (ADS)
Chang, Ya-Mei; Baddeley, Adrian; Wallace, Jeremy; Canci, Michael
2013-04-01
High resolution digital airborne imagery offers unprecedented opportunities for observation and monitoring of vegetation, providing the potential to identify, locate and track individual vegetation objects over time. Analytical tools are required to quantify relevant information. In this paper, locations of trees over a large area of native woodland vegetation were identified using morphological image analysis techniques. Methods of spatial point process statistics were then applied to estimate the spatially-varying tree death risk, and to show that it is significantly non-uniform. [Tree deaths over the area were detected in our previous work (Wallace et al., 2008).] The study area is a major source of ground water for the city of Perth, and the work was motivated by the need to understand and quantify vegetation changes in the context of water extraction and drying climate. The influence of hydrological variables on tree death risk was investigated using spatial statistics (graphical exploratory methods, spatial point pattern modelling and diagnostics).
Spatial Data Management System (SDMS)
NASA Technical Reports Server (NTRS)
Hutchison, Mark W.
1994-01-01
The Spatial Data Management System (SDMS) is a testbed for retrieval and display of spatially related material. SDMS permits the linkage of large graphical display objects with detail displays and explanations of its smaller components. SDMS combines UNIX workstations, MIT's X Window system, TCP/IP and WAIS information retrieval technology to prototype a means of associating aggregate data linked via spatial orientation. SDMS capitalizes upon and extends previous accomplishments of the Software Technology Branch in the area of Virtual Reality and Automated Library Systems.
B. Tyler Wilson; Andrew J. Lister; Rachel I. Riemann
2012-01-01
The paper describes an efficient approach for mapping multiple individual tree species over large spatial domains. The method integrates vegetation phenology derived from MODIS imagery and raster data describing relevant environmental parameters with extensive field plot data of tree species basal area to create maps of tree species abundance and distribution at a 250-...
Using the Gravity Model to Estimate the Spatial Spread of Vector-Borne Diseases
Barrios, José Miguel; Verstraeten, Willem W.; Maes, Piet; Aerts, Jean-Marie; Farifteh, Jamshid; Coppin, Pol
2012-01-01
The gravity models are commonly used spatial interaction models. They have been widely applied in a large set of domains dealing with interactions amongst spatial entities. The spread of vector-borne diseases is also related to the intensity of interaction between spatial entities, namely, the physical habitat of pathogens’ vectors and/or hosts, and urban areas, thus humans. This study implements the concept behind gravity models in the spatial spread of two vector-borne diseases, nephropathia epidemica and Lyme borreliosis, based on current knowledge on the transmission mechanism of these diseases. Two sources of information on vegetated systems were tested: the CORINE land cover map and MODIS NDVI. The size of vegetated areas near urban centers and a local indicator of occupation-related exposure were found significant predictors of disease risk. Both the land cover map and the space-borne dataset were suited yet not equivalent input sources to locate and measure vegetated areas of importance for disease spread. The overall results point at the compatibility of the gravity model concept and the spatial spread of vector-borne diseases. PMID:23202882
Using the gravity model to estimate the spatial spread of vector-borne diseases.
Barrios, José Miguel; Verstraeten, Willem W; Maes, Piet; Aerts, Jean-Marie; Farifteh, Jamshid; Coppin, Pol
2012-11-30
The gravity models are commonly used spatial interaction models. They have been widely applied in a large set of domains dealing with interactions amongst spatial entities. The spread of vector-borne diseases is also related to the intensity of interaction between spatial entities, namely, the physical habitat of pathogens’ vectors and/or hosts, and urban areas, thus humans. This study implements the concept behind gravity models in the spatial spread of two vector-borne diseases, nephropathia epidemica and Lyme borreliosis, based on current knowledge on the transmission mechanism of these diseases. Two sources of information on vegetated systems were tested: the CORINE land cover map and MODIS NDVI. The size of vegetated areas near urban centers and a local indicator of occupation-related exposure were found significant predictors of disease risk. Both the land cover map and the space-borne dataset were suited yet not equivalent input sources to locate and measure vegetated areas of importance for disease spread. The overall results point at the compatibility of the gravity model concept and the spatial spread of vector-borne diseases.
Spatial height directed microfluidic synthesis of transparent inorganic upconversion nano film
NASA Astrophysics Data System (ADS)
Liu, Xiaoxia; Zhu, Cheng; Liao, Wei; Jin, Junyang; Ni, Yaru; Lu, Chunhua; Xu, Zhongzi
2017-11-01
A microfluidic-based synthesis of an inorganic upconversion nano film has been developed with a large area of dense-distributed NaYF4 crystal grains in a silica glass micro-reactor and the film exhibits high transparence, strong upconversion luminescence and robust adhesion with the substrate. The spatial heights of micro-reactors are tuned between 31 and 227 mm, which can regulate flow regimes. The synergistic effect of spatial height and fluid regime is put forward, which influences diffusion paths and assembly ways of different precursor molecules and consequently directs final distributions and morphologies of crystal grains, as well as optical properties due to diversity of surface and thickness of films. The spatial height of 110 mm is advantageous for high transmittance of upconversion film due to the flat surface and appropriate film thickness of 67 nm. The height of 150 mm is in favor of uniform distribution of upconversion fluorescence and achieving the strongest fluorescence due to minimized optical loss. Such a transparent upconversion film with a large area of uniform distribution is promising to promote the application of upconversion materials and spatial height directed microfluidic regime have a certain significance on many microfluidic synthesis.
NASA Astrophysics Data System (ADS)
Liu, Jiping; Kang, Xiaochen; Dong, Chun; Xu, Shenghua
2017-12-01
Surface area estimation is a widely used tool for resource evaluation in the physical world. When processing large scale spatial data, the input/output (I/O) can easily become the bottleneck in parallelizing the algorithm due to the limited physical memory resources and the very slow disk transfer rate. In this paper, we proposed a stream tilling approach to surface area estimation that first decomposed a spatial data set into tiles with topological expansions. With these tiles, the one-to-one mapping relationship between the input and the computing process was broken. Then, we realized a streaming framework towards the scheduling of the I/O processes and computing units. Herein, each computing unit encapsulated a same copy of the estimation algorithm, and multiple asynchronous computing units could work individually in parallel. Finally, the performed experiment demonstrated that our stream tilling estimation can efficiently alleviate the heavy pressures from the I/O-bound work, and the measured speedup after being optimized have greatly outperformed the directly parallel versions in shared memory systems with multi-core processors.
Shafer, Sarah; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.
2015-01-01
Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.
Shafer, Sarah L.; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.
2015-01-01
Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas. PMID:26488750
Low, slow, small target recognition based on spatial vision network
NASA Astrophysics Data System (ADS)
Cheng, Zhao; Guo, Pei; Qi, Xin
2018-03-01
Traditional photoelectric monitoring is monitored using a large number of identical cameras. In order to ensure the full coverage of the monitoring area, this monitoring method uses more cameras, which leads to more monitoring and repetition areas, and higher costs, resulting in more waste. In order to reduce the monitoring cost and solve the difficult problem of finding, identifying and tracking a low altitude, slow speed and small target, this paper presents spatial vision network for low-slow-small targets recognition. Based on camera imaging principle and monitoring model, spatial vision network is modeled and optimized. Simulation experiment results demonstrate that the proposed method has good performance.
Ghost reefs: Nautical charts document large spatial scale of coral reef loss over 240 years
McClenachan, Loren; O’Connor, Grace; Neal, Benjamin P.; Pandolfi, John M.; Jackson, Jeremy B. C.
2017-01-01
Massive declines in population abundances of marine animals have been documented over century-long time scales. However, analogous loss of spatial extent of habitat-forming organisms is less well known because georeferenced data are rare over long time scales, particularly in subtidal, tropical marine regions. We use high-resolution historical nautical charts to quantify changes to benthic structure over 240 years in the Florida Keys, finding an overall loss of 52% (SE, 6.4%) of the area of the seafloor occupied by corals. We find a strong spatial dimension to this decline; the spatial extent of coral in Florida Bay and nearshore declined by 87.5% (SE, 7.2%) and 68.8% (SE, 7.5%), respectively, whereas that of offshore areas of coral remained largely intact. These estimates add to finer-scale loss in live coral cover exceeding 90% in some locations in recent decades. The near-complete elimination of the spatial coverage of nearshore coral represents an underappreciated spatial component of the shifting baseline syndrome, with important lessons for other species and ecosystems. That is, modern surveys are typically designed to assess change only within the species’ known, extant range. For species ranging from corals to sea turtles, this approach may overlook spatial loss over longer time frames, resulting in both overly optimistic views of their current conservation status and underestimates of their restoration potential. PMID:28913420
USDA-ARS?s Scientific Manuscript database
A very promising technique for spatial disaggregation of soil moisture is on the combination of radiometer and radar observations. Despite their demonstrated potential for long term large scale monitoring of soil moisture, passive and active have their disadvantages in terms of temporal and spatial ...
Chan, K L Andrew; Kazarian, Sergei G
2008-10-01
Attenuated total reflection-Fourier transform infrared (ATR-FT-IR) imaging is a very useful tool for capturing chemical images of various materials due to the simple sample preparation and the ability to measure wet samples or samples in an aqueous environment. However, the size of the array detector used for image acquisition is often limited and there is usually a trade off between spatial resolution and the field of view (FOV). The combination of mapping and imaging can be used to acquire images with a larger FOV without sacrificing spatial resolution. Previous attempts have demonstrated this using an infrared microscope and a Germanium hemispherical ATR crystal to achieve images of up to 2.5 mm x 2.5 mm but with varying spatial resolution and depth of penetration across the imaged area. In this paper, we demonstrate a combination of mapping and imaging with a different approach using an external optics housing for large ATR accessories and inverted ATR prisms to achieve ATR-FT-IR images with a large FOV and reasonable spatial resolution. The results have shown that a FOV of 10 mm x 14 mm can be obtained with a spatial resolution of approximately 40-60 microm when using an accessory that gives no magnification. A FOV of 1.3 mm x 1.3 mm can be obtained with spatial resolution of approximately 15-20 microm when using a diamond ATR imaging accessory with 4x magnification. No significant change in image quality such as spatial resolution or depth of penetration has been observed across the whole FOV with this method and the measurement time was approximately 15 minutes for an image consisting of 16 image tiles.
Spatial patterns of native freshwater mussels in the Upper Mississippi River
Ries, Patricia R.; DeJager, Nathan R.; Zigler, Steven J.; Newton, Teresa
2016-01-01
Multiple physical and biological factors structure freshwater mussel communities in large rivers, and their distributions have been described as clumped or patchy. However, few surveys of mussel populations have been conducted over areas large enough and at resolutions fine enough to quantify spatial patterns in their distribution. We used global and local indicators of spatial autocorrelation (i.e., Moran’s I) to quantify spatial patterns of adult and juvenile (≤5 y of age) freshwater mussels across multiple scales based on survey data from 4 reaches (navigation pools 3, 5, 6, and 18) of the Upper Mississippi River, USA. Native mussel densities were sampled at a resolution of ∼300 m and across distances ranging from 21 to 37 km, making these some of the most spatially extensive surveys conducted in a large river. Patch density and the degree and scale of patchiness varied by river reach, age group, and the scale of analysis. In all 4 pools, some patches of adults overlapped patches of juveniles, suggesting spatial and temporal persistence of adequate habitat. In pools 3 and 5, patches of juveniles were found where there were few adults, suggesting recent emergence of positive structuring mechanisms. Last, in pools 3, 5, and 6, some patches of adults were found where there were few juveniles, suggesting that negative structuring mechanisms may have replaced positive ones, leading to a lack of localized recruitment. Our results suggest that: 1) the detection of patches of freshwater mussels requires a multiscaled approach, 2) insights into the spatial and temporal dynamics of structuring mechanisms can be gained by conducting independent analyses of adults and juveniles, and 3) maps of patch distributions can be used to guide restoration and management actions and identify areas where mussels are most likely to influence ecosystem function.
Morelli, Federico
2017-01-01
Road and railway networks are pervasive elements of all environments, which have expanded intensively over the last century in all European countries. These transportation infrastructures have major impacts on the surrounding landscape, representing a threat to biodiversity. Roadsides and railways may function as corridors for dispersal of alien species in fragmented landscapes. However, only few studies have explored the spread of invasive species in relationship to transport network at large spatial scales. We performed a spatial mismatch analysis, based on a spatially explicit correlation test, to investigate whether alien plant species hotspots in Germany and Austria correspond to areas of high density of roads and railways. We tested this independently of the effects of dominant environments in each spatial unit, in order to focus just on the correlation between occurrence of alien species and density of linear transportation infrastructures. We found a significant spatial association between alien plant species hotspots distribution and roads and railways density in both countries. As expected, anthropogenic landscapes, such as urban areas, harbored more alien plant species, followed by water bodies. However, our findings suggested that the distribution of neobiota is strongest correlated to road/railways density than to land use composition. This study provides new evidence, from a transnational scale, that alien plants can use roadsides and rail networks as colonization corridors. Furthermore, our approach contributes to the understanding on alien plant species distribution at large spatial scale by the combination with spatial modeling procedures. PMID:28829818
Kshettry, Aritra; Vaidyanathan, Srinivas; Athreya, Vidya
2017-01-01
There is increasing evidence of the importance of multi-use landscapes for the conservation of large carnivores. However, when carnivore ranges overlap with high density of humans, there are often serious conservation challenges. This is especially true in countries like India where loss of peoples' lives and property to large wildlife are not uncommon. The leopard (Panthera pardus) is a large felid that is widespread in India, often sharing landscapes with high human densities. In order to understand the ecology of leopards in a human use landscape and the nature of human-leopard interactions, we studied (i) the spatial and temporal distribution and the characteristics of leopard attacks on people, (ii) the spatial variability in the pattern of habitat use by the leopard, and (iii) the spatial relationship between attack locations and habitat use by leopards. The study site, located in northern West Bengal, India, is a densely populated mixed-use landscape of 630 km2, comprising of forests, tea plantations, agriculture fields, and human settlements. A total of 171 leopard attacks on humans were reported between January 2009 and March 2016, most of which occurred within the tea-gardens. None of the attacks was fatal. We found significant spatial clustering of locations of leopard attacks on humans. However, most of the attacks were restricted to certain tea estates and occurred mostly between January and May. Analysis of habitat use by leopards showed that the probability of use of areas with more ground vegetation cover was high while that of areas with high density of buildings was low. However, locations of leopard attacks on people did not coincide with areas that showed a higher probability of use by leopards. This indicates that an increased use of an area by leopards, by itself, does not necessarily imply an increase in attacks on people. The spatial and temporal clustering of attack locations allowed us to use this information to prioritize areas to focus mitigation activities in order reduce negative encounters between people and leopards in this landscape which has had a long history of conflict.
2017-01-01
There is increasing evidence of the importance of multi-use landscapes for the conservation of large carnivores. However, when carnivore ranges overlap with high density of humans, there are often serious conservation challenges. This is especially true in countries like India where loss of peoples’ lives and property to large wildlife are not uncommon. The leopard (Panthera pardus) is a large felid that is widespread in India, often sharing landscapes with high human densities. In order to understand the ecology of leopards in a human use landscape and the nature of human-leopard interactions, we studied (i) the spatial and temporal distribution and the characteristics of leopard attacks on people, (ii) the spatial variability in the pattern of habitat use by the leopard, and (iii) the spatial relationship between attack locations and habitat use by leopards. The study site, located in northern West Bengal, India, is a densely populated mixed-use landscape of 630 km2, comprising of forests, tea plantations, agriculture fields, and human settlements. A total of 171 leopard attacks on humans were reported between January 2009 and March 2016, most of which occurred within the tea-gardens. None of the attacks was fatal. We found significant spatial clustering of locations of leopard attacks on humans. However, most of the attacks were restricted to certain tea estates and occurred mostly between January and May. Analysis of habitat use by leopards showed that the probability of use of areas with more ground vegetation cover was high while that of areas with high density of buildings was low. However, locations of leopard attacks on people did not coincide with areas that showed a higher probability of use by leopards. This indicates that an increased use of an area by leopards, by itself, does not necessarily imply an increase in attacks on people. The spatial and temporal clustering of attack locations allowed us to use this information to prioritize areas to focus mitigation activities in order reduce negative encounters between people and leopards in this landscape which has had a long history of conflict. PMID:28493999
NASA Astrophysics Data System (ADS)
Law, Jane; Quick, Matthew
2013-01-01
This paper adopts a Bayesian spatial modeling approach to investigate the distribution of young offender residences in York Region, Southern Ontario, Canada, at the census dissemination area level. Few geographic researches have analyzed offender (as opposed to offense) data at a large map scale (i.e., using a relatively small areal unit of analysis) to minimize aggregation effects. Providing context is the social disorganization theory, which hypothesizes that areas with economic deprivation, high population turnover, and high ethnic heterogeneity exhibit social disorganization and are expected to facilitate higher instances of young offenders. Non-spatial and spatial Poisson models indicate that spatial methods are superior to non-spatial models with respect to model fit and that index of ethnic heterogeneity, residential mobility (1 year moving rate), and percentage of residents receiving government transfer payments are, respectively, the most significant explanatory variables related to young offender location. These findings provide overwhelming support for social disorganization theory as it applies to offender location in York Region, Ontario. Targeting areas where prevalence of young offenders could or could not be explained by social disorganization through decomposing the estimated risk map are helpful for dealing with juvenile offenders in the region. Results prompt discussion into geographically targeted police services and young offender placement pertaining to risk of recidivism. We discuss possible reasons for differences and similarities between the previous findings (that analyzed offense data and/or were conducted at a smaller map scale) and our findings, limitations of our study, and practical outcomes of this research from a law enforcement perspective.
NASA Technical Reports Server (NTRS)
Bromwich, David H.; Chen, Qui-Shi
2005-01-01
Atmospheric numerical simulation and dynamic retrieval method with atmospheric numerical analyses are used to assess the spatial and temporal variability of Antarctic precipitation for the last two decades. First, the Polar MM5 has been run over Antarctica to study the Antarctic precipitation. With a horizontal resolution of 60km, the Polar MM5 has been run for the period of July 1996 through June 1999 in a series of short-term forecasts from initial and boundary conditions provided by the ECMWF operational analyses. In comparison with climatological maps, the major features of the spatial distribution of Antarctic precipitation are well captured by the Polar MM5. Drift snow effects on redistribution of surface accumulation over Antarctica are also assessed with surface wind fields from Polar MM5 in this study. There are complex divergence and convergence patterns of drift snow transport over Antarctica, especially along the coast. It is found that areas with large drift snow transport convergence and divergence are located around escarpment areas where there is large katabatic wind acceleration. In addition, areas with large snow transport divergence are generally accompanied by areas with large snow transport convergence nearby, indicating that drift snow transport is of local importance for the redistribution of the snowfall
Large-scale impacts of herbivores on the structural diversity of African savannas
Asner, Gregory P.; Levick, Shaun R.; Kennedy-Bowdoin, Ty; Knapp, David E.; Emerson, Ruth; Jacobson, James; Colgan, Matthew S.; Martin, Roberta E.
2009-01-01
African savannas are undergoing management intensification, and decision makers are increasingly challenged to balance the needs of large herbivore populations with the maintenance of vegetation and ecosystem diversity. Ensuring the sustainability of Africa's natural protected areas requires information on the efficacy of management decisions at large spatial scales, but often neither experimental treatments nor large-scale responses are available for analysis. Using a new airborne remote sensing system, we mapped the three-dimensional (3-D) structure of vegetation at a spatial resolution of 56 cm throughout 1640 ha of savanna after 6-, 22-, 35-, and 41-year exclusions of herbivores, as well as in unprotected areas, across Kruger National Park in South Africa. Areas in which herbivores were excluded over the short term (6 years) contained 38%–80% less bare ground compared with those that were exposed to mammalian herbivory. In the longer-term (> 22 years), the 3-D structure of woody vegetation differed significantly between protected and accessible landscapes, with up to 11-fold greater woody canopy cover in the areas without herbivores. Our maps revealed 2 scales of ecosystem response to herbivore consumption, one broadly mediated by geologic substrate and the other mediated by hillslope-scale variation in soil nutrient availability and moisture conditions. Our results are the first to quantitatively illustrate the extent to which herbivores can affect the 3-D structural diversity of vegetation across large savanna landscapes. PMID:19258457
NASA Astrophysics Data System (ADS)
Murray, K. D.; Lohman, R.
2017-12-01
Areas of large-scale subsidence are observed over much of the San Joaquin Valley of California due to the extraction of groundwater and hydrocarbons from the subsurface.These signals span regions with spatial extents of up to 100 km and have rates of up to 45 cm/yr or more. InSAR and GPS are complementary methods commonly used to measure such ground displacements and can provide important constraints on crustal deformation models, support groundwater studies, and inform water resource management efforts. However, current standard methods for processing these data sets and creating displacement time series are suboptimal for the deformation observed in areas like the San Joaquin Valley because (1) the ground surface properties are constantly changing due largely to agricultural activity, resulting in low coherence in half or more of a SAR frame, and (2) the deformation signals are distributed throughout the SAR frames, and are comparable to the size of the frames themselves. Therefore, referencing areas of deformation to non-deforming areas and correcting for long wavelength signals (e.g. atmospheric delays, orbital errors) is particularly difficult. We address these challenges by exploiting pixels that are stable in space and time, and use them for weighted spatial averaging and selective filtering before unwrapping. We then compare a range of methods for both long wavelength corrections and referencing via automatic partitioning of non-deforming areas, then benchmark results against continuous GPS measurements. Our final time series consist of nearly 15 years of displacement measurements from continuous GPS data, and Envisat, ALOS-1, Sentinel SAR data, and show significant temporal and spatial variations. We find that the choice of reference and long wavelength corrections can significantly bias long-term rate and seasonal amplitude estimates, causing variations of as much as 100% of the mean estimate. As we enter an era with free and open data access and regular observations plans from missions such as NISAR and the Sentinel constellation, our approach will help users evaluate the significance of observed deformation at a range of spatial scales and in areas with challenging surface properties.
Effect of Variable Spatial Scales on USLE-GIS Computations
NASA Astrophysics Data System (ADS)
Patil, R. J.; Sharma, S. K.
2017-12-01
Use of appropriate spatial scale is very important in Universal Soil Loss Equation (USLE) based spatially distributed soil erosion modelling. This study aimed at assessment of annual rates of soil erosion at different spatial scales/grid sizes and analysing how changes in spatial scales affect USLE-GIS computations using simulation and statistical variabilities. Efforts have been made in this study to recommend an optimum spatial scale for further USLE-GIS computations for management and planning in the study area. The present research study was conducted in Shakkar River watershed, situated in Narsinghpur and Chhindwara districts of Madhya Pradesh, India. Remote Sensing and GIS techniques were integrated with Universal Soil Loss Equation (USLE) to predict spatial distribution of soil erosion in the study area at four different spatial scales viz; 30 m, 50 m, 100 m, and 200 m. Rainfall data, soil map, digital elevation model (DEM) and an executable C++ program, and satellite image of the area were used for preparation of the thematic maps for various USLE factors. Annual rates of soil erosion were estimated for 15 years (1992 to 2006) at four different grid sizes. The statistical analysis of four estimated datasets showed that sediment loss dataset at 30 m spatial scale has a minimum standard deviation (2.16), variance (4.68), percent deviation from observed values (2.68 - 18.91 %), and highest coefficient of determination (R2 = 0.874) among all the four datasets. Thus, it is recommended to adopt this spatial scale for USLE-GIS computations in the study area due to its minimum statistical variability and better agreement with the observed sediment loss data. This study also indicates large scope for use of finer spatial scales in spatially distributed soil erosion modelling.
NASA Astrophysics Data System (ADS)
Stagličić, N.; Matić-Skoko, S.; Pallaoro, A.; Grgičević, R.; Kraljević, M.; Tutman, P.; Dragičević, B.; Dulčić, J.
2011-09-01
Long-term interannual changes in abundance, biomass, diversity and structure of littoral fish assemblages were examined between 1993 and 2009 by experimental trammel net fishing up to six times per year, within the warm period - May to September, at multiple areas along the eastern Adriatic coast with the aim of testing for the consistency of patterns of change across a large spatial scale (˜600 km). The results revealed spatially consistent increasing trends of total fish abundance and biomass growing at an average rate of 15 and 14% per year, respectively. Of the diversity indices analysed, the same pattern of variability was observed for Shannon diversity, while Pielou evenness and average taxonomic distinctness measures Δ ∗ and Δ + showed spatial variability with no obvious temporal trends. Multivariate fish assemblage structure underwent a directional change displaying a similar pattern through time for all the areas. The structural change in fish assemblages generally involved most of the species present in trammel net catches. A large pool of fish species responsible for producing the temporal pattern of assemblage change was relatively different in each of the areas reflecting a large geographic range covered by the study. An analysis of 4 fish species ( Symphodus tinca, Pagellus erythrinus, Mullus surmuletus, Scorpaena porcus) common to each of the study areas as the ones driving the temporal change indicated that there were clear increasing trends of their mean catches across the years at all the study areas. A common pattern among time trajectories across the spatial scale studied implies that the factor affecting the littoral fish assemblages is not localised but regional in nature. As an underlying factor having the potential to induce such widespread and consistent improvements in littoral fish assemblages, a more restrictive artisanal fishery management that has progressively been put in place during the study period, is suggested and discussed.
NASA Technical Reports Server (NTRS)
Famiglietti, J. S.; Wood, Eric F.
1993-01-01
A land surface hydrology parameterization for use in atmospheric GCM's is presented. The parameterization incorporates subgrid scale variability in topography, soils, soil moisture and precipitation. The framework of the model is the statistical distribution of a topography-soils index, which controls the local water balance fluxes, and is therefore taken to represent the large land area. Spatially variable water balance fluxes are integrated with respect to the topography-soils index to yield our large topography-soils distribution, and interval responses are weighted by the probability of occurrence of the interval. Grid square averaged land surface fluxes result. The model functions independently as a macroscale water balance model. Runoff ratio and evapotranspiration efficiency parameterizations are derived and are shown to depend on the spatial variability of the above mentioned properties and processes, as well as the dynamics of land surface-atmosphere interactions.
Spatial relationships between alcohol-related road crashes and retail alcohol availability.
Morrison, Christopher; Ponicki, William R; Gruenewald, Paul J; Wiebe, Douglas J; Smith, Karen
2016-05-01
This study examines spatial relationships between alcohol outlet density and the incidence of alcohol-related crashes. The few prior studies conducted in this area used relatively large spatial units; here we use highly resolved units from Melbourne, Australia (Statistical Area level 1 [SA1] units: mean land area=0.5 km(2); SD=2.2 km(2)), in order to assess different micro-scale spatial relationships for on- and off-premise outlets. Bayesian conditional autoregressive Poisson models were used to assess cross-sectional relationships of three-year counts of alcohol-related crashes (2010-2012) attended by Ambulance Victoria paramedics to densities of bars, restaurants, and off-premise outlets controlling for other land use, demographic and roadway characteristics. Alcohol-related crashes were not related to bar density within local SA1 units, but were positively related to bar density in adjacent SA1 units. Alcohol-related crashes were negatively related to off-premise outlet density in local SA1 units. Examined in one metropolitan area using small spatial units, bar density is related to greater crash risk in surrounding areas. Observed negative relationships for off-premise outlets may be because the origins and destinations of alcohol-affected journeys are in distal locations relative to outlets. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
geoknife: Reproducible web-processing of large gridded datasets
Read, Jordan S.; Walker, Jordan I.; Appling, Alison P.; Blodgett, David L.; Read, Emily K.; Winslow, Luke A.
2016-01-01
Geoprocessing of large gridded data according to overlap with irregular landscape features is common to many large-scale ecological analyses. The geoknife R package was created to facilitate reproducible analyses of gridded datasets found on the U.S. Geological Survey Geo Data Portal web application or elsewhere, using a web-enabled workflow that eliminates the need to download and store large datasets that are reliably hosted on the Internet. The package provides access to several data subset and summarization algorithms that are available on remote web processing servers. Outputs from geoknife include spatial and temporal data subsets, spatially-averaged time series values filtered by user-specified areas of interest, and categorical coverage fractions for various land-use types.
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.
A hierarchical spatial framework for forest landscape planning.
Pete Bettinger; Marie Lennette; K. Norman Johnson; Thomas A. Spies
2005-01-01
A hierarchical spatial framework for large-scale, long-term forest landscape planning is presented along with example policy analyses for a 560,000 ha area of the Oregon Coast Range. The modeling framework suggests utilizing the detail provided by satellite imagery to track forest vegetation condition and for representation of fine-scale features, such as riparian...
Landsat continuity: issues and opportunities for land cover monitoring
Michael A. Wulder; Joanne C. White; Samuel N. Goward; Jeffrey G. Masek; James R. Irons; Martin Herold; Warren B. Cohen; Thomas R. Loveland; Curtis E. Woodcock
2008-01-01
Initiated in 1972, the Landsat program has provided a continuous record of Earth observation for 35 years. The assemblage of Landsat spatial, spectral, and temporal resolutions, over a reasonably sized image extent, results in imagery that can be processed to represent land cover over large areas with an amount of spatial detail that is absolutely unique and...
Barron J. Orr; Grant M. Casady; Daniel G. Tuttle; Willem J. D. van Leeuwen; Laura E. Baker; Colleen I. McDonald; Stuart E. Marsh
2005-01-01
Ground-based ecosystem monitoring presents some practical challenges to natural resource managers and ecologists tasked with assessing vegetation dynamics across large areas through time. RangeView (http://rangeview.arizona.edu) provides online access to spatially and temporally explicit biweekly vegetation indices derived from satellite data. It also permits side-by-...
Environmental concern-based site screening of carbon dioxide geological storage in China.
Cai, Bofeng; Li, Qi; Liu, Guizhen; Liu, Lancui; Jin, Taotao; Shi, Hui
2017-08-08
Environmental impacts and risks related to carbon dioxide (CO 2 ) capture and storage (CCS) projects may have direct effects on the decision-making process during CCS site selection. This paper proposes a novel method of environmental optimization for CCS site selection using China's ecological red line approach. Moreover, this paper established a GIS based spatial analysis model of environmental optimization during CCS site selection by a large database. The comprehensive data coverage of environmental elements and fine 1 km spatial resolution were used in the database. The quartile method was used for value assignment for specific indicators including the prohibited index and restricted index. The screening results show that areas classified as having high environmental suitability (classes III and IV) in China account for 620,800 km 2 and 156,600 km 2 , respectively, and are mainly distributed in Inner Mongolia, Qinghai and Xinjiang. The environmental suitability class IV areas of Bayingol Mongolian Autonomous Prefecture, Hotan Prefecture, Aksu Prefecture, Hulunbuir, Xilingol League and other prefecture-level regions not only cover large land areas, but also form a continuous area in the three provincial-level administrative units. This study may benefit the national macro-strategic deployment and implementation of CCS spatial layout and environmental management in China.
NASA Astrophysics Data System (ADS)
Deo, Ram K.; Domke, Grant M.; Russell, Matthew B.; Woodall, Christopher W.; Andersen, Hans-Erik
2018-05-01
Aboveground biomass (AGB) estimates for regional-scale forest planning have become cost-effective with the free access to satellite data from sensors such as Landsat and MODIS. However, the accuracy of AGB predictions based on passive optical data depends on spatial resolution and spatial extent of target area as fine resolution (small pixels) data are associated with smaller coverage and longer repeat cycles compared to coarse resolution data. This study evaluated various spatial resolutions of Landsat-derived predictors on the accuracy of regional AGB models at three different sites in the eastern USA: Maine, Pennsylvania-New Jersey, and South Carolina. We combined national forest inventory data with Landsat-derived predictors at spatial resolutions ranging from 30–1000 m to understand the optimal spatial resolution of optical data for large-area (regional) AGB estimation. Ten generic models were developed using the data collected in 2014, 2015 and 2016, and the predictions were evaluated (i) at the county-level against the estimates of the USFS Forest Inventory and Analysis Program which relied on EVALIDator tool and national forest inventory data from the 2009–2013 cycle and (ii) within a large number of strips (~1 km wide) predicted via LiDAR metrics at 30 m spatial resolution. The county-level estimates by the EVALIDator and Landsat models were highly related (R 2 > 0.66), although the R 2 varied significantly across sites and resolution of predictors. The mean and standard deviation of county-level estimates followed increasing and decreasing trends, respectively, with models of coarser resolution. The Landsat-based total AGB estimates were larger than the LiDAR-based total estimates within the strips, however the mean of AGB predictions by LiDAR were mostly within one-standard deviations of the mean predictions obtained from the Landsat-based model at any of the resolutions. We conclude that satellite data at resolutions up to 1000 m provide acceptable accuracy for continental scale analysis of AGB.
Geospatial Technologies and Higher Education in Argentina
ERIC Educational Resources Information Center
Leguizamon, Saturnino
2010-01-01
The term "geospatial technologies" encompasses a large area of fields involving cartography, spatial analysis, geographic information system, remote sensing, global positioning systems and many others. These technologies should be expected to be available (as "natural tools") for a country with a large surface and a variety of…
Scale-dependent habitat use by a large free-ranging predator, the Mediterranean fin whale
NASA Astrophysics Data System (ADS)
Cotté, Cédric; Guinet, Christophe; Taupier-Letage, Isabelle; Mate, Bruce; Petiau, Estelle
2009-05-01
Since the heterogeneity of oceanographic conditions drives abundance, distribution, and availability of prey, it is essential to understand how foraging predators interact with their dynamic environment at various spatial and temporal scales. We examined the spatio-temporal relationships between oceanographic features and abundance of fin whales ( Balaenoptera physalus), the largest free-ranging predator in the Western Mediterranean Sea (WM), through two independent approaches. First, spatial modeling was used to estimate whale density, using waiting distance (the distance between detections) for fin whales along ferry routes across the WM, in relation to remotely sensed oceanographic parameters. At a large scale (basin and year), fin whales exhibited fidelity to the northern WM with a summer-aggregated and winter-dispersed pattern. At mesoscale (20-100 km), whales were found in colder, saltier (from an on-board system) and dynamic areas defined by steep altimetric and temperature gradients. Second, using an independent fin whale satellite tracking dataset, we showed that tracked whales were effectively preferentially located in favorable habitats, i.e. in areas of high predicted densities as identified by our previous model using oceanographic data contemporaneous to the tracking period. We suggest that the large-scale fidelity corresponds to temporally and spatially predictable habitat of whale favorite prey, the northern krill ( Meganyctiphanes norvegica), while mesoscale relationships are likely to identify areas of high prey concentration and availability.
NASA Astrophysics Data System (ADS)
Banerjee, Polash; Ghose, Mrinal Kanti; Pradhan, Ratika
2018-05-01
Spatial analysis of water quality impact assessment of highway projects in mountainous areas remains largely unexplored. A methodology is presented here for Spatial Water Quality Impact Assessment (SWQIA) due to highway-broadening-induced vehicular traffic change in the East district of Sikkim. Pollution load of the highway runoff was estimated using an Average Annual Daily Traffic-Based Empirical model in combination with mass balance model to predict pollution in the rivers within the study area. Spatial interpolation and overlay analysis were used for impact mapping. Analytic Hierarchy Process-Based Water Quality Status Index was used to prepare a composite impact map. Model validation criteria, cross-validation criteria, and spatial explicit sensitivity analysis show that the SWQIA model is robust. The study shows that vehicular traffic is a significant contributor to water pollution in the study area. The model is catering specifically to impact analysis of the concerned project. It can be an aid for decision support system for the project stakeholders. The applicability of SWQIA model needs to be explored and validated in the context of a larger set of water quality parameters and project scenarios at a greater spatial scale.
Biological tissue imaging with a position and time sensitive pixelated detector.
Jungmann, Julia H; Smith, Donald F; MacAleese, Luke; Klinkert, Ivo; Visser, Jan; Heeren, Ron M A
2012-10-01
We demonstrate the capabilities of a highly parallel, active pixel detector for large-area, mass spectrometric imaging of biological tissue sections. A bare Timepix assembly (512 × 512 pixels) is combined with chevron microchannel plates on an ion microscope matrix-assisted laser desorption time-of-flight mass spectrometer (MALDI TOF-MS). The detector assembly registers position- and time-resolved images of multiple m/z species in every measurement frame. We prove the applicability of the detection system to biomolecular mass spectrometry imaging on biologically relevant samples by mass-resolved images from Timepix measurements of a peptide-grid benchmark sample and mouse testis tissue slices. Mass-spectral and localization information of analytes at physiologic concentrations are measured in MALDI-TOF-MS imaging experiments. We show a high spatial resolution (pixel size down to 740 × 740 nm(2) on the sample surface) and a spatial resolving power of 6 μm with a microscope mode laser field of view of 100-335 μm. Automated, large-area imaging is demonstrated and the Timepix' potential for fast, large-area image acquisition is highlighted.
Bryan, Brett Anthony; Raymond, Christopher Mark; Crossman, Neville David; King, Darran
2011-02-01
Consideration of the social values people assign to relatively undisturbed native ecosystems is critical for the success of science-based conservation plans. We used an interview process to identify and map social values assigned to 31 ecosystem services provided by natural areas in an agricultural landscape in southern Australia. We then modeled the spatial distribution of 12 components of ecological value commonly used in setting spatial conservation priorities. We used the analytical hierarchy process to weight these components and used multiattribute utility theory to combine them into a single spatial layer of ecological value. Social values assigned to natural areas were negatively correlated with ecological values overall, but were positively correlated with some components of ecological value. In terms of the spatial distribution of values, people valued protected areas, whereas those natural areas underrepresented in the reserve system were of higher ecological value. The habitats of threatened animal species were assigned both high ecological value and high social value. Only small areas were assigned both high ecological value and high social value in the study area, whereas large areas of high ecological value were of low social value, and vice versa. We used the assigned ecological and social values to identify different conservation strategies (e.g., information sharing, community engagement, incentive payments) that may be effective for specific areas. We suggest that consideration of both ecological and social values in selection of conservation strategies can enhance the success of science-based conservation planning. ©2010 Society for Conservation Biology.
Challenges on Java’s small city spatial planning
NASA Astrophysics Data System (ADS)
Wirawan, B.; Tambunan, J. R.
2018-05-01
Most Indonesians nowadays live in the urban area, due to urbanization. 60 percent of the inhabitants of Java, the most populous island in Indonesia, will live in the urban area by 2010, a figure that is higher than the national average of 55 percent. Urbanization has brought a large influx of newcomers not only into the metropolitan or large cities, but also into small and medium cities. One of urbanization’s most concerning impacts is urban sprawl that harms sustainability. There is a dearth of academic literature studying the phenomenon of urban sprawl in Indonesian small cities. Urban sprawl in small cities is commonly ignored, considered as a contained problem the solution for which is a simple use of local spatial plan. Unfortunately, for Indonesia, this solution is difficult to implement because city spatial plans works only within administrative jurisdictions, whilst the urban sprawls themselves generally occur across the borders of different administrative jurisdictions. This study studies urban sprawls occurring in several small cities in Java. While those cities already have spatial plan, most were the general spatial plan (Rencana Tata Ruang Wilayah Kota/Kabupaten) that operates only within the city’s administrative jurisdiction. We are unable to find detailed strategies in these cities to deal with urban sprawl. We also found that all spatial plans are unable to come up with urban growth boundary strategy. Finally, we are also unable to find integrated detailed spatial plan among those cities to answer the urban sprawl situation.
A model for spatial variations in life expectancy; mortality in Chinese regions in 2000.
Congdon, Peter
2007-05-02
Life expectancy in China has been improving markedly but health gains have been uneven and there is inequality in survival chances between regions and in rural as against urban areas. This paper applies a statistical modelling approach to mortality data collected in conjunction with the 2000 Census to formally assess spatial mortality contrasts in China. The modelling approach provides interpretable summary parameters (e.g. the relative mortality risk in rural as against urban areas) and is more parsimonious in terms of parameters than the conventional life table model. Predictive fit is assessed both globally and at the level of individual five year age groups. A proportional model (age and area effects independent) has a worse fit than one allowing age-area interactions following a bilinear form. The best fit is obtained by allowing for child and oldest age mortality rates to vary spatially. There is evidence that age (21 age groups) and area (31 Chinese administrative divisions) are not proportional (i.e. independent) mortality risk factors. In fact, spatial contrasts are greatest at young ages. There is a pronounced rural survival disadvantage, and large differences in life expectancy between provinces.
The challenges of marine spatial planning in the Arctic: Results from the ACCESS programme.
Edwards, Rosemary; Evans, Alan
2017-12-01
Marine spatial planning is increasingly used to manage the demands on marine areas, both spatially and temporally, where several different users may compete for resources or space, to ensure that development is as sustainable as possible. Diminishing sea-ice coverage in the Arctic will allow for potential increases in economic exploitation, and failure to plan for cross-sectoral management could have negative economic and environmental results. During the ACCESS programme, a marine spatial planning tool was developed for the Arctic, enabling the integrated study of human activities related to hydrocarbon exploitation, shipping and fisheries, and the possible environmental impacts, within the context of the next 30 years of climate change. In addition to areas under national jurisdiction, the Arctic Ocean contains a large area of high seas. Resources and ecosystems extend across political boundaries. We use three examples to highlight the need for transboundary planning and governance to be developed at a regional level.
NASA Astrophysics Data System (ADS)
Goldenberg, Romain; Kalantari, Zahra; Destouni, Georgia
2017-04-01
More than half of the world's population lives in cities, a proportion expected to increase to two thirds by 2050 (United Nations (UN), 2015). In this study, we investigate the spatial relationships that may exist between income and/or nationality homogeneity/heterogeneity levels of urban populations and their accessibility to local green-blue areas as possible nature-based solutions for sustainable urban design. For this investigation, we consider as a concrete case study the urban region of Stockholm, Sweden, for which we compile and use available land-cover and vegetation density data (the latter in terms of Normalised Difference Vegetation Index, NDVI) in order to identify and assess the spatial distributions of various green-blue area types and aspects. We further combine this data with spatial distribution data for population density, income and nationality, as well as with road-network data for assessing population travel times to nearby green-blue areas within the region. The present study results converge with those of other recent studies in showing large socio-economic-ethnic segregation in the Stockholm region. Moreover, the present data combination and analysis also show large spatial differences in and important socio-economic-ethnic correlations with accessibility to local green areas and nearby water bodies. Specifically, population income and share of Swedish nationals are well correlated in this region, with increases in both of these variables implying greater possibility to choose where to live within the region. The living choices of richer and more homogeneous (primarily Swedish) population parts are then found to be areas with greater local vegetation density (local green areas as identified by high-resolution NDVI data) and greater area extent of nearby water bodies (blue areas). For comparison, no such correlation is found between increased income or Swedish nationality homogeneity and accessibility to nearby forest areas (overall green area extent) or built facilities for recreation and sports. The found living choice correlations point at the importance of green-blue area parts as possible nature-based solutions in urban design and planning, with potential to improve wellbeing and social sustainability for the whole urban population and not just its rich component.
Small-Area Estimation of Spatial Access to Care and Its Implications for Policy.
Gentili, Monica; Isett, Kim; Serban, Nicoleta; Swann, Julie
2015-10-01
Local or small-area estimates to capture emerging trends across large geographic regions are critical in identifying and addressing community-level health interventions. However, they are often unavailable due to lack of analytic capabilities in compiling and integrating extensive datasets and complementing them with the knowledge about variations in state-level health policies. This study introduces a modeling approach for small-area estimation of spatial access to pediatric primary care that is data "rich" and mathematically rigorous, integrating data and health policy in a systematic way. We illustrate the sensitivity of the model to policy decision making across large geographic regions by performing a systematic comparison of the estimates at the census tract and county levels for Georgia and California. Our results show the proposed approach is able to overcome limitations of other existing models by capturing patient and provider preferences and by incorporating possible changes in health policies. The primary finding is systematic underestimation of spatial access, and inaccurate estimates of disparities across population and across geography at the county level with respect to those at the census tract level with implications on where to focus and which type of interventions to consider.
Farmer data sourcing. The case study of the spatial soil information maps in South Tyrol.
NASA Astrophysics Data System (ADS)
Della Chiesa, Stefano; Niedrist, Georg; Thalheimer, Martin; Hafner, Hansjörg; La Cecilia, Daniele
2017-04-01
Nord-Italian region South Tyrol is Europe's largest apple growing area exporting ca. 15% in Europe and 2% worldwide. Vineyards represent ca. 1% of Italian production. In order to deliver high quality food, most of the farmers in South Tyrol follow sustainable farming practices. One of the key practice is the sustainable soil management, where farmers collect regularly (each 5 years) soil samples and send for analyses to improve cultivation management, yield and finally profitability. However, such data generally remain inaccessible. On this regard, in South Tyrol, private interests and the public administration have established a long tradition of collaboration with the local farming industry. This has granted to the collection of large spatial and temporal database of soil analyses along all the cultivated areas. Thanks to this best practice, information on soil properties are centralized and geocoded. The large dataset consist mainly in soil information of texture, humus content, pH and microelements availability such as, K, Mg, Bor, Mn, Cu Zn. This data was finally spatialized by mean of geostatistical methods and several high-resolution digital maps were created. In this contribution, we present the best practice where farmers data source soil information in South Tyrol. Show the capability of a large spatial-temporal geocoded soil dataset to reproduce detailed digital soil property maps and to assess long-term changes in soil properties. Finally, implication and potential application are discussed.
Muška, Milan; Tušer, Michal; Frouzová, Jaroslava; Mrkvička, Tomáš; Ricard, Daniel; Seďa, Jaromír; Morelli, Federico; Kubečka, Jan
2018-03-29
Understanding spatial distribution of organisms in heterogeneous environment remains one of the chief issues in ecology. Spatial organization of freshwater fish was investigated predominantly on large-scale, neglecting important local conditions and ecological processes. However, small-scale processes are of an essential importance for individual habitat preferences and hence structuring trophic cascades and species coexistence. In this work, we analysed the real-time spatial distribution of pelagic freshwater fish in the Římov Reservoir (Czechia) observed by hydroacoustics in relation to important environmental predictors during 48 hours at 3-h interval. Effect of diurnal cycle was revealed of highest significance in all spatial models with inverse trends between fish distribution and predictors in day and night in general. Our findings highlighted daytime pelagic fish distribution as highly aggregated, with general fish preferences for central, deep and highly illuminated areas, whereas nighttime distribution was more disperse and fish preferred nearshore steep sloped areas with higher depth. This turnover suggests prominent movements of significant part of fish assemblage between pelagic and nearshore areas on a diel basis. In conclusion, hydroacoustics, GIS and spatial modelling proved as valuable tool for predicting local fish distribution and elucidate its drivers, which has far reaching implications for understanding freshwater ecosystem functioning.
Large-scale conservation planning in a multinational marine environment: cost matters.
Mazor, Tessa; Giakoumi, Sylvaine; Kark, Salit; Possingham, Hugh P
2014-07-01
Explicitly including cost in marine conservation planning is essential for achieving feasible and efficient conservation outcomes. Yet, spatial priorities for marine conservation are still often based solely on biodiversity hotspots, species richness, and/or cumulative threat maps. This study aims to provide an approach for including cost when planning large-scale Marine Protected Area (MPA) networks that span multiple countries. Here, we explore the incorporation of cost in the complex setting of the Mediterranean Sea. In order to include cost in conservation prioritization, we developed surrogates that account for revenue from multiple marine sectors: commercial fishing, noncommercial fishing, and aquaculture. Such revenue can translate into an opportunity cost for the implementation of an MPA network. Using the software Marxan, we set conservation targets to protect 10% of the distribution of 77 threatened marine species in the Mediterranean Sea. We compared nine scenarios of opportunity cost by calculating the area and cost required to meet our targets. We further compared our spatial priorities with those that are considered consensus areas by several proposed prioritization schemes in the Mediterranean Sea, none of which explicitly considers cost. We found that for less than 10% of the Sea's area, our conservation targets can be achieved while incurring opportunity costs of less than 1%. In marine systems, we reveal that area is a poor cost surrogate and that the most effective surrogates are those that account for multiple sectors or stakeholders. Furthermore, our results indicate that including cost can greatly influence the selection of spatial priorities for marine conservation of threatened species. Although there are known limitations in multinational large-scale planning, attempting to devise more systematic and rigorous planning methods is especially critical given that collaborative conservation action is on the rise and global financial crisis restricts conservation investments.
Large-area settlement pattern recognition from Landsat-8 data
NASA Astrophysics Data System (ADS)
Wieland, Marc; Pittore, Massimiliano
2016-09-01
The study presents an image processing and analysis pipeline that combines object-based image analysis with a Support Vector Machine to derive a multi-layered settlement product from Landsat-8 data over large areas. 43 image scenes are processed over large parts of Central Asia (Southern Kazakhstan, Kyrgyzstan, Tajikistan and Eastern Uzbekistan). The main tasks tackled by this work include built-up area identification, settlement type classification and urban structure types pattern recognition. Besides commonly used accuracy assessments of the resulting map products, thorough performance evaluations are carried out under varying conditions to tune algorithm parameters and assess their applicability for the given tasks. As part of this, several research questions are being addressed. In particular the influence of the improved spatial and spectral resolution of Landsat-8 on the SVM performance to identify built-up areas and urban structure types are evaluated. Also the influence of an extended feature space including digital elevation model features is tested for mountainous regions. Moreover, the spatial distribution of classification uncertainties is analyzed and compared to the heterogeneity of the building stock within the computational unit of the segments. The study concludes that the information content of Landsat-8 images is sufficient for the tested classification tasks and even detailed urban structures could be extracted with satisfying accuracy. Freely available ancillary settlement point location data could further improve the built-up area classification. Digital elevation features and pan-sharpening could, however, not significantly improve the classification results. The study highlights the importance of dynamically tuned classifier parameters, and underlines the use of Shannon entropy computed from the soft answers of the SVM as a valid measure of the spatial distribution of classification uncertainties.
Falasca, N W; D'Ascenzo, S; Di Domenico, A; Onofrj, M; Tommasi, L; Laeng, B; Franciotti, R
2015-04-01
Magnetoencephalography was recorded during a matching-to-sample plus cueing paradigm, in which participants judged the occurrence of changes in either categorical (CAT) or coordinate (COO) spatial relations. Previously, parietal and frontal lobes were identified as key areas in processing spatial relations and it was shown that each hemisphere was differently involved and modulated by the scope of the attention window (e.g. a large and small cue). In this study, Granger analysis highlighted the patterns of causality among involved brain areas--the direction of information transfer ran from the frontal to the visual cortex in the right hemisphere, whereas it ran in the opposite direction in the left side. Thus, the right frontal area seems to exert top-down influence, supporting the idea that, in this task, top-down signals are selectively related to the right side. Additionally, for CAT change preceded by a small cue, the right frontal gyrus was not involved in the information transfer, indicating a selective specialization of the left hemisphere for this condition. The present findings strengthen the conclusion of the presence of a remarkable hemispheric specialization for spatial relation processing and illustrate the complex interactions between the lateralized parts of the neural network. Moreover, they illustrate how focusing attention over large or small regions of the visual field engages these lateralized networks differently, particularly in the frontal regions of each hemisphere, consistent with the theory that spatial relation judgements require a fronto-parietal network in the left hemisphere for categorical relations and on the right hemisphere for coordinate spatial processing. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
Adapting geostatistics to analyze spatial and temporal trends in weed populations
USDA-ARS?s Scientific Manuscript database
Geostatistics were originally developed in mining to estimate the location, abundance and quality of ore over large areas from soil samples to optimize future mining efforts. Here, some of these methods were adapted to weeds to account for a limited distribution area (i.e., inside a field), variatio...
Spatially explicit identification of status and changes in ecological conditions over large, regional areas is key to targeting and prioritizing areas for potential further study and environmental protection and restoration. A critical limitation to this point has been our abili...
Spatially explicit identification of changes in ecological conditions over large areas is key to targeting and prioritizing areas for environmental protection and restoration by managers at watershed, basin, and regional scales. A critical limitation to this point has bee...
Large constructed wetlands, known as stormwater treatment areas (STAs), have been deployed to remove phosphorus (P) in drainage waters before discharge into the Everglades in South Florida, USA. Their P removal performance depends on internal P cycling under typically hydrated, b...
Spatial Variability of Sources and Mixing State of Atmospheric Particles in a Metropolitan Area.
Ye, Qing; Gu, Peishi; Li, Hugh Z; Robinson, Ellis S; Lipsky, Eric; Kaltsonoudis, Christos; Lee, Alex K Y; Apte, Joshua S; Robinson, Allen L; Sullivan, Ryan C; Presto, Albert A; Donahue, Neil M
2018-05-30
Characterizing intracity variations of atmospheric particulate matter has mostly relied on fixed-site monitoring and quantifying variability in terms of different bulk aerosol species. In this study, we performed ground-based mobile measurements using a single-particle mass spectrometer to study spatial patterns of source-specific particles and the evolution of particle mixing state in 21 areas in the metropolitan area of Pittsburgh, PA. We selected sampling areas based on traffic density and restaurant density with each area ranging from 0.2 to 2 km 2 . Organics dominate particle composition in all of the areas we sampled while the sources of organics differ. The contribution of particles from traffic and restaurant cooking varies greatly on the neighborhood scale. We also investigate how primary and aged components in particles mix across the urban scale. Lastly we quantify and map the particle mixing state for all areas we sampled and discuss the overall pattern of mixing state evolution and its implications. We find that in the upwind and downwind of the urban areas, particles are more internally mixed while in the city center, particle mixing state shows large spatial heterogeneity that is mostly driven by emissions. This study is to our knowledge, the first study to perform fine spatial scale mapping of particle mixing state using ground-based mobile measurement and single-particle mass spectrometry.
Mapping rice areas of South Asia using MODIS multitemporal data
NASA Astrophysics Data System (ADS)
Gumma, Murali Krishna; Nelson, Andrew; Thenkabail, Prasad S.; Singh, Amrendra N.
2011-01-01
Our goal is to map the rice areas of six South Asian countries using moderate-resolution imaging spectroradiometer (MODIS) time-series data for the time period 2000 to 2001. South Asia accounts for almost 40% of the world's harvested rice area and is also home to 74% of the population that lives on less than $2.00 a day. The population of the region is growing faster than its ability to produce rice. Thus, accurate and timely assessment of where and how rice is cultivated is important to craft food security and poverty alleviation strategies. We used a time series of eight-day, 500-m spatial resolution composite images from the MODIS sensor to produce rice maps and rice characteristics (e.g., intensity of cropping, cropping calendar) taking data for the years 2000 to 2001 and by adopting a suite of methods that include spectral matching techniques, decision trees, and ideal temporal profile data banks to rapidly identify and classify rice areas over large spatial extents. These methods are used in conjunction with ancillary spatial data sets (e.g., elevation, precipitation), national statistics, and maps, and a large volume of field-plot data. The resulting rice maps and statistics are compared against a subset of independent field-plot points and the best available subnational statistics on rice areas for the main crop growing season (kharif season). A fuzzy classification accuracy assessment for the 2000 to 2001 rice-map product, based on field-plot data, demonstrated accuracies from 67% to 100% for individual rice classes, with an overall accuracy of 80% for all classes. Most of the mixing was within rice classes. The derived physical rice area was highly correlated with the subnational statistics with R2 values of 97% at the district level and 99% at the state level for 2000 to 2001. These results suggest that the methods, approaches, algorithms, and data sets we used are ideal for rapid, accurate, and large-scale mapping of paddy rice as well as for generating their statistics over large areas.
Mapping rice areas of South Asia using MODIS multitemporal data
Gumma, M.K.; Nelson, A.; Thenkabail, P.S.; Singh, A.N.
2011-01-01
Our goal is to map the rice areas of six South Asian countries using moderate-resolution imaging spectroradiometer (MODIS) time-series data for the time period 2000 to 2001. South Asia accounts for almost 40% of the world's harvested rice area and is also home to 74% of the population that lives on less than $2.00 a day. The population of the region is growing faster than its ability to produce rice. Thus, accurate and timely assessment of where and how rice is cultivated is important to craft food security and poverty alleviation strategies. We used a time series of eight-day, 500-m spatial resolution composite images from the MODIS sensor to produce rice maps and rice characteristics (e.g., intensity of cropping, cropping calendar) taking data for the years 2000 to 2001 and by adopting a suite of methods that include spectral matching techniques, decision trees, and ideal temporal profile data banks to rapidly identify and classify rice areas over large spatial extents. These methods are used in conjunction with ancillary spatial data sets (e.g., elevation, precipitation), national statistics, and maps, and a large volume of field-plot data. The resulting rice maps and statistics are compared against a subset of independent field-plot points and the best available subnational statistics on rice areas for the main crop growing season (kharif season). A fuzzy classification accuracy assessment for the 2000 to 2001 rice-map product, based on field-plot data, demonstrated accuracies from 67% to 100% for individual rice classes, with an overall accuracy of 80% for all classes. Most of the mixing was within rice classes. The derived physical rice area was highly correlated with the subnational statistics with R2 values of 97% at the district level and 99% at the state level for 2000 to 2001. These results suggest that the methods, approaches, algorithms, and data sets we used are ideal for rapid, accurate, and large-scale mapping of paddy rice as well as for generating their statistics over large areas. ?? 2011 Society of Photo-Optical Instrumentation Engineers (SPIE).
Operational monitoring of land-cover change using multitemporal remote sensing data
NASA Astrophysics Data System (ADS)
Rogan, John
2005-11-01
Land-cover change, manifested as either land-cover modification and/or conversion, can occur at all spatial scales, and changes at local scales can have profound, cumulative impacts at broader scales. The implication of operational land-cover monitoring is that researchers have access to a continuous stream of remote sensing data, with the long term goal of providing for consistent and repetitive mapping. Effective large area monitoring of land-cover (i.e., >1000 km2) can only be accomplished by using remotely sensed images as an indirect data source in land-cover change mapping and as a source for land-cover change model projections. Large area monitoring programs face several challenges: (1) choice of appropriate classification scheme/map legend over large, topographically and phenologically diverse areas; (2) issues concerning data consistency and map accuracy (i.e., calibration and validation); (3) very large data volumes; (4) time consuming data processing and interpretation. Therefore, this dissertation research broadly addresses these challenges in the context of examining state-of-the-art image pre-processing, spectral enhancement, classification, and accuracy assessment techniques to assist the California Land-cover Mapping and Monitoring Program (LCMMP). The results of this dissertation revealed that spatially varying haze can be effectively corrected from Landsat data for the purposes of change detection. The Multitemporal Spectral Mixture Analysis (MSMA) spectral enhancement technique produced more accurate land-cover maps than those derived from the Multitemporal Kauth Thomas (MKT) transformation in northern and southern California study areas. A comparison of machine learning classifiers showed that Fuzzy ARTMAP outperformed two classification tree algorithms, based on map accuracy and algorithm robustness. Variation in spatial data error (positional and thematic) was explored in relation to environmental variables using geostatistical interpolation techniques. Finally, the land-cover modification maps generated for three time intervals (1985--1990--1996--2000), with nine change-classes revealed important variations in land-cover gain and loss between northern and southern California study areas.
Broms, Kristin M; Johnson, Devin S; Altwegg, Res; Conquest, Loveday L
2014-03-01
Determining the range of a species and exploring species--habitat associations are central questions in ecology and can be answered by analyzing presence--absence data. Often, both the sampling of sites and the desired area of inference involve neighboring sites; thus, positive spatial autocorrelation between these sites is expected. Using survey data for the Southern Ground Hornbill (Bucorvus leadbeateri) from the Southern African Bird Atlas Project, we compared advantages and disadvantages of three increasingly complex models for species occupancy: an occupancy model that accounted for nondetection but assumed all sites were independent, and two spatial occupancy models that accounted for both nondetection and spatial autocorrelation. We modeled the spatial autocorrelation with an intrinsic conditional autoregressive (ICAR) model and with a restricted spatial regression (RSR) model. Both spatial models can readily be applied to any other gridded, presence--absence data set using a newly introduced R package. The RSR model provided the best inference and was able to capture small-scale variation that the other models did not. It showed that ground hornbills are strongly dependent on protected areas in the north of their South African range, but less so further south. The ICAR models did not capture any spatial autocorrelation in the data, and they took an order, of magnitude longer than the RSR models to run. Thus, the RSR occupancy model appears to be an attractive choice for modeling occurrences at large spatial domains, while accounting for imperfect detection and spatial autocorrelation.
Suzanne M. Joy; R. M. Reich; Richard T. Reynolds
2003-01-01
Traditional land classification techniques for large areas that use Landsat Thematic Mapper (TM) imagery are typically limited to the fixed spatial resolution of the sensors (30m). However, the study of some ecological processes requires land cover classifications at finer spatial resolutions. We model forest vegetation types on the Kaibab National Forest (KNF) in...
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.
Utilizing NASA DISCOVER-AQ Data to Examine Spatial Gradients in Complex Emission Environments
NASA Astrophysics Data System (ADS)
Buzanowicz, M. E.; Moore, W.; Crawford, J. H.; Schroeder, J.
2017-12-01
Although many regulations have been enacted with the goal of improving air quality, many parts of the US are still classified as `non-attainment areas' because they frequently violate federal air quality standards. Adequately monitoring the spatial distribution of pollutants both within and outside of non-attainment areas has been an ongoing challenge for regulators. Observations of near-surface pollution from space-based platforms would provide an unprecedented view of the spatial distribution of pollution, but this goal has not yet been realized due to fundamental limitations of satellites, specifically because the footprint size of satellite measurements may not be sufficiently small enough to capture true gradients in pollution, and rather represents an average over a large area. NASA's DISCOVER-AQ was a multi-year field campaign aimed at improving our understanding of the role that remote sensing, including satellite-based remote sensing, could play in air quality monitoring systems. DISCOVER-AQ data will be utilized to create a metric to examine spatial gradients and how satellites can capture those gradients in areas with complex emission environments. Examining horizontal variability within a vertical column is critical to understanding mixing within the atmosphere. Aircraft spirals conducted during DISCOVER-AQ were divided into octants, and averages of a given a species were calculated, with certain points receiving a flag. These flags were determined by calculating gradients between subsequent octants. Initial calculations have shown that over areas with large point source emissions, such as Platteville and Denver-La Casa in Colorado, and Essex, Maryland, satellite retrievals may not adequately capture spatial variability in the atmosphere, thus complicating satellite inversion techniques and limiting our ability to understand human exposure on sub-grid scales. Further calculations at other locations and for other trace gases are necessary to determine the effects of vertical variability within the atmosphere.
Ramesh, Tharmalingam; Kalle, Riddhika; Rosenlund, Havard; Downs, Colleen T
2017-03-01
Identifying the primary causes affecting population densities and distribution of flagship species are necessary in developing sustainable management strategies for large carnivore conservation. We modeled drivers of spatial density of the common leopard ( Panthera pardus ) using a spatially explicit capture-recapture-Bayesian approach to understand their population dynamics in the Maputaland Conservation Unit, South Africa. We camera-trapped leopards in four protected areas (PAs) of varying sizes and disturbance levels covering 198 camera stations. Ours is the first study to explore the effects of poaching level, abundance of prey species (small, medium, and large), competitors (lion Panthera leo and spotted hyenas Crocuta crocuta ), and habitat on the spatial distribution of common leopard density. Twenty-six male and 41 female leopards were individually identified and estimated leopard density ranged from 1.6 ± 0.62/100 km 2 (smallest PA-Ndumo) to 8.4 ± 1.03/100 km 2 (largest PA-western shores). Although dry forest thickets and plantation habitats largely represented the western shores, the plantation areas had extremely low leopard density compared to native forest. We found that leopard density increased in areas when low poaching levels/no poaching was recorded in dry forest thickets and with high abundance of medium-sized prey, but decreased with increasing abundance of lion. Because local leopard populations are vulnerable to extinction, particularly in smaller PAs, the long-term sustainability of leopard populations depend on developing appropriate management strategies that consider a combination of multiple factors to maintain their optimal habitats.
Identifying western yellow-billed cuckoo breeding habitat with a dual modelling approach
Johnson, Matthew J.; Hatten, James R.; Holmes, Jennifer A.; Shafroth, Patrick B.
2017-01-01
The western population of the yellow-billed cuckoo (Coccyzus americanus) was recently listed as threatened under the federal Endangered Species Act. Yellow-billed cuckoo conservation efforts require the identification of features and area requirements associated with high quality, riparian forest habitat at spatial scales that range from nest microhabitat to landscape, as well as lower-suitability areas that can be enhanced or restored. Spatially explicit models inform conservation efforts by increasing ecological understanding of a target species, especially at landscape scales. Previous yellow-billed cuckoo modelling efforts derived plant-community maps from aerial photography, an expensive and oftentimes inconsistent approach. Satellite models can remotely map vegetation features (e.g., vegetation density, heterogeneity in vegetation density or structure) across large areas with near perfect repeatability, but they usually cannot identify plant communities. We used aerial photos and satellite imagery, and a hierarchical spatial scale approach, to identify yellow-billed cuckoo breeding habitat along the Lower Colorado River and its tributaries. Aerial-photo and satellite models identified several key features associated with yellow-billed cuckoo breeding locations: (1) a 4.5 ha core area of dense cottonwood-willow vegetation, (2) a large native, heterogeneously dense forest (72 ha) around the core area, and (3) moderately rough topography. The odds of yellow-billed cuckoo occurrence decreased rapidly as the amount of tamarisk cover increased or when cottonwood-willow vegetation was limited. We achieved model accuracies of 75–80% in the project area the following year after updating the imagery and location data. The two model types had very similar probability maps, largely predicting the same areas as high quality habitat. While each model provided unique information, a dual-modelling approach provided a more complete picture of yellow-billed cuckoo habitat requirements and will be useful for management and conservation activities.
Kane, Van R.; North, Malcolm P.; Lutz, James A.; Churchill, Derek J.; Roberts, Susan L.; Smith, Douglas F.; McGaughey, Robert J.; Kane, Jonathan T.; Brooks, Matthew L.
