Analyzing spatial clustering and the spatiotemporal nature and trends of HIV/AIDS prevalence using GIS: the case of Malawi, 1994-2010.

PubMed

Zulu, Leo C; Kalipeni, Ezekiel; Johannes, Eliza

2014-05-23

Although local spatiotemporal analysis can improve understanding of geographic variation of the HIV epidemic, its drivers, and the search for targeted interventions, it is limited in sub-Saharan Africa. Despite recent declines, Malawi's estimated 10.0% HIV prevalence (2011) remained among the highest globally. Using data on pregnant women in Malawi, this study 1) examines spatiotemporal trends in HIV prevalence 1994-2010, and 2) for 2010, identifies and maps the spatial variation/clustering of factors associated with HIV prevalence at district level. Inverse distance weighting was used within ArcGIS Geographic Information Systems (GIS) software to generate continuous surfaces of HIV prevalence from point data (1994, 1996, 1999, 2001, 2003, 2005, 2007, and 2010) obtained from surveillance antenatal clinics. From the surfaces prevalence estimates were extracted at district level and the results mapped nationally. Spatial dependency (autocorrelation) and clustering of HIV prevalence were also analyzed. Correlation and multiple regression analyses were used to identify factors associated with HIV prevalence for 2010 and their spatial variation/clustering mapped and compared to HIV clustering. Analysis revealed wide spatial variation in HIV prevalence at regional, urban/rural, district and sub-district levels. However, prevalence was spatially leveling out within and across 'sub-epidemics' while declining significantly after 1999. Prevalence exhibited statistically significant spatial dependence nationally following initial (1995-1999) localized, patchy low/high patterns as the epidemic spread rapidly. Locally, HIV "hotspots" clustered among eleven southern districts/cities while a "coldspot" captured configurations of six central region districts. Preliminary multiple regression of 2010 HIV prevalence produced a model with four significant explanatory factors (adjusted R2 = 0.688): mean distance to main roads, mean travel time to nearest transport, percentage that had taken an HIV test ever, and percentage attaining a senior primary education. Spatial clustering linked some factors to particular subsets of high HIV-prevalence districts. Spatial analysis enhanced understanding of local spatiotemporal variation in HIV prevalence, possible underlying factors, and potential for differentiated spatial targeting of interventions. Findings suggest that intervention strategies should also emphasize improved access to health/HIV services, basic education, and syphilis management, particularly in rural hotspot districts, as further research is done on drivers at finer scale.

Analyzing spatial clustering and the spatiotemporal nature and trends of HIV/AIDS prevalence using GIS: the case of Malawi, 1994-2010

PubMed Central

2014-01-01

Background Although local spatiotemporal analysis can improve understanding of geographic variation of the HIV epidemic, its drivers, and the search for targeted interventions, it is limited in sub-Saharan Africa. Despite recent declines, Malawi’s estimated 10.0% HIV prevalence (2011) remained among the highest globally. Using data on pregnant women in Malawi, this study 1) examines spatiotemporal trends in HIV prevalence 1994-2010, and 2) for 2010, identifies and maps the spatial variation/clustering of factors associated with HIV prevalence at district level. Methods Inverse distance weighting was used within ArcGIS Geographic Information Systems (GIS) software to generate continuous surfaces of HIV prevalence from point data (1994, 1996, 1999, 2001, 2003, 2005, 2007, and 2010) obtained from surveillance antenatal clinics. From the surfaces prevalence estimates were extracted at district level and the results mapped nationally. Spatial dependency (autocorrelation) and clustering of HIV prevalence were also analyzed. Correlation and multiple regression analyses were used to identify factors associated with HIV prevalence for 2010 and their spatial variation/clustering mapped and compared to HIV clustering. Results Analysis revealed wide spatial variation in HIV prevalence at regional, urban/rural, district and sub-district levels. However, prevalence was spatially leveling out within and across ‘sub-epidemics’ while declining significantly after 1999. Prevalence exhibited statistically significant spatial dependence nationally following initial (1995-1999) localized, patchy low/high patterns as the epidemic spread rapidly. Locally, HIV “hotspots” clustered among eleven southern districts/cities while a “coldspot” captured configurations of six central region districts. Preliminary multiple regression of 2010 HIV prevalence produced a model with four significant explanatory factors (adjusted R2 = 0.688): mean distance to main roads, mean travel time to nearest transport, percentage that had taken an HIV test ever, and percentage attaining a senior primary education. Spatial clustering linked some factors to particular subsets of high HIV-prevalence districts. Conclusions Spatial analysis enhanced understanding of local spatiotemporal variation in HIV prevalence, possible underlying factors, and potential for differentiated spatial targeting of interventions. Findings suggest that intervention strategies should also emphasize improved access to health/HIV services, basic education, and syphilis management, particularly in rural hotspot districts, as further research is done on drivers at finer scale. PMID:24886573

Integration of imagery and cartographic data through a common map base

NASA Technical Reports Server (NTRS)

Clark, J.

1983-01-01

Several disparate data types are integrated by using control points as the basis for spatially registering the data to a map base. The data are reprojected to match the coordinates of the reference UTM (Universal Transverse Mercator) map projection, as expressed in lines and samples. Control point selection is the most critical aspect of integrating the Thematic Mapper Simulator MSS imagery with the cartographic data. It is noted that control points chosen from the imagery are subject to error from mislocated points, either points that did not correlate well to the reference map or minor pixel offsets because of interactive cursorring errors. Errors are also introduced in map control points when points are improperly located and digitized, leading to inaccurate latitude and longitude coordinates. Nonsystematic aircraft platform variations, such as yawl, pitch, and roll, affect the spatial fidelity of the imagery in comparison with the quadrangles. Features in adjacent flight paths do not always correspond properly owing to the systematic panorama effect and alteration of flightline direction, as well as platform variations.

Uncertainties in mapping forest carbon in urban ecosystems.

PubMed

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

2017-02-01

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

Role of malnutrition and parasite infections in the spatial variation in children's anaemia risk in northern Angola.

PubMed

Soares Magalhães, Ricardo J; Langa, Antonio; Pedro, João Mário; Sousa-Figueiredo, José Carlos; Clements, Archie C A; Vaz Nery, Susana

2013-05-01

Anaemia is known to have an impact on child development and mortality and is a severe public health problem in most countries in sub-Saharan Africa. We investigated the consistency between ecological and individual-level approaches to anaemia mapping by building spatial anaemia models for children aged ≤15 years using different modelling approaches. We aimed to (i) quantify the role of malnutrition, malaria, Schistosoma haematobium and soil-transmitted helminths (STHs) in anaemia endemicity; and (ii) develop a high resolution predictive risk map of anaemia for the municipality of Dande in northern Angola. We used parasitological survey data for children aged ≤15 years to build Bayesian geostatistical models of malaria (PfPR≤15), S. haematobium, Ascaris lumbricoides and Trichuris trichiura and predict small-scale spatial variations in these infections. Malnutrition, PfPR≤15, and S. haematobium infections were significantly associated with anaemia risk. An estimated 12.5%, 15.6% and 9.8% of anaemia cases could be averted by treating malnutrition, malaria and S. haematobium, respectively. Spatial clusters of high risk of anaemia (>86%) were identified. Using an individual-level approach to anaemia mapping at a small spatial scale, we found that anaemia in children aged ≤15 years is highly heterogeneous and that malnutrition and parasitic infections are important contributors to the spatial variation in anaemia risk. The results presented in this study can help inform the integration of the current provincial malaria control programme with ancillary micronutrient supplementation and control of neglected tropical diseases such as urogenital schistosomiasis and STH infections.

Learning Spatially-Smooth Mappings in Non-Rigid Structure from Motion

PubMed Central

Hamsici, Onur C.; Gotardo, Paulo F.U.; Martinez, Aleix M.

2013-01-01

Non-rigid structure from motion (NRSFM) is a classical underconstrained problem in computer vision. A common approach to make NRSFM more tractable is to constrain 3D shape deformation to be smooth over time. This constraint has been used to compress the deformation model and reduce the number of unknowns that are estimated. However, temporal smoothness cannot be enforced when the data lacks temporal ordering and its benefits are less evident when objects undergo abrupt deformations. This paper proposes a new NRSFM method that addresses these problems by considering deformations as spatial variations in shape space and then enforcing spatial, rather than temporal, smoothness. This is done by modeling each 3D shape coefficient as a function of its input 2D shape. This mapping is learned in the feature space of a rotation invariant kernel, where spatial smoothness is intrinsically defined by the mapping function. As a result, our model represents shape variations compactly using custom-built coefficient bases learned from the input data, rather than a pre-specified set such as the Discrete Cosine Transform. The resulting kernel-based mapping is a by-product of the NRSFM solution and leads to another fundamental advantage of our approach: for a newly observed 2D shape, its 3D shape is recovered by simply evaluating the learned function. PMID:23946937

Learning Spatially-Smooth Mappings in Non-Rigid Structure from Motion.

PubMed

Hamsici, Onur C; Gotardo, Paulo F U; Martinez, Aleix M

2012-01-01

Non-rigid structure from motion (NRSFM) is a classical underconstrained problem in computer vision. A common approach to make NRSFM more tractable is to constrain 3D shape deformation to be smooth over time. This constraint has been used to compress the deformation model and reduce the number of unknowns that are estimated. However, temporal smoothness cannot be enforced when the data lacks temporal ordering and its benefits are less evident when objects undergo abrupt deformations. This paper proposes a new NRSFM method that addresses these problems by considering deformations as spatial variations in shape space and then enforcing spatial, rather than temporal, smoothness. This is done by modeling each 3D shape coefficient as a function of its input 2D shape. This mapping is learned in the feature space of a rotation invariant kernel, where spatial smoothness is intrinsically defined by the mapping function. As a result, our model represents shape variations compactly using custom-built coefficient bases learned from the input data, rather than a pre-specified set such as the Discrete Cosine Transform. The resulting kernel-based mapping is a by-product of the NRSFM solution and leads to another fundamental advantage of our approach: for a newly observed 2D shape, its 3D shape is recovered by simply evaluating the learned function.

A comparison of spatial analysis methods for the construction of topographic maps of retinal cell density.

PubMed

Garza-Gisholt, Eduardo; Hemmi, Jan M; Hart, Nathan S; Collin, Shaun P

2014-01-01

Topographic maps that illustrate variations in the density of different neuronal sub-types across the retina are valuable tools for understanding the adaptive significance of retinal specialisations in different species of vertebrates. To date, such maps have been created from raw count data that have been subjected to only limited analysis (linear interpolation) and, in many cases, have been presented as iso-density contour maps with contour lines that have been smoothed 'by eye'. With the use of stereological approach to count neuronal distribution, a more rigorous approach to analysing the count data is warranted and potentially provides a more accurate representation of the neuron distribution pattern. Moreover, a formal spatial analysis of retinal topography permits a more robust comparison of topographic maps within and between species. In this paper, we present a new R-script for analysing the topography of retinal neurons and compare methods of interpolating and smoothing count data for the construction of topographic maps. We compare four methods for spatial analysis of cell count data: Akima interpolation, thin plate spline interpolation, thin plate spline smoothing and Gaussian kernel smoothing. The use of interpolation 'respects' the observed data and simply calculates the intermediate values required to create iso-density contour maps. Interpolation preserves more of the data but, consequently includes outliers, sampling errors and/or other experimental artefacts. In contrast, smoothing the data reduces the 'noise' caused by artefacts and permits a clearer representation of the dominant, 'real' distribution. This is particularly useful where cell density gradients are shallow and small variations in local density may dramatically influence the perceived spatial pattern of neuronal topography. The thin plate spline and the Gaussian kernel methods both produce similar retinal topography maps but the smoothing parameters used may affect the outcome.

Classifying and mapping wetlands and peat resources using digital cartography

USGS Publications Warehouse

Cameron, Cornelia C.; Emery, David A.

1992-01-01

Digital cartography allows the portrayal of spatial associations among diverse data types and is ideally suited for land use and resource analysis. We have developed methodology that uses digital cartography for the classification of wetlands and their associated peat resources and applied it to a 1:24 000 scale map area in New Hampshire. Classifying and mapping wetlands involves integrating the spatial distribution of wetlands types with depth variations in associated peat quality and character. A hierarchically structured classification that integrates the spatial distribution of variations in (1) vegetation, (2) soil type, (3) hydrology, (4) geologic aspects, and (5) peat characteristics has been developed and can be used to build digital cartographic files for resource and land use analysis. The first three parameters are the bases used by the National Wetlands Inventory to classify wetlands and deepwater habitats of the United States. The fourth parameter, geological aspects, includes slope, relief, depth of wetland (from surface to underlying rock or substrate), wetland stratigraphy, and the type and structure of solid and unconsolidated rock surrounding and underlying the wetland. The fifth parameter, peat characteristics, includes the subsurface variation in ash, acidity, moisture, heating value (Btu), sulfur content, and other chemical properties as shown in specimens obtained from core holes. These parameters can be shown as a series of map data overlays with tables that can be integrated for resource or land use analysis.

A method to estimate the effect of deformable image registration uncertainties on daily dose mapping

PubMed Central

Murphy, Martin J.; Salguero, Francisco J.; Siebers, Jeffrey V.; Staub, David; Vaman, Constantin

2012-01-01

Purpose: To develop a statistical sampling procedure for spatially-correlated uncertainties in deformable image registration and then use it to demonstrate their effect on daily dose mapping. Methods: Sequential daily CT studies are acquired to map anatomical variations prior to fractionated external beam radiotherapy. The CTs are deformably registered to the planning CT to obtain displacement vector fields (DVFs). The DVFs are used to accumulate the dose delivered each day onto the planning CT. Each DVF has spatially-correlated uncertainties associated with it. Principal components analysis (PCA) is applied to measured DVF error maps to produce decorrelated principal component modes of the errors. The modes are sampled independently and reconstructed to produce synthetic registration error maps. The synthetic error maps are convolved with dose mapped via deformable registration to model the resulting uncertainty in the dose mapping. The results are compared to the dose mapping uncertainty that would result from uncorrelated DVF errors that vary randomly from voxel to voxel. Results: The error sampling method is shown to produce synthetic DVF error maps that are statistically indistinguishable from the observed error maps. Spatially-correlated DVF uncertainties modeled by our procedure produce patterns of dose mapping error that are different from that due to randomly distributed uncertainties. Conclusions: Deformable image registration uncertainties have complex spatial distributions. The authors have developed and tested a method to decorrelate the spatial uncertainties and make statistical samples of highly correlated error maps. The sample error maps can be used to investigate the effect of DVF uncertainties on daily dose mapping via deformable image registration. An initial demonstration of this methodology shows that dose mapping uncertainties can be sensitive to spatial patterns in the DVF uncertainties. PMID:22320766

Aboveground biomass mapping in French Guiana by combining remote sensing, forest inventories and environmental data

NASA Astrophysics Data System (ADS)

Fayad, Ibrahim; Baghdadi, Nicolas; Guitet, Stéphane; Bailly, Jean-Stéphane; Hérault, Bruno; Gond, Valéry; El Hajj, Mahmoud; Tong Minh, Dinh Ho

2016-10-01

Mapping forest aboveground biomass (AGB) has become an important task, particularly for the reporting of carbon stocks and changes. AGB can be mapped using synthetic aperture radar data (SAR) or passive optical data. However, these data are insensitive to high AGB levels (>150 Mg/ha, and >300 Mg/ha for P-band), which are commonly found in tropical forests. Studies have mapped the rough variations in AGB by combining optical and environmental data at regional and global scales. Nevertheless, these maps cannot represent local variations in AGB in tropical forests. In this paper, we hypothesize that the problem of misrepresenting local variations in AGB and AGB estimation with good precision occurs because of both methodological limits (signal saturation or dilution bias) and a lack of adequate calibration data in this range of AGB values. We test this hypothesis by developing a calibrated regression model to predict variations in high AGB values (mean >300 Mg/ha) in French Guiana by a methodological approach for spatial extrapolation with data from the optical geoscience laser altimeter system (GLAS), forest inventories, radar, optics, and environmental variables for spatial inter- and extrapolation. Given their higher point count, GLAS data allow a wider coverage of AGB values. We find that the metrics from GLAS footprints are correlated with field AGB estimations (R2 = 0.54, RMSE = 48.3 Mg/ha) with no bias for high values. First, predictive models, including remote-sensing, environmental variables and spatial correlation functions, allow us to obtain ;wall-to-wall; AGB maps over French Guiana with an RMSE for the in situ AGB estimates of ∼50 Mg/ha and R2 = 0.66 at a 1-km grid size. We conclude that a calibrated regression model based on GLAS with dependent environmental data can produce good AGB predictions even for high AGB values if the calibration data fit the AGB range. We also demonstrate that small temporal and spatial mismatches between field data and GLAS footprints are not a problem for regional and global calibrated regression models because field data aim to predict large and deep tendencies in AGB variations from environmental gradients and do not aim to represent high but stochastic and temporally limited variations from forest dynamics. Thus, we advocate including a greater variety of data, even if less precise and shifted, to better represent high AGB values in global models and to improve the fitting of these models for high values.

Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) on Mars Reconnaissance Orbiter (MRO)

NASA Astrophysics Data System (ADS)

Murchie, S.; Arvidson, R.; Bedini, P.; Beisser, K.; Bibring, J.-P.; Bishop, J.; Boldt, J.; Cavender, P.; Choo, T.; Clancy, R. T.; Darlington, E. H.; Des Marais, D.; Espiritu, R.; Fort, D.; Green, R.; Guinness, E.; Hayes, J.; Hash, C.; Heffernan, K.; Hemmler, J.; Heyler, G.; Humm, D.; Hutcheson, J.; Izenberg, N.; Lee, R.; Lees, J.; Lohr, D.; Malaret, E.; Martin, T.; McGovern, J. A.; McGuire, P.; Morris, R.; Mustard, J.; Pelkey, S.; Rhodes, E.; Robinson, M.; Roush, T.; Schaefer, E.; Seagrave, G.; Seelos, F.; Silverglate, P.; Slavney, S.; Smith, M.; Shyong, W.-J.; Strohbehn, K.; Taylor, H.; Thompson, P.; Tossman, B.; Wirzburger, M.; Wolff, M.

2007-05-01

The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) is a hyperspectral imager on the Mars Reconnaissance Orbiter (MRO) spacecraft. CRISM consists of three subassemblies, a gimbaled Optical Sensor Unit (OSU), a Data Processing Unit (DPU), and the Gimbal Motor Electronics (GME). CRISM's objectives are (1) to map the entire surface using a subset of bands to characterize crustal mineralogy, (2) to map the mineralogy of key areas at high spectral and spatial resolution, and (3) to measure spatial and seasonal variations in the atmosphere. These objectives are addressed using three major types of observations. In multispectral mapping mode, with the OSU pointed at planet nadir, data are collected at a subset of 72 wavelengths covering key mineralogic absorptions and binned to pixel footprints of 100 or 200 m/pixel. Nearly the entire planet can be mapped in this fashion. In targeted mode the OSU is scanned to remove most along-track motion, and a region of interest is mapped at full spatial and spectral resolution (15-19 m/pixel, 362-3920 nm at 6.55 nm/channel). Ten additional abbreviated, spatially binned images are taken before and after the main image, providing an emission phase function (EPF) of the site for atmospheric study and correction of surface spectra for atmospheric effects. In atmospheric mode, only the EPF is acquired. Global grids of the resulting lower data volume observations are taken repeatedly throughout the Martian year to measure seasonal variations in atmospheric properties. Raw, calibrated, and map-projected data are delivered to the community with a spectral library to aid in interpretation.

Employing a portable X-Ray fluorescence (P-XRF) analyser and GIS to identify and map heavy metal pollution in soils of a traditional bonfire site

NASA Astrophysics Data System (ADS)

Dao, Ligang; Zhang, Chaosheng; Morrison, Liam

2010-05-01

Soils in the vicinity of bonfires are recipients of metal contaminants from burning of metal-containing materials. In order to better understand the impacts of bonfires on soils, a total of 218 surface soil samples were collected from a traditional bonfire site in Galway City, Ireland. Concentrations of Cu, Pb and Zn were determined using a portable X-ray Fluorescence (P-XRF) analyser. Strong variations were observed for these metals, and several samples contained elevated Zn concentrations which exceeded the intervention threshold of the Dutch criteria (720 mg kg-1). Spatial clusters and spatial outliers were detected using the local Moran's I index and were mapped using GIS. Two clear high value spatial clusters could be observed on the upper left side and centre part of the study area for Cu, Pb and Zn. Results of variogram analyses showed high nugget-sill-ratios for Cu, Pb and Zn, indicating strong spatial variation over short distances which could be resulted from anthropogenic activities. The spatial interpolation method of ordinary kriging was applied to produce the spatial interpolation maps for Cu, Pb and Zn, and the areas with elevated concentrations were in line with historical locations of the bonfires. The hazard maps showed small parts of the study area with Zn concentrations exceeding the Dutch intervention values. In order to prevent further contamination from bonfires, it is advised that tyres and other metal-containing wastes should not be burnt. The results in this study provide useful information for management of bonfires.

Modern Climate Analogues of Late-Quaternary Paleoclimates for the Western United States.

NASA Astrophysics Data System (ADS)

Mock, Cary Jeffrey

This study examined spatial variations of modern and late-Quaternary climates for the western United States. Synoptic climatological analyses of the modern record identified the predominate climatic controls that normally produce the principal modes of spatial climatic variability. They also provided a modern standard to assess past climates. Maps of the month-to-month changes in 500 mb heights, sea-level pressure, temperature, and precipitation illustrated how different climatic controls govern the annual cycle of climatic response. The patterns of precipitation ratios, precipitation bar graphs, and the seasonal precipitation maximum provided additional insight into how different climatic controls influence spatial climatic variations. Synoptic-scale patterns from general circulation model (GCM) simulations or from analyses of climatic indices were used as the basis for finding modern climate analogues for 18 ka and 9 ka. Composite anomaly maps of atmospheric circulation, precipitation, and temperature were compared with effective moisture maps compiled from proxy data to infer how the patterns, which were evident from the proxy data, were generated. The analyses of the modern synoptic climatology indicate that smaller-scale climatic controls must be considered along with larger-scale ones in order to explain patterns of spatial climate heterogeneity. Climatic extremes indicate that changes in the spatial patterns of precipitation seasonality are the exception rather than the rule, reflecting the strong influence of smaller-scale controls. Modern climate analogues for both 18 ka and 9 ka clearly depict the dry Northwest/wet Southwest contrast that is suggested by GCM simulations and paleoclimatic evidence. 18 ka analogues also show the importance of smaller-scale climatic controls in explaining spatial climatic variation in the Northwest and northern Great Plains. 9 ka analogues provide climatological explanations for patterns of spatial heterogeneity over several mountainous areas as suggested by paleoclimatic evidence. Modern analogues of past climates supplement modeling approaches by providing information below the resolution of model simulations. Analogues can be used to examine the controls of spatial paleoclimatic variation if sufficient instrumental data and paleoclimatic evidence are available, and if one carefully exercises uniformitarianism when extrapolating modern relationships to the past.

Natural habitats matter: Determinants of spatial pattern in the composition of animal assemblages of the Czech Republic

NASA Astrophysics Data System (ADS)

Divíšek, Jan; Zelený, David; Culek, Martin; Št'astný, Karel

2014-08-01

Studies that explore species-environment relationships at a broad scale are usually limited by the availability of sufficient habitat description, which is often too coarse to differentiate natural habitat patches. Therefore, it is not well understood how the distribution of natural habitats affects broad-scale patterns in the distribution of animal species. In this study, we evaluate the role of field-mapped natural habitats, land-cover types derived from remote sensing and climate on the composition of assemblages of five distinct animal groups, namely non-volant mammals, birds, reptiles, amphibians and butterflies native to the Czech Republic. First, we used variation partitioning based on redundancy analysis to evaluate the extent to which the environmental variables and their spatial structure might underlie the observed spatial patterns in the composition of animal assemblages. Second, we partitioned variations explained by climate, natural habitats and land-cover to compare their relative importance. Finally, we tested the independent effects of each variable in order to evaluate the significance of their contributions to the environmental model. Our results showed that spatial patterns in the composition of assemblages of almost all the considered animal groups may be ascribed mostly to variations in the environment. Although the shared effects of climatic variables, natural habitats and land-cover types explained the largest proportion of variation in each animal group, the variation explained purely by natural habitats was always higher than the variation explained purely by climate or land-cover. We conclude that most spatial variation in the composition of assemblages of almost all animal groups probably arises from biological processes operating within a spatially structured environment and suggest that natural habitats are important to explain observed patterns because they often perform better than habitat descriptions based on remote sensing. This underlines the value of using appropriate habitat data, for which high-resolution and large-area field-mapping projects are necessary.

Genome-wide profiling of chromosome interactions in Plasmodium falciparum characterizes nuclear architecture and reconfigurations associated with antigenic variation

PubMed Central

Lemieux, Jacob E; Kyes, Sue A; Otto, Thomas D; Feller, Avi I; Eastman, Richard T; Pinches, Robert A; Berriman, Matthew; Su, Xin-zhuan; Newbold, Chris I

2013-01-01

Spatial relationships within the eukaryotic nucleus are essential for proper nuclear function. In Plasmodium falciparum, the repositioning of chromosomes has been implicated in the regulation of the expression of genes responsible for antigenic variation, and the formation of a single, peri-nuclear nucleolus results in the clustering of rDNA. Nevertheless, the precise spatial relationships between chromosomes remain poorly understood, because, until recently, techniques with sufficient resolution have been lacking. Here we have used chromosome conformation capture and second-generation sequencing to study changes in chromosome folding and spatial positioning that occur during switches in var gene expression. We have generated maps of chromosomal spatial affinities within the P. falciparum nucleus at 25 Kb resolution, revealing a structured nucleolus, an absence of chromosome territories, and confirming previously identified clustering of heterochromatin foci. We show that switches in var gene expression do not appear to involve interaction with a distant enhancer, but do result in local changes at the active locus. These maps reveal the folding properties of malaria chromosomes, validate known physical associations, and characterize the global landscape of spatial interactions. Collectively, our data provide critical information for a better understanding of gene expression regulation and antigenic variation in malaria parasites. PMID:23980881

Mapping spatial and temporal variation of stream water temperature in the upper Esopus Creek watershed

NASA Astrophysics Data System (ADS)

Chien, H.; McGlinn, L.

2017-12-01

The upper Esopus Creek and its tributary streams located in the Catskill Mountain region of New York State provide habitats for cold-adapted aquatic species. However, ongoing global warming may change the stream water temperature within a watershed and disturb the persistence of coldwater habitats. Characterizing thermal regimes within the upper Esopus Creek watershed is important to provide information of thermally suitable habitats for aquatic species. The objectives of this study are to measure stream water temperature and map thermal variability among tributaries to the Esopus Creek and within Esopus Creek. These objectives will be achieved by measuring stream water temperature for at least two years. More than 100 water temperature data loggers have been placed in the upper Esopus Creek and their tributaries to collect 30-minute interval water temperatures. With the measured water temperature, we will use spatial interpolation in ArcGIS to create weekly and monthly water temperature surface maps to evaluate the thermal variation over time and space within the upper Esopus Creek watershed. We will characterize responsiveness of water temperature in tributary streams to air temperature as well. This information of spatial and temporal variation of stream water temperature will assist stream managers with prioritizing management practices that maintain or enhance connectivity of thermally suitable habitats in high priority areas.

Predictive Mapping of the Biotic Condition of Conterminous U.S. Rivers and Streams

EPA Science Inventory

Understanding and mapping the spatial variations in the biological condition of streams could provide an important tool for assessment and restoration of stream ecosystems. The US EPA’s National Rivers and Streams Assessment (NRSA) summarizes the percent of stream lengths within ...

Predicting and quantifying soil processes using “geomorphon” landform Classification

USDA-ARS?s Scientific Manuscript database

Soil development and behavior vary spatially at multiple observation scales. Predicting and quantifying soil properties and processes via a catena integrates predictable landscape scale variation relevant to both management decisions and soil survey. Soil maps generally convey variation as a set of ...

Temporal variation in spatial sources of mercury loading to rivers (presentation)

EPA Science Inventory

Source areas within the Fox River watershed (WI, USA) were mapped for individual discharge events. The spatial distribution of source areas varied between, and over the duration of, individual discharge events. The percent contribution of runoff by land cover type within source a...

Temporal variation in spatial sources of discharge in a large watershed

EPA Science Inventory

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...

A BAYESIAN SPATIAL AND TEMPORAL MODELING APPROACH TO MAPPING GEOGRAPHIC VARIATION IN MORTALITY RATES FOR SUBNATIONAL AREAS WITH R-INLA.

PubMed

Khana, Diba; Rossen, Lauren M; Hedegaard, Holly; Warner, Margaret

2018-01-01

Hierarchical Bayes models have been used in disease mapping to examine small scale geographic variation. State level geographic variation for less common causes of mortality outcomes have been reported however county level variation is rarely examined. Due to concerns about statistical reliability and confidentiality, county-level mortality rates based on fewer than 20 deaths are suppressed based on Division of Vital Statistics, National Center for Health Statistics (NCHS) statistical reliability criteria, precluding an examination of spatio-temporal variation in less common causes of mortality outcomes such as suicide rates (SRs) at the county level using direct estimates. Existing Bayesian spatio-temporal modeling strategies can be applied via Integrated Nested Laplace Approximation (INLA) in R to a large number of rare causes of mortality outcomes to enable examination of spatio-temporal variations on smaller geographic scales such as counties. This method allows examination of spatiotemporal variation across the entire U.S., even where the data are sparse. We used mortality data from 2005-2015 to explore spatiotemporal variation in SRs, as one particular application of the Bayesian spatio-temporal modeling strategy in R-INLA to predict year and county-specific SRs. Specifically, hierarchical Bayesian spatio-temporal models were implemented with spatially structured and unstructured random effects, correlated time effects, time varying confounders and space-time interaction terms in the software R-INLA, borrowing strength across both counties and years to produce smoothed county level SRs. Model-based estimates of SRs were mapped to explore geographic variation.

Covariate selection with iterative principal component analysis for predicting physical

USDA-ARS?s Scientific Manuscript database

Local and regional soil data can be improved by coupling new digital soil mapping techniques with high resolution remote sensing products to quantify both spatial and absolute variation of soil properties. The objective of this research was to advance data-driven digital soil mapping techniques for ...

Mapping spatial patterns of denitrifiers at large scales (Invited)

NASA Astrophysics Data System (ADS)

Philippot, L.; Ramette, A.; Saby, N.; Bru, D.; Dequiedt, S.; Ranjard, L.; Jolivet, C.; Arrouays, D.

2010-12-01

Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. Here we combined molecular approaches and geostatistical modeling to explore spatial patterns of the denitrifying community at large scales. The distribution of denitrifrying community was investigated over 107 sites in Burgundy, a 31 500 km2 region of France, using a 16 X 16 km sampling grid. At each sampling site, the abundances of denitrifiers and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time and soil physico-chemical properties to the denitrifier spatial distribution were analyzed by canonical variation partitioning. Our results indicate that 43% to 85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 739 km and used geostatistical modelling to generate predictive maps of the distribution of denitrifiers at the landscape scale. Studying the distribution of the denitrifiers at large scale can help closing the artificial gap between the investigation of microbial processes and microbial community ecology, therefore facilitating our understanding of the relationships between the ecology of denitrifiers and N-fluxes by denitrification.

A Comparison of Spatial Analysis Methods for the Construction of Topographic Maps of Retinal Cell Density

PubMed Central

Garza-Gisholt, Eduardo; Hemmi, Jan M.; Hart, Nathan S.; Collin, Shaun P.

2014-01-01

Topographic maps that illustrate variations in the density of different neuronal sub-types across the retina are valuable tools for understanding the adaptive significance of retinal specialisations in different species of vertebrates. To date, such maps have been created from raw count data that have been subjected to only limited analysis (linear interpolation) and, in many cases, have been presented as iso-density contour maps with contour lines that have been smoothed ‘by eye’. With the use of stereological approach to count neuronal distribution, a more rigorous approach to analysing the count data is warranted and potentially provides a more accurate representation of the neuron distribution pattern. Moreover, a formal spatial analysis of retinal topography permits a more robust comparison of topographic maps within and between species. In this paper, we present a new R-script for analysing the topography of retinal neurons and compare methods of interpolating and smoothing count data for the construction of topographic maps. We compare four methods for spatial analysis of cell count data: Akima interpolation, thin plate spline interpolation, thin plate spline smoothing and Gaussian kernel smoothing. The use of interpolation ‘respects’ the observed data and simply calculates the intermediate values required to create iso-density contour maps. Interpolation preserves more of the data but, consequently includes outliers, sampling errors and/or other experimental artefacts. In contrast, smoothing the data reduces the ‘noise’ caused by artefacts and permits a clearer representation of the dominant, ‘real’ distribution. This is particularly useful where cell density gradients are shallow and small variations in local density may dramatically influence the perceived spatial pattern of neuronal topography. The thin plate spline and the Gaussian kernel methods both produce similar retinal topography maps but the smoothing parameters used may affect the outcome. PMID:24747568

Terahertz Mapping of Microstructure and Thickness Variations

NASA Technical Reports Server (NTRS)

Roth, Donald J.; Seebo, Jeffrey P.; Winfree, William P.

2010-01-01

A noncontact method has been devised for mapping or imaging spatial variations in the thickness and microstructure of a layer of a dielectric material. The method involves (1) placement of the dielectric material on a metal substrate, (2) through-the-thickness pulse-echo measurements by use of electromagnetic waves in the terahertz frequency range with a raster scan in a plane parallel to the substrate surface that do not require coupling of any kind, and (3) appropriate processing of the digitized measurement data.

Mapping Foliar Traits Across Biomes Using Imaging Spectroscopy: A Synthesis

NASA Astrophysics Data System (ADS)

Townsend, P. A.; Singh, A.; Wang, Z.