2014-01-01
Mosaics of tree clumps and openings are characteristic of forests dominated by frequent, low- and moderate-severity fires. When restoring these fire-suppressed forests, managers often try to reproduce these structures to increase ecosystem resilience. We examined unburned and burned forest structures for 1937 0.81 ha sample areas in Yosemite National Park, USA. We estimated severity for fires from 1984 to 2010 using the Landsat-derived Relativized differenced Normalized Burn Ratio (RdNBR) and measured openings and canopy clumps in five height strata using airborne LiDAR data. Because our study area lacked concurrent field data, we identified methods to allow structural analysis using LiDAR data alone. We found three spatial structures, canopy-gap, clump-open, and open, that differed in spatial arrangement and proportion of canopy and openings. As fire severity increased, the total area in canopy decreased while the number of clumps increased, creating a patchwork of openings and multistory tree clumps. The presence of openings > 0.3 ha, an approximate minimum gap size needed to favor shade-intolerant pine regeneration, increased rapidly with loss of canopy area. The range and variation of structures for a given fire severity were specific to each forest type. Low- to moderate-severity fires best replicated the historic clump-opening patterns that were common in forests with frequent fire regimes. Our results suggest that managers consider the following goals for their forest restoration: 1) reduce total canopy cover by breaking up large contiguous areas into variable-sized tree clumps and scattered large individual trees; 2) create a range of opening sizes and shapes, including ~ 50% of the open area in gaps > 0.3 ha; 3) create multistory clumps in addition to single story clumps; 4) retain historic densities of large trees; and 5) vary treatments to include canopy-gap, clump-open, and open mosaics across project areas to mimic the range of patterns found for each forest type in our study.
Urbieta, Itziar R.; Zavala, Gonzalo; Bedia, Joaquin; Gutierrez, Jose M.; San Miguel-Ayanz, Jesus; Camia, Andrea; Keeley, Jon E.; Moreno, Jose M.
2015-01-01
Climate has a strong influence on fire activity, varying across time and space. We analyzed the relationships between fire–weather conditions during the main fire season and antecedent water-balance conditions and fires in two Mediterranean-type regions with contrasted management histories: five southern countries of the European Union (EUMED)(all fires); the Pacific western coast of the USA (California and Oregon, PWUSA)(national forest fires). Total number of fires (≥1 ha), number of large fires (≥100 ha) and area burned were related to mean seasonal fire weather index (FWI), number of days over the 90th percentile of the FWI, and to the standardized precipitation-evapotranspiration index (SPEI) from the preceding 3 (spring) or 8 (autumn through spring) months. Calculations were made at three spatial aggregations in each area, and models related first-difference (year-to-year change) of fires and FWI/climate variables to minimize autocorrelation. An increase in mean seasonal FWI resulted in increases in the three fire variables across spatial scales in both regions. SPEI contributed little to explain fires, with few exceptions. Negative water-balance (dry) conditions from autumn through spring (SPEI8) were generally more important than positive conditions (moist) in spring (SPEI3), both of which contributed positively to fires. The R2 of the models generally improved with increasing area of aggregation. For total number of fires and area burned, the R2 of the models tended to decrease with increasing mean seasonal FWI. Thus, fires were more susceptible to change with climate variability in areas with less amenable conditions for fires (lower FWI) than in areas with higher mean FWI values. The relationships were similar in both regions, albeit weaker in PWUSA, probably due to the wider latitudinal gradient covered in PWUSA than in EUMED. The large variance explained by some of the models indicates that large-scale seasonal forecast could help anticipating fire activity in the investigated areas.
NASA Astrophysics Data System (ADS)
Urbieta, Itziar R.; Zavala, Gonzalo; Bedia, Joaquín; Gutiérrez, José M.; San Miguel-Ayanz, Jesús; Camia, Andrea; Keeley, Jon E.; Moreno, José M.
2015-11-01
Climate has a strong influence on fire activity, varying across time and space. We analyzed the relationships between fire-weather conditions during the main fire season and antecedent water-balance conditions and fires in two Mediterranean-type regions with contrasted management histories: five southern countries of the European Union (EUMED)(all fires); the Pacific western coast of the USA (California and Oregon, PWUSA)(national forest fires). Total number of fires (≥1 ha), number of large fires (≥100 ha) and area burned were related to mean seasonal fire weather index (FWI), number of days over the 90th percentile of the FWI, and to the standardized precipitation-evapotranspiration index (SPEI) from the preceding 3 (spring) or 8 (autumn through spring) months. Calculations were made at three spatial aggregations in each area, and models related first-difference (year-to-year change) of fires and FWI/climate variables to minimize autocorrelation. An increase in mean seasonal FWI resulted in increases in the three fire variables across spatial scales in both regions. SPEI contributed little to explain fires, with few exceptions. Negative water-balance (dry) conditions from autumn through spring (SPEI8) were generally more important than positive conditions (moist) in spring (SPEI3), both of which contributed positively to fires. The R2 of the models generally improved with increasing area of aggregation. For total number of fires and area burned, the R2 of the models tended to decrease with increasing mean seasonal FWI. Thus, fires were more susceptible to change with climate variability in areas with less amenable conditions for fires (lower FWI) than in areas with higher mean FWI values. The relationships were similar in both regions, albeit weaker in PWUSA, probably due to the wider latitudinal gradient covered in PWUSA than in EUMED. The large variance explained by some of the models indicates that large-scale seasonal forecast could help anticipating fire activity in the investigated areas.
Mapping canopy gap fraction and leaf area index at continent-scale from satellite lidar
NASA Astrophysics Data System (ADS)
Mahoney, C.; Hopkinson, C.; Held, A. A.
2015-12-01
Information on canopy cover is essential for understanding spatial and temporal variability in vegetation biomass, local meteorological processes and hydrological transfers within vegetated environments. Gap fraction (GF), an index of canopy cover, is often derived over large areas (100's km2) via airborne laser scanning (ALS), estimates of which are reasonably well understood. However, obtaining country-wide estimates is challenging due to the lack of spatially distributed point cloud data. The Geoscience Laser Altimeter System (GLAS) removes spatial limitations, however, its large footprint nature and continuous waveform data measurements make derivations of GF challenging. ALS data from 3 Australian sites are used as a basis to scale-up GF estimates to GLAS footprint data by the use of a physically-based Weibull function. Spaceborne estimates of GF are employed in conjunction with supplementary predictor variables in the predictive Random Forest algorithm to yield country-wide estimates at a 250 m spatial resolution; country-wide estimates are accompanied with uncertainties at the pixel level. Preliminary estimates of effective Leaf Area Index (eLAI) are also presented by converting GF via the Beer-Lambert law, where an extinction coefficient of 0.5 is employed; deemed acceptable at such spatial scales. The need for such wide-scale quantification of GF and eLAI are key in the assessment and modification of current forest management strategies across Australia. Such work also assists Australia's Terrestrial Ecosystem Research Network (TERN), a key asset to policy makers with regards to the management of the national ecosystem, in fulfilling their government issued mandates.
Waldner, François; Hansen, Matthew C; Potapov, Peter V; Löw, Fabian; Newby, Terence; Ferreira, Stefanus; Defourny, Pierre
2017-01-01
The lack of sufficient ground truth data has always constrained supervised learning, thereby hindering the generation of up-to-date satellite-derived thematic maps. This is all the more true for those applications requiring frequent updates over large areas such as cropland mapping. Therefore, we present a method enabling the automated production of spatially consistent cropland maps at the national scale, based on spectral-temporal features and outdated land cover information. Following an unsupervised approach, this method extracts reliable calibration pixels based on their labels in the outdated map and their spectral signatures. To ensure spatial consistency and coherence in the map, we first propose to generate seamless input images by normalizing the time series and deriving spectral-temporal features that target salient cropland characteristics. Second, we reduce the spatial variability of the class signatures by stratifying the country and by classifying each stratum independently. Finally, we remove speckle with a weighted majority filter accounting for per-pixel classification confidence. Capitalizing on a wall-to-wall validation data set, the method was tested in South Africa using a 16-year old land cover map and multi-sensor Landsat time series. The overall accuracy of the resulting cropland map reached 92%. A spatially explicit validation revealed large variations across the country and suggests that intensive grain-growing areas were better characterized than smallholder farming systems. Informative features in the classification process vary from one stratum to another but features targeting the minimum of vegetation as well as short-wave infrared features were consistently important throughout the country. Overall, the approach showed potential for routinely delivering consistent cropland maps over large areas as required for operational crop monitoring.
Hansen, Matthew C.; Potapov, Peter V.; Löw, Fabian; Newby, Terence; Ferreira, Stefanus; Defourny, Pierre
2017-01-01
The lack of sufficient ground truth data has always constrained supervised learning, thereby hindering the generation of up-to-date satellite-derived thematic maps. This is all the more true for those applications requiring frequent updates over large areas such as cropland mapping. Therefore, we present a method enabling the automated production of spatially consistent cropland maps at the national scale, based on spectral-temporal features and outdated land cover information. Following an unsupervised approach, this method extracts reliable calibration pixels based on their labels in the outdated map and their spectral signatures. To ensure spatial consistency and coherence in the map, we first propose to generate seamless input images by normalizing the time series and deriving spectral-temporal features that target salient cropland characteristics. Second, we reduce the spatial variability of the class signatures by stratifying the country and by classifying each stratum independently. Finally, we remove speckle with a weighted majority filter accounting for per-pixel classification confidence. Capitalizing on a wall-to-wall validation data set, the method was tested in South Africa using a 16-year old land cover map and multi-sensor Landsat time series. The overall accuracy of the resulting cropland map reached 92%. A spatially explicit validation revealed large variations across the country and suggests that intensive grain-growing areas were better characterized than smallholder farming systems. Informative features in the classification process vary from one stratum to another but features targeting the minimum of vegetation as well as short-wave infrared features were consistently important throughout the country. Overall, the approach showed potential for routinely delivering consistent cropland maps over large areas as required for operational crop monitoring. PMID:28817618
Prediction of Ba, Mn and Zn for tropical soils using iron oxides and magnetic susceptibility
NASA Astrophysics Data System (ADS)
Marques Júnior, José; Arantes Camargo, Livia; Reynaldo Ferracciú Alleoni, Luís; Tadeu Pereira, Gener; De Bortoli Teixeira, Daniel; Santos Rabelo de Souza Bahia, Angelica
2017-04-01
Agricultural activity is an important source of potentially toxic elements (PTEs) in soil worldwide but particularly in heavily farmed areas. Spatial distribution characterization of PTE contents in farming areas is crucial to assess further environmental impacts caused by soil contamination. Designing prediction models become quite useful to characterize the spatial variability of continuous variables, as it allows prediction of soil attributes that might be difficult to attain in a large number of samples through conventional methods. This study aimed to evaluate, in three geomorphic surfaces of Oxisols, the capacity for predicting PTEs (Ba, Mn, Zn) and their spatial variability using iron oxides and magnetic susceptibility (MS). Soil samples were collected from three geomorphic surfaces and analyzed for chemical, physical, mineralogical properties, as well as magnetic susceptibility (MS). PTE prediction models were calibrated by multiple linear regression (MLR). MLR calibration accuracy was evaluated using the coefficient of determination (R2). PTE spatial distribution maps were built using the values calculated by the calibrated models that reached the best accuracy by means of geostatistics. The high correlations between the attributes clay, MS, hematite (Hm), iron oxides extracted by sodium dithionite-citrate-bicarbonate (Fed), and iron oxides extracted using acid ammonium oxalate (Feo) with the elements Ba, Mn, and Zn enabled them to be selected as predictors for PTEs. Stepwise multiple linear regression showed that MS and Fed were the best PTE predictors individually, as they promoted no significant increase in R2 when two or more attributes were considered together. The MS-calibrated models for Ba, Mn, and Zn prediction exhibited R2 values of 0.88, 0.66, and 0.55, respectively. These are promising results since MS is a fast, cheap, and non-destructive tool, allowing the prediction of a large number of samples, which in turn enables detailed mapping of large areas. MS predicted values enabled the characterization and the understanding of spatial variability of the studied PTEs.
NASA Astrophysics Data System (ADS)
Priebe, Elizabeth H.; Neville, C. J.; Rudolph, D. L.
2018-03-01
The spatial coverage of hydraulic conductivity ( K) values for large-scale groundwater investigations is often poor because of the high costs associated with hydraulic testing and the large areas under investigation. Domestic water wells are ubiquitous and their well logs represent an untapped resource of information that includes mandatory specific-capacity tests, from which K can be estimated. These specific-capacity tests are routinely conducted at such low pumping rates that well losses are normally insignificant. In this study, a simple and practical approach to augmenting high-quality K values with reconnaissance-level K values from water-well specific-capacity tests is assessed. The integration of lesser quality K values from specific-capacity tests with a high-quality K data set is assessed through comparisons at two different scales: study-area-wide (a 600-km2 area in Ontario, Canada) and in a single geological formation within a portion of the broader study area (200 km2). Results of the comparisons demonstrate that reconnaissance-level K estimates from specific-capacity tests approximate the ranges and distributions of the high-quality K values. Sufficient detail about the physical basis and assumptions that are invoked in the development of the approach are presented here so that it can be applied with confidence by practitioners seeking to enhance their spatial coverage of K values with specific-capacity tests.
NASA Astrophysics Data System (ADS)
Los, Sietse
2017-04-01
Vegetation is water limited in large areas of Spain and therefore a close link exists between vegetation greenness observed from satellite and moisture availability. Here we exploit this link to infer spatial and temporal variability in moisture from MODIS NDVI data and thermal data. Discrepancies in the precipitation - vegetation relationship indicate areas with an alternative supply of water (i.e. not rainfall), this can be natural where moisture is supplied by upwelling groundwater, or can be artificial where crops are irrigated. As a result spatial and temporal variability in vegetation in the La Mancha Plain appears closely linked to topography, geology, rainfall and land use. Crop land shows large variability in year-to-year vegetation greenness; for some areas this variability is linked to variability in rainfall but in other cases this variability is linked to irrigation. The differences in irrigation treatment within one plant functional type, in this case crops, will lead to errors in land surface models when ignored. The magnitude of these effects on the energy, carbon and water balance are assessed at the scale of 250 m to 200 km. Estimating the water balance correctly is of particular important since in some areas in Spain more water is used for irrigation than is supplemented by rainfall.
Variability of winds and temperature in the Bergen area
NASA Astrophysics Data System (ADS)
Schönbein, Daniel; Ólafsson, Haraldur; Asle Olseth, Jan; Furevik, Birgitte
2017-04-01
In recent years, observations have been made by a dense network of automatic weather stations in the Bergen area in W-Norway (Bergen School of Meteorology). Here, cases are presented that feature large spatial variability in winds and temperature and the ability of a numerical model to reproduce this variability is assessed.
Estimating Long Term Surface Soil Moisture in the GCIP Area From Satellite Microwave Observations
NASA Technical Reports Server (NTRS)
Owe, Manfred; deJeu, Vrije; VandeGriend, Adriaan A.
2000-01-01
Soil moisture is an important component of the water and energy balances of the Earth's surface. Furthermore, it has been identified as a parameter of significant potential for improving the accuracy of large-scale land surface-atmosphere interaction models. However, accurate estimates of surface soil moisture are often difficult to make, especially at large spatial scales. Soil moisture is a highly variable land surface parameter, and while point measurements are usually accurate, they are representative only of the immediate site which was sampled. Simple averaging of point values to obtain spatial means often leads to substantial errors. Since remotely sensed observations are already a spatially averaged or areally integrated value, they are ideally suited for measuring land surface parameters, and as such, are a logical input to regional or larger scale land process models. A nine-year database of surface soil moisture is being developed for the Central United States from satellite microwave observations. This region forms much of the GCIP study area, and contains most of the Mississippi, Rio Grande, and Red River drainages. Daytime and nighttime microwave brightness temperatures were observed at a frequency of 6.6 GHz, by the Scanning Multichannel Microwave Radiometer (SMMR), onboard the Nimbus 7 satellite. The life of the SMMR instrument spanned from Nov. 1978 to Aug. 1987. At 6.6 GHz, the instrument provided a spatial resolution of approximately 150 km, and an orbital frequency over any pixel-sized area of about 2 daytime and 2 nighttime passes per week. Ground measurements of surface soil moisture from various locations throughout the study area are used to calibrate the microwave observations. Because ground measurements are usually only single point values, and since the time of satellite coverage does not always coincide with the ground measurements, the soil moisture data were used to calibrate a regional water balance for the top 1, 5, and 10 cm surface layers in order to interpolate daily surface moisture values. Such a climate-based approach is often more appropriate for estimating large-area spatially averaged soil moisture because meteorological data are generally more spatially representative than isolated point measurements of soil moisture. Vegetation radiative transfer characteristics, such as the canopy transmissivity, were estimated from vegetation indices such as the Normalized Difference Vegetation Index (NDVI) and the 37 GHz Microwave Polarization Difference Index (MPDI). Passive microwave remote sensing presents the greatest potential for providing regular spatially representative estimates of surface soil moisture at global scales. Real time estimates should improve weather and climate modelling efforts, while the development of historical data sets will provide necessary information for simulation and validation of long-term climate and global change studies.
Spatial relations between sympatric coyotes and red foxes in North Dakota
Sargeant, A.B.; Allen, S.H.; Hastings, J.O.
1987-01-01
Spatial relations between coyotes (Canis latrans) and red foxes (Vulpes vulpes) on a 360-km2 area in North Dakota were studied during 1977-78. Coyote families occupied large (mean = 61.2 km2), relatively exclusive territories that encompassed about one-half of the study area. Fox families occupied much smaller (mean = 11.9 km2), relatively exclusive, territories that overlapped perimeters of coyote territories and/or encompassed area unoccupied by coyotes. No fox family lived totally within a coyote territory, but 3 fox families lived within the 153.6-km2 home range of an unattached yearling male coyote. Both coyotes and foxes, from families with overlapping territories, tended to use their overlap areas less than was expected by amount of overlap. Encounters between radio-equipped coyotes and foxes from families with overlapping territories occurred less often than was expected by chance. Foxes living near coyotes exhibited considerable tenacity to their territories, and no monitored fox was killed by coyotes during 2,518 fox-days of radio surveillance. A hypothesis for coyote-induced fox population declines, based largely on fox avoidance mechanisms, is presented.
Spatial use and habitat selection of golden eagles in southwestern Idaho
Marzluff, J.M.; Knick, Steven T.; Vekasy, M.S.; Schueck, Linda S.; Zarriello, T.J.
1997-01-01
We measured spatial use and habitat selection of radio-tagged Golden Eagles (Aquila chrysaetos) at eight to nine territories each year from 1992 to 1994 in the Snake River Birds of Prey National Conservation Area. Use of space did not vary between years or sexes, but did vary among seasons (home ranges and travel distances were larger during the nonbreeding than during the breeding season) and among individuals. Home ranges were large, ranging from 190 to 8,330 ha during the breeding season and from 1,370 to 170,000 ha outside of the breeding season, but activity was concentrated in small core areas of 30 to 1,535 ha and 485 to 6,380 ha during the breeding and nonbreeding seasons, respectively. Eagles selected shrub habitats and avoided disturbed areas, grasslands, and agriculture. This resulted in selection for habitat likely to contain their principal prey, black-tailed jackrabbits (Lepus californicus). Individuals with home ranges in extensive shrubland (n = 3) did not select for shrubs in the placement of their core areas or foraging points, but individuals in highly fragmented or dispersed shrublands (n = 5) concentrated their activities and foraged preferentially in jackrabbit habitats (i.e. areas with abundant and large shrub patches). As home ranges expanded outside of the breeding season, individuals selected jackrabbit habitats within their range. Shrubland fragmentation should be minimized so that remaining shrub patches are large enough to support jackrabbits.
Yang, Limin; Huang, Chengquan; Homer, Collin G.; Wylie, Bruce K.; Coan, Michael
2003-01-01
A wide range of urban ecosystem studies, including urban hydrology, urban climate, land use planning, and resource management, require current and accurate geospatial data of urban impervious surfaces. We developed an approach to quantify urban impervious surfaces as a continuous variable by using multisensor and multisource datasets. Subpixel percent impervious surfaces at 30-m resolution were mapped using a regression tree model. The utility, practicality, and affordability of the proposed method for large-area imperviousness mapping were tested over three spatial scales (Sioux Falls, South Dakota, Richmond, Virginia, and the Chesapeake Bay areas of the United States). Average error of predicted versus actual percent impervious surface ranged from 8.8 to 11.4%, with correlation coefficients from 0.82 to 0.91. The approach is being implemented to map impervious surfaces for the entire United States as one of the major components of the circa 2000 national land cover database.
Large area nuclear particle detectors using ET materials
NASA Technical Reports Server (NTRS)
1987-01-01
The purpose of this SBIR Phase 1 feasibility effort was to demonstrate the usefulness of Quantex electron-trapping (ET) materials for spatial detection of nuclear particles over large areas. This demonstration entailed evaluating the prompt visible scintillation as nuclear particles impinged on films of ET materials, and subsequently detecting the nuclear particle impingement information pattern stored in the ET material, by means of the visible-wavelength luminescence produced by near-infrared interrogation. Readily useful levels of scintillation and luminescence outputs are demonstrated.
The MSFC large-area imaging multistep proportional counter
NASA Technical Reports Server (NTRS)
Ramsey, B. D.; Weisskopf, M. C.; Joy, M. K.
1989-01-01
A large-area multistep imaging proportional counter that is being currently developed at the Marshall Space Flight Center is described. The device, known as a multistep fluorescence gated detector, consists of a multiwire proportional counter (MWPC) with a preamplification region. The MWCP features superior spatial resolution with a very high degree of background rejection. It is ideally suited for use in X-ray astronomy in 20-100 keV energy range. The paper includes the MWPC schematic and a list of instrument specifications.
Mode-Selective Amplification in a Large Mode Area Yb-Doped Fiber Using a Photonic Lantern
2016-05-15
in a few mode, double- clad Yb-doped large mode area (LMA) fiber, utilizing an all-fiber photonic lantern. Amplification to multi-watt output power is...that could enable dynamic spatial mode control in high power fiber lasers . © 2016 Optical Society of America OCIS codes: (060.2320) Fiber optics...amplifiers and oscillators; (060.2340) Fiber optics components. http://dx.doi.org/10.1364/OL.41.002157 The impressive growth experienced by fiber lasers and
Locally adaptive, spatially explicit projection of US population for 2030 and 2050.
McKee, Jacob J; Rose, Amy N; Bright, Edward A; Huynh, Timmy; Bhaduri, Budhendra L
2015-02-03
Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Building on the spatial interpolation technique previously developed for high-resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically informed spatial distribution of projected population of the contiguous United States for 2030 and 2050, depicting one of many possible population futures. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection model departs from these by accounting for multiple components that affect population distribution. Modeled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the US Census's projection methodology, with the US Census's official projection as the benchmark. Applications of our model include incorporating multiple various scenario-driven events to produce a range of spatially explicit population futures for suitability modeling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations.
Productivity in the barents sea--response to recent climate variability.
Dalpadado, Padmini; Arrigo, Kevin R; Hjøllo, Solfrid S; Rey, Francisco; Ingvaldsen, Randi B; Sperfeld, Erik; van Dijken, Gert L; Stige, Leif C; Olsen, Are; Ottersen, Geir
2014-01-01
The temporal and spatial dynamics of primary and secondary biomass/production in the Barents Sea since the late 1990s are examined using remote sensing data, observations and a coupled physical-biological model. Field observations of mesozooplankton biomass, and chlorophyll a data from transects (different seasons) and large-scale surveys (autumn) were used for validation of the remote sensing products and modeling results. The validation showed that satellite data are well suited to study temporal and spatial dynamics of chlorophyll a in the Barents Sea and that the model is an essential tool for secondary production estimates. Temperature, open water area, chlorophyll a, and zooplankton biomass show large interannual variations in the Barents Sea. The climatic variability is strongest in the northern and eastern parts. The moderate increase in net primary production evident in this study is likely an ecosystem response to changes in climate during the same period. Increased open water area and duration of open water season, which are related to elevated temperatures, appear to be the key drivers of the changes in annual net primary production that has occurred in the northern and eastern areas of this ecosystem. The temporal and spatial variability in zooplankton biomass appears to be controlled largely by predation pressure. In the southeastern Barents Sea, statistically significant linkages were observed between chlorophyll a and zooplankton biomass, as well as between net primary production and fish biomass, indicating bottom-up trophic interactions in this region.
Productivity in the Barents Sea - Response to Recent Climate Variability
Dalpadado, Padmini; Arrigo, Kevin R.; Hjøllo, Solfrid S.; Rey, Francisco; Ingvaldsen, Randi B.; Sperfeld, Erik; van Dijken, Gert L.; Stige, Leif C.; Olsen, Are; Ottersen, Geir
2014-01-01
The temporal and spatial dynamics of primary and secondary biomass/production in the Barents Sea since the late 1990s are examined using remote sensing data, observations and a coupled physical-biological model. Field observations of mesozooplankton biomass, and chlorophyll a data from transects (different seasons) and large-scale surveys (autumn) were used for validation of the remote sensing products and modeling results. The validation showed that satellite data are well suited to study temporal and spatial dynamics of chlorophyll a in the Barents Sea and that the model is an essential tool for secondary production estimates. Temperature, open water area, chlorophyll a, and zooplankton biomass show large interannual variations in the Barents Sea. The climatic variability is strongest in the northern and eastern parts. The moderate increase in net primary production evident in this study is likely an ecosystem response to changes in climate during the same period. Increased open water area and duration of open water season, which are related to elevated temperatures, appear to be the key drivers of the changes in annual net primary production that has occurred in the northern and eastern areas of this ecosystem. The temporal and spatial variability in zooplankton biomass appears to be controlled largely by predation pressure. In the southeastern Barents Sea, statistically significant linkages were observed between chlorophyll a and zooplankton biomass, as well as between net primary production and fish biomass, indicating bottom-up trophic interactions in this region. PMID:24788513
Temporal and spatial mapping of red grouper Epinephelus morio sound production.
Wall, C C; Simard, P; Lindemuth, M; Lembke, C; Naar, D F; Hu, C; Barnes, B B; Muller-Karger, F E; Mann, D A
2014-11-01
The goals of this project were to determine the daily, seasonal and spatial patterns of red grouper Epinephelus morio sound production on the West Florida Shelf (WFS) using passive acoustics. An 11 month time series of acoustic data from fixed recorders deployed at a known E. morio aggregation site showed that E. morio produce sounds throughout the day and during all months of the year. Increased calling (number of files containing E. morio sound) was correlated to sunrise and sunset, and peaked in late summer (July and August) and early winter (November and December). Due to the ubiquitous production of sound, large-scale spatial mapping across the WFS of E. morio sound production was feasible using recordings from shorter duration-fixed location recorders and autonomous underwater vehicles (AUVs). Epinephelus morio were primarily recorded in waters 15-93 m deep, with increased sound production detected in hard bottom areas and within the Steamboat Lumps Marine Protected Area (Steamboat Lumps). AUV tracks through Steamboat Lumps, an offshore marine reserve where E. morio hole excavations have been previously mapped, showed that hydrophone-integrated AUVs could accurately map the location of soniferous fish over spatial scales of <1 km. The results show that passive acoustics is an effective, non-invasive tool to map the distribution of this species over large spatial scales. © 2014 The Fisheries Society of the British Isles.
Evidence and mapping of extinction debts for global forest-dwelling reptiles, amphibians and mammals
NASA Astrophysics Data System (ADS)
Chen, Youhua; Peng, Shushi
2017-03-01
Evidence of extinction debts for the global distributions of forest-dwelling reptiles, mammals and amphibians was tested and the debt magnitude was estimated and mapped. By using different correlation tests and variable importance analysis, the results showed that spatial richness patterns for the three forest-dwelling terrestrial vertebrate groups had significant and stronger correlations with past forest cover area and other variables in the 1500 s, implying the evidence for extinction debts. Moreover, it was likely that the extinction debts have been partially paid, given that their global richness patterns were also significantly correlated with contemporary forest variables in the 2000 s (but the absolute magnitudes of the correlation coefficients were usually smaller than those calculated for historical forest variables). By utilizing species-area relationships, spatial extinction-debt magnitudes for the three vertebrate groups at the global scale were estimated and the hotspots of extinction debts were identified. These high-debt hotspots were generally situated in areas that did not spatially overlap with hotspots of species richness or high extinction-risk areas based on IUCN threatened status to a large extent. This spatial mismatch pattern suggested that necessary conservation efforts should be directed toward high-debt areas that are still overlooked.
Chen, Youhua; Peng, Shushi
2017-03-16
Evidence of extinction debts for the global distributions of forest-dwelling reptiles, mammals and amphibians was tested and the debt magnitude was estimated and mapped. By using different correlation tests and variable importance analysis, the results showed that spatial richness patterns for the three forest-dwelling terrestrial vertebrate groups had significant and stronger correlations with past forest cover area and other variables in the 1500 s, implying the evidence for extinction debts. Moreover, it was likely that the extinction debts have been partially paid, given that their global richness patterns were also significantly correlated with contemporary forest variables in the 2000 s (but the absolute magnitudes of the correlation coefficients were usually smaller than those calculated for historical forest variables). By utilizing species-area relationships, spatial extinction-debt magnitudes for the three vertebrate groups at the global scale were estimated and the hotspots of extinction debts were identified. These high-debt hotspots were generally situated in areas that did not spatially overlap with hotspots of species richness or high extinction-risk areas based on IUCN threatened status to a large extent. This spatial mismatch pattern suggested that necessary conservation efforts should be directed toward high-debt areas that are still overlooked.
NASA Astrophysics Data System (ADS)
Seker, D. Z.; Unal, A.; Kaya, S.; Alganci, U.
2015-12-01
Migration from rural areas to city centers and their surroundings is an important problem of not only our country but also the countries that under development stage. This uncontrolled and huge amount of migration brings out urbanization and socio - economic problems. The demand on settling the industrial areas and commercial activities nearby the city centers results with a negative change in natural land cover on cities. Negative impacts of human induced activities on natural resources and land cover has been continuously increasing for decades. The main human activities that resulted with destruction and infraction of forest areas can be defined as mining activities, agricultural activities, industrial / commercial activities and urbanization. Temporal monitoring of the changes in spatial distribution of forest areas is significantly important for effective management and planning progress. Changes can occur as spatially large destructions or small infractions. Therefore there is a need for reliable, fast and accurate data sources. At this point, satellite images proved to be a good data source for determination of the land use /cover changes with their capability of monitoring large areas with reasonable temporal resolutions. Spectral information derived from images provides discrimination of land use/cover types from each other. Developments in remote sensing technology in the last decade improved the spatial resolution of satellites and high resolution images were started to be used to detect even small changes in the land surface. As being the megacity of Turkey, Istanbul has been facing a huge migration for the last 20 years and effects of urbanization and other human based activities over forest areas are significant. Main focus of this study is to determine the destructions and infractions in forest areas of Istanbul, Turkey with 2.5m resolution SPOT 5 multi-temporal satellite imagery. Analysis was mainly constructed on threshold based classification of multi-temporal vegetation index data derived from satellite images. Determined changes were exported to GIS environment and spatial overlay and intersection analyses were performed with use of forest type maps and authorized area maps in order to demonstrate the actual situation of destructions and infractions.
Geo-spatial aspects of acceptance of illegal hunting of large carnivores in Scandinavia.
Gangaas, Kristin E; Kaltenborn, Bjørn P; Andreassen, Harry P
2013-01-01
Human-carnivore conflicts are complex and are influenced by: the spatial distribution of the conflict species; the organisation and intensity of management measures such as zoning; historical experience with wildlife; land use patterns; and local cultural traditions. We have used a geographically stratified sampling of social values and attitudes to provide a novel perspective to the human - wildlife conflict. We have focused on acceptance by and disagreements between residents (measured as Potential Conflict Index; PCI) towards illegal hunting of four species of large carnivores (bear, lynx, wolf, wolverine). The study is based on surveys of residents in every municipality in Sweden and Norway who were asked their opinion on illegal hunting. Our results show how certain social values are associated with acceptance of poaching, and how these values differ geographically independent of carnivore abundance. Our approach differs from traditional survey designs, which are often biased towards urban areas. Although these traditional designs intend to be representative of a region (i.e. a random sample from a country), they tend to receive relatively few respondents from rural areas that experience the majority of conflict with carnivores. Acceptance of poaching differed significantly between Norway (12.7-15.7% of respondents) and Sweden (3.3-4.1% of respondents). We found the highest acceptance of illegal hunting in rural areas with free-ranging sheep and strong hunting traditions. Disagreements between residents (as measured by PCI) were highest in areas with intermediate population density. There was no correlation between carnivore density and either acceptance of illegal hunting or PCI. A strong positive correlation between acceptance of illegal hunting and PCI showed that areas with high acceptance of illegal hunting are areas with high potential conflict between people. Our results show that spatially-stratified surveys are required to reveal the large scale patterns in social dynamics of human-wildlife conflicts.
NASA Astrophysics Data System (ADS)
Rochelo, Mark
Urbanization is a fundamental reality in the developed and developing countries around the world creating large concentrations of the population centering on cities and urban centers. Cities can offer many opportunities for those residing there, including infrastructure, health services, rescue services and more. The living space density of cities allows for the opportunity of more effective and environmentally friendly housing, transportation and resources. Cities play a vital role in generating economic production as entities by themselves and as a part of larger urban complex. The benefits can provide for extraordinary amount of people, but only if proper planning and consideration is undertaken. Global urbanization is a progressive evolution, unique in spatial location while consistent to an overall growth pattern and trend. Remotely sensing these patterns from the last forty years of space borne satellites to understand how urbanization has developed is important to understanding past growth as well as planning for the future. Imagery from the Landsat sensor program provides the temporal component, it was the first satellite launched in 1972, providing appropriate spatial resolution needed to cover a large metropolitan statistical area to monitor urban growth and change on a large scale. This research maps the urban spatial and population growth over the Miami - Fort Lauderdale - West Palm Beach Metropolitan Statistical Area (MSA) covering Miami-Dade, Broward, and Palm Beach counties in Southeast Florida from 1974 to 2010 using Landsat imagery. Supervised Maximum Likelihood classification was performed with a combination of spectral and textural training fields employed in ERDAS Image 2014 to classify the images into urban and non-urban areas. Dasymetric mapping of the classification results were combined with census tract data then created a coherent depiction of the Miami - Fort Lauderdale - West Palm Beach MSA. Static maps and animated files were created from the final datasets for enhanced visualizations and understanding of the MSA evolution from 60-meter resolution remotely sensed Landsat images. The simplified methodology will create a database for urban planning and population growth as well as future work in this area.
Landsat continuity: Issues and opportunities for land cover monitoring
Wulder, M.A.; White, Joanne C.; Goward, S.N.; Masek, J.G.; Irons, J.R.; Herold, M.; Cohen, W.B.; Loveland, Thomas R.; Woodcock, C.E.
2008-01-01
Initiated in 1972, the Landsat program has provided a continuous record of earth observation for 35 years. The assemblage of Landsat spatial, spectral, and temporal resolutions, over a reasonably sized image extent, results in imagery that can be processed to represent land cover over large areas with an amount of spatial detail that is absolutely unique and indispensable for monitoring, management, and scientific activities. Recent technical problems with the two existing Landsat satellites, and delays in the development and launch of a successor, increase the likelihood that a gap in Landsat continuity may occur. In this communication, we identify the key features of the Landsat program that have resulted in the extensive use of Landsat data for large area land cover mapping and monitoring. We then augment this list of key features by examining the data needs of existing large area land cover monitoring programs. Subsequently, we use this list as a basis for reviewing the current constellation of earth observation satellites to identify potential alternative data sources for large area land cover applications. Notions of a virtual constellation of satellites to meet large area land cover mapping and monitoring needs are also presented. Finally, research priorities that would facilitate the integration of these alternative data sources into existing large area land cover monitoring programs are identified. Continuity of the Landsat program and the measurements provided are critical for scientific, environmental, economic, and social purposes. It is difficult to overstate the importance of Landsat; there are no other systems in orbit, or planned for launch in the short-term, that can duplicate or approach replication, of the measurements and information conferred by Landsat. While technical and political options are being pursued, there is no satellite image data stream poised to enter the National Satellite Land Remote Sensing Data Archive should system failures occur to Landsat-5 and -7.
Search for Spatially Extended Fermi-LAT Sources Using Two Years of Data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lande, Joshua; Ackermann, Markus; Allafort, Alice
2012-07-13
Spatial extension is an important characteristic for correctly associating {gamma}-ray-emitting sources with their counterparts at other wavelengths and for obtaining an unbiased model of their spectra. We present a new method for quantifying the spatial extension of sources detected by the Large Area Telescope (LAT), the primary science instrument on the Fermi Gamma-ray Space Telescope (Fermi). We perform a series of Monte Carlo simulations to validate this tool and calculate the LAT threshold for detecting the spatial extension of sources. We then test all sources in the second Fermi -LAT catalog (2FGL) for extension. We report the detection of sevenmore » new spatially extended sources.« less
A global approach to estimate irrigated areas - a comparison between different data and statistics
NASA Astrophysics Data System (ADS)
Meier, Jonas; Zabel, Florian; Mauser, Wolfram
2018-02-01
Agriculture is the largest global consumer of water. Irrigated areas constitute 40 % of the total area used for agricultural production (FAO, 2014a) Information on their spatial distribution is highly relevant for regional water management and food security. Spatial information on irrigation is highly important for policy and decision makers, who are facing the transition towards more efficient sustainable agriculture. However, the mapping of irrigated areas still represents a challenge for land use classifications, and existing global data sets differ strongly in their results. The following study tests an existing irrigation map based on statistics and extends the irrigated area using ancillary data. The approach processes and analyzes multi-temporal normalized difference vegetation index (NDVI) SPOT-VGT data and agricultural suitability data - both at a spatial resolution of 30 arcsec - incrementally in a multiple decision tree. It covers the period from 1999 to 2012. The results globally show a 18 % larger irrigated area than existing approaches based on statistical data. The largest differences compared to the official national statistics are found in Asia and particularly in China and India. The additional areas are mainly identified within already known irrigated regions where irrigation is more dense than previously estimated. The validation with global and regional products shows the large divergence of existing data sets with respect to size and distribution of irrigated areas caused by spatial resolution, the considered time period and the input data and assumption made.
Influence of resolution in irrigated area mapping and area estimation
Velpuri, N.M.; Thenkabail, P.S.; Gumma, M.K.; Biradar, C.; Dheeravath, V.; Noojipady, P.; Yuanjie, L.
2009-01-01
The overarching goal of this paper was to determine how irrigated areas change with resolution (or scale) of imagery. Specific objectives investigated were to (a) map irrigated areas using four distinct spatial resolutions (or scales), (b) determine how irrigated areas change with resolutions, and (c) establish the causes of differences in resolution-based irrigated areas. The study was conducted in the very large Krishna River basin (India), which has a high degree of formal contiguous, and informal fragmented irrigated areas. The irrigated areas were mapped using satellite sensor data at four distinct resolutions: (a) NOAA AVHRR Pathfinder 10,000 m, (b) Terra MODIS 500 m, (c) Terra MODIS 250 m, and (d) Landsat ETM+ 30 m. The proportion of irrigated areas relative to Landsat 30 m derived irrigated areas (9.36 million hectares for the Krishna basin) were (a) 95 percent using MODIS 250 m, (b) 93 percent using MODIS 500 m, and (c) 86 percent using AVHRR 10,000 m. In this study, it was found that the precise location of the irrigated areas were better established using finer spatial resolution data. A strong relationship (R2 = 0.74 to 0.95) was observed between irrigated areas determined using various resolutions. This study proved the hypotheses that "the finer the spatial resolution of the sensor used, greater was the irrigated area derived," since at finer spatial resolutions, fragmented areas are detected better. Accuracies and errors were established consistently for three classes (surface water irrigated, ground water/conjunctive use irrigated, and nonirrigated) across the four resolutions mentioned above. The results showed that the Landsat data provided significantly higher overall accuracies (84 percent) when compared to MODIS 500 m (77 percent), MODIS 250 m (79 percent), and AVHRR 10,000 m (63 percent). ?? 2009 American Society for Photogrammetry and Remote Sensing.
NASA Astrophysics Data System (ADS)
Hendrickx, Jan M. H.; Kleissl, Jan; Gómez Vélez, Jesús D.; Hong, Sung-ho; Fábrega Duque, José R.; Vega, David; Moreno Ramírez, Hernán A.; Ogden, Fred L.
2007-04-01
Accurate estimation of sensible and latent heat fluxes as well as soil moisture from remotely sensed satellite images poses a great challenge. Yet, it is critical to face this challenge since the estimation of spatial and temporal distributions of these parameters over large areas is impossible using only ground measurements. A major difficulty for the calibration and validation of operational remote sensing methods such as SEBAL, METRIC, and ALEXI is the ground measurement of sensible heat fluxes at a scale similar to the spatial resolution of the remote sensing image. While the spatial length scale of remote sensing images covers a range from 30 m (LandSat) to 1000 m (MODIS) direct methods to measure sensible heat fluxes such as eddy covariance (EC) only provide point measurements at a scale that may be considerably smaller than the estimate obtained from a remote sensing method. The Large Aperture scintillometer (LAS) flux footprint area is larger (up to 5000 m long) and its spatial extent better constraint than that of EC systems. Therefore, scintillometers offer the unique possibility of measuring the vertical flux of sensible heat averaged over areas comparable with several pixels of a satellite image (up to about 40 Landsat thermal pixels or about 5 MODIS thermal pixels). The objective of this paper is to present our experiences with an existing network of seven scintillometers in New Mexico and a planned network of three scintillometers in the humid tropics of Panama and Colombia.
Vulnerability of ecosystems to climate change moderated by habitat intactness.
Eigenbrod, Felix; Gonzalez, Patrick; Dash, Jadunandan; Steyl, Ilse
2015-01-01
The combined effects of climate change and habitat loss represent a major threat to species and ecosystems around the world. Here, we analyse the vulnerability of ecosystems to climate change based on current levels of habitat intactness and vulnerability to biome shifts, using multiple measures of habitat intactness at two spatial scales. We show that the global extent of refugia depends highly on the definition of habitat intactness and spatial scale of the analysis of intactness. Globally, 28% of terrestrial vegetated area can be considered refugia if all natural vegetated land cover is considered. This, however, drops to 17% if only areas that are at least 50% wilderness at a scale of 48×48 km are considered and to 10% if only areas that are at least 50% wilderness at a scale of 4.8×4.8 km are considered. Our results suggest that, in regions where relatively large, intact wilderness areas remain (e.g. Africa, Australia, boreal regions, South America), conservation of the remaining large-scale refugia is the priority. In human-dominated landscapes, (e.g. most of Europe, much of North America and Southeast Asia), focusing on finer scale refugia is a priority because large-scale wilderness refugia simply no longer exist. Action to conserve such refugia is particularly urgent since only 1 to 2% of global terrestrial vegetated area is classified as refugia and at least 50% covered by the global protected area network. © 2014 John Wiley & Sons Ltd.
Map visualization of groundwater withdrawals at the sub-basin scale
NASA Astrophysics Data System (ADS)
Goode, Daniel J.
2016-06-01
A simple method is proposed to visualize the magnitude of groundwater withdrawals from wells relative to user-defined water-resource metrics. The map is solely an illustration of the withdrawal magnitudes, spatially centered on wells—it is not capture zones or source areas contributing recharge to wells. Common practice is to scale the size (area) of withdrawal well symbols proportional to pumping rate. Symbols are drawn large enough to be visible, but not so large that they overlap excessively. In contrast to such graphics-based symbol sizes, the proposed method uses a depth-rate index (length per time) to visualize the well withdrawal rates by volumetrically consistent areas, called "footprints". The area of each individual well's footprint is the withdrawal rate divided by the depth-rate index. For example, the groundwater recharge rate could be used as a depth-rate index to show how large withdrawals are relative to that recharge. To account for the interference of nearby wells, composite footprints are computed by iterative nearest-neighbor distribution of excess withdrawals on a computational and display grid having uniform square cells. The map shows circular footprints at individual isolated wells and merged footprint areas where wells' individual footprints overlap. Examples are presented for depth-rate indexes corresponding to recharge, to spatially variable stream baseflow (normalized by basin area), and to the average rate of water-table decline (scaled by specific yield). These depth-rate indexes are water-resource metrics, and the footprints visualize the magnitude of withdrawals relative to these metrics.
Map visualization of groundwater withdrawals at the sub-basin scale
Goode, Daniel J.
2016-01-01
A simple method is proposed to visualize the magnitude of groundwater withdrawals from wells relative to user-defined water-resource metrics. The map is solely an illustration of the withdrawal magnitudes, spatially centered on wells—it is not capture zones or source areas contributing recharge to wells. Common practice is to scale the size (area) of withdrawal well symbols proportional to pumping rate. Symbols are drawn large enough to be visible, but not so large that they overlap excessively. In contrast to such graphics-based symbol sizes, the proposed method uses a depth-rate index (length per time) to visualize the well withdrawal rates by volumetrically consistent areas, called “footprints”. The area of each individual well’s footprint is the withdrawal rate divided by the depth-rate index. For example, the groundwater recharge rate could be used as a depth-rate index to show how large withdrawals are relative to that recharge. To account for the interference of nearby wells, composite footprints are computed by iterative nearest-neighbor distribution of excess withdrawals on a computational and display grid having uniform square cells. The map shows circular footprints at individual isolated wells and merged footprint areas where wells’ individual footprints overlap. Examples are presented for depth-rate indexes corresponding to recharge, to spatially variable stream baseflow (normalized by basin area), and to the average rate of water-table decline (scaled by specific yield). These depth-rate indexes are water-resource metrics, and the footprints visualize the magnitude of withdrawals relative to these metrics.
Espinosa, Santiago; Branch, Lyn C.; Cueva, Rubén
2014-01-01
Protected areas are essential for conservation of wildlife populations. However, in the tropics there are two important factors that may interact to threaten this objective: 1) road development associated with large-scale resource extraction near or within protected areas; and 2) historical occupancy by traditional or indigenous groups that depend on wildlife for their survival. To manage wildlife populations in the tropics, it is critical to understand the effects of roads on the spatial extent of hunting and how wildlife is used. A geographical analysis can help us answer questions such as: How do roads affect spatial extent of hunting? How does market vicinity relate to local consumption and trade of bushmeat? How does vicinity to markets influence choice of game? A geographical analysis also can help evaluate the consequences of increased accessibility in landscapes that function as source-sink systems. We applied spatial analyses to evaluate the effects of increased landscape and market accessibility by road development on spatial extent of harvested areas and wildlife use by indigenous hunters. Our study was conducted in Yasuní Biosphere Reserve, Ecuador, which is impacted by road development for oil extraction, and inhabited by the Waorani indigenous group. Hunting activities were self-reported for 12–14 months and each kill was georeferenced. Presence of roads was associated with a two-fold increase of the extraction area. Rates of bushmeat extraction and trade were higher closer to markets than further away. Hunters located closer to markets concentrated their effort on large-bodied species. Our results clearly demonstrate that placing roads within protected areas can seriously reduce their capacity to sustain wildlife populations and potentially threaten livelihoods of indigenous groups who depend on these resources for their survival. Our results critically inform current policy debates regarding resource extraction and road building near or within protected areas. PMID:25489954
Espinosa, Santiago; Branch, Lyn C; Cueva, Rubén
2014-01-01
Protected areas are essential for conservation of wildlife populations. However, in the tropics there are two important factors that may interact to threaten this objective: 1) road development associated with large-scale resource extraction near or within protected areas; and 2) historical occupancy by traditional or indigenous groups that depend on wildlife for their survival. To manage wildlife populations in the tropics, it is critical to understand the effects of roads on the spatial extent of hunting and how wildlife is used. A geographical analysis can help us answer questions such as: How do roads affect spatial extent of hunting? How does market vicinity relate to local consumption and trade of bushmeat? How does vicinity to markets influence choice of game? A geographical analysis also can help evaluate the consequences of increased accessibility in landscapes that function as source-sink systems. We applied spatial analyses to evaluate the effects of increased landscape and market accessibility by road development on spatial extent of harvested areas and wildlife use by indigenous hunters. Our study was conducted in Yasuní Biosphere Reserve, Ecuador, which is impacted by road development for oil extraction, and inhabited by the Waorani indigenous group. Hunting activities were self-reported for 12-14 months and each kill was georeferenced. Presence of roads was associated with a two-fold increase of the extraction area. Rates of bushmeat extraction and trade were higher closer to markets than further away. Hunters located closer to markets concentrated their effort on large-bodied species. Our results clearly demonstrate that placing roads within protected areas can seriously reduce their capacity to sustain wildlife populations and potentially threaten livelihoods of indigenous groups who depend on these resources for their survival. Our results critically inform current policy debates regarding resource extraction and road building near or within protected areas.
Metamaterial devices for molding the flow of diffuse light (Conference Presentation)
NASA Astrophysics Data System (ADS)
Wegener, Martin
2016-09-01
Much of optics in the ballistic regime is about designing devices to mold the flow of light. This task is accomplished via specific spatial distributions of the refractive index or the refractive-index tensor. For light propagating in turbid media, a corresponding design approach has not been applied previously. Here, we review our corresponding recent work in which we design spatial distributions of the light diffusivity or the light-diffusivity tensor to accomplish specific tasks. As an application, we realize cloaking of metal contacts on large-area OLEDs, eliminating the contacts' shadows, thereby homogenizing the diffuse light emission. In more detail, metal contacts on large-area organic light-emitting diodes (OLEDs) are mandatory electrically, but they cast optical shadows, leading to unwanted spatially inhomogeneous diffuse light emission. We show that the contacts can be made invisible either by (i) laminate metamaterials designed by coordinate transformations of the diffusion equation or by (ii) triangular-shaped regions with piecewise constant diffusivity, hence constant concentration of scattering centers. These structures are post-optimized in regard to light throughput by Monte-Carlo ray-tracing simulations and successfully validated by model experiments.
Etherington, L.L.; Eggleston, D.B.
2003-01-01
We assessed determinants and consequences of multistage dispersal on spatial recruitment of the blue crab, Callinectes sapidus, within the Croatan, Albemarle, Pamlico Estuarine System (CAPES), North Carolina, U.S.A. Large-scale sampling of early juvenile crabs over 4 years indicated that spatial abundance patterns were size-dependent and resulted from primary post-larval dispersal (pre-settlement) and secondary juvenile dispersal (early post-settlement). In general, primary dispersal led to high abundances within more seaward habitats, whereas secondary dispersal (which was relatively consistent) expanded the distribution of juveniles, potentially increasing the estuarine nursery capacity. There were strong relationships between juvenile crab density and specific wind characteristics; however, these patterns were spatially explicit. Various physical processes (e.g., seasonal wind events, timing and magnitude of tropical cyclones) interacted to influence dispersal during multiple stages and determined crab recruitment patterns. Our results suggest that the nursery value of different habitats is highly dependent on the dispersal potential (primary and secondary dispersal) to and from these areas, which is largely determined by the relative position of habitats within the estuarine landscape.
Evidence of fuels management and fire weather influencing fire severity in an extreme fire event
Lydersen, Jamie M; Collins, Brandon M.; Brooks, Matthew L.; Matchett, John R.; Shive, Kristen L.; Povak, Nicholas A.; Kane, Van R.; Smith, Douglas F.
2017-01-01
Following changes in vegetation structure and pattern, along with a changing climate, large wildfire incidence has increased in forests throughout the western U.S. Given this increase there is great interest in whether fuels treatments and previous wildfire can alter fire severity patterns in large wildfires. We assessed the relative influence of previous fuels treatments (including wildfire), fire weather, vegetation and water balance on fire severity in the Rim Fire of 2013. We did this at three different spatial scales to investigate whether the influences on fire severity changed across scales. Both fuels treatments and previous low to moderate severity wildfire reduced the prevalence of high severity fire. In general, areas without recent fuels treatments and areas that previously burned at high severity tended to have a greater proportion of high severity fire in the Rim Fire. Areas treated with prescribed fire, especially when combined with thinning, had the lowest proportions of high severity. Proportion of the landscape burned at high severity was most strongly influenced by fire weather and proportional area previously treated for fuels or burned by low to moderate severity wildfire. The proportion treated needed to effectively reduce the amount of high fire severity fire varied by spatial scale of analysis, with smaller spatial scales requiring a greater proportion treated to see an effect on fire severity. When moderate and high severity fire encountered a previously treated area, fire severity was significantly reduced in the treated area relative to the adjacent untreated area. Our results show that fuels treatments and low to moderate severity wildfire can reduce fire severity in a subsequent wildfire, even when burning under fire growth conditions. These results serve as further evidence that both fuels treatments and lower severity wildfire can increase forest resilience.
Spatio-temporal patterns of gun violence in Syracuse, New York 2009-2015.
Larsen, David A; Lane, Sandra; Jennings-Bey, Timothy; Haygood-El, Arnett; Brundage, Kim; Rubinstein, Robert A
2017-01-01
Gun violence in the United States of America is a large public health problem that disproportionately affects urban areas. The epidemiology of gun violence reflects various aspects of an infectious disease including spatial and temporal clustering. We examined the spatial and temporal trends of gun violence in Syracuse, New York, a city of 145,000. We used a spatial scan statistic to reveal spatio-temporal clusters of gunshots investigated and corroborated by Syracuse City Police Department for the years 2009-2015. We also examined predictors of areas with increased gun violence using a multi-level zero-inflated Poisson regression with data from the 2010 census. Two space-time clusters of gun violence were revealed in the city. Higher rates of segregation, poverty and the summer months were all associated with increased risk of gun violence. Previous gunshots in the area were associated with a 26.8% increase in the risk of gun violence. Gun violence in Syracuse, NY is both spatially and temporally stable, with some neighborhoods of the city greatly afflicted.
Spatio-temporal patterns of gun violence in Syracuse, New York 2009-2015
Lane, Sandra; Jennings-Bey, Timothy; Haygood-El, Arnett; Brundage, Kim; Rubinstein, Robert A.
2017-01-01
Gun violence in the United States of America is a large public health problem that disproportionately affects urban areas. The epidemiology of gun violence reflects various aspects of an infectious disease including spatial and temporal clustering. We examined the spatial and temporal trends of gun violence in Syracuse, New York, a city of 145,000. We used a spatial scan statistic to reveal spatio-temporal clusters of gunshots investigated and corroborated by Syracuse City Police Department for the years 2009–2015. We also examined predictors of areas with increased gun violence using a multi-level zero-inflated Poisson regression with data from the 2010 census. Two space-time clusters of gun violence were revealed in the city. Higher rates of segregation, poverty and the summer months were all associated with increased risk of gun violence. Previous gunshots in the area were associated with a 26.8% increase in the risk of gun violence. Gun violence in Syracuse, NY is both spatially and temporally stable, with some neighborhoods of the city greatly afflicted. PMID:28319125
Spatial scale of similarity as an indicator of metacommunity stability in exploited marine systems.
Shackell, Nancy L; Fisher, Jonathan A D; Frank, Kenneth T; Lawton, Peter
2012-01-01
The spatial scale of similarity among fish communities is characteristically large in temperate marine systems: connectivity is enhanced by high rates of dispersal during the larval/juvenile stages and the increased mobility of large-bodied fish. A larger spatial scale of similarity (low beta diversity) is advantageous in heavily exploited systems because locally depleted populations are more likely to be "rescued" by neighboring areas. We explored whether the spatial scale of similarity changed from 1970 to 2006 due to overfishing of dominant, large-bodied groundfish across a 300 000-km2 region of the Northwest Atlantic. Annually, similarities among communities decayed slowly with increasing geographic distance in this open system, but through time the decorrelation distance declined by 33%, concomitant with widespread reductions in biomass, body size, and community evenness. The decline in connectivity stemmed from an erosion of community similarity among local subregions separated by distances as small as 100 km. Larger fish, of the same species, contribute proportionally more viable offspring, so observed body size reductions will have affected maternal output. The cumulative effect of nonlinear maternal influences on egg/larval quality may have compromised the spatial scale of effective larval dispersal, which may account for the delayed recovery of certain member species. Our study adds strong support for using the spatial scale of similarity as an indicator of metacommunity stability both to understand the spatial impacts of exploitation and to refine how spatial structure is used in management plans.
Using Unplanned Fires to Help Suppressing Future Large Fires in Mediterranean Forests
Regos, Adrián; Aquilué, Núria; Retana, Javier; De Cáceres, Miquel; Brotons, Lluís
2014-01-01
Despite the huge resources invested in fire suppression, the impact of wildfires has considerably increased across the Mediterranean region since the second half of the 20th century. Modulating fire suppression efforts in mild weather conditions is an appealing but hotly-debated strategy to use unplanned fires and associated fuel reduction to create opportunities for suppression of large fires in future adverse weather conditions. Using a spatially-explicit fire–succession model developed for Catalonia (Spain), we assessed this opportunistic policy by using two fire suppression strategies that reproduce how firefighters in extreme weather conditions exploit previous fire scars as firefighting opportunities. We designed scenarios by combining different levels of fire suppression efficiency and climatic severity for a 50-year period (2000–2050). An opportunistic fire suppression policy induced large-scale changes in fire regimes and decreased the area burnt under extreme climate conditions, but only accounted for up to 18–22% of the area to be burnt in reference scenarios. The area suppressed in adverse years tended to increase in scenarios with increasing amounts of area burnt during years dominated by mild weather. Climate change had counterintuitive effects on opportunistic fire suppression strategies. Climate warming increased the incidence of large fires under uncontrolled conditions but also indirectly increased opportunities for enhanced fire suppression. Therefore, to shift fire suppression opportunities from adverse to mild years, we would require a disproportionately large amount of area burnt in mild years. We conclude that the strategic planning of fire suppression resources has the potential to become an important cost-effective fuel-reduction strategy at large spatial scale. We do however suggest that this strategy should probably be accompanied by other fuel-reduction treatments applied at broad scales if large-scale changes in fire regimes are to be achieved, especially in the wider context of climate change. PMID:24727853
Using unplanned fires to help suppressing future large fires in Mediterranean forests.
Regos, Adrián; Aquilué, Núria; Retana, Javier; De Cáceres, Miquel; Brotons, Lluís
2014-01-01
Despite the huge resources invested in fire suppression, the impact of wildfires has considerably increased across the Mediterranean region since the second half of the 20th century. Modulating fire suppression efforts in mild weather conditions is an appealing but hotly-debated strategy to use unplanned fires and associated fuel reduction to create opportunities for suppression of large fires in future adverse weather conditions. Using a spatially-explicit fire-succession model developed for Catalonia (Spain), we assessed this opportunistic policy by using two fire suppression strategies that reproduce how firefighters in extreme weather conditions exploit previous fire scars as firefighting opportunities. We designed scenarios by combining different levels of fire suppression efficiency and climatic severity for a 50-year period (2000-2050). An opportunistic fire suppression policy induced large-scale changes in fire regimes and decreased the area burnt under extreme climate conditions, but only accounted for up to 18-22% of the area to be burnt in reference scenarios. The area suppressed in adverse years tended to increase in scenarios with increasing amounts of area burnt during years dominated by mild weather. Climate change had counterintuitive effects on opportunistic fire suppression strategies. Climate warming increased the incidence of large fires under uncontrolled conditions but also indirectly increased opportunities for enhanced fire suppression. Therefore, to shift fire suppression opportunities from adverse to mild years, we would require a disproportionately large amount of area burnt in mild years. We conclude that the strategic planning of fire suppression resources has the potential to become an important cost-effective fuel-reduction strategy at large spatial scale. We do however suggest that this strategy should probably be accompanied by other fuel-reduction treatments applied at broad scales if large-scale changes in fire regimes are to be achieved, especially in the wider context of climate change.
Davidesco, Ido; Harel, Michal; Ramot, Michal; Kramer, Uri; Kipervasser, Svetlana; Andelman, Fani; Neufeld, Miri Y; Goelman, Gadi; Fried, Itzhak; Malach, Rafael
2013-01-16
One of the puzzling aspects in the visual attention literature is the discrepancy between electrophysiological and fMRI findings: whereas fMRI studies reveal strong attentional modulation in the earliest visual areas, single-unit and local field potential studies yielded mixed results. In addition, it is not clear to what extent spatial attention effects extend from early to high-order visual areas. Here we addressed these issues using electrocorticography recordings in epileptic patients. The patients performed a task that allowed simultaneous manipulation of both spatial and object-based attention. They were presented with composite stimuli, consisting of a small object (face or house) superimposed on a large one, and in separate blocks, were instructed to attend one of the objects. We found a consistent increase in broadband high-frequency (30-90 Hz) power, but not in visual evoked potentials, associated with spatial attention starting with V1/V2 and continuing throughout the visual hierarchy. The magnitude of the attentional modulation was correlated with the spatial selectivity of each electrode and its distance from the occipital pole. Interestingly, the latency of the attentional modulation showed a significant decrease along the visual hierarchy. In addition, electrodes placed over high-order visual areas (e.g., fusiform gyrus) showed both effects of spatial and object-based attention. Overall, our results help to reconcile previous observations of discrepancy between fMRI and electrophysiology. They also imply that spatial attention effects can be found both in early and high-order visual cortical areas, in parallel with their stimulus tuning properties.
Toward a RPC-based muon tomography system for cargo containers.
NASA Astrophysics Data System (ADS)
Baesso, P.; Cussans, D.; Thomay, C.; Velthuis, J.
2014-10-01
A large area scanner for cosmic muon tomography is currently being developed at University of Bristol. Thanks to their abundance and penetrating power, cosmic muons have been suggested as ideal candidates to scan large containers in search of special nuclear materials, which are characterized by high-Z and high density. The feasibility of such a scanner heavily depends on the detectors used to track the muons: for a typical container, the minimum required sensitive area is of the order of 100 2. The spatial resolution required depends on the geometrical configuration of the detectors. For practical purposes, a resolution of the order of 1 mm or better is desirable. A good time resolution can be exploited to provide momentum information: a resolution of the order of nanoseconds can be used to separate sub-GeV muons from muons with higher energies. Resistive plate chambers have a low cost per unit area and good spatial and time resolution; these features make them an excellent choice as detectors for muon tomography. In order to instrument a large area demonstrator we have produced 25 new readout boards and 30 glass RPCs. The RPCs measure 1800 mm× 600 mm and are read out using 1.68 mm pitch copper strips. The chambers were tested with a standardized procedure, i.e. without optimizing the working parameters to take into account differences in the manufacturing process, and the results show that the RPCs have an efficiency between 87% and 95%. The readout electronics show a signal to noise ratio greater than 20 for minimum ionizing particles. Spatial resolution better than 500 μm can easily be achieved using commercial read out ASICs. These results are better than the original minimum requirements to pass the tests and we are now ready to install the detectors.
Tallis, Heather; Cole, Aaron; Schill, Steven; Martin, Erik; Heiner, Michael; Paiz, Marie-Claire; Aldous, Allison; Apse, Colin; Nickel, Barry
2017-01-01
Rapidly developing countries contain both the bulk of intact natural areas and biodiversity, and the greatest untapped natural resource stocks, placing them at the forefront of “green” economic development opportunities. However, most lack scientific tools to create development plans that account for biodiversity and ecosystem services, diminishing the real potential to be sustainable. Existing methods focus on biodiversity and carbon priority areas across large geographies (e.g., countries, states/provinces), leaving out essential services associated with water supplies, among others. These hydrologic ecosystem services (HES) are especially absent from methods applied at large geographies and in data-limited contexts. Here, we present a novel, spatially explicit, and relatively simple methodology to identify countrywide HES priority areas. We applied our methodology to the Gabonese Republic, a country undergoing a major economic transformation under a governmental commitment to balance conservation and development goals. We present the first national-scale maps of HES priority areas across Gabon for erosion control, nutrient retention, and groundwater recharge. Priority sub-watersheds covered 44% of the country’s extent. Only 3% of the country was identified as a priority area for all HES simultaneously, highlighting the need to conserve different areas for each different hydrologic service. While spatial tradeoffs occur amongst HES, we identified synergies with two other conservation values, given that 66% of HES priority areas intersect regions of above average area-weighted (by sub-watersheds) total forest carbon stocks and 38% intersect with terrestrial national parks. Considering implications for development, we identified HES priority areas overlapping current or proposed major roads, forestry concessions, and active mining concessions, highlighting the need for proactive planning for avoidance areas and compensatory offsets to mitigate potential conflicts. Collectively, our results provide insight into strategies to protect HES as part of Gabon’s development strategy, while providing a replicable methodology for application to new scales, geographies, and policy contexts. PMID:28594870
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sadoulet, B.
The use of drift chambers in the field of high energy physics is reviewed including existing apparatus, plans and dreams. Comments are made especially on low cost large area drift chambers, use of pulse height information and high spatial resolution applications. (auth)
Chu, Hone-Jay; Lin, Bo-Cheng; Yu, Ming-Run; Chan, Ta-Chien
2016-12-13
Outbreaks of infectious diseases or multi-casualty incidents have the potential to generate a large number of patients. It is a challenge for the healthcare system when demand for care suddenly surges. Traditionally, valuation of heath care spatial accessibility was based on static supply and demand information. In this study, we proposed an optimal model with the three-step floating catchment area (3SFCA) to account for the supply to minimize variability in spatial accessibility. We used empirical dengue fever outbreak data in Tainan City, Taiwan in 2015 to demonstrate the dynamic change in spatial accessibility based on the epidemic trend. The x and y coordinates of dengue-infected patients with precision loss were provided publicly by the Tainan City government, and were used as our model's demand. The spatial accessibility of heath care during the dengue outbreak from August to October 2015 was analyzed spatially and temporally by producing accessibility maps, and conducting capacity change analysis. This study also utilized the particle swarm optimization (PSO) model to decrease the spatial variation in accessibility and shortage areas of healthcare resources as the epidemic went on. The proposed method in this study can help decision makers reallocate healthcare resources spatially when the ratios of demand and supply surge too quickly and form clusters in some locations.
Strong Spatial Influence on Colonization Rates in a Pioneer Zooplankton Metacommunity
Frisch, Dagmar; Cottenie, Karl; Badosa, Anna; Green, Andy J.
2012-01-01
The magnitude of community-wide dispersal is central to metacommunity models, yet dispersal is notoriously difficult to quantify in passive and cryptic dispersers such as many freshwater invertebrates. By overcoming the problem of quantifying dispersal rates, colonization rates into new habitats can provide a useful estimate of the magnitude of effective dispersal. Here we study the influence of spatial and local processes on colonization rates into new ponds that indicate differential dispersal limitation of major zooplankton taxa, with important implications for metacommunity dynamics. We identify regional and local factors that affect zooplankton colonization rates and spatial patterns in a large-scale experimental system. Our study differs from others in the unique setup of the experimental pond area by which we were able to test spatial and environmental variables at a large spatial scale. We quantified colonization rates separately for the Copepoda, Cladocera and Rotifera from samples collected over a period of 21 months in 48 newly constructed temporary ponds of 0.18–2.95 ha distributed in a restored wetland area of 2,700 ha in Doñana National Park, Southern Spain. Species richness upon initial sampling of new ponds was about one third of that in reference ponds, although the rate of detection of new species from thereon were not significantly different, probably owing to high turnover in the dynamic, temporary reference ponds. Environmental heterogeneity had no detectable effect on colonization rates in new ponds. In contrast, connectivity, space (based on latitude and longitude) and surface area were key determinants of colonization rates for copepods and cladocerans. This suggests dispersal limitation in cladocerans and copepods, but not in rotifers, possibly due to differences in propagule size and abundance. PMID:22792241
Strong spatial influence on colonization rates in a pioneer zooplankton metacommunity.
Frisch, Dagmar; Cottenie, Karl; Badosa, Anna; Green, Andy J
2012-01-01
The magnitude of community-wide dispersal is central to metacommunity models, yet dispersal is notoriously difficult to quantify in passive and cryptic dispersers such as many freshwater invertebrates. By overcoming the problem of quantifying dispersal rates, colonization rates into new habitats can provide a useful estimate of the magnitude of effective dispersal. Here we study the influence of spatial and local processes on colonization rates into new ponds that indicate differential dispersal limitation of major zooplankton taxa, with important implications for metacommunity dynamics. We identify regional and local factors that affect zooplankton colonization rates and spatial patterns in a large-scale experimental system. Our study differs from others in the unique setup of the experimental pond area by which we were able to test spatial and environmental variables at a large spatial scale. We quantified colonization rates separately for the Copepoda, Cladocera and Rotifera from samples collected over a period of 21 months in 48 newly constructed temporary ponds of 0.18-2.95 ha distributed in a restored wetland area of 2,700 ha in Doñana National Park, Southern Spain. Species richness upon initial sampling of new ponds was about one third of that in reference ponds, although the rate of detection of new species from thereon were not significantly different, probably owing to high turnover in the dynamic, temporary reference ponds. Environmental heterogeneity had no detectable effect on colonization rates in new ponds. In contrast, connectivity, space (based on latitude and longitude) and surface area were key determinants of colonization rates for copepods and cladocerans. This suggests dispersal limitation in cladocerans and copepods, but not in rotifers, possibly due to differences in propagule size and abundance.
Lamp, Gemma; Alexander, Bonnie; Laycock, Robin; Crewther, David P; Crewther, Sheila G
2016-01-01
Mapping of the underlying neural mechanisms of visuo-spatial working memory (WM) has been shown to consistently elicit activity in right hemisphere dominant fronto-parietal networks. However to date, the bulk of neuroimaging literature has focused largely on the maintenance aspect of visuo-spatial WM, with a scarcity of research into the aspects of WM involving manipulation of information. Thus, this study aimed to compare maintenance-only with maintenance and manipulation of visuo-spatial stimuli (3D cube shapes) utilizing a 1-back task while functional magnetic resonance imaging (fMRI) scans were acquired. Sixteen healthy participants (9 women, M = 23.94 years, SD = 2.49) were required to perform the 1-back task with or without mentally rotating the shapes 90° on a vertical axis. When no rotation was required (maintenance-only condition), a right hemispheric lateralization was revealed across fronto-parietal areas. However, when the task involved maintaining and manipulating the same stimuli through 90° rotation, activation was primarily seen in the bilateral parietal lobe and left fusiform gyrus. The findings confirm that the well-established right lateralized fronto-parietal networks are likely to underlie simple maintenance of visuo-spatial stimuli. The results also suggest that the added demand of manipulation of information maintained online appears to require further neural recruitment of functionally related areas. In particular mental rotation of visuospatial stimuli required bilateral parietal areas, and the left fusiform gyrus potentially to maintain a categorical or object representation. It can be concluded that WM is a complex neural process involving the interaction of an increasingly large network.
Lamp, Gemma; Alexander, Bonnie; Laycock, Robin; Crewther, David P.; Crewther, Sheila G.
2016-01-01
Mapping of the underlying neural mechanisms of visuo-spatial working memory (WM) has been shown to consistently elicit activity in right hemisphere dominant fronto-parietal networks. However to date, the bulk of neuroimaging literature has focused largely on the maintenance aspect of visuo-spatial WM, with a scarcity of research into the aspects of WM involving manipulation of information. Thus, this study aimed to compare maintenance-only with maintenance and manipulation of visuo-spatial stimuli (3D cube shapes) utilizing a 1-back task while functional magnetic resonance imaging (fMRI) scans were acquired. Sixteen healthy participants (9 women, M = 23.94 years, SD = 2.49) were required to perform the 1-back task with or without mentally rotating the shapes 90° on a vertical axis. When no rotation was required (maintenance-only condition), a right hemispheric lateralization was revealed across fronto-parietal areas. However, when the task involved maintaining and manipulating the same stimuli through 90° rotation, activation was primarily seen in the bilateral parietal lobe and left fusiform gyrus. The findings confirm that the well-established right lateralized fronto-parietal networks are likely to underlie simple maintenance of visuo-spatial stimuli. The results also suggest that the added demand of manipulation of information maintained online appears to require further neural recruitment of functionally related areas. In particular mental rotation of visuospatial stimuli required bilateral parietal areas, and the left fusiform gyrus potentially to maintain a categorical or object representation. It can be concluded that WM is a complex neural process involving the interaction of an increasingly large network. PMID:27199694
GREGORY P. ASNER; MICHAEL KELLER; JOSEN M. SILVA
2004-01-01
Selective logging is a dominant form of land use in the Amazon basin and throughout the humid tropics, yet little is known about the spatial variability of forest canopy gap formation and closure following timber harvests. We established chronosequences of large-area (14â158 ha) selective logging sites spanning a 3.5-year period of forest regeneration and two distinct...
Ram Deo; Matthew Russell; Grant Domke; Hans-Erik Andersen; Warren Cohen; Christopher Woodall
2017-01-01
Large-area assessment of aboveground tree biomass (AGB) to inform regional or national forest monitoring programs can be efficiently carried out by combining remotely sensed data and field sample measurements through a generic statistical model, in contrast to site-specific models. We integrated forest inventory plot data with spatial predictors from Landsat time-...
Spatial embedding of structural similarity in the cerebral cortex
Song, H. Francis; Kennedy, Henry; Wang, Xiao-Jing
2014-01-01
Recent anatomical tracing studies have yielded substantial amounts of data on the areal connectivity underlying distributed processing in cortex, yet the fundamental principles that govern the large-scale organization of cortex remain unknown. Here we show that functional similarity between areas as defined by the pattern of shared inputs or outputs is a key to understanding the areal network of cortex. In particular, we report a systematic relation in the monkey, human, and mouse cortex between the occurrence of connections from one area to another and their similarity distance. This characteristic relation is rooted in the wiring distance dependence of connections in the brain. We introduce a weighted, spatially embedded random network model that robustly gives rise to this structure, as well as many other spatial and topological properties observed in cortex. These include features that were not accounted for in any previous model, such as the wide range of interareal connection weights. Connections in the model emerge from an underlying distribution of spatially embedded axons, thereby integrating the two scales of cortical connectivity—individual axons and interareal pathways—into a common geometric framework. These results provide insights into the origin of large-scale connectivity in cortex and have important implications for theories of cortical organization. PMID:25368200
NASA Astrophysics Data System (ADS)
Yang, S. W.; Ma, J. J.; Wang, J. M.
2018-04-01
As representative vulnerable regions of the city, dense distribution areas of temporary color steel building are a major target for control of fire risks, illegal buildings, environmental supervision, urbanization quality and enhancement for city's image. In the domestic and foreign literature, the related research mainly focuses on fire risks and violation monitoring. However, due to temporary color steel building's special characteristics, the corresponding research about temporal and spatial distribution, and influence on urban spatial form etc. has not been reported. Therefore, firstly, the paper research aim plans to extract information of large-scale color steel building from high-resolution images. Secondly, the color steel plate buildings were classified, and the spatial and temporal distribution and aggregation characteristics of small (temporary buildings) and large (factory building, warehouse, etc.) buildings were studied respectively. Thirdly, the coupling relationship between the spatial distribution of color steel plate and the spatial pattern of urban space was analysed. The results show that there is a good coupling relationship between the color steel plate building and the urban spatial form. Different types of color steel plate building represent the pattern of regional differentiation of urban space and the phased pattern of urban development.
Ozone distribution in remote ecologically vulnerable terrain of the southern Sierra Nevada, CA
Jeanne Panek; David Saah; Annie Esperanza; Andrzej Bytnerowicz; Witold Fraczek; Ricardo Cisneros
2013-01-01
Ozone concentration spatial patterns remain largely uncharacterized across the extensive wilderness areas of the Sierra Nevada, CA, despite being downwind of major pollution sources. These natural areas, including four national parks and four national forests, contain forest species that are susceptible to ozone injury. Forests stressed by ozone are also more...
Landsat 7 ETM+ provides an opportunity to extend the area and frequency with
which we are able to monitor the Earth's surface with fine spatial resolution
data. To take advantage of this opportunity it is necessary to move beyond the
traditional image-by-image approac...
Landscape models of adult coho salmon density examined at four spatial extents
Julie C. Firman; E. Ashley Steel; David W. Jensen; Kelly M. Burnett; Kelly Christiansen; Blake E. Feist; David P. Larsen; Kara Anlauf
2011-01-01
Salmon occupy large areas over which comprehensive surveys are not feasible owing to the prohibitive expense of surveying thousands of kilometers of streams. Studies of these populations generally rely on sampling a small portion of the distribution of the species. However, managers often need information about areas that have not been visited. The availability of...
Characterization and spatial modeling of urban sprawl in the Wuhan Metropolitan Area, China
NASA Astrophysics Data System (ADS)
Zeng, Chen; Liu, Yaolin; Stein, Alfred; Jiao, Limin
2015-02-01
Urban sprawl has led to environmental problems and large losses of arable land in China. In this study, we monitor and model urban sprawl by means of a combination of remote sensing, geographical information system and spatial statistics. We use time-series data to explore the potential socio-economic driving forces behind urban sprawl, and spatial models in different scenarios to explore the spatio-temporal interactions. The methodology is applied to the city of Wuhan, China, for the period from 1990 to 2013. The results reveal that the built-up land has expanded and has dispersed in urban clusters. Population growth, and economic and transportation development are still the main causes of urban sprawl; however, when they have developed to certain levels, the area affected by construction in urban areas (Jian Cheng Qu (JCQ)) and the area of cultivated land (ACL) tend to be stable. Spatial regression models are shown to be superior to the traditional models. The interaction among districts with the same administrative status is stronger than if one of those neighbors is in the city center and the other in the suburban area. The expansion of urban built-up land is driven by the socio-economic development at the same period, and greatly influenced by its spatio-temporal neighbors. We conclude that the integration of remote sensing, a geographical information system, and spatial statistics offers an excellent opportunity to explore the spatio-temporal variation and interactions among the districts in the sprawling metropolitan areas. Relevant regulations to control the urban sprawl process are suggested accordingly.
NASA Astrophysics Data System (ADS)
Takodjou Wambo, Jonas Didero; Ganno, Sylvestre; Djonthu Lahe, Yannick Sthopira; Kouankap Nono, Gus Djibril; Fossi, Donald Hermann; Tchouatcha, Milan Stafford; Nzenti, Jean Paul
2018-06-01
Linear and nonlinear geostatistic is commonly used in ore grade estimation and seldom used in Geographical Information System (GIS) technology. In this study, we suggest an approach based on geostatistic linear ordinary kriging (OK) and Geographical Information System (GIS) techniques to investigate the spatial distribution of alluvial gold content, mineralized and gangue layers thicknesses from 73 pits at the Ngoura-Colomines area with the aim to determine controlling factors for the spatial distribution of mineralization and delineate the most prospective area for primary gold mineralization. Gold content varies between 0.1 and 4.6 g/m3 and has been broadly grouped into three statistical classes. These classes have been spatially subdivided into nine zones using ordinary kriging model based on physical and topographical characteristics. Both mineralized and barren layer thicknesses show randomly spatial distribution, and there is no correlation between these parameters and the gold content. This approach has shown that the Ngoura-Colomines area is located in a large shear zone compatible with the Riedel fault system composed of P and P‧ fractures oriented NE-SW and NNE-SSW respectively; E-W trending R fractures and R‧ fractures with NW-SE trends that could have contributed significantly to the establishment of this gold mineralization. The combined OK model and GIS analysis have led to the delineation of Colomines, Tissongo, Madubal and Boutou villages as the most prospective areas for the exploration of primary gold deposit in the study area.
Representation of critical natural capital in China.
Lü, Yihe; Zhang, Liwei; Zeng, Yuan; Fu, Bojie; Whitham, Charlotte; Liu, Shuguang; Wu, Bingfang
2017-08-01
Traditional means of assessing representativeness of conservation value in protected areas depend on measures of structural biodiversity. The effectiveness of priority conservation areas at representing critical natural capital (CNC) (i.e., an essential and renewable subset of natural capital) remains largely unknown. We analyzed the representativeness of CNC-conservation priority areas in national nature reserves (i.e., nature reserves under jurisdiction of the central government with large spatial distribution across the provinces) in China with a new biophysical-based composite indicator approach. With this approach, we integrated the net primary production of vegetation, topography, soil, and climate variables to map and rank terrestrial ecosystems capacities to generate CNC. National nature reserves accounted for 6.7% of CNC-conservation priority areas across China. Considerable gaps (35.2%) existed between overall (or potential) CNC representativeness nationally and CNC representation in national reserves, and there was significant spatial heterogeneity of representativeness in CNC-conservation priority areas at the regional and provincial levels. For example, the best and worst representations were, respectively, 13.0% and 1.6% regionally and 28.9% and 0.0% provincially. Policy in China is transitioning toward the goal of an ecologically sustainable civilization. We identified CNC-conservation priority areas and conservation gaps and thus contribute to the policy goals of optimization of the national nature reserve network and the demarcation of areas critical to improving the representativeness and conservation of highly functioning areas of natural capital. Moreover, our method for assessing representation of CNC can be easily adapted to other large-scale networks of conservation areas because few data are needed, and our model is relatively simple. © 2017 Society for Conservation Biology.
NASA Astrophysics Data System (ADS)
Kubacka, Marta
2013-04-01
The issue of spatial development, and thus proper environmental management and protection at naturally valuable areas is today considered a major hazard to the stability of the World ecological system. The increasing demand for areas with substantial environmental and landscape assets, incorrect spatial development, improper implementation of law as well as low citizen awareness bring about significant risk of irrevocable loss of naturally valuable areas. The elaboration of a Decision Support System in the form of collection of spatial data will facilitate solving complex problems concerning spatial development. The elaboration of a model utilizing a number of IT tools will boost the effectiveness of taking spatial decisions by decision-makers. Proper spatial data management becomes today a key element in management based on knowledge, namely sustainable development. Decision Support Systems are definied as model-based sets of procedures for processing data and judgments to assist a manager in his decision-making. The main purpose of the project was to elaborate the spatial decision support system for the Sieraków Landscape Park. A landscape park in Poland comprises a protected area due to environmental, historic and cultural values as well as landscape assets for the purpose of maintaining and popularizing these values in the conditions of sustainable development. It also defines the forms of protected area management and introduces bans concerning activity at these areas by means of the obligation to prepare and implement environmental protection plans by a director of the complex of landscape parks. As opposed to national parks and reserves, natural landscape parks are not the areas free from economic activity, thus agricultural lands, forest lands and other real properties located within the boundaries of natural landscape parks are subject to economic utilization Research area was subject to the analysis with respect to the implementation of investment actions consisting mainly in the agricultural economy. Versatile relief, diversified geological formations as well as the depth of depositing ground water and the risk of flooding have impact on diversified possibilities of the land use. Intensive agricultural economy at large field area and forestry constitute the major human activity at the area of the Park. The criteria which may be in the form of factors (e.g. soil with much agricultural suitability or very low slopes) or limitations (e.g. soils with little agricultural suitability, forest areas in close vicinity of water bodies) constitute the grounds for taking a decision on determining the areas for agricultural economy. The thesis presents the possibilities which Geographic Information Systems provide at the stage of taking spatial decisions at environmentally valuable areas. The pressure on environmentally valuable areas is growing all over the world and it may be assumed that spatial conflicts between the development of agricultural areas and the natural environment will intensify. Spatial planning is the best possibilities of reducing and mitigating this pressure. This process should take into consideration the provisions of the European Landscape Convention which is the basic instrument for landscape preservation and nature protection.
Kihal-Talantikite, Wahida; Deguen, Séverine; Padilla, Cindy; Siebert, Muriel; Couchoud, Cécile; Vigneau, Cécile; Bayat, Sahar
2015-02-01
Several studies have investigated the implication of biological and environmental factors on geographic variations of end-stage renal disease (ESRD) incidence at large area scales, but none of them assessed the implication of neighbourhood characteristics (healthcare supply, socio-economic level and urbanization degree) on spatial repartition of ESRD. We evaluated the spatial implications of adjustment for neighbourhood characteristics on the spatial distribution of ESRD incidence at the smallest geographic unit in France. All adult patients living in Bretagne and beginning renal replacement therapy during the 2004-09 period were included. Their residential address was geocoded at the census block level. Each census block was characterized by socio-economic deprivation index, healthcare supply and rural/urban typology. Using a spatial scan statistic, we examined whether there were significant clusters of high risk of ESRD incidence. The ESRD incidence was non-randomly spatially distributed, with a cluster of high risk in the western Bretagne region (relative risk, RR = 1.28, P-value = 0.0003). Adjustment for sex, age and neighbourhood characteristics induced cluster shifts. After these adjustments, a significant cluster (P = 0.013) persisted. Our spatial analysis of ESRD incidence at a fine scale, across a mixed rural/urban area, indicated that, beyond age and sex, neighbourhood characteristics explained a great part of spatial distribution of ESRD incidence. However, to better understand spatial variation of ESRD incidence, it would be necessary to research and adjust for other determinants of ESRD.
Turner, D.P.; Dodson, R.; Marks, D.
1996-01-01
Spatially distributed biogeochemical models may be applied over grids at a range of spatial resolutions, however, evaluation of potential errors and loss of information at relatively coarse resolutions is rare. In this study, a georeferenced database at the 1-km spatial resolution was developed to initialize and drive a process-based model (Forest-BGC) of water and carbon balance over a gridded 54976 km2 area covering two river basins in mountainous western Oregon. Corresponding data sets were also prepared at 10-km and 50-km spatial resolutions using commonly employed aggregation schemes. Estimates were made at each grid cell for climate variables including daily solar radiation, air temperature, humidity, and precipitation. The topographic structure, water holding capacity, vegetation type and leaf area index were likewise estimated for initial conditions. The daily time series for the climatic drivers was developed from interpolations of meteorological station data for the water year 1990 (1 October 1989-30 September 1990). Model outputs at the 1-km resolution showed good agreement with observed patterns in runoff and productivity. The ranges for model inputs at the 10-km and 50-km resolutions tended to contract because of the smoothed topography. Estimates for mean evapotranspiration and runoff were relatively insensitive to changing the spatial resolution of the grid whereas estimates of mean annual net primary production varied by 11%. The designation of a vegetation type and leaf area at the 50-km resolution often subsumed significant heterogeneity in vegetation, and this factor accounted for much of the difference in the mean values for the carbon flux variables. Although area wide means for model outputs were generally similar across resolutions, difference maps often revealed large areas of disagreement. Relatively high spatial resolution analyses of biogeochemical cycling are desirable from several perspectives and may be particularly important in the study of the potential impacts of climate change.
LaDage, Lara D.; Roth, Timothy C.; Downs, Cynthia J.; Sinervo, Barry; Pravosudov, Vladimir V.
2017-01-01
Variation in an animal's spatial environment can induce variation in the hippocampus, an area of the brain involved in spatial cognitive processing. Specifically, increased spatial area use is correlated with increased hippocampal attributes, such as volume and neurogenesis. In the side-blotched lizard (Uta stansburiana), males demonstrate alternative reproductive tactics and are either territorial—defending large, clearly defined spatial boundaries—or non-territorial—traversing home ranges that are smaller than the territorial males' territories. Our previous work demonstrated cortical volume (reptilian hippocampal homolog) correlates with these spatial niches. We found that territorial holders have larger medial cortices than non-territory holders, yet these differences in the neural architecture demonstrated some degree of plasticity as well. Although we have demonstrated a link among territoriality, spatial use, and brain plasticity, the mechanisms that underlie this relationship are unclear. Previous studies found that higher testosterone levels can induce increased use of the spatial area and can cause an upregulation in hippocampal attributes. Thus, testosterone may be the mechanistic link between spatial area use and the brain. What remains unclear, however, is if testosterone can affect the cortices independent of spatial experiences and whether testosterone differentially interacts with territorial status to produce the resultant cortical phenotype. In this study, we compared neurogenesis as measured by the total number of doublecortin-positive cells and cortical volume between territorial and non-territorial males supplemented with testosterone. We found no significant differences in the number of doublecortin-positive cells or cortical volume among control territorial, control non-territorial, and testosterone-supplemented non-territorial males, while testosterone-supplemented territorial males had smaller medial cortices containing fewer doublecortin-positive cells. These results demonstrate that testosterone can modulate medial cortical attributes outside of differential spatial processing experiences but that territorial males appear to be more sensitive to alterations in testosterone levels compared with non-territorial males. PMID:28298883
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.
Maximizing Conservation and Production with Intensive Forest Management: It's All About Location
NASA Astrophysics Data System (ADS)
Tittler, Rebecca; Filotas, Élise; Kroese, Jasmin; Messier, Christian
2015-11-01
Functional zoning has been suggested as a way to balance the needs of a viable forest industry with those of healthy ecosystems. Under this system, part of the forest is set aside for protected areas, counterbalanced by intensive and extensive management of the rest of the forest. Studies indicate this may provide adequate timber while minimizing road construction and favoring the development of large mature and old stands. However, it is unclear how the spatial arrangement of intensive management areas may affect the success of this zoning. Should these areas be agglomerated or dispersed throughout the forest landscape? Should managers prioritize (a) proximity to existing roads, (b) distance from protected areas, or (c) site-specific productivity? We use a spatially explicit landscape simulation model to examine the effects of different spatial scenarios on landscape structure, connectivity for native forest wildlife, stand diversity, harvest volume, and road construction: (1) random placement of intensive management areas, and (2-8) all possible combinations of rules (a)-(c). Results favor the agglomeration of intensive management areas. For most wildlife species, connectivity was the highest when intensive management was far from the protected areas. This scenario also resulted in relatively high harvest volumes. Maximizing distance of intensive management areas from protected areas may therefore be the best way to maximize the benefits of intensive management areas while minimizing their potentially negative effects on forest structure and biodiversity.
River eutrophication: irrigated vs. non-irrigated agriculture through different spatial scales.
Monteagudo, Laura; Moreno, José Luis; Picazo, Félix
2012-05-15
The main objective of this study was to determine how spatial scale may affect the results when relating land use to nutrient enrichment of rivers and, secondly, to investigate which agricultural practices are more responsible for river eutrophication in the study area. Agriculture was split into three subclasses (irrigated, non-irrigated and low-impact agriculture) which were correlated to stream nutrient concentration on four spatial scales: large scale (drainage area of total subcatchment and 100 m wide subcatchment corridors) and local scale (5 and 1 km radius buffers). Nitrate, ammonium and orthophosphate concentrations and land use composition (agriculture, urban and forest) were measured at 130 river reaches in south-central Spain during the 2001-2009 period. Results suggested that different spatial scales may lead to different conclusions. Spatial autocorrelation and the inadequate representation of some land uses produced unreal results on large scales. Conversely, local scales did not show data autocorrelation and agriculture subclasses were well represented. The local scale of 1 km buffer was the most appropriate to detect river eutrophication in central Spanish rivers, with irrigated cropland as the main cause of river pollution by nitrate. As regards river management, a threshold of 50% irrigated cropland within a 1 km radius buffer has been obtained using breakpoint regression analysis. This means that no more than 50% of irrigation croplands should be allowed near river banks in order to avoid river eutrophication. Finally, a methodological approach is proposed to choose the appropriate spatial scale when studying river eutrophication caused by diffuse pollution like agriculture. Copyright © 2012 Elsevier Ltd. All rights reserved.
Moving to stay in place: behavioral mechanisms for coexistence of African large carnivores.
Vanak, Abi Tamim; Fortin, Daniel; Thaker, Maria; Ogden, Monika; Owen, Cailey; Greatwood, Sophie; Slotow, Rob
2013-11-01
Most ecosystems have multiple predator species that not only compete for shared prey, but also pose direct threats to each other. These intraguild interactions are key drivers of carnivore community structure, with ecosystem-wide cascading effects. Yet, behavioral mechanisms for coexistence of multiple carnivore species remain poorly understood. The challenges of studying large, free-ranging carnivores have resulted in mainly coarse-scale examination of behavioral strategies without information about all interacting competitors. We overcame some of these challenges by examining the concurrent fine-scale movement decisions of almost all individuals of four large mammalian carnivore species in a closed terrestrial system. We found that the intensity ofintraguild interactions did not follow a simple hierarchical allometric pattern, because spatial and behavioral tactics of subordinate species changed with threat and resource levels across seasons. Lions (Panthera leo) were generally unrestricted and anchored themselves in areas rich in not only their principal prey, but also, during periods of resource limitation (dry season), rich in the main prey for other carnivores. Because of this, the greatest cost (potential intraguild predation) for subordinate carnivores was spatially coupled with the highest potential benefit of resource acquisition (prey-rich areas), especially in the dry season. Leopard (P. pardus) and cheetah (Acinonyx jubatus) overlapped with the home range of lions but minimized their risk using fine-scaled avoidance behaviors and restricted resource acquisition tactics. The cost of intraguild competition was most apparent for cheetahs, especially during the wet season, as areas with energetically rewarding large prey (wildebeest) were avoided when they overlapped highly with the activity areas of lions. Contrary to expectation, the smallest species (African wild dog, Lycaon pictus) did not avoid only lions, but also used multiple tactics to minimize encountering all other competitors. Intraguild competition thus forced wild dogs into areas with the lowest resource availability year round. Coexistence of multiple carnivore species has typically been explained by dietary niche separation, but our multi-scaled movement results suggest that differences in resource acquisition may instead be a consequence of avoiding intraguild competition. We generate a more realistic representation of hierarchical behavioral interactions that may ultimately drive spatially explicit trophic structures of multi-predator communities.
NASA Astrophysics Data System (ADS)
Joshi, Neha; Mitchard, Edward TA; Woo, Natalia; Torres, Jorge; Moll-Rocek, Julian; Ehammer, Andrea; Collins, Murray; Jepsen, Martin R.; Fensholt, Rasmus
2015-03-01
Mapping anthropogenic forest disturbances has largely been focused on distinct delineations of events of deforestation using optical satellite images. In the tropics, frequent cloud cover and the challenge of quantifying forest degradation remain problematic. In this study, we detect processes of deforestation, forest degradation and successional dynamics, using long-wavelength radar (L-band from ALOS PALSAR) backscatter. We present a detection algorithm that allows for repeated disturbances on the same land, and identifies areas with slow- and fast-recovering changes in backscatter in close spatial and temporal proximity. In the study area in Madre de Dios, Peru, 2.3% of land was found to be disturbed over three years, with a false positive rate of 0.3% of area. A low, but significant, detection rate of degradation from sparse and small-scale selective logging was achieved. Disturbances were most common along the tri-national Interoceanic Highway, as well as in mining areas and areas under no land use allocation. A continuous spatial gradient of disturbance was observed, highlighting artefacts arising from imposing discrete boundaries on deforestation events. The magnitude of initial radar backscatter, and backscatter decrease, suggested that large-scale deforestation was likely in areas with initially low biomass, either naturally or since already under anthropogenic use. Further, backscatter increases following disturbance suggested that radar can be used to characterize successional disturbance dynamics, such as biomass accumulation in lands post-abandonment. The presented radar-based detection algorithm is spatially and temporally scalable, and can support monitoring degradation and deforestation in tropical rainforests with the use of products from ALOS-2 and the future SAOCOM and BIOMASS missions.
Cherenkov detectors for spatial imaging applications using discrete-energy photons
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rose, Paul B.; Erickson, Anna S., E-mail: erickson@gatech.edu
Cherenkov detectors can offer a significant advantage in spatial imaging applications when excellent timing response, low noise and cross talk, large area coverage, and the ability to operate in magnetic fields are required. We show that an array of Cherenkov detectors with crude energy resolution coupled with monochromatic photons resulting from a low-energy nuclear reaction can be used to produce a sharp image of material while providing large and inexpensive detector coverage. The analysis of the detector response to relative transmission of photons with various energies allows for reconstruction of material's effective atomic number further aiding in high-Z material identification.
NASA Technical Reports Server (NTRS)
Strahler, A. H.; Woodcock, C. E.; Logan, T. L.
1983-01-01
A timber inventory of the Eldorado National Forest, located in east-central California, provides an example of the use of a Geographic Information System (GIS) to stratify large areas of land for sampling and the collection of statistical data. The raster-based GIS format of the VICAR/IBIS software system allows simple and rapid tabulation of areas, and facilitates the selection of random locations for ground sampling. Algorithms that simplify the complex spatial pattern of raster-based information, and convert raster format data to strings of coordinate vectors, provide a link to conventional vector-based geographic information systems.
Acuña-Marrero, David; Smith, Adam N H; Hammerschlag, Neil; Hearn, Alex; Anderson, Marti J; Calich, Hannah; Pawley, Matthew D M; Fischer, Chris; Salinas-de-León, Pelayo
2017-01-01
The potential effectiveness of marine protected areas (MPAs) as a conservation tool for large sharks has been questioned due to the limited spatial extent of most MPAs in contrast to the complex life history and high mobility of many sharks. Here we evaluated the movement dynamics of a highly migratory apex predatory shark (tiger shark Galeocerdo cuvier) at the Galapagos Marine Reserve (GMR). Using data from satellite tracking passive acoustic telemetry, and stereo baited remote underwater video, we estimated residency, activity spaces, site fidelity, distributional abundances and migration patterns from the GMR and in relation to nesting beaches of green sea turtles (Chelonia mydas), a seasonally abundant and predictable prey source for large tiger sharks. Tiger sharks exhibited a high degree of philopatry, with 93% of the total satellite-tracked time across all individuals occurring within the GMR. Large sharks (> 200 cm TL) concentrated their movements in front of the two most important green sea turtle-nesting beaches in the GMR, visiting them on a daily basis during nocturnal hours. In contrast, small sharks (< 200 cm TL) rarely visited turtle-nesting areas and displayed diurnal presence at a third location where only immature sharks were found. Small and some large individuals remained in the three study areas even outside of the turtle-nesting season. Only two sharks were satellite-tracked outside of the GMR, and following long-distance migrations, both individuals returned to turtle-nesting beaches at the subsequent turtle-nesting season. The spatial patterns of residency and site fidelity of tiger sharks suggest that the presence of a predictable source of prey and suitable habitats might reduce the spatial extent of this large shark that is highly migratory in other parts of its range. This highly philopatric behaviour enhances the potential effectiveness of the GMR for their protection.
Smith, Adam N. H.; Hammerschlag, Neil; Hearn, Alex; Anderson, Marti J.; Calich, Hannah; Pawley, Matthew D. M.; Fischer, Chris; Salinas-de-León, Pelayo
2017-01-01
The potential effectiveness of marine protected areas (MPAs) as a conservation tool for large sharks has been questioned due to the limited spatial extent of most MPAs in contrast to the complex life history and high mobility of many sharks. Here we evaluated the movement dynamics of a highly migratory apex predatory shark (tiger shark Galeocerdo cuvier) at the Galapagos Marine Reserve (GMR). Using data from satellite tracking passive acoustic telemetry, and stereo baited remote underwater video, we estimated residency, activity spaces, site fidelity, distributional abundances and migration patterns from the GMR and in relation to nesting beaches of green sea turtles (Chelonia mydas), a seasonally abundant and predictable prey source for large tiger sharks. Tiger sharks exhibited a high degree of philopatry, with 93% of the total satellite-tracked time across all individuals occurring within the GMR. Large sharks (> 200 cm TL) concentrated their movements in front of the two most important green sea turtle-nesting beaches in the GMR, visiting them on a daily basis during nocturnal hours. In contrast, small sharks (< 200 cm TL) rarely visited turtle-nesting areas and displayed diurnal presence at a third location where only immature sharks were found. Small and some large individuals remained in the three study areas even outside of the turtle-nesting season. Only two sharks were satellite-tracked outside of the GMR, and following long-distance migrations, both individuals returned to turtle-nesting beaches at the subsequent turtle-nesting season. The spatial patterns of residency and site fidelity of tiger sharks suggest that the presence of a predictable source of prey and suitable habitats might reduce the spatial extent of this large shark that is highly migratory in other parts of its range. This highly philopatric behaviour enhances the potential effectiveness of the GMR for their protection. PMID:28829820
Locally-Adaptive, Spatially-Explicit Projection of U.S. Population for 2030 and 2050
McKee, Jacob J.; Rose, Amy N.; Bright, Eddie A.; ...
2015-02-03
Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Moreover, knowing the spatial distribution of future population allows for increased preparation in the event of an emergency. Building on the spatial interpolation technique previously developed for high resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically-informed spatial distribution of the projected population of the contiguous U.S. for 2030 and 2050. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection modelmore » departs from these by accounting for multiple components that affect population distribution. Modelled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the U.S. Census s projection methodology with the U.S. Census s official projection as the benchmark. Applications of our model include, but are not limited to, suitability modelling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations.« less
Locally-Adaptive, Spatially-Explicit Projection of U.S. Population for 2030 and 2050
DOE Office of Scientific and Technical Information (OSTI.GOV)
McKee, Jacob J.; Rose, Amy N.; Bright, Eddie A.
Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Moreover, knowing the spatial distribution of future population allows for increased preparation in the event of an emergency. Building on the spatial interpolation technique previously developed for high resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically-informed spatial distribution of the projected population of the contiguous U.S. for 2030 and 2050. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection modelmore » departs from these by accounting for multiple components that affect population distribution. Modelled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the U.S. Census s projection methodology with the U.S. Census s official projection as the benchmark. Applications of our model include, but are not limited to, suitability modelling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations.« less
High-fidelity large area nano-patterning of silicon with femtosecond light sheet
NASA Astrophysics Data System (ADS)
Sidhu, Mehra S.; Munjal, Pooja; Singh, Kamal P.
2018-01-01
We employ a femtosecond light sheet generated by a cylindrical lens to rapidly produce high-fidelity nano-structures over large area on silicon surface. The Fourier analysis of electron microscopy images of the laser-induced surface structures reveals sharp peaks indicating good homogeneity. We observed an emergence of second-order spatial periodicity on increasing the scan speed. Our reliable approach may rapidly nano-pattern curved solid surfaces and tiny objects for diverse potential applications in optical devices, structural coloring, plasmonic substrates and in high-harmonic generation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Willingham, Alison N.; /Ohio State U.
Statewide surveys of furbearers in Illinois indicate gray (Urocyon cinereoargenteus) and red (Vulpes vulpes) foxes have experienced substantial declines in relative abundance, whereas other species such as raccoons (Procyon lotor) and coyotes (Canis latrans) have exhibited dramatic increases during the same time period. The cause of the declines of gray and red foxes has not been identified, and the current status of gray foxes remains uncertain. Therefore, I conducted a large-scale predator survey and tracked radiocollared gray foxes from 2004 to 2007 in order to determine the distribution, survival, cause-specific mortality sources and land cover associations of gray foxes inmore » an urbanized region of northeastern Illinois, and examined the relationships between the occurrence of gray fox and the presence other species of mesopredators, specifically coyotes and raccoons. Although generalist mesopredators are common and can reach high densities in many urban areas their urban ecology is poorly understood due to their secretive nature and wariness of humans. Understanding how mesopredators utilize urbanized landscapes can be useful in the management and control of disease outbreaks, mitigation of nuisance wildlife issues, and gaining insight into how mesopredators shape wildlife communities in highly fragmented areas. I examined habitat associations of raccoons, opossums (Didelphis virginiana), domestic cats (Felis catus), coyotes, foxes (gray and red), and striped skunks (Mephitis mephitis) at multiple spatial scales in an urban environment. Gray fox occurrence was rare and widely dispersed, and survival estimates were similar to other studies. Gray fox occurrence was negatively associated with natural and semi-natural land cover types. Fox home range size increased with increasing urban development suggesting that foxes may be negatively influenced by urbanization. Gray fox occurrence was not associated with coyote or raccoon presence. However, spatial avoidance and mortality due to coyote predation was documented and disease was a major mortality source for foxes. The declining relative abundance of gray fox in Illinois is likely a result of a combination of factors. Assessment of habitat associations indicated that urban mesopredators, particularly coyotes and foxes, perceived the landscape as relatively homogeneous and that urban mesopredators interacted with the environment at scales larger than that accommodated by remnant habitat patches. Coyote and fox presence was found to be associated with a high degree of urban development at large and intermediate spatial scales. However, at a small spatial scale fox presence was associated with high density urban land cover whereas coyote presence was associated with urban development with increased forest cover. Urban habitats can offer a diversity of prey items and anthropogenic resources and natural land cover could offer coyotes daytime resting opportunities in urban areas where they may not be as tolerated as smaller foxes. Raccoons and opossums were found to utilize moderately developed landscapes with interspersed natural and semi-natural land covers at a large spatial scale, which may facilitate dispersal movements. At intermediate and small spatial scales, both species were found to utilize areas that were moderately developed and included forested land cover. These results indicated that raccoons and opossums used natural areas in proximity to anthropogenic resources. At a large spatial scale, skunk presence was associated with highly developed landscapes with interspersed natural and semi-natural land covers. This may indicate that skunks perceived the urban matrix as more homogeneous than raccoons or opossums. At an intermediate spatial scale skunks were associated with moderate levels of development and increased forest cover, which indicated that they might utilize natural land cover in proximity to human-dominated land cover. At the smallest spatial scale skunk presence was associated with forested land cover surrounded by a suburban matrix. Compared to raccoons and opossums, skunks may not be tolerated in close proximity to human development in urban areas. Domestic cat presence was positively associated with increasingly urbanized and less diverse landscapes with decreased amounts of forest and urban open space at the largest spatial scale. At an intermediate spatial scale, cat presence was associated with a moderate degree of urban development characterized by increased forest cover, and at a small spatial scale cat presence was associated with a high degree of urbanization. Free-ranging domestic cats are often associated with human-dominated landscapes and likely utilize remnant natural habitat patches for hunting purposes, which may have implications for native predator and prey species existing in fragmented habitat patches in proximity to human development.« less
Photonic Lantern Adaptive Spatial Mode Control in LMA Fiber Amplifiers using SPGD
2015-12-15
ll.mit.edu Abstract: We demonstrate adaptive-spatial mode control (ASMC) in few- moded double- clad large mode area (LMA) fiber amplifiers by using an...combination resulting in a single fundamental mode at the output is achieved. 2015 Optical Society of America OCIS codes: (140.3510) Lasers ...fiber; (140.3425) Laser stabilization; (060.2340) Fiber optics components; (110.1080) Active or adaptive optics; References and links 1. C
Vaughan, R. Greg; Heasler, Henry; Jaworowski, Cheryl; Lowenstern, Jacob B.; Keszthelyi, Laszlo P.
2014-01-01
Maps that define the current distribution of geothermally heated ground are useful toward setting a baseline for thermal activity to better detect and understand future anomalous hydrothermal and (or) volcanic activity. Monitoring changes in the dynamic thermal areas also supports decisions regarding the development of Yellowstone National Park infrastructure, preservation and protection of park resources, and ensuring visitor safety. Because of the challenges associated with field-based monitoring of a large, complex geothermal system that is spread out over a large and remote area, satellite-based thermal infrared images from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were used to map the location and spatial extent of active thermal areas, to generate thermal anomaly maps, and to quantify the radiative component of the total geothermal heat flux. ASTER thermal infrared data acquired during winter nights were used to minimize the contribution of solar heating of the surface. The ASTER thermal infrared mapping results were compared to maps of thermal areas based on field investigations and high-resolution aerial photos. Field validation of the ASTER thermal mapping is an ongoing task. The purpose of this report is to make available ASTER-based maps of Yellowstone’s thermal areas. We include an appendix containing the names and characteristics of Yellowstone’s thermal areas, georeferenced TIFF files containing ASTER thermal imagery, and several spatial data sets in Esri shapefile format.
Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations
Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T.; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P.; Rötter, Reimund P.; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank
2016-01-01
We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations. PMID:27055028
Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations.
Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P; Rötter, Reimund P; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank
2016-01-01
We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.
The Large -scale Distribution of Galaxies
NASA Astrophysics Data System (ADS)
Flin, Piotr
A review of the Large-scale structure of the Universe is given. A connection is made with the titanic work by Johannes Kepler in many areas of astronomy and cosmology. A special concern is made to spatial distribution of Galaxies, voids and walls (cellular structure of the Universe). Finaly, the author is concluding that the large scale structure of the Universe can be observed in much greater scale that it was thought twenty years ago.
Leaf area dynamics of conifer forests
DOE Office of Scientific and Technical Information (OSTI.GOV)
Margolis, H.; Oren, R.; Whitehead, D.
1995-07-01
Estimating the surface area of foliage supported by a coniferous forest canopy is critical for modeling its biological properties. Leaf area represents the surface area available for the interception of energy, the absorption of carbon dioxide, and the diffusion of water from the leaf to the atmosphere. The concept of leaf area is pertinent to the physiological and ecological dynamics of conifers at a wide range of spatial scales, from individual leaves to entire biomes. In fact, the leaf area of vegetation at a global level can be thought of as a carbon-absorbing, water-emitting membrane of variable thickness, which canmore » have an important influence on the dynamics and chemistry of the Earth`s atmosphere over both the short and the long term. Unless otherwise specified, references to leaf area herein refer to projected leaf area, i.e., the vertical projection of needles placed on a flat plane. Total leaf surface area is generally from 2.0 to 3.14 times that of projected leaf area for conifers. It has recently been suggested that hemisurface leaf area, i.e., one-half of the total surface area of a leaf, a more useful basis for expressing leaf area than is projected area. This chapter is concerned with the dynamics of coniferous forest leaf area at different spatial and temporal scales. In the first part, we consider various hypotheses related to the control of leaf area development, ranging from simple allometric relations with tree size to more complex mechanistic models that consider the movement of water and nutrients to tree canopies. In the second part, we consider various aspects of leaf area dynamics at varying spatial and temporal scales, including responses to perturbation, seasonal dynamics, genetic variation in crown architecture, the responses to silvicultural treatments, the causes and consequences of senescence, and the direct measurement of coniferous leaf area at large spatial scales using remote sensing.« less
Bressler, David W.; Fortenbaugh, Francesca C.; Robertson, Lynn C.; Silver, Michael A.
2013-01-01
Endogenous visual spatial attention improves perception and enhances neural responses to visual stimuli at attended locations. Although many aspects of visual processing differ significantly between central and peripheral vision, little is known regarding the neural substrates of the eccentricity dependence of spatial attention effects. We measured amplitudes of positive and negative fMRI responses to visual stimuli as a function of eccentricity in a large number of topographically-organized cortical areas. Responses to each stimulus were obtained when the stimulus was attended and when spatial attention was directed to a stimulus in the opposite visual hemifield. Attending to the stimulus increased both positive and negative response amplitudes in all cortical areas we studied: V1, V2, V3, hV4, VO1, LO1, LO2, V3A/B, IPS0, TO1, and TO2. However, the eccentricity dependence of these effects differed considerably across cortical areas. In early visual, ventral, and lateral occipital cortex, attentional enhancement of positive responses was greater for central compared to peripheral eccentricities. The opposite pattern was observed in dorsal stream areas IPS0 and putative MT homolog TO1, where attentional enhancement of positive responses was greater in the periphery. Both the magnitude and the eccentricity dependence of attentional modulation of negative fMRI responses closely mirrored that of positive responses across cortical areas. PMID:23562388
Texture-dependent motion signals in primate middle temporal area
Gharaei, Saba; Tailby, Chris; Solomon, Selina S; Solomon, Samuel G
2013-01-01
Neurons in the middle temporal (MT) area of primate cortex provide an important stage in the analysis of visual motion. For simple stimuli such as bars and plaids some neurons in area MT – pattern cells – seem to signal motion independent of contour orientation, but many neurons – component cells – do not. Why area MT supports both types of receptive field is unclear. To address this we made extracellular recordings from single units in area MT of anaesthetised marmoset monkeys and examined responses to two-dimensional images with a large range of orientations and spatial frequencies. Component and pattern cell response remained distinct during presentation of these complex spatial textures. Direction tuning curves were sharpest in component cells when a texture contained a narrow range of orientations, but were similar across all neurons for textures containing all orientations. Response magnitude of pattern cells, but not component cells, increased with the spatial bandwidth of the texture. In addition, response variability in all neurons was reduced when the stimulus was rich in spatial texture. Fisher information analysis showed that component cells provide more informative responses than pattern cells when a texture contains a narrow range of orientations, but pattern cells had more informative responses for broadband textures. Component cells and pattern cells may therefore coexist because they provide complementary and parallel motion signals. PMID:24000175
Spatial-temporal travel pattern mining using massive taxi trajectory data
NASA Astrophysics Data System (ADS)
Zheng, Linjiang; Xia, Dong; Zhao, Xin; Tan, Longyou; Li, Hang; Chen, Li; Liu, Weining
2018-07-01
Deep understanding of residents' travel patterns would provide helpful insights into the mechanisms of many socioeconomic phenomena. With the rapid development of location-aware computing technologies, researchers have easy access to large quantities of travel data. As an important data source, taxi trajectory data are featured by their high quality, good continuity and wide distribution, making it suitable for travel pattern mining. In this paper, we use taxi trajectory data to study spatial-temporal characterization of urban residents' travel patterns from two aspects: attractive areas and hot paths. Firstly, a framework of trajectory preprocessing, including data cleaning and extracting the taxi passenger pick-up/drop-off points, is presented to reduce the noise and redundancy in raw trajectory data. Then, a grid density based clustering algorithm is proposed to discover travel attractive areas in different periods of a day. On this basis, we put forward a spatial-temporal trajectory clustering method to discover hot paths among travel attractive areas. Compared with previous algorithms, which only consider the spatial constraint between trajectories, temporal constraint is also considered in our method. Through the experiments, we discuss how to determine the optimal parameters of the two clustering algorithms and verify the effectiveness of the algorithms using real data. Furthermore, we analyze spatial-temporal characterization of Chongqing residents' travel pattern.
Mapping Secondary Forest Succession on Abandoned Agricultural Land in the Polish Carpathians
NASA Astrophysics Data System (ADS)
Kolecka, N.; Kozak, J.; Kaim, D.; Dobosz, M.; Ginzler, Ch.; Psomas, A.
2016-06-01
Land abandonment and secondary forest succession have played a significant role in land cover changes and forest cover increase in mountain areas in Europe over the past several decades. Land abandonment can be easily observed in the field over small areas, but it is difficult to map over the large areas, e.g., with remote sensing, due to its subtle and spatially dispersed character. Our previous paper presented how the LiDAR (Light Detection and Ranging) and topographic data were used to detect secondary forest succession on abandoned land in one commune located in the Polish Carpathians by means of object-based image analysis (OBIA) and GIS (Kolecka et al., 2015). This paper proposes how the method can be applied to efficiently map secondary forest succession over the entire Polish Carpathians, incorporating spatial sampling strategy supported by various ancillary data. Here we discuss the methods of spatial sampling, its limitations and results in the context of future secondary forest succession modelling.
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
Mesoscale monitoring of the soil freeze/thaw boundary from orbital microwave radiometry
NASA Technical Reports Server (NTRS)
Dobson, Craig; Ulaby, Fawwaz T.; Zuerndorfer, Brian; England, Anthony W.
1990-01-01
A technique was developed for mapping the spatial extent of frozen soils from the spectral characteristics of the 10.7 to 37 GHz radiobrightness. Through computational models for the spectral radiobrightness of diurnally heated freesing soils, a distinctive radiobrightness signature was identified for frozen soils, and the signature was cast as a discriminant for unsupervised classification. In addition to large area images, local area spatial averages of radiobrightness were calculated for each radiobrightness channel at 7 meteorologic sites within the test region. Local area averages at the meteorologic sites were used to define the preliminary boundaries in the Freeze Indicator discriminate. Freeze Indicator images based upon Nimbus 7, Scanning Multichannel Microwave Radiometer (SMMR) data effectively map temporal variations in the freeze/thaw pattern for the northern Great Plains at the time scale of days. Diurnal thermal gradients have a small but measurable effect upon the SMMR spectral gradient. Scale-space filtering can be used to improve the spatial resolution of a freeze/thaw classified image.
Prediction of iron oxide contents using diffuse reflectance spectroscopy
NASA Astrophysics Data System (ADS)
Marques, José, Jr.; Arantes Camargo, Livia
2015-04-01
Determining soil iron oxides using conventional analysis is relatively unfeasible when large areas are mapped, with the aim of characterizing spatial variability. Diffuse reflectance spectroscopy (DRS) is rapid, less expensive, non-destructive and sometimes more accurate than conventional analysis. Furthermore, this technique allows the simultaneous characterization of many soil attributes with agronomic and environmental relevance. This study aims to assess the DRS capability to predict iron oxides content -hematite and goethite - , characterizing their spatial variability in soils of Brazil. Soil samples collected from an 800-hectare area were scanned in the visible and near-infrared spectral range. Moreover, chemometric calibration was obtained through partial least-squares regression (PLSR). Then, spatial distribution maps of the attributes were constructed using predicted values from calibrated models through geostatistical methods. The studied area presented soils with varied contents of iron oxides as examples for the Oxisols and Entisols. In the spectra of each soil is observed that the reflectance decreases with the content of iron oxides present in the soil. In soils with a high content of iron oxides can be observed more pronounced concavities between 380 and 1100 nm which are characteristic of the presence of these oxides. In soils with higher reflectance it were observed concavity characteristics due to the presence of kaolinite, in agreement with the low iron contents of those soils. The best accuracy of prediction models [residual prediction deviation (RPD) = 1.7] was obtained for goethite within the visible region (380-800 nm), and for hematite (RPD = 2.0) within the visible near infrared (380-2300 nm). The maps of goethite and hematite predicted showed the spatial distribution pattern similar to the maps of clay and iron extracted by dithionite-citrate-bicarbonate, being consistent with the iron oxide contents of soils present in the study area. These results confirm the value of DRS in the mapping of iron oxides in large areas at detailed scale.
Climate limits across space and time on European forest structure
NASA Astrophysics Data System (ADS)
Moreno, A. L. S.; Neumann, M.; Hasenauer, H.
2017-12-01
The impact climate has on forests has been extensively studied. However, the large scale effect climate has on forest structures, such as average diameters, heights and basal area are understudied in a spatially explicit manner. The limits, tipping points and thresholds that climate places on forest structures dictate the services a forest may provide, the vulnerability of a forest to mortality and the potential value of the timber there within. The majority of current research either investigates climate impacts on forest pools and fluxes, on a tree physiological scale or on case studies that are used to extrapolate results and potential impacts. A spatially explicit study on how climate affects forest structure over a large region would give valuable information to stakeholders who are more concerned with ecosystem services that cannot be described by pools and fluxes but require spatially explicit information - such as biodiversity, habitat suitability, and market values. In this study, we quantified the limits that climate (maximum, minimum temperature and precipitation) places on 3 forest structures, diameter at breast height, height, and basal area throughout Europe. Our results show clear climatic zones of high and low upper limits for each forest structure variable studied. We also spatially analyzed how climate restricts the potential bio-physical upper limits and creates tipping points of each forest structure variable and which climate factors are most limiting. Further, we demonstrated how the climate change has affected 8 individual forests across Europe and then the continent as a whole. We find that diameter, height and basal area are limited by climate in different ways and that areas may have high upper limits in one structure and low upper limits in another limitted by different climate variables. We also found that even though individual forests may have increased their potential upper limit forest structure values, European forests as a whole have lost, on average, 5.0%, 1.7% and 6.5% in potential mean forest diameter, height and basal area, respectively.
Lynx home range and movements in Montana and Wyoming: Preliminary results [Chapter 11
John R. Squires; Tom Laurion
2000-01-01
Preliminary telemetry data suggest that lynx in Montana and Wyoming have large home ranges; this result supports the Koehler and Aubry (1994) contention that lynx from southern lynx populations have large spatial-use areas. Annual home ranges of males were larger than females. Straight-line, daily travel distance averaged 2 to 4 km, which is similar to northern...
Romaguera, Mireia; Vaughan, R. Greg; Ettema, J.; Izquierdo-Verdiguier, E.; Hecker, C. A.; van der Meer, F.D.
2018-01-01
This paper explores for the first time the possibilities to use two land surface temperature (LST) time series of different origins (geostationary Meteosat Second Generation satellite data and Noah land surface modelling, LSM), to detect geothermal anomalies and extract the geothermal component of LST, the LSTgt. We hypothesize that in geothermal areas the LSM time series will underestimate the LST as compared to the remote sensing data, since the former does not account for the geothermal component in its model.In order to extract LSTgt, two approaches of different nature (physical based and data mining) were developed and tested in an area of about 560 × 560 km2 centered at the Kenyan Rift. Pre-dawn data in the study area during the first 45 days of 2012 were analyzed.The results show consistent spatial and temporal LSTgt patterns between the two approaches, and systematic differences of about 2 K. A geothermal area map from surface studies was used to assess LSTgt inside and outside the geothermal boundaries. Spatial means were found to be higher inside the geothermal limits, as well as the relative frequency of occurrence of high LSTgt. Results further show that areas with strong topography can result in anomalously high LSTgt values (false positives), which suggests the need for a slope and aspect correction in the inputs to achieve realistic results in those areas. The uncertainty analysis indicates that large uncertainties of the input parameters may limit detection of LSTgt anomalies. To validate the approaches, higher spatial resolution images from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data over the Olkaria geothermal field were used. An established method to estimate radiant geothermal flux was applied providing values between 9 and 24 W/m2 in the geothermal area, which coincides with the LSTgt flux rates obtained with the proposed approaches.The proposed approaches are a first step in estimating LSTgt at large spatial coverage from remote sensing and LSM data series, and provide an innovative framework for future improvements.
Development and calibration of a new gamma camera detector using large square Photomultiplier Tubes
NASA Astrophysics Data System (ADS)
Zeraatkar, N.; Sajedi, S.; Teimourian Fard, B.; Kaviani, S.; Akbarzadeh, A.; Farahani, M. H.; Sarkar, S.; Ay, M. R.
2017-09-01
Large area scintillation detectors applied in gamma cameras as well as Single Photon Computed Tomography (SPECT) systems, have a major role in in-vivo functional imaging. Most of the gamma detectors utilize hexagonal arrangement of Photomultiplier Tubes (PMTs). In this work we applied large square-shaped PMTs with row/column arrangement and positioning. The Use of large square PMTs reduces dead zones in the detector surface. However, the conventional center of gravity method for positioning may not introduce an acceptable result. Hence, the digital correlated signal enhancement (CSE) algorithm was optimized to obtain better linearity and spatial resolution in the developed detector. The performance of the developed detector was evaluated based on NEMA-NU1-2007 standard. The acquired images using this method showed acceptable uniformity and linearity comparing to three commercial gamma cameras. Also the intrinsic and extrinsic spatial resolutions with low-energy high-resolution (LEHR) collimator at 10 cm from surface of the detector were 3.7 mm and 7.5 mm, respectively. The energy resolution of the camera was measured 9.5%. The performance evaluation demonstrated that the developed detector maintains image quality with a reduced number of used PMTs relative to the detection area.
Quantifying Uncontrolled Air Emissions from Two Florida Landfills
Landfill gas emissions, if left uncontrolled, contribute to air toxics, climate change, trospospheric ozone, and urban smog. Measuring emissions from landfills presents unique challenges due to the large and variable source area, spatial and temporal variability of emissions, and...
Joel W. Homan; Charles H. Luce; James P. McNamara; Nancy F. Glenn
2011-01-01
Describing the spatial variability of heterogeneous snowpacks at a watershed or mountain-front scale is important for improvements in large-scale snowmelt modelling. Snowmelt depletion curves, which relate fractional decreases in snowcovered area (SCA) against normalized decreases in snow water equivalent (SWE), are a common approach to scale-up snowmelt models....
Reardon, Sean F.; Farrell, Chad R.; Matthews, Stephen A.; O'Sullivan, David; Bischoff, Kendra; Firebaugh, Glenn
2014-01-01
We use newly developed methods of measuring spatial segregation across a range of spatial scales to assess changes in racial residential segregation patterns in the 100 largest U.S. metropolitan areas from 1990 to 2000. Our results point to three notable trends in segregation from 1990 to 2000: 1) Hispanic-white and Asian-white segregation levels increased at both micro- and macro-scales; 2) black-white segregation declined at a micro-scale, but was unchanged at a macro-scale; and 3) for all three racial groups and for almost all metropolitan areas, macro-scale segregation accounted for more of the total metropolitan area segregation in 2000 than in 1990. Our examination of the variation in these trends among the metropolitan areas suggests that Hispanic-white and Asian-white segregation changes have been driven largely by increases in macro-scale segregation resulting from the rapid growth of the Hispanic and Asian populations in central cities. The changes in black-white segregation, in contrast, appear to be driven by the continuation of a 30-year trend in declining micro-segregation, coupled with persistent and largely stable patterns of macro-segregation. PMID:19569292
Lunga, Dalton D.; Yang, Hsiuhan Lexie; Reith, Andrew E.; ...
2018-02-06
Satellite imagery often exhibits large spatial extent areas that encompass object classes with considerable variability. This often limits large-scale model generalization with machine learning algorithms. Notably, acquisition conditions, including dates, sensor position, lighting condition, and sensor types, often translate into class distribution shifts introducing complex nonlinear factors and hamper the potential impact of machine learning classifiers. Here, this article investigates the challenge of exploiting satellite images using convolutional neural networks (CNN) for settlement classification where the class distribution shifts are significant. We present a large-scale human settlement mapping workflow based-off multiple modules to adapt a pretrained CNN to address themore » negative impact of distribution shift on classification performance. To extend a locally trained classifier onto large spatial extents areas we introduce several submodules: First, a human-in-the-loop element for relabeling of misclassified target domain samples to generate representative examples for model adaptation; second, an efficient hashing module to minimize redundancy and noisy samples from the mass-selected examples; and third, a novel relevance ranking module to minimize the dominance of source example on the target domain. The workflow presents a novel and practical approach to achieve large-scale domain adaptation with binary classifiers that are based-off CNN features. Experimental evaluations are conducted on areas of interest that encompass various image characteristics, including multisensors, multitemporal, and multiangular conditions. Domain adaptation is assessed on source–target pairs through the transfer loss and transfer ratio metrics to illustrate the utility of the workflow.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lunga, Dalton D.; Yang, Hsiuhan Lexie; Reith, Andrew E.
Satellite imagery often exhibits large spatial extent areas that encompass object classes with considerable variability. This often limits large-scale model generalization with machine learning algorithms. Notably, acquisition conditions, including dates, sensor position, lighting condition, and sensor types, often translate into class distribution shifts introducing complex nonlinear factors and hamper the potential impact of machine learning classifiers. Here, this article investigates the challenge of exploiting satellite images using convolutional neural networks (CNN) for settlement classification where the class distribution shifts are significant. We present a large-scale human settlement mapping workflow based-off multiple modules to adapt a pretrained CNN to address themore » negative impact of distribution shift on classification performance. To extend a locally trained classifier onto large spatial extents areas we introduce several submodules: First, a human-in-the-loop element for relabeling of misclassified target domain samples to generate representative examples for model adaptation; second, an efficient hashing module to minimize redundancy and noisy samples from the mass-selected examples; and third, a novel relevance ranking module to minimize the dominance of source example on the target domain. The workflow presents a novel and practical approach to achieve large-scale domain adaptation with binary classifiers that are based-off CNN features. Experimental evaluations are conducted on areas of interest that encompass various image characteristics, including multisensors, multitemporal, and multiangular conditions. Domain adaptation is assessed on source–target pairs through the transfer loss and transfer ratio metrics to illustrate the utility of the workflow.« less
Zajac, R.N.; Lewis, R.S.; Poppe, L.J.; Twichell, D.C.; Vozarik, J.; DiGiacomo-Cohen, M. L.
2003-01-01
Relationships between population abundance and seafloor landscape, or benthoscape, structure were examined for 16 infaunal taxa in eastern Long Island Sound. Based on analyses of a side-scan sonar mosaic, the 19.4-km2 study area was comprised of six distinct large-scale (> km2) benthoscape elements, with varying levels of mesoscale (km2-m2) and small-scale (2) physical and biological habitat heterogeneity. Transition zones among elements varied from ~50 to 200 m in width, comprised ~32% of the benthoscape, and added to overall benthoscape heterogeneity. Population abundances of nine taxa varied significantly among the large-scale elements. Most species were found at high abundances only in one benthoscape element, but three had several foci of elevated abundances. Analyses of population responses to habitat heterogeneity at different spatial scales indicated that abundances of eight taxa varied significantly among spatial scales, but the significant scales were mixed among these species. Relatively large residual variations suggest significant amounts of mesoscale spatial variation were unaccounted for, varying from ~1 km2 to several m2. Responses to transition zones were mixed as well. Abundances of nine taxa varied significantly among transition zones and interiors of benthoscape elements, most with elevated abundances in transition zones. Our results show that infaunal populations exhibit complex and spatially varying patterns of abundance in relation to benthoscape structure and suggest that mesoscale variation may be particularly critical in this regard. Also, transition zones among benthoscape features add considerably to this variation and may be ecological important areas in seafloor environments.
Seliske, L; Norwood, T A; McLaughlin, J R; Wang, S; Palleschi, C; Holowaty, E
2016-06-07
An important public health goal is to decrease the prevalence of key behavioural risk factors, such as tobacco use and obesity. Survey information is often available at the regional level, but heterogeneity within large geographic regions cannot be assessed. Advanced spatial analysis techniques are demonstrated to produce sensible micro area estimates of behavioural risk factors that enable identification of areas with high prevalence. A spatial Bayesian hierarchical model was used to estimate the micro area prevalence of current smoking and excess bodyweight for the Erie-St. Clair region in southwestern Ontario. Estimates were mapped for male and female respondents of five cycles of the Canadian Community Health Survey (CCHS). The micro areas were 2006 Census Dissemination Areas, with an average population of 400-700 people. Two individual-level models were specified: one controlled for survey cycle and age group (model 1), and one controlled for survey cycle, age group and micro area median household income (model 2). Post-stratification was used to derive micro area behavioural risk factor estimates weighted to the population structure. SaTScan analyses were conducted on the granular, postal-code level CCHS data to corroborate findings of elevated prevalence. Current smoking was elevated in two urban areas for both sexes (Sarnia and Windsor), and an additional small community (Chatham) for males only. Areas of excess bodyweight were prevalent in an urban core (Windsor) among males, but not females. Precision of the posterior post-stratified current smoking estimates was improved in model 2, as indicated by narrower credible intervals and a lower coefficient of variation. For excess bodyweight, both models had similar precision. Aggregation of the micro area estimates to CCHS design-based estimates validated the findings. This is among the first studies to apply a full Bayesian model to complex sample survey data to identify micro areas with variation in risk factor prevalence, accounting for spatial correlation and other covariates. Application of micro area analysis techniques helps define areas for public health planning, and may be informative to surveillance and research modeling of relevant chronic disease outcomes.
Apparatus and method for rapid cooling of large area substrates in vacuum
Barth, Kurt L.; Enzenroth, Robert A.; Sampath, Walajabad S.
2012-11-06
The present invention is directed to an apparatus and method for rapid cooling of a large substrate in a vacuum environment. A first cooled plate is brought into close proximity with one surface of a flat substrate. The spatial volume between the first cooling plate and the substrate is sealed and brought to a higher pressure than the surrounding vacuum level to increase the cooling efficiency. A second cooled plate is brought into close proximity with the opposite surface of the flat substrate. A second spatial volume between the second cooling plate and the substrate is sealed and the gas pressure is equalized to the gas pressure in the first spatial volume. The equalization of the gas pressure on both sides of the flat substrate eliminates deflection of the substrate and bending stress in the substrate.
Sun, Guibo; Webster, Chris; Ni, Michael Y; Zhang, Xiaohu
2018-05-07
Uncertainty with respect to built environment (BE) data collection, measure conceptualization and spatial scales is evident in urban health research, but most findings are from relatively lowdensity contexts. We selected Hong Kong, an iconic high-density city, as the study area as limited research has been conducted on uncertainty in such areas. We used geocoded home addresses (n=5732) from a large population-based cohort in Hong Kong to extract BE measures for the participants' place of residence based on an internationally recognized BE framework. Variability of the measures was mapped and Spearman's rank correlation calculated to assess how well the relationships among indicators are preserved across variables and spatial scales. We found extreme variations and uncertainties for the 180 measures collected using comprehensive data and advanced geographic information systems modelling techniques. We highlight the implications of methodological selection and spatial scales of the measures. The results suggest that more robust information regarding urban health research in high-density city would emerge if greater consideration were given to BE data, design methods and spatial scales of the BE measures.
NASA Astrophysics Data System (ADS)
Karch, J.; Krejci, F.; Bartl, B.; Dudak, J.; Kuba, J.; Kvacek, J.; Zemlicka, J.
2016-01-01
State-of-the-art hybrid pixel semiconductor detectors provide excellent imaging properties such as unlimited dynamic range, high spatial resolution, high frame rate and energy sensitivity. Nevertheless, a limitation in the use of these devices for imaging has been the small sensitive area of a few square centimetres. In the field of microtomography we make use of a large area pixel detector assembled from 50 Timepix edgeless chips providing fully sensitive area of 14.3 × 7.15 cm2. We have successfully demonstrated that the enlargement of the sensitive area enables high-quality tomographic measurements of whole objects with high geometrical magnification without any significant degradation in resulting reconstructions related to the chip tilling and edgeless sensor technology properties. The technique of micro-tomography with the newly developed large area detector is applied for samples formed by low attenuation, low contrast materials such a seed from Phacelia tanacetifolia, a charcoalified wood sample and a beeswax seal sample.
Clusters in irregular areas and lattices.
Wieczorek, William F; Delmerico, Alan M; Rogerson, Peter A; Wong, David W S
2012-01-01
Geographic areas of different sizes and shapes of polygons that represent counts or rate data are often encountered in social, economic, health, and other information. Often political or census boundaries are used to define these areas because the information is available only for those geographies. Therefore, these types of boundaries are frequently used to define neighborhoods in spatial analyses using geographic information systems and related approaches such as multilevel models. When point data can be geocoded, it is possible to examine the impact of polygon shape on spatial statistical properties, such as clustering. We utilized point data (alcohol outlets) to examine the issue of polygon shape and size on visualization and statistical properties. The point data were allocated to regular lattices (hexagons and squares) and census areas for zip-code tabulation areas and tracts. The number of units in the lattices was set to be similar to the number of tract and zip-code areas. A spatial clustering statistic and visualization were used to assess the impact of polygon shape for zip- and tract-sized units. Results showed substantial similarities and notable differences across shape and size. The specific circumstances of a spatial analysis that aggregates points to polygons will determine the size and shape of the areal units to be used. The irregular polygons of census units may reflect underlying characteristics that could be missed by large regular lattices. Future research to examine the potential for using a combination of irregular polygons and regular lattices would be useful.