2016-12-01

One of the great promises of imaging spectroscopy - also known as hyperspectral remote sensing - is the ability to map the spatial variation in foliar functional traits, such as nitrogen concentration, pigments, leaf structure, photosynthetic capacity and secondary biochemistry, that drive terrestrial ecosystem processes. A remote-sensing approach enables characterization of within- and between-biome variations that may be crucial to understanding ecosystem responses to pests, pathogens and environmental change. We provide a synthesis of the foliar traits that can be mapped from imaging spectroscopy, as well as an overview of both the major applications of trait maps derived from hyperspectral imagery and current gaps in our knowledge and capacity. Specifically, we make the case that a global imaging spectroscopy mission will provide unique and urgent measurements necessary to understand the response of agricultural and natural systems to rapid global changes. Finally, we present a quantitative framework to utilize imaging spectroscopy to characterize spatial and temporal variation in foliar traits within and between biomes. From this we can infer the dynamics of vegetation function across ecosystems, especially in transition zones and environmentally sensitive systems. Eventual launch of a global imaging spectroscopy mission will enable collection of narrowband VSWIR measurements that will help close major gaps in our understanding of biogeochemical cycles and improve representation of vegetated biomes in Earth system process models.

Global-scale surface spectral variations on Titan seen from Cassini/VIMS

USGS Publications Warehouse

Barnes, J.W.; Brown, R.H.; Soderblom, L.; Buratti, B.J.; Sotin, Christophe; Rodriguez, S.; Le, Mouelic S.; Baines, K.H.; Clark, R.; Nicholson, P.

2007-01-01

We present global-scale maps of Titan from the Visual and Infrared Mapping Spectrometer (VIMS) instrument on Cassini. We map at 64 near-infrared wavelengths simultaneously, covering the atmospheric windows at 0.94, 1.08, 1.28, 1.6, 2.0, 2.8, and 5 ??m with a typical resolution of 50 km/pixel or a typical total integration time of 1 s. Our maps have five to ten times the resolution of ground-based maps, better spectral resolution across most windows, coverage in multiple atmospheric windows, and represent the first spatially resolved maps of Titan at 5 ??m. The VIMS maps provide context and surface spectral information in support of other Cassini instruments. We note a strong latitudinal dependence in the spectral character of Titan's surface, and partition the surface into 9 spectral units that we describe in terms of spectral and spatial characteristics. ?? 2006 Elsevier Inc. All rights reserved.

Mapping the Drivers of Climate Change Vulnerability for Australia’s Threatened Species

PubMed Central

Lee, Jasmine R.; Maggini, Ramona; Taylor, Martin F. J.; Fuller, Richard A.

2015-01-01

Effective conservation management for climate adaptation rests on understanding the factors driving species’ vulnerability in a spatially explicit manner so as to direct on-ground action. However, there have been only few attempts to map the spatial distribution of the factors driving vulnerability to climate change. Here we conduct a species-level assessment of climate change vulnerability for a sample of Australia’s threatened species and map the distribution of species affected by each factor driving climate change vulnerability across the continent. Almost half of the threatened species assessed were considered vulnerable to the impacts of climate change: amphibians being the most vulnerable group, followed by plants, reptiles, mammals and birds. Species with more restricted distributions were more likely to show high climate change vulnerability than widespread species. The main factors driving climate change vulnerability were low genetic variation, dependence on a particular disturbance regime and reliance on a particular moisture regime or habitat. The geographic distribution of the species impacted by each driver varies markedly across the continent, for example species impacted by low genetic variation are prevalent across the human-dominated south-east of the country, while reliance on particular moisture regimes is prevalent across northern Australia. Our results show that actions to address climate adaptation will need to be spatially appropriate, and that in some regions a complex suite of factors driving climate change vulnerability will need to be addressed. Taxonomic and geographic variation in the factors driving climate change vulnerability highlights an urgent need for a spatial prioritisation of climate adaptation actions for threatened species. PMID:26017785

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

NASA Astrophysics Data System (ADS)

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

2010-05-01

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

Geostatistics for spatial genetic structures: study of wild populations of perennial ryegrass.

PubMed

Monestiez, P; Goulard, M; Charmet, G

1994-04-01

Methods based on geostatistics were applied to quantitative traits of agricultural interest measured on a collection of 547 wild populations of perennial ryegrass in France. The mathematical background of these methods, which resembles spatial autocorrelation analysis, is briefly described. When a single variable is studied, the spatial structure analysis is similar to spatial autocorrelation analysis, and a spatial prediction method, called "kriging", gives a filtered map of the spatial pattern over all the sampled area. When complex interactions of agronomic traits with different evaluation sites define a multivariate structure for the spatial analysis, geostatistical methods allow the spatial variations to be broken down into two main spatial structures with ranges of 120 km and 300 km, respectively. The predicted maps that corresponded to each range were interpreted as a result of the isolation-by-distance model and as a consequence of selection by environmental factors. Practical collecting methodology for breeders may be derived from such spatial structures.

Preliminary surficial geologic map of the Newberry Springs 30' x 60' quadrangle, California

USGS Publications Warehouse

Phelps, G.A.; Bedford, D.R.; Lidke, D.J.; Miller, D.M.; Schmidt, K.M.

2012-01-01

The Newberry Springs 30' x 60' quadrangle is located in the central Mojave Desert of southern California. It is split approximately into northern and southern halves by I-40, with the city of Barstow at its western edge and the town of Ludlow near its eastern edge. The map area spans lat 34°30 to 35° N. to long -116 °to -117° W. and covers over 1,000 km2. We integrate the results of surficial geologic mapping conducted during 2002-2005 with compilations of previous surficial mapping and bedrock geologic mapping. Quaternary units are subdivided in detail on the map to distinguish variations in age, process of formation, pedogenesis, lithology, and spatial interdependency, whereas pre-Quaternary bedrock units are grouped into generalized assemblages that emphasize their attributes as hillslope-forming materials and sources of parent material for the Quaternary units. The spatial information in this publication is presented in two forms: a spatial database and a geologic map. The geologic map is a view (the display of an extracted subset of the database at a given time) of the spatial database; it highlights key aspects of the database and necessarily does not show all of the data contained therein. The database contains detailed information about Quaternary geologic unit composition, authorship, and notes regarding geologic units, faults, contacts, and local vegetation. The amount of information contained in the database is too large to show on a single map, so a restricted subset of the information was chosen to summarize the overall nature of the geology. Refer to the database for additional information. Accompanying the spatial data are the map documentation and spatial metadata. The map documentation (this document) describes the geologic setting and history of the Newberry Springs map sheet, summarizes the age and physical character of each map unit, and describes principal faults and folds. The Federal Geographic Data Committee (FGDC) compliant metadata provides detailed information about the digital files and file structure of the spatial data.

Variations in debris distribution and thickness on Himalayan debris-covered glaciers

NASA Astrophysics Data System (ADS)

Gibson, Morgan; Rowan, Ann; Irvine-Fynn, Tristram; Quincey, Duncan; Glasser, Neil

2016-04-01

Many Himalayan glaciers are characterised by extensive supraglacial debris coverage; in Nepal 33% of glaciers exhibit a continuous layer of debris covering their ablation areas. The presence of such a debris layer modulates a glacier's response to climatic change. However, the impact of this modulation is poorly constrained due to inadequate quantification of the impact of supraglacial debris on glacier surface energy balance. Few data exist to describe spatial and temporal variations in parameters such as debris thickness, albedo and surface roughness in energy balance calculations. Consequently, improved understanding of how debris affects Himalayan glacier ablation requires the assessment of surface energy balance model sensitivity to spatial and temporal variability in these parameters. Measurements of debris thickness, surface temperature, reflectance and roughness were collected across Khumbu Glacier during the pre- and post-monsoon seasons of 2014 and 2015. The extent of the spatial variation in each of these parameters are currently being incorporated into a point-based glacier surface energy balance model (CMB-RES, Collier et al., 2014, The Cryosphere), applied on a pixel-by-pixel basis to the glacier surface, to ascertain the sensitivity of glacier surface energy balance and ablation values to these debris parameters. A time series of debris thickness maps have been produced for Khumbu Glacier over a 15-year period (2000-2015) using Mihalcea et al.'s (2008, Cold Reg. Sci. Technol.) method, which utilised multi-temporal ASTER thermal imagery and our in situ debris surface temperature and thickness measurements. Change detection between these maps allowed the identification of variations in debris thickness that could be compared to discrete measurements, glacier surface velocity and morphology of the debris-covered area. Debris thickness was found to vary spatially between 0.1 and 4 metres within each debris thickness map, and temporally on the order of 1 to 2 m. Temporal variability was a result of differential surface lowering, spatial variability in glacier surface velocities and intermittent input of debris to the glacier surface through mass movement. Most debris thickening is seen in initially thin areas of debris (< 0.4 m) or within ~1 km of the glacier terminus. Surface energy balance modelling is currently underway to determine the effect of these variations in debris thickness, and other parameters mentioned previously. Future work will be to calculate debris transport flux on the surface of Khumbu Glacier using the time series of debris thickness maps. Debris flux and refined energy balance calculations will then be incorporated into a 3-D ice flow model to determine the response of Khumbu Glacier to debris transport and climatic changes.

Efficient statistical mapping of avian count data

USGS Publications Warehouse

Royle, J. Andrew; Wikle, C.K.

2005-01-01

We develop a spatial modeling framework for count data that is efficient to implement in high-dimensional prediction problems. We consider spectral parameterizations for the spatially varying mean of a Poisson model. The spectral parameterization of the spatial process is very computationally efficient, enabling effective estimation and prediction in large problems using Markov chain Monte Carlo techniques. We apply this model to creating avian relative abundance maps from North American Breeding Bird Survey (BBS) data. Variation in the ability of observers to count birds is modeled as spatially independent noise, resulting in over-dispersion relative to the Poisson assumption. This approach represents an improvement over existing approaches used for spatial modeling of BBS data which are either inefficient for continental scale modeling and prediction or fail to accommodate important distributional features of count data thus leading to inaccurate accounting of prediction uncertainty.

Quantitative Susceptibility Mapping of Human Brain Reflects Spatial Variation in Tissue Composition

PubMed Central

Li, Wei; Wu, Bing; Liu, Chunlei

2011-01-01

Image phase from gradient echo MRI provides a unique contrast that reflects brain tissue composition variations, such as iron and myelin distribution. Phase imaging is emerging as a powerful tool for the investigation of functional brain anatomy and disease diagnosis. However, the quantitative value of phase is compromised by its nonlocal and orientation dependent properties. There is an increasing need for reliable quantification of magnetic susceptibility, the intrinsic property of tissue. In this study, we developed a novel and accurate susceptibility mapping method that is also phase-wrap insensitive. The proposed susceptibility mapping method utilized two complementary equations: (1) the Fourier relationship of phase and magnetic susceptibility; and (2) the first-order partial derivative of the first equation in the spatial frequency domain. In numerical simulation, this method reconstructed the susceptibility map almost free of streaking artifact. Further, the iterative implementation of this method allowed for high quality reconstruction of susceptibility maps of human brain in vivo. The reconstructed susceptibility map provided excellent contrast of iron-rich deep nuclei and white matter bundles from surrounding tissues. Further, it also revealed anisotropic magnetic susceptibility in brain white matter. Hence, the proposed susceptibility mapping method may provide a powerful tool for the study of brain physiology and pathophysiology. Further elucidation of anisotropic magnetic susceptibility in vivo may allow us to gain more insight into the white matter microarchitectures. PMID:21224002

Spatial access priority mapping (SAPM) with fishers: a quantitative GIS method for participatory planning.

PubMed

Yates, Katherine L; Schoeman, David S

2013-01-01

Spatial management tools, such as marine spatial planning and marine protected areas, are playing an increasingly important role in attempts to improve marine management and accommodate conflicting needs. Robust data are needed to inform decisions among different planning options, and early inclusion of stakeholder involvement is widely regarded as vital for success. One of the biggest stakeholder groups, and the most likely to be adversely impacted by spatial restrictions, is the fishing community. In order to take their priorities into account, planners need to understand spatial variation in their perceived value of the sea. Here a readily accessible, novel method for quantitatively mapping fishers' spatial access priorities is presented. Spatial access priority mapping, or SAPM, uses only basic functions of standard spreadsheet and GIS software. Unlike the use of remote-sensing data, SAPM actively engages fishers in participatory mapping, documenting rather than inferring their priorities. By so doing, SAPM also facilitates the gathering of other useful data, such as local ecological knowledge. The method was tested and validated in Northern Ireland, where over 100 fishers participated in a semi-structured questionnaire and mapping exercise. The response rate was excellent, 97%, demonstrating fishers' willingness to be involved. The resultant maps are easily accessible and instantly informative, providing a very clear visual indication of which areas are most important for the fishers. The maps also provide quantitative data, which can be used to analyse the relative impact of different management options on the fishing industry and can be incorporated into planning software, such as MARXAN, to ensure that conservation goals can be met at minimum negative impact to the industry. This research shows how spatial access priority mapping can facilitate the early engagement of fishers and the ready incorporation of their priorities into the decision-making process in a transparent, quantitative way.

Creating Geologically Based Radon Potential Maps for Kentucky

NASA Astrophysics Data System (ADS)

Overfield, B.; Hahn, E.; Wiggins, A.; Andrews, W. M., Jr.

2017-12-01

Radon potential in the United States, Kentucky in particular, has historically been communicated using a single hazard level for each county; however, physical phenomena are not controlled by administrative boundaries, so single-value county maps do not reflect the significant variations in radon potential in each county. A more accurate approach uses bedrock geology as a predictive tool. A team of nurses, health educators, statisticians, and geologists partnered to create 120 county maps showing spatial variations in radon potential by intersecting residential radon test kit results (N = 60,000) with a statewide 1:24,000-scale bedrock geology coverage to determine statistically valid radon-potential estimates for each geologic unit. Maps using geology as a predictive tool for radon potential are inherently more detailed than single-value county maps. This mapping project revealed that areas in central and south-central Kentucky with the highest radon potential are underlain by shales and karstic limestones.

Modeling Chinese ionospheric layer parameters based on EOF analysis

NASA Astrophysics Data System (ADS)

Yu, You; Wan, Weixing; Xiong, Bo; Ren, Zhipeng; Zhao, Biqiang; Zhang, Yun; Ning, Baiqi; Liu, Libo

2015-05-01

Using 24-ionosonde observations in and around China during the 20th solar cycle, an assimilative model is constructed to map the ionospheric layer parameters (foF2, hmF2, M(3000)F2, and foE) over China based on empirical orthogonal function (EOF) analysis. First, we decompose the background maps from the International Reference Ionosphere model 2007 (IRI-07) into different EOF modes. The obtained EOF modes consist of two factors: the EOF patterns and the corresponding EOF amplitudes. These two factors individually reflect the spatial distributions (e.g., the latitudinal dependence such as the equatorial ionization anomaly structure and the longitude structure with east-west difference) and temporal variations on different time scales (e.g., solar cycle, annual, semiannual, and diurnal variations) of the layer parameters. Then, the EOF patterns and long-term observations of ionosondes are assimilated to get the observed EOF amplitudes, which are further used to construct the Chinese Ionospheric Maps (CIMs) of the layer parameters. In contrast with the IRI-07 model, the mapped CIMs successfully capture the inherent temporal and spatial variations of the ionospheric layer parameters. Finally, comparison of the modeled (EOF and IRI-07 model) and observed values reveals that the EOF model reproduces the observation with smaller root-mean-square errors and higher linear correlation coefficients. In addition, IRI discrepancy at the low latitude especially for foF2 is effectively removed by EOF model.

Modeling Chinese ionospheric layer parameters based on EOF analysis

NASA Astrophysics Data System (ADS)

Yu, You; Wan, Weixing

2016-04-01

Using 24-ionosonde observations in and around China during the 20th solar cycle, an assimilative model is constructed to map the ionospheric layer parameters (foF2, hmF2, M(3000)F2, and foE) over China based on empirical orthogonal function (EOF) analysis. First, we decompose the background maps from the International Reference Ionosphere model 2007 (IRI-07) into different EOF modes. The obtained EOF modes consist of two factors: the EOF patterns and the corresponding EOF amplitudes. These two factors individually reflect the spatial distributions (e.g., the latitudinal dependence such as the equatorial ionization anomaly structure and the longitude structure with east-west difference) and temporal variations on different time scales (e.g., solar cycle, annual, semiannual, and diurnal variations) of the layer parameters. Then, the EOF patterns and long-term observations of ionosondes are assimilated to get the observed EOF amplitudes, which are further used to construct the Chinese Ionospheric Maps (CIMs) of the layer parameters. In contrast with the IRI-07 model, the mapped CIMs successfully capture the inherent temporal and spatial variations of the ionospheric layer parameters. Finally, comparison of the modeled (EOF and IRI-07 model) and observed values reveals that the EOF model reproduces the observation with smaller root-mean-square errors and higher linear correlation co- efficients. In addition, IRI discrepancy at the low latitude especially for foF2 is effectively removed by EOF model.

Use of geographically weighted logistic regression to quantify spatial variation in the environmental and sociodemographic drivers of leptospirosis in Fiji: a modelling study.

PubMed

Mayfield, Helen J; Lowry, John H; Watson, Conall H; Kama, Mike; Nilles, Eric J; Lau, Colleen L

2018-05-01

Leptospirosis is a globally important zoonotic disease, with complex exposure pathways that depend on interactions between human beings, animals, and the environment. Major drivers of outbreaks include flooding, urbanisation, poverty, and agricultural intensification. The intensity of these drivers and their relative importance vary between geographical areas; however, non-spatial regression methods are incapable of capturing the spatial variations. This study aimed to explore the use of geographically weighted logistic regression (GWLR) to provide insights into the ecoepidemiology of human leptospirosis in Fiji. We obtained field data from a cross-sectional community survey done in 2013 in the three main islands of Fiji. A blood sample obtained from each participant (aged 1-90 years) was tested for anti-Leptospira antibodies and household locations were recorded using GPS receivers. We used GWLR to quantify the spatial variation in the relative importance of five environmental and sociodemographic covariates (cattle density, distance to river, poverty rate, residential setting [urban or rural], and maximum rainfall in the wettest month) on leptospirosis transmission in Fiji. We developed two models, one using GWLR and one with standard logistic regression; for each model, the dependent variable was the presence or absence of anti-Leptospira antibodies. GWLR results were compared with results obtained with standard logistic regression, and used to produce a predictive risk map and maps showing the spatial variation in odds ratios (OR) for each covariate. The dataset contained location information for 2046 participants from 1922 households representing 81 communities. The Aikaike information criterion value of the GWLR model was 1935·2 compared with 1254·2 for the standard logistic regression model, indicating that the GWLR model was more efficient. Both models produced similar OR for the covariates, but GWLR also detected spatial variation in the effect of each covariate. Maximum rainfall had the least variation across space (median OR 1·30, IQR 1·27-1·35), and distance to river varied the most (1·45, 1·35-2·05). The predictive risk map indicated that the highest risk was in the interior of Viti Levu, and the agricultural region and southern end of Vanua Levu. GWLR provided a valuable method for modelling spatial heterogeneity of covariates for leptospirosis infection and their relative importance over space. Results of GWLR could be used to inform more place-specific interventions, particularly for diseases with strong environmental or sociodemographic drivers of transmission. WHO, Australian National Health & Medical Research Council, University of Queensland, UK Medical Research Council, Chadwick Trust. Copyright © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.

Mapping the Risk of Soil-Transmitted Helminthic Infections in the Philippines

PubMed Central

Leonardo, Lydia; Gray, Darren J.; Carabin, Hélène; Halton, Kate; McManus, Donald P.; Williams, Gail M.; Rivera, Pilarita; Saniel, Ofelia; Hernandez, Leda; Yakob, Laith; McGarvey, Stephen T.; Clements, Archie C. A.

2015-01-01

Background In order to increase the efficient allocation of soil-transmitted helminth (STH) disease control resources in the Philippines, we aimed to describe for the first time the spatial variation in the prevalence of A. lumbricoides, T. trichiura and hookworm across the country, quantify the association between the physical environment and spatial variation of STH infection and develop predictive risk maps for each infection. Methodology/Principal Findings Data on STH infection from 35,573 individuals across the country were geolocated at the barangay level and included in the analysis. The analysis was stratified geographically in two major regions: 1) Luzon and the Visayas and 2) Mindanao. Bayesian geostatistical models of STH prevalence were developed, including age and sex of individuals and environmental variables (rainfall, land surface temperature and distance to inland water bodies) as predictors, and diagnostic uncertainty was incorporated. The role of environmental variables was different between regions of the Philippines. This analysis revealed that while A. lumbricoides and T. trichiura infections were widespread and highly endemic, hookworm infections were more circumscribed to smaller foci in the Visayas and Mindanao. Conclusions/Significance This analysis revealed significant spatial variation in STH infection prevalence within provinces of the Philippines. This suggests that a spatially targeted approach to STH interventions, including mass drug administration, is warranted. When financially possible, additional STH surveys should be prioritized to high-risk areas identified by our study in Luzon. PMID:26368819

Impact of spatial variation in snow water equivalent and snow ablation on spring snowcover depletion over an alpine ridge

NASA Astrophysics Data System (ADS)

Schirmer, Michael; Harder, Phillip; Pomeroy, John

2016-04-01

The spatial and temporal dynamics of mountain snowmelt are controlled by the spatial distribution of snow accumulation and redistribution and the pattern of melt energy applied to this snowcover. In order to better quantify the spatial variations of accumulation and ablation, Structure-from-Motion techniques were applied to sequential aerial photographs of an alpine ridge in the Canadian Rocky Mountains taken from an Unmanned Aerial Vehicle (UAV). Seven spatial maps of snow depth and changes to depth during late melt (May-July) were generated at very high resolutions covering an area of 800 x 600 m. The accuracy was assessed with over 100 GPS measurements and RMSE were found to be less than 10 cm. Low resolution manual measurements of density permitted calculation of snow water equivalent (SWE) and change in SWE (ablation rate). The results indicate a highly variable initial SWE distribution, which was five times more variable than the spatial variation in ablation rate. Spatial variation in ablation rate was still substantial, with a factor of two difference between north and south aspects and small scale variations due to local dust deposition. However, the impact of spatial variations in ablation rate on the snowcover depletion curve could not be discerned. The reason for this is that only a weak spatial correlation developed between SWE and ablation rate. These findings suggest that despite substantial variations in ablation rate, snowcover depletion curve calculations should emphasize the spatial variation of initial SWE rather than the variation in ablation rate. While there is scientific evidence from other field studies that support this, there are also studies that suggest that spatial variations in ablation rate can influence snowcover depletion curves in complex terrain, particularly in early melt. The development of UAV photogrammetry has provided an opportunity for further detailed measurement of ablation rates, SWE and snowcover depletion over complex terrain and UAV field studies are recommended to clarify the relative importance of SWE and melt variability on snowcover depletion in various environmental conditions.

Optimal mapping of site-specific multivariate soil properties.

PubMed

Burrough, P A; Swindell, J

1997-01-01

This paper demonstrates how geostatistics and fuzzy k-means classification can be used together to improve our practical understanding of crop yield-site response. Two aspects of soil are important for precision farming: (a) sensible classes for a given crop, and (b) their spatial variation. Local site classifications are more sensitive than general taxonomies and can be provided by the method of fuzzy k-means to transform a multivariate data set with i attributes measured at n sites into k overlapping classes; each site has a membership value mk for each class in the range 0-1. Soil variation is of interest when conditions vary over patches manageable by agricultural machinery. The spatial variation of each of the k classes can be analysed by computing the variograms of mk over the n sites. Memberships for each of the k classes can be mapped by ordinary kriging. Areas of class dominance and the transition zones between them can be identified by an inter-class confusion index; reducing the zones to boundaries gives crisp maps of dominant soil groups that can be used to guide precision farming equipment. Automation of the procedure is straightforward given sufficient data. Time variations in soil properties can be automatically incorporated in the computation of membership values. The procedures are illustrated with multi-year crop yield data collected from a 5 ha demonstration field at the Royal Agricultural College in Cirencester, UK.

Modeling spatial variation in avian survival and residency probabilities

USGS Publications Warehouse

Saracco, James F.; Royle, J. Andrew; DeSante, David F.; Gardner, Beth

2010-01-01

The importance of understanding spatial variation in processes driving animal population dynamics is widely recognized. Yet little attention has been paid to spatial modeling of vital rates. Here we describe a hierarchical spatial autoregressive model to provide spatially explicit year-specific estimates of apparent survival (phi) and residency (pi) probabilities from capture-recapture data. We apply the model to data collected on a declining bird species, Wood Thrush (Hylocichla mustelina), as part of a broad-scale bird-banding network, the Monitoring Avian Productivity and Survivorship (MAPS) program. The Wood Thrush analysis showed variability in both phi and pi among years and across space. Spatial heterogeneity in residency probability was particularly striking, suggesting the importance of understanding the role of transients in local populations. We found broad-scale spatial patterning in Wood Thrush phi and pi that lend insight into population trends and can direct conservation and research. The spatial model developed here represents a significant advance over approaches to investigating spatial pattern in vital rates that aggregate data at coarse spatial scales and do not explicitly incorporate spatial information in the model. Further development and application of hierarchical capture-recapture models offers the opportunity to more fully investigate spatiotemporal variation in the processes that drive population changes.

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

NASA Astrophysics Data System (ADS)

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

2000-08-01

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

Imaging Local Polarization in Ferroelectric Thin Films by Coherent X-Ray Bragg Projection Ptychography

NASA Astrophysics Data System (ADS)

Hruszkewycz, S. O.; Highland, M. J.; Holt, M. V.; Kim, Dongjin; Folkman, C. M.; Thompson, Carol; Tripathi, A.; Stephenson, G. B.; Hong, Seungbum; Fuoss, P. H.

2013-04-01

We used x-ray Bragg projection ptychography (BPP) to map spatial variations of ferroelectric polarization in thin film PbTiO3, which exhibited a striped nanoscale domain pattern on a high-miscut (001) SrTiO3 substrate. By converting the reconstructed BPP phase image to picometer-scale ionic displacements in the polar unit cell, a quantitative polarization map was made that was consistent with other characterization. The spatial resolution of 5.7 nm demonstrated here establishes BPP as an important tool for nanoscale ferroelectric domain imaging, especially in complex environments accessible with hard x rays.

Mapping the distribution of the denitrifier community at large scales (Invited)

NASA Astrophysics Data System (ADS)

Philippot, L.; Bru, D.; Ramette, A.; Dequiedt, S.; Ranjard, L.; Jolivet, C.; Arrouays, D.

2010-12-01

Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. Here we combined molecular approaches and geostatistical modeling to explore spatial patterns of the denitrifying community at large scales. The distribution of denitrifrying community was investigated over 107 sites in Burgundy, a 31 500 km2 region of France, using a 16 X 16 km sampling grid. At each sampling site, the abundances of denitrifiers and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time and soil physico-chemical properties to the denitrifier spatial distribution were analyzed by canonical variation partitioning. Our results indicate that 43% to 85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 740 km and used geostatistical modelling to generate predictive maps of the distribution of denitrifiers at the landscape scale. Studying the distribution of the denitrifiers at large scale can help closing the artificial gap between the investigation of microbial processes and microbial community ecology, therefore facilitating our understanding of the relationships between the ecology of denitrifiers and N-fluxes by denitrification.

Landscape genomics of Sphaeralcea ambigua in the Mojave Desert: a multivariate, spatially-explicit approach to guide ecological restoration

USGS Publications Warehouse

Shryock, Daniel F.; Havrilla, Caroline A.; DeFalco, Lesley; Esque, Todd C.; Custer, Nathan; Wood, Troy E.

2015-01-01

Local adaptation influences plant species’ responses to climate change and their performance in ecological restoration. Fine-scale physiological or phenological adaptations that direct demographic processes may drive intraspecific variability when baseline environmental conditions change. Landscape genomics characterize adaptive differentiation by identifying environmental drivers of adaptive genetic variability and mapping the associated landscape patterns. We applied such an approach to Sphaeralcea ambigua, an important restoration plant in the arid southwestern United States, by analyzing variation at 153 amplified fragment length polymorphism loci in the context of environmental gradients separating 47 Mojave Desert populations. We identified 37 potentially adaptive loci through a combination of genome scan approaches. We then used a generalized dissimilarity model (GDM) to relate variability in potentially adaptive loci with spatial gradients in temperature, precipitation, and topography. We identified non-linear thresholds in loci frequencies driven by summer maximum temperature and water stress, along with continuous variation corresponding to temperature seasonality. Two GDM-based approaches for mapping predicted patterns of local adaptation are compared. Additionally, we assess uncertainty in spatial interpolations through a novel spatial bootstrapping approach. Our study presents robust, accessible methods for deriving spatially-explicit models of adaptive genetic variability in non-model species that will inform climate change modelling and ecological restoration.

Quantification of regional nonuniformity and paradoxical intramural mechanics in hypertrophic cardiomyopathy by high frame rate ultrasound myocardial strain mapping.

PubMed

Sengupta, Partho P; Mehta, Vimal; Arora, Ramesh; Mohan, Jagdish C; Khandheria, Bijoy K

2005-07-01

This study tested the hypothesis that linear mapping of regional myocardial strain comprehensively assesses variations in regional myocardial function in hypertrophic cardiomyopathy. Hypertrophic cardiomyopathy is characterized by disorganized myocardial architecture that results in spatial and temporal nonuniformity of regional function. Left ventricular deformation was quantified in 20 patients with hypertrophic cardiomyopathy and compared with 25 age- and sex-matched control subjects. Abnormalities in subendocardial strain ranged from reduced longitudinal shortening to paradoxical systolic lengthening and delayed regional longitudinal contractions that were often located in small subsegmental areas. These variations were underestimated significantly by arbitrary measurements compared with linear mapping, in which a region of interest was moved across the longitudinal length of left ventricle (difference of peak and least strain, 10.7% +/- 5.1% vs 17% +/- 5.5%; P < .001). Echocardiographic assessment of variations in regional strain requires careful mapping and may be inappropriately assessed if left ventricular segments are sampled at arbitrary focal locations.

Spatially Detailed Porosity Prediction From Airborne Electromagnetics and Sparse Borehole Fluid Sampling

NASA Astrophysics Data System (ADS)

Macnae, J.; Ley-Cooper, Y.

2009-05-01

Sub-surface porosity is of importance in estimating fluid contant and salt-load parameters for hydrological modelling. While sparse boreholes may adequately sample the depth to a sub-horizontal water-table and usually also adequately sample ground-water salinity, they do not provide adequate sampling of the spatial variations in porosity or hydraulic permeability caused by spatial variations in sedimentary and other geological processes.. We show in this presentation that spatially detailed porosity can be estimated by applying Archie's law to conductivity estimates from airborne electromagnetic surveys with interpolated ground-water conductivity values. The prediction was tested on data from the Chowilla flood plain in the Murray-Darling Basin of South Australia. A frequency domain, helicopter-borne electromagnetic system collected data at 6 frequencies and 3 to 4 m spacings on lines spaced 100 m apart. This data was transformed into conductivity-depth sections, from which a 3D bulk-conductivity map could be created with about 30 m spatial resolution and 2 to 5 m vertical depth resolution. For that portion of the volume below the interpolated water-table, we predicted porosity in each cell using Archie's law. Generally, predicted porosities were in the 30 to 50 % range, consistent with expectations for the partially consolidated sediments in the floodplain. Porosities were directly measured on core from eight boreholes in the area, and compared quite well with the predictions. The predicted porosity map was spatially consistent, and when combined with measured salinities in the ground water, was able to provide a detailed 3D map of salt-loads in the saturated zone, and as such contribute to a hazard assessment of the saline threat to the river.

Scale-dependent variation in forest structures in naturally dynamic boreal forest landscapes

NASA Astrophysics Data System (ADS)

Kulha, Niko; Pasanen, Leena; De Grandpré, Louis; Kuuluvainen, Timo; Aakala, Tuomas

2017-04-01

Natural forest structures vary at multiple spatial scales. This variation reflects the occurrence of driving factors, such as disturbances and variation in soil or topography. To explore and understand the linkages of forest structural characteristics and factors driving their variation, we need to recognize how the structural characteristics vary in relation to spatial scale. This can be achieved by identifying scale-dependent features in forest structure within unmanaged forest landscapes. By identifying these features and examining their relationship with potential driving factors, we can better understand the dynamics of forest structural development. Here, we examine the spatial variation in forest structures at multiple spatial scales, utilizing data from old-growth boreal forests in two regions with contrasting disturbance regimes: northern Finland and north-eastern Québec, Canada ( 67° 45'N, 29° 36'E, 49° 39'N, 67° 55'W, respectively). The three landscapes (4 km2 each) in Finland are dominated by Pinus sylvestris and Picea abies, whereas the two landscapes in Québec are dominated by Abies balsamea and Picea mariana. Québec's forests are a subject to cyclic outbreaks of the eastern spruce budworm, causing extensive mortality especially in A. balsamea-dominated stands. In the Finnish landscapes, gap- to patch-scale disturbances due to tree senescence, fungi and wind, as well as infrequent surface fires in areas dominated by P. sylvestris, prevail. Owing to the differences in the species compositions and the disturbance regimes, we expect differing scales of variation between the landscapes. To quantify patterns of variation, we visually interpret stereopairs of recent aerial photographs. From the photographs, we collect information on forest canopy coverage, species composition and dead wood. For the interpretation, each 4 km2 plot is divided into 0.1ha square cells (4096 per plot). Interpretations are validated against field observations and compiled to raster maps. We analyze the raster maps with Bayesian scale space approach (iBSiZer), which aims in capturing credible variations at different spatial scales. As a result, we can detect structural entities (e.g. patches with higher canopy cover), which deviate credibly from their surroundings. The detected entities can further be linked to specific drivers. Our results show that the role of a particular driving factor varies in relation to spatial scale. For example, in the Finnish landscapes, topoedaphic factors exerted a stronger control on broad-scale forest structural characteristics, whereas recent disturbances (quantified as the amount of dead wood) appeared to play an important role in explaining the smaller scale variation of forest structures. Here, we showcase the methodology used in the detection of scale-dependent forest structural entities and present the results of our analysis of the spatial scales of variation in the natural boreal forest structures.

Scaling up functional traits for ecosystem services with remote sensing: concepts and methods.