Godoy, B S; Queiroz, L L; Lodi, S; Oliveira, L G
2017-04-01
The aquatic insect community is an important element for stream functionality and diversity, but the effects of altitude and conservation areas on the aquatic insect community have been poorly explored in neotropical ecozone. The lack of studies about the relative importance of space and environment on community structure is another obstacle within aquatic insect ecology, which precludes the inclusion of these studies in more current frameworks, like the metacommunity dynamics. We evaluated the relationship between the aquatic insect community structure at 19 streams in the Brazilian Cerrado and spatial and environmental variables, namely geographical distance among sites, stream altitude, chemical variables, and environmental protection areas. We partitioned the variance explained by spatial and environmental components using a partial redundancy analysis. The environment exhibited a strong spatial structure for abundance and number of genera, increasing these community parameters with elevated water conductivity. Only community composition had a large unexplained portion of variance, with a small portion constrained by environmental (altitude and conductivity) and spatial factors. A relevant point in the result was the streams with high conductivity were located outside of the conservation areas. These results suggest that the relationship between number of genera and abundance with environmental conditions is always associated with spatial configuration of streams. Our study shows that altitude is an important determinant of community structure, as it exerts indirect influences, and electrical conductivity directly determines community composition, and that some national parks may be inefficient in maintaining the diversity of aquatic insects in the Cerrado region.
Spatial relationships among cereal yields and selected soil physical and chemical properties.
Lipiec, Jerzy; Usowicz, Bogusław
2018-08-15
Sandy soils occupy large area in Poland (about 50%) and in the world. This study aimed at determining spatial relationships of cereal yields and the selected soil physical and chemical properties in three study years (2001-2003) on low productive sandy Podzol soil (Podlasie, Poland). The yields and soil properties in plough and subsoil layers were determined at 72-150 points. The test crops were: wheat, wheat and barley mixture and oats. To explore the spatial relationship between cereal yields and each soil property spatial statistics was used. The best fitting models were adjusted to empirical semivariance and cross-semivariance, which were used to draw maps using kriging. Majority of the soil properties and crop yields exhibited low and medium variability (coefficient of variation 5-70%). The effective ranges of the spatial dependence (the distance at which data are autocorrelated) for yields and all soil properties were 24.3-58.5m and 10.5-373m, respectively. Nugget to sill ratios showed that crop yields and soil properties were strongly spatially dependent except bulk density. Majority of the pairs in cross-semivariograms exhibited strong spatial interdependence. The ranges of the spatial dependence varied in plough layer between 54.6m for yield×pH up to 2433m for yield×silt content. Corresponding ranges in subsoil were 24.8m for crop yield×clay content in 2003 and 1404m for yield×bulk density. Kriging maps allowed separating sub-field area with the lowest yield and soil cation exchange capacity, organic carbon content and pH. This area had lighter color on the aerial photograph due to high content of the sand and low content of soil organic carbon. The results will help farmers at identifying sub-field areas for applying localized management practices to improve these soil properties and further spatial studies in larger scale. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.
Hudda, N; Fruin, S A
2016-04-05
We measured particle size distributions and spatial patterns of particle number (PN) and particle surface area concentrations downwind from the Los Angeles International Airport (LAX) where large increases (over local background) in PN concentrations routinely extended 18 km downwind. These elevations were mostly comprised of ultrafine particles smaller than 40 nm. For a given downwind distance, the greatest increases in PN concentrations, along with the smallest mean sizes, were detected at locations under the landing jet trajectories. The smaller size of particles in the impacted area, as compared to the ambient urban aerosol, increased calculated lung deposition fractions to 0.7-0.8 from 0.5-0.7. A diffusion charging instrument (DiSCMini), that simulates alveolar lung deposition, measured a fivefold increase in alveolar-lung deposited surface area concentrations 2-3 km downwind from the airport (over local background), decreasing steadily to a twofold increase 18 km downwind. These ratios (elevated lung-deposited surface area over background) were lower than the corresponding ratios for elevated PN concentrations, which decreased from tenfold to twofold over the same distance, but the spatial patterns of elevated concentrations were similar. It appears that PN concentration can serve as a nonlinear proxy for lung deposited surface area downwind of major airports.
NASA Technical Reports Server (NTRS)
Li, Xiaofan; Sui, C.-H.; Lau, K-M.; Adamec, D.
1999-01-01
A two-dimensional coupled ocean-cloud resolving atmosphere model is used to investigate possible roles of convective scale ocean disturbances induced by atmospheric precipitation on ocean mixed-layer heat and salt budgets. The model couples a cloud resolving model with an embedded mixed layer-ocean circulation model. Five experiment are performed under imposed large-scale atmospheric forcing in terms of vertical velocity derived from the TOGA COARE observations during a selected seven-day period. The dominant variability of mixed-layer temperature and salinity are simulated by the coupled model with imposed large-scale forcing. The mixed-layer temperatures in the coupled experiments with 1-D and 2-D ocean models show similar variations when salinity effects are not included. When salinity effects are included, however, differences in the domain-mean mixed-layer salinity and temperature between coupled experiments with 1-D and 2-D ocean models could be as large as 0.3 PSU and 0.4 C respectively. Without fresh water effects, the nocturnal heat loss over ocean surface causes deep mixed layers and weak cooling rates so that the nocturnal mixed-layer temperatures tend to be horizontally-uniform. The fresh water flux, however, causes shallow mixed layers over convective areas while the nocturnal heat loss causes deep mixed layer over convection-free areas so that the mixed-layer temperatures have large horizontal fluctuations. Furthermore, fresh water flux exhibits larger spatial fluctuations than surface heat flux because heavy rainfall occurs over convective areas embedded in broad non-convective or clear areas, whereas diurnal signals over whole model areas yield high spatial correlation of surface heat flux. As a result, mixed-layer salinities contribute more to the density differences than do mixed-layer temperatures.
Daytime Locations in Spatial Mismatch: Job Accessibility and Employment at Reentry From Prison
Lens, Michael C.
2017-01-01
Individuals recently released from prison confront many barriers to employment. One potential obstacle is spatial mismatch—the concentration of low-skilled, nonwhite job-seekers within central cities and the prevalence of relevant job opportunities in outlying areas. Prior research has found mixed results about the importance of residential place for reentry outcomes. In this article, we propose that residential location matters for finding work, but this largely static measure does not capture the range of geographic contexts that individuals inhabit throughout the day. We combine novel, real-time GPS information on daytime locations and self-reported employment collected from smartphones with sophisticated measures of job accessibility to test the relative importance of spatial mismatch based on residence and daytime locations. Our findings suggest that the ability of low-skilled, poor, and urban individuals to compensate for their residential deficits by traveling to job-rich areas is an overlooked and salient consideration in spatial mismatch perspectives. PMID:28224468
NASA Astrophysics Data System (ADS)
Iinuma, Takeshi; Hino, Ryota; Uchida, Naoki; Nakamura, Wataru; Kido, Motoyuki; Osada, Yukihito; Miura, Satoshi
2016-11-01
Large interplate earthquakes are often followed by postseismic slip that is considered to occur in areas surrounding the coseismic ruptures. Such spatial separation is expected from the difference in frictional and material properties in and around the faults. However, even though the 2011 Tohoku Earthquake ruptured a vast area on the plate interface, the estimation of high-resolution slip is usually difficult because of the lack of seafloor geodetic data. Here using the seafloor and terrestrial geodetic data, we investigated the postseismic slip to examine whether it was spatially separated with the coseismic slip by applying a comprehensive finite-element method model to subtract the viscoelastic components from the observed postseismic displacements. The high-resolution co- and postseismic slip distributions clarified the spatial separation, which also agreed with the activities of interplate and repeating earthquakes. These findings suggest that the conventional frictional property model is valid for the source region of gigantic earthquakes.
Iinuma, Takeshi; Hino, Ryota; Uchida, Naoki; Nakamura, Wataru; Kido, Motoyuki; Osada, Yukihito; Miura, Satoshi
2016-01-01
Large interplate earthquakes are often followed by postseismic slip that is considered to occur in areas surrounding the coseismic ruptures. Such spatial separation is expected from the difference in frictional and material properties in and around the faults. However, even though the 2011 Tohoku Earthquake ruptured a vast area on the plate interface, the estimation of high-resolution slip is usually difficult because of the lack of seafloor geodetic data. Here using the seafloor and terrestrial geodetic data, we investigated the postseismic slip to examine whether it was spatially separated with the coseismic slip by applying a comprehensive finite-element method model to subtract the viscoelastic components from the observed postseismic displacements. The high-resolution co- and postseismic slip distributions clarified the spatial separation, which also agreed with the activities of interplate and repeating earthquakes. These findings suggest that the conventional frictional property model is valid for the source region of gigantic earthquakes. PMID:27853138
Smith, Catherine M; Downs, Sara H; Mitchell, Andy; Hayward, Andrew C; Fry, Hannah; Le Comber, Steven C
2015-01-01
Bovine tuberculosis is a disease of historical importance to human health in the UK that remains a major animal health and economic issue. Control of the disease in cattle is complicated by the presence of a reservoir species, the Eurasian badger. In spite of uncertainty in the degree to which cattle disease results from transmission from badgers, and opposition from environmental groups, culling of badgers has been licenced in two large areas in England. Methods to limit culls to smaller areas that target badgers infected with TB whilst minimising the number of uninfected badgers culled is therefore of considerable interest. Here, we use historical data from a large-scale field trial of badger culling to assess two alternative hypothetical methods of targeting TB-infected badgers based on the distribution of cattle TB incidents: (i) a simple circular 'ring cull'; and (ii) geographic profiling, a novel technique for spatial targeting of infectious disease control that predicts the locations of sources of infection based on the distribution of linked cases. Our results showed that both methods required coverage of very large areas to ensure a substantial proportion of infected badgers were removed, and would result in many uninfected badgers being culled. Geographic profiling, which accounts for clustering of infections in badger and cattle populations, produced a small but non-significant increase in the proportion of setts with TB-infected compared to uninfected badgers included in a cull. It also provided no overall improvement at targeting setts with infected badgers compared to the ring cull. Cattle TB incidents in this study were therefore insufficiently clustered around TB-infected badger setts to design an efficient spatially targeted cull; and this analysis provided no evidence to support a move towards spatially targeted badger culling policies for bovine TB control.
Spatial distribution of allergenic pollen through a large metropolitan area.
Werchan, Barbora; Werchan, Matthias; Mücke, Hans-Guido; Gauger, Ulrich; Simoleit, Anke; Zuberbier, Torsten; Bergmann, Karl-Christian
2017-04-01
For nearly a decade, the majority of the world's population has been living in cities, including a considerable percentage of people suffering from pollen allergy. The increasing concentration of people in cities results in larger populations being exposed to allergenic pollen at the same time. There is almost no information about spatial distribution of pollen within cities as well as a lack of information about the possible impact to human health. To obtain this increasing need for pollen exposure studies on an intra-urban scale, a novelty screening network of 14 weekly changed pollen traps was established within a large metropolitan area-Berlin, Germany. Gravimetric pollen traps were placed at a uniform street-level height from March until October 2014. Three important allergenic pollen types for Central Europe-birch (Betula), grasses (Poaceae), and mugwort (Artemisia)-were monitored. Remarkable spatial and temporal variations of pollen sedimentation within the city and the influences by urban local sources are shown. The observed differences between the trap with the overall highest and the trap with the overall lowest amount of pollen sedimentation were in the case of birch pollen 245%, grass pollen 306%, and mugwort pollen 1962%. Differences of this magnitude can probably lead to different health impacts on allergy sufferers in one city. Therefore, pollen should be monitored preferably in two or more appropriate locations within large cities and as a part of natural air quality regulations.
Performance of GPS-devices for environmental exposure assessment.
Beekhuizen, Johan; Kromhout, Hans; Huss, Anke; Vermeulen, Roel
2013-01-01
Integration of individual time-location patterns with spatially resolved exposure maps enables a more accurate estimation of personal exposures to environmental pollutants than using estimates at fixed locations. Current global positioning system (GPS) devices can be used to track an individual's location. However, information on GPS-performance in environmental exposure assessment is largely missing. We therefore performed two studies. First, a commute-study, where the commute of 12 individuals was tracked twice, testing GPS-performance for five transport modes and two wearing modes. Second, an urban-tracking study, where one individual was tracked repeatedly through different areas, focused on the effect of building obstruction on GPS-performance. The median error from the true path for walking was 3.7 m, biking 2.9 m, train 4.8 m, bus 4.9 m, and car 3.3 m. Errors were larger in a high-rise commercial area (median error=7.1 m) compared with a low-rise residential area (median error=2.2 m). Thus, GPS-performance largely depends on the transport mode and urban built-up. Although ~85% of all errors were <10 m, almost 1% of the errors were >50 m. Modern GPS-devices are useful tools for environmental exposure assessment, but large GPS-errors might affect estimates of exposures with high spatial variability.
Spatial boundary of urban ‘acid islands’ in southern China
Du, E.; de Vries, W.; Liu, X.; Fang, J.; Galloway, J. N.; Jiang, Y.
2015-01-01
Elevated emissions of sulfur dioxide, nitrogen oxides and ammonia in China have resulted in high levels of sulfur and nitrogen deposition, being contributors to soil acidification, especially in and near large cities. However, knowledge gaps still exist in the way that large cities shape spatial patterns of acid deposition. Here, we assessed the patterns of pH, sulfate, nitrate and ammonium in bulk precipitation and throughfall in southern China’s forests by synthesizing data from published literature. Concentrations and fluxes of sulfate, nitrate and ammonium in bulk precipitation and throughfall exhibited a power-law increase with a closer distance to the nearest large cities, and accordingly pH showed a logarithmic decline. Our findings indicate the occurrence of urban ‘acid islands’ with a critical radius of approximately 70 km in southern China, receiving potential acid loads of more than 2 keq ha−1 yr−1. These urban acid islands covered an area of 0.70 million km2, accounting for nearly 30% of the land area in southern China. Despite a significant capacity to neutralize acids in precipitation, our analysis highlights a substantial contribution of ammonium to potential acid load. Our results suggest a joint control on emissions of multiple acid precursors from urban areas in southern China. PMID:26211880
Spatial boundary of urban 'acid islands' in southern China.
Du, E; de Vries, W; Liu, X; Fang, J; Galloway, J N; Jiang, Y
2015-07-27
Elevated emissions of sulfur dioxide, nitrogen oxides and ammonia in China have resulted in high levels of sulfur and nitrogen deposition, being contributors to soil acidification, especially in and near large cities. However, knowledge gaps still exist in the way that large cities shape spatial patterns of acid deposition. Here, we assessed the patterns of pH, sulfate, nitrate and ammonium in bulk precipitation and throughfall in southern China's forests by synthesizing data from published literature. Concentrations and fluxes of sulfate, nitrate and ammonium in bulk precipitation and throughfall exhibited a power-law increase with a closer distance to the nearest large cities, and accordingly pH showed a logarithmic decline. Our findings indicate the occurrence of urban 'acid islands' with a critical radius of approximately 70 km in southern China, receiving potential acid loads of more than 2 keq ha(-1) yr(-1). These urban acid islands covered an area of 0.70 million km(2), accounting for nearly 30% of the land area in southern China. Despite a significant capacity to neutralize acids in precipitation, our analysis highlights a substantial contribution of ammonium to potential acid load. Our results suggest a joint control on emissions of multiple acid precursors from urban areas in southern China.
Using excess 4He to quantify variability in aquitard leakage
NASA Astrophysics Data System (ADS)
Gardner, W. Payton; Harrington, Glenn A.; Smerdon, Brian D.
2012-10-01
SummaryFluid flux through aquitards controls the rate of recharge, discharge, cross-formational fluid flow and contaminant transport in subsurface systems. In this paper, concentrations of 4He are used to investigate the spatial distribution of vertical fluid flux through the regionally extensive Great Artesian Basin aquitard system in northern South Australia. Two vertical profiles of 4He concentration in aquitard pore water, augmented with regional sampling of aquifers above and below the aquitard were used to estimate fluid flux at multiple locations over a large spatial area. 4He concentrations in the shallow aquifer above the Great Artesian Basin range from atmospheric equilibrium to 1000 times enriched over atmosphere. Fluid flux through the aquitard was estimated by fitting observed helium concentrations at each sampling site with a 1-D model of helium transport through the aquitard. Estimated fluid fluxes through the aquitard vary over three orders of magnitude across the study area. In areas of competent aquitard, fluid fluxes are less than 0.003 mm/yr, and mass transport of helium is dominated by molecular diffusion. Preferential discharge zones are clearly identifiable with fluid fluxes up to 3 mm/yr. Our results show that fluid flux through a regionally extensive aquitard can be highly variable at large spatial scales, and that 4He concentrations in aquifers bounding the aquitard system provide a convenient and sensitive method for investigating aquitard flux at the regional scale.
Spatial environmental heterogeneity affects plant growth and thermal performance on a green roof.
Buckland-Nicks, Michael; Heim, Amy; Lundholm, Jeremy
2016-05-15
Green roofs provide ecosystem services, including stormwater retention and reductions in heat transfer through the roof. Microclimates, as well as designed features of green roofs, such as substrate and vegetation, affect the magnitude of these services. Many green roofs are partially shaded by surrounding buildings, but the effects of this within-roof spatial environmental heterogeneity on thermal performance and other ecosystem services have not been examined. We quantified the effects of spatial heterogeneity in solar radiation, substrate depth and other variables affected by these drivers on vegetation and ecosystem services in an extensive green roof. Spatial heterogeneity in substrate depth and insolation were correlated with differential growth, survival and flowering in two focal plant species. These effects were likely driven by the resulting spatial heterogeneity in substrate temperature and moisture content. Thermal performance (indicated by heat flux and substrate temperature) was influenced by spatial heterogeneity in vegetation cover and substrate depth. Areas with less insolation were cooler in summer and had greater substrate moisture, leading to more favorable conditions for plant growth and survival. Spatial variation in substrate moisture (7%-26% volumetric moisture content) and temperature (21°C-36°C) during hot sunny conditions in summer could cause large differences in stormwater retention and heat flux within a single green roof. Shaded areas promote smaller heat fluxes through the roof, leading to energy savings, but lower evapotranspiration in these areas should reduce stormwater retention capacity. Spatial heterogeneity can thus result in trade-offs between different ecosystem services. The effects of these spatial heterogeneities are likely widespread in green roofs. Structures that provide shelter from sun and wind may be productively utilized to design higher functioning green roofs and increase biodiversity by providing habitat heterogeneity. Copyright © 2016 Elsevier B.V. All rights reserved.
Muposhi, Victor K.; Gandiwa, Edson; Chemura, Abel; Bartels, Paul; Makuza, Stanley M.; Madiri, Tinaapi H.
2016-01-01
An understanding of the habitat selection patterns by wild herbivores is critical for adaptive management, particularly towards ecosystem management and wildlife conservation in semi arid savanna ecosystems. We tested the following predictions: (i) surface water availability, habitat quality and human presence have a strong influence on the spatial distribution of wild herbivores in the dry season, (ii) habitat suitability for large herbivores would be higher compared to medium-sized herbivores in the dry season, and (iii) spatial extent of suitable habitats for wild herbivores will be different between years, i.e., 2006 and 2010, in Matetsi Safari Area, Zimbabwe. MaxEnt modeling was done to determine the habitat suitability of large herbivores and medium-sized herbivores. MaxEnt modeling of habitat suitability for large herbivores using the environmental variables was successful for the selected species in 2006 and 2010, except for elephant (Loxodonta africana) for the year 2010. Overall, large herbivores probability of occurrence was mostly influenced by distance from rivers. Distance from roads influenced much of the variability in the probability of occurrence of medium-sized herbivores. The overall predicted area for large and medium-sized herbivores was not different. Large herbivores may not necessarily utilize larger habitat patches over medium-sized herbivores due to the habitat homogenizing effect of water provisioning. Effect of surface water availability, proximity to riverine ecosystems and roads on habitat suitability of large and medium-sized herbivores in the dry season was highly variable thus could change from one year to another. We recommend adaptive management initiatives aimed at ensuring dynamic water supply in protected areas through temporal closure and or opening of water points to promote heterogeneity of wildlife habitats. PMID:27680673
Large-scale modeling of rain fields from a rain cell deterministic model
NASA Astrophysics Data System (ADS)
FéRal, Laurent; Sauvageot, Henri; Castanet, Laurent; Lemorton, JoëL.; Cornet, FréDéRic; Leconte, Katia
2006-04-01
A methodology to simulate two-dimensional rain rate fields at large scale (1000 × 1000 km2, the scale of a satellite telecommunication beam or a terrestrial fixed broadband wireless access network) is proposed. It relies on a rain rate field cellular decomposition. At small scale (˜20 × 20 km2), the rain field is split up into its macroscopic components, the rain cells, described by the Hybrid Cell (HYCELL) cellular model. At midscale (˜150 × 150 km2), the rain field results from the conglomeration of rain cells modeled by HYCELL. To account for the rain cell spatial distribution at midscale, the latter is modeled by a doubly aggregative isotropic random walk, the optimal parameterization of which is derived from radar observations at midscale. The extension of the simulation area from the midscale to the large scale (1000 × 1000 km2) requires the modeling of the weather frontal area. The latter is first modeled by a Gaussian field with anisotropic covariance function. The Gaussian field is then turned into a binary field, giving the large-scale locations over which it is raining. This transformation requires the definition of the rain occupation rate over large-scale areas. Its probability distribution is determined from observations by the French operational radar network ARAMIS. The coupling with the rain field modeling at midscale is immediate whenever the large-scale field is split up into midscale subareas. The rain field thus generated accounts for the local CDF at each point, defining a structure spatially correlated at small scale, midscale, and large scale. It is then suggested that this approach be used by system designers to evaluate diversity gain, terrestrial path attenuation, or slant path attenuation for different azimuth and elevation angle directions.
Denudation rates and tectonic geomorphology of the Spanish Betic Cordillera
NASA Astrophysics Data System (ADS)
Bellin, N.; Vanacker, V.; Kubik, P. W.
2014-03-01
The tectonic control on landscape morphology and long-term denudation is largely documented for settings with high uplift rates. Relatively little is known about the rates of geomorphic response in areas of low tectonic uplift. Here, we evaluate spatial variations in denudation of the Spanish Betic Cordillera based on cosmogenic 10Be-derived denudation rates. Denudation rates are compared to published data on rock uplift and exhumation of the Betic Cordillera to evaluate steady-state topography. The spatial patterns of catchment-wide denudation rates (n=20) are then analysed together with topographic metrics of hillslope and channel morphology. Catchments draining the Betic ranges have relatively low denudation rates (64±54 mm kyr), but also show large variation as they range from 14 to 246 mm kyr-1. Catchment-wide denudation is linearly proportional to the mean hillslope gradient and local relief. Despite large spatial variation in denudation, the magnitude and spatial pattern of denudation rates are generally consistent with longer-term local uplift rates derived from elevated marine deposits, fission-track measurements and vertical fault slip rates. This might be indicative of a steady-state topography where rock uplift is balanced by denudation.
Snow depth spatial structure from hillslope to basin scale
NASA Astrophysics Data System (ADS)
Deems, J. S.
2017-12-01
Knowledge of spatial patterns of snow accumulation is required for understanding the hydrology, climatology, and ecology of mountain regions. Spatial structure in snow accumulation patterns changes with the scale of observation, a feature that has been characterized using fractal dimensions calculated from lidar-derived snow depth maps: fractal scaling structure at short length scales, with a `scale break' transition to more stochastic patterns at longer separation distances. Previous work has shown that this fractal structure of snow depth distributions differs between sites with different vegetation and terrain characteristics. Forested areas showed a transition to a nearly random spatial distribution at a much shorter lag distance than do unforested sites, enabling a statistical characterization. Alpine areas, however, showed strong spatial structure for a much wider scale range, and were the source of the dominant spatial pattern observable over a wider area. These spatial structure characteristics suggest that the choice of measurement or model resolution (satellite sensor, DEM, field survey point spacing, etc.) will strongly affect the estimates of snow volume or mass, as well as the magnitude of spatial variability. These prior efforts used data sets that were high resolution ( 1 m laser point spacing) but of limited extent ( 1 km2), constraining detection of scale features such as fractal dimension or scale breaks to areas of relatively similar characteristics and to lag distances of under 500 m. New datasets available from the NASA JPL Airborne Snow Observatory (ASO) provide similar resolution but over large areas, enabling assessment of snow spatial structure across an entire watershed, or in similar vegetation or physiography but in different parts of the basin. Additionally, the multi-year ASO time series allows an investigation into the temporal stability of these scale characteristics, within a single snow season and between seasons of strongly varying accumulation totals and patterns. This presentation will explore initial results from this study, using data from the Tuolumne River Basin in California, USA. Fractal scaling characteristics derived from ASO lidar snow depth measurements are examined at the basin scale, as well as in varying topographic and forest cover environments.
NASA Astrophysics Data System (ADS)
Fan, J.; He, H.; Hu, T.; Li, G.; Gao, H.; Zhao, X.
2017-09-01
China's cities have been undergoing rapid and intense urbanization processes in the past few decades. Shandong is a coastal province which is located in East China with big economy and population scales, and which also plays an important role in the rapid process of China's modernization. The DMSP/OLS dataset has been widely used for the urban development assessments in long time-series and large spatial scales situations. In this paper, we used a time series of nighttime light data to estimate the landscape spatial pattern changes of cities in Shandong province from 1994 to 2012. Nine landscape metrics were calculated and analyzed to figure out the spatial patterns of urban area developments of the cities in Shandong province. The landscape metrics include the number of patches (NP), the landscape total area (TA), the aggregation index (AI), the largest patch index (LPI), the mean patch area (AREA_MN), the landscape shape index (LSI), the total edge length (TE), the edge density (ED), and the mean radius of gyration (GYRATE_MN). The experimental results reveal that, in 1994-2012, the total urban area of cities in Shandong province expanded for 1.17 times, the average urban area increased by about 93.00%, the average annual growth rate of the TE metric is 2.67 %, while the ED metric decreased about 1.44 % annually. Bigger cities in this area show relative slower urbanization development processes, such as Jinan and Qingdao. Coastal cities represented much more rapid expansion velocities than inland cities. In the middle area of Shandong province, the connectivity between developed urban areas was constantly increased.
Mu, Lan; Wang, Fahui; Chen, Vivien W.; Wu, Xiao-Cheng
2015-01-01
Similar geographic areas often have great variations in population size. In health data management and analysis, it is desirable to obtain regions of comparable population by decomposing areas of large population (to gain more spatial variability) and merging areas of small population (to mask privacy of data). Based on the Peano curve algorithm and modified scale-space clustering, this research proposes a mixed-level regionalization (MLR) method to construct geographic areas with comparable population. The method accounts for spatial connectivity and compactness, attributive homogeneity, and exogenous criteria such as minimum (and approximately equal) population or disease counts. A case study using Louisiana cancer data illustrates the MLR method and its strengths and limitations. A major benefit of the method is that most upper level geographic boundaries can be preserved to increase familiarity of constructed areas. Therefore, the MLR method is more human-oriented and place-based than computer-oriented and space-based. PMID:26251551
Do lower income areas have more pedestrian casualties?
Noland, Robert B; Klein, Nicholas J; Tulach, Nicholas K
2013-10-01
Pedestrian and motor vehicle casualties are analyzed for the State of New Jersey with the objective of determining how the income of an area may be associated with casualties. We develop a maximum-likelihood negative binomial model to examine how various spatially defined variables, including road, income, and vehicle ownership, may be associated with casualties using census block-group level data. Due to suspected spatial correlation in the data we also employ a conditional autoregressive Bayesian model using Markov Chain Monte Carlo simulation, implemented with Crimestat software. Results suggest that spatial correlation is an issue as some variables are not statistically significant in the spatial model. We find that both pedestrian and motor vehicle casualties are greater in lower income block groups. Both are also associated with less household vehicle ownership, which is not surprising for pedestrian casualties, but is a surprising result for motor vehicle casualties. Controls for various road categories provide expected relationships. Individual level data is further examined to determine relationships between the location of a crash victim and their residence zip code, and this largely confirms a residual effect associated with both lower income individuals and lower income areas. Copyright © 2013 Elsevier Ltd. All rights reserved.
Spatial grain and the causes of regional diversity gradients in ants.
Kaspari, Michael; Yuan, May; Alonso, Leeanne
2003-03-01
Gradients of species richness (S; the number of species of a given taxon in a given area and time) are ubiquitous. A key goal in ecology is to understand whether and how the many processes that generate these gradients act at different spatial scales. Here we evaluate six hypotheses for diversity gradients with 49 New World ant communities, from tundra to rain forest. We contrast their performance at three spatial grains from S(plot), the average number of ant species nesting in a m2 plot, through Fisher's alpha, an index that treats our 30 1-m2 plots as subsamples of a locality's diversity. At the smallest grain, S(plot), was tightly correlated (r2 = 0.99) with colony abundance in a fashion indistinguishable from the packing of randomly selected individuals into a fixed space. As spatial grain increased, the coaction of two factors linked to high net rates of diversification--warm temperatures and large areas of uniform climate--accounted for 75% of the variation in Fisher's alpha. However, the mechanisms underlying these correlations (i.e., precisely how temperature and area shape the balance of speciation to extinction) remain elusive.
Scale dependence of the diversity-stability relationship in a temperate grassland.
Zhang, Yunhai; He, Nianpeng; Loreau, Michel; Pan, Qingmin; Han, Xingguo
2018-05-01
A positive relationship between biodiversity and ecosystem stability has been reported in many ecosystems; however, it has yet to be determined whether and how spatial scale affects this relationship. Here, for the first time, we assessed the effects of alpha, beta and gamma diversity on ecosystem stability and the scale dependence of the slope of the diversity-stability relationship.By employing a long-term (33 years) dataset from a temperate grassland, northern China, we calculated the all possible spatial scales with the complete combination from the basic 1-m 2 plots.Species richness was positively associated with ecosystem stability through species asynchrony and overyielding at all spatial scales (1, 2, 3, 4 and 5 m 2 ). Both alpha and beta diversity were positively associated with gamma stability.Moreover, the slope of the diversity-area relationship was significantly higher than that of the stability-area relationship, resulting in a decline of the slope of the diversity-stability relationship with increasing area. Synthesis. With the positive species diversity effect on ecosystem stability from small to large spatial scales, our findings demonstrate the need to maintain a high biodiversity and biotic heterogeneity as insurance against the risks incurred by ecosystems in the face of global environmental changes.
NASA Astrophysics Data System (ADS)
Ba, Yu Tao; xian Liu, Bao; Sun, Feng; Wang, Li hua; Tang, Yu jia; Zhang, Da wei
2017-04-01
High-resolution mapping of PM2.5 is the prerequisite for precise analytics and subsequent anti-pollution interventions. Considering the large variances of particulate distribution, urban-scale mapping is challenging either with ground-based fixed stations, with satellites or via models. In this study, a dynamic fusion method between high-density sensor network and MODIS Aerosol Optical Depth (AOD) was introduced. The sensor network was deployed in Beijing ( > 1000 fixed monitors across 16000 km2 area) to provide raw observations with high temporal resolution (sampling interval < 1 hour), high spatial resolution in flat areas ( < 1 km), and low spatial resolution in mountainous areas ( > 5 km). The MODIS AOD was calibrated to provide distribution map with low temporal resolution (daily) and moderate spatial resolution ( = 3 km). By encoding the data quality and defects (e.g. could, reflectance, abnormal), a hybrid interpolation procedure with cross-validation generated PM2.5 distribution with both high temporal and spatial resolution. Several no-pollutant and high-pollution periods were tested to validate the proposed fusion method for capturing the instantaneous patterns of PM2.5 emission.
A simple distributed sediment delivery approach for rural catchments
NASA Astrophysics Data System (ADS)
Reid, Lucas; Scherer, Ulrike
2014-05-01
The transfer of sediments from source areas to surface waters is a complex process. In process based erosion models sediment input is thus quantified by representing all relevant sub processes such as detachment, transport and deposition of sediment particles along the flow path to the river. A successful application of these models requires, however, a large amount of spatially highly resolved data on physical catchment characteristics, which is only available for a few, well examined small catchments. For the lack of appropriate models, the empirical Universal Soil Loss Equation (USLE) is widely applied to quantify the sediment production in meso to large scale basins. As the USLE provides long-term mean soil loss rates, it is often combined with spatially lumped models to estimate the sediment delivery ratio (SDR). In these models, the SDR is related to data on morphological characteristics of the catchment such as average local relief, drainage density, proportion of depressions or soil texture. Some approaches include the relative distance between sediment source areas and the river channels. However, several studies showed that spatially lumped parameters describing the morphological characteristics are only of limited value to represent the factors of influence on sediment transport at the catchment scale. Sediment delivery is controlled by the location of the sediment source areas in the catchment and the morphology along the flow path to the surface water bodies. This complex interaction of spatially varied physiographic characteristics cannot be adequately represented by lumped morphological parameters. The objective of this study is to develop a simple but spatially distributed approach to quantify the sediment delivery ratio by considering the characteristics of the flow paths in a catchment. We selected a small catchment located in in an intensively cultivated loess region in Southwest Germany as study area for the development of the SDR approach. The flow pathways were extracted in a geographic information system. Then the sediment delivery ratio for each source area was determined using an empirical approach considering the slope, morphology and land use properties along the flow path. As a benchmark for the calibration of the model parameters we used results of a detailed process based erosion model available for the study area. Afterwards the approach was tested in larger catchments located in the same loess region.
NASA Astrophysics Data System (ADS)
Hussain, M.; Chen, D.
2014-11-01
Buildings, the basic unit of an urban landscape, host most of its socio-economic activities and play an important role in the creation of urban land-use patterns. The spatial arrangement of different building types creates varied urban land-use clusters which can provide an insight to understand the relationships between social, economic, and living spaces. The classification of such urban clusters can help in policy-making and resource management. In many countries including the UK no national-level cadastral database containing information on individual building types exists in public domain. In this paper, we present a framework for inferring functional types of buildings based on the analysis of their form (e.g. geometrical properties, such as area and perimeter, layout) and spatial relationship from large topographic and address-based GIS database. Machine learning algorithms along with exploratory spatial analysis techniques are used to create the classification rules. The classification is extended to two further levels based on the functions (use) of buildings derived from address-based data. The developed methodology was applied to the Manchester metropolitan area using the Ordnance Survey's MasterMap®, a large-scale topographic and address-based data available for the UK.
Gervasi, Vincenzo; Sand, Hakan; Zimmermann, Barbara; Mattisson, Jenny; Wabakken, Petter; Linnell, John D C
2013-10-01
Recolonizing carnivores can have a large impact on the status of wild ungulates, which have often modified their behavior in the absence of predation. Therefore, understanding the dynamics of reestablished predator-prey systems is crucial to predict their potential ecosystem effects. We decomposed the spatial structure of predation by recolonizing wolves (Canis lupus) on two sympatric ungulates, moose (Alces alces) and roe deer (Capreolus capreolus), in Scandinavia during a 10-year study. We monitored 18 wolves with GPS collars, distributed over 12 territories, and collected records from predation events. By using conditional logistic regression, we assessed the contributions of three main factors, the utilization patterns of each wolf territory, the spatial distribution of both prey species, and fine-scale landscape structure, in determining the spatial structure of moose and roe deer predation risk. The reestablished predator-prey system showed a remarkable spatial variation in kill occurrence at the intra-territorial level, with kill probabilities varying by several orders of magnitude inside the same territory. Variation in predation risk was evident also when a spatially homogeneous probability for a wolf to encounter a prey was simulated. Even inside the same territory, with the same landscape structure, and when exposed to predation by the same wolves, the two prey species experienced an opposite spatial distribution of predation risk. In particular, increased predation risk for moose was associated with open areas, especially clearcuts and young forest stands, whereas risk was lowered for roe deer in the same habitat types. Thus, fine-scale landscape structure can generate contrasting predation risk patterns in sympatric ungulates, so that they can experience large differences in the spatial distribution of risk and refuge areas when exposed to predation by a recolonizing predator. Territories with an earlier recolonization were not associated with a lower hunting success for wolves. Such constant efficiency in wolf predation during the recolonization process is in line with previous findings about the naive nature of Scandinavian moose to wolf predation. This, together with the human-dominated nature of the Scandinavian ecosystem, seems to limit the possibility for wolves to have large ecosystem effects and to establish a behaviorally mediated trophic cascade in Scandinavia.
Mahoney, Peter J; Young, Julie K; Hersey, Kent R; Larsen, Randy T; McMillan, Brock R; Stoner, David C
2018-04-01
Predator control is often implemented with the intent of disrupting top-down regulation in sensitive prey populations. However, ambiguity surrounding the efficacy of predator management, as well as the strength of top-down effects of predators in general, is often exacerbated by the spatially implicit analytical approaches used in assessing data with explicit spatial structure. Here, we highlight the importance of considering spatial context in the case of a predator control study in south-central Utah. We assessed the spatial match between aerial removal risk in coyotes (Canis latrans) and mule deer (Odocoileus hemionus) resource selection during parturition using a spatially explicit, multi-level Bayesian model. With our model, we were able to evaluate spatial congruence between management action (i.e., coyote removal) and objective (i.e., parturient deer site selection) at two distinct scales: the level of the management unit and the individual coyote removal. In the case of the former, our results indicated substantial spatial heterogeneity in expected congruence between removal risk and parturient deer site selection across large areas, and is a reflection of logistical constraints acting on the management strategy and differences in space use between the two species. At the level of the individual removal, we demonstrated that the potential management benefits of a removed coyote were highly variable across all individuals removed and in many cases, spatially distinct from parturient deer resource selection. Our methods and results provide a means of evaluating where we might anticipate an impact of predator control, while emphasizing the need to weight individual removals based on spatial proximity to management objectives in any assessment of large-scale predator control. Although we highlight the importance of spatial context in assessments of predator control strategy, we believe our methods are readily generalizable in any management or large-scale experimental framework where spatial context is likely an important driver of outcomes. © 2018 by the Ecological Society of America.
The Spatial Scaling of Global Rainfall Extremes
NASA Astrophysics Data System (ADS)
Devineni, N.; Xi, C.; Lall, U.; Rahill-Marier, B.
2013-12-01
Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (upto 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. A clear understanding of the space-time rainfall patterns for events or for a season will enable in assessing the spatial distribution of areas likely to have a high/low inundation potential for each type of rainfall forcing. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances. We also investigate the connection of persistent rainfall events at different latitudinal bands to large-scale climate phenomena such as ENSO. Finally, we present the scaling phenomena of contiguous flooded areas as a result of large scale organization of long duration rainfall events. This can be used for spatially distributed flood risk assessment conditional on a particular rainfall scenario. Statistical models for spatio-temporal loss simulation including model uncertainty to support regional and portfolio analysis can be developed.
NASA Astrophysics Data System (ADS)
Yang, Dedi; Chen, Jin; Zhou, Yuan; Chen, Xiang; Chen, Xuehong; Cao, Xin
2017-06-01
Plastic greenhouses (PGs) are an important agriculture development technique to protect and control the growing environment for food crops. The extensive use of PGs can change the agriculture landscape and affects the local environment. Accurately mapping and estimating the coverage of PGs is a necessity to the strategic planning of modern agriculture. Unfortunately, PG mapping over large areas is methodologically challenging, as the medium spatial resolution satellite imagery (such as Landsat data) used for analysis lacks spatial details and spectral variations. To fill the gap, the paper proposes a new plastic greenhouse index (PGI) based on the spectral, sensitivity, and separability analysis of PGs using medium spatial resolution images. In the context of the Landsat Enhanced Thematic Mapper Plus (ETM+) imagery, the paper examines the effectiveness and capability of the proposed PGI. The results indicate that PGs in Landsat ETM+ image can be successfully detected by the PGI if the PG fraction is greater than 12% in a mixed pixel. A kappa coefficient of 0.83 and overall accuracy of 91.2% were achieved when applying the proposed PGI in the case of Weifang District, Shandong, China. These results show that the proposed index can be applied to identifying transparent PGs in atmospheric corrected Landsat image and has the potential for the digital mapping of plastic greenhouse coverage over a large area.
Griffin, Kingsley J; Hedge, Luke H; González-Rivero, Manuel; Hoegh-Guldberg, Ove I; Johnston, Emma L
2017-07-01
Historically, marine ecologists have lacked efficient tools that are capable of capturing detailed species distribution data over large areas. Emerging technologies such as high-resolution imaging and associated machine-learning image-scoring software are providing new tools to map species over large areas in the ocean. Here, we combine a novel diver propulsion vehicle (DPV) imaging system with free-to-use machine-learning software to semi-automatically generate dense and widespread abundance records of a habitat-forming algae over ~5,000 m 2 of temperate reef. We employ replicable spatial techniques to test the effectiveness of traditional diver-based sampling, and better understand the distribution and spatial arrangement of one key algal species. We found that the effectiveness of a traditional survey depended on the level of spatial structuring, and generally 10-20 transects (50 × 1 m) were required to obtain reliable results. This represents 2-20 times greater replication than have been collected in previous studies. Furthermore, we demonstrate the usefulness of fine-resolution distribution modeling for understanding patterns in canopy algae cover at multiple spatial scales, and discuss applications to other marine habitats. Our analyses demonstrate that semi-automated methods of data gathering and processing provide more accurate results than traditional methods for describing habitat structure at seascape scales, and therefore represent vastly improved techniques for understanding and managing marine seascapes.
NASA Technical Reports Server (NTRS)
Lillesand, T. M.; Werth, L. F. (Principal Investigator)
1980-01-01
A 25% improvement in average classification accuracy was realized by processing double-date vs. single-date data. Under the spectrally and spatially complex site conditions characterizing the geographical area used, further improvement in wetland classification accuracy is apparently precluded by the spectral and spatial resolution restrictions of the LANDSAT MSS. Full scene analysis of scanning densitometer data extracted from scale infrared photography failed to permit discrimination of many wetland and nonwetland cover types. When classification of photographic data was limited to wetland areas only, much more detailed and accurate classification could be made. The integration of conventional image interpretation (to simply delineate wetland boundaries) and machine assisted classification (to discriminate among cover types present within the wetland areas) appears to warrant further research to study the feasibility and cost of extending this methodology over a large area using LANDSAT and/or small scale photography.
R Barbero; J T Abatzoglou; E A Steel
2014-01-01
Very large-fires (VLFs) have widespread impacts on ecosystems, air quality, fire suppression resources, and in many regions account for a majority of total area burned. Empirical generalized linear models of the largest fires (>5000 ha) across the contiguous United States (US) were developed at ¡Â60 km spatial and weekly temporal resolutions using solely atmospheric...
K. Bruce Jones; Anne C. Neale; Timothy G. Wade; James D. Wickham; Chad L. Cross; Curtis M. Edmonds; Thomas R. Loveland; Maliha S. Nash; Kurt H. Riitters; Elizabeth R. Smith
2001-01-01
Spatially explicit identification of changes in ecological conditions over large areas is key to targeting and prioitizing areas for environmental protection and restoration by managers at watershed, basin, and regional scales. A critical limitation to this point has been the development of methods to conduct such broad-scale assessments. Field-based methods have...
Murguía, Diego I; Bringezu, Stefan; Schaldach, Rüdiger
2016-09-15
Biodiversity loss is widely recognized as a serious global environmental change process. While large-scale metal mining activities do not belong to the top drivers of such change, these operations exert or may intensify pressures on biodiversity by adversely changing habitats, directly and indirectly, at local and regional scales. So far, analyses of global spatial dynamics of mining and its burden on biodiversity focused on the overlap between mines and protected areas or areas of high value for conservation. However, it is less clear how operating metal mines are globally exerting pressure on zones of different biodiversity richness; a similar gap exists for unmined but known mineral deposits. By using vascular plants' diversity as a proxy to quantify overall biodiversity, this study provides a first examination of the global spatial distribution of mines and deposits for five key metals across different biodiversity zones. The results indicate that mines and deposits are not randomly distributed, but concentrated within intermediate and high diversity zones, especially bauxite and silver. In contrast, iron, gold, and copper mines and deposits are closer to a more proportional distribution while showing a high concentration in the intermediate biodiversity zone. Considering the five metals together, 63% and 61% of available mines and deposits, respectively, are located in intermediate diversity zones, comprising 52% of the global land terrestrial surface. 23% of mines and 20% of ore deposits are located in areas of high plant diversity, covering 17% of the land. 13% of mines and 19% of deposits are in areas of low plant diversity, comprising 31% of the land surface. Thus, there seems to be potential for opening new mines in areas of low biodiversity in the future. Copyright © 2016 Elsevier Ltd. All rights reserved.
Opal photonic crystals infiltrated with chalcogenide glasses
DOE Office of Scientific and Technical Information (OSTI.GOV)
Astratov, V. N.; Adawi, A. M.; Skolnick, M. S.
Composite opal structures for nonlinear applications are obtained by infiltration with chalcogenide glasses As{sub 2}S{sub 3} and AsSe by precipitation from solution. Analysis of spatially resolved optical spectra reveals that the glass aggregates into submillimeter areas inside the opal. These areas exhibit large shifts in the optical stop bands by up to 80 nm, and by comparison with modelling are shown to have uniform glass filling factors of opal pores up to 40%. Characterization of the domain structure of the opals prior to infiltration by large area angle-resolved spectroscopy is an important step in the analysis of the properties ofmore » the infiltrated regions. {copyright} 2001 American Institute of Physics.« less
NASA Astrophysics Data System (ADS)
Yi, Yonghong; Kimball, John S.; Chen, Richard H.; Moghaddam, Mahta; Reichle, Rolf H.; Mishra, Umakant; Zona, Donatella; Oechel, Walter C.
2018-01-01
An important feature of the Arctic is large spatial heterogeneity in active layer conditions, which is generally poorly represented by global models and can lead to large uncertainties in predicting regional ecosystem responses and climate feedbacks. In this study, we developed a spatially integrated modeling and analysis framework combining field observations, local-scale ( ˜ 50 m resolution) active layer thickness (ALT) and soil moisture maps derived from low-frequency (L + P-band) airborne radar measurements, and global satellite environmental observations to investigate the ALT sensitivity to recent climate trends and landscape heterogeneity in Alaska. Modeled ALT results show good correspondence with in situ measurements in higher-permafrost-probability (PP ≥ 70 %) areas (n = 33; R = 0.60; mean bias = 1.58 cm; RMSE = 20.32 cm), but with larger uncertainty in sporadic and discontinuous permafrost areas. The model results also reveal widespread ALT deepening since 2001, with smaller ALT increases in northern Alaska (mean trend = 0.32±1.18 cm yr-1) and much larger increases (> 3 cm yr-1) across interior and southern Alaska. The positive ALT trend coincides with regional warming and a longer snow-free season (R = 0.60 ± 0.32). A spatially integrated analysis of the radar retrievals and model sensitivity simulations demonstrated that uncertainty in the spatial and vertical distribution of soil organic carbon (SOC) was the largest factor affecting modeled ALT accuracy, while soil moisture played a secondary role. Potential improvements in characterizing SOC heterogeneity, including better spatial sampling of soil conditions and advances in remote sensing of SOC and soil moisture, will enable more accurate predictions of active layer conditions and refinement of the modeling framework across a larger domain.
Bilateral parietal contributions to spatial language.
Conder, Julie; Fridriksson, Julius; Baylis, Gordon C; Smith, Cameron M; Boiteau, Timothy W; Almor, Amit
2017-01-01
It is commonly held that language is largely lateralized to the left hemisphere in most individuals, whereas spatial processing is associated with right hemisphere regions. In recent years, a number of neuroimaging studies have yielded conflicting results regarding the role of language and spatial processing areas in processing language about space (e.g., Carpenter, Just, Keller, Eddy, & Thulborn, 1999; Damasio et al., 2001). In the present study, we used sparse scanning event-related functional magnetic resonance imaging (fMRI) to investigate the neural correlates of spatial language, that is; language used to communicate the spatial relationship of one object to another. During scanning, participants listened to sentences about object relationships that were either spatial or non-spatial in nature (color or size relationships). Sentences describing spatial relationships elicited more activation in the superior parietal lobule and precuneus bilaterally in comparison to sentences describing size or color relationships. Activation of the precuneus suggests that spatial sentences elicit spatial-mental imagery, while the activation of the SPL suggests sentences containing spatial language involve integration of two distinct sets of information - linguistic and spatial. Copyright © 2016 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Cao, Hui; Knitter, Sebastian; Liu, Changgeng; Redding, Brandon; Khokha, Mustafa Kezar; Choma, Michael Andrew
2017-02-01
Speckle formation is a limiting factor when using coherent sources for imaging and sensing, but can provide useful information about the motion of an object. Illumination sources with tunable spatial coherence are therefore desirable as they can offer both speckled and speckle-free images. Efficient methods of coherence switching have been achieved with a solid-state degenerate laser, and here we demonstrate a semiconductor-based degenerate laser system that can be switched between a large number of mutually incoherent spatial modes and few-mode operation. Our system is designed around a semiconductor gain element, and overcomes barriers presented by previous low spatial coherence lasers. The gain medium is an electrically-pumped vertical external cavity surface emitting laser (VECSEL) with a large active area. The use of a degenerate external cavity enables either distributing the laser emission over a large ( 1000) number of mutually incoherent spatial modes or concentrating emission to few modes by using a pinhole in the Fourier plane of the self-imaging cavity. To demonstrate the unique potential of spatial coherence switching for multimodal biomedical imaging, we use both low and high spatial coherence light generated by our VECSEL-based degenerate laser for imaging embryo heart function in Xenopus, an important animal model of heart disease. The low-coherence illumination is used for high-speed (100 frames per second) speckle-free imaging of dynamic heart structure, while the high-coherence emission is used for laser speckle contrast imaging of the blood flow.
Dorazio, Robert; Delampady, Mohan; Dey, Soumen; Gopalaswamy, Arjun M.; Karanth, K. Ullas; Nichols, James D.
2017-01-01
Conservationists and managers are continually under pressure from the public, the media, and political policy makers to provide “tiger numbers,” not just for protected reserves, but also for large spatial scales, including landscapes, regions, states, nations, and even globally. Estimating the abundance of tigers within relatively small areas (e.g., protected reserves) is becoming increasingly tractable (see Chaps. 9 and 10), but doing so for larger spatial scales still presents a formidable challenge. Those who seek “tiger numbers” are often not satisfied by estimates of tiger occupancy alone, regardless of the reliability of the estimates (see Chaps. 4 and 5). As a result, wherever tiger conservation efforts are underway, either substantially or nominally, scientists and managers are frequently asked to provide putative large-scale tiger numbers based either on a total count or on an extrapolation of some sort (see Chaps. 1 and 2).
Spatial organization of foreshocks as a tool to forecast large earthquakes.
Lippiello, E; Marzocchi, W; de Arcangelis, L; Godano, C
2012-01-01
An increase in the number of smaller magnitude events, retrospectively named foreshocks, is often observed before large earthquakes. We show that the linear density probability of earthquakes occurring before and after small or intermediate mainshocks displays a symmetrical behavior, indicating that the size of the area fractured during the mainshock is encoded in the foreshock spatial organization. This observation can be used to discriminate spatial clustering due to foreshocks from the one induced by aftershocks and is implemented in an alarm-based model to forecast m > 6 earthquakes. A retrospective study of the last 19 years Southern California catalog shows that the daily occurrence probability presents isolated peaks closely located in time and space to the epicenters of five of the six m > 6 earthquakes. We find daily probabilities as high as 25% (in cells of size 0.04 × 0.04deg(2)), with significant probability gains with respect to standard models.
Spatial organization of foreshocks as a tool to forecast large earthquakes
Lippiello, E.; Marzocchi, W.; de Arcangelis, L.; Godano, C.
2012-01-01
An increase in the number of smaller magnitude events, retrospectively named foreshocks, is often observed before large earthquakes. We show that the linear density probability of earthquakes occurring before and after small or intermediate mainshocks displays a symmetrical behavior, indicating that the size of the area fractured during the mainshock is encoded in the foreshock spatial organization. This observation can be used to discriminate spatial clustering due to foreshocks from the one induced by aftershocks and is implemented in an alarm-based model to forecast m > 6 earthquakes. A retrospective study of the last 19 years Southern California catalog shows that the daily occurrence probability presents isolated peaks closely located in time and space to the epicenters of five of the six m > 6 earthquakes. We find daily probabilities as high as 25% (in cells of size 0.04 × 0.04deg2), with significant probability gains with respect to standard models. PMID:23152938
Modeling α- and β-diversity in a tropical forest from remotely sensed and spatial data
NASA Astrophysics Data System (ADS)
Hernández-Stefanoni, J. Luis; Gallardo-Cruz, J. Alberto; Meave, Jorge A.; Rocchini, Duccio; Bello-Pineda, Javier; López-Martínez, J. Omar
2012-10-01
Comprehensive information on species distribution and species composition patterns of plant communities is required for effective conservation and management of biodiversity. Remote sensing offers an inexpensive means of attaining complete spatial coverage for large areas, at regular time intervals, and can therefore be extremely useful for estimating both species richness and spatial variation of species composition (α- and β-diversity). An essential step to map such attributes is to identify and understand their main drivers. We used remotely sensed data as a surrogate of plant productivity and habitat structure variables for explaining α- and β-diversity, and evaluated the relative roles of productivity-habitat structure and spatial variables in explaining observed patterns of α- and β-diversity by using a Principal Coordinates of Neighbor Matrices analysis. We also examined the relationship between remotely sensed and field data, in order to map α- and β-diversity at the landscape-level in the Yucatan Peninsula, using a regression kriging procedure. These two procedures integrate the relationship of species richness and spatial species turnover both with remotely sensed data and spatial structure. The empirical models so obtained can be used to predict species richness and variation in species composition, and they can be regarded as valuable tools not only for identifying areas with high local species richness (α-diversity), but also areas with high species turnover (β-diversity). Ultimately, information obtained in this way can help maximize the number of species preserved in a landscape.
Xian, George; Homer, Collin G.; Granneman, Brian; Meyer, Debra K.
2012-01-01
Remote sensing information has been widely used to monitor vegetation condition and variations in a variety of ecosystems, including shrublands. Careful application of remotely sensed imagery can provide additional spatially explicit, continuous, and extensive data on the composition and condition of shrubland ecosystems. Historically, the most widely available remote sensing information has been collected by Landsat, which has offered large spatial coverage and moderate spatial resolution data globally for nearly three decades. Such medium-resolution satellite remote sensing information can quantify the distribution and variation of terrestrial ecosystems. Landsat imagery has been frequently used with other high-resolution remote sensing data to classify sagebrush components and quantify their spatial distributions (Ramsey and others, 2004; Seefeldt and Booth, 2004; Stow and others, 2008; Underwood and others, 2007). Modeling algorithms have been developed to use field measurements and satellite remote sensing data to quantify the extent and evaluate the quality of shrub ecosystem components in large geographic areas (Homer and others, 2009). The percent cover of sagebrush ecosystem components, including bare-ground, herbaceous, litter, sagebrush, and shrub, have been quantified for entire western states (Homer and others, 2012). Furthermore, research has demonstrated the use of current measurements with historical archives of Landsat imagery to quantify the variations of these components for the last two decades (Xian and others, 2012). The modeling method used to quantify the extent and spatial distribution of sagebrush components over a large area also has required considerable amounts of training data to meet targeted accuracy requirements. These training data have maintained product accuracy by ensuring that they are derived from good quality field measurements collected during appropriate ecosystem phenology and subsequently maximized by extrapolation on high-resolution remote sensing data (Homer and others, 2012). This method has proven its utility; however, to develop these products across even larger areas will require additional cost efficiencies to ensure that an adequate product can be developed for the lowest cost possible. Given the vast geographic extent of shrubland ecosystems in the western United States, identifying cost efficiencies with optimal training data development and subsequent application to medium resolution satellite imagery provide the most likely areas for methodological efficiency gains. The primary objective of this research was to conduct a series of sensitivity tests to evaluate the most optimal and practical way to develop Landsat scale information for estimating the extent and distribution of sagebrush ecosystem components over large areas in the conterminous United States. An existing dataset of sagebrush components developed from extensive field measurements, high-resolution satellite imagery, and medium resolution Landsat imagery in Wyoming was used as the reference database (Homer and others, 2012). Statistical analysis was performed to analyze the relation between the accuracy of sagebrush components and the amount and distribution of training data on Landsat scenes needed to obtain accurate predictions.
NASA Technical Reports Server (NTRS)
Lowery, Anthony R.; Smith, Robert B.
1994-01-01
Stochastic inversion for flexural loads and flexural rigidity of the continental elastic layer can be accomplished most effectively by using the coherence of gravity and topography. However, the spatial resolution of coherence analysis has been limited by use of two-dimensional periodogram spectra from very large (greater than 10(exp 5)sq km) windows that generally include multiple tectonic features. Using a two-dimensional spectral estimator based on the maximum entropy method, the spatial resolution of flexural proerties can be enhanced by a factor of 4 or more, enabling more detailed analysis at the scale of individual tectonic features. This new approach is used to map the spatial variation of flexural rigidity along the Basin and Range transition to the Colorado Plateau and Middle Rocky Mountains physiographic provinces. Large variations in flexural isostatic responses are found, with rigidities ranging from as low as 8.7 x 10(exp 20) N m (elastic thickness (T(sub e) = 4.6 km) in the Basin and Range to as high as 4.1 x 10(exp 24) N m T(sub e) = 77 km) in the Middle Rocky Mountains. These results compare favorably woith independent determinations of flexural rigidity in the region. Areas of low flexural rigidity correlate strongly with areas of high surface heat flow, as is expected from the contingence of flexural rigidity on a temperature-dependent flow law. Also, late Cenozoic normal faults with large displacements are found primarily in area of low flexural rigidity region. The highest flexural rigidity is found within the Archean Wyoming craton, where evidence suggests that deeply rooted cratonic lithosphere may play a role in determining the distribution of tectonism at the surface.
Spatio-temporal modeling of chronic PM 10 exposure for the Nurses' Health Study
NASA Astrophysics Data System (ADS)
Yanosky, Jeff D.; Paciorek, Christopher J.; Schwartz, Joel; Laden, Francine; Puett, Robin; Suh, Helen H.
2008-06-01
Chronic epidemiological studies of airborne particulate matter (PM) have typically characterized the chronic PM exposures of their study populations using city- or county-wide ambient concentrations, which limit the studies to areas where nearby monitoring data are available and which ignore within-city spatial gradients in ambient PM concentrations. To provide more spatially refined and precise chronic exposure measures, we used a Geographic Information System (GIS)-based spatial smoothing model to predict monthly outdoor PM10 concentrations in the northeastern and midwestern United States. This model included monthly smooth spatial terms and smooth regression terms of GIS-derived and meteorological predictors. Using cross-validation and other pre-specified selection criteria, terms for distance to road by road class, urban land use, block group and county population density, point- and area-source PM10 emissions, elevation, wind speed, and precipitation were found to be important determinants of PM10 concentrations and were included in the final model. Final model performance was strong (cross-validation R2=0.62), with little bias (-0.4 μg m-3) and high precision (6.4 μg m-3). The final model (with monthly spatial terms) performed better than a model with seasonal spatial terms (cross-validation R2=0.54). The addition of GIS-derived and meteorological predictors improved predictive performance over spatial smoothing (cross-validation R2=0.51) or inverse distance weighted interpolation (cross-validation R2=0.29) methods alone and increased the spatial resolution of predictions. The model performed well in both rural and urban areas, across seasons, and across the entire time period. The strong model performance demonstrates its suitability as a means to estimate individual-specific chronic PM10 exposures for large populations.
Bressler, David W; Fortenbaugh, Francesca C; Robertson, Lynn C; Silver, Michael A
2013-06-07
Endogenous visual spatial attention improves perception and enhances neural responses to visual stimuli at attended locations. Although many aspects of visual processing differ significantly between central and peripheral vision, little is known regarding the neural substrates of the eccentricity dependence of spatial attention effects. We measured amplitudes of positive and negative fMRI responses to visual stimuli as a function of eccentricity in a large number of topographically-organized cortical areas. Responses to each stimulus were obtained when the stimulus was attended and when spatial attention was directed to a stimulus in the opposite visual hemifield. Attending to the stimulus increased both positive and negative response amplitudes in all cortical areas we studied: V1, V2, V3, hV4, VO1, LO1, LO2, V3A/B, IPS0, TO1, and TO2. However, the eccentricity dependence of these effects differed considerably across cortical areas. In early visual, ventral, and lateral occipital cortex, attentional enhancement of positive responses was greater for central compared to peripheral eccentricities. The opposite pattern was observed in dorsal stream areas IPS0 and putative MT homolog TO1, where attentional enhancement of positive responses was greater in the periphery. Both the magnitude and the eccentricity dependence of attentional modulation of negative fMRI responses closely mirrored that of positive responses across cortical areas. Copyright © 2013 Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Abdo, A. A.; National Academy of Sciences, Washington, D.C. 20001; Ackermann, M.
We report on measurements of the cosmic-ray induced {gamma}-ray emission of Earth's atmosphere by the Large Area Telescope on board the Fermi Gamma-ray Space Telescope. The Large Area Telescope has observed the Earth during its commissioning phase and with a dedicated Earth limb following observation in September 2008. These measurements yielded {approx}6.4x10{sup 6} photons with energies >100 MeV and {approx}250 hours total live time for the highest quality data selection. This allows the study of the spatial and spectral distributions of these photons with unprecedented detail. The spectrum of the emission--often referred to as Earth albedo gamma-ray emission--has a power-lawmore » shape up to 500 GeV with spectral index {gamma}=2.79{+-}0.06.« less
Robinson, Stacie J.; Samuel, Michael D.; Lopez, Davin L.; Shelton, Paul
2012-01-01
One of the pervasive challenges in landscape genetics is detecting gene flow patterns within continuous populations of highly mobile wildlife. Understanding population genetic structure within a continuous population can give insights into social structure, movement across the landscape and contact between populations, which influence ecological interactions, reproductive dynamics or pathogen transmission. We investigated the genetic structure of a large population of deer spanning the area of Wisconsin and Illinois, USA, affected by chronic wasting disease. We combined multiscale investigation, landscape genetic techniques and spatial statistical modelling to address the complex questions of landscape factors influencing population structure. We sampled over 2000 deer and used spatial autocorrelation and a spatial principal components analysis to describe the population genetic structure. We evaluated landscape effects on this pattern using a spatial autoregressive model within a model selection framework to test alternative hypotheses about gene flow. We found high levels of genetic connectivity, with gradients of variation across the large continuous population of white-tailed deer. At the fine scale, spatial clustering of related animals was correlated with the amount and arrangement of forested habitat. At the broader scale, impediments to dispersal were important to shaping genetic connectivity within the population. We found significant barrier effects of individual state and interstate highways and rivers. Our results offer an important understanding of deer biology and movement that will help inform the management of this species in an area where overabundance and disease spread are primary concerns.
NASA Astrophysics Data System (ADS)
Marcum, Richard A.; Davis, Curt H.; Scott, Grant J.; Nivin, Tyler W.
2017-10-01
We evaluated how deep convolutional neural networks (DCNN) could assist in the labor-intensive process of human visual searches for objects of interest in high-resolution imagery over large areas of the Earth's surface. Various DCNN were trained and tested using fewer than 100 positive training examples (China only) from a worldwide surface-to-air-missile (SAM) site dataset. A ResNet-101 DCNN achieved a 98.2% average accuracy for the China SAM site data. The ResNet-101 DCNN was used to process ˜19.6 M image chips over a large study area in southeastern China. DCNN chip detections (˜9300) were postprocessed with a spatial clustering algorithm to produce a ranked list of ˜2100 candidate SAM site locations. The combination of DCNN processing and spatial clustering effectively reduced the search area by ˜660X (0.15% of the DCNN-processed land area). An efficient web interface was used to facilitate a rapid serial human review of the candidate SAM sites in the China study area. Four novice imagery analysts with no prior imagery analysis experience were able to complete a DCNN-assisted SAM site search in an average time of ˜42 min. This search was ˜81X faster than a traditional visual search over an equivalent land area of ˜88,640 km2 while achieving nearly identical statistical accuracy (˜90% F1).
NASA Astrophysics Data System (ADS)
Shi, X.; Zhao, C.
2017-12-01
Haze aerosol pollution has been a focus issue in China, and its characteristics is highly demanded. With limited observation sites, aerosol properties obtained from a single site is frequently used to represent the haze condition over a large domain, such as tens of kilometers. This could result in high uncertainties in the haze characteristics due to their spatial variation. Using a network observation from November 2015 to February 2016 over an urban city in North China with high spatial resolution, this study examines the spatial representation of ground site observations. A method is first developed to determine the representative area of measurements from limited stations. The key idea of this method is to determine the spatial variability of particulate matter with diameters less than 2.5 μm (PM2.5) concentration using a variance function in 2km x 2km grids. Based on the high spatial resolution (0.5km x 0.5km) measurements of PM2.5, the grids in which PM2.5 have high correlations and weak value differences are determined as the representation area of measurements at these grids. Note that the size representation area is not exactly a circle region. It shows that the size representation are for the study region and study period ranges from 0.25 km2 to 16.25 km2. The representation area varies with locations. For the 20 km x 20 km study region, 10 station observations would have a good representation of the PM2.5 observations obtained from current 169 stations at the four-month time scale.
NASA Astrophysics Data System (ADS)
Sugimoto, Akira; Sakai, Yuta; Nagasaka, Kouhei; Ekino, Toshikazu
2015-11-01
The nanoscale spatial distributions of large gap-like structure on superconducting FeSe1-xTex were investigated by scanning tunneling microscopy/spectroscopy (STM/STS). The STM topography shows regular atomic lattice arrangements with the lattice spacing ∼0.38 nm, together with the randomly distributed large spots due to the excess Fe atoms. From the STS measurements, the small gap structures of Δ ∼ 7 meV were partly observed. On the other hand, the high-bias dI/dV curves exhibit the broad peak structures at the negative biases of VPG = -200 to -400 mV in the measured whole surface area. The average of these large gaps is |VPGave| ∼ 305 mV with the standard deviation of σ ∼ 48 mV. The spatial distributions of the VPG exhibit the domain structures consisting of the relatively smaller gaps (<250 meV), which correspond to the excess Fe positions. The small gap Δ ∼ 7 meV is also observed at those positions, suggesting that the excess Fe affects the electronic structures of FeSe1-xTex.
Photonic lantern adaptive spatial mode control in LMA fiber amplifiers.
Montoya, Juan; Aleshire, Chris; Hwang, Christopher; Fontaine, Nicolas K; Velázquez-Benítez, Amado; Martz, Dale H; Fan, T Y; Ripin, Dan
2016-02-22
We demonstrate adaptive-spatial mode control (ASMC) in few-moded double-clad large mode area (LMA) fiber amplifiers by using an all-fiber-based photonic lantern. Three single-mode fiber inputs are used to adaptively inject the appropriate superposition of input modes in a multimode gain fiber to achieve the desired mode at the output. By actively adjusting the relative phase of the single-mode inputs, near-unity coherent combination resulting in a single fundamental mode at the output is achieved.
Wei, Yan-Li; Bao, Lian-Jun; Wu, Chen-Chou; Zeng, Eddy Y
2016-08-01
Anthropogenic impacts have continuously intensified in mega urban centers with increasing urbanization and growing population. The spatial distribution pattern of such impacts can be assessed with soil halogenated flame retardants (HFRs) as HFRs are mostly derived from the production and use of various consumer products. In the present study, soil samples were collected from the Pearl River Delta (PRD), a large urbanized region in southern China, and its surrounding areas and analyzed for a group of HFRs, i.e., polybrominated diphenyl ethers (PBDEs), decabromodiphenyl ethane, bis(hexachlorocyclopentadieno)cyclooctane (DP) and hexabromobenzene. The sum concentrations of HFRs and PBDEs were in the ranges of 0.66-6500 and 0.37-5700 (mean: 290 and 250) ng g(-1) dry weight, respectively, around the middle level of the global range. BDE-209 was the predominant compound likely due to the huge amounts of usage and its persistence. The concentrations of HFRs were greater in the land-use types of residency, industry and landfill than in agriculture, forestry and drinking water source, and were also greater in the central PRD than in its surrounding areas. The concentrations of HFRs were moderately significantly (r(2) = 0.32-0.57; p < 0.05) correlated with urbanization levels, population densities and gross domestic productions in fifteen administrative districts. The spatial distribution of DP isomers appeared to be stereoselective as indicated by the similarity in the spatial patterns for the ratio of anti-DP versus the sum of DP isomers (fanti-DP) and DP concentrations. Finally, the concentrations of HFRs sharply decreased with increasing distance from an e-waste recycling site, indicating that e-waste derived HFRs largely remained in local soil. Copyright © 2016 Elsevier Ltd. All rights reserved.
Robustness of spatial micronetworks
NASA Astrophysics Data System (ADS)
McAndrew, Thomas C.; Danforth, Christopher M.; Bagrow, James P.
2015-04-01
Power lines, roadways, pipelines, and other physical infrastructure are critical to modern society. These structures may be viewed as spatial networks where geographic distances play a role in the functionality and construction cost of links. Traditionally, studies of network robustness have primarily considered the connectedness of large, random networks. Yet for spatial infrastructure, physical distances must also play a role in network robustness. Understanding the robustness of small spatial networks is particularly important with the increasing interest in microgrids, i.e., small-area distributed power grids that are well suited to using renewable energy resources. We study the random failures of links in small networks where functionality depends on both spatial distance and topological connectedness. By introducing a percolation model where the failure of each link is proportional to its spatial length, we find that when failures depend on spatial distances, networks are more fragile than expected. Accounting for spatial effects in both construction and robustness is important for designing efficient microgrids and other network infrastructure.
Exploring spatial-temporal dynamics of fire regime features in mainland Spain
NASA Astrophysics Data System (ADS)
Jiménez-Ruano, Adrián; Rodrigues Mimbrero, Marcos; de la Riva Fernández, Juan
2017-10-01
This paper explores spatial-temporal dynamics in fire regime features, such as fire frequency, burnt area, large fires and natural- and human-caused fires, as an essential part of fire regime characterization. Changes in fire features are analysed at different spatial - regional and provincial/NUTS3 - levels, together with summer and winter temporal scales, using historical fire data from Spain for the period 1974-2013. Temporal shifts in fire features are investigated by means of change point detection procedures - Pettitt test, AMOC (at most one change), PELT (pruned exact linear time) and BinSeg (binary segmentation) - at a regional level to identify changes in the time series of the features. A trend analysis was conducted using the Mann-Kendall and Sen's slope tests at both the regional and NUTS3 level. Finally, we applied a principal component analysis (PCA) and varimax rotation to trend outputs - mainly Sen's slope values - to summarize overall temporal behaviour and to explore potential links in the evolution of fire features. Our results suggest that most fire features show remarkable shifts between the late 1980s and the first half of the 1990s. Mann-Kendall outputs revealed negative trends in the Mediterranean region. Results from Sen's slope suggest high spatial and intra-annual variability across the study area. Fire activity related to human sources seems to be experiencing an overall decrease in the northwestern provinces, particularly pronounced during summer. Similarly, the Hinterland and the Mediterranean coast are gradually becoming less fire affected. Finally, PCA enabled trends to be synthesized into four main components: winter fire frequency (PC1), summer burnt area (PC2), large fires (PC3) and natural fires (PC4).
Large Oil Spill Classification Using SAR Images Based on Spatial Histogram
NASA Astrophysics Data System (ADS)
Schvartzman, I.; Havivi, S.; Maman, S.; Rotman, S. R.; Blumberg, D. G.
2016-06-01
Among the different types of marine pollution, oil spill is a major threat to the sea ecosystems. Remote sensing is used in oil spill response. Synthetic Aperture Radar (SAR) is an active microwave sensor that operates under all weather conditions and provides information about the surface roughness and covers large areas at a high spatial resolution. SAR is widely used to identify and track pollutants in the sea, which may be due to a secondary effect of a large natural disaster or by a man-made one . The detection of oil spill in SAR imagery relies on the decrease of the backscattering from the sea surface, due to the increased viscosity, resulting in a dark formation that contrasts with the brightness of the surrounding area. Most of the use of SAR images for oil spill detection is done by visual interpretation. Trained interpreters scan the image, and mark areas of low backscatter and where shape is a-symmetrical. It is very difficult to apply this method for a wide area. In contrast to visual interpretation, automatic detection algorithms were suggested and are mainly based on scanning dark formations, extracting features, and applying big data analysis. We propose a new algorithm that applies a nonlinear spatial filter that detects dark formations and is not susceptible to noises, such as internal or speckle. The advantages of this algorithm are both in run time and the results retrieved. The algorithm was tested in genesimulations as well as on COSMO-SkyMed images, detecting the Deep Horizon oil spill in the Gulf of Mexico (occurred on 20/4/2010). The simulation results show that even in a noisy environment, oil spill is detected. Applying the algorithm to the Deep Horizon oil spill, the algorithm classified the oil spill better than focusing on dark formation algorithm. Furthermore, the results were validated by the National Oceanic and Atmospheric Administration (NOAA) data.
NASA Technical Reports Server (NTRS)
Hussain, A. K. M. F.
1980-01-01
Comparisons of the distributions of large scale structures in turbulent flow with distributions based on time dependent signals from stationary probes and the Taylor hypothesis are presented. The study investigated an area in the near field of a 7.62 cm circular air jet at a Re of 32,000, specifically having coherent structures through small-amplitude controlled excitation and stable vortex pairing in the jet column mode. Hot-wire and X-wire anemometry were employed to establish phase averaged spatial distributions of longitudinal and lateral velocities, coherent Reynolds stress and vorticity, background turbulent intensities, streamlines and pseudo-stream functions. The Taylor hypothesis was used to calculate spatial distributions of the phase-averaged properties, with results indicating that the usage of the local time-average velocity or streamwise velocity produces large distortions.
The market value of cultural heritage in urban areas: an application of spatial hedonic pricing
NASA Astrophysics Data System (ADS)
Lazrak, Faroek; Nijkamp, Peter; Rietveld, Piet; Rouwendal, Jan
2014-01-01
The current literature often values intangible goods like cultural heritage by applying stated preference methods. In recent years, however, the increasing availability of large databases on real estate transactions and listed prices has opened up new research possibilities and has reduced various existing barriers to applications of conventional (spatial) hedonic analysis to the real estate market. The present paper provides one of the first applications using a spatial autoregressive model to investigate the impact of cultural heritage—in particular, listed buildings and historic-cultural sites (or historic landmarks)—on the value of real estate in cities. In addition, this paper suggests a novel way of specifying the spatial weight matrix—only prices of sold houses influence current price—in identifying the spatial dependency effects between sold properties. The empirical application in the present study concerns the Dutch urban area of Zaanstad, a historic area for which over a long period of more than 20 years detailed information on individual dwellings, and their market prices are available in a GIS context. In this paper, the effect of cultural heritage is analysed in three complementary ways. First, we measure the effect of a listed building on its market price in the relevant area concerned. Secondly, we investigate the value that listed heritage has on nearby property. And finally, we estimate the effect of historic-cultural sites on real estate prices. We find that, to purchase a listed building, buyers are willing to pay an additional 26.9 %, while surrounding houses are worth an extra 0.28 % for each additional listed building within a 50-m radius. Houses sold within a conservation area appear to gain a premium of 26.4 % which confirms the existence of a `historic ensemble' effect.
Hyperspectral remote sensing of wild oyster reefs
NASA Astrophysics Data System (ADS)
Le Bris, Anthony; Rosa, Philippe; Lerouxel, Astrid; Cognie, Bruno; Gernez, Pierre; Launeau, Patrick; Robin, Marc; Barillé, Laurent
2016-04-01
The invasion of the wild oyster Crassostrea gigas along the western European Atlantic coast has generated changes in the structure and functioning of intertidal ecosystems. Considered as an invasive species and a trophic competitor of the cultivated conspecific oyster, it is now seen as a resource by oyster farmers following recurrent mass summer mortalities of oyster spat since 2008. Spatial distribution maps of wild oyster reefs are required by local authorities to help define management strategies. In this work, visible-near infrared (VNIR) hyperspectral and multispectral remote sensing was investigated to map two contrasted intertidal reef structures: clusters of vertical oysters building three-dimensional dense reefs in muddy areas and oysters growing horizontally creating large flat reefs in rocky areas. A spectral library, collected in situ for various conditions with an ASD spectroradiometer, was used to run Spectral Angle Mapper classifications on airborne data obtained with an HySpex sensor (160 spectral bands) and SPOT satellite HRG multispectral data (3 spectral bands). With HySpex spectral/spatial resolution, horizontal oysters in the rocky area were correctly classified but the detection was less efficient for vertical oysters in muddy areas. Poor results were obtained with the multispectral image and from spatially or spectrally degraded HySpex data, it was clear that the spectral resolution was more important than the spatial resolution. In fact, there was a systematic mud deposition on shells of vertical oyster reefs explaining the misclassification of 30% of pixels recognized as mud or microphytobenthos. Spatial distribution maps of oyster reefs were coupled with in situ biomass measurements to illustrate the interest of a remote sensing product to provide stock estimations of wild oyster reefs to be exploited by oyster producers. This work highlights the interest of developing remote sensing techniques for aquaculture applications in coastal areas.
NASA Astrophysics Data System (ADS)
Yue, Y.; Tong, X.; Wang, K.; Fensholt, R.; Brandt, M.
2017-12-01
With the aim to combat desertification and improve the ecological environment, mega-engineering afforestation projects have been launched in the karst regions of southwest China around the turn of the new millennium. A positive impact of these projects on vegetation cover has been shown, however, it remains unclear if conservation efforts have been able to effectively restore ecosystem properties and reduce the sensitivity of the karst ecosystem to climate variations at large scales. Here we use passive microwave and optical satellite time series data combined with the ecosystem model LPJ-GUESS and show widespread increase in vegetation cover with a clear demarcation at the Chinese national border contrasting the conditions of neighboring countries. We apply a breakpoint detection to identify permanent changes in vegetation time series and assess the vegetation's sensitivity against climate before and after the breakpoints. A majority (74%) of the breakpoints were detected between 2001 and 2004 and are remarkably in line with the implementation and spatial extent of the Grain to Green project. We stratify the counties of the study area into four groups according to the extent of Grain to Green conservation areas and find distinct differences between the groups. Vegetation trends are similar prior to afforestation activities (1982-2000), but clearly diverge at a later stage, following the spatial extent of conservation areas. Moreover, vegetation cover dynamics were increasingly decoupled from climatic influence in areas of high conservation efforts. Whereas both vegetation resilience and resistance were considerably improved in areas with large conservation efforts thereby showing an increase in ecosystem stability, ongoing degradation and an amplified sensitivity to climate variability was found in areas with limited project implementation. Our study concludes that large scale conservation projects can regionally contribute to a greening Earth and are able to mitigate desertification by increasing the vegetation cover and reducing the ecosystem sensitivity to climate change, however, degradation remains a serious issue in the karst ecosystem of southwest China.
PP-SWAT: A phython-based computing software for efficient multiobjective callibration of SWAT
USDA-ARS?s Scientific Manuscript database
With enhanced data availability, distributed watershed models for large areas with high spatial and temporal resolution are increasingly used to understand water budgets and examine effects of human activities and climate change/variability on water resources. Developing parallel computing software...
Region-specific patterns and drivers of macroscale forest plant invasions
Basil V. Iannone; Christopher M. Oswalt; Andrew M. Liebhold; Qinfeng Guo; Kevin M. Potter; Gabriela C. Nunez-Mir; Sonja N. Oswalt; Bryan C. Pijanowski; Songlin Fei; Bethany Bradley
2015-01-01
Aim Stronger inferences about biological invasions may be obtained when accounting for multiple invasion measures and the spatial heterogeneity occurring across large geographic areas. We pursued this enquiry by utilizing a multimeasure, multiregional framework to investigate forest plant invasions at a subcontinental scale. ...
Lake Michigan nearshore: How modeling scenarios can improve dialog between modelers and ecologists
The nearshore of Lake Michigan, similarly to the other Great Lakes, experiences environmental concerns due to excessive eutrophication. Assessing the nearshore is challenging because fluctuating nutrient loads, and ever-changing currents cause this area to exhibit large spatial a...
Neural Codes for One's Own Position and Direction in a Real-World "Vista" Environment.
Sulpizio, Valentina; Boccia, Maddalena; Guariglia, Cecilia; Galati, Gaspare
2018-01-01
Humans, like animals, rely on an accurate knowledge of one's spatial position and facing direction to keep orientated in the surrounding space. Although previous neuroimaging studies demonstrated that scene-selective regions (the parahippocampal place area or PPA, the occipital place area or OPA and the retrosplenial complex or RSC), and the hippocampus (HC) are implicated in coding position and facing direction within small-(room-sized) and large-scale navigational environments, little is known about how these regions represent these spatial quantities in a large open-field environment. Here, we used functional magnetic resonance imaging (fMRI) in humans to explore the neural codes of these navigationally-relevant information while participants viewed images which varied for position and facing direction within a familiar, real-world circular square. We observed neural adaptation for repeated directions in the HC, even if no navigational task was required. Further, we found that the amount of knowledge of the environment interacts with the PPA selectivity in encoding positions: individuals who needed more time to memorize positions in the square during a preliminary training task showed less neural attenuation in this scene-selective region. We also observed adaptation effects, which reflect the real distances between consecutive positions, in scene-selective regions but not in the HC. When examining the multi-voxel patterns of activity we observed that scene-responsive regions and the HC encoded both spatial information and that the RSC classification accuracy for positions was higher in individuals scoring higher to a self-reported questionnaire of spatial abilities. Our findings provide new insight into how the human brain represents a real, large-scale "vista" space, demonstrating the presence of neural codes for position and direction in both scene-selective and hippocampal regions, and revealing the existence, in the former regions, of a map-like spatial representation reflecting real-world distance between consecutive positions.
Saito, Masayuki; Koike, Fumito
2013-01-01
Urbanization may alter mammal assemblages via habitat loss, food subsidies, and other factors related to human activities. The general distribution patterns of wild mammal assemblages along urban–rural–forest landscape gradients have not been studied, although many studies have focused on a single species or taxon, such as rodents. We quantitatively evaluated the effects of the urban–rural–forest gradient and spatial scale on the distributions of large and mid-sized mammals in the world's largest metropolitan area in warm-temperate Asia using nonspecific camera-trapping along two linear transects spanning from the urban zone in the Tokyo metropolitan area to surrounding rural and forest landscapes. Many large and mid-sized species generally decreased from forest landscapes to urban cores, although some species preferred anthropogenic landscapes. Sika deer (Cervus nippon), Reeves' muntjac (Muntiacus reevesi), Japanese macaque (Macaca fuscata), Japanese squirrel (Sciurus lis), Japanese marten (Martes melampus), Japanese badger (Meles anakuma), and wild boar (Sus scrofa) generally dominated the mammal assemblage of the forest landscape. Raccoon (Procyon lotor), raccoon dog (Nyctereutes procyonoides), and Japanese hare (Lepus brachyurus) dominated the mammal assemblage in the intermediate zone (i.e., rural and suburban landscape). Cats (feral and free-roaming housecats; Felis catus) were common in the urban assemblage. The key spatial scales for forest species were more than 4000-m radius, indicating that conservation and management plans for these mammal assemblages should be considered on large spatial scales. However, small green spaces will also be important for mammal conservation in the urban landscape, because an indigenous omnivore (raccoon dog) had a smaller key spatial scale (500-m radius) than those of forest mammals. Urbanization was generally the most important factor in the distributions of mammals, and it is necessary to consider the spatial scale of management according to the degree of urbanization. PMID:23741495
Saito, Masayuki; Koike, Fumito
2013-01-01
Urbanization may alter mammal assemblages via habitat loss, food subsidies, and other factors related to human activities. The general distribution patterns of wild mammal assemblages along urban-rural-forest landscape gradients have not been studied, although many studies have focused on a single species or taxon, such as rodents. We quantitatively evaluated the effects of the urban-rural-forest gradient and spatial scale on the distributions of large and mid-sized mammals in the world's largest metropolitan area in warm-temperate Asia using nonspecific camera-trapping along two linear transects spanning from the urban zone in the Tokyo metropolitan area to surrounding rural and forest landscapes. Many large and mid-sized species generally decreased from forest landscapes to urban cores, although some species preferred anthropogenic landscapes. Sika deer (Cervus nippon), Reeves' muntjac (Muntiacus reevesi), Japanese macaque (Macaca fuscata), Japanese squirrel (Sciurus lis), Japanese marten (Martes melampus), Japanese badger (Meles anakuma), and wild boar (Sus scrofa) generally dominated the mammal assemblage of the forest landscape. Raccoon (Procyon lotor), raccoon dog (Nyctereutes procyonoides), and Japanese hare (Lepus brachyurus) dominated the mammal assemblage in the intermediate zone (i.e., rural and suburban landscape). Cats (feral and free-roaming housecats; Felis catus) were common in the urban assemblage. The key spatial scales for forest species were more than 4000-m radius, indicating that conservation and management plans for these mammal assemblages should be considered on large spatial scales. However, small green spaces will also be important for mammal conservation in the urban landscape, because an indigenous omnivore (raccoon dog) had a smaller key spatial scale (500-m radius) than those of forest mammals. Urbanization was generally the most important factor in the distributions of mammals, and it is necessary to consider the spatial scale of management according to the degree of urbanization.
Large-scale cortical correlation structure of spontaneous oscillatory activity
Hipp, Joerg F.; Hawellek, David J.; Corbetta, Maurizio; Siegel, Markus; Engel, Andreas K.
2013-01-01
Little is known about the brain-wide correlation of electrophysiological signals. Here we show that spontaneous oscillatory neuronal activity exhibits frequency-specific spatial correlation structure in the human brain. We developed an analysis approach that discounts spurious correlation of signal power caused by the limited spatial resolution of electrophysiological measures. We applied this approach to source estimates of spontaneous neuronal activity reconstructed from magnetoencephalography (MEG). Overall, correlation of power across cortical regions was strongest in the alpha to beta frequency range (8–32 Hz) and correlation patterns depended on the underlying oscillation frequency. Global hubs resided in the medial temporal lobe in the theta frequency range (4–6 Hz), in lateral parietal areas in the alpha to beta frequency range (8–23 Hz), and in sensorimotor areas for higher frequencies (32–45 Hz). Our data suggest that interactions in various large-scale cortical networks may be reflected in frequency specific power-envelope correlations. PMID:22561454
Ackermann, M.; Ajello, M.; Baldini, L.; ...
2017-07-10
The spatial extension of a γ-ray source is an essential ingredient to determine its spectral properties, as well as its potential multiwavelength counterpart. The capability to spatially resolve γ-ray sources is greatly improved by the newly delivered Fermi-Large Area Telescope (LAT) Pass 8 event-level analysis, which provides a greater acceptance and an improved point-spread function, two crucial factors for the detection of extended sources. Here, we present a complete search for extended sources located within 7° from the Galactic plane, using 6 yr of Fermi-LAT data above 10 GeV. We find 46 extended sources and provide their morphological and spectralmore » characteristics. As a result, this constitutes the first catalog of hard Fermi-LAT extended sources, named the Fermi Galactic Extended Source Catalog, which allows a thorough study of the properties of the Galactic plane in the sub-TeV domain.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ackermann, M.; Buehler, R.; Ajello, M.
The spatial extension of a γ -ray source is an essential ingredient to determine its spectral properties, as well as its potential multiwavelength counterpart. The capability to spatially resolve γ -ray sources is greatly improved by the newly delivered Fermi -Large Area Telescope (LAT) Pass 8 event-level analysis, which provides a greater acceptance and an improved point-spread function, two crucial factors for the detection of extended sources. Here, we present a complete search for extended sources located within 7° from the Galactic plane, using 6 yr of Fermi -LAT data above 10 GeV. We find 46 extended sources and providemore » their morphological and spectral characteristics. This constitutes the first catalog of hard Fermi -LAT extended sources, named the Fermi Galactic Extended Source Catalog, which allows a thorough study of the properties of the Galactic plane in the sub-TeV domain.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ackermann, M.; Ajello, M.; Baldini, L.
The spatial extension of a γ-ray source is an essential ingredient to determine its spectral properties, as well as its potential multiwavelength counterpart. The capability to spatially resolve γ-ray sources is greatly improved by the newly delivered Fermi-Large Area Telescope (LAT) Pass 8 event-level analysis, which provides a greater acceptance and an improved point-spread function, two crucial factors for the detection of extended sources. Here, we present a complete search for extended sources located within 7° from the Galactic plane, using 6 yr of Fermi-LAT data above 10 GeV. We find 46 extended sources and provide their morphological and spectralmore » characteristics. As a result, this constitutes the first catalog of hard Fermi-LAT extended sources, named the Fermi Galactic Extended Source Catalog, which allows a thorough study of the properties of the Galactic plane in the sub-TeV domain.« less
NASA Astrophysics Data System (ADS)
Ackermann, M.; Ajello, M.; Baldini, L.; Ballet, J.; Barbiellini, G.; Bastieri, D.; Bellazzini, R.; Bissaldi, E.; Bloom, E. D.; Bonino, R.; Bottacini, E.; Brandt, T. J.; Bregeon, J.; Bruel, P.; Buehler, R.; Cameron, R. A.; Caragiulo, M.; Caraveo, P. A.; Castro, D.; Cavazzuti, E.; Cecchi, C.; Charles, E.; Chekhtman, A.; Cheung, C. C.; Chiaro, G.; Ciprini, S.; Cohen, J. M.; Costantin, D.; Costanza, F.; Cutini, S.; D'Ammando, F.; de Palma, F.; Desiante, R.; Digel, S. W.; Di Lalla, N.; Di Mauro, M.; Di Venere, L.; Favuzzi, C.; Fegan, S. J.; Ferrara, E. C.; Franckowiak, A.; Fukazawa, Y.; Funk, S.; Fusco, P.; Gargano, F.; Gasparrini, D.; Giglietto, N.; Giordano, F.; Giroletti, M.; Green, D.; Grenier, I. A.; Grondin, M.-H.; Guillemot, L.; Guiriec, S.; Harding, A. K.; Hays, E.; Hewitt, J. W.; Horan, D.; Hou, X.; Jóhannesson, G.; Kamae, T.; Kuss, M.; La Mura, G.; Larsson, S.; Lemoine-Goumard, M.; Li, J.; Longo, F.; Loparco, F.; Lubrano, P.; Magill, J. D.; Maldera, S.; Malyshev, D.; Manfreda, A.; Mazziotta, M. N.; Michelson, P. F.; Mitthumsiri, W.; Mizuno, T.; Monzani, M. E.; Morselli, A.; Moskalenko, I. V.; Negro, M.; Nuss, E.; Ohsugi, T.; Omodei, N.; Orienti, M.; Orlando, E.; Ormes, J. F.; Paliya, V. S.; Paneque, D.; Perkins, J. S.; Persic, M.; Pesce-Rollins, M.; Petrosian, V.; Piron, F.; Porter, T. A.; Principe, G.; Rainò, S.; Rando, R.; Razzano, M.; Razzaque, S.; Reimer, A.; Reimer, O.; Reposeur, T.; Sgrò, C.; Simone, D.; Siskind, E. J.; Spada, F.; Spandre, G.; Spinelli, P.; Suson, D. J.; Tak, D.; Thayer, J. B.; Thompson, D. J.; Torres, D. F.; Tosti, G.; Troja, E.; Vianello, G.; Wood, K. S.; Wood, M.
2017-07-01
The spatial extension of a γ-ray source is an essential ingredient to determine its spectral properties, as well as its potential multiwavelength counterpart. The capability to spatially resolve γ-ray sources is greatly improved by the newly delivered Fermi-Large Area Telescope (LAT) Pass 8 event-level analysis, which provides a greater acceptance and an improved point-spread function, two crucial factors for the detection of extended sources. Here, we present a complete search for extended sources located within 7° from the Galactic plane, using 6 yr of Fermi-LAT data above 10 GeV. We find 46 extended sources and provide their morphological and spectral characteristics. This constitutes the first catalog of hard Fermi-LAT extended sources, named the Fermi Galactic Extended Source Catalog, which allows a thorough study of the properties of the Galactic plane in the sub-TeV domain.
Mapping the Spatial Distribution of CO2 release from Kīlauea Volcano, Hawaii, USA
NASA Astrophysics Data System (ADS)
Elias, T.; Werner, C. A.; Kern, C.; Sutton, A. J.; Hauri, E. H.; Kelly, P. J.
2014-12-01
Kīlauea Volcano is a large emitter of volcanic CO2 with emission rates ranging from 7500-30,000 t/d. However, Kīlauea presents a challenging situation for CO2 emission rate measurement in that the main source of SO2 is the active vent in Halema'uma'u Crater, whereas CO2 emits mainly from a large (> 1km2) diffuse region east of the vent. Previous researchers recognized this issue and advocated for the use of a plume-integrated concentration ratio paired with the SO2 emission to determine CO2 emission rates; however, this worked best prior to the opening of the summit vent in 2008, or when SO2emission was still diffuse as opposed to focused degassing from the vent. We used two techniques to study the spatial distribution and temporal variability of CO2 release from the summit caldera in July, 2014. Eddy covariance measurements made at 14 locations in the area of diffuse emission resulted in elevated fluxes that generally ranged from 500 to > 5000 g/m2d, or typical of other volcanic and hydrothermal areas worldwide. MultiGas measurements of the CO2 and SO2 concentration in air at 1-m above the ground identified approximately seven areas of elevated area of CO2 degassing in the caldera. The CO2 concentrations in air were spatially well correlated to approximately 100 m and displayed anisotropy that was consistent with the measured wind direction. Areas of highest CO2 concentration correlated with the areas of highest flux using the eddy covariance method and were found near the middle of the caldera approximately 1 km NE of the active vent. This area overlies the inferred location of the shallow summit reservoir, and is characterized by linear fractures with adhered sublimate deposits at the surface. A few of the fractures are visibly fuming, but much of the degassing in the area is not apparent. Future work includes monitoring the fluxes in this area over time, and attempting to quantify emission rates from the areas of measured flux.
NASA Astrophysics Data System (ADS)
Wang, Jun; Wang, Yang; Zeng, Hui
2016-01-01
A key issue to address in synthesizing spatial data with variable-support in spatial analysis and modeling is the change-of-support problem. We present an approach for solving the change-of-support and variable-support data fusion problems. This approach is based on geostatistical inverse modeling that explicitly accounts for differences in spatial support. The inverse model is applied here to produce both the best predictions of a target support and prediction uncertainties, based on one or more measurements, while honoring measurements. Spatial data covering large geographic areas often exhibit spatial nonstationarity and can lead to computational challenge due to the large data size. We developed a local-window geostatistical inverse modeling approach to accommodate these issues of spatial nonstationarity and alleviate computational burden. We conducted experiments using synthetic and real-world raster data. Synthetic data were generated and aggregated to multiple supports and downscaled back to the original support to analyze the accuracy of spatial predictions and the correctness of prediction uncertainties. Similar experiments were conducted for real-world raster data. Real-world data with variable-support were statistically fused to produce single-support predictions and associated uncertainties. The modeling results demonstrate that geostatistical inverse modeling can produce accurate predictions and associated prediction uncertainties. It is shown that the local-window geostatistical inverse modeling approach suggested offers a practical way to solve the well-known change-of-support problem and variable-support data fusion problem in spatial analysis and modeling.
A time series of urban extent in China using DSMP/OLS nighttime light data
Chen, Dongsheng; Chen, Le; Wang, Huan; Guan, Qingfeng
2018-01-01
Urban extent data play an important role in urban management and urban studies, such as monitoring the process of urbanization and changes in the spatial configuration of urban areas. Traditional methods of extracting urban-extent information are primarily based on manual investigations and classifications using remote sensing images, and these methods have such problems as large costs in labor and time and low precision. This study proposes an improved, simplified and flexible method for extracting urban extents over multiple scales and the construction of spatiotemporal models using DMSP/OLS nighttime light (NTL) for practical situations. This method eliminates the regional temporal and spatial inconsistency of thresholding NTL in large-scale and multi-temporal scenes. Using this method, we have extracted the urban extents and calculated the corresponding areas on the county, municipal and provincial scales in China from 2000 to 2012. In addition, validation with the data of reference data shows that the overall accuracy (OA), Kappa and F1 Scores were 0.996, 0.793, and 0.782, respectively. We increased the spatial resolution of the urban extent to 500 m (approximately four times finer than the results of previous studies). Based on the urban extent dataset proposed above, we analyzed changes in urban extents over time and observed that urban sprawl has grown in all of the counties of China. We also identified three patterns of urban sprawl: Early Urban Growth, Constant Urban Growth and Recent Urban Growth. In addition, these trends of urban sprawl are consistent with the western, eastern and central cities of China, respectively, in terms of their spatial distribution, socioeconomic characteristics and historical background. Additionally, the urban extents display the spatial configurations of urban areas intuitively. The proposed urban extent dataset is available for download and can provide reference data and support for future studies of urbanization and urban planning. PMID:29795685
Estimating of Soil Texture Using Landsat Imagery: a Case Study in Thatta Tehsil, Sindh
NASA Astrophysics Data System (ADS)
Khalil, Zahid
2016-07-01
Soil texture is considered as an important environment factor for agricultural growth. It is the most essential part for soil classification in large scale. Today the precise soil information in large scale is of great demand from various stakeholders including soil scientists, environmental managers, land use planners and traditional agricultural users. With the increasing demand of soil properties in fine scale spatial resolution made the traditional laboratory methods inadequate. In addition the costs of soil analysis with precision agriculture systems are more expensive than traditional methods. In this regard, the application of geo-spatial techniques can be used as an alternative for examining soil analysis. This study aims to examine the ability of Geo-spatial techniques in identifying the spatial patterns of soil attributes in fine scale. Around 28 samples of soil were collected from the different areas of Thatta Tehsil, Sindh, Pakistan for analyzing soil texture. An Ordinary Least Square (OLS) regression analysis was used to relate the reflectance values of Landsat8 OLI imagery with the soil variables. The analysis showed there was a significant relationship (p<0.05) of band 2 and 5 with silt% (R2 = 0.52), and band 4 and 6 with clay% (R2 =0.40). The equation derived from OLS analysis was then used for the whole study area for deriving soil attributes. The USDA textural classification triangle was implementing for the derivation of soil texture map in GIS environment. The outcome revealed that the 'sandy loam' was in great quantity followed by loam, sandy clay loam and clay loam. The outcome shows that the Geo-spatial techniques could be used efficiently for mapping soil texture of a larger area in fine scale. This technology helped in decreasing cost, time and increase detailed information by reducing field work to a considerable level.
Scales of Spatial Heterogeneity of Plastic Marine Debris in the Northeast Pacific Ocean
Goldstein, Miriam C.; Titmus, Andrew J.; Ford, Michael
2013-01-01
Plastic debris has been documented in many marine ecosystems, including remote coastlines, the water column, the deep sea, and subtropical gyres. The North Pacific Subtropical Gyre (NPSG), colloquially called the “Great Pacific Garbage Patch,” has been an area of particular scientific and public concern. However, quantitative assessments of the extent and variability of plastic in the NPSG have been limited. Here, we quantify the distribution, abundance, and size of plastic in a subset of the eastern Pacific (approximately 20–40°N, 120–155°W) over multiple spatial scales. Samples were collected in Summer 2009 using surface and subsurface plankton net tows and quantitative visual observations, and Fall 2010 using surface net tows only. We documented widespread, though spatially variable, plastic pollution in this portion of the NPSG and adjacent waters. The overall median microplastic numerical concentration in Summer 2009 was 0.448 particles m−2 and in Fall 2010 was 0.021 particles m−2, but plastic concentrations were highly variable over the submesoscale (10 s of km). Size-frequency spectra were skewed towards small particles, with the most abundant particles having a cross-sectional area of approximately 0.01 cm2. Most microplastic was found on the sea surface, with the highest densities detected in low-wind conditions. The numerical majority of objects were small particles collected with nets, but the majority of debris surface area was found in large objects assessed visually. Our ability to detect high-plastic areas varied with methodology, as stations with substantial microplastic did not necessarily also contain large visually observable objects. A power analysis of our data suggests that high variability of surface microplastic will make future changes in abundance difficult to detect without substantial sampling effort. Our findings suggest that assessment and monitoring of oceanic plastic debris must account for high spatial variability, particularly in regards to the evaluation of initiatives designed to reduce marine debris. PMID:24278233
Scales of spatial heterogeneity of plastic marine debris in the northeast pacific ocean.
Goldstein, Miriam C; Titmus, Andrew J; Ford, Michael
2013-01-01
Plastic debris has been documented in many marine ecosystems, including remote coastlines, the water column, the deep sea, and subtropical gyres. The North Pacific Subtropical Gyre (NPSG), colloquially called the "Great Pacific Garbage Patch," has been an area of particular scientific and public concern. However, quantitative assessments of the extent and variability of plastic in the NPSG have been limited. Here, we quantify the distribution, abundance, and size of plastic in a subset of the eastern Pacific (approximately 20-40°N, 120-155°W) over multiple spatial scales. Samples were collected in Summer 2009 using surface and subsurface plankton net tows and quantitative visual observations, and Fall 2010 using surface net tows only. We documented widespread, though spatially variable, plastic pollution in this portion of the NPSG and adjacent waters. The overall median microplastic numerical concentration in Summer 2009 was 0.448 particles m(-2) and in Fall 2010 was 0.021 particles m(-2), but plastic concentrations were highly variable over the submesoscale (10 s of km). Size-frequency spectra were skewed towards small particles, with the most abundant particles having a cross-sectional area of approximately 0.01 cm(2). Most microplastic was found on the sea surface, with the highest densities detected in low-wind conditions. The numerical majority of objects were small particles collected with nets, but the majority of debris surface area was found in large objects assessed visually. Our ability to detect high-plastic areas varied with methodology, as stations with substantial microplastic did not necessarily also contain large visually observable objects. A power analysis of our data suggests that high variability of surface microplastic will make future changes in abundance difficult to detect without substantial sampling effort. Our findings suggest that assessment and monitoring of oceanic plastic debris must account for high spatial variability, particularly in regards to the evaluation of initiatives designed to reduce marine debris.
Campbell, Stuart J.; Hoey, Andrew S.; Maynard, Jeffrey; Kartawijaya, Tasrif; Cinner, Joshua; Graham, Nicholas A. J.; Baird, Andrew H.
2012-01-01
The effectiveness of marine protected areas depends largely on whether people comply with the rules. We quantified temporal changes in benthic composition, reef fish biomass, and fishing effort among marine park zones (including no-take areas) to assess levels of compliance following the 2005 rezoning of the government-controlled Karimunjawa National Park (KNP), Indonesia. Four years after the rezoning awareness of fishing regulations was high amongst local fishers, ranging from 79.5±7.9 (SE) % for spatial restrictions to 97.7±1.2% for bans on the use of poisons. Despite this high awareness and strong compliance with gear restrictions, compliance with spatial restrictions was weak. In the four years following the rezoning reef fish biomass declined across all zones within KNP, with >50% reduction within the no-take Core and Protection Zones. These declines were primarily driven by decreases in the biomass of groups targeted by local fishers; planktivores, herbivores, piscivores, and invertivores. These declines in fish biomass were not driven by changes in habitat quality; coral cover increased in all zones, possibly as a result of a shift in fishing gears from those which can damage reefs (i.e., nets) to those which cause little direct damage (i.e., handlines and spears). Direct observations of fishing activities in 2009 revealed there was limited variation in fishing effort between zones in which fishing was allowed or prohibited. The apparent willingness of the KNP communities to comply with gear restrictions, but not spatial restrictions is difficult to explain and highlights the complexities of the social and economic dynamics that influence the ecological success of marine protected areas. Clearly the increased and high awareness of fishery restrictions following the rezoning is a positive step. The challenge now is to understand and foster the conditions that may facilitate compliance with spatial restrictions within KNP and marine parks worldwide. PMID:23226237
A new approach to large area microchannel plate manufacture
NASA Technical Reports Server (NTRS)
1986-01-01
Methods of manufacture of twisted single elements as the base for producing microchannel plates (MCP) are discussed. Initial evaluations validated the off-axis channel concept and no technological roadblocks were identified which would prevent fabrication of high gain, high spatial resolution, large format MCP's using this technique. The first MP's have operated at stable gains of 3 million with pulse height resolution superior to results obtained by standard chevron MCP's.
Turelli, Michael; Barton, Nicholas H
2017-06-01
A novel strategy for controlling the spread of arboviral diseases such as dengue, Zika and chikungunya is to transform mosquito populations with virus-suppressing Wolbachia. In general, Wolbachia transinfected into mosquitoes induce fitness costs through lower viability or fecundity. These maternally inherited bacteria also produce a frequency-dependent advantage for infected females by inducing cytoplasmic incompatibility (CI), which kills the embryos produced by uninfected females mated to infected males. These competing effects, a frequency-dependent advantage and frequency-independent costs, produce bistable Wolbachia frequency dynamics. Above a threshold frequency, denoted pˆ, CI drives fitness-decreasing Wolbachia transinfections through local populations; but below pˆ, infection frequencies tend to decline to zero. If pˆ is not too high, CI also drives spatial spread once infections become established over sufficiently large areas. We illustrate how simple models provide testable predictions concerning the spatial and temporal dynamics of Wolbachia introductions, focusing on rate of spatial spread, the shape of spreading waves, and the conditions for initiating spread from local introductions. First, we consider the robustness of diffusion-based predictions to incorporating two important features of wMel-Aedes aegypti biology that may be inconsistent with the diffusion approximations, namely fast local dynamics induced by complete CI (i.e., all embryos produced from incompatible crosses die) and long-tailed, non-Gaussian dispersal. With complete CI, our numerical analyses show that long-tailed dispersal changes wave-width predictions only slightly; but it can significantly reduce wave speed relative to the diffusion prediction; it also allows smaller local introductions to initiate spatial spread. Second, we use approximations for pˆ and dispersal distances to predict the outcome of 2013 releases of wMel-infected Aedes aegypti in Cairns, Australia, Third, we describe new data from Ae. aegypti populations near Cairns, Australia that demonstrate long-distance dispersal and provide an approximate lower bound on pˆ for wMel in northeastern Australia. Finally, we apply our analyses to produce operational guidelines for efficient transformation of vector populations over large areas. We demonstrate that even very slow spatial spread, on the order of 10-20 m/month (as predicted), can produce area-wide population transformation within a few years following initial releases covering about 20-30% of the target area. Copyright © 2017 Elsevier Inc. All rights reserved.
Kauhl, B; Maier, W; Schweikart, J; Keste, A; Moskwyn, M
2018-01-10
Hypertension is one of the most frequently diagnosed chronic conditions in Germany. Targeted prevention strategies and allocation of general practitioners where they are needed most are necessary to prevent severe complications arising from high blood pressure. However, data on chronic diseases in Germany are mostly available through survey data, which do not only underestimate the actual prevalence but are also only available on coarse spatial scales. The discussion of including area deprivation for planning of healthcare is still relatively young in Germany, although previous studies have shown that area deprivation is associated with adverse health outcomes, irrespective of individual characteristics. The aim of this study is therefore to analyze the spatial distribution of hypertension at very fine geographic scales and to assess location-specific associations between hypertension, socio-demographic population characteristics and area deprivation based on health insurance claims of the AOK Nordost. To visualize the spatial distribution of hypertension prevalence at very fine geographic scales, we used the conditional autoregressive Besag-York-Mollié (BYM) model. Geographically weighted regression modelling (GWR) was applied to analyze the location-specific association of hypertension to area deprivation and further socio-demographic population characteristics. The sex- and age-adjusted prevalence of hypertension was 33.1% in 2012 and varied widely across northeastern Germany. The main risk factors for hypertension were proportions of insurants aged 45-64, 65 and older, area deprivation and proportion of persons commuting to work outside their residential municipality. The GWR model revealed important regional variations in the strength of the examined associations. Area deprivation has only a significant and therefore direct influence in large parts of Mecklenburg-West Pomerania. However, the spatially varying strength of the association between demographic variables and hypertension indicates that there also exists an indirect effect of area deprivation on the prevalence of hypertension. It can therefore be expected that persons ageing in deprived areas will be at greater risk of hypertension, irrespective of their individual characteristics. The future planning and allocation of primary healthcare in northeastern Germany would therefore greatly benefit from considering the effect of area deprivation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
G. Ostrouchov; W.E.Doll; D.A.Wolf
2003-07-01
Unexploded ordnance(UXO)surveys encompass large areas, and the cost of surveying these areas can be high. Enactment of earlier protocols for sampling UXO sites have shown the shortcomings of these procedures and led to a call for development of scientifically defensible statistical procedures for survey design and analysis. This project is one of three funded by SERDP to address this need.
Winterbach, Christiaan W.; Boast, Lorraine K.; Klein, Rebecca; Somers, Michael J.
2015-01-01
Prey availability and human-carnivore conflict are strong determinants that govern the spatial distribution and abundance of large carnivore species and determine the suitability of areas for their conservation. For wide-ranging large carnivores such as cheetahs (Acinonyx jubatus), additional conservation areas beyond protected area boundaries are crucial to effectively conserve them both inside and outside protected areas. Although cheetahs prefer preying on wild prey, they also cause conflict with people by predating on especially small livestock. We investigated whether the distribution of cheetahs’ preferred prey and small livestock biomass could be used to explore the potential suitability of agricultural areas in Botswana for the long-term persistence of its cheetah population. We found it gave a good point of departure for identifying priority areas for land management, the threat to connectivity between cheetah populations, and areas where the reduction and mitigation of human-cheetah conflict is critical. Our analysis showed the existence of a wide prey base for cheetahs across large parts of Botswana’s agricultural areas, which provide additional large areas with high conservation potential. Twenty percent of wild prey biomass appears to be the critical point to distinguish between high and low probable levels of human-cheetah conflict. We identified focal areas in the agricultural zones where restoring wild prey numbers in concurrence with effective human-cheetah conflict mitigation efforts are the most immediate conservation strategies needed to maintain Botswana’s still large and contiguous cheetah population. PMID:26213646
Winterbach, Hanlie E K; Winterbach, Christiaan W; Boast, Lorraine K; Klein, Rebecca; Somers, Michael J
2015-01-01
Prey availability and human-carnivore conflict are strong determinants that govern the spatial distribution and abundance of large carnivore species and determine the suitability of areas for their conservation. For wide-ranging large carnivores such as cheetahs (Acinonyx jubatus), additional conservation areas beyond protected area boundaries are crucial to effectively conserve them both inside and outside protected areas. Although cheetahs prefer preying on wild prey, they also cause conflict with people by predating on especially small livestock. We investigated whether the distribution of cheetahs' preferred prey and small livestock biomass could be used to explore the potential suitability of agricultural areas in Botswana for the long-term persistence of its cheetah population. We found it gave a good point of departure for identifying priority areas for land management, the threat to connectivity between cheetah populations, and areas where the reduction and mitigation of human-cheetah conflict is critical. Our analysis showed the existence of a wide prey base for cheetahs across large parts of Botswana's agricultural areas, which provide additional large areas with high conservation potential. Twenty percent of wild prey biomass appears to be the critical point to distinguish between high and low probable levels of human-cheetah conflict. We identified focal areas in the agricultural zones where restoring wild prey numbers in concurrence with effective human-cheetah conflict mitigation efforts are the most immediate conservation strategies needed to maintain Botswana's still large and contiguous cheetah population.
Vulnerability of the global terrestrial ecosystems to climate change.
Li, Delong; Wu, Shuyao; Liu, Laibao; Zhang, Yatong; Li, Shuangcheng
2018-05-27
Climate change has far-reaching impacts on ecosystems. Recent attempts to quantify such impacts focus on measuring exposure to climate change but largely ignore ecosystem resistance and resilience, which may also affect the vulnerability outcomes. In this study, the relative vulnerability of global terrestrial ecosystems to short-term climate variability was assessed by simultaneously integrating exposure, sensitivity, and resilience at a high spatial resolution (0.05°). The results show that vulnerable areas are currently distributed primarily in plains. Responses to climate change vary among ecosystems and deserts and xeric shrublands are the most vulnerable biomes. Global vulnerability patterns are determined largely by exposure, while ecosystem sensitivity and resilience may exacerbate or alleviate external climate pressures at local scales; there is a highly significant negative correlation between exposure and sensitivity. Globally, 61.31% of the terrestrial vegetated area is capable of mitigating climate change impacts and those areas are concentrated in polar regions, boreal forests, tropical rainforests, and intact forests. Under current sensitivity and resilience conditions, vulnerable areas are projected to develop in high Northern Hemisphere latitudes in the future. The results suggest that integrating all three aspects of vulnerability (exposure, sensitivity, and resilience) may offer more comprehensive and spatially explicit adaptation strategies to reduce the impacts of climate change on terrestrial ecosystems. © 2018 John Wiley & Sons Ltd.
Nicol, Samuel; Roach, Jennifer K.; Griffith, Brad
2013-01-01
Over the past 50 years, the number and size of high-latitude lakes have decreased throughout many regions; however, individual lake trends have been variable in direction and magnitude. This spatial heterogeneity in lake change makes statistical detection of temporal trends challenging, particularly in small analysis areas where weak trends are difficult to separate from inter- and intra-annual variability. Factors affecting trend detection include inherent variability, trend magnitude, and sample size. In this paper, we investigated how the statistical power to detect average linear trends in lake size of 0.5, 1.0 and 2.0 %/year was affected by the size of the analysis area and the number of years of monitoring in National Wildlife Refuges in Alaska. We estimated power for large (930–4,560 sq km) study areas within refuges and for 2.6, 12.9, and 25.9 sq km cells nested within study areas over temporal extents of 4–50 years. We found that: (1) trends in study areas could be detected within 5–15 years, (2) trends smaller than 2.0 %/year would take >50 years to detect in cells within study areas, and (3) there was substantial spatial variation in the time required to detect change among cells. Power was particularly low in the smallest cells which typically had the fewest lakes. Because small but ecologically meaningful trends may take decades to detect, early establishment of long-term monitoring will enhance power to detect change. Our results have broad applicability and our method is useful for any study involving change detection among variable spatial and temporal extents.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kostova, T; Carlsen, T
2003-11-21
We present a spatially-explicit individual-based computational model of rodent dynamics, customized for the prairie vole species, M. Ochrogaster. The model is based on trophic relationships and represents important features such as territorial competition, mating behavior, density-dependent predation and dispersal out of the modeled spatial region. Vegetation growth and vole fecundity are dependent on climatic components. The results of simulations show that the model correctly predicts the overall temporal dynamics of the population density. Time-series analysis shows a very good match between the periods corresponding to the peak population density frequencies predicted by the model and the ones reported in themore » literature. The model is used to study the relation between persistence, landscape area and predation. We introduce the notions of average time to extinction (ATE) and persistence frequency to quantify persistence. While the ATE decreases with decrease of area, it is a bell-shaped function of the predation level: increasing for 'small' and decreasing for 'large' predation levels.« less
Uncovering urban human mobility from large scale taxi GPS data
NASA Astrophysics Data System (ADS)
Tang, Jinjun; Liu, Fang; Wang, Yinhai; Wang, Hua
2015-11-01
Taxi GPS trajectories data contain massive spatial and temporal information of urban human activity and mobility. Taking taxi as mobile sensors, the information derived from taxi trips benefits the city and transportation planning. The original data used in study are collected from more than 1100 taxi drivers in Harbin city. We firstly divide the city area into 400 different transportation districts and analyze the origin and destination distribution in urban area on weekday and weekend. The Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is used to cluster pick-up and drop-off locations. Furthermore, four spatial interaction models are calibrated and compared based on trajectories in shopping center of Harbin city to study the pick-up location searching behavior. By extracting taxi trips from GPS data, travel distance, time and average speed in occupied and non-occupied status are then used to investigate human mobility. Finally, we use observed OD matrix of center area in Harbin city to model the traffic distribution patterns based on entropy-maximizing method, and the estimation performance verify its effectiveness in case study.
Functional Geometry Alignment and Localization of Brain Areas.
Langs, Georg; Golland, Polina; Tie, Yanmei; Rigolo, Laura; Golby, Alexandra J
2010-01-01
Matching functional brain regions across individuals is a challenging task, largely due to the variability in their location and extent. It is particularly difficult, but highly relevant, for patients with pathologies such as brain tumors, which can cause substantial reorganization of functional systems. In such cases spatial registration based on anatomical data is only of limited value if the goal is to establish correspondences of functional areas among different individuals, or to localize potentially displaced active regions. Rather than rely on spatial alignment, we propose to perform registration in an alternative space whose geometry is governed by the functional interaction patterns in the brain. We first embed each brain into a functional map that reflects connectivity patterns during a fMRI experiment. The resulting functional maps are then registered, and the obtained correspondences are propagated back to the two brains. In application to a language fMRI experiment, our preliminary results suggest that the proposed method yields improved functional correspondences across subjects. This advantage is pronounced for subjects with tumors that affect the language areas and thus cause spatial reorganization of the functional regions.
NASA Astrophysics Data System (ADS)
Usowicz, B.; Marczewski, W.; Lipiec, J.; Usowicz, J. B.; Sokolowska, Z.; Dabkowska-Naskret, H.; Hajnos, M.; Lukowski, M. I.
2009-04-01
The purpose is obtaining trustful ground based measurement data of SM (Soil Moisture) for validating SMOS, respectively to spatial and temporal distribution and variations. A use of Time Domain Reflectometric (TDR) method is fast, simple and less destructive, to the soil matter, than a usual standard gravimetric method. TDR tools operate efficiently, enable nearly instant measurements, and allow on collecting many measurements from numerous sites, even when operated manually in short time intervals. The method enables also very frequent sampling of SM at few selected fixed sites, when long terms of temporal variations are needed. In effect one obtains reasonably large data base for determining spatial and temporal distributions of SM. The study is devoted to determining a plan on collecting TDR data, in the scales of small and large field areas, and checking their relevance to those available from gravimetric methods. Finally, the ground based SM distributions are needed for validating other SM distributions, available remotely in larger scales, from the satellite data of ENVISAT-ASAR, and from SMOS (Soil Moisture and Ocean Salinity Mission) when it becomes operational. The ground based evaluations are served mainly by geo-statistical analysis. The space borne estimations are retrieved by image processing and physical models, proper to relevant Remote Sensing (RS) instruments on the orbit. Finally, validation must engage again the geo-statistical evaluations, to assess the agreement between direct and remote sensing means, and provide a measure of trust for extending the limited scales of the ground based data, on concluding the agreement in scales proper to the satellite data. The study is focused mainly on trustful evaluating data from the ground, provided independently on satellite data sources. SM ground based data are collected permanently at 2 selected tests sites, and temporary in areas around the tests sites, in one day sessions, repeated several times per vegetation season. Permanent measurements are provided in profiles, down to 50 cm below surface. Temporary SM measurements are collected by hand held TDR (FOM/mts type, Easy Test Ltd., Lublin, Poland) from the top surface layer (1-6 cm), in a grid covering small and large areas, containing few hundred sites. The same places are served by collecting soil samples for the gravimetric analysis of SM, bulk density, other physical and textural characteristics. Sessions on measurement in large areas on the scale of community are repeated for separate days. The two methods used were compared with correlation coefficient, regression equation and differences of values. The spatial variability of soil moisture from gravimetric and TDR measurements were analyzed using geostatistical methods. The semivariogram parameters were determined and mathematical functions were fitted to empirically derived semivariograms. These functions were used for estimation of spatial distribution of soil moisture in cultivated fields by the kriging method. The results showed that spatial distribution patterns of topsoil soil moisture in the investigated areas obtained from TDR and gravimetric methods were in general similar to each other. The TDR soil moisture contents were dependent on bulk density and texture of soil. In areas with fine-textured soils of lower soil bulk densities (approximately below 1.35 Mg m^-3) we observed that TDR soil moisture and spatial differentiation were greater compared to those with gravimetric method. However at higher bulk densities the inverse was true. The spatial patterns were further modified in areas with domination of coarse-textured soils. Decrease of measurement points results in smoothing soil moisture pattern and at the same time in a greater estimation error. The TDR method can be useful tool for ground moisture measurements and validation of satellite data. The use of specific calibration or correction for soil bulk density and texture with respect to the reflectometric method is recommended. The study is a contribution to the project SWEX (AO-3275) and funded by the Polish Ministry of Science and Higher Education (in part by Grant No. N305 046 31/1707 and in part by Grant No. N305 107 32/3865).
Research of GIS-services applicability for solution of spatial analysis tasks.
NASA Astrophysics Data System (ADS)
Terekhin, D. A.; Botygin, I. A.; Sherstneva, A. I.; Sherstnev, V. S.
2017-01-01
Experiments for working out the areas of applying various gis-services in the tasks of spatial analysis are discussed in this paper. Google Maps, Yandex Maps, Microsoft SQL Server are used as services of spatial analysis. All services have shown a comparable speed of analyzing the spatial data when carrying out elemental spatial requests (building up the buffer zone of a point object) as well as the preferences of Microsoft SQL Server in operating with more complicated spatial requests. When building up elemental spatial requests, internet-services show higher efficiency due to cliental data handling with JavaScript-subprograms. A weak point of public internet-services is an impossibility to handle data on a server side and a barren variety of spatial analysis functions. Microsoft SQL Server offers a large variety of functions needed for spatial analysis on the server side. The authors conclude that when solving practical problems, the capabilities of internet-services used in building up routes and completing other functions with spatial analysis with Microsoft SQL Server should be involved.
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.
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.
de Pesters, A; Coon, W G; Brunner, P; Gunduz, A; Ritaccio, A L; Brunet, N M; de Weerd, P; Roberts, M J; Oostenveld, R; Fries, P; Schalk, G
2016-07-01
Performing different tasks, such as generating motor movements or processing sensory input, requires the recruitment of specific networks of neuronal populations. Previous studies suggested that power variations in the alpha band (8-12Hz) may implement such recruitment of task-specific populations by increasing cortical excitability in task-related areas while inhibiting population-level cortical activity in task-unrelated areas (Klimesch et al., 2007; Jensen and Mazaheri, 2010). However, the precise temporal and spatial relationships between the modulatory function implemented by alpha oscillations and population-level cortical activity remained undefined. Furthermore, while several studies suggested that alpha power indexes task-related populations across large and spatially separated cortical areas, it was largely unclear whether alpha power also differentially indexes smaller networks of task-related neuronal populations. Here we addressed these questions by investigating the temporal and spatial relationships of electrocorticographic (ECoG) power modulations in the alpha band and in the broadband gamma range (70-170Hz, indexing population-level activity) during auditory and motor tasks in five human subjects and one macaque monkey. In line with previous research, our results confirm that broadband gamma power accurately tracks task-related behavior and that alpha power decreases in task-related areas. More importantly, they demonstrate that alpha power suppression lags population-level activity in auditory areas during the auditory task, but precedes it in motor areas during the motor task. This suppression of alpha power in task-related areas was accompanied by an increase in areas not related to the task. In addition, we show for the first time that these differential modulations of alpha power could be observed not only across widely distributed systems (e.g., motor vs. auditory system), but also within the auditory system. Specifically, alpha power was suppressed in the locations within the auditory system that most robustly responded to particular sound stimuli. Altogether, our results provide experimental evidence for a mechanism that preferentially recruits task-related neuronal populations by increasing cortical excitability in task-related cortical areas and decreasing cortical excitability in task-unrelated areas. This mechanism is implemented by variations in alpha power and is common to humans and the non-human primate under study. These results contribute to an increasingly refined understanding of the mechanisms underlying the selection of the specific neuronal populations required for task execution. Copyright © 2016 Elsevier Inc. All rights reserved.
Nishiguchi, Shu; Yorozu, Ayanori; Adachi, Daiki; Takahashi, Masaki; Aoyama, Tomoki
2017-08-08
The Timed Up and Go (TUG) test may be a useful tool to detect not only mobility impairment but also possible cognitive impairment. In this cross-sectional study, we used the TUG test to investigate the associations between trajectory-based spatial parameters measured by laser range sensor (LRS) and cognitive impairment in community-dwelling older adults. The participants were 63 community-dwelling older adults (mean age, 73.0 ± 6.3 years). The trajectory-based spatial parameters during the TUG test were measured using an LRS. In each forward and backward phase, we calculated the minimum distance from the marker, the maximum distance from the x-axis (center line), the length of the trajectories, and the area of region surrounded by the trajectory of the center of gravity and the x-axis (center line). We measured mild cognitive impairment using the Mini-Mental State Examination score (26/27 was the cut-off score for defining mild cognitive impairment). Compared with participants with normal cognitive function, those with mild cognitive impairment exhibited the following trajectory-based spatial parameters: short minimum distance from the marker (p = 0.044), narrow area of center of gravity in the forward phase (p = 0.012), and a large forward/whole phase ratio of the area of the center of gravity (p = 0.026) during the TUG test. In multivariate logistic regression analyses, a short minimum distance from the marker (odds ratio [OR]: 0.82, 95% confidence interval [CI]: 0.69-0.98), narrow area of the center of gravity in the forward phase (OR: 0.01, 95% CI: 0.00-0.36), and large forward/whole phase ratio of the area of the center of gravity (OR: 0.94, 95% CI: 0.88-0.99) were independently associated with mild cognitive impairment. In conclusion, our results indicate that some of the trajectory-based spatial parameters measured by LRS during the TUG test were independently associated with cognitive impairment in older adults. In particular, older adults with cognitive impairment exhibit shorter minimum distances from the marker and asymmetrical trajectories during the TUG test.
Spatial and temporal avoidance of risk within a large carnivore guild.
Dröge, Egil; Creel, Scott; Becker, Matthew S; M'soka, Jassiel
2017-01-01
Within a large carnivore guild, subordinate competitors (African wild dog, Lycaon pictus , and cheetah, Acinonyx jubatus ) might reduce the limiting effects of dominant competitors (lion, Panthera leo , and spotted hyena, Crocuta crocuta ) by avoiding them in space, in time, or through patterns of prey selection. Understanding how these competitors cope with one other can inform strategies for their conservation. We tested how mechanisms of niche partitioning promote coexistence by quantifying patterns of prey selection and the use of space and time by all members of the large carnivore guild within Liuwa Plain National Park in western Zambia. Lions and hyenas specialized on wildebeest, whereas wild dogs and cheetahs selected broader diets including smaller and less abundant prey. Spatially, cheetahs showed no detectable avoidance of areas heavily used by dominant competitors, but wild dogs avoided areas heavily used by lions. Temporally, the proportion of kills by lions and hyenas did not detectably differ across four time periods (day, crepuscular, early night, and late night), but wild dogs and especially cheetahs concentrated on time windows that avoided nighttime hunting by lions and hyenas. Our results provide new insight into the conditions under which partitioning may not allow for coexistence for one subordinate species, the African wild dog, while it does for cheetah. Because of differences in responses to dominant competitors, African wild dogs may be more prone to competitive exclusion (local extirpation), particularly in open, uniform ecosystems with simple (often wildebeest dominated) prey communities, where spatial avoidance is difficult.
Large-scale derived flood frequency analysis based on continuous simulation
NASA Astrophysics Data System (ADS)
Dung Nguyen, Viet; Hundecha, Yeshewatesfa; Guse, Björn; Vorogushyn, Sergiy; Merz, Bruno
2016-04-01
There is an increasing need for spatially consistent flood risk assessments at the regional scale (several 100.000 km2), in particular in the insurance industry and for national risk reduction strategies. However, most large-scale flood risk assessments are composed of smaller-scale assessments and show spatial inconsistencies. To overcome this deficit, a large-scale flood model composed of a weather generator and catchments models was developed reflecting the spatially inherent heterogeneity. The weather generator is a multisite and multivariate stochastic model capable of generating synthetic meteorological fields (precipitation, temperature, etc.) at daily resolution for the regional scale. These fields respect the observed autocorrelation, spatial correlation and co-variance between the variables. They are used as input into catchment models. A long-term simulation of this combined system enables to derive very long discharge series at many catchment locations serving as a basic for spatially consistent flood risk estimates at the regional scale. This combined model was set up and validated for major river catchments in Germany. The weather generator was trained by 53-year observation data at 528 stations covering not only the complete Germany but also parts of France, Switzerland, Czech Republic and Australia with the aggregated spatial scale of 443,931 km2. 10.000 years of daily meteorological fields for the study area were generated. Likewise, rainfall-runoff simulations with SWIM were performed for the entire Elbe, Rhine, Weser, Donau and Ems catchments. The validation results illustrate a good performance of the combined system, as the simulated flood magnitudes and frequencies agree well with the observed flood data. Based on continuous simulation this model chain is then used to estimate flood quantiles for the whole Germany including upstream headwater catchments in neighbouring countries. This continuous large scale approach overcomes the several drawbacks reported in traditional approaches for the derived flood frequency analysis and therefore is recommended for large scale flood risk case studies.
Grosse, Guido; Robinson, Joel E.; Bryant, Robin; Taylor, Maxwell D.; Harper, William; DeMasi, Amy; Kyker-Snowman, Emily; Veremeeva, Alexandra; Schirrmeister, Lutz; Harden, Jennifer
2013-01-01
This digital database is the product of collaboration between the U.S. Geological Survey, the Geophysical Institute at the University of Alaska, Fairbanks; the Los Altos Hills Foothill College GeoSpatial Technology Certificate Program; the Alfred Wegener Institute for Polar and Marine Research, Potsdam, Germany; and the Institute of Physical Chemical and Biological Problems in Soil Science of the Russian Academy of Sciences. The primary goal for creating this digital database is to enhance current estimates of soil organic carbon stored in deep permafrost, in particular the late Pleistocene syngenetic ice-rich permafrost deposits of the Yedoma Suite. Previous studies estimated that Yedoma deposits cover about 1 million square kilometers of a large region in central and eastern Siberia, but these estimates generally are based on maps with scales smaller than 1:10,000,000. Taking into account this large area, it was estimated that Yedoma may store as much as 500 petagrams of soil organic carbon, a large part of which is vulnerable to thaw and mobilization from thermokarst and erosion. To refine assessments of the spatial distribution of Yedoma deposits, we digitized 11 Russian Quaternary geologic maps. Our study focused on extracting geologic units interpreted by us as late Pleistocene ice-rich syngenetic Yedoma deposits based on lithology, ground ice conditions, stratigraphy, and geomorphological and spatial association. These Yedoma units then were merged into a single data layer across map tiles. The spatial database provides a useful update of the spatial distribution of this deposit for an approximately 2.32 million square kilometers land area in Siberia that will (1) serve as a core database for future refinements of Yedoma distribution in additional regions, and (2) provide a starting point to revise the size of deep but thaw-vulnerable permafrost carbon pools in the Arctic based on surface geology and the distribution of cryolithofacies types at high spatial resolution. However, we recognize that the extent of Yedoma deposits presented in this database is not complete for a global assessment, because Yedoma deposits also occur in the Taymyr lowlands and Chukotka, and in parts of Alaska and northwestern Canada.
NASA Astrophysics Data System (ADS)
Marshall, Hans-Peter
The distribution of water in the snow-covered areas of the world is an important climate change indicator, and it is a vital component of the water cycle. At local and regional scales, the snow water equivalent (SWE), the amount of liquid water a given area of the snowpack represents, is very important for water resource management, flood forecasting, and prediction of available hydropower energy. Measurements from only a few automatic weather stations, such as the SNOTEL network, or sparse manual snowpack measurements are typically extrapolated for estimating SWE over an entire basin. Widespread spatial variability in the distribution of SWE and snowpack stratigraphy at local scales causes large errors in these basin estimates. Remote sensing measurements offer a promising alternative, due to their large spatial coverage and high temporal resolution. Although snow cover extent can currently be estimated from remote sensing data, accurately quantifying SWE from remote sensing measurements has remained difficult, due to a high sensitivity to variations in grain size and stratigraphy. In alpine snowpacks, the large degree of spatial variability of snowpack properties and geometry, caused by topographic, vegetative, and microclimatic effects, also makes prediction of snow avalanches very difficult. Ground-based radar and penetrometer measurements can quickly and accurately characterize snowpack properties and SWE in the field. A portable lightweight radar was developed, and allows a real-time estimate of SWE to within 10%, as well as measurements of depths of all major density transitions within the snowpack. New analysis techniques developed in this thesis allow accurate estimates of mechanical properties and an index of grain size to be retrieved from the SnowMicroPenetrometer. These two tools together allow rapid characterization of the snowpack's geometry, mechanical properties, and SWE, and are used to guide a finite element model to study the stress distribution on a slope. The ability to accurately characterize snowpack properties at much higher resolutions and spatial extent than previously possible will hopefully help lead to a more complete understanding of spatial variability, its effect on remote sensing measurements and snow slope stability, and result in improvements in avalanche prediction and accuracy of SWE estimates from space.
Spatially tuned normalization explains attention modulation variance within neurons.