PubMed

Abelleira Martínez, Oscar J; Fremier, Alexander K; Günter, Sven; Ramos Bendaña, Zayra; Vierling, Lee; Galbraith, Sara M; Bosque-Pérez, Nilsa A; Ordoñez, Jenny C

2016-07-01

Ecosystem service-based management requires an accurate understanding of how human modification influences ecosystem processes and these relationships are most accurate when based on functional traits. Although trait variation is typically sampled at local scales, remote sensing methods can facilitate scaling up trait variation to regional scales needed for ecosystem service management. We review concepts and methods for scaling up plant and animal functional traits from local to regional spatial scales with the goal of assessing impacts of human modification on ecosystem processes and services. We focus our objectives on considerations and approaches for (1) conducting local plot-level sampling of trait variation and (2) scaling up trait variation to regional spatial scales using remotely sensed data. We show that sampling methods for scaling up traits need to account for the modification of trait variation due to land cover change and species introductions. Sampling intraspecific variation, stratification by land cover type or landscape context, or inference of traits from published sources may be necessary depending on the traits of interest. Passive and active remote sensing are useful for mapping plant phenological, chemical, and structural traits. Combining these methods can significantly improve their capacity for mapping plant trait variation. These methods can also be used to map landscape and vegetation structure in order to infer animal trait variation. Due to high context dependency, relationships between trait variation and remotely sensed data are not directly transferable across regions. We end our review with a brief synthesis of issues to consider and outlook for the development of these approaches. Research that relates typical functional trait metrics, such as the community-weighted mean, with remote sensing data and that relates variation in traits that cannot be remotely sensed to other proxies is needed. Our review narrows the gap between functional trait and remote sensing methods for ecosystem service management.

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.

Random field assessment of nanoscopic inhomogeneity of bone

PubMed Central

Dong, X. Neil; Luo, Qing; Sparkman, Daniel M.; Millwater, Harry R.; Wang, Xiaodu

2010-01-01

Bone quality is significantly correlated with the inhomogeneous distribution of material and ultrastructural properties (e.g., modulus and mineralization) of the tissue. Current techniques for quantifying inhomogeneity consist of descriptive statistics such as mean, standard deviation and coefficient of variation. However, these parameters do not describe the spatial variations of bone properties. The objective of this study was to develop a novel statistical method to characterize and quantitatively describe the spatial variation of bone properties at ultrastructural levels. To do so, a random field defined by an exponential covariance function was used to present the spatial uncertainty of elastic modulus by delineating the correlation of the modulus at different locations in bone lamellae. The correlation length, a characteristic parameter of the covariance function, was employed to estimate the fluctuation of the elastic modulus in the random field. Using this approach, two distribution maps of the elastic modulus within bone lamellae were generated using simulation and compared with those obtained experimentally by a combination of atomic force microscopy and nanoindentation techniques. The simulation-generated maps of elastic modulus were in close agreement with the experimental ones, thus validating the random field approach in defining the inhomogeneity of elastic modulus in lamellae of bone. Indeed, generation of such random fields will facilitate multi-scale modeling of bone in more pragmatic details. PMID:20817128

Ecological genomics meets community-level modelling of biodiversity: mapping the genomic landscape of current and future environmental adaptation.

PubMed

Fitzpatrick, Matthew C; Keller, Stephen R

2015-01-01

Local adaptation is a central feature of most species occupying spatially heterogeneous environments, and may factor critically in responses to environmental change. However, most efforts to model the response of species to climate change ignore intraspecific variation due to local adaptation. Here, we present a new perspective on spatial modelling of organism-environment relationships that combines genomic data and community-level modelling to develop scenarios regarding the geographic distribution of genomic variation in response to environmental change. Rather than modelling species within communities, we use these techniques to model large numbers of loci across genomes. Using balsam poplar (Populus balsamifera) as a case study, we demonstrate how our framework can accommodate nonlinear responses of loci to environmental gradients. We identify a threshold response to temperature in the circadian clock gene GIGANTEA-5 (GI5), suggesting that this gene has experienced strong local adaptation to temperature. We also demonstrate how these methods can map ecological adaptation from genomic data, including the identification of predicted differences in the genetic composition of populations under current and future climates. Community-level modelling of genomic variation represents an important advance in landscape genomics and spatial modelling of biodiversity that moves beyond species-level assessments of climate change vulnerability. © 2014 John Wiley & Sons Ltd/CNRS.

Application of geostatistics with Indicator Kriging for analyzing spatial variability of groundwater arsenic concentrations in Southwest Bangladesh.

PubMed

Hassan, M Manzurul; Atkins, Peter J

2011-01-01

This article seeks to explore the spatial variability of groundwater arsenic (As) concentrations in Southwestern Bangladesh. Facts about spatial pattern of As are important to understand the complex processes of As concentrations and its spatial predictions in the unsampled areas of the study site. The relevant As data for this study were collected from Southwest Bangladesh and were analyzed with Flow Injection Hydride Generation Atomic Absorption Spectrometry (FI-HG-AAS). A geostatistical analysis with Indicator Kriging (IK) was employed to investigate the regionalized variation of As concentration. The IK prediction map shows a highly uneven spatial pattern of arsenic concentrations. The safe zones are mainly concentrated in the north, central and south part of the study area in a scattered manner, while the contamination zones are found to be concentrated in the west and northeast parts of the study area. The southwest part of the study area is contaminated with a highly irregular pattern. A Generalized Linear Model (GLM) was also used to investigate the relationship between As concentrations and aquifer depths. A negligible negative correlation between aquifer depth and arsenic concentrations was found in the study area. The fitted value with 95 % confidence interval shows a decreasing tendency of arsenic concentrations with the increase of aquifer depth. The adjusted mean smoothed lowess curve with a bandwidth of 0.8 shows an increasing trend of arsenic concentration up to a depth of 75 m, with some erratic fluctuations and regional variations at the depth between 30 m and 60 m. The borehole lithology was considered to analyze and map the pattern of As variability with aquifer depths. The study has performed an investigation of spatial pattern and variation of As concentrations.

Spatial and temporal patterns of locally-acquired dengue transmission in northern Queensland, Australia, 1993-2012.

PubMed

Naish, Suchithra; Dale, Pat; Mackenzie, John S; McBride, John; Mengersen, Kerrie; Tong, Shilu

2014-01-01

Dengue has been a major public health concern in Australia since it re-emerged in Queensland in 1992-1993. We explored spatio-temporal characteristics of locally-acquired dengue cases in northern tropical Queensland, Australia during the period 1993-2012. Locally-acquired notified cases of dengue were collected for northern tropical Queensland from 1993 to 2012. Descriptive spatial and temporal analyses were conducted using geographic information system tools and geostatistical techniques. 2,398 locally-acquired dengue cases were recorded in northern tropical Queensland during the study period. The areas affected by the dengue cases exhibited spatial and temporal variation over the study period. Notified cases of dengue occurred more frequently in autumn. Mapping of dengue by statistical local areas (census units) reveals the presence of substantial spatio-temporal variation over time and place. Statistically significant differences in dengue incidence rates among males and females (with more cases in females) (χ(2) = 15.17, d.f.  = 1, p<0.01). Differences were observed among age groups, but these were not statistically significant. There was a significant positive spatial autocorrelation of dengue incidence for the four sub-periods, with the Moran's I statistic ranging from 0.011 to 0.463 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the northern Queensland. Tropical areas are potential high-risk areas for mosquito-borne diseases such as dengue. This study demonstrated that the locally-acquired dengue cases have exhibited a spatial and temporal variation over the past twenty years in northern tropical Queensland, Australia. Therefore, this study provides an impetus for further investigation of clusters and risk factors in these high-risk areas.

Spatial and Temporal Patterns of Locally-Acquired Dengue Transmission in Northern Queensland, Australia, 1993–2012

PubMed Central

Naish, Suchithra; Dale, Pat; Mackenzie, John S.; McBride, John; Mengersen, Kerrie; Tong, Shilu

2014-01-01

Background Dengue has been a major public health concern in Australia since it re-emerged in Queensland in 1992–1993. We explored spatio-temporal characteristics of locally-acquired dengue cases in northern tropical Queensland, Australia during the period 1993–2012. Methods Locally-acquired notified cases of dengue were collected for northern tropical Queensland from 1993 to 2012. Descriptive spatial and temporal analyses were conducted using geographic information system tools and geostatistical techniques. Results 2,398 locally-acquired dengue cases were recorded in northern tropical Queensland during the study period. The areas affected by the dengue cases exhibited spatial and temporal variation over the study period. Notified cases of dengue occurred more frequently in autumn. Mapping of dengue by statistical local areas (census units) reveals the presence of substantial spatio-temporal variation over time and place. Statistically significant differences in dengue incidence rates among males and females (with more cases in females) (χ2 = 15.17, d.f. = 1, p<0.01). Differences were observed among age groups, but these were not statistically significant. There was a significant positive spatial autocorrelation of dengue incidence for the four sub-periods, with the Moran's I statistic ranging from 0.011 to 0.463 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the northern Queensland. Conclusions Tropical areas are potential high-risk areas for mosquito-borne diseases such as dengue. This study demonstrated that the locally-acquired dengue cases have exhibited a spatial and temporal variation over the past twenty years in northern tropical Queensland, Australia. Therefore, this study provides an impetus for further investigation of clusters and risk factors in these high-risk areas. PMID:24691549

Effects of Topography-driven Micro-climatology on Evaporation

NASA Astrophysics Data System (ADS)

Adams, D. D.; Boll, J.; Wagenbrenner, N. S.

2017-12-01

The effects of spatial-temporal variation of climatic conditions on evaporation in micro-climates are not well defined. Current spatially-based remote sensing and modeling for evaporation is limited for high resolutions and complex topographies. We investigated the effect of topography-driven micro-climatology on evaporation supported by field measurements and modeling. Fourteen anemometers and thermometers were installed in intersecting transects over the complex topography of the Cook Agronomy Farm, Pullman, WA. WindNinja was used to create 2-D vector maps based on recorded observations for wind. Spatial analysis of vector maps using ArcGIS was performed for analysis of wind patterns and variation. Based on field measurements, wind speed and direction show consequential variability based on hill-slope location in this complex topography. Wind speed and wind direction varied up to threefold and more than 45 degrees, respectively for a given time interval. The use of existing wind models enables prediction of wind variability over the landscape and subsequently topography-driven evaporation patterns relative to wind. The magnitude of the spatial-temporal variability of wind therefore resulted in variable evaporation rates over the landscape. These variations may contribute to uneven crop development patterns observed during the late growth stages of the agricultural crops at the study location. Use of hill-slope location indexes and appropriate methods for estimating actual evaporation support development of methodologies to better define topography-driven heterogeneity in evaporation. The cumulative effects of spatially-variable climatic factors on evaporation are important to quantify the localized water balance and inform precision farming practices.

Remote detection of fluid-related diagenetic mineralogical variations in the Wingate Sandstone at different spatial and spectral resolutions

NASA Astrophysics Data System (ADS)

Okyay, Unal; Khan, Shuhab D.

2016-02-01

Well-exposed eolian units of the Jurassic system on the Colorado Plateau including the Wingate Sandstone, show prominent color variations throughout southeastern Utah due to diagenetic changes that include precipitation and/or removal of iron oxide, clay, and carbonate cement. Spatially variable characteristic diagenetic changes suggest fluid-rock interactions through the sandstone. Distinctive spectral signatures of diagenetic minerals can be used to map diagenetic mineral variability and possibly fluid-flow pathways. The main objective of this work was to identify characteristic diagenetic minerals, and map their spatial variability from regional to outcrop scale in Wingate Sandstone exposures of Lisbon Valley, Utah. Laboratory reflectance spectroscopy analysis of the samples facilitated identification of diagnostic spectral characteristics of the common diagenetic minerals and their relative abundances between altered and unaltered Wingate Sandstone. Comparison of reflectance spectroscopy with satellite, airborne, and ground-based imaging spectroscopy data provided a method for mapping and evaluating spatial variations of diagenetic minerals. The Feature-oriented Principal Component Selection method was used on Advanced Spaceborne Thermal Emission and Reflection Radiometer data so as to map common mineral groups throughout the broader Wingate Sandstone exposure in the area. The Minimum Noise Fraction and Spectral Angle Mapper methods were applied on airborne HyMap and ground-based hyperspectral imaging data to identify and map mineralogical changes. The satellite and airborne data showed that out of 25.55 km2 total exposure of Wingate Sandstone in Lisbon Valley, unaltered sandstone cover 12.55 km2, and altered sandstone cover 8.90 km2 in the northwest flank and 5.09 km2 in the southern flank of the anticline. The ground-based hyperspectral data demonstrated the ability to identify and map mineral assemblages with two-dimensional lateral continuity on near-vertical rock faces. The results showed that 39.71% of the scanned outcrop is bleached and 20.60% is unbleached while 6.33% remain unclassified, and 33.36% is masked-out as vegetation. The bleached and unbleached areas are alternating throughout the vertical face of the outcrop. The relative hematite abundance observed in the unbleached areas are somewhat symmetrical. This indicates fairly similar reaction intensities along the upper and lower reaction fronts observed in the vertical section. The distribution geometry and relative abundances of diagenetic minerals not only suggest multiple paths of fluid-flow in Wingate Sandstone but also provides some insight about relative direction of past fluid-flow.

Application of Remote Sensing for Generation of Groundwater Prospect Map

NASA Astrophysics Data System (ADS)

Inayathulla, Masool

2016-07-01

In developing accurate hydrogeomorphological analysis, monitoring, ability to generate information in spatial and temporal domain and delineation of land features are crucial for successful analysis and prediction of groundwater resources. However, the use of RS and GIS in handling large amount of spatial data provides to gain accurate information for delineating the geological and geomorphological characteristics and allied significance, which are considered as a controlling factor for the occurrence and movement of groundwater used IRS LISS II data on 1: 50000 scale along with topographic maps in various parts of India to develop integrated groundwater potential zones. The present work is an attempt to integrate RS and GIS based analysis and methodology in groundwater potential zone identification in the Arkavathi Basin, Bangalore, study area. The information on geology, geomorphology, soil, slope, rainfall, water level and land use/land cover was gathered, in addition, GIS platform was used for the integration of various themes. The composite map generated was further classified according to the spatial variation of the groundwater potential. Five categories of groundwater potential zones namely poor, moderate to poor, moderate, good and very good were identified and delineated. The hydrogeomorphological units like valley fills and alluvial plain and are potential zones for groundwater exploration and development and valley fills associated with lineaments is highly promising area for ground water recharging. The spatial variation of the potential indicates that groundwater occurrence is controlled by geology, land use / land cover, slope and landforms.

Spatial variation of physicochemical and bacteriological parameters elucidation with GIS in Rangat Bay, Middle Andaman, India

NASA Astrophysics Data System (ADS)

Dheenan, P. S.; Jha, Dilip Kumar; Vinithkumar, N. V.; Ponmalar, A. Angelin; Venkateshwaran, P.; Kirubagaran, R.

2014-01-01

The purpose of this study was to determine the concentration, distribution of bacteria and physicochemical property of surface seawater in Rangat Bay, Middle Andaman, Andaman Islands (India). The bay experiences tidal variations. Perhaps physicochemical properties of seawater in Rangat Bay were found not to vary significantly. The concentration of faecal streptococci was high (2.2 × 103 CFU/100 mL) at creek and harbour area, whereas total coliforms were high (7.0 × 102 CFU/100 mL) at mangrove area. Similarly, total heterotrophic bacterial concentration was high (5.92 × 104 CFU/100 mL) in mangrove and harbour area. The Vibrio cholerae and Vibrio parahaemolyticus concentration was high (4.2 × 104 CFU/100 mL and 9 × 103 CFU/100 mL) at open sea. Cluster analysis showed grouping of stations in different tidal periods. The spatial maps clearly depicted the bacterial concentration pattern in the bay. The combined approach of multivariate analysis and spatial mapping techniques was proved to be useful in the current study.

A comparison of small-area hospitalisation rates, estimated morbidity and hospital access.

PubMed

Shulman, H; Birkin, M; Clarke, G P

2015-11-01

Published data on hospitalisation rates tend to reveal marked spatial variations within a city or region. Such variations may simply reflect corresponding variations in need at the small-area level. However, they might also be a consequence of poorer accessibility to medical facilities for certain communities within the region. To help answer this question it is important to compare these variable hospitalisation rates with small-area estimates of need. This paper first maps hospitalisation rates at the small-area level across the region of Yorkshire in the UK to show the spatial variations present. Then the Health Survey of England is used to explore the characteristics of persons with heart disease, using chi-square and logistic regression analysis. Using the most significant variables from this analysis the authors build a spatial microsimulation model of morbidity for heart disease for the Yorkshire region. We then compare these estimates of need with the patterns of hospitalisation rates seen across the region. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Using estimates of natural variation to detect ecologically important change in forest spatial patterns: a case study, Cascade Range, eastern Washington.

Treesearch

Paul F. Hessburg; Bradley G. Smith; R. Brion Salter

1999-01-01

Using hierarchical clustering techniques, we grouped subwatersheds on the eastern slope of the Cascade Range in Washington State into ecological subregions by similarity of area in potential vegetation and climate attributes. We then built spatially continuous historical and current vegetation maps for 48 randomly selected subwatersheds from interpretations of 1938-49...

Dorsolateral Striatal Lesions Impair Navigation Based on Landmark-Goal Vectors but Facilitate Spatial Learning Based on a "Cognitive Map"

ERIC Educational Resources Information Center

Kosaki, Yutaka; Poulter, Steven L.; Austen, Joe M.; McGregor, Anthony

2015-01-01

In three experiments, the nature of the interaction between multiple memory systems in rats solving a variation of a spatial task in the water maze was investigated. Throughout training rats were able to find a submerged platform at a fixed distance and direction from an intramaze landmark by learning a landmark-goal vector. Extramaze cues were…

Elemental and topographical imaging of microscopic variations in deposition on NSTX-U and DIII-D samples

NASA Astrophysics Data System (ADS)

Skinner, C. H.; Kaita, R.; Koel, B. E.; Chrobak, C. P.; Wampler, W. R.

2017-10-01

Tokamak plasma facing components (PFCs) have surface roughness that can cause microscopic spatial variations in erosion and deposition and hence influence material migration. Previous RBS measurements showed indirect evidence for this but the spatial (0.5mm) resolution was insufficient for direct imaging. We will present elemental images at sub-micron resolution of deposition on NSTX-U and DiMES samples that show strong microscopic variations and correlate this with 3D topographical maps of surface irregularities. The elemental imaging is performed with a Scanning Auger Microprobe (SAM) that measures element-specific Auger electrons excited by an SEM electron beam. 3D topographical maps of the samples are performed with a Leica DCM 3D confocal light microscope and compared to the elemental deposition pattern. The initial results appear consistent with erosion at the downstream edges of the surface pores exposed to the incident ion flux, whereas the deeper regions are shadowed and serve as deposition traps. Support was provided through DOE Contract Numbers DE-AC02-09CH11466, DE-FC02-04ER54698 and DE-NA0003525.

Highly spatially- and seasonally-resolved predictive contamination maps for persistent organic pollutants: development and validation.

PubMed

Ballabio, Cristiano; Guazzoni, Niccoló; Comolli, Roberto; Tremolada, Paolo

2013-08-01

A reliable spatial assessment of the POPs contamination in soils is essential for burden studies and flux evaluations. Soil characteristics and properties vary enormously even within small spatial scale and over time; therefore soil capacity of accumulating POPs varies greatly. In order to include this very high spatial and temporal variability, models can be used for assessing soil accumulation capacity in a specific time and space and, from it, the spatial distribution and temporal trends of POPs concentrations. In this work, predictive contamination maps of the accumulation capacity of soils were developed at a space resolution of 1×1m with a time frame of one day, in a study area located in the central Alps. Physical algorithms for temperature and organic carbon estimation along the soil profile and across the year were fitted to estimate the horizontal, vertical and seasonal distribution of the contamination potential for PCBs in soil (Ksa maps). The resulting maps were cross-validated with an independent set of PCB contamination data, showing very good agreement (e.g. for CB-153, R(2)=0.80, p-value≤2.2·10(-06)). Slopes of the regression between predicted Ksa and experimental concentrations were used to map the soil contamination for the whole area, taking into account soil characteristics and temperature conditions. These maps offer the opportunity to evaluate burden (concentration maps) and fluxes (emission maps) with highly resolved temporal and spatial detail. In addition, in order to explain the observed low autumn PCB concentrations in soil related to the high Ksa values of this period, a dynamic model of seasonal variation of soil concentrations was developed basing on rate parameters fitted on measured concentrations. The model was able to describe, at least partially, the observed different behavior between the quite rapid discharge phase in summer and the slow recharge phase in autumn. Copyright © 2013 Elsevier B.V. All rights reserved.

Predictions of avian Plasmodium expansion under climate change.

PubMed

Loiseau, Claire; Harrigan, Ryan J; Bichet, Coraline; Julliard, Romain; Garnier, Stéphane; Lendvai, Adám Z; Chastel, Olivier; Sorci, Gabriele

2013-01-01

Vector-borne diseases are particularly responsive to changing environmental conditions. Diurnal temperature variation has been identified as a particularly important factor for the development of malaria parasites within vectors. Here, we conducted a survey across France, screening populations of the house sparrow (Passer domesticus) for malaria (Plasmodium relictum). We investigated whether variation in remotely-sensed environmental variables accounted for the spatial variation observed in prevalence and parasitemia. While prevalence was highly correlated to diurnal temperature range and other measures of temperature variation, environmental conditions could not predict spatial variation in parasitemia. Based on our empirical data, we mapped malaria distribution under climate change scenarios and predicted that Plasmodium occurrence will spread to regions in northern France, and that prevalence levels are likely to increase in locations where transmission already occurs. Our findings, based on remote sensing tools coupled with empirical data suggest that climatic change will significantly alter transmission of malaria parasites.

Mapping variation in radon potential both between and within geological units.

PubMed

Miles, J C H; Appleton, J D

2005-09-01

Previously, the potential for high radon levels in UK houses has been mapped either on the basis of grouping the results of radon measurements in houses by grid squares or by geological units. In both cases, lognormal modelling of the distribution of radon concentrations was applied to allow the estimated proportion of houses above the UK radon Action Level (AL, 200 Bq m(-3)) to be mapped. This paper describes a method of combining the grid square and geological mapping methods to give more accurate maps than either method can provide separately. The land area is first divided up using a combination of bedrock and superficial geological characteristics derived from digital geological map data. Each different combination of geological characteristics may appear at the land surface in many discontinuous locations across the country. HPA has a database of over 430,000 houses in which long-term measurements of radon concentration have been made, and whose locations are accurately known. Each of these measurements is allocated to the appropriate bedrock--superficial geological combination underlying it. Taking each geological combination in turn, the spatial variation of radon potential is mapped, treating the combination as if it were continuous over the land area. All of the maps of radon potential within different geological combinations are then combined to produce a map of variation in radon potential over the whole land surface.

Spatially Resolved Isotopic Source Signatures of Wetland Methane Emissions

NASA Astrophysics Data System (ADS)

Ganesan, A. L.; Stell, A. C.; Gedney, N.; Comyn-Platt, E.; Hayman, G.; Rigby, M.; Poulter, B.; Hornibrook, E. R. C.

2018-04-01

We present the first spatially resolved wetland δ13C(CH4) source signature map based on data characterizing wetland ecosystems and demonstrate good agreement with wetland signatures derived from atmospheric observations. The source signature map resolves a latitudinal difference of 10‰ between northern high-latitude (mean -67.8‰) and tropical (mean -56.7‰) wetlands and shows significant regional variations on top of the latitudinal gradient. We assess the errors in inverse modeling studies aiming to separate CH4 sources and sinks by comparing atmospheric δ13C(CH4) derived using our spatially resolved map against the common assumption of globally uniform wetland δ13C(CH4) signature. We find a larger interhemispheric gradient, a larger high-latitude seasonal cycle, and smaller trend over the period 2000-2012. The implication is that erroneous CH4 fluxes would be derived to compensate for the biases imposed by not utilizing spatially resolved signatures for the largest source of CH4 emissions. These biases are significant when compared to the size of observed signals.

(abstract) Topographic Signatures in Geology

NASA Technical Reports Server (NTRS)

Farr, Tom G.; Evans, Diane L.

1996-01-01

Topographic information is required for many Earth Science investigations. For example, topography is an important element in regional and global geomorphic studies because it reflects the interplay between the climate-driven processes of erosion and the tectonic processes of uplift. A number of techniques have been developed to analyze digital topographic data, including Fourier texture analysis. A Fourier transform of the topography of an area allows the spatial frequency content of the topography to be analyzed. Band-pass filtering of the transform produces images representing the amplitude of different spatial wavelengths. These are then used in a multi-band classification to map units based on their spatial frequency content. The results using a radar image instead of digital topography showed good correspondence to a geologic map, however brightness variations in the image unrelated to topography caused errors. An additional benefit to the use of Fourier band-pass images for the classification is that the textural signatures of the units are quantative measures of the spatial characteristics of the units that may be used to map similar units in similar environments.

Ecosystem services of boreal forests - Carbon budget mapping at high resolution.

PubMed

Akujärvi, Anu; Lehtonen, Aleksi; Liski, Jari

2016-10-01

The carbon (C) cycle of forests produces ecosystem services (ES) such as climate regulation and timber production. Mapping these ES using simple land cover -based proxies might add remarkable inaccuracy to the estimates. A framework to map the current status of the C budget of boreal forested landscapes was developed. The C stocks of biomass and soil and the annual change in these stocks were quantified in a 20 × 20 m resolution at the regional level on mineral soils in southern Finland. The fine-scale variation of the estimates was analyzed geo-statistically. The reliability of the estimates was evaluated by comparing them to measurements from the national multi-source forest inventory. The C stocks of forests increased slightly from the south coast to inland whereas the changes in these stocks were more uniform. The spatial patches of C stocks were larger than those of C stock changes. The patch size of the C stocks reflected the spatial variation in the environmental conditions, and that of the C stock changes the typical area of forest management compartments. The simulated estimates agreed well with the measurements indicating a good mapping framework performance. The mapping framework is the basis for evaluating the effects of forest management alternatives on C budget at high resolution across large spatial scales. It will be coupled with the assessment of other ES and biodiversity to study their relationships. The framework integrated a wide suite of simulation models and extensive inventory data. It provided reliable estimates of the human influence on C cycle in forested landscapes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Geographic variation in sexual behavior can explain geospatial heterogeneity in the severity of the HIV epidemic in Malawi.

PubMed

Palk, Laurence; Blower, Sally

2018-02-09

In sub-Saharan Africa, where ~ 25 million individuals are infected with HIV and transmission is predominantly heterosexual, there is substantial geographic variation in the severity of epidemics. This variation has yet to be explained. Here, we propose that it is due to geographic variation in the size of the high-risk group (HRG): the group with a high number of sex partners. We test our hypothesis by conducting a geospatial analysis of data from Malawi, where ~ 13% of women and ~ 8% of men are infected with HIV. We used georeferenced HIV testing and behavioral data from ~ 14,000 participants of a nationally representative population-level survey: the 2010 Malawi Demographic and Health Survey (MDHS). We constructed gender-stratified epidemic surface prevalence (ESP) maps by spatially smoothing and interpolating the HIV testing data. We used the behavioral data to construct gender-stratified risk maps that reveal geographic variation in the size of the HRG. We tested our hypothesis by fitting gender-stratified spatial error regression (SER) models to the MDHS data. The ESP maps show considerable geographic variation in prevalence: 1-29% (women), 1-20% (men). Risk maps reveal substantial geographic variation in the size of the HRG: 0-40% (women), 16-58% (men). Prevalence and the size of the HRG are highest in urban centers. However, the majority of HIV-infected individuals (~75% of women, ~ 80% of men) live in rural areas, as does most of the HRG (~ 80% of women, ~ 85% of men). We identify a significant (P < 0.001) geospatial relationship linking the size of the HRG with prevalence: the greater the size, the higher the prevalence. SER models show HIV prevalence in women is expected to exceed the national average in districts where > 20% of women are in the HRG. Most importantly, the SER models show that geographic variation in the size of the HRG can explain a substantial proportion (73% for women, 67% for men) of the geographic variation in epidemic severity. Taken together, our results provide substantial support for our hypothesis. They provide a potential mechanistic explanation for the geographic variation in the severity of the HIV epidemic in Malawi and, potentially, in other countries in sub-Saharan Africa.

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

Xiao, Kai; Ma, Ying -Zhong; Simpson, Mary Jane

Charge carrier trapping degrades the performance of organometallic halide perovskite solar cells. To characterize the locations of electronic trap states in a heterogeneous photoactive layer, a spatially resolved approach is essential. Here, we report a comparative study on methylammonium lead tri-iodide perovskite thin films subject to different thermal annealing times using a combined photoluminescence (PL) and femtosecond transient absorption microscopy (TAM) approach to spatially map trap states. This approach coregisters the initially populated electronic excited states with the regions that recombine radiatively. Although the TAM images are relatively homogeneous for both samples, the corresponding PL images are highly structured. Themore » remarkable variation in the PL intensities as compared to transient absorption signal amplitude suggests spatially dependent PL quantum efficiency, indicative of trapping events. Furthermore, detailed analysis enables identification of two trapping regimes: a densely packed trapping region and a sparse trapping area that appear as unique spatial features in scaled PL maps.« less

Hurricane Directional Wave Spectrum Spatial Variation in the Open Ocean and at Landfall

NASA Technical Reports Server (NTRS)

Walsh, E. J.; Wright, C. W.; Vandemark, D.; Krabill, W. B.; Garcia, A. W.; Houston, S. H.; Powell, M. D.; Black, P. G.; Marks, F. D.; Busalacchi, Antonio J. (Technical Monitor)

2000-01-01

The sea surface directional wave spectrum was measured for the first time in all quadrants of a hurricane in open water using the NASA airborne scanning radar altimeter (SRA) carried aboard one of the NOAA WP-3D hurricane hunter aircraft at 1.5 km height. The SRA measures the energetic portion of the directional wave spectrum by generating a topographic map of the sea surface. At 8 Hz, the SRA sweeps a radar beam of 1 E half-power width (two-way) across the aircraft ground track over a swath equal to 0.8 of the aircraft height, simultaneously measuring the backscattered power at its 36 GHz (8.3 mm) operating frequency and the range to the sea surface at 64 positions. These slant ranges are multiplied by the cosine of the incidence angles to determine the vertical distances from the aircraft to the sea surface. Subtracting these distances from the aircraft height produces the sea surface elevation map. The sea surface topography is interpolated to a uniform grid, transformed by a two-dimensional FFT, and Doppler corrected. The open-ocean data were acquired on 24 August 1998 when hurricane Bonnie was east of the Bahamas and moving slowly to the north. Individual waves with heights up to 18 m were observed and the spatial variation of the wave field was dramatic. The dominant waves generally propagated at significant angles to the downwind direction. At some positions there were three different wave fields of comparable energy crossing each other. The NOAA aircraft spent over five hours within 180 km of the hurricane Bonnie eye, and made five eye penetrations. A 3-minute animation of the directional wave spectrum spatial variation over this period will be shown as well as summary plots of the wave field spatial variation. On 26 August 1998, the NOAA aircraft flew at 2.2 km height when hurricane Bonnie was making landfall near Wilmington, NC, documenting the directional wave spectrum in the region between Charleston, SC and Cape Hatteras, NC. The aircraft ground track included both segments along the shoreline and Pamlico Sound as well as far offshore. An animation of the directional wave spectrum spatial variation at landfall will be presented and contrasted with the spatial variation when Bonnie was in the open ocean on 24 August 1998.

National-scale cropland mapping based on spectral-temporal features and outdated land cover information.

PubMed

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.

National-scale cropland mapping based on spectral-temporal features and outdated land cover information

PubMed Central

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

Mapping the unknown: Modeling future scenarios of riverine fish communities

EPA Science Inventory

Riverscapes can be defined by spatial and temporal variation in a suite of environmental conditions that influence the distribution and persistence of riverine fish populations. Fish in riverscapes can exhibit extensive movements, require seasonally-distinct habitats for spawnin...

Atmospheric circulation patterns and spatial climatic variations in Beringia

NASA Astrophysics Data System (ADS)

Mock, Cary J.; Bartlein, Patrick J.; Anderson, Patricia M.

1998-08-01

Analyses of more than 40 years of climatic data reveal intriguing spatial variations in climatic patterns for Beringia (North-eastern Siberia and Alaska), aiding the understanding of the hierarchy of climatic controls that operate at different spatial scales within the Arctic. A synoptic climatology, using a subjective classification methodology on January and July sea level pressure, and July 500 hPa height anomaly patterns, identified 13 major atmospheric circulation patterns (26 pairs consisting of 13 synoptic/temperature and 13 synoptic/precipitation comparisons) that occur over Beringia. Composite anomaly maps of circulation, temperature, and precipitation described the spatial variability of surface climatic responses to circulation. Results indicate that nine synoptic pairs yield homogeneous surface climatic anomaly patterns throughout most of Beringia. However, many of the surface climatic responses illustrate heterogeneous anomaly patterns as a result of variations in circulation controls, such as troughing over East Asia and the Pacific subtropical high superimposed over topography, with small shifts in atmospheric circulation dramatically altering spatial variations of anomaly patterns. Distinctive contrasts in climatic responses, as suggested from ten synoptic pairs, are clearly evident for Western Beringia versus Eastern Beringia. These results offer important implications for scholars interested in assessing late Quaternary climatic change in the region from interannual to millennial timescales.

Estimating and mapping ecological processes influencing microbial community assembly

PubMed Central

Stegen, James C.; Lin, Xueju; Fredrickson, Jim K.; Konopka, Allan E.

2015-01-01

Ecological community assembly is governed by a combination of (i) selection resulting from among-taxa differences in performance; (ii) dispersal resulting from organismal movement; and (iii) ecological drift resulting from stochastic changes in population sizes. The relative importance and nature of these processes can vary across environments. Selection can be homogeneous or variable, and while dispersal is a rate, we conceptualize extreme dispersal rates as two categories; dispersal limitation results from limited exchange of organisms among communities, and homogenizing dispersal results from high levels of organism exchange. To estimate the influence and spatial variation of each process we extend a recently developed statistical framework, use a simulation model to evaluate the accuracy of the extended framework, and use the framework to examine subsurface microbial communities over two geologic formations. For each subsurface community we estimate the degree to which it is influenced by homogeneous selection, variable selection, dispersal limitation, and homogenizing dispersal. Our analyses revealed that the relative influences of these ecological processes vary substantially across communities even within a geologic formation. We further identify environmental and spatial features associated with each ecological process, which allowed mapping of spatial variation in ecological-process-influences. The resulting maps provide a new lens through which ecological systems can be understood; in the subsurface system investigated here they revealed that the influence of variable selection was associated with the rate at which redox conditions change with subsurface depth. PMID:25983725

UK-5 Van Allen belt radiation exposure: A special study to determine the trapped particle intensities on the UK-5 satellite with spatial mapping of the ambient flux environment

NASA Technical Reports Server (NTRS)

Stassinopoulos, E. G.