Ni, Amy M; Maunsell, John H R
2017-09-01
Spatial attention improves perception of attended parts of a scene, a behavioral enhancement accompanied by modulations of neuronal firing rates. These modulations vary in size across neurons in the same brain area. Models of normalization explain much of this variance in attention modulation with differences in tuned normalization across neurons (Lee J, Maunsell JHR. PLoS One 4: e4651, 2009; Ni AM, Ray S, Maunsell JHR. Neuron 73: 803-813, 2012). However, recent studies suggest that normalization tuning varies with spatial location both across and within neurons (Ruff DA, Alberts JJ, Cohen MR. J Neurophysiol 116: 1375-1386, 2016; Verhoef BE, Maunsell JHR. eLife 5: e17256, 2016). Here we show directly that attention modulation and normalization tuning do in fact covary within individual neurons, in addition to across neurons as previously demonstrated. We recorded the activity of isolated neurons in the middle temporal area of two rhesus monkeys as they performed a change-detection task that controlled the focus of spatial attention. Using the same two drifting Gabor stimuli and the same two receptive field locations for each neuron, we found that switching which stimulus was presented at which location affected both attention modulation and normalization in a correlated way within neurons. We present an equal-maximum-suppression spatially tuned normalization model that explains this covariance both across and within neurons: each stimulus generates equally strong suppression of its own excitatory drive, but its suppression of distant stimuli is typically less. This new model specifies how the tuned normalization associated with each stimulus location varies across space both within and across neurons, changing our understanding of the normalization mechanism and how attention modulations depend on this mechanism. NEW & NOTEWORTHY Tuned normalization studies have demonstrated that the variance in attention modulation size seen across neurons from the same cortical area can be largely explained by between-neuron differences in normalization strength. Here we demonstrate that attention modulation size varies within neurons as well and that this variance is largely explained by within-neuron differences in normalization strength. We provide a new spatially tuned normalization model that explains this broad range of observed normalization and attention effects. Copyright © 2017 the American Physiological Society.
Illumination design for semiconductor backlight inspection and application extensions
NASA Astrophysics Data System (ADS)
Zhou, Wei; Rutherford, Todd; Hart, Darcy
2013-09-01
High speed strobe based illumination scheme is one of the most critical factors for high throughput semiconductor defect inspection applications. HB LEDs are always the first and best options for such applications due to numerous unique advantages such as excellent spatial and temporal stability, fast responding time, large and linear intensity dynamic range and no heat issue for the extremely low duty cycle applications. For some applications where a large area is required to be illuminated simultaneously, it remains a great challenge to efficiently package a large amount of HB-LEDs in a highly confined 3D space, to generate a seamless illuminated area with high luminance efficiency and spatial uniformity. A novel 3D structured collimation lens is presented in this paper. The non-circular edge shape reduces the intensity drop at the channel boundaries, while the secondary curvatures on the top of the collimator lens efficiently guides the light into desired angular space. The number of the edges and the radius of the top surface curvature are control parameters for the system level performance and the manufacture cost trade-off. The proposed 3D structured LED collimation lens also maintains the benefits of traditional LED collimation lens such as coupling efficiency and mold manufacture capability. The applications can be extended into other non-illumination area like parallelism measurement and solar panel concentrator etc.
The Use of Electromagnetic Induction Techniques for Soil Mapping
NASA Astrophysics Data System (ADS)
Brevik, Eric C.; Doolittle, Jim
2015-04-01
Soils have high natural spatial variability. This has been recognized for a long time, and many methods of mapping that spatial variability have been investigated. One technique that has received considerable attention over the last ~30 years is electromagnetic induction (EMI). Particularly when coupled with modern GPS and GIS systems, EMI techniques have allowed the rapid and relatively inexpensive collection of large spatially-related data sets that can be correlated to soil properties that either directly or indirectly influence electrical conductance in the soil. Soil electrical conductivity is directly controlled by soil water content, soluble salt content, clay content and mineralogy, and temperature. A wide range of indirect controls have been identified, such as soil organic matter content and bulk density; both influence water relationships in the soil. EMI techniques work best in areas where there are large changes in one soil property that influences soil electrical conductance, and don't work as well when soil properties that influence electrical conductance are largely homogenous. This presentation will present examples of situations where EMI techniques were successful as well as a couple of examples of situations where EMI was not so useful in mapping the spatial variability of soil properties. Reasons for both the successes and failures will be discussed.
Estimating occupancy probability of moose using hunter survey data
Crum, Nathan J.; Fuller, Angela K.; Sutherland, Christopher S.; Cooch, Evan G.; Hurst, Jeremy E.
2017-01-01
Monitoring rare species can be difficult, especially across large spatial extents, making conventional methods of population monitoring costly and logistically challenging. Citizen science has the potential to produce observational data across large areas that can be used to monitor wildlife distributions using occupancy models. We used citizen science (i.e., hunter surveys) to facilitate monitoring of moose (Alces alces) populations, an especially important endeavor because of their recent apparent declines in the northeastern and upper midwestern regions of the United States. To better understand patterns of occurrence of moose in New York, we used data collected through an annual survey of approximately 11,000 hunters between 2012 and 2014 that recorded detection–non-detection data of moose and other species. We estimated patterns of occurrence of moose in relation to land cover characteristics, climate effects, and interspecific interactions using occupancy models to analyze spatially referenced moose observations. Coniferous and deciduous forest with low prevalence of white-tailed deer (Odocoileus virginianus) had the highest probability of moose occurrence. This study highlights the potential of data collected using citizen science for understanding the spatial distribution of low-density species across large spatial extents and providing key information regarding where and when future research and management activities should be focused.
Design Issues in Small-Area Studies of Environment and Health
Elliott, Paul; Savitz, David A.
2008-01-01
Background Small-area studies are part of the tradition of spatial epidemiology, which is concerned with the analysis of geographic patterns of disease with respect to environmental, demographic, socioeconomic, and other factors. We focus on etiologic research, where the aim is to make inferences about spatially varying environmental factors influencing the risk of disease. Methods and results We illustrate the approach through three exemplars: a) magnetic fields from overhead electric power lines and the occurrence of childhood leukemia, which illustrates the use of geographic information systems to focus on areas with high exposure prevalence; b) drinking-water disinfection by-products and reproductive outcomes, taking advantage of large between- to within-area variability in exposures from the water supply; and c) chronic exposure to air pollutants and cardiorespiratory health, where issues of socioeconomic confounding are particularly important. Discussion The small-area epidemiologic approach assigns exposure estimates to individuals based on location of residence or other geographic variables such as workplace or school. In this way, large populations can be studied, increasing the ability to investigate rare exposures or rare diseases. The approach is most effective when there is well-defined exposure variation across geographic units, limited within-area variation, and good control for potential confounding across areas. Conclusions In conjunction with traditional individual-based approaches, small-area studies offer a valuable addition to the armamentarium of the environmental epidemiologist. Modeling of exposure patterns coupled with collection of individual-level data on subsamples of the population should lead to improved risk estimates (i.e., less potential for bias) and help strengthen etiologic inference. PMID:18709174
2017-01-01
The magnitude of diffusive carbon dioxide (CO2) and methane (CH4) emission from man-made reservoirs is uncertain because the spatial variability generally is not well-represented. Here, we examine the spatial variability and its drivers for partial pressure, gas-exchange velocity (k), and diffusive flux of CO2 and CH4 in three tropical reservoirs using spatially resolved measurements of both gas concentrations and k. We observed high spatial variability in CO2 and CH4 concentrations and flux within all three reservoirs, with river inflow areas generally displaying elevated CH4 concentrations. Conversely, areas close to the dam are generally characterized by low concentrations and are therefore not likely to be representative for the whole system. A large share (44–83%) of the within-reservoir variability of gas concentration was explained by dissolved oxygen, pH, chlorophyll, water depth, and within-reservoir location. High spatial variability in k was observed, and kCH4 was persistently higher (on average, 2.5 times more) than kCO2. Not accounting for the within-reservoir variability in concentrations and k may lead to up to 80% underestimation of whole-system diffusive emission of CO2 and CH4. Our findings provide valuable information on how to develop field-sampling strategies to reliably capture the spatial heterogeneity of diffusive carbon fluxes from reservoirs. PMID:29257874
It is currently possible to measure landscape change over large areas and determine trends in ecological and hydrological condition using advanced space-based technologies accompanied by geospatial data. Specifically, this process is being tested in a community-based watershed in...
THE SAN PEDRO SPATIAL DATA ARCHIVE, A DATABASE BROWSER FOR COMMUNITY-BASED ENVIRONMENTAL PROTECTION
It is currently possible to measure landscape change over large areas and determine trends in ecological and hydrological condition using advanced space-based technologies accompanied by geospatial data. Specifically, this process is being tested in a community-based watershed in...
Data regarding grazing utilization in the western United States are typically compiled within administrative boundaries(e.g. allotment,pasture). For large areas, an assumption of uniform distribution is seldom valid. Previous studies show that vegetation type, degree of slope, an...
Investigation of the near subsurface using acoustic to seismic coupling
USDA-ARS?s Scientific Manuscript database
Agricultural, hydrological and civil engineering applications have realized a need for information of the near subsurface over large areas. In order to obtain this spatially distributed data over such scales, the measurement technique must be highly mobile with a short acquisition time. Therefore, s...
Two-stage cluster sampling reduces the cost of collecting accuracy assessment reference data by constraining sample elements to fall within a limited number of geographic domains (clusters). However, because classification error is typically positively spatially correlated, withi...
the System Modeling & Geospatial Data Science Group in the Strategic Energy Analysis Center. Areas Publications Oliveira, R and Moreno, R. 2016. Harvesting, Integrating and Distributing Large Open Geospatial Datasets Using Free and Open-Source Software. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7
Pedersen, Marie; Siroux, Valérie; Pin, Isabelle; Charles, Marie Aline; Forhan, Anne; Hulin, Agnés; Galineau, Julien; Lepeule, Johanna; Giorgis-Allemand, Lise; Sunyer, Jordi; Annesi-Maesano, Isabella; Slama, Rémy
2013-10-01
Spatially-resolved air pollution models can be developed in large areas. The resulting increased exposure contrasts and population size offer opportunities to better characterize the effect of atmospheric pollutants on respiratory health. However the heterogeneity of these areas may also enhance the potential for confounding. We aimed to discuss some analytical approaches to handle this trade-off. We modeled NO2 and PM10 concentrations at the home addresses of 1082 pregnant mothers from EDEN cohort living in and around urban areas, using ADMS dispersion model. Simulations were performed to identify the best strategy to limit confounding by unmeasured factors varying with area type. We examined the relation between modeled concentrations and respiratory health in infants using regression models with and without adjustment or interaction terms with area type. Simulations indicated that adjustment for area limited the bias due to unmeasured confounders varying with area at the costs of a slight decrease in statistical power. In our cohort, rural and urban areas differed for air pollution levels and for many factors associated with respiratory health and exposure. Area tended to modify effect measures of air pollution on respiratory health. Increasing the size of the study area also increases the potential for residual confounding. Our simulations suggest that adjusting for type of area is a good option to limit residual confounding due to area-associated factors without restricting the area size. Other statistical approaches developed in the field of spatial epidemiology are an alternative to control for poorly-measured spatially-varying confounders. © 2013 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Schneider, C. A.; Aggett, G. R.; Hattendorf, M. J.
2007-12-01
Better information on evapotranspiration (ET) is essential to better understanding of consumptive use of water by crops. RTi is using NASA Earth-sun System research results and METRIC (Mapping ET at high Resolution with Internalized Calibration) to increase the repeatability and accuracy of consumptive use estimates. METRIC, an image-processing model for calculating ET as a residual of the surface energy balance, utilizes the thermal band on various satellite remote sensors. Calculating actual ET from satellites can avoid many of the assumptions driving other methods of calculating ET over a large area. Because it is physically based and does not rely on explicit knowledge of crop type in the field, a large potential source of error should be eliminated. This paper assesses sources of error in current operational estimates of ET for an area of the South Platte irrigated lands of Colorado, and benchmarks potential improvements in the accuracy of ET estimates gained using METRIC, as well as the processing efficiency of consumptive use demand for large irrigated lands. Examples highlighting how better water planning decisions and water management can be achieved via enhanced monitoring of the temporal and spatial relationships between water demand and water availability are provided.
The role of spatial organization in preference for color pairs.
Schloss, Karen B; Palmer, Stephen E
2011-01-01
We investigated how spatial organization influences color-pair preference asymmetries: differential preference for one color pair over another when the pairs contain the same colors in opposite spatial configurations. Schloss and Palmer (2011, Attention, Perception, & Psychophysics 73 55-571) found weak figure ground preference asymmetries for small squares centered on large squares in aesthetic ratings. Here, we found robust preference asymmetries using a more sensitive forced-choice task: participants strongly prefer pairs with yellower, lighter figures on bluer, darker grounds (experiment 1). We also investigated which spatial factors influence these preference asymmetries. Relative area of the two component regions is clearly important, and perceived 3-D area of the 2-D displays (ie after the ground is amodally completed behind the figure) is more influential than 2-D area (experiment 2). Surroundedness is not required, because yellowness blueness effects were comparable for pairs in which the figure was surrounded by the ground, and for mosaic arrangements in which the regions were adjacent and separated by a gap (experiment 3). Lightness darkness effects, however, were opposite for figure ground versus mosaic organizations: people prefer figure-ground organizations in which smaller regions are lighter, but prefer mosaic organizations in which smaller regions are darker. Physiological, phenomenological, and ecological explanations of the reported results are discussed.
Spatial variation in coral reef fish and benthic communities in the central Saudi Arabian Red Sea.
Khalil, Maha T; Bouwmeester, Jessica; Berumen, Michael L
2017-01-01
Local-scale ecological information is critical as a sound basis for spatial management and conservation and as support for ongoing research in relatively unstudied areas. We conducted visual surveys of fish and benthic communities on nine reefs (3-24 km from shore) in the Thuwal area of the central Saudi Arabian Red Sea. Fish biomass increased with increasing distance from shore, but was generally low compared to reefs experiencing minimal human influence around the world. All reefs had a herbivore-dominated trophic structure and few top predators, such as sharks, jacks, or large groupers. Coral cover was considerably lower on inshore reefs, likely due to a 2010 bleaching event. Community analyses showed inshore reefs to be characterized by turf algae, slower-growing corals, lower herbivore diversity, and highly abundant turf-farming damselfishes. Offshore reefs had more planktivorous fishes, a more diverse herbivore assemblage, and faster-growing corals . All reefs appear to be impacted by overfishing, and inshore reefs seem more vulnerable to thermal bleaching. The study provides a description of the spatial variation in biomass and community structure in the central Saudi Arabian Red Sea and provides a basis for spatial prioritization and subsequent marine protected area design in Thuwal.
Scale dependence of the diversity–stability relationship in a temperate grassland
Zhang, Yunhai; He, Nianpeng; Loreau, Michel; Pan, Qingmin; Han, Xingguo
2018-01-01
A positive relationship between biodiversity and ecosystem stability has been reported in many ecosystems; however, it has yet to be determined whether and how spatial scale affects this relationship. Here, for the first time, we assessed the effects of alpha, beta and gamma diversity on ecosystem stability and the scale dependence of the slope of the diversity–stability relationship.By employing a long-term (33 years) dataset from a temperate grassland, northern China, we calculated the all possible spatial scales with the complete combination from the basic 1-m2 plots.Species richness was positively associated with ecosystem stability through species asynchrony and overyielding at all spatial scales (1, 2, 3, 4 and 5 m2). Both alpha and beta diversity were positively associated with gamma stability.Moreover, the slope of the diversity–area relationship was significantly higher than that of the stability–area relationship, resulting in a decline of the slope of the diversity–stability relationship with increasing area.Synthesis. With the positive species diversity effect on ecosystem stability from small to large spatial scales, our findings demonstrate the need to maintain a high biodiversity and biotic heterogeneity as insurance against the risks incurred by ecosystems in the face of global environmental changes. PMID:29725139
Jian, Wenjuan; Chen, Minyou; McFarland, Dennis J
2017-11-01
Phase-locking value (PLV) is a potentially useful feature in sensorimotor rhythm-based brain-computer interface (BCI). However, volume conduction may cause spurious zero-phase coupling between two EEG signals and it is not clear whether PLV effects are independent of spectral amplitude. Volume conduction might be reduced by spatial filtering, but it is uncertain what impact this might have on PLV. Therefore, the goal of this study was to explore whether zero-phase PLV is meaningful and how it is affected by spatial filtering. Both amplitude and PLV feature were extracted in the frequency band of 10-15 Hz by classical methods using archival EEG data of 18 subjects trained on a two-target BCI task. The results show that with right ear-referenced data, there is meaningful long-range zero-phase synchronization likely involving the primary motor area and the supplementary motor area that cannot be explained by volume conduction. Another novel finding is that the large Laplacian spatial filter enhances the amplitude feature but eliminates most of the phase information seen in ear-referenced data. A bipolar channel using phase-coupled areas also includes both phase and amplitude information and has a significant practical advantage since fewer channels required.
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
Spatial variation in coral reef fish and benthic communities in the central Saudi Arabian Red Sea
Bouwmeester, Jessica; Berumen, Michael L.
2017-01-01
Local-scale ecological information is critical as a sound basis for spatial management and conservation and as support for ongoing research in relatively unstudied areas. We conducted visual surveys of fish and benthic communities on nine reefs (3–24 km from shore) in the Thuwal area of the central Saudi Arabian Red Sea. Fish biomass increased with increasing distance from shore, but was generally low compared to reefs experiencing minimal human influence around the world. All reefs had a herbivore-dominated trophic structure and few top predators, such as sharks, jacks, or large groupers. Coral cover was considerably lower on inshore reefs, likely due to a 2010 bleaching event. Community analyses showed inshore reefs to be characterized by turf algae, slower-growing corals, lower herbivore diversity, and highly abundant turf-farming damselfishes. Offshore reefs had more planktivorous fishes, a more diverse herbivore assemblage, and faster-growing corals. All reefs appear to be impacted by overfishing, and inshore reefs seem more vulnerable to thermal bleaching. The study provides a description of the spatial variation in biomass and community structure in the central Saudi Arabian Red Sea and provides a basis for spatial prioritization and subsequent marine protected area design in Thuwal. PMID:28603671
Species Distribution Modelling: Contrasting presence-only models with plot abundance data.
Gomes, Vitor H F; IJff, Stéphanie D; Raes, Niels; Amaral, Iêda Leão; Salomão, Rafael P; de Souza Coelho, Luiz; de Almeida Matos, Francisca Dionízia; Castilho, Carolina V; de Andrade Lima Filho, Diogenes; López, Dairon Cárdenas; Guevara, Juan Ernesto; Magnusson, William E; Phillips, Oliver L; Wittmann, Florian; de Jesus Veiga Carim, Marcelo; Martins, Maria Pires; Irume, Mariana Victória; Sabatier, Daniel; Molino, Jean-François; Bánki, Olaf S; da Silva Guimarães, José Renan; Pitman, Nigel C A; Piedade, Maria Teresa Fernandez; Mendoza, Abel Monteagudo; Luize, Bruno Garcia; Venticinque, Eduardo Martins; de Leão Novo, Evlyn Márcia Moraes; Vargas, Percy Núñez; Silva, Thiago Sanna Freire; Manzatto, Angelo Gilberto; Terborgh, John; Reis, Neidiane Farias Costa; Montero, Juan Carlos; Casula, Katia Regina; Marimon, Beatriz S; Marimon, Ben-Hur; Coronado, Euridice N Honorio; Feldpausch, Ted R; Duque, Alvaro; Zartman, Charles Eugene; Arboleda, Nicolás Castaño; Killeen, Timothy J; Mostacedo, Bonifacio; Vasquez, Rodolfo; Schöngart, Jochen; Assis, Rafael L; Medeiros, Marcelo Brilhante; Simon, Marcelo Fragomeni; Andrade, Ana; Laurance, William F; Camargo, José Luís; Demarchi, Layon O; Laurance, Susan G W; de Sousa Farias, Emanuelle; Nascimento, Henrique Eduardo Mendonça; Revilla, Juan David Cardenas; Quaresma, Adriano; Costa, Flavia R C; Vieira, Ima Célia Guimarães; Cintra, Bruno Barçante Ladvocat; Castellanos, Hernán; Brienen, Roel; Stevenson, Pablo R; Feitosa, Yuri; Duivenvoorden, Joost F; Aymard C, Gerardo A; Mogollón, Hugo F; Targhetta, Natalia; Comiskey, James A; Vicentini, Alberto; Lopes, Aline; Damasco, Gabriel; Dávila, Nállarett; García-Villacorta, Roosevelt; Levis, Carolina; Schietti, Juliana; Souza, Priscila; Emilio, Thaise; Alonso, Alfonso; Neill, David; Dallmeier, Francisco; Ferreira, Leandro Valle; Araujo-Murakami, Alejandro; Praia, Daniel; do Amaral, Dário Dantas; Carvalho, Fernanda Antunes; de Souza, Fernanda Coelho; Feeley, Kenneth; Arroyo, Luzmila; Pansonato, Marcelo Petratti; Gribel, Rogerio; Villa, Boris; Licona, Juan Carlos; Fine, Paul V A; Cerón, Carlos; Baraloto, Chris; Jimenez, Eliana M; Stropp, Juliana; Engel, Julien; Silveira, Marcos; Mora, Maria Cristina Peñuela; Petronelli, Pascal; Maas, Paul; Thomas-Caesar, Raquel; Henkel, Terry W; Daly, Doug; Paredes, Marcos Ríos; Baker, Tim R; Fuentes, Alfredo; Peres, Carlos A; Chave, Jerome; Pena, Jose Luis Marcelo; Dexter, Kyle G; Silman, Miles R; Jørgensen, Peter Møller; Pennington, Toby; Di Fiore, Anthony; Valverde, Fernando Cornejo; Phillips, Juan Fernando; Rivas-Torres, Gonzalo; von Hildebrand, Patricio; van Andel, Tinde R; Ruschel, Ademir R; Prieto, Adriana; Rudas, Agustín; Hoffman, Bruce; Vela, César I A; Barbosa, Edelcilio Marques; Zent, Egleé L; Gonzales, George Pepe Gallardo; Doza, Hilda Paulette Dávila; de Andrade Miranda, Ires Paula; Guillaumet, Jean-Louis; Pinto, Linder Felipe Mozombite; de Matos Bonates, Luiz Carlos; Silva, Natalino; Gómez, Ricardo Zárate; Zent, Stanford; Gonzales, Therany; Vos, Vincent A; Malhi, Yadvinder; Oliveira, Alexandre A; Cano, Angela; Albuquerque, Bianca Weiss; Vriesendorp, Corine; Correa, Diego Felipe; Torre, Emilio Vilanova; van der Heijden, Geertje; Ramirez-Angulo, Hirma; Ramos, José Ferreira; Young, Kenneth R; Rocha, Maira; Nascimento, Marcelo Trindade; Medina, Maria Natalia Umaña; Tirado, Milton; Wang, Ophelia; Sierra, Rodrigo; Torres-Lezama, Armando; Mendoza, Casimiro; Ferreira, Cid; Baider, Cláudia; Villarroel, Daniel; Balslev, Henrik; Mesones, Italo; Giraldo, Ligia Estela Urrego; Casas, Luisa Fernanda; Reategui, Manuel Augusto Ahuite; Linares-Palomino, Reynaldo; Zagt, Roderick; Cárdenas, Sasha; Farfan-Rios, William; Sampaio, Adeilza Felipe; Pauletto, Daniela; Sandoval, Elvis H Valderrama; Arevalo, Freddy Ramirez; Huamantupa-Chuquimaco, Isau; Garcia-Cabrera, Karina; Hernandez, Lionel; Gamarra, Luis Valenzuela; Alexiades, Miguel N; Pansini, Susamar; Cuenca, Walter Palacios; Milliken, William; Ricardo, Joana; Lopez-Gonzalez, Gabriela; Pos, Edwin; Ter Steege, Hans
2018-01-17
Species distribution models (SDMs) are widely used in ecology and conservation. Presence-only SDMs such as MaxEnt frequently use natural history collections (NHCs) as occurrence data, given their huge numbers and accessibility. NHCs are often spatially biased which may generate inaccuracies in SDMs. Here, we test how the distribution of NHCs and MaxEnt predictions relates to a spatial abundance model, based on a large plot dataset for Amazonian tree species, using inverse distance weighting (IDW). We also propose a new pipeline to deal with inconsistencies in NHCs and to limit the area of occupancy of the species. We found a significant but weak positive relationship between the distribution of NHCs and IDW for 66% of the species. The relationship between SDMs and IDW was also significant but weakly positive for 95% of the species, and sensitivity for both analyses was high. Furthermore, the pipeline removed half of the NHCs records. Presence-only SDM applications should consider this limitation, especially for large biodiversity assessments projects, when they are automatically generated without subsequent checking. Our pipeline provides a conservative estimate of a species' area of occupancy, within an area slightly larger than its extent of occurrence, compatible to e.g. IUCN red list assessments.
Finding Food Deserts: A Comparison of Methods Measuring Spatial Access to Food Stores.
Jaskiewicz, Lara; Block, Daniel; Chavez, Noel
2016-05-01
Public health research has increasingly focused on how access to resources affects health behaviors. Mapping environmental factors, such as distance to a supermarket, can identify intervention points toward improving food access in low-income and minority communities. However, the existing literature provides little guidance on choosing the most appropriate measures of spatial access. This study compared the results of different measures of spatial access to large food stores and the locations of high and low access identified by each. The data set included U.S. Census population data and the locations of large food stores in the six-county area around Chicago, Illinois. Six measures of spatial access were calculated at the census block group level and the results compared. The analysis found that there was little agreement in the identified locations of high or low access between measures. This study illustrates the importance of considering the access measure used when conducting research, interpreting results, or comparing studies. Future research should explore the correlation of different measures with health behaviors and health outcomes. © 2015 Society for Public Health Education.
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
Ghosh, Subimal; Vittal, H.; Sharma, Tarul; Karmakar, Subhankar; Kasiviswanathan, K. S.; Dhanesh, Y.; Sudheer, K. P.; Gunthe, S. S.
2016-01-01
India’s agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC) model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins. PMID:27463092
Ghosh, Subimal; Vittal, H; Sharma, Tarul; Karmakar, Subhankar; Kasiviswanathan, K S; Dhanesh, Y; Sudheer, K P; Gunthe, S S
2016-01-01
India's agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC) model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins.
Groundwater level responses to precipitation variability in Mediterranean insular aquifers
NASA Astrophysics Data System (ADS)
Lorenzo-Lacruz, Jorge; Garcia, Celso; Morán-Tejeda, Enrique
2017-09-01
Groundwater is one of the largest and most important sources of fresh water on many regions under Mediterranean climate conditions, which are exposed to large precipitation variability that includes frequent meteorological drought episodes, and present high evapotranspiration rates and water demand during the dry season. The dependence on groundwater increases in those areas with predominant permeable lithologies, contributing to aquifer recharge and the abundance of ephemeral streams. The increasing pressure of tourism on water resources in many Mediterranean coastal areas, and uncertainty related to future precipitation and water availability, make it urgent to understand the spatio-temporal response of groundwater bodies to precipitation variability, if sustainable use of the resource is to be achieved. We present an assessment of the response of aquifers to precipitation variability based on correlations between the Standardized Precipitation Index (SPI) at various time scales and the Standardized Groundwater Index (SGI) across a Mediterranean island. We detected three main responses of aquifers to accumulated precipitation anomalies: (i) at short time scales of the SPI (<6 months); (ii) at medium time scales (6-24 months); and at long time scales (>24 months). The differing responses were mainly explained by differences in lithology and the percentage of highly permeable rock strata in the aquifer recharge areas. We also identified differences in the months and seasons when aquifer storages are more dependent on precipitation; these were related to climate seasonality and the degree of aquifer exploitation or underground water extraction. The recharge of some aquifers, especially in mountainous areas, is related to precipitation variability within a limited spatial extent, whereas for aquifers located in the plains, precipitation variability influence much larger areas; the topography and geological structure of the island explain these differences. Results indicate large spatial variability in the response of aquifers to precipitation in a very small area, highlighting the importance of having high spatial resolution hydro-climatic databases available to enable full understanding of the effects of climate variability on scarce water resources.
Ecoregion-Based Conservation Planning in the Mediterranean: Dealing with Large-Scale Heterogeneity
Giakoumi, Sylvaine; Sini, Maria; Gerovasileiou, Vasilis; Mazor, Tessa; Beher, Jutta; Possingham, Hugh P.; Abdulla, Ameer; Çinar, Melih Ertan; Dendrinos, Panagiotis; Gucu, Ali Cemal; Karamanlidis, Alexandros A.; Rodic, Petra; Panayotidis, Panayotis; Taskin, Ergun; Jaklin, Andrej; Voultsiadou, Eleni; Webster, Chloë; Zenetos, Argyro; Katsanevakis, Stelios
2013-01-01
Spatial priorities for the conservation of three key Mediterranean habitats, i.e. seagrass Posidonia oceanica meadows, coralligenous formations, and marine caves, were determined through a systematic planning approach. Available information on the distribution of these habitats across the entire Mediterranean Sea was compiled to produce basin-scale distribution maps. Conservation targets for each habitat type were set according to European Union guidelines. Surrogates were used to estimate the spatial variation of opportunity cost for commercial, non-commercial fishing, and aquaculture. Marxan conservation planning software was used to evaluate the comparative utility of two planning scenarios: (a) a whole-basin scenario, referring to selection of priority areas across the whole Mediterranean Sea, and (b) an ecoregional scenario, in which priority areas were selected within eight predefined ecoregions. Although both scenarios required approximately the same total area to be protected in order to achieve conservation targets, the opportunity cost differed between them. The whole-basin scenario yielded a lower opportunity cost, but the Alboran Sea ecoregion was not represented and priority areas were predominantly located in the Ionian, Aegean, and Adriatic Seas. In comparison, the ecoregional scenario resulted in a higher representation of ecoregions and a more even distribution of priority areas, albeit with a higher opportunity cost. We suggest that planning at the ecoregional level ensures better representativeness of the selected conservation features and adequate protection of species, functional, and genetic diversity across the basin. While there are several initiatives that identify priority areas in the Mediterranean Sea, our approach is novel as it combines three issues: (a) it is based on the distribution of habitats and not species, which was rarely the case in previous efforts, (b) it considers spatial variability of cost throughout this socioeconomically heterogeneous basin, and (c) it adopts ecoregions as the most appropriate level for large-scale planning. PMID:24155901
Spatial Supermarket Redlining and Neighborhood Vulnerability: A Case Study of Hartford, Connecticut
Zhang, Mengyao
2015-01-01
The disinclination of chain supermarkets to locate or pull out existing stores from impoverished neighborhoods is termed as “supermarket redlining”. This paper attempts to map and understand the spatial effects of potential supermarket redlining on food vulnerability in urban disadvantaged neighborhoods of Hartford, Connecticut. Using a combination of statistical and spatial analysis functions, we first, built a Supermarket Redlining Index (SuRI) from five indicators such as sales volume, employee count, accepts food coupons from federally assisted programs, and size and population density of the service area to rank supermarkets in the order of their importance. Second, to understand the effect of redlining, a Supermarket Redlining Impact Model (SuRIM) was built with eleven indicators describing both the socioeconomic and food access vulnerabilities. The interaction of these vulnerabilities would identify the final outcome: neighborhoods where the impact of supermarket redlining would be critical. Results mapped critical areas in the inner-city of Hartford where if a nearby supermarket closes or relocates to a suburb with limited mitigation efforts to gill the grocery gap, a large number of minority, poor, and disadvantaged residents will experience difficulties to access healthy food leading to food insecurity or perhaps a food desert. We also suggest mitigation efforts to reduce the impact of large supermarket closures. PMID:27034615
Spatial Supermarket Redlining and Neighborhood Vulnerability: A Case Study of Hartford, Connecticut.
Zhang, Mengyao; Debarchana, Ghosh
2016-02-01
The disinclination of chain supermarkets to locate or pull out existing stores from impoverished neighborhoods is termed as "supermarket redlining". This paper attempts to map and understand the spatial effects of potential supermarket redlining on food vulnerability in urban disadvantaged neighborhoods of Hartford, Connecticut. Using a combination of statistical and spatial analysis functions, we first, built a Supermarket Redlining Index (SuRI) from five indicators such as sales volume, employee count, accepts food coupons from federally assisted programs, and size and population density of the service area to rank supermarkets in the order of their importance. Second, to understand the effect of redlining, a Supermarket Redlining Impact Model (SuRIM) was built with eleven indicators describing both the socioeconomic and food access vulnerabilities. The interaction of these vulnerabilities would identify the final outcome: neighborhoods where the impact of supermarket redlining would be critical. Results mapped critical areas in the inner-city of Hartford where if a nearby supermarket closes or relocates to a suburb with limited mitigation efforts to gill the grocery gap, a large number of minority, poor, and disadvantaged residents will experience difficulties to access healthy food leading to food insecurity or perhaps a food desert. We also suggest mitigation efforts to reduce the impact of large supermarket closures.
Spatial variability of specific surface area of arable soils in Poland
NASA Astrophysics Data System (ADS)
Sokolowski, S.; Sokolowska, Z.; Usowicz, B.
2012-04-01
Evaluation of soil spatial variability is an important issue in agrophysics and in environmental research. Knowledge of spatial variability of physico-chemical properties enables a better understanding of several processes that take place in soils. In particular, it is well known that mineralogical, organic, as well as particle-size compositions of soils vary in a wide range. Specific surface area of soils is one of the most significant characteristics of soils. It can be not only related to the type of soil, mainly to the content of clay, but also largely determines several physical and chemical properties of soils and is often used as a controlling factor in numerous biological processes. Knowledge of the specific surface area is necessary in calculating certain basic soil characteristics, such as the dielectric permeability of soil, water retention curve, water transport in the soil, cation exchange capacity and pesticide adsorption. The aim of the present study is two-fold. First, we carry out recognition of soil total specific surface area patterns in the territory of Poland and perform the investigation of features of its spatial variability. Next, semivariograms and fractal analysis are used to characterize and compare the spatial variability of soil specific surface area in two soil horizons (A and B). Specific surface area of about 1000 samples was determined by analyzing water vapor adsorption isotherms via the BET method. The collected data of the values of specific surface area of mineral soil representatives for the territory of Poland were then used to describe its spatial variability by employing geostatistical techniques and fractal theory. Using the data calculated for some selected points within the entire territory and along selected directions, the values of semivariance were determined. The slope of the regression line of the log-log plot of semi-variance versus the distance was used to estimate the fractal dimension, D. Specific surface area in A and B horizons was space-dependent, with the range of spatial dependence of about 2.5°. Variogram surfaces showed anisotropy of the specific surface area in both horizons with a trend toward the W to E directions. The smallest fractal dimensions were obtained for W to E directions and the highest values - for S to N directions. * The work was financially supported in part by the ESA Programme for European Cooperating States (PECS), No.98084 "SWEX-R, Soil Water and Energy Exchange/Research", AO3275.
[Soil and forest structure in the Colombian Amazon].
Calle-Rendón, Bayron R; Moreno, Flavio; Cárdenas López, Dairon
2011-09-01
Forests structural differences could result of environmental variations at different scales. Because soils are an important component of plant's environment, it is possible that edaphic and structural variables are associated and that, in consequence, spatial autocorrelation occurs. This paper aims to answer two questions: (1) are structural and edaphic variables associated at local scale in a terra firme forest of Colombian Amazonia? and (2) are these variables regionalized at the scale of work? To answer these questions we analyzed the data of a 6ha plot established in a terra firme forest of the Amacayacu National Park. Structural variables included basal area and density of large trees (diameter > or = 10cm) (Gdos and Ndos), basal area and density of understory individuals (diameter < 10cm) (Gsot and Nsot) and number of species of large trees (sp). Edaphic variables included were pH, organic matter, P, Mg, Ca, K, Al, sand, silt and clay. Structural and edaphic variables were reduced through a principal component analysis (PCA); then, the association between edaphic and structural components from PCA was evaluated by multiple regressions. The existence of regionalization of these variables was studied through isotropic variograms, and autocorrelated variables were spatially mapped. PCA found two significant components for structure, corresponding to the structure of large trees (G, Gdos, Ndos and sp) and of small trees (N, Nsot and Gsot), which explained 43.9% and 36.2% of total variance, respectively. Four components were identified for edaphic variables, which globally explained 81.9% of total variance and basically represent drainage and soil fertility. Regression analyses were significant (p < 0.05) and showed that the structure of both large and small trees is associated with greater sand contents and low soil fertility, though they explained a low proportion of total variability (R2 was 4.9% and 16.5% for the structure of large trees and small tress, respectively). Variables with spatial autocorrelation were the structure of small trees, Al, silt, and sand. Among them, Nsot and sand content showed similar patterns of spatial distribution inside the plot.
Large-Area All-Textile Pressure Sensors for Monitoring Human Motion and Physiological Signals.
Liu, Mengmeng; Pu, Xiong; Jiang, Chunyan; Liu, Ting; Huang, Xin; Chen, Libo; Du, Chunhua; Sun, Jiangman; Hu, Weiguo; Wang, Zhong Lin
2017-11-01
Wearable pressure sensors, which can perceive and respond to environmental stimuli, are essential components of smart textiles. Here, large-area all-textile-based pressure-sensor arrays are successfully realized on common fabric substrates. The textile sensor unit achieves high sensitivity (14.4 kPa -1 ), low detection limit (2 Pa), fast response (≈24 ms), low power consumption (<6 µW), and mechanical stability under harsh deformations. Thanks to these merits, the textile sensor is demonstrated to be able to recognize finger movement, hand gestures, acoustic vibrations, and real-time pulse wave. Furthermore, large-area sensor arrays are successfully fabricated on one textile substrate to spatially map tactile stimuli and can be directly incorporated into a fabric garment for stylish designs without sacrifice of comfort, suggesting great potential in smart textiles or wearable electronics. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Electronic sensor and actuator webs for large-area complex geometry cardiac mapping and therapy
Kim, Dae-Hyeong; Ghaffari, Roozbeh; Lu, Nanshu; Wang, Shuodao; Lee, Stephen P.; Keum, Hohyun; D’Angelo, Robert; Klinker, Lauren; Su, Yewang; Lu, Chaofeng; Kim, Yun-Soung; Ameen, Abid; Li, Yuhang; Zhang, Yihui; de Graff, Bassel; Hsu, Yung-Yu; Liu, ZhuangJian; Ruskin, Jeremy; Xu, Lizhi; Lu, Chi; Omenetto, Fiorenzo G.; Huang, Yonggang; Mansour, Moussa; Slepian, Marvin J.; Rogers, John A.
2012-01-01
Curved surfaces, complex geometries, and time-dynamic deformations of the heart create challenges in establishing intimate, nonconstraining interfaces between cardiac structures and medical devices or surgical tools, particularly over large areas. We constructed large area designs for diagnostic and therapeutic stretchable sensor and actuator webs that conformally wrap the epicardium, establishing robust contact without sutures, mechanical fixtures, tapes, or surgical adhesives. These multifunctional web devices exploit open, mesh layouts and mount on thin, bio-resorbable sheets of silk to facilitate handling in a way that yields, after dissolution, exceptionally low mechanical moduli and thicknesses. In vivo studies in rabbit and pig animal models demonstrate the effectiveness of these device webs for measuring and spatially mapping temperature, electrophysiological signals, strain, and physical contact in sheet and balloon-based systems that also have the potential to deliver energy to perform localized tissue ablation. PMID:23150574
Large-area ordered Ge-Si compound quantum dot molecules on dot-patterned Si (001) substrates
NASA Astrophysics Data System (ADS)
Lei, Hui; Zhou, Tong; Wang, Shuguang; Fan, Yongliang; Zhong, Zhenyang
2014-08-01
We report on the formation of large-area ordered Ge-Si compound quantum dot molecules (CQDMs) in a combination of nanosphere lithography and self-assembly. Truncated-pyramid-like Si dots with {11n} facets are readily formed, which are spatially ordered in a large area with controlled period and size. Each Si dot induces four self-assembled Ge-rich dots at its base edges that can be fourfold symmetric along <110> directions. A model based on surface chemical potential accounts well for these phenomena. Our results disclose the critical effect of surface curvature on the diffusion and the aggregation of Ge adatoms and shed new light on the unique features and the inherent mechanism of self-assembled QDs on patterned substrates. Such a configuration of one Si QD surrounded by fourfold symmetric Ge-rich QDs can be seen as a CQDM with unique features, which will have potential applications in novel devices.
Abdo, A. A.; Ackermann, M.; Ajello, M.; ...
2009-12-29
In this paper, we report on measurements of the cosmic-ray induced γ-ray emission of Earth’s atmosphere by the Large Area Telescope on board the Fermi Gamma-ray Space Telescope. The Large Area Telescope has observed the Earth during its commissioning phase and with a dedicated Earth limb following observation in September 2008. These measurements yielded ~6.4 × 10 6 photons with energies > 100 MeV and ~ 250 hours total live time for the highest quality data selection. This allows the study of the spatial and spectral distributions of these photons with unprecedented detail. In additon, the spectrum of the emission—oftenmore » referred to as Earth albedo gamma-ray emission—has a power-law shape up to 500 GeV with spectral index Γ = 2.79 ± 0.06 .« less
Capture zone area distributions for nucleation and growth of islands during submonolayer deposition
DOE Office of Scientific and Technical Information (OSTI.GOV)
Han, Yong; Li, Maozhi; Evans, James W.
2016-12-07
A fundamental evolution equation is developed to describe the distribution of areas of capture zones (CZs) associated with islands formed by homogeneous nucleation and growth during submonolayer deposition on perfect flat surfaces. This equation involves various quantities which characterize subtle spatial aspects of the nucleation process. These quantities in turn depend on the complex stochastic geometry of the CZ tessellation of the surface, and their detailed form determines the CZ area distribution (CZD) including its asymptotic features. For small CZ areas, behavior of the CZD reflects the critical island size, i. For large CZ areas, it may reflect the probabilitymore » for nucleation near such large CZs. Predictions are compared with kinetic Monte Carlo simulation data for models with two-dimensional compact islands with i = 1 (irreversible island formation by diffusing adatom pairs) and i = 0 (adatoms spontaneously convert to stable nuclei, e.g., by exchange with the substrate).« less
Detecting changes in the spatial distribution of nitrate contamination in ground water
Liu, Z.-J.; Hallberg, G.R.; Zimmerman, D.L.; Libra, R.D.
1997-01-01
Many studies of ground water pollution in general and nitrate contamination in particular have often relied on a one-time investigation, tracking of individual wells, or aggregate summaries. Studies of changes in spatial distribution of contaminants over time are lacking. This paper presents a method to compare spatial distributions for possible changes over time. The large-scale spatial distribution at a given time can be considered as a surface over the area (a trend surface). The changes in spatial distribution from period to period can be revealed by the differences in the shape and/or height of surfaces. If such a surface is described by a polynomial function, changes in surfaces can be detected by testing statistically for differences in their corresponding polynomial functions. This method was applied to nitrate concentration in a population of wells in an agricultural drainage basin in Iowa, sampled in three different years. For the period of 1981-1992, the large-scale spatial distribution of nitrate concentration did not show significant change in the shape of spatial surfaces; while the magnitude of nitrate concentration in the basin, or height of the computed surfaces showed significant fluctuations. The change in magnitude of nitrate concentration is closely related to climatic variations, especially in precipitation. The lack of change in the shape of spatial surfaces means that either the influence of land use/nitrogen management was overshadowed by climatic influence, or the changes in land use/management occurred in a random fashion.
NASA Astrophysics Data System (ADS)
Croke, Jacky; Todd, Peter; Thompson, Chris; Watson, Fiona; Denham, Robert; Khanal, Giri
2013-02-01
Advances in remote sensing and digital terrain processing now allow for a sophisticated analysis of spatial and temporal changes in erosion and deposition. Digital elevation models (DEMs) can now be constructed and differenced to produce DEMs of Difference (DoD), which are used to assess net landscape change for morphological budgeting. To date this has been most effectively achieved in gravel-bed rivers over relatively small spatial scales. If the full potential of the technology is to be realised, additional studies are required at larger scales and across a wider range of geomorphic features. This study presents an assessment of the basin-scale spatial patterns of erosion, deposition, and net morphological change that resulted from a catastrophic flood event in the Lockyer Creek catchment of SE Queensland (SEQ) in January 2011. Multitemporal Light Detection and Ranging (LiDAR) DEMs were used to construct a DoD that was then combined with a one-dimensional flow hydraulic model HEC-RAS to delineate five major geomorphic landforms, including inner-channel area, within-channel benches, macrochannel banks, and floodplain. The LiDAR uncertainties were quantified and applied together with a probabilistic representation of uncertainty thresholded at a conservative 95% confidence interval. The elevation change distribution (ECD) for the 100-km2 study area indicates a magnitude of elevation change spanning almost 10 m but the mean elevation change of 0.04 m confirms that a large part of the landscape was characterised by relatively low magnitude changes over a large spatial area. Mean elevation changes varied by geomorphic feature and only two, the within-channel benches and macrochannel banks, were net erosional with an estimated combined loss of 1,815,149 m3 of sediment. The floodplain was the zone of major net deposition but mean elevation changes approached the defined critical limit of uncertainty. Areal and volumetric ECDs for this extreme event provide a representative expression of the balance between erosion and deposition, and importantly sediment redistribution, which is extremely difficult to quantify using more traditional channel planform or cross-sectional surveys. The ability of LiDAR to make a rapid and accurate assessment of key geomorphic processes over large spatial scales contributes to our understanding of key processes and, as demonstrated here, to the assessment of major geomorphological hazards such as extreme flood events.
ESRI applications of GIS technology: Mineral resource development
NASA Technical Reports Server (NTRS)
Derrenbacher, W.
1981-01-01
The application of geographic information systems technology to large scale regional assessment related to mineral resource development, identifying candidate sites for related industry, and evaluating sites for waste disposal is discussed. Efforts to develop data bases were conducted at scales ranging from 1:3,000,000 to 1:25,000. In several instances, broad screening was conducted for large areas at a very general scale with more detailed studies subsequently undertaken in promising areas windowed out of the generalized data base. Increasingly, the systems which are developed are structured as the spatial framework for the long-term collection, storage, referencing, and retrieval of vast amounts of data about large regions. Typically, the reconnaissance data base for a large region is structured at 1:250,000 scale, data bases for smaller areas being structured at 1:25,000, 1:50,000 or 1:63,360. An integrated data base for the coterminous US was implemented at a scale of 1:3,000,000 for two separate efforts.
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.
Estimates of reservoir methane emissions based on a spatially ...
Global estimates of methane (CH4) emissions from reservoirs are poorly constrained, partly due to the challenges of accounting for intra-reservoir spatial variability. Reservoir-scale emission rates are often estimated by extrapolating from measurement made at a few locations; however, error and bias associated with this approach can be large and difficult to quantify. Here we use a generalized random tessellation survey (GRTS) design to generate estimates of central tendency and variance at multiple spatial scales in a reservoir. GRTS survey designs are probabilistic and spatially balanced which eliminates bias associated with expert judgment in site selection. GRTS surveys also allow for variance estimates that account for spatial pattern in emission rates. Total CH4 emission rates (i.e. sum of ebullition and diffusive emissions) were 4.8 (±2.1), 33.0 (±10.7), and 8.3 (±2.2) mg CH4 m-2 h-1 in open-waters, tributary associated areas, and the entire reservoir for the period in August 2014 during which 115 sites were sampled across an 7.98 km2 reservoir in Southwestern, Ohio, USA. Tributary areas occupy 12% of the reservoir surface, but were the source of 41% of total CH4 emissions, highlighting the importance of riverine-lacustrine transition zones. Ebullition accounted for >90% of CH4 emission at all spatial scales. Confidence interval estimates that incorporated spatial pattern in CH4 emissions were up to 29% narrower than when spatial independence
Baldrighi, Elisa; Lavaleye, Marc; Aliani, Stefano; Conversi, Alessandra; Manini, Elena
2014-01-01
The large-scale deep-sea biodiversity distribution of the benthic fauna was explored in the Mediterranean Sea, which can be seen as a miniature model of the oceans of the world. Within the framework of the BIOFUN project (“Biodiversity and Ecosystem Functioning in Contrasting Southern European Deep-sea Environments: from viruses to megafauna”), we investigated the large spatial scale variability (over >1,000 km) of the bathyal macrofauna communities that inhabit the Mediterranean basin, and their relationships with the environmental variables. The macrofauna abundance, biomass, community structure and functional diversity were analysed and the α-diversity and β-diversity were estimated across six selected slope areas at different longitudes and along three main depths. The macrobenthic standing stock and α-diversity were lower in the deep-sea sediments of the eastern Mediterranean basin, compared to the western and central basins. The macrofaunal standing stock and diversity decreased significantly from the upper bathyal to the lower bathyal slope stations. The major changes in the community composition of the higher taxa and in the trophic (functional) structure occurred at different longitudes, rather than at increasing water depth. For the β-diversity, very high dissimilarities emerged at all levels: (i) between basins; (ii) between slopes within the same basin; and (iii) between stations at different depths; this therefore demonstrates the high macrofaunal diversity of the Mediterranean basins at large spatial scales. Overall, the food sources (i.e., quantity and quality) that characterised the west, central and eastern Mediterranean basins, as well as sediment grain size, appear to influence the macrobenthic standing stock and the biodiversity along the different slope areas. PMID:25225909
Baldrighi, Elisa; Lavaleye, Marc; Aliani, Stefano; Conversi, Alessandra; Manini, Elena
2014-01-01
The large-scale deep-sea biodiversity distribution of the benthic fauna was explored in the Mediterranean Sea, which can be seen as a miniature model of the oceans of the world. Within the framework of the BIOFUN project ("Biodiversity and Ecosystem Functioning in Contrasting Southern European Deep-sea Environments: from viruses to megafauna"), we investigated the large spatial scale variability (over >1,000 km) of the bathyal macrofauna communities that inhabit the Mediterranean basin, and their relationships with the environmental variables. The macrofauna abundance, biomass, community structure and functional diversity were analysed and the α-diversity and β-diversity were estimated across six selected slope areas at different longitudes and along three main depths. The macrobenthic standing stock and α-diversity were lower in the deep-sea sediments of the eastern Mediterranean basin, compared to the western and central basins. The macrofaunal standing stock and diversity decreased significantly from the upper bathyal to the lower bathyal slope stations. The major changes in the community composition of the higher taxa and in the trophic (functional) structure occurred at different longitudes, rather than at increasing water depth. For the β-diversity, very high dissimilarities emerged at all levels: (i) between basins; (ii) between slopes within the same basin; and (iii) between stations at different depths; this therefore demonstrates the high macrofaunal diversity of the Mediterranean basins at large spatial scales. Overall, the food sources (i.e., quantity and quality) that characterised the west, central and eastern Mediterranean basins, as well as sediment grain size, appear to influence the macrobenthic standing stock and the biodiversity along the different slope areas.
Thermal emission from large area chemical vapor deposited graphene devices
NASA Astrophysics Data System (ADS)
Luxmoore, I. J.; Adlem, C.; Poole, T.; Lawton, L. M.; Mahlmeister, N. H.; Nash, G. R.
2013-09-01
The spatial variation of thermal emission from large area graphene grown by chemical vapor deposition, transferred onto SiO2/Si substrates and fabricated into field effect transistor structures, has been investigated using infra-red microscopy. A peak in thermal emission occurs, the position of which can be altered by reversal of the current direction. The experimental results are compared with a one dimensional finite element model, which accounts for Joule heating and electrostatic effects, and it is found that the thermal emission is governed by the charge distribution in the graphene and maximum Joule heating occurs at the point of minimum charge density.
NASA Astrophysics Data System (ADS)
Cao, An-ye; Dou, Lin-ming; Wang, Chang-bin; Yao, Xiao-xiao; Dong, Jing-yuan; Gu, Yu
2016-11-01
Identification of precursory characteristics is a key issue for rock burst prevention. The aim of this research is to provide a reference for assessing rock burst risk and determining potential rock burst risk areas in coal mining. In this work, the microseismic multidimensional information for the identification of rock bursts and spatial-temporal pre-warning was investigated in a specific coalface which suffered high rock burst risk in a mining area near a large residual coal pillar. Firstly, microseismicity evolution prior to a disastrous rock burst was qualitatively analysed, and the abnormal clustering of seismic sources, abnormal variations in daily total energy release, and event counts can be regarded as precursors to rock burst. Secondly, passive tomographic imaging has been used to locate high seismic activity zones and assess rock burst hazard when the coalface passes through residual pillar areas. The results show that high-velocity or velocity anomaly regions correlated well with strong seismic activities in future mining periods and that passive tomography has the potential to describe, both quantitatively and periodically, hazardous regions and assess rock burst risk. Finally, the bursting strain energy index was further used for short-term spatial-temporal pre-warning of rock bursts. The temporal sequence curve and spatial contour nephograms indicate that the status of the danger and the specific hazardous zones, and levels of rock burst risk can be quantitatively and rapidly analysed in short time and in space. The multidimensional precursory characteristic identification of rock bursts, including qualitative analysis, intermediate and short-time quantitative predictions, can guide the choice of measures implemented to control rock bursts in the field, and provides a new approach to monitor and forecast rock bursts in space and time.
USDA-ARS?s Scientific Manuscript database
With enhanced data availability, distributed watershed models for large areas with high spatial and temporal resolution are increasingly used to understand water budgets and examine effects of human activities and climate change/variability on water resources. Developing parallel computing software...
Forest health monitoring and other environmental assessments require information on the spatial distribution of basic soil physical and chemical properties. Traditional soil surveys are not available for large areas of forestland in the western US but there are some soil resour...
Carl H. Key; Nathan C. Benson
2006-01-01
Landscape Assessment primarily addresses the need to identify and quantify fire effects over large areas, at times involving many burns. In contrast to individual case studies, the ability to compare results is emphasized along with the capacity to aggregate information across broad regions and over time. Results show the spatial heterogeneity of burns and how fire...
Green infrastructure is a widely used framework for conservation planning in the United States and elsewhere. The main components of green infrastructure are hubs and corridors. Hubs are large areas of natural vegetation, and corridors are linear features that connect hubs. W...
Large scale, spatially-explicit test of the refuge strategy for delaying insecticide resistance
USDA-ARS?s Scientific Manuscript database
The refuge strategy used worldwide to delay the evolution of arthropod resistance to pesticides consists of leaving areas where a pesticide is not used near fields where the pesticide is used. Yet, empirical approaches are lacking to characterize effects of putative refuges on resistance evolution. ...
A spatially explicit suspended-sediment load model for western Oregon
Wise, Daniel R.; O'Connor, Jim
2016-06-27
Knowledge of the regionally important patterns and factors in suspended-sediment sources and transport could support broad-scale, water-quality management objectives and priorities. Because of biases and limitations of this model, however, these results are most applicable for general comparisons and for broad areas such as large watersheds. For example, despite having similar area, precipitation, and land-use, the Umpqua River Basin generates 68 percent more suspended sediment than the Rogue River Basin, chiefly because of the large area of Coast Range sedimentary province in the Umpqua River Basin. By contrast, the Rogue River Basin contains a much larger area of Klamath terrane rocks, which produce significantly less suspended load, although recent fire disturbance (in 2002) has apparently elevated suspended sediment yields in the tributary Illinois River watershed. Fine-scaled analysis, however, will require more intensive, locally focused measurements.
Enabling Interactive Measurements from Large Coverage Microscopy
Bajcsy, Peter; Vandecreme, Antoine; Amelot, Julien; Chalfoun, Joe; Majurski, Michael; Brady, Mary
2017-01-01
Microscopy could be an important tool for characterizing stem cell products if quantitative measurements could be collected over multiple spatial and temporal scales. With the cells changing states over time and being several orders of magnitude smaller than cell products, modern microscopes are already capable of imaging large spatial areas, repeat imaging over time, and acquiring images over several spectra. However, characterizing stem cell products from such large image collections is challenging because of data size, required computations, and lack of interactive quantitative measurements needed to determine release criteria. We present a measurement web system consisting of available algorithms, extensions to a client-server framework using Deep Zoom, and the configuration know-how to provide the information needed for inspecting the quality of a cell product. The cell and other data sets are accessible via the prototype web-based system at http://isg.nist.gov/deepzoomweb. PMID:28663600
A continental scale trophic cascade from wolves through coyotes to foxes.
Newsome, Thomas M; Ripple, William J
2015-01-01
Top-down processes, via the direct and indirect effects of interspecific competitive killing (no consumption of the kill) or intraguild predation (consumption of the kill), can potentially influence the spatial distribution of terrestrial predators, but few studies have demonstrated the phenomenon at a continental scale. For example, in North America, grey wolves Canis lupus are known to kill coyotes Canis latrans, and coyotes, in turn, may kill foxes Vulpes spp., but the spatial effects of these competitive interactions at large scales are unknown. Here, we analyse fur return data across eight jurisdictions in North America to test whether the presence or absence of wolves has caused a continent-wide shift in coyote and red fox Vulpes vulpes density. Our results support the existence of a continental scale cascade whereby coyotes outnumber red foxes in areas where wolves have been extirpated by humans, whereas red foxes outnumber coyotes in areas where wolves are present. However, for a distance of up to 200 km on the edge of wolf distribution, there is a transition zone where the effects of top-down control are weakened, possibly due to the rapid dispersal and reinvasion capabilities of coyotes into areas where wolves are sporadically distributed or at low densities. Our results have implications for understanding how the restoration of wolf populations across North America could potentially affect co-occurring predators and prey. We conclude that large carnivores may need to occupy large continuous areas to facilitate among-carnivore cascades and that studies of small areas may not be indicative of the effects of top-down mesopredator control. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.
NASA Astrophysics Data System (ADS)
Reppucci, Antonio; Moreno, Laura
2010-12-01
Information on Soil moisture spatial and temporal evolution is of great importance for managing the utilization of soils and vegetation, in particular in environments where the water resources are scarce. In-situ measurement of soil moisture are costly and not able to sample the spatial behaviour of a whole region. Thanks to their all weather capability and wide coverage, Synthetic Aperture Radar (SAR) images offer the opportunity to monitor large area with high resolution. This study presents the results of a project, partially founded by the Catalan government, to improve the monitoring of soil moisture using Earth Observation data. In particular the project is focused on the calibration of existing semi-empirical algorithm in the area of study. This will be done using co-located SAR and in-situ measurements acquired during several field campaigns. Observed deviations between SAR measurements and in-situ measurement are discussed.
Uncertainty in Random Forests: What does it mean in a spatial context?
NASA Astrophysics Data System (ADS)
Klump, Jens; Fouedjio, Francky
2017-04-01
Geochemical surveys are an important part of exploration for mineral resources and in environmental studies. The samples and chemical analyses are often laborious and difficult to obtain and therefore come at a high cost. As a consequence, these surveys are characterised by datasets with large numbers of variables but relatively few data points when compared to conventional big data problems. With more remote sensing platforms and sensor networks being deployed, large volumes of auxiliary data of the surveyed areas are becoming available. The use of these auxiliary data has the potential to improve the prediction of chemical element concentrations over the whole study area. Kriging is a well established geostatistical method for the prediction of spatial data but requires significant pre-processing and makes some basic assumptions about the underlying distribution of the data. Some machine learning algorithms, on the other hand, may require less data pre-processing and are non-parametric. In this study we used a dataset provided by Kirkwood et al. [1] to explore the potential use of Random Forest in geochemical mapping. We chose Random Forest because it is a well understood machine learning method and has the advantage that it provides us with a measure of uncertainty. By comparing Random Forest to Kriging we found that both methods produced comparable maps of estimated values for our variables of interest. Kriging outperformed Random Forest for variables of interest with relatively strong spatial correlation. The measure of uncertainty provided by Random Forest seems to be quite different to the measure of uncertainty provided by Kriging. In particular, the lack of spatial context can give misleading results in areas without ground truth data. In conclusion, our preliminary results show that the model driven approach in geostatistics gives us more reliable estimates for our target variables than Random Forest for variables with relatively strong spatial correlation. However, in cases of weak spatial correlation Random Forest, as a nonparametric method, may give the better results once we have a better understanding of the meaning of its uncertainty measures in a spatial context. References [1] Kirkwood, C., M. Cave, D. Beamish, S. Grebby, and A. Ferreira (2016), A machine learning approach to geochemical mapping, Journal of Geochemical Exploration, 163, 28-40, doi:10.1016/j.gexplo.2016.05.003.
Archfield, Stacey A.; Pugliese, Alessio; Castellarin, Attilio; Skøien, Jon O.; Kiang, Julie E.
2013-01-01
In the United States, estimation of flood frequency quantiles at ungauged locations has been largely based on regional regression techniques that relate measurable catchment descriptors to flood quantiles. More recently, spatial interpolation techniques of point data have been shown to be effective for predicting streamflow statistics (i.e., flood flows and low-flow indices) in ungauged catchments. Literature reports successful applications of two techniques, canonical kriging, CK (or physiographical-space-based interpolation, PSBI), and topological kriging, TK (or top-kriging). CK performs the spatial interpolation of the streamflow statistic of interest in the two-dimensional space of catchment descriptors. TK predicts the streamflow statistic along river networks taking both the catchment area and nested nature of catchments into account. It is of interest to understand how these spatial interpolation methods compare with generalized least squares (GLS) regression, one of the most common approaches to estimate flood quantiles at ungauged locations. By means of a leave-one-out cross-validation procedure, the performance of CK and TK was compared to GLS regression equations developed for the prediction of 10, 50, 100 and 500 yr floods for 61 streamgauges in the southeast United States. TK substantially outperforms GLS and CK for the study area, particularly for large catchments. The performance of TK over GLS highlights an important distinction between the treatments of spatial correlation when using regression-based or spatial interpolation methods to estimate flood quantiles at ungauged locations. The analysis also shows that coupling TK with CK slightly improves the performance of TK; however, the improvement is marginal when compared to the improvement in performance over GLS.
Physically-based failure analysis of shallow layered soil deposits over large areas
NASA Astrophysics Data System (ADS)
Cuomo, Sabatino; Castorino, Giuseppe Claudio; Iervolino, Aniello
2014-05-01
In the last decades, the analysis of slope stability conditions over large areas has become popular among scientists and practitioners (Cascini et al., 2011; Cuomo and Della Sala, 2013). This is due to the availability of new computational tools (Baum et al., 2002; Godt et al., 2008; Baum and Godt, 2012; Salciarini et al., 2012) - implemented in GIS (Geographic Information System) platforms - which allow taking into account the major hydraulic and mechanical issues related to slope failure, even for unsaturated soils, as well as the spatial variability of both topography and soil properties. However, the effectiveness (Sorbino et al., 2010) of the above methods it is still controversial for landslides forecasting especially depending on the accuracy of DTM (Digital Terrain Model) and for the chance that distinct triggering mechanisms may occur over large area. Among the major uncertainties, layering of soil deposits is of primary importance due to soil layer conductivity contrast and differences in shear strength. This work deals with the hazard analysis of shallow landslides over large areas, considering two distinct schematizations of soil stratigraphy, i.e. homogeneous or layered. To this purpose, the physically-based model TRIGRS (Baum et al., 2002) is firstly used, then extended to the case of layered deposit: specifically, a unique set of hydraulic properties is assumed while distinct soil unit weight and shear strength are considered for each soil layer. Both models are applied to a significant study area of Southern Italy, about 4 km2 large, where shallow deposits of air-fall volcanic (pyroclastic) soils have been affected by several landslides, causing victims, damages and economic losses. The achieved results highlight that soil volume globally mobilized over the study area highly depends on local stratigraphy of shallow deposits. This relates to the depth of critical slip surface which rarely corresponds to the bedrock contact where cohesionless coarse materials lie on deeper soil layers with small effective cohesion. It is also shown that, due to a more realistic assessment of soil stratigraphy, the success of the model may increase when performing a back-analysis of a recent real event. References Baum, R. L., W. Z. Savage, and J. W. Godt (2002), TRIGRS-A Fortran program for transient rainfall infiltration and grid-based regional slope-stability analysis. U.S. Geological Survey, Open-file report 02-424, 35 p. Baum, R.L., Godt, J.W. (2012) Assessment of shallow landslide potential using 1-D and 3-D slope stability analysis Landslides and Engineered Slopes: Protecting Society through Improved Understanding - Eberhardt et al. (eds) 2012 Taylor & Francis Group, London, ISBN 978-0-415-62123-6, 1667-1672. Cascini L., Cuomo S., Della Sala M. (2011). Spatial and temporal occurrence of rainfall-induced shallow landslides of flow type: A case of Sarno-Quindici, Italy. Geomorphology, 126(1-2), 148-158. Cuomo S., Della Sala M. (2013). Spatially distributed analysis of shallow landslides and soil erosion induced by rainfall. (submitted to Natural Hazards). Godt, J.W., Baum, R.L., Savage, W.Z., Salciarini, D., Schulz, W.H., Harp, E.L. (2008). Transient deterministic shallow landslide modeling: requirements for susceptibility and hazard assessments in a GIS framework. Engineering Geology 102, 214-226. Salciarini, D., Tamagnini, C., Conversini, P., Rapinesi, S. (2012). Spatially distributed rainfall thresholds for the initiation of shallow landslides. Natural Hazards 61, 229-245. Sorbino G., Sica C., Cascini L. (2010). Susceptibility analysis of shallow landslides source areas using physically based models. Natural Hazards, 53(2), 313-332.
Drewnowski, Adam; Rehm, Colin D; Moudon, Anne V; Arterburn, David
2014-07-24
Identifying areas of high diabetes prevalence can have an impact on public health prevention and intervention programs. Local health practitioners and public health agencies lack small-area data on obesity and diabetes. Clinical data from the Group Health Cooperative health care system were used to estimate diabetes prevalence among 59,767 adults by census tract. Area-based measures of socioeconomic status and the Modified Retail Food Environment Index were obtained at the census-tract level in King County, Washington. Spatial analyses and regression models were used to assess the relationship between census tract-level diabetes and area-based socioeconomic status and food environment variables. The mediating effect of obesity on the geographic distribution of diabetes was also examined. In this population of insured adults, diabetes was concentrated in south and southeast King County, with smoothed diabetes prevalence ranging from 6.9% to 21.2%. In spatial regression models, home value and college education were more strongly associated with diabetes than was household income. For each 50% increase in median home value, diabetes prevalence was 1.2 percentage points lower. The Modified Retail Food Environment Index was not related to diabetes at the census-tract level. The observed associations between area-based socioeconomic status and diabetes were largely mediated by obesity (home value, 58%; education, 47%). The observed geographic disparities in diabetes among insured adults by census tract point to the importance of area socioeconomic status. Small-area studies can help health professionals design community-based programs for diabetes prevention and control.
Automated identification of potential snow avalanche release areas based on digital elevation models
NASA Astrophysics Data System (ADS)
Bühler, Y.; Kumar, S.; Veitinger, J.; Christen, M.; Stoffel, A.; Snehmani
2013-05-01
The identification of snow avalanche release areas is a very difficult task. The release mechanism of snow avalanches depends on many different terrain, meteorological, snowpack and triggering parameters and their interactions, which are very difficult to assess. In many alpine regions such as the Indian Himalaya, nearly no information on avalanche release areas exists mainly due to the very rough and poorly accessible terrain, the vast size of the region and the lack of avalanche records. However avalanche release information is urgently required for numerical simulation of avalanche events to plan mitigation measures, for hazard mapping and to secure important roads. The Rohtang tunnel access road near Manali, Himachal Pradesh, India, is such an example. By far the most reliable way to identify avalanche release areas is using historic avalanche records and field investigations accomplished by avalanche experts in the formation zones. But both methods are not feasible for this area due to the rough terrain, its vast extent and lack of time. Therefore, we develop an operational, easy-to-use automated potential release area (PRA) detection tool in Python/ArcGIS which uses high spatial resolution digital elevation models (DEMs) and forest cover information derived from airborne remote sensing instruments as input. Such instruments can acquire spatially continuous data even over inaccessible terrain and cover large areas. We validate our tool using a database of historic avalanches acquired over 56 yr in the neighborhood of Davos, Switzerland, and apply this method for the avalanche tracks along the Rohtang tunnel access road. This tool, used by avalanche experts, delivers valuable input to identify focus areas for more-detailed investigations on avalanche release areas in remote regions such as the Indian Himalaya and is a precondition for large-scale avalanche hazard mapping.
Tarimo, Beatrice; Dick, Øystein B; Gobakken, Terje; Totland, Ørjan
2015-12-01
Anthropogenic uses of fire play a key role in regulating fire regimes in African savannas. These fires contribute the highest proportion of the globally burned area, substantial biomass burning emissions and threaten maintenance and enhancement of carbon stocks. An understanding of fire regimes at local scales is required for the estimation and prediction of the contribution of these fires to the global carbon cycle and for fire management. We assessed the spatio-temporal distribution of fires in miombo woodlands of Tanzania, utilizing the MODIS active fire product and Landsat satellite images for the past ~40 years. Our results show that up to 50.6% of the woodland area is affected by fire each year. An early and a late dry season peak in wetter and drier miombo, respectively, characterize the annual fire season. Wetter miombo areas have higher fire activity within a shorter annual fire season and have shorter return intervals. The fire regime is characterized by small-sized fires, with a higher ratio of small than large burned areas in the frequency-size distribution (β = 2.16 ± 0.04). Large-sized fires are rare, and occur more frequently in drier than in wetter miombo. Both fire prevalence and burned extents have decreased in the past decade. At a large scale, more than half of the woodland area has less than 2 years of fire return intervals, which prevent the occurrence of large intense fires. The sizes of fires, season of burning and spatial extent of occurrence are generally consistent across time, at the scale of the current analysis. Where traditional use of fire is restricted, a reassessment of fire management strategies may be required, if sustainability of tree cover is a priority. In such cases, there is a need to combine traditional and contemporary fire management practices.
High dose bystander effects in spatially fractionated radiation therapy
Asur, Rajalakshmi; Butterworth, Karl T.; Penagaricano, Jose A.; Prise, Kevin M.; Griffin, Robert J.
2014-01-01
Traditional radiotherapy of bulky tumors has certain limitations. Spatially fractionated radiation therapy (GRID) and intensity modulated radiotherapy (IMRT) are examples of advanced modulated beam therapies that help in significant reductions in normal tissue damage. GRID refers to the delivery of a single high dose of radiation to a large treatment area that is divided into several smaller fields, while IMRT allows improved dose conformity to the tumor target compared to conventional three-dimensional conformal radiotherapy. In this review, we consider spatially fractionated radiotherapy approaches focusing on GRID and IMRT, and present complementary evidence from different studies which support the role of radiation induced signaling effects in the overall radiobiological rationale for these treatments. PMID:24246848
Mishima, T; Kao, K C
1982-03-15
New laser interferometry has been developed, based on the principle that a 2-D fringe pattern can be produced by interference of spatially coherent light beams. To avoid the effect of reflection from the back surface of the substrate, the Brewster angle of incidence is adopted; to suppress the effect of diffraction, a lens or a lens system is used. This laser interferometry is an efficient nondestructive technique for the determination of thickness distributions or uniformities of low absorbing films on transparent substrates over a large area without involving laborious computations. The limitation of spatial resolution, thickness resolution, and visibility of fringes is fully analyzed.
Taggart, S. James; Mondragon, Jennifer; Andrews, A.G.; Nielsen, J.K.
2008-01-01
Most examples of positive population responses to marine protected areas (MPAs) have been documented for tropical reef species with very small home ranges; the utility of MPAs for commercially harvested temperate species that have large movement patterns remains poorly tested. We measured the distribution and abundance of red king Paralithodes camtschaticus and Tanner Chionoecetes bairdi crabs inside and outside of MPAs in Glacier Bay National Park, Alaska, USA. By tagging a sub-sample of crabs with sonic tags, we estimated the movement of adult crabs from one of the MPAs (Muir Inlet) into the central portion of Glacier Bay where fishing still occurs. Tanner crabs and red king crabs moved similar average distances per day, although Tanner crabs had a higher transfer out of the Muir Inlet MPA into the central bay. Tanner crab movements were characterized by large variation among individual crabs, both in distance and direction traveled, while red king crabs migrated seasonally between 2 specific areas. Although Tanner crabs exhibited relatively large movements, distribution and abundance data suggest that they may be restricted at large spatial scales by habitat barriers. MPAs that are effective at protecting king and especially Tanner crab brood stock from fishing mortality will likely need to be larger than is typical of MPAs worldwide. However, by incorporating information on the seasonal movements of red king crabs and the location of habitat barriers for Tanner crabs, MPAs could likely be designed that would effectively protect adults from fishing mortality. ?? Inter-Research 2008.
Ali, Mohammad; Goovaerts, Pierre; Nazia, Nushrat; Haq, M Zahirul; Yunus, Mohammad; Emch, Michael
2006-10-13
Disease maps can serve to display incidence rates geographically, to inform on public health provision about the success or failure of interventions, and to make hypothesis or to provide evidences concerning disease etiology. Poisson kriging was recently introduced to filter the noise attached to rates recorded over sparsely populated administrative units. Its benefit over simple population-weighted averages and empirical Bayesian smoothers was demonstrated by simulation studies using county-level cancer mortality rates. This paper presents the first application of Poisson kriging to the spatial interpolation of local disease rates, resulting in continuous maps of disease rate estimates and the associated prediction variance. The methodology is illustrated using cholera and dysentery data collected in a cholera endemic area (Matlab) of Bangladesh. The spatial analysis was confined to patrilineally-related clusters of households, known as baris, located within 9 kilometers from the Matlab hospital to avoid underestimating the risk of disease incidence, since patients far away from the medical facilities are less likely to travel. Semivariogram models reveal a range of autocorrelation of 1.1 km for dysentery and 0.37 km for cholera. This result translates into a cholera risk map that is patchier than the dysentery map that shows a large zone of high incidence in the south-central part of the study area, which is quasi-urban. On both maps, lower risk values are found in the Northern part of the study area, which is also the most distant from the Matlab hospital. The weaker spatial continuity of cholera versus dysentery incidence rates resulted in larger kriging variance across the study area. The approach presented in this paper enables researchers to incorporate the pattern of spatial dependence of incidence rates into the mapping of risk values and the quantification of the associated uncertainty. Differences in spatial patterns, in particular the range of spatial autocorrelation, reflect differences in the mode of transmission of cholera and dysentery. Our risk maps for cholera and dysentery incidences should help identifying putative factors of increased disease incidence, leading to more effective prevention and remedial actions in endemic areas.
Ali, Mohammad; Goovaerts, Pierre; Nazia, Nushrat; Haq, M Zahirul; Yunus, Mohammad; Emch, Michael
2006-01-01
Background Disease maps can serve to display incidence rates geographically, to inform on public health provision about the success or failure of interventions, and to make hypothesis or to provide evidences concerning disease etiology. Poisson kriging was recently introduced to filter the noise attached to rates recorded over sparsely populated administrative units. Its benefit over simple population-weighted averages and empirical Bayesian smoothers was demonstrated by simulation studies using county-level cancer mortality rates. This paper presents the first application of Poisson kriging to the spatial interpolation of local disease rates, resulting in continuous maps of disease rate estimates and the associated prediction variance. The methodology is illustrated using cholera and dysentery data collected in a cholera endemic area (Matlab) of Bangladesh. Results The spatial analysis was confined to patrilineally-related clusters of households, known as baris, located within 9 kilometers from the Matlab hospital to avoid underestimating the risk of disease incidence, since patients far away from the medical facilities are less likely to travel. Semivariogram models reveal a range of autocorrelation of 1.1 km for dysentery and 0.37 km for cholera. This result translates into a cholera risk map that is patchier than the dysentery map that shows a large zone of high incidence in the south-central part of the study area, which is quasi-urban. On both maps, lower risk values are found in the Northern part of the study area, which is also the most distant from the Matlab hospital. The weaker spatial continuity of cholera versus dysentery incidence rates resulted in larger kriging variance across the study area. Conclusion The approach presented in this paper enables researchers to incorporate the pattern of spatial dependence of incidence rates into the mapping of risk values and the quantification of the associated uncertainty. Differences in spatial patterns, in particular the range of spatial autocorrelation, reflect differences in the mode of transmission of cholera and dysentery. Our risk maps for cholera and dysentery incidences should help identifying putative factors of increased disease incidence, leading to more effective prevention and remedial actions in endemic areas. PMID:17038192
NASA Astrophysics Data System (ADS)
Simier, M.; Blanc, L.; Aliaume, C.; Diouf, P. S.; Albaret, J. J.
2004-01-01
As a consequence of the Sahelian drought, the Sine Saloum, a large estuarine system located in Senegal (West Africa), has become an "inverse estuary" since the late sixties, i.e. salinity increases upstream and reaches 100 in some places. To study the fish assemblages of such a modified system, a survey was conducted in 1992, collecting fish every two months with a purse seine at eight sites spread over the three main branches of the estuary. A total of 73 species belonging to 35 families were identified. Eight species comprised 97% of the total numbers of fish. The predominant species was a small clupeid, Sardinella maderensis, representing more than half of the total biomass and nearly 70% of the total number of fish. The spatio-temporal structure of the fish assemblages was studied using the STATIS-CoA method, which combines the multitable approach with the correspondence analysis method. Whatever the season, a strong spatial organization of fish assemblages was observed, mainly related to depth and salinity. Three types of assemblages were identified. In shallow water areas, fish assemblages were dominated by Mugilidae, Gerreidae and Cichlidae and were stable with time. In open water areas, large fluctuations in the species composition were observed, due to the occasional presence of large schools of pelagic species: in the southern area, where salinity and water transparency were the lowest, the main species were Ilisha africana, Brachydeuterus auritus and Chloroscombrus chrysurus, associated with a few Sciaenidae and Tetraodontidae, while the poorest areas were characterized by only two dominant species, S. maderensis and Scomberomorus tritor.
Spatial patterns of agricultural expansion determine impacts on biodiversity and carbon storage.
Chaplin-Kramer, Rebecca; Sharp, Richard P; Mandle, Lisa; Sim, Sarah; Johnson, Justin; Butnar, Isabela; Milà I Canals, Llorenç; Eichelberger, Bradley A; Ramler, Ivan; Mueller, Carina; McLachlan, Nikolaus; Yousefi, Anahita; King, Henry; Kareiva, Peter M
2015-06-16
The agricultural expansion and intensification required to meet growing food and agri-based product demand present important challenges to future levels and management of biodiversity and ecosystem services. Influential actors such as corporations, governments, and multilateral organizations have made commitments to meeting future agricultural demand sustainably and preserving critical ecosystems. Current approaches to predicting the impacts of agricultural expansion involve calculation of total land conversion and assessment of the impacts on biodiversity or ecosystem services on a per-area basis, generally assuming a linear relationship between impact and land area. However, the impacts of continuing land development are often not linear and can vary considerably with spatial configuration. We demonstrate what could be gained by spatially explicit analysis of agricultural expansion at a large scale compared with the simple measure of total area converted, with a focus on the impacts on biodiversity and carbon storage. Using simple modeling approaches for two regions of Brazil, we find that for the same amount of land conversion, the declines in biodiversity and carbon storage can vary two- to fourfold depending on the spatial pattern of conversion. Impacts increase most rapidly in the earliest stages of agricultural expansion and are more pronounced in scenarios where conversion occurs in forest interiors compared with expansion into forests from their edges. This study reveals the importance of spatially explicit information in the assessment of land-use change impacts and for future land management and conservation.
Spatial Access to Primary Care Providers in Appalachia
Donohoe, Joseph; Marshall, Vince; Tan, Xi; Camacho, Fabian T.; Anderson, Roger T.; Balkrishnan, Rajesh
2016-01-01
Purpose: The goal of this research was to examine spatial access to primary care physicians in Appalachia using both traditional access measures and the 2-step floating catchment area (2SFCA) method. Spatial access to care was compared between urban and rural regions of Appalachia. Methods: The study region included Appalachia counties of Pennsylvania, Ohio, Kentucky, and North Carolina. Primary care physicians during 2008 and total census block group populations were geocoded into GIS software. Ratios of county physicians to population, driving time to nearest primary care physician, and various 2SFCA approaches were compared. Results: Urban areas of the study region had shorter travel times to their closest primary care physician. Provider to population ratios produced results that varied widely from one county to another because of strict geographic boundaries. The 2SFCA method produced varied results depending on the distance decay weight and variable catchment size techniques chose. 2SFCA scores showed greater access to care in urban areas of Pennsylvania, Ohio, and North Carolina. Conclusion: The different parameters of the 2SFCA method—distance decay weights and variable catchment sizes—have a large impact on the resulting spatial access to primary care scores. The findings of this study suggest that using a relative 2SFCA approach, the spatial access ratio method, when detailed patient travel data are unavailable. The 2SFCA method shows promise for measuring access to care in Appalachia, but more research on patient travel preferences is needed to inform implementation. PMID:26906524
Spatial patterns of agricultural expansion determine impacts on biodiversity and carbon storage
Chaplin-Kramer, Rebecca; Sharp, Richard P.; Mandle, Lisa; Sim, Sarah; Johnson, Justin; Butnar, Isabela; Milà i Canals, Llorenç; Eichelberger, Bradley A.; Ramler, Ivan; Mueller, Carina; McLachlan, Nikolaus; Yousefi, Anahita; King, Henry; Kareiva, Peter M.
2015-01-01
The agricultural expansion and intensification required to meet growing food and agri-based product demand present important challenges to future levels and management of biodiversity and ecosystem services. Influential actors such as corporations, governments, and multilateral organizations have made commitments to meeting future agricultural demand sustainably and preserving critical ecosystems. Current approaches to predicting the impacts of agricultural expansion involve calculation of total land conversion and assessment of the impacts on biodiversity or ecosystem services on a per-area basis, generally assuming a linear relationship between impact and land area. However, the impacts of continuing land development are often not linear and can vary considerably with spatial configuration. We demonstrate what could be gained by spatially explicit analysis of agricultural expansion at a large scale compared with the simple measure of total area converted, with a focus on the impacts on biodiversity and carbon storage. Using simple modeling approaches for two regions of Brazil, we find that for the same amount of land conversion, the declines in biodiversity and carbon storage can vary two- to fourfold depending on the spatial pattern of conversion. Impacts increase most rapidly in the earliest stages of agricultural expansion and are more pronounced in scenarios where conversion occurs in forest interiors compared with expansion into forests from their edges. This study reveals the importance of spatially explicit information in the assessment of land-use change impacts and for future land management and conservation. PMID:26082547
NASA Astrophysics Data System (ADS)
Casu, Francesco; Manconi, Andrea; Pepe, Antonio; Lanari, Riccardo
2010-05-01
Differential Synthetic Aperture Radar Interferometry (DInSAR) is a remote sensing technique that allows producing spatially dense deformation maps of the Earth surface, with centimeter accuracy. To this end, the phase difference of SAR image pairs acquired before and after a deformation episode is properly exploited. This technique, originally applied to investigate single deformation events, has been further extended to analyze the temporal evolution of the deformation field through the generation of displacement time-series. A well-established approach is represented by the Small BAseline Subset (SBAS) technique (Berardino et al., 2002), whose capability to analyze deformation events at low and full spatial resolution has largely been demonstrated. However, in areas where large and/or rapid deformation phenomena occur, the exploitation of the differential interferograms, thus also of the displacement time-series, can be strongly limited by the presence of significant misregistration errors and/or very high fringe rates, making unfeasible the phase unwrapping step. In this work, we propose advances on the generation of deformation time-series in areas affected by large deformation dynamics. We present an extension of the amplitude-based Pixel-Offset analyses by applying the SBAS strategy, in order to move from the investigation of single (large) deformation events to that of dynamic phenomena. The above-mentioned method has been tested on an ENVISAT SAR data archive (Track 61, Frames 7173-7191) related to the Galapagos Islands, focusing on Sierra Negra caldera (Galapagos Islands), an active volcanic area often characterized by large and rapid deformation events leading to severe image misregistration effects (Yun et al., 2007). Moreover, we present a cross-validation of the retrieved deformation estimates comparing our results to continuous GPS measurements and to synthetic deformation obtained by independently modeling the interferometric phase information when available. References: P. Berardino et al., (2002), A new algorithm for Surface Deformation Monitoring based on Small Baseline Differential SAR Interferograms, IEEE Transactions on Geoscience and Remote Sensing, vol. 40, 11, pp. 2375-2383. S-H. Yun et al., (2007), Interferogram formation in the presence of complex and large deformation, Geophys. Res. Lett., vol. 34, L12305.
Mobile measurements of air pollutants with an instrumented car in populated areas
NASA Astrophysics Data System (ADS)
Weber, Konradin; Scharifi, Emad; Fischer, Christian; Pohl, Tobias; Lange, Martin; Boehlke, Christoph
2017-04-01
Detailed mobile measurement of gases and fine particulate matter has been reported in the literature to be suitable to exhibit the air pollutants concentration in populated areas. This concentration is linked to the increase of number of cars, construction areas, industries and other emission sources. However, fixed measurement stations, mostly operated by environmental agencies, are limited in numbers and cannot cover a large area in monitoring. For this reason, to overcome this drawback, mobile measurements of the variability of gases (such as O3, NO, NO2) and particulate matter concentration were carried out during this study using an instrumented car. This car was able to deliver measurement results of all these compounds in a large area. The experimental results in this work demonstrate a large spatial variability of gases and fine particulate matters mainly depended on the traffic density and the location. These effects are especially obvious in the city core and the high traffic roads. In terms of fine particulate matter, this becomes evident for PM 10 and PM 2.5, where the mass and number concentration increases with arriving these zones.
Fine-scale spatial climate variation and drought mediate the likelihood of reburning.
Parks, Sean A; Parisien, Marc-André; Miller, Carol; Holsinger, Lisa M; Baggett, Larry Scott
2018-03-01
In many forested ecosystems, it is increasingly recognized that the probability of burning is substantially reduced within the footprint of previously burned areas. This self-limiting effect of wildland fire is considered a fundamental emergent property of ecosystems and is partly responsible for structuring landscape heterogeneity (i.e., mosaics of different age classes), thereby reducing the likelihood of uncharacteristically large fires in regions with active fire regimes. However, the strength and longevity of this self-limiting phenomenon is not well understood in most fire-prone ecosystems. In this study, we quantify the self-limiting effect in terms of its strength and longevity for five fire-prone study areas in western North America and investigate how each measure varies along a spatial climatic gradient and according to temporal (i.e., annual) climatic variation. Results indicate that the longevity (i.e., number of years) of the self-limiting effect ranges between 15 yr in the warm and dry study area in the southwestern United States to 33 yr in the cold, northern study areas in located in northwestern Montana and the boreal forest of Canada. We also found that spatial climatic variation has a strong influence on wildland fire's self-limiting capacity. Specifically, the self-limiting effect within each study area was stronger and lasted longer in areas with low mean moisture deficit (i.e., wetter and cooler settings) compared to areas with high mean moisture deficit (warmer and drier settings). Last, our findings show that annual climatic variation influences wildland fire's self-limiting effect: drought conditions weakened the strength and longevity of the self-limiting effect in all study areas, albeit at varying magnitudes. Overall, our study provides support for the idea that wildland fire contributes to spatial heterogeneity in fuel ages that subsequently mediate future fire sizes and effects. However, our findings show that the strength and longevity of the self-limiting effect varies considerably according to spatial and temporal climatic variation, providing land and fire managers relevant information for effective planning and management of fire and highlighting that fire itself is an important factor contributing to fire-free intervals. © 2017 by the Ecological Society of America.
NASA Astrophysics Data System (ADS)
Sciambi, A.; Pelliccione, M.; Bank, S. R.; Gossard, A. C.; Goldhaber-Gordon, D.
2010-09-01
We propose a probe technique capable of performing local low-temperature spectroscopy on a two-dimensional electron system (2DES) in a semiconductor heterostructure. Motivated by predicted spatially-structured electron phases, the probe uses a charged metal tip to induce electrons to tunnel locally, directly below the tip, from a "probe" 2DES to a "subject" 2DES of interest. We test this concept with large-area (nonscanning) tunneling measurements, and predict a high spatial resolution and spectroscopic capability, with minimal influence on the physics in the subject 2DES.
Neurophysiological Organization of the Middle Face Patch in Macaque Inferior Temporal Cortex
Aparicio, Paul L.; Issa, Elias B.
2016-01-01
While early cortical visual areas contain fine scale spatial organization of neuronal properties, such as orientation preference, the spatial organization of higher-level visual areas is less well understood. The fMRI demonstration of face-preferring regions in human ventral cortex and monkey inferior temporal cortex (“face patches”) raises the question of how neural selectivity for faces is organized. Here, we targeted hundreds of spatially registered neural recordings to the largest fMRI-identified face-preferring region in monkeys, the middle face patch (MFP), and show that the MFP contains a graded enrichment of face-preferring neurons. At its center, as much as 93% of the sites we sampled responded twice as strongly to faces than to nonface objects. We estimate the maximum neurophysiological size of the MFP to be ∼6 mm in diameter, consistent with its previously reported size under fMRI. Importantly, face selectivity in the MFP varied strongly even between neighboring sites. Additionally, extremely face-selective sites were ∼40 times more likely to be present inside the MFP than outside. These results provide the first direct quantification of the size and neural composition of the MFP by showing that the cortical tissue localized to the fMRI defined region consists of a very high fraction of face-preferring sites near its center, and a monotonic decrease in that fraction along any radial spatial axis. SIGNIFICANCE STATEMENT The underlying organization of neurons that give rise to the large spatial regions of activity observed with fMRI is not well understood. Neurophysiological studies that have targeted the fMRI identified face patches in monkeys have provided evidence for both large-scale clustering and a heterogeneous spatial organization. Here we used a novel x-ray imaging system to spatially map the responses of hundreds of sites in and around the middle face patch. We observed that face-selective signal localized to the middle face patch was characterized by a gradual spatial enrichment. Furthermore, strongly face-selective sites were ∼40 times more likely to be found inside the patch than outside of the patch. PMID:27810930
Neurophysiological Organization of the Middle Face Patch in Macaque Inferior Temporal Cortex.
Aparicio, Paul L; Issa, Elias B; DiCarlo, James J
2016-12-14
While early cortical visual areas contain fine scale spatial organization of neuronal properties, such as orientation preference, the spatial organization of higher-level visual areas is less well understood. The fMRI demonstration of face-preferring regions in human ventral cortex and monkey inferior temporal cortex ("face patches") raises the question of how neural selectivity for faces is organized. Here, we targeted hundreds of spatially registered neural recordings to the largest fMRI-identified face-preferring region in monkeys, the middle face patch (MFP), and show that the MFP contains a graded enrichment of face-preferring neurons. At its center, as much as 93% of the sites we sampled responded twice as strongly to faces than to nonface objects. We estimate the maximum neurophysiological size of the MFP to be ∼6 mm in diameter, consistent with its previously reported size under fMRI. Importantly, face selectivity in the MFP varied strongly even between neighboring sites. Additionally, extremely face-selective sites were ∼40 times more likely to be present inside the MFP than outside. These results provide the first direct quantification of the size and neural composition of the MFP by showing that the cortical tissue localized to the fMRI defined region consists of a very high fraction of face-preferring sites near its center, and a monotonic decrease in that fraction along any radial spatial axis. The underlying organization of neurons that give rise to the large spatial regions of activity observed with fMRI is not well understood. Neurophysiological studies that have targeted the fMRI identified face patches in monkeys have provided evidence for both large-scale clustering and a heterogeneous spatial organization. Here we used a novel x-ray imaging system to spatially map the responses of hundreds of sites in and around the middle face patch. We observed that face-selective signal localized to the middle face patch was characterized by a gradual spatial enrichment. Furthermore, strongly face-selective sites were ∼40 times more likely to be found inside the patch than outside of the patch. Copyright © 2016 the authors 0270-6474/16/3612729-17$15.00/0.
Gordon, Christopher E; Price, Owen F; Tasker, Elizabeth M
2017-07-01
There is a public perception that large high-severity wildfires decrease biodiversity and increase fire hazard by homogenizing vegetation composition and increasing the cover of mid-story vegetation. But a growing literature suggests that vegetation responses are nuanced. LiDAR technology provides a promising remote sensing tool to test hypotheses about post-fire vegetation regrowth because vegetation cover can be quantified within different height strata at fine scales over large areas. We assess the usefulness of airborne LiDAR data for measuring post-fire mid-story vegetation regrowth over a range of spatial resolutions (10 × 10 m, 30 × 30 m, 50 × 50 m, 100 × 100 m cell size) and investigate the effect of fire severity on regrowth amount and spatial pattern following a mixed severity wildfire in Warrumbungle National Park, Australia. We predicted that recovery would be more vigorous in areas of high fire severity, because park managers observed dense post-fire regrowth in these areas. Moderate to strong positive associations were observed between LiDAR and field surveys of mid-story vegetation cover between 0.5-3.0 m. Thus our LiDAR survey was an apt representation of on-ground vegetation cover. LiDAR-derived mid-story vegetation cover was 22-40% lower in areas of low and moderate than high fire severity. Linear mixed-effects models showed that fire severity was among the strongest biophysical predictors of mid-story vegetation cover irrespective of spatial resolution. However much of the variance associated with these models was unexplained, presumably because soil seed banks varied at finer scales than our LiDAR maps. Dense patches of mid-story vegetation regrowth were small (median size 0.01 ha) and evenly distributed between areas of low, moderate and high fire severity, demonstrating that high-severity fires do not homogenize vegetation cover. Our results are relevant for ecosystem conservation and fire management because they: indicate that native vegetation are responsive and resilient to high-severity fire, and show the usefulness of remote sensing tools such as LiDAR to monitor post-fire vegetation recovery over large areas in situ. © 2017 by the Ecological Society of America.
Qin, Changbo; Jia, Yangwen; Su, Z; Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen
2008-07-29
This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems.
Qin, Changbo; Jia, Yangwen; Su, Z.(Bob); Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen
2008-01-01
This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems. PMID:27879946
A map overlay error model based on boundary geometry
Gaeuman, D.; Symanzik, J.; Schmidt, J.C.
2005-01-01
An error model for quantifying the magnitudes and variability of errors generated in the areas of polygons during spatial overlay of vector geographic information system layers is presented. Numerical simulation of polygon boundary displacements was used to propagate coordinate errors to spatial overlays. The model departs from most previous error models in that it incorporates spatial dependence of coordinate errors at the scale of the boundary segment. It can be readily adapted to match the scale of error-boundary interactions responsible for error generation on a given overlay. The area of error generated by overlay depends on the sinuosity of polygon boundaries, as well as the magnitude of the coordinate errors on the input layers. Asymmetry in boundary shape has relatively little effect on error generation. Overlay errors are affected by real differences in boundary positions on the input layers, as well as errors in the boundary positions. Real differences between input layers tend to compensate for much of the error generated by coordinate errors. Thus, the area of change measured on an overlay layer produced by the XOR overlay operation will be more accurate if the area of real change depicted on the overlay is large. The model presented here considers these interactions, making it especially useful for estimating errors studies of landscape change over time. ?? 2005 The Ohio State University.
The human footprint in Mexico: physical geography and historical legacies.
González-Abraham, Charlotte; Ezcurra, Exequiel; Garcillán, Pedro P; Ortega-Rubio, Alfredo; Kolb, Melanie; Bezaury Creel, Juan E
2015-01-01
Using publicly available data on land use and transportation corridors we calculated the human footprint index for the whole of Mexico to identify large-scale spatial patterns in the anthropogenic transformation of the land surface. We developed a map of the human footprint for the whole country and identified the ecological regions that have most transformed by human action. Additionally, we analyzed the extent to which (a) physical geography, expressed spatially in the form of biomes and ecoregions, compared to (b) historical geography, expressed as the spatial distribution of past human settlements, have driven the patterns of human modification of the land. Overall Mexico still has 56% of its land surface with low impact from human activities, but these areas are not evenly distributed. The lowest values are on the arid north and northwest, and the tropical southeast, while the highest values run along the coast of the Gulf of Mexico and from there inland along an east-to-west corridor that follows the Mexican transversal volcanic ranges and the associated upland plateau. The distribution of low- and high footprint areas within ecoregions forms a complex mosaic: the generally well-conserved Mexican deserts have some highly transformed agro-industrial areas, while many well-conserved, low footprint areas still persist in the highly-transformed ecoregions of central Mexico. We conclude that the spatial spread of the human footprint in Mexico is both the result of the limitations imposed by physical geography to human development at the biome level, and, within different biomes, of a complex history of past civilizations and technologies, including the 20th Century demographic explosion but also the spatial pattern of ancient settlements that were occupied by the Spanish Colony.
The Human Footprint in Mexico: Physical Geography and Historical Legacies
Ortega-Rubio, Alfredo; Kolb, Melanie; Bezaury Creel, Juan E.
2015-01-01
Using publicly available data on land use and transportation corridors we calculated the human footprint index for the whole of Mexico to identify large-scale spatial patterns in the anthropogenic transformation of the land surface. We developed a map of the human footprint for the whole country and identified the ecological regions that have most transformed by human action. Additionally, we analyzed the extent to which (a) physical geography, expressed spatially in the form of biomes and ecoregions, compared to (b) historical geography, expressed as the spatial distribution of past human settlements, have driven the patterns of human modification of the land. Overall Mexico still has 56% of its land surface with low impact from human activities, but these areas are not evenly distributed. The lowest values are on the arid north and northwest, and the tropical southeast, while the highest values run along the coast of the Gulf of Mexico and from there inland along an east-to-west corridor that follows the Mexican transversal volcanic ranges and the associated upland plateau. The distribution of low- and high footprint areas within ecoregions forms a complex mosaic: the generally well-conserved Mexican deserts have some highly transformed agro-industrial areas, while many well-conserved, low footprint areas still persist in the highly-transformed ecoregions of central Mexico. We conclude that the spatial spread of the human footprint in Mexico is both the result of the limitations imposed by physical geography to human development at the biome level, and, within different biomes, of a complex history of past civilizations and technologies, including the 20th Century demographic explosion but also the spatial pattern of ancient settlements that were occupied by the Spanish Colony. PMID:25803839
Puerta, Patricia; Hunsicker, Mary E.; Quetglas, Antoni; Álvarez-Berastegui, Diego; Esteban, Antonio; González, María; Hidalgo, Manuel
2015-01-01
Populations of the same species can experience different responses to the environment throughout their distributional range as a result of spatial and temporal heterogeneity in habitat conditions. This highlights the importance of understanding the processes governing species distribution at local scales. However, research on species distribution often averages environmental covariates across large geographic areas, missing variability in population-environment interactions within geographically distinct regions. We used spatially explicit models to identify interactions between species and environmental, including chlorophyll a (Chla) and sea surface temperature (SST), and trophic (prey density) conditions, along with processes governing the distribution of two cephalopods with contrasting life-histories (octopus and squid) across the western Mediterranean Sea. This approach is relevant for cephalopods, since their population dynamics are especially sensitive to variations in habitat conditions and rarely stable in abundance and location. The regional distributions of the two cephalopod species matched two different trophic pathways present in the western Mediterranean Sea, associated with the Gulf of Lion upwelling and the Ebro river discharges respectively. The effects of the studied environmental and trophic conditions were spatially variant in both species, with usually stronger effects along their distributional boundaries. We identify areas where prey availability limited the abundance of cephalopod populations as well as contrasting effects of temperature in the warmest regions. Despite distributional patterns matching productive areas, a general negative effect of Chla on cephalopod densities suggests that competition pressure is common in the study area. Additionally, results highlight the importance of trophic interactions, beyond other common environmental factors, in shaping the distribution of cephalopod populations. Our study presents a valuable approach for understanding the spatially variant ecology of cephalopod populations, which is important for fisheries and ecosystem management. PMID:26201075
High Performance Geostatistical Modeling of Biospheric Resources
NASA Astrophysics Data System (ADS)
Pedelty, J. A.; Morisette, J. T.; Smith, J. A.; Schnase, J. L.; Crosier, C. S.; Stohlgren, T. J.
2004-12-01
We are using parallel geostatistical codes to study spatial relationships among biospheric resources in several study areas. For example, spatial statistical models based on large- and small-scale variability have been used to predict species richness of both native and exotic plants (hot spots of diversity) and patterns of exotic plant invasion. However, broader use of geostastics in natural resource modeling, especially at regional and national scales, has been limited due to the large computing requirements of these applications. To address this problem, we implemented parallel versions of the kriging spatial interpolation algorithm. The first uses the Message Passing Interface (MPI) in a master/slave paradigm on an open source Linux Beowulf cluster, while the second is implemented with the new proprietary Xgrid distributed processing system on an Xserve G5 cluster from Apple Computer, Inc. These techniques are proving effective and provide the basis for a national decision support capability for invasive species management that is being jointly developed by NASA and the US Geological Survey.
Lensfree on-chip microscopy over a wide field-of-view using pixel super-resolution
Bishara, Waheb; Su, Ting-Wei; Coskun, Ahmet F.; Ozcan, Aydogan
2010-01-01
We demonstrate lensfree holographic microscopy on a chip to achieve ~0.6 µm spatial resolution corresponding to a numerical aperture of ~0.5 over a large field-of-view of ~24 mm2. By using partially coherent illumination from a large aperture (~50 µm), we acquire lower resolution lensfree in-line holograms of the objects with unit fringe magnification. For each lensfree hologram, the pixel size at the sensor chip limits the spatial resolution of the reconstructed image. To circumvent this limitation, we implement a sub-pixel shifting based super-resolution algorithm to effectively recover much higher resolution digital holograms of the objects, permitting sub-micron spatial resolution to be achieved across the entire sensor chip active area, which is also equivalent to the imaging field-of-view (24 mm2) due to unit magnification. We demonstrate the success of this pixel super-resolution approach by imaging patterned transparent substrates, blood smear samples, as well as Caenoharbditis Elegans. PMID:20588977
Electro-optical design of a long slit streak tube
NASA Astrophysics Data System (ADS)
Tian, Liping; Tian, Jinshou; Wen, Wenlong; Chen, Ping; Wang, Xing; Hui, Dandan; Wang, Junfeng
2017-11-01
A small size and long slit streak tube with high spatial resolution was designed and optimized. Curved photocathode and screen were adopted to increase the photocathode working area and spatial resolution. High physical temporal resolution obtained by using a slit accelerating electrode. Deflection sensitivity of the streak tube was improved by adopting two-folded deflection plates. The simulations indicate that the photocathode effective working area can reach 30mm × 5mm. The static spatial resolution is higher than 40lp/mm and 12lp/mm along scanning and slit directions respectively while the physical temporal resolution is higher than 60ps. The magnification is 0.75 and 0.77 in scanning and slit directions. And also, the deflection sensitivity is as high as 37mm/kV. The external dimension of the streak tube are only ∅74mm×231mm. Thus, it can be applied to laser imaging radar system for large field of view and high range precision detection.
Barral, Paula; Carmona, Alejandra; Nahuelhual, Laura
2016-01-01
Growing concern about the loss of ecosystem services (ES) promotes their spatial representation as a key tool for the internalization of the ES framework into land use policies. Paradoxically, mapping approaches meant to inform policy decisions focus on the magnitude and spatial distribution of the biophysical supply of ES, largely ignoring the social mechanisms by which these services influence human wellbeing. If social mechanisms affecting ES demand, enhancing it or reducing it, are taken more into account, then policies are more effective. By developing and applying a new mapping routine to two distinct socio-ecological systems, we show a strong spatial uncoupling between ES supply and socio-ecological vulnerability to the loss of ES, under scenarios of land use and cover change. Public policies based on ES supply might not only fail at detecting priority conservation areas for the wellbeing of human societies, but may also increase their vulnerability by neglecting areas of currently low, but highly valued ES supply. PMID:27167737
Laterra, Pedro; Barral, Paula; Carmona, Alejandra; Nahuelhual, Laura
2016-01-01
Growing concern about the loss of ecosystem services (ES) promotes their spatial representation as a key tool for the internalization of the ES framework into land use policies. Paradoxically, mapping approaches meant to inform policy decisions focus on the magnitude and spatial distribution of the biophysical supply of ES, largely ignoring the social mechanisms by which these services influence human wellbeing. If social mechanisms affecting ES demand, enhancing it or reducing it, are taken more into account, then policies are more effective. By developing and applying a new mapping routine to two distinct socio-ecological systems, we show a strong spatial uncoupling between ES supply and socio-ecological vulnerability to the loss of ES, under scenarios of land use and cover change. Public policies based on ES supply might not only fail at detecting priority conservation areas for the wellbeing of human societies, but may also increase their vulnerability by neglecting areas of currently low, but highly valued ES supply.
Ouyang, Min; Tian, Hui; Wang, Zhenghua; Hong, Liu; Mao, Zijun
2017-01-17
This article studies a general type of initiating events in critical infrastructures, called spatially localized failures (SLFs), which are defined as the failure of a set of infrastructure components distributed in a spatially localized area due to damage sustained, while other components outside the area do not directly fail. These failures can be regarded as a special type of intentional attack, such as bomb or explosive assault, or a generalized modeling of the impact of localized natural hazards on large-scale systems. This article introduces three SLFs models: node centered SLFs, district-based SLFs, and circle-shaped SLFs, and proposes a SLFs-induced vulnerability analysis method from three aspects: identification of critical locations, comparisons of infrastructure vulnerability to random failures, topologically localized failures and SLFs, and quantification of infrastructure information value. The proposed SLFs-induced vulnerability analysis method is finally applied to the Chinese railway system and can be also easily adapted to analyze other critical infrastructures for valuable protection suggestions. © 2017 Society for Risk Analysis.
Local multiplicity adjustment for the spatial scan statistic using the Gumbel distribution.
Gangnon, Ronald E
2012-03-01
The spatial scan statistic is an important and widely used tool for cluster detection. It is based on the simultaneous evaluation of the statistical significance of the maximum likelihood ratio test statistic over a large collection of potential clusters. In most cluster detection problems, there is variation in the extent of local multiplicity across the study region. For example, using a fixed maximum geographic radius for clusters, urban areas typically have many overlapping potential clusters, whereas rural areas have relatively few. The spatial scan statistic does not account for local multiplicity variation. We describe a previously proposed local multiplicity adjustment based on a nested Bonferroni correction and propose a novel adjustment based on a Gumbel distribution approximation to the distribution of a local scan statistic. We compare the performance of all three statistics in terms of power and a novel unbiased cluster detection criterion. These methods are then applied to the well-known New York leukemia dataset and a Wisconsin breast cancer incidence dataset. © 2011, The International Biometric Society.
Local multiplicity adjustment for the spatial scan statistic using the Gumbel distribution
Gangnon, Ronald E.
2011-01-01
Summary The spatial scan statistic is an important and widely used tool for cluster detection. It is based on the simultaneous evaluation of the statistical significance of the maximum likelihood ratio test statistic over a large collection of potential clusters. In most cluster detection problems, there is variation in the extent of local multiplicity across the study region. For example, using a fixed maximum geographic radius for clusters, urban areas typically have many overlapping potential clusters, while rural areas have relatively few. The spatial scan statistic does not account for local multiplicity variation. We describe a previously proposed local multiplicity adjustment based on a nested Bonferroni correction and propose a novel adjustment based on a Gumbel distribution approximation to the distribution of a local scan statistic. We compare the performance of all three statistics in terms of power and a novel unbiased cluster detection criterion. These methods are then applied to the well-known New York leukemia dataset and a Wisconsin breast cancer incidence dataset. PMID:21762118
AlRyalat, Saif Aldeen
2017-01-01
Gender similarities and differences have long been a matter of debate in almost all human research, especially upon reaching the discussion about brain functions. This large scale meta-analysis was performed on functional MRI studies. It included more than 700 active brain foci from more than 70 different experiments to study gender related similarities and differences in brain activation strategies for three of the main brain functions: Visual-spatial cognition, memory, and emotion. Areas that are significantly activated by both genders (i.e. core areas) for the tested brain function are mentioned, whereas those areas significantly activated exclusively in one gender are the gender specific areas. During visual-spatial cognition task, and in addition to the core areas, males significantly activated their left superior frontal gyrus, compared with left superior parietal lobule in females. For memory tasks, several different brain areas activated by each gender, but females significantly activated two areas from the limbic system during memory retrieval tasks. For emotional task, males tend to recruit their bilateral prefrontal regions, whereas females tend to recruit their bilateral amygdalae. This meta-analysis provides an overview based on functional MRI studies on how males and females use their brain.
Urquhart, Erin A; Schaeffer, Blake A; Stumpf, Richard P; Loftin, Keith A; Werdell, P Jeremy
2017-07-01
Cyanobacterial harmful algal blooms (CyanoHAB) are thought to be increasing globally over the past few decades, but relatively little quantitative information is available about the spatial extent of blooms. Satellite remote sensing provides a potential technology for identifying cyanoHABs in multiple water bodies and across geo-political boundaries. An assessment method was developed using MEdium Resolution Imaging Spectrometer (MERIS) imagery to quantify cyanoHAB surface area extent, transferable to different spatial areas, in Florida, Ohio, and California for the test period of 2008 to 2012. Temporal assessment was used to evaluate changes in satellite resolvable inland waterbodies for each state of interest. To further assess cyanoHAB risk within the states, the World Health Organization's (WHO) recreational guidance level thresholds were used to categorize surface area of cyanoHABs into three risk categories: low, moderate, and high-risk bloom area. Results showed that in Florida, the area of cyanoHABs increased largely due to observed increases in high-risk bloom area. California exhibited a slight decrease in cyanoHAB extent, primarily attributed to decreases in Northern California. In Ohio (excluding Lake Erie), little change in cyanoHAB surface area was observed. This study uses satellite remote sensing to quantify changes in inland cyanoHAB surface area across numerous water bodies within an entire state. The temporal assessment method developed here will be relevant into the future as it is transferable to the Ocean Land Colour Instrument (OLCI) on Sentinel-3A/3B missions. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.
Urquhart, Erin A.; Schaeffer, Blake A.; Stumpf, Richard P.; Loftin, Keith A.; Werdell, P. Jeremy
2017-01-01
Cyanobacterial harmful algal blooms (CyanoHAB) are thought to be increasing globally over the past few decades, but relatively little quantitative information is available about the spatial extent of blooms. Satellite remote sensing provides a potential technology for identifying cyanoHABs in multiple water bodies and across geo-political boundaries. An assessment method was developed using MEdium Resolution Imaging Spectrometer (MERIS) imagery to quantify cyanoHAB surface area extent, transferable to different spatial areas, in Florida, Ohio, and California for the test period of 2008 to 2012. Temporal assessment was used to evaluate changes in satellite resolvable inland waterbodies for each state of interest. To further assess cyanoHAB risk within the states, the World Health Organization’s (WHO) recreational guidance level thresholds were used to categorize surface area of cyanoHABs into three risk categories: low, moderate, and high-risk bloom area. Results showed that in Florida, the area of cyanoHABs increased largely due to observed increases in high-risk bloom area. California exhibited a slight decrease in cyanoHAB extent, primarily attributed to decreases in Northern California. In Ohio (excluding Lake Erie), little change in cyanoHAB surface area was observed. This study uses satellite remote sensing to quantify changes in inland cyanoHAB surface area across numerous water bodies within an entire state. The temporal assessment method developed here will be relevant into the future as it is transferable to the Ocean Land Colour Instrument (OLCI) on Sentinel-3A/3B missions.
Evaluation of commercial available fusion algorithms for Geoeye data
NASA Astrophysics Data System (ADS)
Vaiopoulos, Aristides D.; Nikolakopoulos, Konstantinos G.
2013-10-01
In this study ten commercial available fusion techniques and more especially the Ehlers, Gram-Schmidt, High Pass Filter, Local Mean Matching (LMM), Local Mean and Variance Matching (LMVM), Modified IHS (ModIHS), Pansharp, PCA, HCS (Hyperspherical Color Space) and Wavelet were used for the fusion of Geoeye panchromatic and multispectral data. The panchromatic data have a spatial resolution of 0.5m while the multispectral data have a spatial resolution of 2.0m. The optical result, the statistical parameters and different quality indexes such as ERGAS, Q, entropy were examined and the results are presented. The broader area of Pendeli mountain near to the city of Athens Greece and more especially two sub areas with different characteristics were chosen for the comparison. The first sub area is located at the edge of the urban fabric and combines at the same time the characteristics of an urban and a rural area. The second sub area comprises a large open quarry and it is suitable to examine which fused product is more suitable for mine monitoring.
Spatial distribution of vehicle emission inventories in the Federal District, Brazil
NASA Astrophysics Data System (ADS)
Réquia, Weeberb João; Koutrakis, Petros; Roig, Henrique Llacer
2015-07-01
Air pollution poses an important public health risk, especially in large urban areas. Information about the spatial distribution of air pollutants can be used as a tool for developing public policies to reduce source emissions. Air pollution monitoring networks provide information about pollutant concentrations; however, they are not available in every urban area. Among the 5570 cities in Brazil, for example, only 1.7% of them have air pollution monitoring networks. In this study we assess vehicle emissions for main traffic routes of the Federal District (state of Brazil) and characterize their spatial patterns. Toward this end, we used a bottom-up method to predict emissions and to characterize their spatial patterns using Global Moran's (Spatial autocorrelation analysis) and Getis-Ord General G (High/Low cluster analysis). Our findings suggested that light duty vehicles are primarily responsible for the vehicular emissions of CO (68.9%), CH4 (93.6%), and CO2 (57.9%), whereas heavy duty vehicles are primarily responsible for the vehicular emissions of NMHC (92.9%), NOx (90.7%), and PM (97.4%). Furthermore, CO2 is the pollutant with the highest emissions, over 30 million tons/year. In the spatial autocorrelation analysis was identified cluster (p < 0.01) for all types of vehicles and for all pollutants. However, we identified high cluster only for the light vehicles.
Testing the dual-pathway model for auditory processing in human cortex.
Zündorf, Ida C; Lewald, Jörg; Karnath, Hans-Otto
2016-01-01
Analogous to the visual system, auditory information has been proposed to be processed in two largely segregated streams: an anteroventral ("what") pathway mainly subserving sound identification and a posterodorsal ("where") stream mainly subserving sound localization. Despite the popularity of this assumption, the degree of separation of spatial and non-spatial auditory information processing in cortex is still under discussion. In the present study, a statistical approach was implemented to investigate potential behavioral dissociations for spatial and non-spatial auditory processing in stroke patients, and voxel-wise lesion analyses were used to uncover their neural correlates. The results generally provided support for anatomically and functionally segregated auditory networks. However, some degree of anatomo-functional overlap between "what" and "where" aspects of processing was found in the superior pars opercularis of right inferior frontal gyrus (Brodmann area 44), suggesting the potential existence of a shared target area of both auditory streams in this region. Moreover, beyond the typically defined posterodorsal stream (i.e., posterior superior temporal gyrus, inferior parietal lobule, and superior frontal sulcus), occipital lesions were found to be associated with sound localization deficits. These results, indicating anatomically and functionally complex cortical networks for spatial and non-spatial auditory processing, are roughly consistent with the dual-pathway model of auditory processing in its original form, but argue for the need to refine and extend this widely accepted hypothesis. Copyright © 2015 Elsevier Inc. All rights reserved.
Crist, Michele R.; Knick, Steven T.; Hanser, Steven E.
2017-01-01
The delineation of priority areas in western North America for managing Greater Sage-Grouse (Centrocercus urophasianus) represents a broad-scale experiment in conservation biology. The strategy of limiting spatial disturbance and focusing conservation actions within delineated areas may benefit the greatest proportion of Greater Sage-Grouse. However, land use under normal restrictions outside priority areas potentially limits dispersal and gene flow, which can isolate priority areas and lead to spatially disjunct populations. We used graph theory, representing priority areas as spatially distributed nodes interconnected by movement corridors, to understand the capacity of priority areas to function as connected networks in the Bi-State, Central, and Washington regions of the Greater Sage-Grouse range. The Bi-State and Central networks were highly centralized; the dominant pathways and shortest linkages primarily connected a small number of large and centrally located priority areas. These priority areas are likely strongholds for Greater Sage-Grouse populations and might also function as refugia and sources. Priority areas in the Central network were more connected than those in the Bi-State and Washington networks. Almost 90% of the priority areas in the Central network had ≥2 pathways to other priority areas when movement through the landscape was set at an upper threshold (effective resistance, ER12). At a lower threshold (ER4), 83 of 123 priority areas in the Central network were clustered in 9 interconnected subgroups. The current conservation strategy has risks; 45 of 61 priority areas in the Bi-State network, 68 of 123 in the Central network, and all 4 priority areas in the Washington network had ≤1 connection to another priority area at the lower ER4threshold. Priority areas with few linkages also averaged greater environmental resistance to movement along connecting pathways. Without maintaining corridors to larger priority areas or a clustered group, isolation of small priority areas could lead to regional loss of Greater Sage-Grouse
Clark, Amy E
2016-05-06
The spatial structure of archeological sites can help reconstruct the settlement dynamics of hunter-gatherers by providing information on the number and length of occupations. This study seeks to access this information through a comparison of seven sites. These sites are open-air and were all excavated over large spatial areas, up to 2,000 m(2) , and are therefore ideal for spatial analysis, which was done using two complementary methods, lithic refitting and density zones. Both methods were assessed statistically using confidence intervals. The statistically significant results from each site were then compiled to evaluate trends that occur across the seven sites. These results were used to assess the "spatial consistency" of each assemblage and, through that, the number and duration of occupations. This study demonstrates that spatial analysis can be a powerful tool in research on occupation dynamics and can help disentangle the many occupations that often make up an archeological assemblage. © 2016 Wiley Periodicals, Inc.
VoPham, Trang; Hart, Jaime E; Laden, Francine; Chiang, Yao-Yi
2018-04-17
Geospatial artificial intelligence (geoAI) is an emerging scientific discipline that combines innovations in spatial science, artificial intelligence methods in machine learning (e.g., deep learning), data mining, and high-performance computing to extract knowledge from spatial big data. In environmental epidemiology, exposure modeling is a commonly used approach to conduct exposure assessment to determine the distribution of exposures in study populations. geoAI technologies provide important advantages for exposure modeling in environmental epidemiology, including the ability to incorporate large amounts of big spatial and temporal data in a variety of formats; computational efficiency; flexibility in algorithms and workflows to accommodate relevant characteristics of spatial (environmental) processes including spatial nonstationarity; and scalability to model other environmental exposures across different geographic areas. The objectives of this commentary are to provide an overview of key concepts surrounding the evolving and interdisciplinary field of geoAI including spatial data science, machine learning, deep learning, and data mining; recent geoAI applications in research; and potential future directions for geoAI in environmental epidemiology.
PLANNING AND RESPONSE IN THE AFTERMATH OF A LARGE CRISIS: AN AGENT-BASED INFORMATICS FRAMEWORK*
Barrett, Christopher; Bisset, Keith; Chandan, Shridhar; Chen, Jiangzhuo; Chungbaek, Youngyun; Eubank, Stephen; Evrenosoğlu, Yaman; Lewis, Bryan; Lum, Kristian; Marathe, Achla; Marathe, Madhav; Mortveit, Henning; Parikh, Nidhi; Phadke, Arun; Reed, Jeffrey; Rivers, Caitlin; Saha, Sudip; Stretz, Paula; Swarup, Samarth; Thorp, James; Vullikanti, Anil; Xie, Dawen
2014-01-01
We present a synthetic information and modeling environment that can allow policy makers to study various counter-factual experiments in the event of a large human-initiated crisis. The specific scenario we consider is a ground detonation caused by an improvised nuclear device in a large urban region. In contrast to earlier work in this area that focuses largely on the prompt effects on human health and injury, we focus on co-evolution of individual and collective behavior and its interaction with the differentially damaged infrastructure. This allows us to study short term secondary and tertiary effects. The present environment is suitable for studying the dynamical outcomes over a two week period after the initial blast. A novel computing and data processing architecture is described; the architecture allows us to represent multiple co-evolving infrastructures and social networks at a highly resolved temporal, spatial, and individual scale. The representation allows us to study the emergent behavior of individuals as well as specific strategies to reduce casualties and injuries that exploit the spatial and temporal nature of the secondary and tertiary effects. A number of important conclusions are obtained using the modeling environment. For example, the studies decisively show that deploying ad hoc communication networks to reach individuals in the affected area is likely to have a significant impact on the overall casualties and injuries. PMID:25580055
PLANNING AND RESPONSE IN THE AFTERMATH OF A LARGE CRISIS: AN AGENT-BASED INFORMATICS FRAMEWORK*
Barrett, Christopher; Bisset, Keith; Chandan, Shridhar; Chen, Jiangzhuo; Chungbaek, Youngyun; Eubank, Stephen; Evrenosoğlu, Yaman; Lewis, Bryan; Lum, Kristian; Marathe, Achla; Marathe, Madhav; Mortveit, Henning; Parikh, Nidhi; Phadke, Arun; Reed, Jeffrey; Rivers, Caitlin; Saha, Sudip; Stretz, Paula; Swarup, Samarth; Thorp, James; Vullikanti, Anil; Xie, Dawen
2013-01-01
We present a synthetic information and modeling environment that can allow policy makers to study various counter-factual experiments in the event of a large human-initiated crisis. The specific scenario we consider is a ground detonation caused by an improvised nuclear device in a large urban region. In contrast to earlier work in this area that focuses largely on the prompt effects on human health and injury, we focus on co-evolution of individual and collective behavior and its interaction with the differentially damaged infrastructure. This allows us to study short term secondary and tertiary effects. The present environment is suitable for studying the dynamical outcomes over a two week period after the initial blast. A novel computing and data processing architecture is described; the architecture allows us to represent multiple co-evolving infrastructures and social networks at a highly resolved temporal, spatial, and individual scale. The representation allows us to study the emergent behavior of individuals as well as specific strategies to reduce casualties and injuries that exploit the spatial and temporal nature of the secondary and tertiary effects. A number of important conclusions are obtained using the modeling environment. For example, the studies decisively show that deploying ad hoc communication networks to reach individuals in the affected area is likely to have a significant impact on the overall casualties and injuries.
West, Amanda; Kumar, Sunil; Jarnevich, Catherine S.
2016-01-01
Regional analysis of large wildfire potential given climate change scenarios is crucial to understanding areas most at risk in the future, yet wildfire models are not often developed and tested at this spatial scale. We fit three historical climate suitability models for large wildfires (i.e. ≥ 400 ha) in Colorado andWyoming using topography and decadal climate averages corresponding to wildfire occurrence at the same temporal scale. The historical models classified points of known large wildfire occurrence with high accuracies. Using a novel approach in wildfire modeling, we applied the historical models to independent climate and wildfire datasets, and the resulting sensitivities were 0.75, 0.81, and 0.83 for Maxent, Generalized Linear, and Multivariate Adaptive Regression Splines, respectively. We projected the historic models into future climate space using data from 15 global circulation models and two representative concentration pathway scenarios. Maps from these geospatial analyses can be used to evaluate the changing spatial distribution of climate suitability of large wildfires in these states. April relative humidity was the most important covariate in all models, providing insight to the climate space of large wildfires in this region. These methods incorporate monthly and seasonal climate averages at a spatial resolution relevant to land management (i.e. 1 km2) and provide a tool that can be modified for other regions of North America, or adapted for other parts of the world.
Spatial Distribution of Ozone Precursors in the Uinta Basin
NASA Astrophysics Data System (ADS)
Mangum, C. D.; Lyman, S. N.
2012-12-01
Wintertime ozone mixing ratios in the Uinta Basin of Utah exceeding the EPA National Ambient Air Quality Standards measured during 2010 and 2011 led to a large campaign carried out in 2012 that included a study of the spatial distribution of ozone precursors in the Basin. In this study, speciated hydrocarbon mixing ratios (compounds with 6-11 carbon atoms) were measure at 10 sites around the Uinta Basin with Radiello passive samplers, and NO2, NO, and NOx (NO2 + NO) mixing ratios were measured at 16 sites with Ogawa passive sampler and active sampling instruments. Analysis of the Radiello passive samplers was carried out by CS2 desorption and analyzed on a Shimadzu QP-2010 GCMS. Analysis of the Ogawa passive samplers was done via 18.2 megohm water extraction and analyzed with a Dionex ICS-3000 ion chromatography system. February average hydrocarbon mixing ratios were highest in the area of maximum gas production (64.5 ppb as C3), lower in areas of oil production (24.3-30.0 ppb as C3), and lowest in urban areas and on the Basin rim (1.7-17.0 ppb as C3). February average for NOx was highest in the most densely populated urban area, Vernal (11.2 ppb), lower in in the area of maximum gas production (6.1 ppb), and lower still in areas of oil production and on the Basin Rim (0.6-2.7 ppb). Hydrocarbon speciation showed significant differences in spatial distribution around the Basin. Higher mixing ratios of toluene and other aromatics were much more prevalent in gas producing areas than oil producing areas. Similar mixing ratios of straight-chain alkane were observed in both areas. Higher mixing ratios of cycloalkanes were slightly more prevalent in gas producing than oil producing areas.
Christianen, M J A; Middelburg, J J; Holthuijsen, S J; Jouta, J; Compton, T J; van der Heide, T; Piersma, T; Sinninghe Damsté, J S; van der Veer, H W; Schouten, S; Olff, H
2017-06-01
Coastal food webs can be supported by local benthic or pelagic primary producers and by the import of organic matter. Distinguishing between these energy sources is essential for our understanding of ecosystem functioning. However, the relative contribution of these components to the food web at the landscape scale is often unclear, as many studies lack good taxonomic and spatial resolution across large areas. Here, using stable carbon isotopes, we report on the primary carbon sources for consumers and their spatial variability across one of the world's largest intertidal ecosystems (Dutch Wadden Sea; 1460 km 2 intertidal surface area), at an exceptionally high taxonomic (178 species) and spatial resolution (9,165 samples from 839 locations). The absence of overlap in δ 13 C values between consumers and terrestrial organic matter suggests that benthic and pelagic producers dominate carbon input into this food web. In combination with the consistent enrichment of benthic primary producers (δ 13 C -16.3‰) relative to pelagic primary producers (δ 13 C -18.8) across the landscape, this allowed the use of a two-food-source isotope-mixing model. This spatially resolved modelling revealed that benthic primary producers (microphytobenthos) are the most important energy source for the majority of consumers at higher trophic levels (worms, molluscs, crustaceans, fish, and birds), and thus to the whole food web. In addition, we found large spatial heterogeneity in the δ 13 C values of benthic primary producers (δ 13 C -19.2 to -11.5‰) and primary consumers (δ 13 C -25.5 to -9.9‰), emphasizing the need for spatially explicit sampling of benthic and pelagic primary producers in coastal ecosystems. Our findings have important implications for our understanding of the functioning of ecological networks and for the management of coastal ecosystems. © 2017 by the Ecological Society of America.
Coexistence between wildlife and humans at fine spatial scales.
Carter, Neil H; Shrestha, Binoj K; Karki, Jhamak B; Pradhan, Narendra Man Babu; Liu, Jianguo
2012-09-18
Many wildlife species face imminent extinction because of human impacts, and therefore, a prevailing belief is that some wildlife species, particularly large carnivores and ungulates, cannot coexist with people at fine spatial scales (i.e., cannot regularly use the exact same point locations). This belief provides rationale for various conservation programs, such as resettling human communities outside protected areas. However, quantitative information on the capacity and mechanisms for wildlife to coexist with humans at fine spatial scales is scarce. Such information is vital, because the world is becoming increasingly crowded. Here, we provide empirical information about the capacity and mechanisms for tigers (a globally endangered species) to coexist with humans at fine spatial scales inside and outside Nepal's Chitwan National Park, a flagship protected area for imperiled wildlife. Information obtained from field cameras in 2010 and 2011 indicated that human presence (i.e., people on foot and vehicles) was ubiquitous and abundant throughout the study site; however, tiger density was also high. Surprisingly, even at a fine spatial scale (i.e., camera locations), tigers spatially overlapped with people on foot and vehicles in both years. However, in both years, tigers offset their temporal activity patterns to be much less active during the day when human activity peaked. In addition to temporal displacement, tiger-human coexistence was likely enhanced by abundant tiger prey and low levels of tiger poaching. Incorporating fine-scale spatial and temporal activity patterns into conservation plans can help address a major global challenge-meeting human needs while sustaining wildlife.
Age-related macular degeneration changes the processing of visual scenes in the brain.
Ramanoël, Stephen; Chokron, Sylvie; Hera, Ruxandra; Kauffmann, Louise; Chiquet, Christophe; Krainik, Alexandre; Peyrin, Carole
2018-01-01
In age-related macular degeneration (AMD), the processing of fine details in a visual scene, based on a high spatial frequency processing, is impaired, while the processing of global shapes, based on a low spatial frequency processing, is relatively well preserved. The present fMRI study aimed to investigate the residual abilities and functional brain changes of spatial frequency processing in visual scenes in AMD patients. AMD patients and normally sighted elderly participants performed a categorization task using large black and white photographs of scenes (indoors vs. outdoors) filtered in low and high spatial frequencies, and nonfiltered. The study also explored the effect of luminance contrast on the processing of high spatial frequencies. The contrast across scenes was either unmodified or equalized using a root-mean-square contrast normalization in order to increase contrast in high-pass filtered scenes. Performance was lower for high-pass filtered scenes than for low-pass and nonfiltered scenes, for both AMD patients and controls. The deficit for processing high spatial frequencies was more pronounced in AMD patients than in controls and was associated with lower activity for patients than controls not only in the occipital areas dedicated to central and peripheral visual fields but also in a distant cerebral region specialized for scene perception, the parahippocampal place area. Increasing the contrast improved the processing of high spatial frequency content and spurred activation of the occipital cortex for AMD patients. These findings may lead to new perspectives for rehabilitation procedures for AMD patients.
Socio-Spatial Patterning of Off-Sale and On-Sale Alcohol Outlets in a Texas City
Han, Daikwon; Gorman, Dennis M.
2014-01-01
Introduction and Aims To examine the socio-spatial patterning of off-sale and on-sale alcohol outlets following a policy change that ended prohibition of off-sale outlets in Lubbock, Texas. Design and Methods The spatial patterning of alcohol outlets by licensing type was examined using the k-function difference (D statistic) to compare the relative degree of spatial aggregation of the two types of alcohol outlets and by the spatial scan statistic to identify statistically significant geographic clusters of outlets. The sociodemographic characteristics of the areas containing clusters of outlets were compared to the rest of the city. In addition, the socioeconomic characteristics of census block groups with and without existing on-sale outlets were compared, as were the socioeconomic characteristics of census block groups with and without the newly issued off-sale licenses. Results The existing on-sale premises in Lubbock and the newly established off-sale premises introduced as a result of the 2009 policy change displayed different spatial patterns, with the latter being more spatially dispersed. A large cluster of on-sale outlets identified in the north-east of the city was located in a socially and economically disadvantaged area of the city. Discussion and Conclusion The findings support the view that it is important to understand the local context of deprivation within a city when examining the location of alcohol outlets and add to the existing research by drawing attention to the importance of geographic scale in assessing such relationships. PMID:24320205
Socio-spatial patterning of off-sale and on-sale alcohol outlets in a Texas city.
Han, Daikwon; Gorman, Dennis M
2014-03-01
To examine the socio-spatial patterning of off-sale and on-sale alcohol outlets following a policy change that ended prohibition of off-sale outlets in Lubbock, Texas. The spatial patterning of alcohol outlets by licensing type was examined using the k-function difference (D statistic) to compare the relative degree of spatial aggregation of the two types of alcohol outlets and by the spatial scan statistic to identify statistically significant geographic clusters of outlets. The sociodemographic characteristics of the areas containing clusters of outlets were compared with the rest of the city. In addition, the socioeconomic characteristics of census block groups with and without existing on-sale outlets were compared, as were the socioeconomic characteristics of census block groups with and without the newly issued off-sale licenses. The existing on-sale premises in Lubbock and the newly established off-sale premises introduced as a result of the 2009 policy change displayed different spatial patterns, with the latter being more spatially dispersed. A large cluster of on-sale outlets identified in the north-east of the city was located in a socially and economically disadvantaged area of the city. The findings support the view that it is important to understand the local context of deprivation within a city when examining the location of alcohol outlets and add to the existing research by drawing attention to the importance of geographic scale in assessing such relationships. © 2013 Australasian Professional Society on Alcohol and other Drugs.
Deliano, Matthias; Scheich, Henning; Ohl, Frank W
2009-12-16
Several studies have shown that animals can learn to make specific use of intracortical microstimulation (ICMS) of sensory cortex within behavioral tasks. Here, we investigate how the focal, artificial activation by ICMS leads to a meaningful, behaviorally interpretable signal. In natural learning, this involves large-scale activity patterns in widespread brain-networks. We therefore trained gerbils to discriminate closely neighboring ICMS sites within primary auditory cortex producing evoked responses largely overlapping in space. In parallel, during training, we recorded electrocorticograms (ECoGs) at high spatial resolution. Applying a multivariate classification procedure, we identified late spatial patterns that emerged with discrimination learning from the ongoing poststimulus ECoG. These patterns contained information about the preceding conditioned stimulus, and were associated with a subsequent correct behavioral response by the animal. Thereby, relevant pattern information was mainly carried by neuron populations outside the range of the lateral spatial spread of ICMS-evoked cortical activation (approximately 1.2 mm). This demonstrates that the stimulated cortical area not only encoded information about the stimulation sites by its focal, stimulus-driven activation, but also provided meaningful signals in its ongoing activity related to the interpretation of ICMS learned by the animal. This involved the stimulated area as a whole, and apparently required large-scale integration in the brain. However, ICMS locally interfered with the ongoing cortical dynamics by suppressing pattern formation near the stimulation sites. The interaction between ICMS and ongoing cortical activity has several implications for the design of ICMS protocols and cortical neuroprostheses, since the meaningful interpretation of ICMS depends on this interaction.