1972-01-01

Vehicle encountered electron and proton fluxes were calculated for a set of nominal UK-5 trajectories with new computational methods and new electron environment models. Temporal variations in the electron data were considered and partially accounted for. Field strength calculations were performed with an extrapolated model on the basis of linear secular variation predictions. Tabular maps for selected electron and proton energies were constructed as functions of latitude and longitude for specified altitudes. Orbital flux integration results are presented in graphical and tabular form; they are analyzed, explained, and discussed.

Mapping soil textural fractions across a large watershed in north-east Florida.

PubMed

Lamsal, S; Mishra, U

2010-08-01

Assessment of regional scale soil spatial variation and mapping their distribution is constrained by sparse data which are collected using field surveys that are labor intensive and cost prohibitive. We explored geostatistical (ordinary kriging-OK), regression (Regression Tree-RT), and hybrid methods (RT plus residual Sequential Gaussian Simulation-SGS) to map soil textural fractions across the Santa Fe River Watershed (3585 km(2)) in north-east Florida. Soil samples collected from four depths (L1: 0-30 cm, L2: 30-60 cm, L3: 60-120 cm, and L4: 120-180 cm) at 141 locations were analyzed for soil textural fractions (sand, silt and clay contents), and combined with textural data (15 profiles) assembled under the Florida Soil Characterization program. Textural fractions in L1 and L2 were autocorrelated, and spatially mapped across the watershed. OK performance was poor, which may be attributed to the sparse sampling. RT model structure varied among textural fractions, and the model explained variations ranged from 25% for L1 silt to 61% for L2 clay content. Regression residuals were simulated using SGS, and the average of simulated residuals were used to approximate regression residual distribution map, which were added to regression trend maps. Independent validation of the prediction maps showed that regression models performed slightly better than OK, and regression combined with average of simulated regression residuals improved predictions beyond the regression model. Sand content >90% in both 0-30 and 30-60 cm covered 80.6% of the watershed area. Copyright 2010 Elsevier Ltd. All rights reserved.

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.

Cross-sectional transport imaging in a multijunction solar cell

DOE PAGES

Haegel, Nancy M.; Ke, Chi -Wen; Taha, Hesham; ...

2016-12-01

Here, we combine a highly localized electron-beam point source excitation to generate excess free carriers with the spatial resolution of optical near-field imaging to map recombination in a cross-sectioned multijunction (Ga 0.5In 0.5P/GaIn 0.01As/Ge) solar cell. By mapping the spatial variations in emission of light for fixed generation (as opposed to traditional cathodoluminescence (CL), which maps integrated emission as a function of position of generation), it is possible to directly monitor the motion of carriers and photons. We observe carrier diffusion throughout the full width of the middle (GaInAs) cell, as well as luminescent coupling from point source excitation inmore » the top cell GaInP to the middle cell. Supporting CL and near-field photoluminescence (PL) measurements demonstrate the excitation-dependent Fermi level splitting effects that influence cross-sectioned spectroscopy results, as well as transport limitations on the spatial resolution of conventional cross-sectional far-field measurements.« less

Spatially Regularized Machine Learning for Task and Resting-state fMRI

PubMed Central

Song, Xiaomu; Panych, Lawrence P.; Chen, Nan-kuei

2015-01-01

Background Reliable mapping of brain function across sessions and/or subjects in task- and resting-state has been a critical challenge for quantitative fMRI studies although it has been intensively addressed in the past decades. New Method A spatially regularized support vector machine (SVM) technique was developed for the reliable brain mapping in task- and resting-state. Unlike most existing SVM-based brain mapping techniques, which implement supervised classifications of specific brain functional states or disorders, the proposed method performs a semi-supervised classification for the general brain function mapping where spatial correlation of fMRI is integrated into the SVM learning. The method can adapt to intra- and inter-subject variations induced by fMRI nonstationarity, and identify a true boundary between active and inactive voxels, or between functionally connected and unconnected voxels in a feature space. Results The method was evaluated using synthetic and experimental data at the individual and group level. Multiple features were evaluated in terms of their contributions to the spatially regularized SVM learning. Reliable mapping results in both task- and resting-state were obtained from individual subjects and at the group level. Comparison with Existing Methods A comparison study was performed with independent component analysis, general linear model, and correlation analysis methods. Experimental results indicate that the proposed method can provide a better or comparable mapping performance at the individual and group level. Conclusions The proposed method can provide accurate and reliable mapping of brain function in task- and resting-state, and is applicable to a variety of quantitative fMRI studies. PMID:26470627

First CRISM Observations of Mars

NASA Astrophysics Data System (ADS)

Murchie, S.; Arvidson, R.; Bedini, P.; Beisser, K.; Bibring, J.; Bishop, J.; Brown, A.; Boldt, J.; Cavender, P.; Choo, T.; Clancy, R. T.; Darlington, E. H.; Des Marais, D.; Espiritu, R.; Fort, D.; Green, R.; Guinness, E.; Hayes, J.; Hash, C.; Heffernan, K.; Humm, D.; Hutcheson, J.; Izenberg, N.; Lees, J.; Malaret, E.; Martin, T.; McGovern, J. A.; McGuire, P.; Morris, R.; Mustard, J.; Pelkey, S.; Robinson, M.; Roush, T.; Seelos, F.; Seelos, K.; Slavney, S.; Smith, M.; Shyong, W. J.; Strohbehn, K.; Taylor, H.; Wirzburger, M.; Wolff, M.

2006-12-01

CRISM will make its first observations of Mars from MRO in late September 2006, and regular science observations begin in early November. CRISM is a gimbaled, hyperspectral imager whose objectives are (1) to map the entire surface using a subset of bands to characterize crustal mineralogy, (2) to map the mineralogy of key areas at high spectral and spatial resolution, and (3) to measure spatial and seasonal variations in the atmosphere. These objectives are addressed using three major types of observations. In the multispectral survey, with the gimbal pointed at planet nadir, data are collected at a subset of 72 wavelengths covering key mineralogic absorptions, and binned to pixel footprints of 100 or 200 m per pixel. Nearly the entire planet will be mapped in this fashion. In targeted orservations, the gimbal is scanned to remove most along-track motion, and a region of interest is mapped at full spatial and spectral resolution (15-19 m per pixel, 362-3920 nm at 6.55 nm per channel). Ten additional abbreviated, spatially-binned images are taken before and after the main image, providing an emission phase function (EPF) of the site for atmospheric study and correction of surface spectra for atmospheric effects. In atmospheric mode, only the EPF is acquired. Global grids of the resulting lower data volume observations are taken repeatedly throughout the Martian year to measure seasonal variations in atmospheric properties. Raw, calibrated, and map-projected data are delivered to the community with a spectral library to aid in interpretation. CRISM has undergone calibrations during its cruise to Mars using internal sources, including a closed loop controlled integrating sphere that serves as a radiometric reference. On 26 September a protective lens cover will be deployed. First data from Mars will focus on targeted observations of Phoenix and MER, targeted observations of sulfate- and phyllosilicate-containing sites identified by Mars Express per OMEGA, acquisition of initial EPF grids, and multispectral survey of the northern plains. Our presentation will discuss first results from targeted observations and multispectral mapping. Data processing and first analysis of EPFs will be discussed in companion abstracts.

Spatial and temporal variation of moisture content in the soil profiles of two different agricultural fields of semi-arid region.

PubMed

Baskan, Oguz; Kosker, Yakup; Erpul, Gunay

2013-12-01

Modeling spatio-temporal variation of soil moisture with depth in the soil profile plays an important role for semi-arid crop production from an agro-hydrological perspective. This study was performed in Guvenc Catchment. Two soil series that were called Tabyabayir (TaS) and Kervanpinari (KeS) and classified as Leptosol and Vertisol Soil Groups were used in this research. The TeS has a much shallower (0-34 cm) than the KeS (0-134 cm). At every sampling time, a total of geo-referenced 100 soil moisture samples were taken based on horizon depths. The results indicated that soil moisture content changed spatially and temporally with soil texture and profile depth significantly. In addition, land use was to be important factor when soil was shallow. When the soil conditions were towards to dry, higher values for the coefficient of variation (CV) were observed for TaS (58 and 43% for A and C horizons, respectively); however, the profile CV values were rather stable at the KeS. Spatial variability range of TaS was always higher at both dry and wet soil conditions when compared to that of KeS. Excessive drying of soil prevented to describe any spatial model for surface horizon, additionally resulting in a high nugget variance in the subsurface horizon for the TaS. On the contrary to TaS, distribution maps were formed all horizons for the KeS at any measurement times. These maps, depicting both dry and wet soil conditions through the profile depth, are highly expected to reduce the uncertainty associated with spatially and temporally determining the hydraulic responses of the catchment soils.

Uncertainty in the profitability of fertilizer management based on various sampling designs.

NASA Astrophysics Data System (ADS)

Muhammed, Shibu; Ben, Marchant; Webster, Richard; Milne, Alice; Dailey, Gordon; Whitmore, Andrew

2016-04-01

Many farmers sample their soil to measure the concentrations of plant nutrients, including phosphorus (P), so as to decide how much fertilizer to apply. Now that fertilizer can be applied at variable rates, farmers want to know whether maps of nutrient concentration made from grid samples or from field subdivisions (zones within their fields) are merited: do such maps lead to greater profit than would a single measurement on a bulked sample for each field when all costs are taken into account? We have examined the merits of grid-based and zone-based sampling strategies over single field-based averages using continuous spatial data on wheat yields at harvest in six fields in southern England and simulated concentrations of P in the soil. Features of the spatial variation in the yields provide predictions about which sampling scheme is likely to be most cost effective, but there is uncertainty associated with these predictions that must be communicated to farmers. Where variograms of the yield have large variances and long effective ranges, grid-sampling and mapping nutrients are likely to be cost-effective. Where effective ranges are short, sampling must be dense to reveal the spatial variation and may be expensive. In these circumstances variable-rate application of fertilizer is likely to be impracticable and almost certainly not cost-effective. We have explored several methods for communicating these results and found that the most effective method was using probability maps that show the likelihood of grid-based and zone-based sampling being more profitable that a field-based estimate.

CRISM/HiRISE Correlative Spectroscopy

NASA Astrophysics Data System (ADS)

Seelos, F. P.; Murchie, S. L.; McGovern, A.; Milazzo, M. P.; Herkenhoff, K. E.

2011-12-01

The Mars Reconnaissance Orbiter (MRO) Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) and High Resolution Imaging Science Experiment (HiRISE) are complementary investigations with high spectral resolution and broad wavelength coverage (CRISM ~20 m/pxl; ~400 - 4000 nm, 6.55 nm sampling) and high spatial resolution with broadband color capability (HiRISE ~25 cm/pxl; ~500, 700, 900 nm band centers, ~200-300 nm FWHM). Over the course of the MRO mission it has become apparent that spectral variations in the IR detected by CRISM (~1000 nm - 4000 nm) sometimes correlate spatially with visible and near infrared 3-band color variations observed by HiRISE. We have developed a data processing procedure that establishes a numerical mapping between HiRISE color and CRISM VNIR and IR spectral data and provides a statistical evaluation of the uncertainty in the mapping, with the objective of extrapolating CRISM-inferred mineralogy to the HiRISE spatial scale. The MRO mission profile, spacecraft capabilities, and science planning process emphasize coordinated observations - the simultaneous observation of a common target by multiple instruments. The commonalities of CRISM/HiRISE coordinated observations present a unique opportunity for tandem data analysis. Recent advances in the systematic processing of CRISM hyperspectral targeted observations account for gimbal-induced photometric variations and transform the data to a synthetic nadir acquisition geometry. The CRISM VNIR (~400 nm - 1000 nm) data can then be convolved to the HiRISE Infrared, Red, and Blue/Green (IRB) response functions to generate a compatible CRISM IRB product. Statistical evaluation of the CRISM/HiRISE spatial overlap region establishes a quantitative link between the data sets. IRB spectral similarity mapping for each HiRISE color spatial pixel with respect to the CRISM IRB product allows a given HiRISE pixel to be populated with information derived from the coordinated CRISM observation, including correlative VNIR or IR spectral data, spectral summary parameters, or browse products. To properly characterize the quality and fidelity of the IRB correlation, a series of ancillary information bands that record the numerical behavior of the procedure are also generated. Prototype CRISM/HiRISE correlative data products have been generated for a small number of coordinated observation pairs. The resulting products have the potential to support integrated spectral and morphological mapping at sub-meter spatial scales. Such data products would be invaluable for strategic and tactical science operations on landed missions, and would allow observations from a landed platform to be evaluated in a CRISM-based spectral and mineralogical context.

Random field assessment of nanoscopic inhomogeneity of bone.

PubMed

Dong, X Neil; Luo, Qing; Sparkman, Daniel M; Millwater, Harry R; Wang, Xiaodu

2010-12-01

Bone quality is significantly correlated with the inhomogeneous distribution of material and ultrastructural properties (e.g., modulus and mineralization) of the tissue. Current techniques for quantifying inhomogeneity consist of descriptive statistics such as mean, standard deviation and coefficient of variation. However, these parameters do not describe the spatial variations of bone properties. The objective of this study was to develop a novel statistical method to characterize and quantitatively describe the spatial variation of bone properties at ultrastructural levels. To do so, a random field defined by an exponential covariance function was used to represent the spatial uncertainty of elastic modulus by delineating the correlation of the modulus at different locations in bone lamellae. The correlation length, a characteristic parameter of the covariance function, was employed to estimate the fluctuation of the elastic modulus in the random field. Using this approach, two distribution maps of the elastic modulus within bone lamellae were generated using simulation and compared with those obtained experimentally by a combination of atomic force microscopy and nanoindentation techniques. The simulation-generated maps of elastic modulus were in close agreement with the experimental ones, thus validating the random field approach in defining the inhomogeneity of elastic modulus in lamellae of bone. Indeed, generation of such random fields will facilitate multi-scale modeling of bone in more pragmatic details. Copyright © 2010 Elsevier Inc. All rights reserved.

Preliminary isostatic residual gravity anomaly map of Paso Robles 30 x 60 minute quadrangle, California

USGS Publications Warehouse

McPhee, D.K.; Langenheim, V.E.; Watt, J.T.

2011-01-01

This isostatic residual gravity map is part of an effort to map the three-dimensional distribution of rocks in the central California Coast Ranges and will serve as a basis for modeling the shape of basins and for determining the location and geometry of faults within the Paso Robles quadrangle. Local spatial variations in the Earth\\'s gravity field, after accounting for variations caused by elevation, terrain, and deep crustal structure reflect the distribution of densities in the mid- to upper crust. Densities often can be related to rock type, and abrupt spatial changes in density commonly mark lithological or structural boundaries. High-density rocks exposed within the central Coast Ranges include Mesozoic granitic rocks (exposed northwest of Paso Robles), Jurassic to Cretaceous marine strata of the Great Valley Sequence (exposed primarily northeast of the San Andreas fault), and Mesozoic sedimentary and volcanic rocks of the Franciscan Complex [exposed in the Santa Lucia Range and northeast of the San Andreas fault (SAF) near Parkfield, California]. Alluvial sediments and Tertiary sedimentary rocks are characterized by low densities; however, with increasing depth of burial and age, the densities of these rocks may become indistinguishable from those of older basement rocks.

VARIABLE RATE APPLICATION OF SOIL HERBICIDES IN ARABLE CROPS: FROM THEORY TO PRACTICE.

PubMed

Heijting, S; Kempenaar, C

2014-01-01

Soil herbicides are applied around crop emergence and kill germinating weeds in the surface layer of the soil. These herbicides play an important role in the chemical management of weeds in major arable crops. From an environmental point of view there is a clear need for smarter application of these chemicals. This paper presents research done in The Netherlands on Variable Rate Application (VRA) of soil herbicides by taking into account spatial variation of the soil. Herbicides adsorbed to soil parameters such as clay or organic matter are not available for herbicidal activity. Decision Support Rules (DSR) describe the relation between the soil parameter and herbicide dosage needed for effectively controlling weeds. Research methods such as greenhouse trials, models and on farm research to develop DSR are discussed and results are presented. Another important ingredient for VRA of soil herbicides is an accurate soil map of the field. Sampling and subsequent interpolation is costly. Soil scans measuring a proxy that is subsequently translated into soil properties such as clay fraction and soil organic matter content offer a quicker way to achieve such maps but validation is needed. DSR is applied to the soil map to get the variable dosage map. The farmer combines this map with the routing, spray volume and spray boom width in the Farm Management Information System (FMIS), resulting in a task file. This task file can subsequently be read by the board computer resulting in a VRA spray map. Reduction in soil herbicide depends on the DSR, the spatial variation and pattern of the soil, the spatial configuration of the routing and the technical advances of the spray equipment. Recently, within the framework the Programma Precisie Landbouw, first steps were made to test and implement this in practice. Currently, theory and practice of VRA of soil herbicides is developed within the research program IJKakker in close cooperation with pioneering farmers in The Netherlands.

Surface compositional variation on the comet 67P/Churyumov-Gerasimenko by OSIRIS data

NASA Astrophysics Data System (ADS)

Barucci, M. A.; Fornasier, S.; Feller, C.; Perna, D.; Hasselmann, H.; Deshapriya, J. D. P.; Fulchignoni, M.; Besse, S.; Sierks, H.; Forgia, F.; Lazzarin, M.; Pommerol, A.; Oklay, N.; Lara, L.; Scholten, F.; Preusker, F.; Leyrat, C.; Pajola, M.; Osiris-Rosetta Team

2015-10-01

Since the Rosetta mission arrived at the comet 67P/Churyumov-Gerasimenko (67/P C-G) on July 2014, the comet nucleus has been mapped by both OSIRIS (Optical, Spectroscopic, and Infrared Remote Imaging System, [1]) NAC (Narrow Angle Camera) and WAC (Wide Angle Camera) acquiring a huge quantity of surface's images at different wavelength bands, under variable illumination conditions and spatial resolution, and producing the most detailed maps at the highest spatial resolution of a comet nucleus surface.67/P C-G's nucleus shows an irregular bi-lobed shape of complex morphology with terrains showing intricate features [2, 3] and a heterogeneity surface at different scales.

Harnessing cell-to-cell variations to probe bacterial structure and biophysics

NASA Astrophysics Data System (ADS)

Cass, Julie A.

Advances in microscopy and biotechnology have given us novel insights into cellular biology and physics. While bacteria were long considered to be relatively unstructured, the development of fluorescence microscopy techniques, and spatially and temporally resolved high-throughput quantitative studies, have uncovered that the bacterial cell is highly organized, and its structure rigorously maintained. In this thesis I will describe our gateTool software, designed to harness cell-to-cell variations to probe bacterial structure, and discuss two exciting aspects of structure that we have employed gateTool to investigate: (i) chromosome organization and the cellular mechanisms for controlling DNA dynamics, and (ii) the study of cell wall synthesis, and how the genes in the synthesis pathway impact cellular shape. In the first project, we develop a spatial and temporal mapping of cell-cycle-dependent chromosomal organization, and use this quantitative map to discover that chromosomal loci segregate from midcell with universal dynamics. In the second project, I describe preliminary time- lapse and snapshot imaging analysis suggesting phentoypical coherence across peptidoglycan synthesis pathways.

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

PubMed Central

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

2004-01-01

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

Does Walkability Contribute to Geographic Variation in Psychosocial Distress? A Spatial Analysis of 91,142 Members of the 45 and Up Study in Sydney, Australia.

PubMed

Mayne, Darren J; Morgan, Geoffrey G; Jalaludin, Bin B; Bauman, Adrian E

2018-02-06

Walkability describes the capacity of the built environment to promote walking, and has been proposed as a potential focus for community-level mental health planning. We evaluated this possibility by examining the contribution of area-level walkability to variation in psychosocial distress in a population cohort at spatial scales comparable to those used for regional planning in Sydney, Australia. Data on psychosocial distress were analysed for 91,142 respondents to the 45 and Up Study baseline survey between January 2006 and April 2009. We fit conditional auto regression models at the postal area level to obtain smoothed "disease maps" for psychosocial distress, and assess its association with area-level walkability after adjusting for individual- and area-level factors. Prevalence of psychosocial distress was 7.8%; similar for low (7.9%), low-medium (7.9%), medium-high (8.0%), and high (7.4%) walkability areas; and decreased with reducing postal area socioeconomic disadvantage: 12.2% (most), 9.3%, 7.5%, 5.9%, and 4.7% (least). Unadjusted disease maps indicated strong geographic clustering of psychosocial distress with 99.0% of excess prevalence due to unobserved and spatially structured factors, which was reduced to 55.3% in fully adjusted maps. Spatial and unstructured variance decreased by 97.3% and 39.8% after adjusting for individual-level factors, and another 2.3% and 4.2% with the inclusions of area-level factors. Excess prevalence of psychosocial distress in postal areas was attenuated in adjusted models but remained spatially structured. Postal area prevalence of high psychosocial distress is geographically clustered in Sydney, but is unrelated to postal area walkability. Area-level socioeconomic disadvantage makes a small contribution to this spatial structure; however, community-level mental health planning will likely deliver greatest benefits by focusing on individual-level contributors to disease burden and inequality associated with psychosocial distress.

Advancing Analysis of Spatio-Temporal Variations of Soil Nutrients in the Water Level Fluctuation Zone of China’s Three Gorges Reservoir Using Self-Organizing Map

PubMed Central

Ye, Chen; Li, Siyue; Yang, Yuyi; Shu, Xiao; Zhang, Jiaquan; Zhang, Quanfa

2015-01-01

The ~350 km2 water level fluctuation zone (WLFZ) in the Three Gorges Reservoir (TGR) of China, situated at the intersection of terrestrial and aquatic ecosystems, experiences a great hydrological change with prolonged winter inundation. Soil samples were collected in 12 sites pre- (September 2008) and post submergence (June 2009) in the WLFZ and analyzed for soil nutrients. Self-organizing map (SOM) and statistical analysis including multi-way ANOVA, paired-T test, and stepwise least squares multiple regression were employed to determine the spatio-temporal variations of soil nutrients in relation to submergence, and their correlations with soil physical characteristics. Results showed significant spatial variability in nutrients along ~600 km long shoreline of the TGR before and after submergence. There were higher contents of organic matter, total nitrogen (TN), and nitrate (NO3-) in the lower reach and total phosphorus (TP) in the upper reach that were primarily due to the spatial variations in soil particle size composition and anthropogenic activities. Submergence enhanced soil available potassium (K), while significantly decreased soil N, possibly due to the alterations of soil particle size composition and increase in soil pH. In addition, SOM analysis determined important roles of soil pH value, bulk density, soil particle size (i.e., silt and sand) and nutrients (TP, TK, and AK) on the spatial and temporal variations in soil quality. Our results suggest that urban sewage and agricultural runoffs are primary pollutants that affect soil nutrients in the WLFZ of TGR. PMID:25789612

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

PubMed

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

2014-08-01

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

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

PubMed Central

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

2014-01-01

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

Integrating population dynamics into mapping human exposure to seismic hazard

NASA Astrophysics Data System (ADS)

Freire, S.; Aubrecht, C.

2012-11-01

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

Spatial Variation in Mobility-Lifetime Product in Bulk TlBr and CZT

NASA Astrophysics Data System (ADS)

Phillips, David; Haegel, Nancy; Blaine, Kevin; Kim, Hadong; Ciampi, Guido; Cirignano, Len

2012-02-01

The energy resolution of a semiconductor radiation detector depends on the charge transport properties of the semiconductor, and the mobility-lifetime (μτ) product is a key figure of merit for charge transport. In this work, we investigate the effects of two impurities, Na and Cu, on the μτ product in bulk thallium bromide (TlBr) using cathodoluminescence (CL) and transport imaging. Transport imaging uses a scanning electron microscope to generate a line of charge carriers on the surface of a bulk sample, and the intensity and spatial distribution of the recombination luminescence are recorded. A Green's function approach is used to model the generation, diffusion, and recombination of charge carriers under steady-state conditions. The luminescence distribution is fit to the model to extract the ambipolar diffusion length and the μτ product, providing a high-resolution correlation between the luminescence variations due to dopants/defects and the quantitative transport behavior. The μτ product has been mapped across a 40 μm segment of TlBr at a resolution of 2 μm. Additionally, this approach has been used to locally map variations in ambipolar diffusion length and μτ product due to extended defects in cadmium zinc telluride (CZT).

Multi-Scale and Object-Oriented Analysis for Mountain Terrain Segmentation and Geomorphological Assessment

NASA Astrophysics Data System (ADS)

Marston, B. K.; Bishop, M. P.; Shroder, J. F.

2009-12-01

Digital terrain analysis of mountain topography is widely utilized for mapping landforms, assessing the role of surface processes in landscape evolution, and estimating the spatial variation of erosion. Numerous geomorphometry techniques exist to characterize terrain surface parameters, although their utility to characterize the spatial hierarchical structure of the topography and permit an assessment of the erosion/tectonic impact on the landscape is very limited due to scale and data integration issues. To address this problem, we apply scale-dependent geomorphometric and object-oriented analyses to characterize the hierarchical spatial structure of mountain topography. Specifically, we utilized a high resolution digital elevation model to characterize complex topography in the Shimshal Valley in the Western Himalaya of Pakistan. To accomplish this, we generate terrain objects (geomorphological features and landform) including valley floors and walls, drainage basins, drainage network, ridge network, slope facets, and elemental forms based upon curvature. Object-oriented analysis was used to characterize object properties accounting for object size, shape, and morphometry. The spatial overlay and integration of terrain objects at various scales defines the nature of the hierarchical organization. Our results indicate that variations in the spatial complexity of the terrain hierarchical organization is related to the spatio-temporal influence of surface processes and landscape evolution dynamics. Terrain segmentation and the integration of multi-scale terrain information permits further assessment of process domains and erosion, tectonic impact potential, and natural hazard potential. We demonstrate this with landform mapping and geomorphological assessment examples.

Object-based vegetation classification with high resolution remote sensing imagery

NASA Astrophysics Data System (ADS)

Yu, Qian

Vegetation species are valuable indicators to understand the earth system. Information from mapping of vegetation species and community distribution at large scales provides important insight for studying the phenological (growth) cycles of vegetation and plant physiology. Such information plays an important role in land process modeling including climate, ecosystem and hydrological models. The rapidly growing remote sensing technology has increased its potential in vegetation species mapping. However, extracting information at a species level is still a challenging research topic. I proposed an effective method for extracting vegetation species distribution from remotely sensed data and investigated some ways for accuracy improvement. The study consists of three phases. Firstly, a statistical analysis was conducted to explore the spatial variation and class separability of vegetation as a function of image scale. This analysis aimed to confirm that high resolution imagery contains the information on spatial vegetation variation and these species classes can be potentially separable. The second phase was a major effort in advancing classification by proposing a method for extracting vegetation species from high spatial resolution remote sensing data. The proposed classification employs an object-based approach that integrates GIS and remote sensing data and explores the usefulness of ancillary information. The whole process includes image segmentation, feature generation and selection, and nearest neighbor classification. The third phase introduces a spatial regression model for evaluating the mapping quality from the above vegetation classification results. The effects of six categories of sample characteristics on the classification uncertainty are examined: topography, sample membership, sample density, spatial composition characteristics, training reliability and sample object features. This evaluation analysis answered several interesting scientific questions such as (1) whether the sample characteristics affect the classification accuracy and how significant if it does; (2) how much variance of classification uncertainty can be explained by above factors. This research is carried out on a hilly peninsular area in Mediterranean climate, Point Reyes National Seashore (PRNS) in Northern California. The area mainly consists of a heterogeneous, semi-natural broadleaf and conifer woodland, shrub land, and annual grassland. A detailed list of vegetation alliances is used in this study. Research results from the first phase indicates that vegetation spatial variation as reflected by the average local variance (ALV) keeps a high level of magnitude between 1 m and 4 m resolution. (Abstract shortened by UMI.)

Remote Sensing of Salinity and Overview of Results from Aquarius

NASA Technical Reports Server (NTRS)

Le Vine, D. M.; Dinnat, E. P.; Meissner, T.; Wentz, F.; Yueh, S. H.; Lagerloef, G. S. E.

2015-01-01

Aquarius is a combined active/passive microwave (L-band) instrument designed to map the salinity of global oceans from space. The specific goal of Aquarius is to monitor the seasonal and interannual variation of the large scale features of the sea surface salinity (SSS) field of the open ocean (i.e. away from land). The instrumentation has been designed to provide monthly maps with a spatial resolution of 150 km and an accuracy of 0.2 psu

Mapping ground water vulnerability to pesticide leaching with a process-based metamodel of EuroPEARL.

PubMed

Tiktak, A; Boesten, J J T I; van der Linden, A M A; Vanclooster, M

2006-01-01

To support EU policy, indicators of pesticide leaching at the European level are required. For this reason, a metamodel of the spatially distributed European pesticide leaching model EuroPEARL was developed. EuroPEARL considers transient flow and solute transport and assumes Freundlich adsorption, first-order degradation and passive plant uptake of pesticides. Physical parameters are depth dependent while (bio)-chemical parameters are depth, temperature, and moisture dependent. The metamodel is based on an analytical expression that describes the mass fraction of pesticide leached. The metamodel ignores vertical parameter variations and assumes steady flow. The calibration dataset was generated with EuroPEARL and consisted of approximately 60,000 simulations done for 56 pesticides with different half-lives and partitioning coefficients. The target variable was the 80th percentile of the annual average leaching concentration at 1-m depth from a time series of 20 yr. The metamodel explains over 90% of the variation of the original model with only four independent spatial attributes. These parameters are available in European soil and climate databases, so that the calibrated metamodel could be applied to generate maps of the predicted leaching concentration in the European Union. Maps generated with the metamodel showed a good similarity with the maps obtained with EuroPEARL, which was confirmed by means of quantitative performance indicators.

Spatio-temporal patterns of Barmah Forest virus disease in Queensland, Australia.

PubMed

Naish, Suchithra; Hu, Wenbiao; Mengersen, Kerrie; Tong, Shilu

2011-01-01

Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ(2) = 7587, df = 7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland.

A Land System representation for global assessments and land-use modeling.

PubMed

van Asselen, Sanneke; Verburg, Peter H

2012-10-01

Current global scale land-change models used for integrated assessments and climate modeling are based on classifications of land cover. However, land-use management intensity and livestock keeping are also important aspects of land use, and are an integrated part of land systems. This article aims to classify, map, and to characterize Land Systems (LS) at a global scale and analyze the spatial determinants of these systems. Besides proposing such a classification, the article tests if global assessments can be based on globally uniform allocation rules. Land cover, livestock, and agricultural intensity data are used to map LS using a hierarchical classification method. Logistic regressions are used to analyze variation in spatial determinants of LS. The analysis of the spatial determinants of LS indicates strong associations between LS and a range of socioeconomic and biophysical indicators of human-environment interactions. The set of identified spatial determinants of a LS differs among regions and scales, especially for (mosaic) cropland systems, grassland systems with livestock, and settlements. (Semi-)Natural LS have more similar spatial determinants across regions and scales. Using LS in global models is expected to result in a more accurate representation of land use capturing important aspects of land systems and land architecture: the variation in land cover and the link between land-use intensity and landscape composition. Because the set of most important spatial determinants of LS varies among regions and scales, land-change models that include the human drivers of land change are best parameterized at sub-global level, where similar biophysical, socioeconomic and cultural conditions prevail in the specific regions. © 2012 Blackwell Publishing Ltd.

Estimating and mapping ecological processes influencing microbial community assembly

DOE PAGES

Stegen, James C.; Lin, Xueju; Fredrickson, Jim K.; ...

2015-05-01

Ecological community assembly is governed by a combination of (i) selection resulting from among-taxa differences in performance; (ii) dispersal resulting from organismal movement; and (iii) ecological drift resulting from stochastic changes in population sizes. The relative importance and nature of these processes can vary across environments. Selection can be homogeneous or variable, and while dispersal is a rate, we conceptualize extreme dispersal rates as two categories; dispersal limitation results from limited exchange of organisms among communities, and homogenizing dispersal results from high levels of organism exchange. To estimate the influence and spatial variation of each process we extend a recentlymore » developed statistical framework, use a simulation model to evaluate the accuracy of the extended framework, and use the framework to examine subsurface microbial communities over two geologic formations. For each subsurface community we estimate the degree to which it is influenced by homogeneous selection, variable selection, dispersal limitation, and homogenizing dispersal. Our analyses revealed that the relative influences of these ecological processes vary substantially across communities even within a geologic formation. We further identify environmental and spatial features associated with each ecological process, which allowed mapping of spatial variation in ecological-process-influences. The resulting maps provide a new lens through which ecological systems can be understood; in the subsurface system investigated here they revealed that the influence of variable selection was associated with the rate at which redox conditions change with subsurface depth.« less

Mapping Copper and Lead Concentrations at Abandoned Mine Areas Using Element Analysis Data from ICP–AES and Portable XRF Instruments: A Comparative Study

PubMed Central

Lee, Hyeongyu; Choi, Yosoon; Suh, Jangwon; Lee, Seung-Ho

2016-01-01

Understanding spatial variation of potentially toxic trace elements (PTEs) in soil is necessary to identify the proper measures for preventing soil contamination at both operating and abandoned mining areas. Many studies have been conducted worldwide to explore the spatial variation of PTEs and to create soil contamination maps using geostatistical methods. However, they generally depend only on inductively coupled plasma atomic emission spectrometry (ICP–AES) analysis data, therefore such studies are limited by insufficient input data owing to the disadvantages of ICP–AES analysis such as its costly operation and lengthy period required for analysis. To overcome this limitation, this study used both ICP–AES and portable X-ray fluorescence (PXRF) analysis data, with relatively low accuracy, for mapping copper and lead concentrations at a section of the Busan abandoned mine in Korea and compared the prediction performances of four different approaches: the application of ordinary kriging to ICP–AES analysis data, PXRF analysis data, both ICP–AES and transformed PXRF analysis data by considering the correlation between the ICP–AES and PXRF analysis data, and co-kriging to both the ICP–AES (primary variable) and PXRF analysis data (secondary variable). Their results were compared using an independent validation data set. The results obtained in this case study showed that the application of ordinary kriging to both ICP–AES and transformed PXRF analysis data is the most accurate approach when considers the spatial distribution of copper and lead contaminants in the soil and the estimation errors at 11 sampling points for validation. Therefore, when generating soil contamination maps for an abandoned mine, it is beneficial to use the proposed approach that incorporates the advantageous aspects of both ICP–AES and PXRF analysis data. PMID:27043594

Mapping Copper and Lead Concentrations at Abandoned Mine Areas Using Element Analysis Data from ICP-AES and Portable XRF Instruments: A Comparative Study.