The scaling of contact rates with population density for the infectious disease models.
Hu, Hao; Nigmatulina, Karima; Eckhoff, Philip
2013-08-01
Contact rates and patterns among individuals in a geographic area drive transmission of directly-transmitted pathogens, making it essential to understand and estimate contacts for simulation of disease dynamics. Under the uniform mixing assumption, one of two mechanisms is typically used to describe the relation between contact rate and population density: density-dependent or frequency-dependent. Based on existing evidence of population threshold and human mobility patterns, we formulated a spatial contact model to describe the appropriate form of transmission with initial growth at low density and saturation at higher density. We show that the two mechanisms are extreme cases that do not capture real population movement across all scales. Empirical data of human and wildlife diseases indicate that a nonlinear function may work better when looking at the full spectrum of densities. This estimation can be applied to large areas with population mixing in general activities. For crowds with unusually large densities (e.g., transportation terminals, stadiums, or mass gatherings), the lack of organized social contact structure deviates the physical contacts towards a special case of the spatial contact model - the dynamics of kinetic gas molecule collision. In this case, an ideal gas model with van der Waals correction fits well; existing movement observation data and the contact rate between individuals is estimated using kinetic theory. A complete picture of contact rate scaling with population density may help clarify the definition of transmission rates in heterogeneous, large-scale spatial systems. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.
Towards a New Assessment of Urban Areas from Local to Global Scales
NASA Astrophysics Data System (ADS)
Bhaduri, B. L.; Roy Chowdhury, P. K.; McKee, J.; Weaver, J.; Bright, E.; Weber, E.
2015-12-01
Since early 2000s, starting with NASA MODIS, satellite based remote sensing has facilitated collection of imagery with medium spatial resolution but high temporal resolution (daily). This trend continues with an increasing number of sensors and data products. Increasing spatial and temporal resolutions of remotely sensed data archives, from both public and commercial sources, have significantly enhanced the quality of mapping and change data products. However, even with automation of such analysis on evolving computing platforms, rates of data processing have been suboptimal largely because of the ever-increasing pixel to processor ratio coupled with limitations of the computing architectures. Novel approaches utilizing spatiotemporal data mining techniques and computational architectures have emerged that demonstrates the potential for sustained and geographically scalable landscape monitoring to be operational. We exemplify this challenge with two broad research initiatives on High Performance Geocomputation at Oak Ridge National Laboratory: (a) mapping global settlement distribution; (b) developing national critical infrastructure databases. Our present effort, on large GPU based architectures, to exploit high resolution (1m or less) satellite and airborne imagery for extracting settlements at global scale is yielding understanding of human settlement patterns and urban areas at unprecedented resolution. Comparison of such urban land cover database, with existing national and global land cover products, at various geographic scales in selected parts of the world is revealing intriguing patterns and insights for urban assessment. Early results, from the USA, Taiwan, and Egypt, indicate closer agreements (5-10%) in urban area assessments among databases at larger, aggregated geographic extents. However, spatial variability at local scales could be significantly different (over 50% disagreement).
Meng, Ran; Wu, Jin; Zhao, Feng; ...
2018-06-01
Understanding post-fire forest recovery is pivotal to the study of forest dynamics and global carbon cycle. Field-based studies indicated a convex response of forest recovery rate to burn severity at the individual tree level, related with fire-induced tree mortality; however, these findings were constrained in spatial/temporal extents, while not detectable by traditional optical remote sensing studies, largely attributing to the contaminated effect from understory recovery. For this work, we examined whether the combined use of multi-sensor remote sensing techniques (i.e., 1m simultaneous airborne imaging spectroscopy and LiDAR and 2m satellite multi-spectral imagery) to separate canopy recovery from understory recovery wouldmore » enable to quantify post-fire forest recovery rate spanning a large gradient in burn severity over large-scales. Our study was conducted in a mixed pine-oak forest in Long Island, NY, three years after a top-killing fire. Our studies remotely detected an initial increase and then decline of forest recovery rate to burn severity across the burned area, with a maximum canopy area-based recovery rate of 10% per year at moderate forest burn severity class. More intriguingly, such remotely detected convex relationships also held at species level, with pine trees being more resilient to high burn severity and having a higher maximum recovery rate (12% per year) than oak trees (4% per year). These results are one of the first quantitative evidences showing the effects of fire adaptive strategies on post-fire forest recovery, derived from relatively large spatial-temporal domains. Our study thus provides the methodological advance to link multi-sensor remote sensing techniques to monitor forest dynamics in a spatially explicit manner over large-scales, with important implications for fire-related forest management, and for constraining/benchmarking fire effect schemes in ecological process models.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Meng, Ran; Wu, Jin; Zhao, Feng
Understanding post-fire forest recovery is pivotal to the study of forest dynamics and global carbon cycle. Field-based studies indicated a convex response of forest recovery rate to burn severity at the individual tree level, related with fire-induced tree mortality; however, these findings were constrained in spatial/temporal extents, while not detectable by traditional optical remote sensing studies, largely attributing to the contaminated effect from understory recovery. For this work, we examined whether the combined use of multi-sensor remote sensing techniques (i.e., 1m simultaneous airborne imaging spectroscopy and LiDAR and 2m satellite multi-spectral imagery) to separate canopy recovery from understory recovery wouldmore » enable to quantify post-fire forest recovery rate spanning a large gradient in burn severity over large-scales. Our study was conducted in a mixed pine-oak forest in Long Island, NY, three years after a top-killing fire. Our studies remotely detected an initial increase and then decline of forest recovery rate to burn severity across the burned area, with a maximum canopy area-based recovery rate of 10% per year at moderate forest burn severity class. More intriguingly, such remotely detected convex relationships also held at species level, with pine trees being more resilient to high burn severity and having a higher maximum recovery rate (12% per year) than oak trees (4% per year). These results are one of the first quantitative evidences showing the effects of fire adaptive strategies on post-fire forest recovery, derived from relatively large spatial-temporal domains. Our study thus provides the methodological advance to link multi-sensor remote sensing techniques to monitor forest dynamics in a spatially explicit manner over large-scales, with important implications for fire-related forest management, and for constraining/benchmarking fire effect schemes in ecological process models.« less
The History of the M31 Disk from Resolved Stellar Populations as Seen by PHAT
NASA Astrophysics Data System (ADS)
Lewis, A. R.; Dalcanton, J. J.; Dolphin, A. E.; Weisz, D. R.; Williams, B. F.; PHAT Collaboration
2014-03-01
The Panchromatic Hubble Andromeda Treasury (PHAT) is an HST multi-cycle treasury program that is mapping the resolved stellar populations of ˜1/3 of M31 from the UV through the near-IR. These data provide color and luminosity information for more than 150 million stars in the M31 disk. We use stellar evolution models to fit the luminous main sequence to derive spatially-resolved recent star formation histories (SFHs) over large areas of M31 with 50-100 pc resolution. These include individual star-forming regions as well as quiescent portions of the disk. We use the gridded SFHs to create movies of star formation activity to study the evolution of individual star-forming events across the disk. Outside of the star-forming regions, we use our resolved stellar photometry to derive the full SFHs of larger regions. These allow us to probe spatial and temporal trends in age and metallicity across a large radial baseline, providing constraints on the global formation and evolution of the disk over a Hubble time. M31 is the only large disk galaxy that is close enough to obtain the photometry necessary for this type of spatially-resolved SFH mapping.
Designing Exhibits for Gender Equity
ERIC Educational Resources Information Center
Dancu, Toni Nicole
2010-01-01
Gender equity has been a national and global aim for over half a century (Ceci & Williams, 2007; National Center for Education Statistics, 2003; National Science Board, 2008). While gains have been made, one area where inequity remains is spatial reasoning ability, where a large gender gap in favor of males has persisted over the years…
Evidence of biotic resistance to invasions in forests of the Eastern USA
Basil V. Iannone III; Kevin M. Potter; Kelly-Ann Dixon Hamil; Whitney Huang; Hao Zhang; Qinfeng Guo; Christopher M. Oswalt; Christopher W. Woodall; Songlin Fei
2016-01-01
Context Detecting biotic resistance to biological invasions across large geographic areas may require acknowledging multiple metrics of niche usage and potential spatial heterogeneity in associations between invasive and native species diversity and dominance.Objectives Determine (1) if native communities are ...
Robert. R. Ziemer
1991-01-01
Summary - There is increasing concern about how land management practices influence the frequency of mass erosion and sedimentation over large temporal and spatial scales. Monte Carlo simulations can identify fruitful areas for continuing cooperation between scientists in the U.S.A. and Japan.
A computational method for optimizing fuel treatment locations
Mark A. Finney
2006-01-01
Modeling and experiments have suggested that spatial fuel treatment patterns can influence the movement of large fires. On simple theoretical landscapes consisting of two fuel types (treated and untreated) optimal patterns can be analytically derived that disrupt fire growth efficiently (i.e. with less area treated than random patterns). Although conceptually simple,...
USDA-ARS?s Scientific Manuscript database
The estimation of spatial patterns in surface fluxes from aircraft observations poses several challenges in presence of heterogeneous land cover. In particular, the effects of turbulence on scalar transport and the different behavior of passive (e.g. moisture) versus active (e.g. temperature) scalar...
NASA Astrophysics Data System (ADS)
Lee, Joong Gwang; Nietch, Christopher T.; Panguluri, Srinivas
2018-05-01
Urban stormwater runoff quantity and quality are strongly dependent upon catchment properties. Models are used to simulate the runoff characteristics, but the output from a stormwater management model is dependent on how the catchment area is subdivided and represented as spatial elements. For green infrastructure modeling, we suggest a discretization method that distinguishes directly connected impervious area (DCIA) from the total impervious area (TIA). Pervious buffers, which receive runoff from upgradient impervious areas should also be identified as a separate subset of the entire pervious area (PA). This separation provides an improved model representation of the runoff process. With these criteria in mind, an approach to spatial discretization for projects using the US Environmental Protection Agency's Storm Water Management Model (SWMM) is demonstrated for the Shayler Crossing watershed (SHC), a well-monitored, residential suburban area occupying 100 ha, east of Cincinnati, Ohio. The model relies on a highly resolved spatial database of urban land cover, stormwater drainage features, and topography. To verify the spatial discretization approach, a hypothetical analysis was conducted. Six different representations of a common urbanscape that discharges runoff to a single storm inlet were evaluated with eight 24 h synthetic storms. This analysis allowed us to select a discretization scheme that balances complexity in model setup with presumed accuracy of the output with respect to the most complex discretization option considered. The balanced approach delineates directly and indirectly connected impervious areas (ICIA), buffering pervious area (BPA) receiving impervious runoff, and the other pervious area within a SWMM subcatchment. It performed well at the watershed scale with minimal calibration effort (Nash-Sutcliffe coefficient = 0.852; R2 = 0.871). The approach accommodates the distribution of runoff contributions from different spatial components and flow pathways that would impact green infrastructure performance. A developed SWMM model using the discretization approach is calibrated by adjusting parameters per land cover component, instead of per subcatchment and, therefore, can be applied to relatively large watersheds if the land cover components are relatively homogeneous and/or categorized appropriately in the GIS that supports the model parameterization. Finally, with a few model adjustments, we show how the simulated stream hydrograph can be separated into the relative contributions from different land cover types and subsurface sources, adding insight to the potential effectiveness of planned green infrastructure scenarios at the watershed scale.
Zhang, Yan; Chen, Lujun; Sun, Renhua; Dai, Tianjiao; Tian, Jinping; Zheng, Wei; Wen, Donghui
2016-06-01
Anthropogenic activities usually contaminate water environments, and have led to the eutrophication of many estuaries and shifts in microbial communities. In this study, the temporal and spatial changes of the microbial community in an industrial effluent receiving area in Hangzhou Bay were investigated by 454 pyrosequencing. The bacterial community showed higher richness and biodiversity than the archaeal community in all sediments. Proteobacteria dominated in the bacterial communities of all the samples; Marine_Group_I and Methanomicrobia were the two dominant archaeal classes in the effluent receiving area. PCoA and AMOVA revealed strong seasonal but minor spatial changes in both bacterial and archaeal communities in the sediments. The seasonal changes of the bacterial community were less significant than those of the archaeal community, which mainly consisted of fluctuations in abundance of a large proportion of longstanding species rather than the appearance and disappearance of major archaeal species. Temperature was found to positively correlate with the dominant bacteria, Betaproteobacteria, and negatively correlate with the dominant archaea, Marine_Group_I; and might be the primary driving force for the seasonal variation of the microbial community. Copyright © 2016. Published by Elsevier B.V.
Analysis of Alaskan burn severity patterns using remotely sensed data
Duffy, P.A.; Epting, J.; Graham, J.M.; Rupp, T.S.; McGuire, A.D.
2007-01-01
Wildland fire is the dominant large-scale disturbance mechanism in the Alaskan boreal forest, and it strongly influences forest structure and function. In this research, patterns of burn severity in the Alaskan boreal forest are characterised using 24 fires. First, the relationship between burn severity and area burned is quantified using a linear regression. Second, the spatial correlation of burn severity as a function of topography is modelled using a variogram analysis. Finally, the relationship between vegetation type and spatial patterns of burn severity is quantified using linear models where variograms account for spatial correlation. These results show that: 1) average burn severity increases with the natural logarithm of the area of the wildfire, 2) burn severity is more variable in topographically complex landscapes than in flat landscapes, and 3) there is a significant relationship between burn severity and vegetation type in flat landscapes but not in topographically complex landscapes. These results strengthen the argument that differential flammability of vegetation exists in some boreal landscapes of Alaska. Additionally, these results suggest that through feedbacks between vegetation and burn severity, the distribution of forest vegetation through time is likely more stable in flat terrain than it is in areas with more complex topography. ?? IAWF 2007.
Wildfire risk assessment in a typical Mediterranean wildland-urban interface of Greece.
Mitsopoulos, Ioannis; Mallinis, Giorgos; Arianoutsou, Margarita
2015-04-01
The purpose of this study was to assess spatial wildfire risk in a typical Mediterranean wildland-urban interface (WUI) in Greece and the potential effect of three different burning condition scenarios on the following four major wildfire risk components: burn probability, conditional flame length, fire size, and source-sink ratio. We applied the Minimum Travel Time fire simulation algorithm using the FlamMap and ArcFuels tools to characterize the potential response of the wildfire risk to a range of different burning scenarios. We created site-specific fuel models of the study area by measuring the field fuel parameters in representative natural fuel complexes, and we determined the spatial extent of the different fuel types and residential structures in the study area using photointerpretation procedures of large scale natural color orthophotographs. The results included simulated spatially explicit fire risk components along with wildfire risk exposure analysis and the expected net value change. Statistical significance differences in simulation outputs between the scenarios were obtained using Tukey's significance test. The results of this study provide valuable information for decision support systems for short-term predictions of wildfire risk potential and inform wildland fire management of typical WUI areas in Greece.
Wildfire Risk Assessment in a Typical Mediterranean Wildland-Urban Interface of Greece
NASA Astrophysics Data System (ADS)
Mitsopoulos, Ioannis; Mallinis, Giorgos; Arianoutsou, Margarita
2015-04-01
The purpose of this study was to assess spatial wildfire risk in a typical Mediterranean wildland-urban interface (WUI) in Greece and the potential effect of three different burning condition scenarios on the following four major wildfire risk components: burn probability, conditional flame length, fire size, and source-sink ratio. We applied the Minimum Travel Time fire simulation algorithm using the FlamMap and ArcFuels tools to characterize the potential response of the wildfire risk to a range of different burning scenarios. We created site-specific fuel models of the study area by measuring the field fuel parameters in representative natural fuel complexes, and we determined the spatial extent of the different fuel types and residential structures in the study area using photointerpretation procedures of large scale natural color orthophotographs. The results included simulated spatially explicit fire risk components along with wildfire risk exposure analysis and the expected net value change. Statistical significance differences in simulation outputs between the scenarios were obtained using Tukey's significance test. The results of this study provide valuable information for decision support systems for short-term predictions of wildfire risk potential and inform wildland fire management of typical WUI areas in Greece.
Wickham, J.D.; Stehman, S.V.; Smith, J.H.; Wade, T.G.; Yang, L.
2004-01-01
Two-stage cluster sampling reduces the cost of collecting accuracy assessment reference data by constraining sample elements to fall within a limited number of geographic domains (clusters). However, because classification error is typically positively spatially correlated, within-cluster correlation may reduce the precision of the accuracy estimates. The detailed population information to quantify a priori the effect of within-cluster correlation on precision is typically unavailable. Consequently, a convenient, practical approach to evaluate the likely performance of a two-stage cluster sample is needed. We describe such an a priori evaluation protocol focusing on the spatial distribution of the sample by land-cover class across different cluster sizes and costs of different sampling options, including options not imposing clustering. This protocol also assesses the two-stage design's adequacy for estimating the precision of accuracy estimates for rare land-cover classes. We illustrate the approach using two large-area, regional accuracy assessments from the National Land-Cover Data (NLCD), and describe how the a priorievaluation was used as a decision-making tool when implementing the NLCD design.
Isola, A A; Schmitt, H; van Stevendaal, U; Begemann, P G; Coulon, P; Boussel, L; Grass, M
2011-09-21
Large area detector computed tomography systems with fast rotating gantries enable volumetric dynamic cardiac perfusion studies. Prospectively, ECG-triggered acquisitions limit the data acquisition to a predefined cardiac phase and thereby reduce x-ray dose and limit motion artefacts. Even in the case of highly accurate prospective triggering and stable heart rate, spatial misalignment of the cardiac volumes acquired and reconstructed per cardiac cycle may occur due to small motion pattern variations from cycle to cycle. These misalignments reduce the accuracy of the quantitative analysis of myocardial perfusion parameters on a per voxel basis. An image-based solution to this problem is elastic 3D image registration of dynamic volume sequences with variable contrast, as it is introduced in this contribution. After circular cone-beam CT reconstruction of cardiac volumes covering large areas of the myocardial tissue, the complete series is aligned with respect to a chosen reference volume. The results of the registration process and the perfusion analysis with and without registration are evaluated quantitatively in this paper. The spatial alignment leads to improved quantification of myocardial perfusion for three different pig data sets.
Mantini, D.; Marzetti, L.; Corbetta, M.; Romani, G.L.; Del Gratta, C.
2017-01-01
Two major non-invasive brain mapping techniques, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), have complementary advantages with regard to their spatial and temporal resolution. We propose an approach based on the integration of EEG and fMRI, enabling the EEG temporal dynamics of information processing to be characterized within spatially well-defined fMRI large-scale networks. First, the fMRI data are decomposed into networks by means of spatial independent component analysis (sICA), and those associated with intrinsic activity and/or responding to task performance are selected using information from the related time-courses. Next, the EEG data over all sensors are averaged with respect to event timing, thus calculating event-related potentials (ERPs). The ERPs are subjected to temporal ICA (tICA), and the resulting components are localized with the weighted minimum norm (WMNLS) algorithm using the task-related fMRI networks as priors. Finally, the temporal contribution of each ERP component in the areas belonging to the fMRI large-scale networks is estimated. The proposed approach has been evaluated on visual target detection data. Our results confirm that two different components, commonly observed in EEG when presenting novel and salient stimuli respectively, are related to the neuronal activation in large-scale networks, operating at different latencies and associated with different functional processes. PMID:20052528
Playground usage and physical activity levels of children based on playground spatial features.
Reimers, Anne K; Knapp, Guido
2017-01-01
Being outdoors is one of the strongest correlates of physical activity in children. Playgrounds are spaces especially designed to enable and foster physical activity in children. This study aimed to analyze the relationship between the spatial features of public playgrounds and the usage and physical activity levels of children playing in them. A quantitative, observational study was conducted of ten playgrounds in one district of a middle-sized town in Germany. Playground spatial features were captured using an audit instrument and the playground manual of the town. Playground usage and physical activity levels of children were assessed using a modified version of the System for Observing Play and Leisure Activity in Youth. Negative binomial models were used to analyze the count data. The number of children using the playgrounds and the number of children actively playing in them were higher in those with more varied facilities and without naturalness. Girls played more actively in playgrounds without multi-purpose areas. Cleanliness, esthetics, play facility quality, division of functional areas and playground size were not related to any outcome variable. Playground spatial features are related to playground usage and activity levels of the children in the playgrounds. Playgrounds should offer a wide variety of play facilities and provide spaces for diverse play activities to respond to the needs of large numbers of different children and to provide activity-friendly areas enabling their healthy development.
NASA Technical Reports Server (NTRS)
Desai, U. D.; Orwig, Larry E.
1988-01-01
In the areas of high spatial resolution, the evaluation of a hard X-ray detector with 65 micron spatial resolution for operation in the energy range from 30 to 400 keV is proposed. The basic detector is a thick large-area scintillator faceplate, composed of a matrix of high-density scintillating glass fibers, attached to a proximity type image intensifier tube with a resistive-anode digital readout system. Such a detector, combined with a coded-aperture mask, would be ideal for use as a modest-sized hard X-ray imaging instrument up to X-ray energies as high as several hundred keV. As an integral part of this study it was also proposed that several techniques be critically evaluated for X-ray image coding which could be used with this detector. In the area of high spectral resolution, it is proposed to evaluate two different types of detectors for use as X-ray spectrometers for solar flares: planar silicon detectors and high-purity germanium detectors (HPGe). Instruments utilizing these high-spatial-resolution detectors for hard X-ray imaging measurements from 30 to 400 keV and high-spectral-resolution detectors for measurements over a similar energy range would be ideally suited for making crucial solar flare observations during the upcoming maximum in the solar cycle.
NASA Astrophysics Data System (ADS)
Sadewo, E.; Syabri, I.; Pradono
2018-05-01
In the theory of urban transformation, there has been growing attention to the development of metropolitan outskirts. While the debate of the post-suburbanization process has already settled, the knowledge on the development beyond is still questionable. This paper examines the urban spatial pattern transformation beyond the Jabodetabek Metropolitan Area post-suburbanization. We use the medium and large enterprise (MLE) data from the economic census (EC) and population data from village potential census (PODES) with two cross sectional times of reference. The 2005 and 2006 data are assumed to represent the post-suburbia situation, and the 2014 and 2016 data represents the situation beyond. We analyzed the extent of which post-suburban spatial pattern in JMA would develope by utilizing the Exploratory Spatial Data Analysis (ESDA) method. The result shows that the polycentric urban structure of JMA has strengthened. The low order service function which was previously clustered in suburban areas is recentralized in the urban core, leaving the manufacturing sector as the main function in the post-suburbia. It is implied that the post-suburban status has reached a steady state for a long term before its next transformation. Those transformations are followed by the shift in population dynamics, whereas workers tend to polarize based on the proximity to their job location. The findings recall further study regarding the post-suburban commuting pattern.
Martinet, Louis-Emmanuel; Ahmed, Omar J.; Lepage, Kyle Q.; Cash, Sydney S.
2015-01-01
Understanding the spatiotemporal dynamics of brain activity is crucial for inferring the underlying synaptic and nonsynaptic mechanisms of brain dysfunction. Focal seizures with secondary generalization are traditionally considered to begin in a limited spatial region and spread to connected areas, which can include both pathological and normal brain tissue. The mechanisms underlying this spread are important to our understanding of seizures and to improve therapies for surgical intervention. Here we study the properties of seizure recruitment—how electrical brain activity transitions to large voltage fluctuations characteristic of spike-and-wave seizures. We do so using invasive subdural electrode arrays from a population of 16 patients with pharmacoresistant epilepsy. We find an average delay of ∼30 s for a broad area of cortex (8 × 8 cm) to be recruited into the seizure, at an estimated speed of ∼4 mm/s. The spatiotemporal characteristics of recruitment reveal two categories of patients: one in which seizure recruitment of neighboring cortical regions follows a spatially organized pattern consistent from seizure to seizure, and a second group without consistent spatial organization of activity during recruitment. The consistent, organized recruitment correlates with a more regular, compared with small-world, connectivity pattern in simulation and successful surgical treatment of epilepsy. We propose that an improved understanding of how the seizure recruits brain regions into large amplitude voltage fluctuations provides novel information to improve surgical treatment of epilepsy and highlights the slow spread of massive local activity across a vast extent of cortex during seizure. PMID:26109670
NASA Astrophysics Data System (ADS)
Bartos, M. D.; Kerkez, B.; Noh, S.; Seo, D. J.
2017-12-01
In this study, we develop and evaluate a high resolution urban flash flood monitoring system using a wireless sensor network (WSN), a real-time rainfall-runoff model, and spatially-explicit radar rainfall predictions. Flooding is the leading cause of natural disaster fatalities in the US, with flash flooding in particular responsible for a majority of flooding deaths. While many riverine flood models have been operationalized into early warning systems, there is currently no model that is capable of reliably predicting flash floods in urban areas. Urban flash floods are particularly difficult to model due to a lack of rainfall and runoff data at appropriate scales. To address this problem, we develop a wide-area flood-monitoring wireless sensor network for the Dallas-Fort Worth metroplex, and use this network to characterize rainfall-runoff response over multiple heterogeneous catchments. First, we deploy a network of 22 wireless sensor nodes to collect real-time stream stage measurements over catchments ranging from 2-80 km2 in size. Next, we characterize the rainfall-runoff response of each catchment by combining stream stage data with gage and radar-based precipitation measurements. Finally, we demonstrate the potential for real-time flash flood prediction by joining the derived rainfall-runoff models with real-time radar rainfall predictions. We find that runoff response is highly heterogeneous among catchments, with large variabilities in runoff response detected even among nearby gages. However, when spatially-explicit rainfall fields are included, spatial variability in runoff response is largely captured. This result highlights the importance of increased spatial coverage for flash flood prediction.
Linard, Catherine; Lamarque, Pénélope; Heyman, Paul; Ducoffre, Geneviève; Luyasu, Victor; Tersago, Katrien; Vanwambeke, Sophie O; Lambin, Eric F
2007-05-02
Vector-borne and zoonotic diseases generally display clear spatial patterns due to different space-dependent factors. Land cover and land use influence disease transmission by controlling both the spatial distribution of vectors or hosts, and the probability of contact with susceptible human populations. The objective of this study was to combine environmental and socio-economic factors to explain the spatial distribution of two emerging human diseases in Belgium, Puumala virus (PUUV) and Lyme borreliosis. Municipalities were taken as units of analysis. Negative binomial regressions including a correction for spatial endogeneity show that the spatial distribution of PUUV and Lyme borreliosis infections are associated with a combination of factors linked to the vector and host populations, to human behaviours, and to landscape attributes. Both diseases are associated with the presence of forests, which are the preferred habitat for vector or host populations. The PUUV infection risk is higher in remote forest areas, where the level of urbanisation is low, and among low-income populations. The Lyme borreliosis transmission risk is higher in mixed landscapes with forests and spatially dispersed houses, mostly in wealthy peri-urban areas. The spatial dependence resulting from a combination of endogenous and exogenous processes could be accounted for in the model on PUUV but not for Lyme borreliosis. A large part of the spatial variation in disease risk can be explained by environmental and socio-economic factors. The two diseases not only are most prevalent in different regions but also affect different groups of people. Combining these two criteria may increase the efficiency of information campaigns through appropriate targeting.
McKenna, James E.; Schaeffer, Jeffrey S.; Stewart, Jana S.; Slattery, Michael T.
2015-01-01
Classifications are typically specific to particular issues or areas, leading to patchworks of subjectively defined spatial units. Stream conservation is hindered by the lack of a universal habitat classification system and would benefit from an independent hydrology-guided spatial framework of units encompassing all aquatic habitats at multiple spatial scales within large regions. We present a system that explicitly separates the spatial framework from any particular classification developed from the framework. The framework was constructed from landscape variables that are hydrologically and biologically relevant, covered all space within the study area, and was nested hierarchically and spatially related at scales ranging from the stream reach to the entire region; classifications may be developed from any subset of the 9 basins, 107 watersheds, 459 subwatersheds, or 10,000s of valley segments or stream reaches. To illustrate the advantages of this approach, we developed a fish-guided classification generated from a framework for the Great Lakes region that produced a mosaic of habitat units which, when aggregated, formed larger patches of more general conditions at progressively broader spatial scales. We identified greater than 1,200 distinct fish habitat types at the valley segment scale, most of which were rare. Comparisons of biodiversity and species assemblages are easily examined at any scale. This system can identify and quantify habitat types, evaluate habitat quality for conservation and/or restoration, and assist managers and policymakers with prioritization of protection and restoration efforts. Similar spatial frameworks and habitat classifications can be developed for any organism in any riverine ecosystem.
NASA Astrophysics Data System (ADS)
Zhang, S.; Wang, Y.; Ju, H.
2017-12-01
The interprovincial terrestrial physical geographical entities are the key areas of regional integrated management. Based on toponomy dictionaries and different thematic maps, the attributes and the spatial extent of the interprovincial terrestrial physical geographical names (ITPGN, including terrain ITPGN and water ITPGN) were extracted. The coefficient of variation and Moran's I were combined together to measure the spatial variation and spatial association of ITPGN. The influencing factors of the distribution of ITPGN and the implications for the regional management were further discussed. The results showed that 11325 ITPGN were extracted, including 7082 terrain ITPGN and 4243 water ITPGN. Hunan Province had the largest number of ITPGN in China, and Shanghai had the smallest number. The spatial variance of the terrain ITPGN was larger than that of the water ITPGN, and the ITPGN showed a significant agglomeration phenomenon in the southern part of China. Further analysis showed that the number of ITPGN was positively related with the relative elevation and the population where the relative elevation was lower than 2000m and the population was less than 50 million. But the number of ITPGN showed a negative relationship with the two factors when their values became larger, indicating a large number of unnamed entities existed in complex terrain areas and a decreasing number of terrestrial physical geographical entities in densely populated area. Based on these analysis, we suggest the government take the ITPGN as management units to realize a balance development between different parts of the entities and strengthen the geographical names census and the nomination of unnamed interprovincial physical geographical entities. This study also demonstrated that the methods of literature survey, coefficient of variation and Moran's I can be combined to enhance the understanding of the spatial pattern of ITPGN.
Zhao, Yan; Bai, Linyan; Feng, Jianzhong; Lin, Xiaosong; Wang, Li; Xu, Lijun; Ran, Qiyun; Wang, Kui
2016-04-19
Multiple cropping provides China with a very important system of intensive cultivation, and can effectively enhance the efficiency of farmland use while improving regional food production and security. A multiple cropping index (MCI), which represents the intensity of multiple cropping and reflects the effects of climate change on agricultural production and cropping systems, often serves as a useful parameter. Therefore, monitoring the dynamic changes in the MCI of farmland over a large area using remote sensing data is essential. For this purpose, nearly 30 years of MCIs related to dry land in the North China Plain (NCP) were efficiently extracted from remotely sensed leaf area index (LAI) data from the Global LAnd Surface Satellite (GLASS). Next, the characteristics of the spatial-temporal change in MCI were analyzed. First, 2162 typical arable sample sites were selected based on a gridded spatial sampling strategy, and then the LAI information was extracted from the samples. Second, the Savizky-Golay filter was used to smooth the LAI time-series data of the samples, and then the MCIs of the samples were obtained using a second-order difference algorithm. Finally, the geo-statistical Kriging method was employed to map the spatial distribution of the MCIs and to obtain a time-series dataset of the MCIs of dry land over the NCP. The results showed that all of the MCIs in the NCP showed an increasing trend over the entire study period and increased most rapidly from 1982 to 2002. Spatially, MCIs decreased from south to north; also, high MCIs were mainly concentrated in the relatively flat areas. In addition, the partial spatial changes of MCIs had clear geographical characteristics, with the largest change in Henan Province.
Zhao, Yan; Bai, Linyan; Feng, Jianzhong; Lin, Xiaosong; Wang, Li; Xu, Lijun; Ran, Qiyun; Wang, Kui
2016-01-01
Multiple cropping provides China with a very important system of intensive cultivation, and can effectively enhance the efficiency of farmland use while improving regional food production and security. A multiple cropping index (MCI), which represents the intensity of multiple cropping and reflects the effects of climate change on agricultural production and cropping systems, often serves as a useful parameter. Therefore, monitoring the dynamic changes in the MCI of farmland over a large area using remote sensing data is essential. For this purpose, nearly 30 years of MCIs related to dry land in the North China Plain (NCP) were efficiently extracted from remotely sensed leaf area index (LAI) data from the Global LAnd Surface Satellite (GLASS). Next, the characteristics of the spatial-temporal change in MCI were analyzed. First, 2162 typical arable sample sites were selected based on a gridded spatial sampling strategy, and then the LAI information was extracted from the samples. Second, the Savizky-Golay filter was used to smooth the LAI time-series data of the samples, and then the MCIs of the samples were obtained using a second-order difference algorithm. Finally, the geo-statistical Kriging method was employed to map the spatial distribution of the MCIs and to obtain a time-series dataset of the MCIs of dry land over the NCP. The results showed that all of the MCIs in the NCP showed an increasing trend over the entire study period and increased most rapidly from 1982 to 2002. Spatially, MCIs decreased from south to north; also, high MCIs were mainly concentrated in the relatively flat areas. In addition, the partial spatial changes of MCIs had clear geographical characteristics, with the largest change in Henan Province. PMID:27104536
Solutions for extracting file level spatial metadata from airborne mission data
NASA Astrophysics Data System (ADS)
Schwab, M. J.; Stanley, M.; Pals, J.; Brodzik, M.; Fowler, C.; Icebridge Engineering/Spatial Metadata
2011-12-01
Authors: Michael Stanley Mark Schwab Jon Pals Mary J. Brodzik Cathy Fowler Collaboration: Raytheon EED and NSIDC Raytheon / EED 5700 Rivertech Court Riverdale, MD 20737 NSIDC University of Colorado UCB 449 Boulder, CO 80309-0449 Data sets acquired from satellites and aircraft may differ in many ways. We will focus on the differences in spatial coverage between the two platforms. Satellite data sets over a given period typically cover large geographic regions. These data are collected in a consistent, predictable and well understood manner due to the uniformity of satellite orbits. Since satellite data collection paths are typically smooth and uniform the data from satellite instruments can usually be described with simple spatial metadata. Subsequently, these spatial metadata can be stored and searched easily and efficiently. Conversely, aircraft have significantly more freedom to change paths, circle, overlap, and vary altitude all of which add complexity to the spatial metadata. Aircraft are also subject to wind and other elements that result in even more complicated and unpredictable spatial coverage areas. This unpredictability and complexity makes it more difficult to extract usable spatial metadata from data sets collected on aircraft missions. It is not feasible to use all of the location data from aircraft mission data sets for use as spatial metadata. The number of data points in typical data sets poses serious performance problems for spatial searching. In order to provide efficient spatial searching of the large number of files cataloged in our systems, we need to extract approximate spatial descriptions as geo-polygons from a small number of vertices (fewer than two hundred). We present some of the challenges and solutions for creating airborne mission-derived spatial metadata. We are implementing these methods to create the spatial metadata for insertion of IceBridge mission data into ECS for public access through NSIDC and ECHO but, they are potentially extensible to any aircraft mission data.
NASA Astrophysics Data System (ADS)
Kahru, Mati; Mitchell, B. Greg
2001-02-01
Time series of surface chlorophyll a concentration (Chl) and colored dissolved organic matter (CDOM) derived from the Ocean Color and Temperature Sensor and Sea-Viewing Wide Field-of-View Sensor were evaluated for the California Current area using regional algorithms. Satellite data composited for 8-day periods provide the ability to describe large-scale changes in surface parameters. These changes are difficult to detect based on in situ observations alone that suffer from undersampling the large temporal and spatial variability, especially in Chl. We detected no significant bias in satellite Chl estimates compared with ship-based measurements. The variability in CDOM concentration was significantly smaller than that in Chl, both spatially and temporally. While being subject to large interannual and short-term variations, offshore waters (100-1000 km from the shore) have an annual cycle of Chl and CDOM with a maximum in winter-spring (December-March) and a minimum in late summer. For inshore waters the maximum is more likely in spring (April-May). We detect significant increase in both Chl and CDOM off central and southern California during the La Niña year of 1999. The trend of increasing Chl and CDOM from October 1996 to June 2000 is statistically significant in many areas.
Large Area MEMS Based Ultrasound Device for Cancer Detection.
Wodnicki, Robert; Thomenius, Kai; Hooi, Fong Ming; Sinha, Sumedha P; Carson, Paul L; Lin, Der-Song; Zhuang, Xuefeng; Khuri-Yakub, Pierre; Woychik, Charles
2011-08-21
We present image results obtained using a prototype ultrasound array which demonstrates the fundamental architecture for a large area MEMS based ultrasound device for detection of breast cancer. The prototype array consists of a tiling of capacitive Micro-Machined Ultrasound Transducers (cMUTs) which have been flip-chip attached to a rigid organic substrate. The pitch on the cMUT elements is 185 um and the operating frequency is nominally 9 MHz. The spatial resolution of the new probe is comparable to production PZT probes, however the sensitivity is reduced by conditions that should be correctable. Simulated opposed-view image registration and Speed of Sound volume reconstruction results for ultrasound in the mammographic geometry are also presented.
NASA Astrophysics Data System (ADS)
Rasera, L. G.; Mariethoz, G.; Lane, S. N.
2017-12-01
Frequent acquisition of high-resolution digital elevation models (HR-DEMs) over large areas is expensive and difficult. Satellite-derived low-resolution digital elevation models (LR-DEMs) provide extensive coverage of Earth's surface but at coarser spatial and temporal resolutions. Although useful for large scale problems, LR-DEMs are not suitable for modeling hydrologic and geomorphic processes at scales smaller than their spatial resolution. In this work, we present a multiple-point geostatistical approach for downscaling a target LR-DEM based on available high-resolution training data and recurrent high-resolution remote sensing images. The method aims at generating several equiprobable HR-DEMs conditioned to a given target LR-DEM by borrowing small scale topographic patterns from an analogue containing data at both coarse and fine scales. An application of the methodology is demonstrated by using an ensemble of simulated HR-DEMs as input to a flow-routing algorithm. The proposed framework enables a probabilistic assessment of the spatial structures generated by natural phenomena operating at scales finer than the available terrain elevation measurements. A case study in the Swiss Alps is provided to illustrate the methodology.
Suppressive mechanisms in visual motion processing: from perception to intelligence
Tadin, Duje
2015-01-01
Perception operates on an immense amount of incoming information that greatly exceeds the brain's processing capacity. Because of this fundamental limitation, the ability to suppress irrelevant information is a key determinant of perceptual efficiency. Here, I will review a series of studies investigating suppressive mechanisms in visual motion processing, namely perceptual suppression of large, background-like motions. These spatial suppression mechanisms are adaptive, operating only when sensory inputs are sufficiently robust to guarantee visibility. Converging correlational and causal evidence links these behavioral results with inhibitory center-surround mechanisms, namely those in cortical area MT. Spatial suppression is abnormally weak in several special populations, including the elderly and those with schizophrenia—a deficit that is evidenced by better-than-normal direction discriminations of large moving stimuli. Theoretical work shows that this abnormal weakening of spatial suppression should result in motion segregation deficits, but direct behavioral support of this hypothesis is lacking. Finally, I will argue that the ability to suppress information is a fundamental neural process that applies not only to perception but also to cognition in general. Supporting this argument, I will discuss recent research that shows individual differences in spatial suppression of motion signals strongly predict individual variations in IQ scores. PMID:26299386
NASA Technical Reports Server (NTRS)
Ryan, Robert E.; Irons, James; Spruce, Joseph P.; Underwood, Lauren W.; Pagnutti, Mary
2006-01-01
This study explores the use of synthetic thermal center pivot irrigation scenes to estimate temperature retrieval accuracy for thermal remote sensed data, such as data acquired from current and proposed Landsat-like thermal systems. Center pivot irrigation is a common practice in the western United States and in other parts of the world where water resources are scarce. Wide-area ET (evapotranspiration) estimates and reliable water management decisions depend on accurate temperature information retrieval from remotely sensed data. Spatial resolution, sensor noise, and the temperature step between a field and its surrounding area impose limits on the ability to retrieve temperature information. Spatial resolution is an interrelationship between GSD (ground sample distance) and a measure of image sharpness, such as edge response or edge slope. Edge response and edge slope are intuitive, and direct measures of spatial resolution are easier to visualize and estimate than the more common Modulation Transfer Function or Point Spread Function. For these reasons, recent data specifications, such as those for the LDCM (Landsat Data Continuity Mission), have used GSD and edge response to specify spatial resolution. For this study, we have defined a 400-800 m diameter center pivot irrigation area with a large 25 K temperature step associated with a 300 K well-watered field surrounded by an infinite 325 K dry area. In this context, we defined the benchmark problem as an easily modeled, highly common stressing case. By parametrically varying GSD (30-240 m) and edge slope, we determined the number of pixels and field area fraction that meet a given temperature accuracy estimate for 400-m, 600-m, and 800-m diameter field sizes. Results of this project will help assess the utility of proposed specifications for the LDCM and other future thermal remote sensing missions and for water resource management.
Forster, A.; Merriam, D.F.; Davis, J.C.
1997-01-01
Large numbers of bottom-hole temperatures (BHTs) and temperatures measured during drill-stem tests (DSTs) are available in areas explored for hydrocarbons, but their usefulness for estimating geothermal gradients and heat-flow density is limited. We investigated a large data set of BHT and DST measurements taken in boreholes in the American Midcontinent, a geologically uniform stable cratonic area, and propose an empirical correction for BHTs based on relationships between BHTs, DSTs, and thermal logs. This empirical correction is compared with similar approaches determined for other areas. The data were analyzed by multivariate statistics prior to the BHT correction to identify anomalous measurements and quantify external influences. Spatial patterns in temperature measurements for major stratigraphic units outline relations to regional structure. Comparision of temperature and structure trend-surface residuals reveals a relationship between temperature highs and local structure highs. The anticlines, developed by continuous but intermittent movement of basement fault blocks in the Late Paleozoic, are subtle features having closures of 10-30 m and contain relatively small hydrocarbon reservoirs. The temperature anomalies of the order of 5-7 ??C may reflect fluids moving upward along fractures and faults, rather than changes in thermal conductivity resulting from different pore fluids. ?? Springer-Verlag 1997.
Forster, A.; Merriam, D.F.; Davis, J.C.
1997-01-01
Large numbers of bottom-hole temperatures (BHTs) and temperatures measured during drill-stem tests (DSTs) are available in areas explored for hydrocarbons, but their usefulness for estimating geothermal gradients and heat-flow density is limited. We investigated a large data set of BHT and DST measurements taken in boreholes in the American Midcontinent, a geologically uniform stable cratonic area, and propose an empirical correction for BHTs based on relationships between BHTs, DSTs, and thermal logs. This empirical correction is compared with similar approaches determined for other areas. The data were analyzed by multivariate statistics prior to the BHT correction to identify anomalous measurements and quantify external influences. Spatial patterns in temperature measurements for major stratigraphic units outline relations to regional structure. Comparision of temperature and structure trend-surface residuals reveals a relationship between temperature highs and local structure highs. The anticlines, developed by continuous but intermittent movement of basement fault blocks in the Late Paleozoic, are subtle features having closures of 10-30 m and contain relatively small hydrocarbon reservoirs. The temperature anomalies of the order of 5-7??C may reflect fluids moving upward along fractures and faults, rather than changes in thermal conductivity resulting from different pore fluids.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Calix, R.E.; Diener, D.
1995-12-31
MEC Analytical Systems, Inc., has conducted marine monitoring of a large ocean wastewater outfall since 1985. This EPA mandated monitoring program was designed to measure the spatial and temporal variability of the biological communities and assess the impact associated with the discharge. The ostracod Euphilomedes carcarodonta, has shown enhanced abundances centered at the outfall since the late 70`s. While flow rates continue to increase the concentration of solids and contaminants has been decreasing with improve treatment levels. However the abundance and spatial distribution of this species has remain relatively unchanged. It is hypothesized that this species feeds on the smallmore » organic particles. In contrast, the abundance of the polychaete Capitella capitata, an indicator of disturbed habitat and organic enrichment, has decreased significantly. This decrease correlates with decreasing concentrations of wastewater solids and decreasing sediment organic carbon concentrations. The brittle star, Amphiodia urtica, has been found to be one of the most sensitive species to wastewater discharges and its abundance was significantly decreased over a large area in the 70`s. Since 1985 this species has shown a steady recovery of abundance to areas near the discharge. This recovery correlates with lower sediment contaminant levels and decreased solid concentrations, and indicates that the environmental quality near the discharge is similar to reference areas.« less
First-in-human pilot study of a spatial frequency domain oxygenation imaging system
NASA Astrophysics Data System (ADS)
Gioux, Sylvain; Mazhar, Amaan; Lee, Bernard T.; Lin, Samuel J.; Tobias, Adam M.; Cuccia, David J.; Stockdale, Alan; Oketokoun, Rafiou; Ashitate, Yoshitomo; Kelly, Edward; Weinmann, Maxwell; Durr, Nicholas J.; Moffitt, Lorissa A.; Durkin, Anthony J.; Tromberg, Bruce J.; Frangioni, John V.
2011-08-01
Oxygenation measurements are widely used in patient care. However, most clinically available instruments currently consist of contact probes that only provide global monitoring of the patient (e.g., pulse oximetry probes) or local monitoring of small areas (e.g., spectroscopy-based probes). Visualization of oxygenation over large areas of tissue, without a priori knowledge of the location of defects, has the potential to improve patient management in many surgical and critical care applications. In this study, we present a clinically compatible multispectral spatial frequency domain imaging (SFDI) system optimized for surgical oxygenation imaging. This system was used to image tissue oxygenation over a large area (16×12 cm) and was validated during preclinical studies by comparing results obtained with an FDA-approved clinical oxygenation probe. Skin flap, bowel, and liver vascular occlusion experiments were performed on Yorkshire pigs and demonstrated that over the course of the experiment, relative changes in oxygen saturation measured using SFDI had an accuracy within 10% of those made using the FDA-approved device. Finally, the new SFDI system was translated to the clinic in a first-in-human pilot study that imaged skin flap oxygenation during reconstructive breast surgery. Overall, this study lays the foundation for clinical translation of endogenous contrast imaging using SFDI.
First-in-human pilot study of a spatial frequency domain oxygenation imaging system
Gioux, Sylvain; Mazhar, Amaan; Lee, Bernard T.; Lin, Samuel J.; Tobias, Adam M.; Cuccia, David J.; Stockdale, Alan; Oketokoun, Rafiou; Ashitate, Yoshitomo; Kelly, Edward; Weinmann, Maxwell; Durr, Nicholas J.; Moffitt, Lorissa A.; Durkin, Anthony J.; Tromberg, Bruce J.; Frangioni, John V.
2011-01-01
Oxygenation measurements are widely used in patient care. However, most clinically available instruments currently consist of contact probes that only provide global monitoring of the patient (e.g., pulse oximetry probes) or local monitoring of small areas (e.g., spectroscopy-based probes). Visualization of oxygenation over large areas of tissue, without a priori knowledge of the location of defects, has the potential to improve patient management in many surgical and critical care applications. In this study, we present a clinically compatible multispectral spatial frequency domain imaging (SFDI) system optimized for surgical oxygenation imaging. This system was used to image tissue oxygenation over a large area (16×12 cm) and was validated during preclinical studies by comparing results obtained with an FDA-approved clinical oxygenation probe. Skin flap, bowel, and liver vascular occlusion experiments were performed on Yorkshire pigs and demonstrated that over the course of the experiment, relative changes in oxygen saturation measured using SFDI had an accuracy within 10% of those made using the FDA-approved device. Finally, the new SFDI system was translated to the clinic in a first-in-human pilot study that imaged skin flap oxygenation during reconstructive breast surgery. Overall, this study lays the foundation for clinical translation of endogenous contrast imaging using SFDI. PMID:21895327
NASA Technical Reports Server (NTRS)
Lin, Bing; Xu, Kuan-Man; Minnis, Patrick; Wielicki, Bruce A.; Hu, Yongxiang; Chambers, Lin; Fan, Alice; Sun, Wenbo
2007-01-01
Measurements of cloud properties and atmospheric radiation taken between January and August 1998 by the Tropical Rainfall Measuring Mission (TRMM) satellite were used to investigate the effect of spatial and temporal scales on the coincident occurrences of tropical individual cirrus clouds (ICCs) and deep convective systems (DCSs). It is found that there is little or even negative correlation between instantaneous occurrences of ICC and DCS in small areas, in which both types of clouds cannot grow and expand simultaneously. When spatial and temporal domains are increased, ICCs become more dependent on DCSs due to the origination of many ICCs from DCSs and moisture supply from the DCS in the upper troposphere for the ICCs to grow, resulting in significant positive correlation between the two types of tropical high clouds in large spatial and long temporal scales. This result may suggest that the decrease of tropical high clouds with SST from model simulations is likely caused by restricted spatial domains and limited temporal periods. Finally, the radiative feedback due to the change in tropical high cloud area coverage with sea surface temperature appears small and about -0.14 W/sq m per degree Kelvin.
Congdon, Peter
2014-04-01
Health data may be collected across one spatial framework (e.g. health provider agencies), but contrasts in health over another spatial framework (neighbourhoods) may be of policy interest. In the UK, population prevalence totals for chronic diseases are provided for populations served by general practitioner practices, but not for neighbourhoods (small areas of circa 1500 people), raising the question whether data for one framework can be used to provide spatially interpolated estimates of disease prevalence for the other. A discrete process convolution is applied to this end and has advantages when there are a relatively large number of area units in one or other framework. Additionally, the interpolation is modified to take account of the observed neighbourhood indicators (e.g. hospitalisation rates) of neighbourhood disease prevalence. These are reflective indicators of neighbourhood prevalence viewed as a latent construct. An illustrative application is to prevalence of psychosis in northeast London, containing 190 general practitioner practices and 562 neighbourhoods, including an assessment of sensitivity to kernel choice (e.g. normal vs exponential). This application illustrates how a zero-inflated Poisson can be used as the likelihood model for a reflective indicator.
An analysis of spatial representativeness of air temperature monitoring stations
NASA Astrophysics Data System (ADS)
Liu, Suhua; Su, Hongbo; Tian, Jing; Wang, Weizhen
2018-05-01
Surface air temperature is an essential variable for monitoring the atmosphere, and it is generally acquired at meteorological stations that can provide information about only a small area within an r m radius ( r-neighborhood) of the station, which is called the representable radius. In studies on a local scale, ground-based observations of surface air temperatures obtained from scattered stations are usually interpolated using a variety of methods without ascertaining their effectiveness. Thus, it is necessary to evaluate the spatial representativeness of ground-based observations of surface air temperature before conducting studies on a local scale. The present study used remote sensing data to estimate the spatial distribution of surface air temperature using the advection-energy balance for air temperature (ADEBAT) model. Two target stations in the study area were selected to conduct an analysis of spatial representativeness. The results showed that one station (AWS 7) had a representable radius of about 400 m with a possible error of less than 1 K, while the other station (AWS 16) had the radius of about 250 m. The representable radius was large when the heterogeneity of land cover around the station was small.
Ferrari, Renata; Marzinelli, Ezequiel M; Ayroza, Camila Rezende; Jordan, Alan; Figueira, Will F; Byrne, Maria; Malcolm, Hamish A; Williams, Stefan B; Steinberg, Peter D
2018-01-01
Marine protected areas (MPAs) are designed to reduce threats to biodiversity and ecosystem functioning from anthropogenic activities. Assessment of MPAs effectiveness requires synchronous sampling of protected and non-protected areas at multiple spatial and temporal scales. We used an autonomous underwater vehicle to map benthic communities in replicate 'no-take' and 'general-use' (fishing allowed) zones within three MPAs along 7o of latitude. We recorded 92 taxa and 38 morpho-groups across three large MPAs. We found that important habitat-forming biota (e.g. massive sponges) were more prevalent and abundant in no-take zones, while short ephemeral algae were more abundant in general-use zones, suggesting potential short-term effects of zoning (5-10 years). Yet, short-term effects of zoning were not detected at the community level (community structure or composition), while community structure varied significantly among MPAs. We conclude that by allowing rapid, simultaneous assessments at multiple spatial scales, autonomous underwater vehicles are useful to document changes in marine communities and identify adequate scales to manage them. This study advanced knowledge of marine benthic communities and their conservation in three ways. First, we quantified benthic biodiversity and abundance, generating the first baseline of these benthic communities against which the effectiveness of three large MPAs can be assessed. Second, we identified the taxonomic resolution necessary to assess both short and long-term effects of MPAs, concluding that coarse taxonomic resolution is sufficient given that analyses of community structure at different taxonomic levels were generally consistent. Yet, observed differences were taxa-specific and may have not been evident using our broader taxonomic classifications, a classification of mid to high taxonomic resolution may be necessary to determine zoning effects on key taxa. Third, we provide an example of statistical analyses and sampling design that once temporal sampling is incorporated will be useful to detect changes of marine benthic communities across multiple spatial and temporal scales.
Ayroza, Camila Rezende; Jordan, Alan; Figueira, Will F.; Byrne, Maria; Malcolm, Hamish A.; Williams, Stefan B.; Steinberg, Peter D.
2018-01-01
Marine protected areas (MPAs) are designed to reduce threats to biodiversity and ecosystem functioning from anthropogenic activities. Assessment of MPAs effectiveness requires synchronous sampling of protected and non-protected areas at multiple spatial and temporal scales. We used an autonomous underwater vehicle to map benthic communities in replicate ‘no-take’ and ‘general-use’ (fishing allowed) zones within three MPAs along 7o of latitude. We recorded 92 taxa and 38 morpho-groups across three large MPAs. We found that important habitat-forming biota (e.g. massive sponges) were more prevalent and abundant in no-take zones, while short ephemeral algae were more abundant in general-use zones, suggesting potential short-term effects of zoning (5–10 years). Yet, short-term effects of zoning were not detected at the community level (community structure or composition), while community structure varied significantly among MPAs. We conclude that by allowing rapid, simultaneous assessments at multiple spatial scales, autonomous underwater vehicles are useful to document changes in marine communities and identify adequate scales to manage them. This study advanced knowledge of marine benthic communities and their conservation in three ways. First, we quantified benthic biodiversity and abundance, generating the first baseline of these benthic communities against which the effectiveness of three large MPAs can be assessed. Second, we identified the taxonomic resolution necessary to assess both short and long-term effects of MPAs, concluding that coarse taxonomic resolution is sufficient given that analyses of community structure at different taxonomic levels were generally consistent. Yet, observed differences were taxa-specific and may have not been evident using our broader taxonomic classifications, a classification of mid to high taxonomic resolution may be necessary to determine zoning effects on key taxa. Third, we provide an example of statistical analyses and sampling design that once temporal sampling is incorporated will be useful to detect changes of marine benthic communities across multiple spatial and temporal scales. PMID:29547656
Managing Floodplain Expectations on the Lower Missouri River, USA.
NASA Astrophysics Data System (ADS)
Bulliner, E. A., IV; Jacobson, R. B.; Lindner, G. A.; Paukert, C.; Bouska, K.
2017-12-01
The Missouri River is an archetype of the challenges of managing large rivers and their floodplains for multiple objectives. At 1.3 million km2 drainage area, the Missouri boasts the largest reservoir system in North America with 91 km3 of total storage; in an average year the system generates 10 billion kilowatt hours of electricity. The Lower Missouri River floodplain extends 1,300 km downstream from the reservoir system and encompasses approximately 9,200 km2. For the past 150 years, the floodplain has been predominantly used for agriculture much of which is protected from flooding by private and Federal levees. Reservoir system operating policies prioritize flood-hazard reduction but in recent years, large, damaging floods have demonstrated system limitations. These large floods and changing societal values have created new expectations about how conversion of floodplain agricultural lands to conservation lands might increase ecosystem services, in particular decreasing flood risk and mitigating fluxes of nutrients to the Gulf of Mexico. Our research addresses these expectations at multiple spatial scales by starting with hydrologic and hydraulic models to understand controls on floodplain hydrodynamics. The results document the substantial regional spatial variability in floodplain connectivity that exists because of multi-decadal channel adjustments to channelization and sediment budgets. Exploration of levee setback scenarios with 1- and 2-dimensional hydrodynamic models indicates modest and spatially variable gains in flood-hazard reduction are possible if substantial land areas (50% or more) are converted from agricultural production. Estimates of potential denitrification benefits of connecting floodplains indicate that the floodplain has the capacity to remove 100's to 1,000's of metric tons of N each year, but amounts to a maximum of about 5% the existing load of 200,000 ton*y-1. The results indicate that in this river-floodplain system, the ecosystem services associated with floodplain conversion can be substantial, but the sum of benefits needed to justify land conversion over broad areas remains uncertain.
Land use and carbon dynamics in the southeastern United States from 1992 to 2050
Zhao, Shuqing; Liu, Shuguang; Sohl, Terry L.; Young, Claudia; Werner, Jeremy M.
2013-01-01
Land use and land cover change (LUCC) plays an important role in determining the spatial distribution, magnitude, and temporal change of terrestrial carbon sources and sinks. However, the impacts of LUCC are not well understood and quantified over large areas. The goal of this study was to quantify the spatial and temporal patterns of carbon dynamics in various terrestrial ecosystems in the southeastern United States from 1992 to 2050 using a process-based modeling system and then to investigate the impacts of LUCC. Spatial LUCC information was reconstructed and projected using the FOREcasting SCEnarios of future land cover (FORE-SCE) model according to information derived from Landsat observations and other sources. Results indicated that urban expansion (from 3.7% in 1992 to 9.2% in 2050) was expected to be the primary driver for other land cover changes in the region, leading to various declines in forest, cropland, and hay/pasture. The region was projected to be a carbon sink of 60.4 gC m−2 yr−1 on average during the study period, primarily due to the legacy impacts of large-scale conversion of cropland to forest that happened since the 1950s. Nevertheless, the regional carbon sequestration rate was expected to decline because of the slowing down of carbon accumulation in aging forests and the decline of forest area.
Tack, Jason D.; Fedy, Bradley C.
2015-01-01
Proactive conservation planning for species requires the identification of important spatial attributes across ecologically relevant scales in a model-based framework. However, it is often difficult to develop predictive models, as the explanatory data required for model development across regional management scales is rarely available. Golden eagles are a large-ranging predator of conservation concern in the United States that may be negatively affected by wind energy development. Thus, identifying landscapes least likely to pose conflict between eagles and wind development via shared space prior to development will be critical for conserving populations in the face of imposing development. We used publically available data on golden eagle nests to generate predictive models of golden eagle nesting sites in Wyoming, USA, using a suite of environmental and anthropogenic variables. By overlaying predictive models of golden eagle nesting habitat with wind energy resource maps, we highlight areas of potential conflict among eagle nesting habitat and wind development. However, our results suggest that wind potential and the relative probability of golden eagle nesting are not necessarily spatially correlated. Indeed, the majority of our sample frame includes areas with disparate predictions between suitable nesting habitat and potential for developing wind energy resources. Map predictions cannot replace on-the-ground monitoring for potential risk of wind turbines on wildlife populations, though they provide industry and managers a useful framework to first assess potential development. PMID:26262876
Tack, Jason D.; Fedy, Bradley C.
2015-01-01
Proactive conservation planning for species requires the identification of important spatial attributes across ecologically relevant scales in a model-based framework. However, it is often difficult to develop predictive models, as the explanatory data required for model development across regional management scales is rarely available. Golden eagles are a large-ranging predator of conservation concern in the United States that may be negatively affected by wind energy development. Thus, identifying landscapes least likely to pose conflict between eagles and wind development via shared space prior to development will be critical for conserving populations in the face of imposing development. We used publically available data on golden eagle nests to generate predictive models of golden eagle nesting sites in Wyoming, USA, using a suite of environmental and anthropogenic variables. By overlaying predictive models of golden eagle nesting habitat with wind energy resource maps, we highlight areas of potential conflict among eagle nesting habitat and wind development. However, our results suggest that wind potential and the relative probability of golden eagle nesting are not necessarily spatially correlated. Indeed, the majority of our sample frame includes areas with disparate predictions between suitable nesting habitat and potential for developing wind energy resources. Map predictions cannot replace on-the-ground monitoring for potential risk of wind turbines on wildlife populations, though they provide industry and managers a useful framework to first assess potential development.
Treml, Benjamin E; Jacobs, Alan G; Bell, Robert T; Thompson, Michael O; Hanrath, Tobias
2016-02-10
Much of the promise of nanomaterials derives from their size-dependent, and hence tunable, properties. Impressive advances have been made in the synthesis of nanoscale building blocks with precisely tailored size, shape and composition. Significant attention is now turning toward creating thin film structures in which size-dependent properties can be spatially programmed with high fidelity. Nonequilibrium processing techniques present exciting opportunities to create nanostructured thin films with unprecedented spatial control over their optical and electronic properties. Here, we demonstrate single scan laser spike annealing (ssLSA) on CdSe nanocrystal (NC) thin films as an experimental test bed to illustrate how the size-dependent photoluminescence (PL) emission can be tuned throughout the visible range and in spatially defined profiles during a single annealing step. Through control of the annealing temperature and time, we discovered that NC fusion is a kinetically limited process with a constant activation energy in over 2 orders of magnitude of NC growth rate. To underscore the broader technological implications of this work, we demonstrate the scalability of LSA to process large area NC films with periodically modulated PL emission, resulting in tunable emission properties of a large area film. New insights into the processing-structure-property relationships presented here offer significant advances in our fundamental understanding of kinetics of nanomaterials as well as technological implications for the production of nanomaterial films.
A Distributive, Non-Destructive, Real-Time Approach to Snowpack Monitoring
NASA Technical Reports Server (NTRS)
Frolik, Jeff; Skalka, Christian
2012-01-01
This invention is designed to ascertain the snow water equivalence (SWE) of snowpacks with better spatial and temporal resolutions than present techniques. The approach is ground-based, as opposed to some techniques that are air-based. In addition, the approach is compact, non-destructive, and can be communicated with remotely, and thus can be deployed in areas not possible with current methods. Presently there are two principal ground-based techniques for obtaining SWE measurements. The first is manual snow core measurements of the snowpack. This approach is labor-intensive, destructive, and has poor temporal resolution. The second approach is to deploy a large (e.g., 3x3 m) snowpillow, which requires significant infrastructure, is potentially hazardous [uses a approximately equal to 200-gallon (approximately equal to 760-L) antifreeze-filled bladder], and requires deployment in a large, flat area. High deployment costs necessitate few installations, thus yielding poor spatial resolution of data. Both approaches have limited usefulness in complex and/or avalanche-prone terrains. This approach is compact, non-destructive to the snowpack, provides high temporal resolution data, and due to potential low cost, can be deployed with high spatial resolution. The invention consists of three primary components: a robust wireless network and computing platform designed for harsh climates, new SWE sensing strategies, and algorithms for smart sampling, data logging, and SWE computation.
Tack, Jason D; Fedy, Bradley C
2015-01-01
Proactive conservation planning for species requires the identification of important spatial attributes across ecologically relevant scales in a model-based framework. However, it is often difficult to develop predictive models, as the explanatory data required for model development across regional management scales is rarely available. Golden eagles are a large-ranging predator of conservation concern in the United States that may be negatively affected by wind energy development. Thus, identifying landscapes least likely to pose conflict between eagles and wind development via shared space prior to development will be critical for conserving populations in the face of imposing development. We used publically available data on golden eagle nests to generate predictive models of golden eagle nesting sites in Wyoming, USA, using a suite of environmental and anthropogenic variables. By overlaying predictive models of golden eagle nesting habitat with wind energy resource maps, we highlight areas of potential conflict among eagle nesting habitat and wind development. However, our results suggest that wind potential and the relative probability of golden eagle nesting are not necessarily spatially correlated. Indeed, the majority of our sample frame includes areas with disparate predictions between suitable nesting habitat and potential for developing wind energy resources. Map predictions cannot replace on-the-ground monitoring for potential risk of wind turbines on wildlife populations, though they provide industry and managers a useful framework to first assess potential development.
Large-area super-resolution optical imaging by using core-shell microfibers
NASA Astrophysics Data System (ADS)
Liu, Cheng-Yang; Lo, Wei-Chieh
2017-09-01
We first numerically and experimentally report large-area super-resolution optical imaging achieved by using core-shell microfibers. The particular spatial electromagnetic waves for different core-shell microfibers are studied by using finite-difference time-domain and ray tracing calculations. The focusing properties of photonic nanojets are evaluated in terms of intensity profile and full width at half-maximum along propagation and transversal directions. In experiment, the general optical fiber is chemically etched down to 6 μm diameter and coated with different metallic thin films by using glancing angle deposition. The direct imaging of photonic nanojets for different core-shell microfibers is performed with a scanning optical microscope system. We show that the intensity distribution of a photonic nanojet is highly related to the metallic shell due to the surface plasmon polaritons. Furthermore, large-area super-resolution optical imaging is performed by using different core-shell microfibers placed over the nano-scale grating with 150 nm line width. The core-shell microfiber-assisted imaging is achieved with super-resolution and hundreds of times the field-of-view in contrast to microspheres. The possible applications of these core-shell optical microfibers include real-time large-area micro-fluidics and nano-structure inspections.
Building-Based Analysis of the Spatial Provision of Urban Parks in Shenzhen, China.
Gao, Wenxiu; Lyu, Qiang; Fan, Xiang; Yang, Xiaochun; Liu, Jiangtao; Zhang, Xirui
2017-12-06
Urban parks provide important environmental, social, and economic benefits to people and urban areas. The literature demonstrates that proximity to urban parks is one of the key factors influencing people's willingness to use them. Therefore, the provision of urban parks near residential areas and workplaces is one of the key factors influencing quality of life. This study designed a solution based on the spatial association between urban parks and buildings where people live or work to identify whether people in different buildings have nearby urban parks available for their daily lives. A building density map based on building floor area (BFA) was used to illustrate the spatial distribution of urban parks and five indices were designed to measure the scales, service coverage and potential service loads of urban parks and reveal areas lacking urban park services in an acceptable walking distance. With such solution, we investigated the provision of urban parks in ten districts of Shenzhen in China, which has grown from several small villages to a megacity in only 30 years. The results indicate that the spatial provision of urban parks in Shenzhen is not sufficient since people in about 65% of the buildings cannot access urban parks by walking 10-min. The distribution and service coverage of the existing urban parks is not balanced at the district level. In some districts, the existing urban parks have good numbers of potential users and even have large service loads, while in some districts, the building densities surrounding the existing parks are quite low and at the same time there is no urban parks nearby some high-density areas.