PubMed

Lee, Hyeongyu; Choi, Yosoon; Suh, Jangwon; Lee, Seung-Ho

2016-03-30

Understanding spatial variation of potentially toxic trace elements (PTEs) in soil is necessary to identify the proper measures for preventing soil contamination at both operating and abandoned mining areas. Many studies have been conducted worldwide to explore the spatial variation of PTEs and to create soil contamination maps using geostatistical methods. However, they generally depend only on inductively coupled plasma atomic emission spectrometry (ICP-AES) analysis data, therefore such studies are limited by insufficient input data owing to the disadvantages of ICP-AES analysis such as its costly operation and lengthy period required for analysis. To overcome this limitation, this study used both ICP-AES and portable X-ray fluorescence (PXRF) analysis data, with relatively low accuracy, for mapping copper and lead concentrations at a section of the Busan abandoned mine in Korea and compared the prediction performances of four different approaches: the application of ordinary kriging to ICP-AES analysis data, PXRF analysis data, both ICP-AES and transformed PXRF analysis data by considering the correlation between the ICP-AES and PXRF analysis data, and co-kriging to both the ICP-AES (primary variable) and PXRF analysis data (secondary variable). Their results were compared using an independent validation data set. The results obtained in this case study showed that the application of ordinary kriging to both ICP-AES and transformed PXRF analysis data is the most accurate approach when considers the spatial distribution of copper and lead contaminants in the soil and the estimation errors at 11 sampling points for validation. Therefore, when generating soil contamination maps for an abandoned mine, it is beneficial to use the proposed approach that incorporates the advantageous aspects of both ICP-AES and PXRF analysis data.

Imaging electronic trap states in perovskite thin films with combined fluorescence and femtosecond transient absorption microscopy

DOE PAGES

Xiao, Kai; Ma, Ying -Zhong; Simpson, Mary Jane; ...

2016-04-22

Charge carrier trapping degrades the performance of organometallic halide perovskite solar cells. To characterize the locations of electronic trap states in a heterogeneous photoactive layer, a spatially resolved approach is essential. Here, we report a comparative study on methylammonium lead tri-iodide perovskite thin films subject to different thermal annealing times using a combined photoluminescence (PL) and femtosecond transient absorption microscopy (TAM) approach to spatially map trap states. This approach coregisters the initially populated electronic excited states with the regions that recombine radiatively. Although the TAM images are relatively homogeneous for both samples, the corresponding PL images are highly structured. Themore » remarkable variation in the PL intensities as compared to transient absorption signal amplitude suggests spatially dependent PL quantum efficiency, indicative of trapping events. Furthermore, detailed analysis enables identification of two trapping regimes: a densely packed trapping region and a sparse trapping area that appear as unique spatial features in scaled PL maps.« less

Geostatistical modelling of household malaria in Malawi

NASA Astrophysics Data System (ADS)

Chirombo, J.; Lowe, R.; Kazembe, L.

2012-04-01

Malaria is one of the most important diseases in the world today, common in tropical and subtropical areas with sub-Saharan Africa being the region most burdened, including Malawi. This region has the right combination of biotic and abiotic components, including socioeconomic, climatic and environmental factors that sustain transmission of the disease. Differences in these conditions across the country consequently lead to spatial variation in risk of the disease. Analysis of nationwide survey data that takes into account this spatial variation is crucial in a resource constrained country like Malawi for targeted allocation of scare resources in the fight against malaria. Previous efforts to map malaria risk in Malawi have been based on limited data collected from small surveys. The Malaria Indicator Survey conducted in 2010 is the most comprehensive malaria survey carried out in Malawi and provides point referenced data for the study. The data has been shown to be spatially correlated. We use Bayesian logistic regression models with spatial correlation to model the relationship between malaria presence in children and covariates such as socioeconomic status of households and meteorological conditions. This spatial model is then used to assess how malaria varies spatially and a malaria risk map for Malawi is produced. By taking intervention measures into account, the developed model is used to assess whether they have an effect on the spatial distribution of the disease and Bayesian kriging is used to predict areas where malaria risk is more likely to increase. It is hoped that this study can help reveal areas that require more attention from the authorities in the continuing fight against malaria, particularly in children under the age of five.

Cloud and fog interactions with coastal forests in the California Channel Islands

NASA Astrophysics Data System (ADS)

Still, C. J.; Baguskas, S. A.; Williams, P.; Fischer, D. T.; Carbone, M. S.; Rastogi, B.

2015-12-01

Coastal forests in California are frequently covered by clouds or immersed in fog in the rain-free summer. Scientists have long surmised that fog might provide critical water inputs to these forests. However, until recently, there has been little ecophysiological research to support how or why plants should prefer foggy regions; similarly, there is very little work quantifying water delivered to ecosystems by fog drip except for a few notable sites along the California coast. However, without spatial datasets of summer cloudcover and fog inundation, combined with detailed process studies, questions regarding the roles of cloud shading and fog drip in dictating plant distributions and ecosystem physiology cannot be addressed effectively. The overall objective of this project is to better understand how cloudcover and fog influence forest metabolism, growth, and distribution. Across a range of sites in California's Channel Islands National Park we measured a wide variety of ecosystem processes and properties. We then related these to cloudcover and fog immersion maps created using satellite datasets and airport and radiosonde observations. We compiled a spatially continuous dataset of summertime cloudcover frequency of the Southern California bight using satellite imagery from the NOAA geostationary GOES-11 Imager. We also created map of summertime cloudcover frequency of this area using MODIS imagery. To assess the ability of our mapping approach to predict spatial and temporal fog inundation patterns, we compared our monthly average daytime fog maps for GOES pixels corresponding to stations where fog inputs were measured with fog collectors in a Bishop pine forest. We also compared our cloudcover maps to measurements of irradiance measurements. Our results demonstrate that cloudcover and fog strongly modulate radiation, water, and carbon budgets, as well as forest distributions, in this semi-arid environment. Measurements of summertime fog drip, pine sapflow and growth, and soil respiration are strongly related to variations in cloudcover and fog drip. Importantly, spatial variations in cloud cover and fog immersion drive large changes in modeled water budgets and correspond closely to patterns of tree growth and mortality.

Contrasting patterns of fine-scale herb layer species composition in temperate forests

NASA Astrophysics Data System (ADS)

Chudomelová, Markéta; Zelený, David; Li, Ching-Feng

2017-04-01

Although being well described at the landscape level, patterns in species composition of forest herb layer are rarely studied at smaller scales. Here, we examined fine-scale environmental determinants and spatial structures of herb layer communities in thermophilous oak- and hornbeam dominated forests of the south-eastern part of the Czech Republic. Species composition of herb layer vegetation and environmental variables were recorded within a fixed grid of 2 × 2 m subplots regularly distributed within 1-ha quadrate plots in three forest stands. For each site, environmental models best explaining species composition were constructed using constrained ordination analysis. Spatial eigenvector mapping was used to model and account for spatial structures in community variation. Mean Ellenberg indicator values calculated for each subplot were used for ecological interpretation of spatially structured residual variation. The amount of variation explained by environmental and spatial models as well as the selection of variables with the best explanatory power differed among sites. As an important environmental factor, relative elevation was common to all three sites, while pH and canopy openness were shared by two sites. Both environmental and community variation was mostly coarse-scaled, as was the spatially structured portion of residual variation. When corrected for bias due to spatial autocorrelation, those environmental factors with already weak explanatory power lost their significance. Only a weak evidence of possibly omitted environmental predictor was found for autocorrelated residuals of site models using mean Ellenberg indicator values. Community structure was determined by different factors at different sites. The relative importance of environmental filtering vs. spatial processes was also site specific, implying that results of fine-scale studies tend to be shaped by local conditions. Contrary to expectations based on other studies, overall dominance of spatial processes at fine scale has not been detected. Ecologists should keep this in mind when making generalizations about community dynamics.

Mapping plastic greenhouse with medium spatial resolution satellite data: Development of a new spectral index

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.

Comprehensive lake dynamics mapping at continental scales using Landsat 8

USDA-ARS?s Scientific Manuscript database

Inland lakes, important water resources, play a crucial role in the global water cycle and are sensitive to global warming and human activities. There clearly is a pressing need to understand temporal and spatial variations of lakes at global and continental scales. The recent operation of Landsat...

SUMMARY OF TECHNIQUES AND UNIQUE USES FOR DIRECT PUSH METHODS IN SITE CHARACTERIZATION ON CONTAMINATED FIELD SITES

EPA Science Inventory

Site characterization of subsurface contaminant transport is often hampered by a lack of knowledge of site heterogeneity and temporal variations in hydrogeochemistry. Two case studies are reviewed to illustrate the utility of macro-scale mapping information along with spatially-...

Phylogenetic congruence of lichenised fungi and algae is affected by spatial scale and taxonomic diversity.

PubMed

Buckley, Hannah L; Rafat, Arash; Ridden, Johnathon D; Cruickshank, Robert H; Ridgway, Hayley J; Paterson, Adrian M

2014-01-01

The role of species' interactions in structuring biological communities remains unclear. Mutualistic symbioses, involving close positive interactions between two distinct organismal lineages, provide an excellent means to explore the roles of both evolutionary and ecological processes in determining how positive interactions affect community structure. In this study, we investigate patterns of co-diversification between fungi and algae for a range of New Zealand lichens at the community, genus, and species levels and explore explanations for possible patterns related to spatial scale and pattern, taxonomic diversity of the lichens considered, and the level sampling replication. We assembled six independent datasets to compare patterns in phylogenetic congruence with varied spatial extent of sampling, taxonomic diversity and level of specimen replication. For each dataset, we used the DNA sequences from the ITS regions of both the fungal and algal genomes from lichen specimens to produce genetic distance matrices. Phylogenetic congruence between fungi and algae was quantified using distance-based redundancy analysis and we used geographic distance matrices in Moran's eigenvector mapping and variance partitioning to evaluate the effects of spatial variation on the quantification of phylogenetic congruence. Phylogenetic congruence was highly significant for all datasets and a large proportion of variance in both algal and fungal genetic distances was explained by partner genetic variation. Spatial variables, primarily at large and intermediate scales, were also important for explaining genetic diversity patterns in all datasets. Interestingly, spatial structuring was stronger for fungal than algal genetic variation. As the spatial extent of the samples increased, so too did the proportion of explained variation that was shared between the spatial variables and the partners' genetic variation. Different lichen taxa showed some variation in their phylogenetic congruence and spatial genetic patterns and where greater sample replication was used, the amount of variation explained by partner genetic variation increased. Our results suggest that the phylogenetic congruence pattern, at least at small spatial scales, is likely due to reciprocal co-adaptation or co-dispersal. However, the detection of these patterns varies among different lichen taxa, across spatial scales and with different levels of sample replication. This work provides insight into the complexities faced in determining how evolutionary and ecological processes may interact to generate diversity in symbiotic association patterns at the population and community levels. Further, it highlights the critical importance of considering sample replication, taxonomic diversity and spatial scale in designing studies of co-diversification.

Remote sensing of potential lunar resources. 2: High spatial resolution mapping of spectral reflectance ratios and implications for nearside mare TiO2 content`

NASA Technical Reports Server (NTRS)

Melendrez, David E.; Johnson, Jeffrey R.; Larson, Stephen M.; Singer, Robert B.

1994-01-01

High spatial resolution maps illustrating variations in spectral reflectance 400/560 nm ratio values have been generated for the following mare regions: (1) the border between southern Mare Serenitatis and northern Mare Tranquillitatis (including the MS-2 standard area and Apollo 17 landing site), (2) central Mare Tranquillitatis, (3) Oceanus Procellarum near Seleucus, and (4) southern Oceanus Procellarum and Flamsteed. We have also obtained 320-1000 nm reflectance spectra of several sites relative to MS-2 to facilitate scaling of the images and provide additional information on surface composition. Inferred TiO2 abundances for these mare regions have been determined using an empirical calibration which relates the weight percent TiO2 in mature mare regolith to the observed 400/560 nm ratio. Mare areas with high TiO2 abundances are probably rich in ilmenite (FeTiO3) a potential lunar resource. The highest potential TiO2 concentrations we have identified in the nearside maria occur in central Mare Tranquillitatis. Inferred TiO2 contents for these areas are greater than 9 wt% and are spatially consistent with the highest-TiO2 regions mapped previously at lower spatial resolution. We note that the morphology of surface units with high 400/560 nm ratio values increases in complexity at higher spatial resolutions. Comparisons have been made with previously published geologic maps, Lunar Orbiter IV, and ground-based images, and some possible morphologic correlatins have been found between our mapped 400/560 nm ratio values and volcanic landforms such as lava flows, mare domes, and collapse pits.

Climate downscaling effects on predictive ecological models: a case study for threatened and endangered vertebrates in the southeastern United States

USGS Publications Warehouse

Bucklin, David N.; Watling, James I.; Speroterra, Carolina; Brandt, Laura A.; Mazzotti, Frank J.; Romañach, Stephanie S.

2013-01-01

High-resolution (downscaled) projections of future climate conditions are critical inputs to a wide variety of ecological and socioeconomic models and are created using numerous different approaches. Here, we conduct a sensitivity analysis of spatial predictions from climate envelope models for threatened and endangered vertebrates in the southeastern United States to determine whether two different downscaling approaches (with and without the use of a regional climate model) affect climate envelope model predictions when all other sources of variation are held constant. We found that prediction maps differed spatially between downscaling approaches and that the variation attributable to downscaling technique was comparable to variation between maps generated using different general circulation models (GCMs). Precipitation variables tended to show greater discrepancies between downscaling techniques than temperature variables, and for one GCM, there was evidence that more poorly resolved precipitation variables contributed relatively more to model uncertainty than more well-resolved variables. Our work suggests that ecological modelers requiring high-resolution climate projections should carefully consider the type of downscaling applied to the climate projections prior to their use in predictive ecological modeling. The uncertainty associated with alternative downscaling methods may rival that of other, more widely appreciated sources of variation, such as the general circulation model or emissions scenario with which future climate projections are created.

Atlas of depth-duration frequency of precipitation annual maxima for Texas

USGS Publications Warehouse

Asquith, William H.; Roussel, Meghan C.

2004-01-01

Ninety-six maps depicting the spatial variation of the depth-duration frequency of precipitation annual maxima for Texas are presented. The recurrence intervals represented are 2, 5, 10, 25, 50, 100, 250, and 500 years. The storm durations represented are 15 and 30 minutes; 1, 2, 3, 6, and 12 hours; and 1, 2, 3, 5, and 7 days. The maps were derived using geographically referenced parameter maps of probability distributions used in previously published research by the U.S. Geological Survey to model the magnitude and frequency of precipitation annual maxima for Texas. The maps in this report apply that research and update depth-duration frequency of precipitation maps available in earlier studies done by the National Weather Service.

The impacts of disturbance on the spatial and temporal variations of carbon balance in forest ecosystems on Hokkaido, Japan

NASA Astrophysics Data System (ADS)

Hirata, R.; Ito, A.; Saigusa, N.

2013-12-01

Carbon balance in a forest ecosystem can be quite variable if the forest ecosystem structure and function change abruptly as a result of disturbance and subsequent recovery processes. A map of forest age is useful for upscaling carbon balance from the site level to a regional scale because it provides information about when disturbance occurred and how it spread over a wide area. In this study, we used maps of forest age to help evaluate spatial and temporal variations in the carbon balance of forest ecosystems with a process-based ecosystem model. Forests less than 60 years old account for more than 70% of Japanese forests because forest stands have been quickly replaced after disturbance caused by thinning, harvesting, plantations, fires, typhoons, and insect damage. However, few studies have attempted to quantify how much disturbance affects the spatial and temporal variations of carbon balance. In this study, we focused on how disturbance and subsequent re-growth affected the spatial and temporal variations of the carbon balance of forests. We adapted the Vegetation Integrative SImulator for Trace Gases (VISIT) model in order to simulate carbon balance on Hokkaido, which is the northernmost island of Japan. The model was validated with tower flux data obtained from forests with ages between 0 and 43 years. Simulations of the carbon balance were conducted for the period 1948-2010 after a 1000-year spin-up at a spatial resolution of 1 km × 1 km. We investigated two case studies of simulated carbon balance: one that took into account the spatial distribution of forest ages derived from forest inventory data, and another that ignored the impact of disturbance (i.e., no disturbance and a homogeneous distribution of ages). We first focused on the difference from 2000-2010 in the spatial distribution of net ecosystem production (NEP) between the disturbance and non-disturbance cases. In the non-disturbance case, the temporal and spatial changes in NEP were gradual and ranged from 0 to 1 t C ha-1 y-1, depending on meteorological conditions such as temperature or solar radiation. In the disturbance case, however, large NEP changes ranging from 3 to 5 t C ha-1 y-1 were distributed in patches like hotspots, because the forests in those spots ranged in age from 20 to 100 years and were younger than the forests in the non-disturbance case. In the 1970s, wood harvesting and tree planting were conducted intensively on Hokkaido. In the disturbance case during this period, there were many hotspots where NEP was negative. We next focused on the difference between the disturbance and non-disturbance cases of temporal variations of spatially averaged NEP on Hokkaido. Until 1970, the difference between the two cases of average NEP was less than 0.01 t C ha-1 y-1. After 1970, the difference became large and reached about 0.5 t C ha-1 y-1, the implication being that the regional NEP in the disturbance case increased to as much as 2-5 times the regional NEP of the non-disturbance case. Our results show the importance of considering forest age when simulating the carbon balance of forests. Carbon balance maps that take forest age into account are useful for carbon management and prediction of ecosystem feedbacks on climate change.

Estimation of global soil respiration by accounting for land-use changes derived from remote sensing data.

PubMed

Adachi, Minaco; Ito, Akihiko; Yonemura, Seiichiro; Takeuchi, Wataru

2017-09-15

Soil respiration is one of the largest carbon fluxes from terrestrial ecosystems. Estimating global soil respiration is difficult because of its high spatiotemporal variability and sensitivity to land-use change. Satellite monitoring provides useful data for estimating the global carbon budget, but few studies have estimated global soil respiration using satellite data. We provide preliminary insights into the estimation of global soil respiration in 2001 and 2009 using empirically derived soil temperature equations for 17 ecosystems obtained by field studies, as well as MODIS climate data and land-use maps at a 4-km resolution. The daytime surface temperature from winter to early summer based on the MODIS data tended to be higher than the field-observed soil temperatures in subarctic and temperate ecosystems. The estimated global soil respiration was 94.8 and 93.8 Pg C yr -1 in 2001 and 2009, respectively. However, the MODIS land-use maps had insufficient spatial resolution to evaluate the effect of land-use change on soil respiration. The spatial variation of soil respiration (Q 10 ) values was higher but its spatial variation was lower in high-latitude areas than in other areas. However, Q 10 in tropical areas was more variable and was not accurately estimated (the values were >7.5 or <1.0) because of the low seasonal variation in soil respiration in tropical ecosystems. To solve these problems, it will be necessary to validate our results using a combination of remote sensing data at higher spatial resolution and field observations for many different ecosystems, and it will be necessary to account for the effects of more soil factors in the predictive equations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Thermal and albedo mapping of the polar regions of Mars using Viking thermal mapper observations: 1. North polar region

NASA Technical Reports Server (NTRS)

Paige, David A.; Bachman, Jennifer E.; Keegan, Kenneth D.

1994-01-01

We present the first maps of the apparent thermal inertia and albedo of the north polar region of Mars. The observations used to create these maps were acquired by the infrared thermal mapper (IRTM) instruments on the two Viking orbiters over a 50-day period in 1978 during the Martian early northern summer season. The maps cover the region from 60 deg N to the north pole at a spatial resolution of 1/2 deg of latitude. The analysis and interpretation of these maps is aided by the results of a one-dimensional radiative convective model, which is used to calculate diurnal variations in surface and atmospheric temperatures, and brightness temperatures at the top of the atmospphere for a wide range of assumptions concerning aerosol optical properties and aerosol optical depths. The results of these calculations show that the effects of the Martian atmosphere on remote determinations of surface thermal inertia are more significant than have been indicated in previous studies. The maps of apparent thermal inertia and albedo show a great deal of spatial structure that is well correlated with surface features.

Kalman/Map filtering-aided fast normalized cross correlation-based Wi-Fi fingerprinting location sensing.

PubMed

Sun, Yongliang; Xu, Yubin; Li, Cheng; Ma, Lin

2013-11-13

A Kalman/map filtering (KMF)-aided fast normalized cross correlation (FNCC)-based Wi-Fi fingerprinting location sensing system is proposed in this paper. Compared with conventional neighbor selection algorithms that calculate localization results with received signal strength (RSS) mean samples, the proposed FNCC algorithm makes use of all the on-line RSS samples and reference point RSS variations to achieve higher fingerprinting accuracy. The FNCC computes efficiently while maintaining the same accuracy as the basic normalized cross correlation. Additionally, a KMF is also proposed to process fingerprinting localization results. It employs a new map matching algorithm to nonlinearize the linear location prediction process of Kalman filtering (KF) that takes advantage of spatial proximities of consecutive localization results. With a calibration model integrated into an indoor map, the map matching algorithm corrects unreasonable prediction locations of the KF according to the building interior structure. Thus, more accurate prediction locations are obtained. Using these locations, the KMF considerably improves fingerprinting algorithm performance. Experimental results demonstrate that the FNCC algorithm with reduced computational complexity outperforms other neighbor selection algorithms and the KMF effectively improves location sensing accuracy by using indoor map information and spatial proximities of consecutive localization results.

Kalman/Map Filtering-Aided Fast Normalized Cross Correlation-Based Wi-Fi Fingerprinting Location Sensing

PubMed Central

Sun, Yongliang; Xu, Yubin; Li, Cheng; Ma, Lin

2013-01-01

A Kalman/map filtering (KMF)-aided fast normalized cross correlation (FNCC)-based Wi-Fi fingerprinting location sensing system is proposed in this paper. Compared with conventional neighbor selection algorithms that calculate localization results with received signal strength (RSS) mean samples, the proposed FNCC algorithm makes use of all the on-line RSS samples and reference point RSS variations to achieve higher fingerprinting accuracy. The FNCC computes efficiently while maintaining the same accuracy as the basic normalized cross correlation. Additionally, a KMF is also proposed to process fingerprinting localization results. It employs a new map matching algorithm to nonlinearize the linear location prediction process of Kalman filtering (KF) that takes advantage of spatial proximities of consecutive localization results. With a calibration model integrated into an indoor map, the map matching algorithm corrects unreasonable prediction locations of the KF according to the building interior structure. Thus, more accurate prediction locations are obtained. Using these locations, the KMF considerably improves fingerprinting algorithm performance. Experimental results demonstrate that the FNCC algorithm with reduced computational complexity outperforms other neighbor selection algorithms and the KMF effectively improves location sensing accuracy by using indoor map information and spatial proximities of consecutive localization results. PMID:24233027

The 2004 Opposition of Ceres Observed with Adaptive Optics on the VLT

NASA Technical Reports Server (NTRS)

Erard, S.; Frorni, O.; Ollivier, M.; Dotto, E.; Roush, T.; Poulet, F.; Mueller, T.

2005-01-01

The close opposition of Ceres in January 2004 has been observed with the NACO adaptive optics system on the VLT. Both imaging and spectroscopy were performed in the 1.1-4.1 m range. Extensive longitudinal coverage was acquired during a three days run, with spatial resolution up to 50 km in imaging mode. The scientific objectives are 1) to provide the first IR map of Ceres; 2) to map possible compositional variations at the surface. Only imaging results are presented here.

Accuracy assessment of seven global land cover datasets over China

NASA Astrophysics Data System (ADS)

Yang, Yongke; Xiao, Pengfeng; Feng, Xuezhi; Li, Haixing

2017-03-01

Land cover (LC) is the vital foundation to Earth science. Up to now, several global LC datasets have arisen with efforts of many scientific communities. To provide guidelines for data usage over China, nine LC maps from seven global LC datasets (IGBP DISCover, UMD, GLC, MCD12Q1, GLCNMO, CCI-LC, and GlobeLand30) were evaluated in this study. First, we compared their similarities and discrepancies in both area and spatial patterns, and analysed their inherent relations to data sources and classification schemes and methods. Next, five sets of validation sample units (VSUs) were collected to calculate their accuracy quantitatively. Further, we built a spatial analysis model and depicted their spatial variation in accuracy based on the five sets of VSUs. The results show that, there are evident discrepancies among these LC maps in both area and spatial patterns. For LC maps produced by different institutes, GLC 2000 and CCI-LC 2000 have the highest overall spatial agreement (53.8%). For LC maps produced by same institutes, overall spatial agreement of CCI-LC 2000 and 2010, and MCD12Q1 2001 and 2010 reach up to 99.8% and 73.2%, respectively; while more efforts are still needed if we hope to use these LC maps as time series data for model inputting, since both CCI-LC and MCD12Q1 fail to represent the rapid changing trend of several key LC classes in the early 21st century, in particular urban and built-up, snow and ice, water bodies, and permanent wetlands. With the highest spatial resolution, the overall accuracy of GlobeLand30 2010 is 82.39%. For the other six LC datasets with coarse resolution, CCI-LC 2010/2000 has the highest overall accuracy, and following are MCD12Q1 2010/2001, GLC 2000, GLCNMO 2008, IGBP DISCover, and UMD in turn. Beside that all maps exhibit high accuracy in homogeneous regions; local accuracies in other regions are quite different, particularly in Farming-Pastoral Zone of North China, mountains in Northeast China, and Southeast Hills. Special attention should be paid for data users who are interested in these regions.

AGN Space Telescope and Optical Reverberation Mapping Project. IV. Velocity-Delay Mapping of Broad Emission Lines in NGC 5548

NASA Astrophysics Data System (ADS)

Horne, Keith D.; Agn Storm Team

2015-01-01

Two-dimensional velocity-delay maps of AGN broad emission line regions can be recovered by modelling observations of reverberating emission-line profiles on the assumption that the line profile variations are driven by changes in ionising radiation from a compact source near the black hole. The observable light travel time delay resolves spatial structure on iso-delay paraboloids, while the doppler shift resolves kinematic structure along the observer's line-of-sight. Velocity-delay maps will be presented and briefly discussed for the Lyman alpha, CIV and Hbeta line profiles based on the HST and ground-based spectrophotometric monitoring of NGC 5548 during the 2014 AGN STORM campaign.

A variational Bayes spatiotemporal model for electromagnetic brain mapping.

PubMed

Nathoo, F S; Babul, A; Moiseev, A; Virji-Babul, N; Beg, M F

2014-03-01

In this article, we present a new variational Bayes approach for solving the neuroelectromagnetic inverse problem arising in studies involving electroencephalography (EEG) and magnetoencephalography (MEG). This high-dimensional spatiotemporal estimation problem involves the recovery of time-varying neural activity at a large number of locations within the brain, from electromagnetic signals recorded at a relatively small number of external locations on or near the scalp. Framing this problem within the context of spatial variable selection for an underdetermined functional linear model, we propose a spatial mixture formulation where the profile of electrical activity within the brain is represented through location-specific spike-and-slab priors based on a spatial logistic specification. The prior specification accommodates spatial clustering in brain activation, while also allowing for the inclusion of auxiliary information derived from alternative imaging modalities, such as functional magnetic resonance imaging (fMRI). We develop a variational Bayes approach for computing estimates of neural source activity, and incorporate a nonparametric bootstrap for interval estimation. The proposed methodology is compared with several alternative approaches through simulation studies, and is applied to the analysis of a multimodal neuroimaging study examining the neural response to face perception using EEG, MEG, and fMRI. © 2013, The International Biometric Society.

Predictive models and spatial variations of vital capacity in healthy people from 6 to 84 years old in China based on geographical factors.

PubMed

He, Jinwei; Ge, Miao; Wang, Congxia; Jiang, Naigui; Zhang, Mingxin; Yun, Pujun

2014-07-01

The aim of this study was to provide a scientific basic for a unified standard of the reference value of vital capacity (VC) of healthy subjects from 6 and 84 years old in China. The normal reference value of VC was correlated to seven geographical factors, including altitude (X1), annual duration of sunshine (X2), annual mean air temperature (X3), annual mean relative humidity (X4), annual precipitation amount (X5), annual air temperature range (X6) and annual mean wind speed (X7). Predictive models were established by five different linear and nonlinear methods. The best models were selected by t-test. The geographical distribution map of VC in different age groups can be interpolated by Kriging's method using ArcGIS software. It was found that the correlation of VC and geographical factors in China was quite significant, especially for both males and females aged from 6 to 45. The best models were built for different age groups. The geographical distribution map shows the spatial variations of VC in China precisely. The VC of healthy subjects can be simulated by the best model or acquired from the geographical distribution map provided the geographical factors for that city or county of China are known.

The Orbiting Carbon Observatory Mission: Watching the Earth Breathe Mapping CO2 from Space

NASA Technical Reports Server (NTRS)

Boain, Ron

2007-01-01

Approach: Collect spatially resolved, high resolution spectroscopic observations of CO2 and O2 absorption in reflected sunlight. Use these data to resolve spatial and temporal variations in the column averaged CO2 dry air mole fraction, X(sub CO2) over the sunlit hemisphere. Employ independent calibration and validation approaches to produce X(sub CO2) estimates with random errors and biases no larger than 1-2 ppm (0.3-0.5%) on regional scales at monthly intervals.

Schools, Air Pollution, and Active Transportation: An Exploratory Spatial Analysis of Calgary, Canada.

PubMed

Bertazzon, Stefania; Shahid, Rizwan

2017-07-25

An exploratory spatial analysis investigates the location of schools in Calgary (Canada) in relation to air pollution and active transportation options. Air pollution exhibits marked spatial variation throughout the city, along with distinct spatial patterns in summer and winter; however, all school locations lie within low to moderate pollution levels. Conversely, the study shows that almost half of the schools lie in low walkability locations; likewise, transitability is low for 60% of schools, and only bikability is widespread, with 93% of schools in very bikable locations. School locations are subsequently categorized by pollution exposure and active transportation options. This analysis identifies and maps schools according to two levels of concern: schools in car-dependent locations and relatively high pollution; and schools in locations conducive of active transportation, yet exposed to relatively high pollution. The findings can be mapped and effectively communicated to the public, health practitioners, and school boards. The study contributes with an explicitly spatial approach to the intra-urban public health literature. Developed for a moderately polluted city, the methods can be extended to more severely polluted environments, to assist in developing spatial public health policies to improve respiratory outcomes, neurodevelopment, and metabolic and attention disorders in school-aged children.

Atmospheric deposition maps for the Rocky Mountains

USGS Publications Warehouse

Nanus, L.; Campbell, D.H.; Ingersoll, G.P.; Clow, D.W.; Mast, M.A.

2003-01-01

Variability in atmospheric deposition across the Rocky Mountains is influenced by elevation, slope, aspect, and precipitation amount and by regional and local sources of air pollution. To improve estimates of deposition in mountainous regions, maps of average annual atmospheric deposition loadings of nitrate, sulfate, and acidity were developed for the Rocky Mountains by using spatial statistics. A parameter-elevation regressions on independent slopes model (PRISM) was incorporated to account for variations in precipitation amount over mountainous regions. Chemical data were obtained from the National Atmospheric Deposition Program/National Trends Network and from annual snowpack surveys conducted by the US Geological Survey and National Park Service, in cooperation with other Federal, State and local agencies. Surface concentration maps were created by ordinary kriging in a geographic information system, using a local trend and mathematical model to estimate the spatial variance. Atmospheric-deposition maps were constructed at 1-km resolution by multiplying surface concentrations from the kriged grid and estimates of precipitation amount from the PRISM model. Maps indicate an increasing spatial trend in concentration and deposition of the modeled constituents, particularly nitrate and sulfate, from north to south throughout the Rocky Mountains and identify hot-spots of atmospheric deposition that result from combined local and regional sources of air pollution. Highest nitrate (2.5-3.0kg/ha N) and sulfate (10.0-12.0kg/ha SO4) deposition is found in northern Colorado.

On the Science-Policy Bridge: Do Spatial Heat Vulnerability Assessment Studies Influence Policy?

PubMed

Wolf, Tanja; Chuang, Wen-Ching; McGregor, Glenn

2015-10-23

Human vulnerability to heat varies at a range of spatial scales, especially within cities where there can be noticeable intra-urban differences in heat risk factors. Mapping and visualizing intra-urban heat vulnerability offers opportunities for presenting information to support decision-making. For example the visualization of the spatial variation of heat vulnerability has the potential to enable local governments to identify hot spots of vulnerability and allocate resources and increase assistance to people in areas of greatest need. Recently there has been a proliferation of heat vulnerability mapping studies, all of which, to varying degrees, justify the process of vulnerability mapping in a policy context. However, to date, there has not been a systematic review of the extent to which the results of vulnerability mapping studies have been applied in decision-making. Accordingly we undertook a comprehensive review of 37 recently published papers that use geospatial techniques for assessing human vulnerability to heat. In addition, we conducted an anonymous survey of the lead authors of the 37 papers in order to establish the level of interaction between the researchers as science information producers and local authorities as information users. Both paper review and author survey results show that heat vulnerability mapping has been used in an attempt to communicate policy recommendations, raise awareness and induce institutional networking and learning, but has not as yet had a substantive influence on policymaking or preventive action.

Atlas warping for brain morphometry

NASA Astrophysics Data System (ADS)

Machado, Alexei M. C.; Gee, James C.

1998-06-01

In this work, we describe an automated approach to morphometry based on spatial normalizations of the data, and demonstrate its application to the analysis of gender differences in the human corpus callosum. The purpose is to describe a population by a reduced and representative set of variables, from which a prior model can be constructed. Our approach is rooted in the assumption that individual anatomies can be considered as quantitative variations on a common underlying qualitative plane. We can therefore imagine that a given individual's anatomy is a warped version of some referential anatomy, also known as an atlas. The spatial warps which transform a labeled atlas into anatomic alignment with a population yield immediate knowledge about organ size and shape in the group. Furthermore, variation within the set of spatial warps is directly related to the anatomic variation among the subjects. Specifically, the shape statistics--mean and variance of the mappings--for the population can be calculated in a special basis, and an eigendecomposition of the variance performed to identify the most significant modes of shape variation. The results obtained with the corpus callosum study confirm the existence of substantial anatomical differences between males and females, as reported in previous experimental work.

Preliminary work of mangrove ecosystem carbon stock mapping in small island using remote sensing: above and below ground carbon stock mapping on medium resolution satellite image

NASA Astrophysics Data System (ADS)

Wicaksono, Pramaditya; Danoedoro, Projo; Hartono, Hartono; Nehren, Udo; Ribbe, Lars

2011-11-01

Mangrove forest is an important ecosystem located in coastal area that provides various important ecological and economical services. One of the services provided by mangrove forest is the ability to act as carbon sink by sequestering CO2 from atmosphere through photosynthesis and carbon burial on the sediment. The carbon buried on mangrove sediment may persist for millennia before return to the atmosphere, and thus act as an effective long-term carbon sink. Therefore, it is important to understand the distribution of carbon stored within mangrove forest in a spatial and temporal context. In this paper, an effort to map carbon stocks in mangrove forest is presented using remote sensing technology to overcome the handicap encountered by field survey. In mangrove carbon stock mapping, the use of medium spatial resolution Landsat 7 ETM+ is emphasized. Landsat 7 ETM+ images are relatively cheap, widely available and have large area coverage, and thus provide a cost and time effective way of mapping mangrove carbon stocks. Using field data, two image processing techniques namely Vegetation Index and Linear Spectral Unmixing (LSU) were evaluated to find the best method to explain the variation in mangrove carbon stocks using remote sensing data. In addition, we also tried to estimate mangrove carbon sequestration rate via multitemporal analysis. Finally, the technique which produces significantly better result was used to produce a map of mangrove forest carbon stocks, which is spatially extensive and temporally repetitive.

Mapping wood density globally using remote sensing and climatological data

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

The use of crop rotation for mapping soil organic content in farmland

NASA Astrophysics Data System (ADS)

Yang, Lin; Song, Min; Zhu, A.-Xing; Qin, Chengzhi

2017-04-01

Most of the current digital soil mapping uses natural environmental covariates. However, human activities have significantly impacted the development of soil properties since half a century, and therefore become an important factor affecting soil spatial variability. Many researches have done field experiments to show how soil properties are impacted and changed by human activities, however, spatial variation data of human activities as environmental covariates have been rarely used in digital soil mapping. In this paper, we took crop rotation as an example of agricultural activities, and explored its effectiveness in characterizing and mapping the spatial variability of soil. The cultivated area of Xuanzhou city and Langxi County in Anhui Province was chosen as the study area. Three main crop rotations,including double-rice, wheat-rice,and oilseed rape-cotton were observed through field investigation in 2010. The spatial distribution of the three crop rotations in the study area was obtained by multi-phase remote sensing image interpretation using a supervised classification method. One-way analysis of variance (ANOVA) for topsoil organic content in the three crop rotation groups was performed. Factor importance of seven natural environmental covariates, crop rotation, Land use and NDVI were generated by variable importance criterion of Random Forest. Different combinations of environmental covariates were selected according to the importance rankings of environmental covariates for predicting SOC using Random Forest and Soil Landscape Inference Model (SOLIM). A cross validation was generated to evaluated the mapping accuracies. The results showed that there were siginificant differences of topsoil organic content among the three crop rotation groups. The crop rotation is more important than parent material, land use or NDVI according to the importance ranking calculated by Random Forest. In addition, crop rotation improved the mapping accuracy, especially for the flat clutivated area. This study demonstrates the usefulness of human activities in digital soil mapping and thus indicates the necessity for human activity factors in digital soil mapping studies.

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

USGS Publications Warehouse

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

2015-01-01

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

Mapping and predictive variations of soil bacterial richness across France

PubMed Central

Dequietd, Samuel; Saby, Nicolas P. A.; Lelièvre, Mélanie; Nowak, Virginie; Tripied, Julie; Régnier, Tiffanie; Jolivet, Claudy; Arrouays, Dominique; Wincker, Patrick; Cruaud, Corinne; Karimi, Battle; Bispo, Antonio; Maron, Pierre Alain; Chemidlin Prévost-Bouré, Nicolas; Ranjard, Lionel

2017-01-01

Although numerous studies have demonstrated the key role of bacterial diversity in soil functions and ecosystem services, little is known about the variations and determinants of such diversity on a nationwide scale. The overall objectives of this study were i) to describe the bacterial taxonomic richness variations across France, ii) to identify the ecological processes (i.e. selection by the environment and dispersal limitation) influencing this distribution, and iii) to develop a statistical predictive model of soil bacterial richness. We used the French Soil Quality Monitoring Network (RMQS), which covers all of France with 2,173 sites. The soil bacterial richness (i.e. OTU number) was determined by pyrosequencing 16S rRNA genes and related to the soil characteristics, climatic conditions, geomorphology, land use and space. Mapping of bacterial richness revealed a heterogeneous spatial distribution, structured into patches of about 111km, where the main drivers were the soil physico-chemical properties (18% of explained variance), the spatial descriptors (5.25%, 1.89% and 1.02% for the fine, medium and coarse scales, respectively), and the land use (1.4%). Based on these drivers, a predictive model was developed, which allows a good prediction of the bacterial richness (R2adj of 0.56) and provides a reference value for a given pedoclimatic condition. PMID:29059218

Mapping and predictive variations of soil bacterial richness across France.

PubMed

Terrat, Sébastien; Horrigue, Walid; Dequiedt, Samuel; Saby, Nicolas P A; Lelièvre, Mélanie; Nowak, Virginie; Tripied, Julie; Régnier, Tiffanie; Jolivet, Claudy; Arrouays, Dominique; Wincker, Patrick; Cruaud, Corinne; Karimi, Battle; Bispo, Antonio; Maron, Pierre Alain; Chemidlin Prévost-Bouré, Nicolas; Ranjard, Lionel

2017-01-01

Although numerous studies have demonstrated the key role of bacterial diversity in soil functions and ecosystem services, little is known about the variations and determinants of such diversity on a nationwide scale. The overall objectives of this study were i) to describe the bacterial taxonomic richness variations across France, ii) to identify the ecological processes (i.e. selection by the environment and dispersal limitation) influencing this distribution, and iii) to develop a statistical predictive model of soil bacterial richness. We used the French Soil Quality Monitoring Network (RMQS), which covers all of France with 2,173 sites. The soil bacterial richness (i.e. OTU number) was determined by pyrosequencing 16S rRNA genes and related to the soil characteristics, climatic conditions, geomorphology, land use and space. Mapping of bacterial richness revealed a heterogeneous spatial distribution, structured into patches of about 111km, where the main drivers were the soil physico-chemical properties (18% of explained variance), the spatial descriptors (5.25%, 1.89% and 1.02% for the fine, medium and coarse scales, respectively), and the land use (1.4%). Based on these drivers, a predictive model was developed, which allows a good prediction of the bacterial richness (R2adj of 0.56) and provides a reference value for a given pedoclimatic condition.

Spatio-Temporal Patterns of Barmah Forest Virus Disease in Queensland, Australia

PubMed Central

Naish, Suchithra; Hu, Wenbiao; Mengersen, Kerrie; Tong, Shilu

2011-01-01

Background Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. Methods/Principal Findings We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ2 = 7587, df = 7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. Conclusions/Significance This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland. PMID:22022430

Towards integrated assessment of the northern Adriatic Sea sediment budget using remote sensing

NASA Astrophysics Data System (ADS)

Taramelli, A.; Filipponi, F.; Valentini, E.; Zucca, F.; Gutierrez, O. Q.; Liberti, L.; Cordella, M.

2014-12-01

Understanding the factors influencing sediment fluxes is a key issue to interpret the evolution of coastal sedimentation under natural and human impact and relevant for the natural resources management. Despite river plumes represent one of the major gain in sedimentary budget of littoral cells, knowledge of factors influencing complex behavior of coastal plumes, like river discharge characteristics, wind stress and hydro-climatic variables, has not been yet fully investigated. Use of Earth Observation data allows the identification of spatial and temporal variations of suspended sediments related to river runoff, seafloor erosion, sediment transport and deposition processes. Objective of the study is to investigate sediment fluxes in northern Adriatic Sea by linking suspended sediment patterns of coastal plumes to hydrologic and climatic forcing regulating the sedimentary cell budget and geomorphological evolution in coastal systems and continental shelf waters. Analysis of Total Suspended Matter (TSM) product, derived from 2002-2012 MERIS time series, was done to map changes in spatial and temporal dimension of suspended sediments, focusing on turbid plume waters and intense wind stress conditions. From the generated multi temporal TSM maps, dispersal patterns of major freshwater runoff plumes in northern Adriatic Sea were evaluated through spatial variability of coastal plumes shape and extent. Additionally, sediment supply from river distributary mouths was estimated from TSM and correlated with river discharge rates, wind field and wave field through time. Spatial based methodology has been developed to identify events of wave-generated resuspension of sediments, which cause variation in water column turbidity, occurring during intense wind stress and extreme metocean conditions, especially in the winter period. The identified resuspension events were qualitatively described and compared with to hydro-climatic variables. The identification of spatial and temporal pattern variability highlighted the presence of seasonal sediment dynamics linked to the seasonal cycle in river discharge and wind stress. Results suggest that sediment fluxes generate geomorphological variations in northern Adriatic Sea, which are mainly controlled by river discharge rates and modulated by the winds.

Neutron absorption constraints on the composition of 4 Vesta

USGS Publications Warehouse

Prettyman, Thomas H.; Mittlefehldt, David W.; Yamashita, Naoyuki; Beck, Andrew W.; Feldman, William C.; Hendricks, John S.; Lawrence, David J.; McCoy, Timothy J.; McSween, Harry Y.; Paplowski, Patrick N.; Reedy, Robert C.; Toplis, Michael J.; Le Corre, Lucille; Mizzon, Hugau; Reddy, Vishnu; Titus, Timothy N.; Raymond, Carol A.; Russell, Christopher T.

2013-01-01

Global maps of the macroscopic thermal neutron absorption cross section of Vesta's regolith by the Gamma Ray and Neutron Detector (GRaND) on board the NASA Dawn spacecraft provide constraints on the abundance and distribution of Fe, Ca, Al, Mg, and other rock-forming elements. From a circular, polar low-altitude mapping orbit, GRaND sampled the regolith to decimeter depths with a spatial resolution of about 300 km. At this spatial scale, the variation in neutron absorption is about seven times lower than that of the Moon. The observed variation is consistent with the range of absorption for howardite whole-rock compositions, which further supports the connection between Vesta and the howardite, eucrite, and diogenite meteorites. We find a strong correlation between neutron absorption and the percentage of eucritic materials in howardites and polymict breccias, which enables petrologic mapping of Vesta's surface. The distribution of basaltic eucrite and diogenite determined from neutron absorption measurements is qualitatively similar to that indicated by visible and near infrared spectroscopy. The Rheasilvia basin and ejecta blanket has relatively low absorption, consistent with Mg-rich orthopyroxene. Based on a combination of Fe and neutron absorption measurements, olivine-rich lithologies are not detected on the spatial scales sampled by GRaND. The sensitivity of GRaND to the presence of mantle material is described and implications for the absence of an olivine signature are discussed. High absorption values found in Vesta's “dark” hemisphere, where exogenic hydrogen has accumulated, indicate that this region is richer in basaltic eucrite, representative of Vesta's ancient upper crust.

Neutron absorption constraints on the composition of 4 Vesta

NASA Astrophysics Data System (ADS)

Prettyman, Thomas H.; Mittlefehldt, David W.; Yamashita, Naoyuki; Beck, Andrew W.; Feldman, William C.; Hendricks, John S.; Lawrence, David J.; McCoy, Timothy J.; McSween, Harry Y.; Peplowski, Patrick N.; Reedy, Robert C.; Toplis, Michael J.; Corre, Lucille; Mizzon, Hugau; Reddy, Vishnu; Titus, Timothy N.; Raymond, Carol A.; Russell, Christopher T.

2013-11-01

Global maps of the macroscopic thermal neutron absorption cross section of Vesta's regolith by the Gamma Ray and Neutron Detector (GRaND) on board the NASA Dawn spacecraft provide constraints on the abundance and distribution of Fe, Ca, Al, Mg, and other rock-forming elements. From a circular, polar low-altitude mapping orbit, GRaND sampled the regolith to decimeter depths with a spatial resolution of about 300 km. At this spatial scale, the variation in neutron absorption is about seven times lower than that of the Moon. The observed variation is consistent with the range of absorption for howardite whole-rock compositions, which further supports the connection between Vesta and the howardite, eucrite, and diogenite meteorites. We find a strong correlation between neutron absorption and the percentage of eucritic materials in howardites and polymict breccias, which enables petrologic mapping of Vesta's surface. The distribution of basaltic eucrite and diogenite determined from neutron absorption measurements is qualitatively similar to that indicated by visible and near infrared spectroscopy. The Rheasilvia basin and ejecta blanket has relatively low absorption, consistent with Mg-rich orthopyroxene. Based on a combination of Fe and neutron absorption measurements, olivine-rich lithologies are not detected on the spatial scales sampled by GRaND. The sensitivity of GRaND to the presence of mantle material is described and implications for the absence of an olivine signature are discussed. High absorption values found in Vesta's "dark" hemisphere, where exogenic hydrogen has accumulated, indicate that this region is richer in basaltic eucrite, representative of Vesta's ancient upper crust.

How Deep Is Your SNARC? Interactions Between Numerical Magnitude, Response Hands, and Reachability in Peripersonal Space.

PubMed

Lohmann, Johannes; Schroeder, Philipp A; Nuerk, Hans-Christoph; Plewnia, Christian; Butz, Martin V

2018-01-01

Spatial, physical, and semantic magnitude dimensions can influence action decisions in human cognitive processing and interact with each other. For example, in the spatial-numerical associations of response code (SNARC) effect, semantic numerical magnitude facilitates left-hand or right-hand responding dependent on the small or large magnitude of number symbols. SNARC-like interactions of numerical magnitudes with the radial spatial dimension (depth) were postulated from early on. Usually, the SNARC effect in any direction is investigated using fronto-parallel computer monitors for presentation of stimuli. In such 2D setups, however, the metaphorical and literal interpretation of the radial depth axis with seemingly close/far stimuli or responses are not distinct. Hence, it is difficult to draw clear conclusions with respect to the contribution of different spatial mappings to the SNARC effect. In order to disentangle the different mappings in a natural way, we studied parametrical interactions between semantic numerical magnitude, horizontal directional responses, and perceptual distance by means of stereoscopic depth in an immersive virtual reality (VR). Two VR experiments show horizontal SNARC effects across all spatial displacements in traditional latency measures and kinematic response parameters. No indications of a SNARC effect along the depth axis, as it would be predicted by a direct mapping account, were observed, but the results show a non-linear relationship between horizontal SNARC slopes and physical distance. Steepest SNARC slopes were observed for digits presented close to the hands. We conclude that spatial-numerical processing is susceptible to effector-based processes but relatively resilient to task-irrelevant variations of radial-spatial magnitudes.

Soil maps as data input for soil erosion models: errors related to map scales

NASA Astrophysics Data System (ADS)

van Dijk, Paul; Sauter, Joëlle; Hofstetter, Elodie

2010-05-01

Soil erosion rates depend in many ways on soil and soil surface characteristics which vary in space and in time. To account for spatial variations of soil features, most distributed soil erosion models require data input derived from soil maps. Ideally, the level of spatial detail contained in the applied soil map should correspond to the objective of the modelling study. However, often the model user has only one soil map available which is then applied without questioning its suitability. The present study seeks to determine in how far soil map scale can be a source of error in erosion model output. The study was conducted on two different spatial scales, with for each of them a convenient soil erosion model: a) the catchment scale using the physically-based Limbourg Soil Erosion Model (LISEM), and b) the regional scale using the decision-tree expert model MESALES. The suitability of the applied soil map was evaluated with respect to an imaginary though realistic study objective for both models: the definition of erosion control measures at strategic locations at the catchment scale; the identification of target areas for the definition of control measures strategies at the regional scale. Two catchments were selected to test the sensitivity of LISEM to the spatial detail contained in soil maps: one catchment with relatively little contrast in soil texture, dominated by loess-derived soil (south of the Alsace), and one catchment with strongly contrasted soils at the limit between the Alsatian piedmont and the loess-covered hills of the Kochersberg. LISEM was run for both catchments using different soil maps ranging in scale from 1/25 000 to 1/100 000 to derive soil related input parameters. The comparison of the output differences was used to quantify the map scale impact on the quality of the model output. The sensitivity of MESALES was tested on the Haut-Rhin county for which two soil maps are available for comparison: 1/50 000 and 1/100 000. The order of resulting target areas (communes) was compared to evaluate the error induced by using the coarser soil data at 1/100 000. Results shows that both models are sensitive to the soil map scale used for model data input. A low sensitivity was found for the catchment with relatively homogeneous soil textures and the use of 1/100 000 soil maps seems allowed. The results for the catchment with strong soil texture variations showed significant differences depending on soil map scale on 75% of the catchment area. Here, the use of 1/100 000 soil map will indeed lead to wrong erosion diagnostics and will hamper the definition of a sound erosion control strategy. The regional scale model MESALES proved to be very sensitive to soil information. The two soil related model parameters (crusting sensitivity, and soil erodibility) reacted very often in the same direction therewith amplifying the change in the final erosion hazard class. The 1/100 000 soil map yielded different results on 40% of the sloping area compared to the 1/50 000 map. Significant differences in the order of target areas were found as well. The present study shows that the degree of sensitivity of the model output to soil map scale is rather variable and depends partly on the spatial variability of soil texture within the study area. Soil (textural) diversity needs to be accounted for to assure a fruitful use of soil erosion models. In some situations this might imply that additional soil data need to be collected in the field to refine the available soil map.

Reconstructing spatial and temporal patterns of paleoglaciation across Central Asia

NASA Astrophysics Data System (ADS)

Stroeven, Arjen P.

2014-05-01

Understanding the behaviour of mountain glaciers and ice caps, the evolution of mountain landscapes, and testing global climate models all require well-constrained information on past spatial and temporal patterns of glacier change. Particularly important are transitional regions that have high spatial and temporal variation in glacier activity and that can provide a sensitive record of past climate change. Central Asia is an extreme continental location with glaciers that have responded sensitively to variations in major regional climate systems. As an international team, we are reconstructing glacial histories of several areas of the Tibetan Plateau as well as along the Tian Shan, Altai and Kunlun Mountains. Building on previous work, we are using remote sensing-based geomorphological mapping augmented with field observations to map out glacial landforms and the maximum distributions of erratics. We then use cosmogenic nuclide Be-10 and Al-26, optically stimulated luminescence, and electron spin resonance dating of moraines and other landforms to compare dating techniques and to constrain the ages of defined extents of paleo-glaciers and ice caps. Comparing consistently dated glacial histories across central Asia provides an opportunity to examine shifts in the dominance patterns of climate systems over time in the region. Results to date show significant variations in the timing and extent of glaciation, including areas in the southeast Tibetan Plateau and Tian Shan with extensive valley and small polythermal ice cap glaciation during the global last glacial maximum in contrast to areas in central and northeast Tibetan Plateau that had very limited valley glacier expansion then. Initial numerical modelling attempting to simulate mapped and dated paleoglacial extents indicates that relatively limited cooling is sufficient to produce observed past expansions of glaciers across the Tibetan Plateau, and predicts complex basal thermal regimes in some locations that match patterns of past glacial erosion inferred from landform patterns and ages. Future modelling will examine glacier behaviour along major mountain ranges across central Asia.

Mapping forest structure, species gradients and growth in an urban area using lidar and hyperspectral imagery

NASA Astrophysics Data System (ADS)

Gu, Huan

Urban forests play an important role in the urban ecosystem by providing a range of ecosystem services. Characterization of forest structure, species variation and growth in urban forests is critical for understanding the status, function and process of urban ecosystems, and helping maximize the benefits of urban ecosystems through management. The development of methods and applications to quantify urban forests using remote sensing data has lagged the study of natural forests due to the heterogeneity and complexity of urban ecosystems. In this dissertation, I quantify and map forest structure, species gradients and forest growth in an urban area using discrete-return lidar, airborne imaging spectroscopy and thermal infrared data. Specific objectives are: (1) to demonstrate the utility of leaf-off lidar originally collected for topographic mapping to characterize and map forest structure and associated uncertainties, including aboveground biomass, basal area, diameter, height and crown size; (2) to map species gradients using forest structural variables estimated from lidar and foliar functional traits, vegetation indices derived from AVIRIS hyperspectral imagery in conjunction with field-measured species data; and (3) to identify factors related to relative growth rates in aboveground biomass in the urban forests, and assess forest growth patterns across areas with varying degree of human interactions. The findings from this dissertation are: (1) leaf-off lidar originally acquired for topographic mapping provides a robust, potentially low-cost approach to quantify spatial patterns of forest structure and carbon stock in urban areas; (2) foliar functional traits and vegetation indices from hyperspectral data capture gradients of species distributions in the heterogeneous urban landscape; (3) species gradients, stand structure, foliar functional traits and temperature are strongly related to forest growth in the urban forests; and (4) high uncertainties in our ability to map forest structure, species gradient and growth rate occur in residential neighborhoods and along forest edges. Maps generated from this dissertation provide estimates of broad-scale spatial variations in forest structure, species distributions and growth to the city forest managers. The associated maps of uncertainty help managers understand the limitations of the maps and identify locations where the maps are more reliable and where more data are needed.

The History of Electromagnetic Induction Techniques in Soil Survey

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Doolittle, Jim

2014-05-01

Electromagnetic induction (EMI) has been used to characterize the spatial variability of soil properties since the late 1970s. Initially used to assess soil salinity, the use of EMI in soil studies has expanded to include: mapping soil types; characterizing soil water content and flow patterns; assessing variations in soil texture, compaction, organic matter content, and pH; and determining the depth to subsurface horizons, stratigraphic layers or bedrock, among other uses. In all cases the soil property being investigated must influence soil apparent electrical conductivity (ECa) either directly or indirectly for EMI techniques to be effective. An increasing number and diversity of EMI sensors have been developed in response to users' needs and the availability of allied technologies, which have greatly improved the functionality of these tools. EMI investigations provide several benefits for soil studies. The large amount of georeferenced data that can be rapidly and inexpensively collected with EMI provides more complete characterization of the spatial variations in soil properties than traditional sampling techniques. In addition, compared to traditional soil survey methods, EMI can more effectively characterize diffuse soil boundaries and identify included areas of dissimilar soils within mapped soil units, giving soil scientists greater confidence when collecting spatial soil information. EMI techniques do have limitations; results are site-specific and can vary depending on the complex interactions among multiple and variable soil properties. Despite this, EMI techniques are increasingly being used to investigate the spatial variability of soil properties at field and landscape scales.

Craniofacial plasticity in ancient Peru.

PubMed

Stone, Jessica H; Chew, Kristen; Ross, Ann H; Verano, John W

2015-01-01

Numerous studies have utilized craniometric data to explore the roles of genetic diversity and environment in human cranial shape variation. Peru is a particularly interesting region to examine cranial variation due to the wide variety of high and low altitude ecological zones, which in combination with rugged terrain have created isolated populations with vastly different physiological adaptations. This study examines seven samples from throughout Peru in an effort to understand the contributions of environmental adaptation and genetic relatedness to craniofacial variation at a regional scale. Morphological variation was investigated using a canonical discriminant analysis and Mahalanobis D(2) analysis. Results indicate that all groups are significantly different from one another with the closest relationship between Yauyos and Jahuay, two sites that are located geographically close in central Peru but in very different ecozones. The relationship between latitude/longitude and face shape was also examined with a spatial autocorrelation analysis (Moran's I) using ArcMap and show that there is significant spatial patterning for facial measures and geographic location suggesting that there is an association between biological variation and geographic location.

Matching Deep Tow Camera study and Sea Floor geochemical characterization of gas migration at the Tainan Ridge, South China Sea

NASA Astrophysics Data System (ADS)

Fan, L. F.; Lien, K. L.; Hsieh, I. C.; Lin, S.

2017-12-01

Methane seep in deep sea environment could lead to build up of chemosynthesis communities, and a number of geological and biological anomalies as compare to the surrounding area. In order to examine the linkage between seep anomalies and those at the vicinity background area, and to detail mapping those spatial variations, we used a deep towed camera system (TowCam) to survey seafloor on the Tainan Ridge, Northeastern South China Sea (SCS). The underwater sea floor pictures could provide better spatial variations to demonstrate impact of methane seep on the sea floor. Water column variations of salinity, temperature, dissolved oxygen were applied to delineate fine scale variations at the study area. In addition, sediment cores were collected for chemical analyses to confirm the existence of local spatial variations. Our results show large spatial variations existed as a result of differences in methane flux. In fact, methane is the driving force for the observed biogeochemical variations in the water column, on the sea floor, and in the sediment. Of the area we have surveyed, there are approximately 7% of total towcam survey data showing abnormal water properties. Corresponding to the water column anomalies, underwater sea floor pictures taken from those places showed that chemosynthetic clams and muscles could be identified, together with authigenic carbonate buildups, and bacterial mats. Moreover, sediment cores with chemical anomalies also matched those in the water column and on the sea floor. These anomalies, however, represent only a small portion of the area surveyed and could not be identified with typical (random) coring method. Methane seep, therefore, require tedious and multiple types of surveys to better understand the scale and magnitude of seep and biogeochemical anomalies those were driven by gas migrations.

Estimation of regional differences in wind erosion sensitivity in Hungary

NASA Astrophysics Data System (ADS)

Mezősi, G.; Blanka, V.; Bata, T.; Kovács, F.; Meyer, B.

2015-01-01

In Hungary, wind erosion is one of the most serious natural hazards. Spatial and temporal variation in the factors that determine the location and intensity of wind erosion damage are not well known, nor are the regional and local sensitivities to erosion. Because of methodological challenges, no multi-factor, regional wind erosion sensitivity map is available for Hungary. The aim of this study was to develop a method to estimate the regional differences in wind erosion sensitivity and exposure in Hungary. Wind erosion sensitivity was modelled using the key factors of soil sensitivity, vegetation cover and wind erodibility as proxies. These factors were first estimated separately by factor sensitivity maps and later combined by fuzzy logic into a regional-scale wind erosion sensitivity map. Large areas were evaluated by using publicly available data sets of remotely sensed vegetation information, soil maps and meteorological data on wind speed. The resulting estimates were verified by field studies and examining the economic losses from wind erosion as compensated by the state insurance company. The spatial resolution of the resulting sensitivity map is suitable for regional applications, as identifying sensitive areas is the foundation for diverse land development control measures and implementing management activities.

Spatial luminescence imaging of dopant incorporation in CdTe Films

DOE PAGES

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

2017-01-25

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

A tale of two "forests": random forest machine learning AIDS tropical forest carbon mapping.

PubMed

Mascaro, Joseph; Asner, Gregory P; Knapp, David E; Kennedy-Bowdoin, Ty; Martin, Roberta E; Anderson, Christopher; Higgins, Mark; Chadwick, K Dana

2014-01-01

Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus). The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such as regionally stratified sampling and upscaling, and it has rarely been employed with spatial data. Here, we evaluated the performance of Random Forest in upscaling airborne LiDAR (Light Detection and Ranging)-based carbon estimates compared to the stratification approach over a 16-million hectare focal area of the Western Amazon. We considered two runs of Random Forest, both with and without spatial contextual modeling by including--in the latter case--x, and y position directly in the model. In each case, we set aside 8 million hectares (i.e., half of the focal area) for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called "out-of-bag"), which proved insufficient for this spatial application. In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area, compared to 37% for stratification or 43% by Random Forest without spatial context. With the 60% improvement in explained variation, RMSE against validation LiDAR samples improved from 33 to 26 Mg C ha(-1) when using Random Forest with spatial context. Our results suggest that spatial context should be considered when using Random Forest, and that doing so may result in substantially improved carbon stock modeling for purposes of climate change mitigation.

A Tale of Two “Forests”: Random Forest Machine Learning Aids Tropical Forest Carbon Mapping

PubMed Central

Mascaro, Joseph; Asner, Gregory P.; Knapp, David E.; Kennedy-Bowdoin, Ty; Martin, Roberta E.; Anderson, Christopher; Higgins, Mark; Chadwick, K. Dana

2014-01-01

Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus). The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such as regionally stratified sampling and upscaling, and it has rarely been employed with spatial data. Here, we evaluated the performance of Random Forest in upscaling airborne LiDAR (Light Detection and Ranging)-based carbon estimates compared to the stratification approach over a 16-million hectare focal area of the Western Amazon. We considered two runs of Random Forest, both with and without spatial contextual modeling by including—in the latter case—x, and y position directly in the model. In each case, we set aside 8 million hectares (i.e., half of the focal area) for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called “out-of-bag”), which proved insufficient for this spatial application. In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area, compared to 37% for stratification or 43% by Random Forest without spatial context. With the 60% improvement in explained variation, RMSE against validation LiDAR samples improved from 33 to 26 Mg C ha−1 when using Random Forest with spatial context. Our results suggest that spatial context should be considered when using Random Forest, and that doing so may result in substantially improved carbon stock modeling for purposes of climate change mitigation. PMID:24489686

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

PubMed

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

2017-09-11

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

Temporal and spatial structure in a daily wildfire-start data set from the western United States (198696)

USGS Publications Warehouse

Bartlein, P.J.; Hostetler, S.W.; Shafer, S.L.; Holman, J.O.; Solomon, A.M.

2008-01-01

The temporal and spatial structure of 332 404 daily fire-start records from the western United States for the period 1986 through 1996 is illustrated using several complimentary visualisation techniques. We supplement maps and time series plots with Hovmo??ller diagrams that reduce the spatial dimensionality of the daily data in order to reveal the underlying space?time structure. The mapped distributions of all lightning- and human-started fires during the 11-year interval show similar first-order patterns that reflect the broad-scale distribution of vegetation across the West and the annual cycle of climate. Lightning-started fires are concentrated in the summer half-year and occur in widespread outbreaks that last a few days and reflect coherent weather-related controls. In contrast, fires started by humans occur throughout the year and tend to be concentrated in regions surrounding large-population centres or intensive-agricultural areas. Although the primary controls of human-started fires are their location relative to burnable fuel and the level of human activity, spatially coherent, weather-related variations in their incidence can also be noted. ?? IAWF 2008.

Landscape-Scale Controls on Aboveground Forest Carbon Stocks on the Osa Peninsula, Costa Rica

PubMed Central

Taylor, Philip; Asner, Gregory; Dahlin, Kyla; Anderson, Christopher; Knapp, David; Martin, Roberta; Mascaro, Joseph; Chazdon, Robin; Cole, Rebecca; Wanek, Wolfgang; Hofhansl, Florian; Malavassi, Edgar; Vilchez-Alvarado, Braulio; Townsend, Alan

2015-01-01

Tropical forests store large amounts of carbon in tree biomass, although the environmental controls on forest carbon stocks remain poorly resolved. Emerging airborne remote sensing techniques offer a powerful approach to understand how aboveground carbon density (ACD) varies across tropical landscapes. In this study, we evaluate the accuracy of the Carnegie Airborne Observatory (CAO) Light Detection and Ranging (LiDAR) system to detect top-of-canopy tree height (TCH) and ACD across the Osa Peninsula, Costa Rica. LiDAR and field-estimated TCH and ACD were highly correlated across a wide range of forest ages and types. Top-of-canopy height (TCH) reached 67 m, and ACD surpassed 225 Mg C ha-1, indicating both that airborne CAO LiDAR-based estimates of ACD are accurate in tall, high-biomass forests and that the Osa Peninsula harbors some of the most carbon-rich forests in the Neotropics. We also examined the relative influence of lithologic, topoedaphic and climatic factors on regional patterns in ACD, which are known to influence ACD by regulating forest productivity and turnover. Analyses revealed a spatially nested set of factors controlling ACD patterns, with geologic variation explaining up to 16% of the mapped ACD variation at the regional scale, while local variation in topographic slope explained an additional 18%. Lithologic and topoedaphic factors also explained more ACD variation at 30-m than at 100-m spatial resolution, suggesting that environmental filtering depends on the spatial scale of terrain variation. Our result indicate that patterns in ACD are partially controlled by spatial variation in geologic history and geomorphic processes underpinning topographic diversity across landscapes. ACD also exhibited spatial autocorrelation, which may reflect biological processes that influence ACD, such as the assembly of species or phenotypes across the landscape, but additional research is needed to resolve how abiotic and biotic factors contribute to ACD variation across high biomass, high diversity tropical landscapes. PMID:26061884

Resolution-enhanced Mapping Spectrometer

NASA Technical Reports Server (NTRS)

Kumer, J. B.; Aubrun, J. N.; Rosenberg, W. J.; Roche, A. E.

1993-01-01

A familiar mapping spectrometer implementation utilizes two dimensional detector arrays with spectral dispersion along one direction and spatial along the other. Spectral images are formed by spatially scanning across the scene (i.e., push-broom scanning). For imaging grating and prism spectrometers, the slit is perpendicular to the spatial scan direction. For spectrometers utilizing linearly variable focal-plane-mounted filters the spatial scan direction is perpendicular to the direction of spectral variation. These spectrometers share the common limitation that the number of spectral resolution elements is given by the number of pixels along the spectral (or dispersive) direction. Resolution enhancement by first passing the light input to the spectrometer through a scanned etalon or Michelson is discussed. Thus, while a detector element is scanned through a spatial resolution element of the scene, it is also temporally sampled. The analysis for all the pixels in the dispersive direction is addressed. Several specific examples are discussed. The alternate use of a Michelson for the same enhancement purpose is also discussed. Suitable for weight constrained deep space missions, hardware systems were developed including actuators, sensor, and electronics such that low-resolution etalons with performance required for implementation would weigh less than one pound.

Horizontal and vertical variability of soil properties in a trace element contaminated area

NASA Astrophysics Data System (ADS)

Burgos, Pilar; Madejón, Engracia; Pérez-de-Mora, Alfredo; Cabrera, Francisco

2008-02-01

The spatial distribution of some soil chemical properties and trace element contents of a plot affected by the Aznalcóllar mine spill were investigated using statistical and geostatistical methods to assess the extent of soil contamination. Total and EDTA-extractable soil trace element concentrations and total S content showed great variability and high coefficients of variation in the three examined depths. Soil in the plot was found to be significantly contaminated by As, Cd, Cu, Pb and Zn within a wide range of pH. Total trace element concentrations at all depths (0-60 cm) were much higher than background values of non-affected soil, indicating that despite the clean-up operations, the concentration of trace elements in the experimental plot was still high. The spatial distribution of the different variables was estimated by kriging to design contour maps. These maps allowed the identification of specific zones with high metal concentrations and low pH values corresponding to spots of residual sludge. Moreover, kriged maps showed distinct spatial distribution and hence different behaviour for the elements considered. This information may be applied to optimise remediation strategies in highly and moderately contaminated areas.

Spatio-temporal variation in groundwater head affected by stratigraphic heterogeneity of the alluvial aquifer in Northwest India

NASA Astrophysics Data System (ADS)

van Dijk, W. M.; Joshi, S. K.; Densmore, A. L.; Jackson, C. R.; Sutanudjaja, E.; Lafare, A. E. A.; Gupta, S.; Mackay, J. D.; Mason, P. J.; Sinha, R.

2017-12-01

Groundwater is a primary source of freshwater in the alluvial aquifer system of northwestern India. Unsustainable exploitation of the groundwater resources has led to a regional hotspot in groundwater depletion. Rapid groundwater-level decline shows spatial variation, as the effects of various stresses, including precipitation, potential evapotranspiration and abstraction, are likely to be influenced by the stratigraphic and geomorphic heterogeneity between sediment fan and interfan areas (see Geomorphological map in Figure A). We used a transfer function-noise (TFN) time series approach to quantify the effect of the various stress components in the period 1974-2010, based on predefined impulse response functions (IRFs) of von Asmuth et al. (2008). The objective of this study was 1) to acquire the impulse response function of various stresses, 2) assess the spatial estimation parameter (the zeroth moment, M0) of the spatial development of the groundwater head and 3) relate the spatial M0 to the observed stratigraphic and geomorphic heterogeneity. We collected information on the groundwater head pre- and post-monsoon, the district-wise monthly precipitation and potential evapotranspiration, and we modeled the monthly abstraction rate using land-use information. The TFN identified the IRF of precipitation as well as abstraction. The IRF, summarized in the parameter M0, identified a hotspot for the abstraction stress (see M0 spatial map for abstraction in Figure B) at the margins of the Sutlej and Yamuna fans. No hotspot is observed for the precipitation stress, but the M0 for precipitation increases with distance from the Himalayan front. At larger distances from the Himalayan front, observed groundwater head rises cannot be explained by the IRFs for the abstraction and precipitation stresses. This is likely because the current TFN models do not account for other stresses, such as recharge by canal leakage, which are locally important. We conclude that the spatial variation in the M0 for abstraction is controlled by stratigraphic and geomorphic heterogeneity. The fan margins and the interfan area are more affected by abstraction as these areas are underlain by fewer, and thinner, aquifer bodies them the fans themselves. Von Ashmuth et al,2008. Ground Water, 46 (1), 30-40

Habitat sequencing and the importance of discharge in inferences

Treesearch

Robert H. Hilderbrand; A. Dennis Lemly; C. Andrew Dolloff

1999-01-01

The authors constructed stream maps for a low-­gradient trout stream in southwestern Virginia during autumn (base flow) and spring (elevated flows) to compare spatial and temporal variation in stream habitats. Pool-riffle sequencing and total area occupied by pools and riffles changed substantially depending on the level of discharge: reduced discharge resulted in an...

Temporal and spatial variations of rainfall erosivity in Southern Taiwan

NASA Astrophysics Data System (ADS)

Lee, Ming-Hsi; Lin, Huan-Hsuan; Chu, Chun-Kuang

2014-05-01

Soil erosion models are essential in developing effective soil and water resource conservation strategies. Soil erosion is generally evaluated using the Universal Soil Loss Equation (USLE) with an appropriate regional scale description. Among factors in the USLE model, the rainfall erosivity index (R) provides one of the clearest indications of the effects of climate change. Accurate estimation of rainfall erosivity requires continuous rainfall data; however, such data rarely demonstrate good spatial and temporal coverage. The data set consisted of 9240 storm events for the period 1993 to 2011, monitored by 27 rainfall stations of the Central Weather Bureau (CWB) in southern Taiwan, was used to analyze the temporal-spatial variations of rainfall erosivity. The spatial distribution map was plotted based on rainfall erosivity by the Kriging interpolation method. Results indicated that rainfall erosivity is mainly concentrated in rainy season from June to November typically contributed 90% of the yearly R factor. The temporal variations of monthly rainfall erosivity during June to November and annual rainfall erosivity have increasing trend from 1993 to 2011. There is an increasing trend from southwest to northeast in spatial distribution of rainfall erosivity in southern Taiwan. The results further indicated that there is a higher relationship between elevation and rainfall erosivity. The method developed in this study may also be useful for sediment disasters on Climate Change.

Spatial multi-scale variability of soil nutrients in relation to environmental factors in a typical agricultural region, eastern China.

PubMed

Liu, Yang; Lv, Jianshu; Zhang, Bing; Bi, Jun

2013-04-15

Identifying the sources of spatial variability and deficiency risk of soil nutrients is a crucial issue for soil and agriculture management. A total of 1247 topsoil samples (0-20 cm) were collected at the nodes of a 2×2 km grid in Rizhao City and the contents of soil organic carbon (OC), total nitrogen (TN), and total phosphorus (TP) were determined. Factorial kriging analysis (FKA), stepwise multiple regression, and indicator kriging (IK) were appled to investigate the scale dependent correlations among soil nutrients, identify the sources of spatial variability at each spatial scale, and delineate the potential risk of soil nutrient deficiency. Linear model of co-regionalization (LMC) fitting indicated that the presence of multi-scale variation was comprised of nugget effect, an exponential structure with a range of 12 km (local scale), and a spherical structure with a range of 84 km (regional scale). The short-range variation of OC and TN was mainly dominated by land use types, and TP was controlled by terrain. At long-range scale, spatial variation of OC, TN, and TP was dominated by parent material. Indicator kriging maps depicted the probability of soil nutrient deficiency compared with the background values in eastern Shandong province. The high deficiency risk area of all nutrient integration was mainly located in eastern and northwestern parts. Copyright © 2013 Elsevier B.V. All rights reserved.

Geographic variations of ecosystem service intensity in Fuzhou City, China.

PubMed

Hu, Xisheng; Hong, Wei; Qiu, Rongzu; Hong, Tao; Chen, Can; Wu, Chengzhen

2015-04-15

Ecosystem services are strongly influenced by the landscape configuration of natural and human systems. So they are heterogeneous across landscapes. However lack of the knowledge of spatial variations of ecosystem services constrains the effective management and conservation of ecosystems. We presented a spatially explicit and quantitative assessment of the geographic variations in ecosystem services for the Fuzhou City in 2009 using exploratory spatial data analysis (ESDA) and semivariance analysis. Results confirmed a significant and positive spatial autocorrelation, and revealed several hot-spots and cold-spots for the spatial distribution of ecosystem service intensity (ESI) in the study area. Also the trend surface analysis indicated that the level of ESI tended to be reduced gradually from north to south and from west to east, with a trough in the urban central area, which was quite in accordance with land-use structure. A more precise cluster map was then developed using the range of lag distance, deriving from semivariance analysis, as neighborhood size instead of default value in the software of ESRI ArcGIS 10.0, and geographical clusters where population growth and land-use pressure varied significantly and positively with ESI across the city were also created by geographically weighted regression (GWR). This study has good policy implications applicable to prioritize areas for conservation or construction, and design ecological corridor to improve ecosystem service delivery to benefiting areas. Copyright © 2015 Elsevier B.V. All rights reserved.

Mars: Detaching of the Free Water Signature (FWS) Presence Regions on the Base of HEND/ODYSSEY Data and Their Correlation with Some Permafrost Features from MOC Data

NASA Technical Reports Server (NTRS)

Kuzmin, R. O.; Mitrofanov, I. G.; Litvak, M. L.; Boynton, M. V.; Saunders, R. S.

2003-01-01

The first results from global mapping of the neutron albedo from Mars by HEND instrument have shown the noticeable deficit of both the epithermal (EN) and the fast (FN) neutrons counts rate in the high latitudes regions of both hemispheres of the planet. The deficit is indicative for high enriching of the surface regolith by hydrogen, which may correspond to amount of any water phases and forms. The objectives of our study are the spatial and temporal variations of the free water (ice) signature in the Martian surface layer on the base of HEND/ODYSSEY data and their correlation with spatial spreading of some permafrost features, mapped on the base of MOC images. For the study we used the results of the global mapping (pixel 5 x5 ) of EN and FN albedo, realized by HEND/ODYSSEY in the period from 17 February to 10 December 2002 year.

Aeromagnetic survey map of the central California Coast Ranges

USGS Publications Warehouse

Langenheim, V.E.; Jachens, R.C.; Moussaoui, K.

2009-01-01

This aeromagnetic survey was flown as part of a Cooperative Research and Development Agreement (CRADA) with the Pacific Gas and Electric Company and is intended to promote further understanding of the geology and structure in the central California Coast Ranges by serving as a basis for geophysical interpretations and by supporting geological mapping, mineral and water resource investigations, and other topical studies. Local spatial variations in the Earth's magnetic field (evident as anomalies on aeromagnetic maps) reflect the distribution of magnetic minerals, primarily magnetite, in the underlying rocks. In many cases the volume content of magnetic minerals can be related to rock type, and abrupt spatial changes in the amount of magnetic minerals can commonly mark lithologic or structural boundaries. Bodies of serpentinite and other mafic and ultramafic rocks tend to produce the most intense magnetic anomalies, but such generalizations must be applied with caution because rocks with more felsic compositions, such as the porphyritic granodiorite-granite of the La Panza Range, and even some sedimentary units, also can cause measurable magnetic anomalies.

Compositional Mapping of the Transantarctic Mountains Using Orbital Reflectance Data

NASA Astrophysics Data System (ADS)

Salvatore, M. R.; Niebuhr, S.; Morin, P. J.; Cox, S.

2014-12-01

We report on our progress of remotely mapping compositional variations throughout the Transantarctic Mountains (TAM) using orbital spectroscopic data. These techniques were originally proven effective in Antarctica using moderate spatial resolution (30 m/pixel) Advanced Land Imager (ALI) data, and showed great successes in identifying even minor variations in composition throughout the McMurdo Dry Valleys (MDV) [Salvatore et al., 2013]. However, due to the orbital inclination of the Earth Observing-1 spacecraft, ALI is unable to image the central and southern TAM, making comparable studies at comparable resolutions impossible on a continental scale. Fortunately, the WorldView-2 satellite (DigitalGlobe, Inc.) boasts high-resolution (2 m/pixel) multispectral capabilities, with 8 spectral bands located between 427 nm and 908 nm, and is able to image the entirety of the TAM through off-nadir pointing capabilities. This provides the ability to continue our remote spectral mapping campaign throughout the TAM to identify compositional variations in support of past and future field operations. We present an updated map of relative spectral variability (RSV) in the vicinity of Shackleton Glacier. This mapping product consists of 91 individual WorldView-2 images, each corrected to top-of-atmosphere radiance and parameterized to highlight known compositional properties. The mapped area covers approximately 17,850 square kilometers of ice-covered and exposed terrain. Compositional variations are easily mapped, and small-scale variations in iron-bearing mineralogy are particularly well resolved. We also describe our updated atmospheric correction algorithm for the WorldView-2 dataset, which utilizes in-scene techniques to derive surface reflectance and does not necessitate the use of radiative transfer modeling. Our technique is validated using laboratory reflectance measurements. In conjunction with the Polar Rock Repository at the Ohio State University, we have measured hundreds of individual samples in an effort to verify and "ground-truth" this atmospheric removal algorithm. Using these methodologies and revised techniques, our objective is to make a fully calibrated and atmospherically corrected spectral map of the central TAM available to the scientific community.

Spatial Intensity Duration Frequency Relationships Using Hierarchical Bayesian Analysis for Urban Areas

NASA Astrophysics Data System (ADS)

Rupa, Chandra; Mujumdar, Pradeep

2016-04-01

In urban areas, quantification of extreme precipitation is important in the design of storm water drains and other infrastructure. Intensity Duration Frequency (IDF) relationships are generally used to obtain design return level for a given duration and return period. Due to lack of availability of extreme precipitation data for sufficiently large number of years, estimating the probability of extreme events is difficult. Typically, a single station data is used to obtain the design return levels for various durations and return periods, which are used in the design of urban infrastructure for the entire city. In an urban setting, the spatial variation of precipitation can be high; the precipitation amounts and patterns often vary within short distances of less than 5 km. Therefore it is crucial to study the uncertainties in the spatial variation of return levels for various durations. In this work, the extreme precipitation is modeled spatially using the Bayesian hierarchical analysis and the spatial variation of return levels is studied. The analysis is carried out with Block Maxima approach for defining the extreme precipitation, using Generalized Extreme Value (GEV) distribution for Bangalore city, Karnataka state, India. Daily data for nineteen stations in and around Bangalore city is considered in the study. The analysis is carried out for summer maxima (March - May), monsoon maxima (June - September) and the annual maxima rainfall. In the hierarchical analysis, the statistical model is specified in three layers. The data layer models the block maxima, pooling the extreme precipitation from all the stations. In the process layer, the latent spatial process characterized by geographical and climatological covariates (lat-lon, elevation, mean temperature etc.) which drives the extreme precipitation is modeled and in the prior level, the prior distributions that govern the latent process are modeled. Markov Chain Monte Carlo (MCMC) algorithm (Metropolis Hastings algorithm within a Gibbs sampler) is used to obtain the samples of parameters from the posterior distribution of parameters. The spatial maps of return levels for specified return periods, along with the associated uncertainties, are obtained for the summer, monsoon and annual maxima rainfall. Considering various covariates, the best fit model is selected using Deviance Information Criteria. It is observed that the geographical covariates outweigh the climatological covariates for the monsoon maxima rainfall (latitude and longitude). The best covariates for summer maxima and annual maxima rainfall are mean summer precipitation and mean monsoon precipitation respectively, including elevation for both the cases. The scale invariance theory, which states that statistical properties of a process observed at various scales are governed by the same relationship, is used to disaggregate the daily rainfall to hourly scales. The spatial maps of the scale are obtained for the study area. The spatial maps of IDF relationships thus generated are useful in storm water designs, adequacy analysis and identifying the vulnerable flooding areas.

Improving Calibration of the MBH-σ* Relation for AGN with the BRAVE Program

NASA Astrophysics Data System (ADS)

Batiste, Merida; Bentz, Misty C.; Manne-Nicholas, Emily; Raimundo, Sandra I.; Onken, Christopher A.; Vestergaard, Marianne; Bershady, Matthew A.

2017-01-01

The MBH - σ* relation for AGN, which relates the mass of the central supermassive black hole (MBH) to the bulge stellar velocity dispersion (σ*) of the host galaxy, is a powerful tool for studying the evolution of structure across cosmic time. Accurate calibration of this relation is essential, and much effort has been put into improving MBH determinations with this in mind. However calibration remains difficult because many nearby AGN with secure MBH determinations are hosted by late-type galaxies, with significant kinematic substructure such as bars, disks and rings. Kinematic substructure is known to contaminate and bias σ* determinations from long-slit and single aperture spectroscopy, ultimately limiting the utility of the MBH - σ* relation, and hampering efforts to investigate morphological dependencies. Integral-field spectroscopy (IFS) can be used to map the two dimensional kinematics, providing a method for measuring σ* absent some of the biases inherent in other methods, and giving a more complete picture of the spatial variations in the dynamics. We present the first set of results from the BRAVE program, the long-term goal of which is to use IFS to more accurately determine σ* for the calibrating sample of reverberation-mapped AGN. We present IFS kinematic maps for the sample of galaxies we have so far observed, which show clearly how spatial variation can impact σ* determinations from long-slit spectroscopy. We present a new fit to the MBH - σ* relation for the sample of 16 reverberation-mapped AGN for which we currently have σ* determinations from IFS, as well as a new determination of the virial scaling factor, f, for use with reverberation-mapping.

Integrationof Remote Sensing and Geographic information system in Ground Water Quality Assessment and Management

NASA Astrophysics Data System (ADS)

Shakak, N.

2015-04-01

Spatial variations in ground water quality in the Khartoum state, Sudan, have been studied using geographic information system (GIS) and remote sensing technique. Gegraphical informtion system a tool which is used for storing, analyzing and displaying spatial data is also used for investigating ground water quality information. Khartoum landsat mosac image aquired in 2013was used, Arc/Gis software applied to extract the boundary of the study area, the image was classified to create land use/land cover map. The land use map,geological and soil map are used for correlation between land use , geological formations, and soil types to understand the source of natural pollution that can lower the ground water quality. For this study, the global positioning system (GPS), used in the field to identify the borehole location in a three dimentional coordinate (Latitude, longitude, and altitude), water samples were collected from 156 borehole wells, and analyzed for physico-chemical parameters like electrical conductivity, Total dissolved solid,Chloride, Nitrate, Sodium, Magnisium, Calcium,and Flouride, using standard techniques in the laboratory and compared with the standards.The ground water quality maps of the entire study area have been prepared using spatial interpolation technique for all the above parameters.then the created maps used to visualize, analyze, and understand the relationship among the measured points. Mapping was coded for potable zones, non-potable zones in the study area, in terms of water quality sutability for drinking water and sutability for irrigation. In general satellite remote sensing in conjunction with geographical information system (GIS) offers great potential for water resource development and management.

On the Science-Policy Bridge: Do Spatial Heat Vulnerability Assessment Studies Influence Policy?

PubMed Central

Wolf, Tanja; Chuang, Wen-Ching; McGregor, Glenn

2015-01-01

Human vulnerability to heat varies at a range of spatial scales, especially within cities where there can be noticeable intra-urban differences in heat risk factors. Mapping and visualizing intra-urban heat vulnerability offers opportunities for presenting information to support decision-making. For example the visualization of the spatial variation of heat vulnerability has the potential to enable local governments to identify hot spots of vulnerability and allocate resources and increase assistance to people in areas of greatest need. Recently there has been a proliferation of heat vulnerability mapping studies, all of which, to varying degrees, justify the process of vulnerability mapping in a policy context. However, to date, there has not been a systematic review of the extent to which the results of vulnerability mapping studies have been applied in decision-making. Accordingly we undertook a comprehensive review of 37 recently published papers that use geospatial techniques for assessing human vulnerability to heat. In addition, we conducted an anonymous survey of the lead authors of the 37 papers in order to establish the level of interaction between the researchers as science information producers and local authorities as information users. Both paper review and author survey results show that heat vulnerability mapping has been used in an attempt to communicate policy recommendations, raise awareness and induce institutional networking and learning, but has not as yet had a substantive influence on policymaking or preventive action. PMID:26512681

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.

Spatio-temporal analysis of prodelta dynamics by means of new satellite generation: the case of Po river by Landsat-8 data

NASA Astrophysics Data System (ADS)

Manzo, Ciro; Braga, Federica; Zaggia, Luca; Brando, Vittorio Ernesto; Giardino, Claudia; Bresciani, Mariano; Bassani, Cristiana

2018-04-01

This paper describes a procedure to perform spatio-temporal analysis of river plume dispersion in prodelta areas by multi-temporal Landsat-8-derived products for identifying zones sensitive to water discharge and for providing geostatistical patterns of turbidity linked to different meteo-marine forcings. In particular, we characterized the temporal and spatial variability of turbidity and sea surface temperature (SST) in the Po River prodelta (Northern Adriatic Sea, Italy) during the period 2013-2016. To perform this analysis, a two-pronged processing methodology was implemented and the resulting outputs were analysed through a series of statistical tools. A pixel-based spatial correlation analysis was carried out by comparing temporal curves of turbidity and SST hypercubes with in situ time series of wind speed and water discharge, providing correlation coefficient maps. A geostatistical analysis was performed to determine the spatial dependency of the turbidity datasets per each satellite image, providing maps of correlation and variograms. The results show a linear correlation between water discharge and turbidity variations in the points more affected by the buoyant plumes and along the southern coast of Po River delta. Better inverse correlation was found between turbidity and SST during floods rather than other periods. The correlation maps of wind speed with turbidity show different spatial patterns depending on local or basin-scale wind effects. Variogram maps identify different spatial anisotropy structures of turbidity in response to ambient conditions (i.e. strong Bora or Scirocco winds, floods). Since the implemented processing methodology is based on open source software and free satellite data, it represents a promising tool for the monitoring of maritime ecosystems and to address water quality analyses and the investigations of sediment dynamics in estuarine and coastal waters.

An LES study on the spatial variability impact of surface sensible heat flux (SHF) on the convective boundary layer (CBL)

NASA Astrophysics Data System (ADS)

Kang, S. L.; Chun, J.; Kumar, A.

2015-12-01

We study the spatial variability impact of surface sensible heat flux (SHF) on the convective boundary layer (CBL), using the Weather Research and Forecasting (WRF) model in large eddy simulation (LES) mode. In order to investigate the response of the CBL to multi-scale feature of the surface SHF field over a local area of several tens of kilometers or smaller, an analytic surface SHF map is crated as a function of the chosen feature. The spatial variation in the SHF map is prescribed with a two-dimensional analytical perturbation field, which is generated by using the inverse transform technique of the Fourier series whose coefficients are controlled, of which spectrum to have a particular slope in the chosen range of wavelength. Then, the CBL responses to various SHF heterogeneities are summarized as a function of the spectral slope, in terms of mean structure, turbulence statistics and cross-scale processes. The range of feasible SHF heterogeneities is obtained from the SHF maps produced by a land surface model (LSM) of the WRF system. The LSM-derived SHF maps are a function of geographical data on various resolutions. Based on the numerical experiment results with the surface heterogeneities in the range, we will discuss the uncertainty in the SHF heterogeneity and its impact on the atmosphere in a numerical model. Also we will present the range of spatial scale of the surface SHF heterogeneity that significantly influence on the whole CBL. Lastly, we will report the test result of the hypothesis that the spatial variability of SHF is more representative of surface thermal heterogeneity than is the latent heat flux over the local area of several tens of kilometers or smaller.

A Holistic Landscape Description Reveals That Landscape Configuration Changes More over Time than Composition: Implications for Landscape Ecology Studies.

PubMed

Mimet, Anne; Pellissier, Vincent; Houet, Thomas; Julliard, Romain; Simon, Laurent

2016-01-01

Space-for-time substitution-that is, the assumption that spatial variations of a system can explain and predict the effect of temporal variations-is widely used in ecology. However, it is questionable whether it can validly be used to explain changes in biodiversity over time in response to land-cover changes. Here, we hypothesize that different temporal vs spatial trajectories of landscape composition and configuration may limit space-for-time substitution in landscape ecology. Land-cover conversion changes not just the surface areas given over to particular types of land cover, but also affects isolation, patch size and heterogeneity. This means that a small change in land cover over time may have only minor repercussions on landscape composition but potentially major consequences for landscape configuration. Using land-cover maps of the Paris region for 1982 and 2003, we made a holistic description of the landscape disentangling landscape composition from configuration. After controlling for spatial variations, we analyzed and compared the amplitudes of changes in landscape composition and configuration over time. For comparable spatial variations, landscape configuration varied more than twice as much as composition over time. Temporal changes in composition and configuration were not always spatially matched. The fact that landscape composition and configuration do not vary equally in space and time calls into question the use of space-for-time substitution in landscape ecology studies. The instability of landscapes over time appears to be attributable to configurational changes in the main. This may go some way to explaining why the landscape variables that account for changes over time in biodiversity are not the same ones that account for the spatial distribution of biodiversity.

Image processing for quantifying fracture orientation and length scale transitions during brittle deformation

NASA Astrophysics Data System (ADS)

Rizzo, R. E.; Healy, D.; Farrell, N. J.

2017-12-01

We have implemented a novel image processing tool, namely two-dimensional (2D) Morlet wavelet analysis, capable of detecting changes occurring in fracture patterns at different scales of observation, and able of recognising the dominant fracture orientations and the spatial configurations for progressively larger (or smaller) scale of analysis. Because of its inherited anisotropy, the Morlet wavelet is proved to be an excellent choice for detecting directional linear features, i.e. regions where the amplitude of the signal is regular along one direction and has sharp variation along the perpendicular direction. Performances of the Morlet wavelet are tested against the 'classic' Mexican hat wavelet, deploying a complex synthetic fracture network. When applied to a natural fracture network, formed triaxially (σ1>σ2=σ3) deforming a core sample of the Hopeman sandstone, the combination of 2D Morlet wavelet and wavelet coefficient maps allows for the detection of characteristic scale orientation and length transitions, associated with the shifts from distributed damage to the growth of localised macroscopic shear fracture. A complementary outcome arises from the wavelet coefficient maps produced by increasing the wavelet scale parameter. These maps can be used to chart the variations in the spatial distribution of the analysed entities, meaning that it is possible to retrieve information on the density of fracture patterns at specific length scales during deformation.

Schools, Air Pollution, and Active Transportation: An Exploratory Spatial Analysis of Calgary, Canada

PubMed Central

Bertazzon, Stefania; Shahid, Rizwan

2017-01-01

An exploratory spatial analysis investigates the location of schools in Calgary (Canada) in relation to air pollution and active transportation options. Air pollution exhibits marked spatial variation throughout the city, along with distinct spatial patterns in summer and winter; however, all school locations lie within low to moderate pollution levels. Conversely, the study shows that almost half of the schools lie in low walkability locations; likewise, transitability is low for 60% of schools, and only bikability is widespread, with 93% of schools in very bikable locations. School locations are subsequently categorized by pollution exposure and active transportation options. This analysis identifies and maps schools according to two levels of concern: schools in car-dependent locations and relatively high pollution; and schools in locations conducive of active transportation, yet exposed to relatively high pollution. The findings can be mapped and effectively communicated to the public, health practitioners, and school boards. The study contributes with an explicitly spatial approach to the intra-urban public health literature. Developed for a moderately polluted city, the methods can be extended to more severely polluted environments, to assist in developing spatial public health policies to improve respiratory outcomes, neurodevelopment, and metabolic and attention disorders in school-aged children. PMID:28757577

Long-term comparison of Kuparuk Watershed active layer maps, northern Alaska, USA

NASA Astrophysics Data System (ADS)

Nyland, K. E.; Queen, C.; Nelson, F. E.; Shiklomanov, N. I.; Streletskiy, D. A.; Klene, A. E.

2017-12-01

The active layer, or the uppermost soil horizon that thaws seasonally, is among the most dynamic components of the permafrost system. Evaluation of the thickness and spatial variation of the active layer is critical to many components of Arctic research, including climatology, ecology, environmental monitoring, and engineering. In this study we mapped active-layer thickness (ALT) across the 22,278 sq. km Kuparuk River basin on Alaska's North Slope throughout the summer of 2016. The Kuparuk River extends from the Brooks Range through the Arctic Foothills and across the Arctic Coastal Plain physiographic provinces, and drains into the Beaufort Sea. Methodology followed procedures used to produce an ALT map of the basin in 1995 accounting for the effects of topography, vegetation, topoclimate, and soils, using the same spatial sampling scheme for direct ALT and temperature measurement at representative locations and relating these parameters to vegetation-soil associations. A simple semi-empirical engineering solution was used to estimate thaw rates for the different associations. An improved lapse-rate formulation and a higher-resolution DEM were used to relate temperature to elevation. Three ALT maps were generated for the 2016 summer, combining measured thaw depth, temperature records, the 25 m ArcticDEM, high resolution remote sensed data, empirical laps rates, and a topoclimatic index through the thaw solution. These maps were used to track the spatial progression of thaw through the 2016 summer season and estimate a total volume of thawed soil. Maps produced in this study were compared to the 1995 map to track areas of significant geographic changes in patterns of ALT and total volume of thawed soil.

Multi-Compartment T2 Relaxometry Using a Spatially Constrained Multi-Gaussian Model

PubMed Central

Raj, Ashish; Pandya, Sneha; Shen, Xiaobo; LoCastro, Eve; Nguyen, Thanh D.; Gauthier, Susan A.

2014-01-01

The brain’s myelin content can be mapped by T2-relaxometry, which resolves multiple differentially relaxing T2 pools from multi-echo MRI. Unfortunately, the conventional fitting procedure is a hard and numerically ill-posed problem. Consequently, the T2 distributions and myelin maps become very sensitive to noise and are frequently difficult to interpret diagnostically. Although regularization can improve stability, it is generally not adequate, particularly at relatively low signal to noise ratio (SNR) of around 100–200. The purpose of this study was to obtain a fitting algorithm which is able to overcome these difficulties and generate usable myelin maps from noisy acquisitions in a realistic scan time. To this end, we restrict the T2 distribution to only 3 distinct resolvable tissue compartments, modeled as Gaussians: myelin water, intra/extra-cellular water and a slow relaxing cerebrospinal fluid compartment. We also impose spatial smoothness expectation that volume fractions and T2 relaxation times of tissue compartments change smoothly within coherent brain regions. The method greatly improves robustness to noise, reduces spatial variations, improves definition of white matter fibers, and enhances detection of demyelinating lesions. Due to efficient design, the additional spatial aspect does not cause an increase in processing time. The proposed method was applied to fast spiral acquisitions on which conventional fitting gives uninterpretable results. While these fast acquisitions suffer from noise and inhomogeneity artifacts, our preliminary results indicate the potential of spatially constrained 3-pool T2 relaxometry. PMID:24896833

Simultaneous Noncontact Precision Imaging of Microstructural and Thickness Variation in Dielectric Materials Using Terahertz Energy

NASA Technical Reports Server (NTRS)

Roth, Don J.; Seebo, Jeffrey P.; Winfree, William P.

2008-01-01

This article describes a noncontact single-sided terahertz electromagnetic measurement and imaging method that simultaneously characterizes microstructural (egs. spatially-lateral density) and thickness variation in dielectric (insulating) materials. The method was demonstrated for two materials-Space Shuttle External Tank sprayed-on foam insulation and a silicon nitride ceramic. It is believed that this method can be used as an inspection method for current and future NASA thermal protection system and other dielectric material inspection applications, where microstructural and thickness variation require precision mapping. Scale-up to more complex shapes such as cylindrical structures and structures with beveled regions would appear to be feasible.

Precision agriculture in dry land: spatial variability of crop yield and roles of soil surveys, aerial photos, and digital elevation models

NASA Astrophysics Data System (ADS)

Nachabe, Mahmood; Ahuja, Laj; Shaffer, Mary Lou; Ascough, J.; Flynn, Brian; Cipra, J.

1998-12-01

In dryland, yield of crop varies substantially in space, often changing by an order of magnitude within few meters. Precision agriculture aims at exploiting this variability by changing agriculture management practices in space according to site specific conditions. Thus instead of managing a field (typical area 50 to 100 hectares) as a single unit using average conditions, the field is partitioned into small pieces of land known as management units. The size of management units can be in the order of 100 to 1,000 m2 to capture the patterns of variation of yield in the field. Agricultural practices like seeding rate, type of crop, and tillage and fertilizers are applied at the scale of the management unit to suit local agronomic conditions in unit. If successfully practiced, precision agriculture has the potential of increasing income and minimizing environmental impacts by reducing over application of crop production inputs. In the 90s, the implementation of precision agriculture was facilitated tremendously due to the wide availability and use of three technologies: (1) the Global Positioning System (GPS), (2) the Geographic Information System (GIS), and (3) remote sensing. The introduction of the GPS allowed the farmer to determine his coordinate location as equipments are moved in the field. Thus, any piece of equipment can be easily programmed to vary agricultural practices according to coordinate location over the field. The GIS allowed the storage and manipulation of large sets of data and the production of yield maps. Yield maps can be correlated with soil attributes from soil survey, and/or topographical attributes from a Digital Elevation Model (DEM). This helps predicting variation of potential yield over the landscape based on the spatial distribution of soil and topographical attributes. Soil attributes may include soil PH, Organic Matter, porosity, and hydraulic conductivity, whereas topographical attributes involve the estimations of elevation, slope, aspect, curvature, and specific catchment area. Finally remote sensing provided a means of assessing soil and crop conditions over large scales from the air, without excessive sampling on the ground. There are two objectives for this work. The first objective is to analyze the spatial variability of yield across a spectrum of scales to identify the spatial characteristics of yield variation; in essence, we are trying to answer the following questions, at what scale of management unit we should resolve the field level variability and what is the relationship between this resolution and the observed variability form a yield map? The second objective is to identify the soil and topographical attributes that control yield variation over the landscape topography. We already know that, because erosion and deposition are major processes in the formation of a catena, soil variations occur in response to surface and subsurface flow over the landscape. Also landscape positions corresponding to low elevation tend to have high catchment area which usually results in high soil water content in the root zone and thick A horizon. Can topographical attributes explain yield variation observed in the landscape? Will topographical attributes extracted from a DEM compensate for the relatively poor spatial resolution from a soil survey?

Temporal and spatial variabilities in the surface moisture content of a fine-grained beach

NASA Astrophysics Data System (ADS)

Namikas, S. L.; Edwards, B. L.; Bitton, M. C. A.; Booth, J. L.; Zhu, Y.

2010-01-01

This study examined spatial and temporal variations in the surface moisture content of a fine-grained beach at Padre Island, Texas, USA. Surface moisture measurements were collected on a 27 × 24 m grid that extended from the dune toe to the upper foreshore. The grid was surveyed at 2 to 4 h intervals for two tidal cycles, generating 17 maps of the spatial distribution of surface moisture. Simultaneous measurements of air temperature and humidity, wind speed and direction, tidal elevation, and water table elevation were used to interpret observed changes in surface moisture. It was found that the spatial distribution of surface moisture was broadly characterized by a cross-shore gradient of high to low content moving landward from the swash zone. The distribution of surface moisture was conceptualized in terms of three zones: saturated (> 25%), intermediate or transitional (5-25%), and dry (< 5%). The position of the saturated zone corresponded to the uppermost swash zone and therefore shifted in accordance with tidal elevation. Moisture contents in the intermediate and dry zones were primarily related to variation in water table depth (which was in turn controlled by tidal elevation) and to a lesser extent by evaporation. Signals associated with atmospheric processes such as evaporation were muted by the minimal degree of variation in atmospheric parameters experienced during most of the study period, but were apparent for the last few hours. The observed spatial and temporal variations in moisture content correspond reasonably well with observations of key controlling processes, but more work is needed to fully characterize this process suite.

Geostatistical approach for management of soil nutrients with special emphasis on different forms of potassium considering their spatial variation in intensive cropping system of West Bengal, India.

PubMed

Chatterjee, Sourov; Santra, Priyabrata; Majumdar, Kaushik; Ghosh, Debjani; Das, Indranil; Sanyal, S K

2015-04-01

A large part of precision agriculture research in the developing countries is devoted towards precision nutrient management aspects. This has led to better economics and efficiency of nutrient use with off-farm advantages of environmental security. The keystone of precision nutrient management is analysis and interpretation of spatial variability of soils by establishing management zones. In this study, spatial variability of major soil nutrient contents was evaluated in the Ghoragacha village of North 24 Parganas district of West Bengal, India. Surface soil samples from 100 locations, covering different cropping systems of the village, was collected from 0 to 15 cm depth using 100×100 m grid system and analyzed in the laboratory to determine organic carbon (OC), available nitrogen (N), phosphorus (P), and potassium (K) contents of the soil as well as its water-soluble K (KWS), exchangeable K (KEX), and non-exchangeable forms of K (KNEX). Geostatistical analyses were performed to determine the spatial variation structure of each nutrient content within the village, followed by the generation of surface maps through kriging. Four commonly used semivariogram models, i.e., spherical, exponential, Gaussian, and linear models were fitted to each soil property, and the best one was used to prepare surface maps through krigging. Spherical model was found the best for available N and P contents, while linear and exponential model was the best for OC and available K, and for KWS and KNEK, Gausian model was the best. Surface maps of nutrient contents showed that N content (129-195 kg ha(-1)) was the most limiting factor throughout the village, while P status was generally very high ( 10-678 kg ha(-1)) in the soils of the present village. Among the different soil K fractions, KWS registered the maximum variability (CV 75%), while the remaining soil K fractions showed moderate to high variation. Interestingly, KNEX content also showed high variability, which essentially indicates reserve native K exploitation under intensive cultivation. These maps highlight the necessity of estimating the other soil K fractions as well for better understanding of soil K supplying capacity and K fertilization strategy rather than the current recommendations, based on the plant-available K alone. In conclusion, the present study revealed that the variability of nutrient distribution was a consequence of complex interactions between the cropping system, nutrient application rates, and the native soil characteristics, and such interactions could be utilized to develop the nutrient management strategies for intensive small-holder system.

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

USGS Publications Warehouse

Balk, Benjamin; Elder, Kelly

2000-01-01

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

Spatially patterned matrix elasticity directs stem cell fate

NASA Astrophysics Data System (ADS)

Yang, Chun; DelRio, Frank W.; Ma, Hao; Killaars, Anouk R.; Basta, Lena P.; Kyburz, Kyle A.; Anseth, Kristi S.

2016-08-01

There is a growing appreciation for the functional role of matrix mechanics in regulating stem cell self-renewal and differentiation processes. However, it is largely unknown how subcellular, spatial mechanical variations in the local extracellular environment mediate intracellular signal transduction and direct cell fate. Here, the effect of spatial distribution, magnitude, and organization of subcellular matrix mechanical properties on human mesenchymal stem cell (hMSCs) function was investigated. Exploiting a photodegradation reaction, a hydrogel cell culture substrate was fabricated with regions of spatially varied and distinct mechanical properties, which were subsequently mapped and quantified by atomic force microscopy (AFM). The variations in the underlying matrix mechanics were found to regulate cellular adhesion and transcriptional events. Highly spread, elongated morphologies and higher Yes-associated protein (YAP) activation were observed in hMSCs seeded on hydrogels with higher concentrations of stiff regions in a dose-dependent manner. However, when the spatial organization of the mechanically stiff regions was altered from a regular to randomized pattern, lower levels of YAP activation with smaller and more rounded cell morphologies were induced in hMSCs. We infer from these results that irregular, disorganized variations in matrix mechanics, compared with regular patterns, appear to disrupt actin organization, and lead to different cell fates; this was verified by observations of lower alkaline phosphatase (ALP) activity and higher expression of CD105, a stem cell marker, in hMSCs in random versus regular patterns of mechanical properties. Collectively, this material platform has allowed innovative experiments to elucidate a novel spatial mechanical dosing mechanism that correlates to both the magnitude and organization of spatial stiffness.

Global Mapping of Provisioning Ecosystem Services

NASA Astrophysics Data System (ADS)

Bingham, Lisa; Straatsma, Menno; Karssenberg, Derek

2016-04-01

Attributing monetary value to ecosystem services for decision-making has become more relevant as a basis for decision-making. There are a number of problematic aspects of the calculations, including consistency of economy represented (e.g., purchasing price, production price) and determining which ecosystem subservices to include in a valuation. While several authors have proposed methods for calculating ecosystem services and calculations are presented for global and regional studies, the calculations are mostly broken down into biomes and regions without showing spatially explicit results. The key to decision-making for governments is to be able to make spatial-based decisions because a large spatial variation may exist within a biome or region. Our objective was to compute the spatial distribution of global ecosystem services based on 89 subservices. Initially, only the provisioning ecosystem service category is presented. The provisioning ecosystem service category was calculated using 6 ecosystem services (food, water, raw materials, genetic resources, medical resources, and ornaments) divided into 41 subservices. Global data sets were obtained from a variety of governmental and research agencies for the year 2005 because this is the most data complete and recent year available. All data originated either in tabular or grid formats and were disaggregated to 10 km cell length grids. A lookup table with production values by subservice by country were disaggregated over the economic zone (either marine, land, or combination) based on the spatial existence of the subservice (e.g. forest cover, crop land, non-arable land). Values express the production price in international dollars per hectare. The ecosystem services and the ecosystem service category(ies) maps may be used to show spatial variation of a service within and between countries as well as to specifically show the values within specific regions (e.g. countries, continents), biomes (e.g. coastal, forest), or hazardous regions (e.g. landslides, flood plains, war zones). A preliminary example of the provisioning ecosystem service category illustrates the valuation of deltaic regions and a second example illustrates the valuation of the subservice category of food production prices in flood zones. Future work of this research will spatially represent the calculations of the remaining three ecosystem service categories (regulating, habitat, cultural) and investigate the propagation of uncertainty of the input data to ecosystem service maps.

Mapping Successional Stages in a Wet Tropical Forest Using Landsat ETM+ and Forest Inventory Data

NASA Technical Reports Server (NTRS)

Goncalves, Fabio G.; Yatskov, Mikhail; dos Santos, Joao Roberto; Treuhaft, Robert N.; Law, Beverly E.

2010-01-01

In this study, we test whether an existing classification technique based on the integration of Landsat ETM+ and forest inventory data enables detailed characterization of successional stages in a wet tropical forest site. The specific objectives were: (1) to map forest age classes across the La Selva Biological Station in Costa Rica; and (2) to quantify uncertainties in the proposed approach in relation to field data and existing vegetation maps. Although significant relationships between vegetation height entropy (a surrogate for forest age) and ETM+ data were detected, the classification scheme tested in this study was not suitable for characterizing spatial variation in age at La Selva, as evidenced by the error matrix and the low Kappa coefficient (12.9%). Factors affecting the performance of the classification at this particular study site include the smooth transition in vegetation structure between intermediate and advanced successional stages, and the low sensitivity of NDVI to variations in vertical structure at high biomass levels.

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-01-01

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

Mapping Submarine Groundwater Discharge - how to investigate spatial discharge variability on coastal and beach scales

NASA Astrophysics Data System (ADS)

Stieglitz, T. C.; Burnett, W. C.; Rapaglia, J.

2008-12-01

Submarine groundwater discharge (SGD) is now increasingly recognized as an important component in the water balance, water quality and ecology of the coastal zone. A multitude of methods are currently employed to study SGD, ranging from point flux measurements with seepage meters to methods integrating over various spatial and temporal scales such as hydrological models, geophysical techniques or surface water tracer approaches. From studies in a large variety of hydrogeological settings, researchers in this field have come to expect that SGD is rarely uniformly distributed. Here we discuss the application of: (a) the mapping of subsurface electrical conductivity in a discharge zone on a beach; and (b) the large-scale mapping of radon in coastal surface water to improving our understanding of SGD and its spatial variability. On a beach scale, as part of intercomparison studies of a UNESCO/IAEA working group, mapping of subsurface electrical conductivity in a beach face have elucidated the non-uniform distribution of SGD associated with rock fractures, volcanic settings and man-made structures (e.g., piers, jetties). Variations in direct point measurements of SGD flux with seepage meters were linked to the subsurface conductivity distribution. We demonstrate how the combination of these two techniques may complement one another to better constrain SGD measurements. On kilometer to hundred kilometer scales, the spatial distribution and regional importance of SGD can be investigated by mapping relevant tracers in the coastal ocean. The radon isotope Rn-222 is a commonly used tracer for SGD investigations due to its significant enrichment in groundwater, and continuous mapping of this tracer, in combination with ocean water salinity, can be used to efficiently infer locations of SGD along a coastline on large scales. We use a surface-towed, continuously recording multi-detector setup installed on a moving vessel. This tool was used in various coastal environments, e.g. in Florida, Brazil, Mauritius and Australia's Great Barrier Reef lagoon. From shore-parallel transects along the Central Great Barrier Reef coastline, numerous processes and locations of SGD were identified, including terrestrially-derived fresh SGD and the recirculation of seawater in mangrove forests, as well as riverine sources. From variations in the inverse relationship of the two tracers radon and salinity, some aspects of regional freshwater input into the lagoon during the tropical wet season could be assessed. Such surveys on coastal scales can be a useful tool to obtain an overview of locations and processes of SGD on an unknown coastline.

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

PubMed

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

2013-03-01

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

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

PubMed Central

2013-01-01

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

On the feasibility of real-time mapping of the geoelectric field across North America

USGS Publications Warehouse

Love, Jeffrey J.; Rigler, E. Joshua; Kelbert, Anna; Finn, Carol A.; Bedrosian, Paul A.; Balch, Christopher C.

2018-06-08

A review is given of the present feasibility for accurately mapping geoelectric fields across North America in near-realtime by modeling geomagnetic monitoring and magnetotelluric survey data. Should this capability be successfully developed, it could inform utility companies of magnetic-storm interference on electric-power-grid systems. That real-time mapping of geoelectric fields is a challenge is reflective of (1) the spatiotemporal complexity of geomagnetic variation, especially during magnetic storms, (2) the sparse distribution of ground-based geomagnetic monitoring stations that report data in realtime, (3) the spatial complexity of three-dimensional solid-Earth impedance, and (4) the geographically incomplete state of continental-scale magnetotelluric surveys.

Evaluation of the airborne visible-infrared imaging spectrometer for mapping subtle lithological variation

NASA Technical Reports Server (NTRS)

Kruse, Fred A.

1990-01-01

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), flown aboard the NASA ER-2 aircraft in 1987 and 1989, used four linear arrays and four individual spectrometers to collect data simultaneously from the 224 bands in a scanned 614 pixel-wide swath perpendicular to the aircraft direction. The research had two goals. One was to evaluate the AVIRIS data. The other was to look at the subtle lithological variation at the two test sites to develop a better understanding of the regional geology and surficial processes. The geometric characteristics of the data, adequacy of the spatial resolution, and adequacy of the spectral sampling interval are evaluated. Geologic differences at the test sites were mapped. They included lithological variation caused by primary sedimentary layering, facies variation, and weathering; and subtle mineralogical differences caused by hydrothermal alterations of igneous and sedimentary rocks. The investigation used laboratory, field, and aircraft spectral measurements; known properties of geological materials; digital image processing and spectrum processing techniques; and field geologic data to evaluate the selected characteristics of the AVIRIS data.

Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra - coupling field observations with remote sensing data

NASA Astrophysics Data System (ADS)

Mikola, Juha; Virtanen, Tarmo; Linkosalmi, Maiju; Vähä, Emmi; Nyman, Johanna; Postanogova, Olga; Räsänen, Aleksi; Kotze, D. Johan; Laurila, Tuomas; Juutinen, Sari; Kondratyev, Vladimir; Aurela, Mika

2018-05-01

Arctic tundra ecosystems will play a key role in future climate change due to intensifying permafrost thawing, plant growth and ecosystem carbon exchange, but monitoring these changes may be challenging due to the heterogeneity of Arctic landscapes. We examined spatial variation and linkages of soil and plant attributes in a site of Siberian Arctic tundra in Tiksi, northeast Russia, and evaluated possibilities to capture this variation by remote sensing for the benefit of carbon exchange measurements and landscape extrapolation. We distinguished nine land cover types (LCTs) and to characterize them, sampled 92 study plots for plant and soil attributes in 2014. Moreover, to test if variation in plant and soil attributes can be detected using remote sensing, we produced a normalized difference vegetation index (NDVI) and topographical parameters for each study plot using three very high spatial resolution multispectral satellite images. We found that soils ranged from mineral soils in bare soil and lichen tundra LCTs to soils of high percentage of organic matter (OM) in graminoid tundra, bog, dry fen and wet fen. OM content of the top soil was on average 14 g dm-3 in bare soil and lichen tundra and 89 g dm-3 in other LCTs. Total moss biomass varied from 0 to 820 g m-2, total vascular shoot mass from 7 to 112 g m-2 and vascular leaf area index (LAI) from 0.04 to 0.95 among LCTs. In late summer, soil temperatures at 15 cm depth were on average 14 °C in bare soil and lichen tundra, and varied from 5 to 9 °C in other LCTs. On average, depth of the biologically active, unfrozen soil layer doubled from early July to mid-August. When contrasted across study plots, moss biomass was positively associated with soil OM % and OM content and negatively associated with soil temperature, explaining 14-34 % of variation. Vascular shoot mass and LAI were also positively associated with soil OM content, and LAI with active layer depth, but only explained 6-15 % of variation. NDVI captured variation in vascular LAI better than in moss biomass, but while this difference was significant with late season NDVI, it was minimal with early season NDVI. For this reason, soil attributes associated with moss mass were better captured by early season NDVI. Topographic attributes were related to LAI and many soil attributes, but not to moss biomass and could not increase the amount of spatial variation explained in plant and soil attributes above that achieved by NDVI. The LCT map we produced had low to moderate uncertainty in predictions for plant and soil properties except for moss biomass and bare soil and lichen tundra LCTs. Our results illustrate a typical tundra ecosystem with great fine-scale spatial variation in both plant and soil attributes. Mosses dominate plant biomass and control many soil attributes, including OM % and temperature, but variation in moss biomass is difficult to capture by remote sensing reflectance, topography or a LCT map. Despite the general accuracy of landscape level predictions in our LCT approach, this indicates challenges in the spatial extrapolation of some of those vegetation and soil attributes that are relevant for the regional ecosystem and global climate models.

Sound pressure distribution and power flow within the gerbil ear canal from 100 Hz to 80 kHz

PubMed Central

Ravicz, Michael E.; Olson, Elizabeth S.; Rosowski, John J.

2008-01-01

Sound pressure was mapped in the bony ear canal of gerbils during closed-field sound stimulation at frequencies from 0.1 to 80 kHz. A 1.27-mm-diam probe-tube microphone or a 0.17-mm-diam fiber-optic miniature microphone was positioned along approximately longitudinal trajectories within the 2.3-mm-diam ear canal. Substantial spatial variations in sound pressure, sharp minima in magnitude, and half-cycle phase changes occurred at frequencies >30 kHz. The sound frequencies of these transitions increased with decreasing distance from the tympanic membrane (TM). Sound pressure measured orthogonally across the surface of the TM showed only small variations at frequencies below 60 kHz. Hence, the ear canal sound field can be described fairly well as a one-dimensional standing wave pattern. Ear-canal power reflectance estimated from longitudinal spatial variations was roughly constant at 0.2–0.5 at frequencies between 30 and 45 kHz. In contrast, reflectance increased at higher frequencies to at least 0.8 above 60 kHz. Sound pressure was also mapped in a microphone-terminated uniform tube—an “artificial ear.” Comparison with ear canal sound fields suggests that an artificial ear or “artificial cavity calibration” technique may underestimate the in situ sound pressure by 5–15 dB between 40 and 60 kHz. PMID:17902852

Comparison of grain to grain orientation and stiffness mapping by spatially resolved acoustic spectroscopy and EBSD.

PubMed

Mark, A F; Li, W; Sharples, S; Withers, P J

2017-07-01

Our aim was to establish the capability of spatially resolved acoustic spectroscopy (SRAS) to map grain orientations and the anisotropy in stiffness at the sub-mm to micron scale by comparing the method with electron backscatter diffraction (EBSD) undertaken within a scanning electron microscope. In the former the grain orientations are deduced by measuring the spatial variation in elastic modulus; conversely, in EBSD the elastic anisotropy is deduced from direct measurements of the crystal orientations. The two test-cases comprise mapping the fusion zones for large TIG and MMA welds in thick power plant austenitic and ferritic steels, respectively; these are technologically important because, among other things, elastic anisotropy can cause ultrasonic weld inspection methods to become inaccurate because it causes bending in the paths of sound waves. The spatial resolution of SRAS is not as good as that for EBSD (∼100 μm vs. ∼a few nm), nor is the angular resolution (∼1.5° vs. ∼0.5°). However the method can be applied to much larger areas (currently on the order of 300 mm square), is much faster (∼5 times), is cheaper and easier to perform, and it could be undertaken on the manufacturing floor. Given these advantages, particularly to industrial users, and the on-going improvements to the method, SRAS has the potential to become a standard method for orientation mapping, particularly in cases where the elastic anisotropy is important over macroscopic/component length scales. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.

Remote sensing data with the conditional latin hypercube sampling and geostatistical approach to delineate landscape changes induced by large chronological physical disturbances.

PubMed

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.

Linear models of coregionalization for multivariate lattice data: Order-dependent and order-free cMCARs.

PubMed

MacNab, Ying C

2016-08-01

This paper concerns with multivariate conditional autoregressive models defined by linear combination of independent or correlated underlying spatial processes. Known as linear models of coregionalization, the method offers a systematic and unified approach for formulating multivariate extensions to a broad range of univariate conditional autoregressive models. The resulting multivariate spatial models represent classes of coregionalized multivariate conditional autoregressive models that enable flexible modelling of multivariate spatial interactions, yielding coregionalization models with symmetric or asymmetric cross-covariances of different spatial variation and smoothness. In the context of multivariate disease mapping, for example, they facilitate borrowing strength both over space and cross variables, allowing for more flexible multivariate spatial smoothing. Specifically, we present a broadened coregionalization framework to include order-dependent, order-free, and order-robust multivariate models; a new class of order-free coregionalized multivariate conditional autoregressives is introduced. We tackle computational challenges and present solutions that are integral for Bayesian analysis of these models. We also discuss two ways of computing deviance information criterion for comparison among competing hierarchical models with or without unidentifiable prior parameters. The models and related methodology are developed in the broad context of modelling multivariate data on spatial lattice and illustrated in the context of multivariate disease mapping. The coregionalization framework and related methods also present a general approach for building spatially structured cross-covariance functions for multivariate geostatistics. © The Author(s) 2016.

Imaging spectroscopy of Mars in the thermal infrared: seasonal variations of H2O2 and mapping of the D/H ratio

NASA Astrophysics Data System (ADS)

Encrenaz, Therese; DeWitt, Curtis; Richter, Matthew; Greathouse, Thomas; Fouchet, Thierry; Lefevre, Franck; Montmessin, Franck; Forget, Francois; Bezard, Bruno; Atreya, Sushil

2017-04-01

Since 2002, we have been monitoring the spatial distribution and the seasonal variations of H2O2 on Mars, using high-resolution imaging spectroscopy with the Texas Echelon Cross Echelle Spectrograph (TEXES) at the Infrared Telescope Facility (IRTF) at Maunakea Observatory (Hawaii). These observations have shown that a better agreement with global climate models is obtained when heterogeneous chemistry is introduced in the photochemical model (Encrenaz et al. 2015, AA 578, A127). In addition, in April 2014, we have obtained a map of D/H on Mars using the Echelon Cross Echelle Spectrograph (EXES) aboard the stratospheric Observatory for Infrared Astronomy (SOFIA; Encrenaz et al. 2015, AA 586, A62). In 2016, new observations have been obtained on H2O2 with TEXES and on D/H with EXES, allowing us to better analyze the seasonal variations of these parameters. These data will be presented and compared with previous measurements.

Geographic Variation in Mortality Among Children and Adolescents Diagnosed with Cancer in Tennessee: Does Race Matter?

PubMed Central

Lindley, Lisa C.; Oyana, Tonny J.

2017-01-01

Cancer is one of the leading causes of death among children in the United States. Previous research has examined geographic variation in cancer incidence and survival, but the geographic variation in mortality among children and adolescents is not as well understood. The purpose of this study was to investigate geographic variation by race in mortality among children and adolescents diagnosed with cancer in Tennessee. Using an innovative combination of spatial and non-spatial analysis techniques with data from the 2004–2011 Tennessee Cancer Registry, pediatric deaths were mapped and the affect of race on the proximity to rural areas and clusters of mortality were explored with multivariate regressions. The findings revealed that African American children and adolescents in Tennessee were more likely than their counterparts of other races to reside in rural areas with close proximity to mortality clusters of children and adolescents with a cancer. Findings have clinical implications for pediatric oncology nurses regarding the delivery of supportive care at end of life for rural African American children and adolescents. PMID:26458417

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

NASA Astrophysics Data System (ADS)

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

2015-08-01

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

A polar grid estimator of forest canopy structure metrics using airborne laser scanning data

Treesearch

Nicholas R. Vaughn; Greg P. Asner; Christian P. Giardina

2013-01-01

The structure of a forest canopy is the key determinant of light transmission, use and understory availability. Airborne light detection and ranging (LiDAR) has been used successfully to measure multiple canopy structural properties, thereby greatly reducing the fieldwork required to map spatial variation in structure. However, lidar metrics to date do not reflect the...

Integrative Spatial Data Analytics for Public Health Studies of New York State

PubMed Central

Chen, Xin; Wang, Fusheng

2016-01-01

Increased accessibility of health data made available by the government provides unique opportunity for spatial analytics with much higher resolution to discover patterns of diseases, and their correlation with spatial impact indicators. This paper demonstrated our vision of integrative spatial analytics for public health by linking the New York Cancer Mapping Dataset with datasets containing potential spatial impact indicators. We performed spatial based discovery of disease patterns and variations across New York State, and identify potential correlations between diseases and demographic, socio-economic and environmental indicators. Our methods were validated by three correlation studies: the correlation between stomach cancer and Asian race, the correlation between breast cancer and high education population, and the correlation between lung cancer and air toxics. Our work will allow public health researchers, government officials or other practitioners to adequately identify, analyze, and monitor health problems at the community or neighborhood level for New York State. PMID:28269834

A photometric function of planetary surfaces for gourmets

NASA Astrophysics Data System (ADS)

Shkuratov, Yuriy; Korokhin, Viktor; Shevchenko, Vasilij; Mikhalchenko, Olga; Belskaya, Irina; Kaydash, Vadym; Videen, Gorden; Zubko, Evgenij; Velikodsky, Yuriy

2018-03-01

A new photometric model with small number of parameters is presented. The model is based on an assumption that there exist such surfaces for which spatial brightness variations caused by small topography undulations can be reproduced exactly by corresponding spatial variations of albedo. This indistinguishability results in a differential equation suggesting a new photometric function that generalizes, in particular, the Akimov disk-function. Our model provides excellent fits in a wide phase-angle range for integral observations of asteroids of different albedos. We also carried out fitting to integral observations of the Moon and Mercury, confirming difficulties in describing Mercury's phase function at large phase angles, which were also found for the Hapke model. Comparisons of global latitude and longitude trends with our model calculations have shown good coincidence for the Moon. To retrieve the lunar trends, we use the phase-ratio technique, applying it to our telescope observations. Mapping the model parameters using LROC WAC data were carried out for a region comprising the Reiner Gamma formation. This mapping allows us to calculate phase-ratio images of the region, showing at large phase angles systematically steeper phase curves of young craters and smaller steepness for the very Reiner Gamma formation.

Statistical Maps of Ground Magnetic Disturbance Derived from Global Geospace Models

NASA Astrophysics Data System (ADS)

Rigler, E. J.; Wiltberger, M. J.; Love, J. J.

2017-12-01

Electric currents in space are the principal driver of magnetic variations measured at Earth's surface. These in turn induce geoelectric fields that present a natural hazard for technological systems like high-voltage power distribution networks. Modern global geospace models can reasonably simulate large-scale geomagnetic response to solar wind variations, but they are less successful at deterministic predictions of intense localized geomagnetic activity that most impacts technological systems on the ground. Still, recent studies have shown that these models can accurately reproduce the spatial statistical distributions of geomagnetic activity, suggesting that their physics are largely correct. Since the magnetosphere is a largely externally driven system, most model-measurement discrepancies probably arise from uncertain boundary conditions. So, with realistic distributions of solar wind parameters to establish its boundary conditions, we use the Lyon-Fedder-Mobarry (LFM) geospace model to build a synthetic multivariate statistical model of gridded ground magnetic disturbance. From this, we analyze the spatial modes of geomagnetic response, regress on available measurements to fill in unsampled locations on the grid, and estimate the global probability distribution of extreme magnetic disturbance. The latter offers a prototype geomagnetic "hazard map", similar to those used to characterize better-known geophysical hazards like earthquakes and floods.

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

PubMed

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

2017-11-01

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

Geographical Gradients in Argentinean Terrestrial Mammal Species Richness and Their Environmental Correlates

PubMed Central

Márquez, Ana L.; Real, Raimundo; Kin, Marta S.; Guerrero, José Carlos; Galván, Betina; Barbosa, A. Márcia; Olivero, Jesús; Palomo, L. Javier; Vargas, J. Mario; Justo, Enrique

2012-01-01

We analysed the main geographical trends of terrestrial mammal species richness (SR) in Argentina, assessing how broad-scale environmental variation (defined by climatic and topographic variables) and the spatial form of the country (defined by spatial filters based on spatial eigenvector mapping (SEVM)) influence the kinds and the numbers of mammal species along these geographical trends. We also evaluated if there are pure geographical trends not accounted for by the environmental or spatial factors. The environmental variables and spatial filters that simultaneously correlated with the geographical variables and SR were considered potential causes of the geographic trends. We performed partial correlations between SR and the geographical variables, maintaining the selected explanatory variables statistically constant, to determine if SR was fully explained by them or if a significant residual geographic pattern remained. All groups and subgroups presented a latitudinal gradient not attributable to the spatial form of the country. Most of these trends were not explained by climate. We used a variation partitioning procedure to quantify the pure geographic trend (PGT) that remained unaccounted for. The PGT was larger for latitudinal than for longitudinal gradients. This suggests that historical or purely geographical causes may also be relevant drivers of these geographical gradients in mammal diversity. PMID:23028254

Blind image fusion for hyperspectral imaging with the directional total variation

NASA Astrophysics Data System (ADS)

Bungert, Leon; Coomes, David A.; Ehrhardt, Matthias J.; Rasch, Jennifer; Reisenhofer, Rafael; Schönlieb, Carola-Bibiane

2018-04-01

Hyperspectral imaging is a cutting-edge type of remote sensing used for mapping vegetation properties, rock minerals and other materials. A major drawback of hyperspectral imaging devices is their intrinsic low spatial resolution. In this paper, we propose a method for increasing the spatial resolution of a hyperspectral image by fusing it with an image of higher spatial resolution that was obtained with a different imaging modality. This is accomplished by solving a variational problem in which the regularization functional is the directional total variation. To accommodate for possible mis-registrations between the two images, we consider a non-convex blind super-resolution problem where both a fused image and the corresponding convolution kernel are estimated. Using this approach, our model can realign the given images if needed. Our experimental results indicate that the non-convexity is negligible in practice and that reliable solutions can be computed using a variety of different optimization algorithms. Numerical results on real remote sensing data from plant sciences and urban monitoring show the potential of the proposed method and suggests that it is robust with respect to the regularization parameters, mis-registration and the shape of the kernel.

Greenland iceberg melt variability from high-resolution satellite observations

NASA Astrophysics Data System (ADS)

Enderlin, Ellyn M.; Carrigan, Caroline J.; Kochtitzky, William H.; Cuadros, Alexandra; Moon, Twila; Hamilton, Gordon S.

2018-02-01

Iceberg discharge from the Greenland Ice Sheet accounts for up to half of the freshwater flux to surrounding fjords and ocean basins, yet the spatial distribution of iceberg meltwater fluxes is poorly understood. One of the primary limitations for mapping iceberg meltwater fluxes, and changes over time, is the dearth of iceberg submarine melt rate estimates. Here we use a remote sensing approach to estimate submarine melt rates during 2011-2016 for 637 icebergs discharged from seven marine-terminating glaciers fringing the Greenland Ice Sheet. We find that spatial variations in iceberg melt rates generally follow expected patterns based on hydrographic observations, including a decrease in melt rate with latitude and an increase in melt rate with iceberg draft. However, we find no longitudinal variations in melt rates within individual fjords. We do not resolve coherent seasonal to interannual patterns in melt rates across all study sites, though we attribute a 4-fold melt rate increase from March to April 2011 near Jakobshavn Isbræ to fjord circulation changes induced by the seasonal onset of iceberg calving. Overall, our results suggest that remotely sensed iceberg melt rates can be used to characterize spatial and temporal variations in oceanic forcing near often inaccessible marine-terminating glaciers.

Radiofrequency Ablation, MR Thermometry, and High-Spatial-Resolution MR Parametric Imaging with a Single, Minimally Invasive Device.

PubMed

Ertürk, M Arcan; Sathyanarayana Hegde, Shashank; Bottomley, Paul A

2016-12-01

Purpose To develop and demonstrate in vitro and in vivo a single interventional magnetic resonance (MR)-active device that integrates the functions of precise identification of a tissue site with the delivery of radiofrequency (RF) energy for ablation, high-spatial-resolution thermal mapping to monitor thermal dose, and quantitative MR imaging relaxometry to document ablation-induced tissue changes for characterizing ablated tissue. Materials and Methods All animal studies were approved by the institutional animal care and use committee. A loopless MR imaging antenna composed of a tuned microcable either 0.8 or 2.2 mm in diameter with an extended central conductor was switched between a 3-T MR imaging unit and an RF power source to monitor and perform RF ablation in bovine muscle and human artery samples in vitro and in rabbits in vivo. High-spatial-resolution (250-300-μm) proton resonance frequency shift MR thermometry was interleaved with ablations. Quantitative spin-lattice (T1) and spin-spin (T2) relaxation time MR imaging mapping was performed before and after ablation. These maps were compared with findings from gross tissue examination of the region of ablated tissue after MR imaging. Results High-spatial-resolution MR imaging afforded temperature mapping in less than 8 seconds for monitoring ablation temperatures in excess of 85°C delivered by the same device. This produced irreversible thermal injury and necrosis. Quantitative MR imaging relaxation time maps demonstrated up to a twofold variation in mean regional T1 and T2 after ablation versus before ablation. Conclusion A simple, integrated, minimally invasive interventional probe that provides image-guided therapy delivery, thermal mapping of dose, and detection of ablation-associated MR imaging parametric changes was developed and demonstrated. With this single-device approach, coupling-related safety concerns associated with multiple conductor approaches were avoided. © RSNA, 2016 Online supplemental material is available for this article.

Hurricane Directional Wave Spectrum Spatial Variation in the Open Ocean

NASA Technical Reports Server (NTRS)

Wright, C. W.; Walsh, E. J.; Vandemark, D.; Krabill, W. B.; Garcia, A. W.

1999-01-01

The sea surface directional wave spectrum was measured for the first time in all quadrants of a hurricane in open water using the NASA airborne scanning radar altimeter (SRA) carried aboard one of the NOAA WP-3D hurricane hunter aircraft at 1.5 km height. The SRA measures the energetic portion of the directional wave spectrum by generating a topographic map of the sea surface. At 8 Hz, the SRA sweeps a radar beam of 1 deg half-power width (two-way) across the aircraft ground track over a swath equal to 0. 8 of the aircraft height, simultaneously measuring the backscattered power at its 36 GHz (8.3 mm) operating frequency and the range to the sea surface at 64 positions. These slant ranges are multiplied by the cosine of the incidence angles to determine the vertical distances from the aircraft to the sea surface. Subtracting these distances from the aircraft height produces the sea surface elevation map. The sea surface topography is interpolated to a uniform grid, transformed by a two-dimensional FFT, and Doppler corrected. The data presented were acquired on 24 August 1998 when hurricane Bonnie was east of the Bahamas and moving slowly to the north. Wave heights up to 18 m were observed and the spatial variation of the wave field was dramatic. The dominant waves generally propagated at significant angles to the downwind direction and at times there were wave fields traveling at right angles to each other. The NOAA aircraft spent over five hours within 180 km of the hurricane Bonnie eye, and made five eye penetrations. A 2-minute animation of the directional wave spectrum spatial variation over this period will be shown.

Stand-level variation in evapotranspiration in non-water-limited eucalypt forests

NASA Astrophysics Data System (ADS)

Benyon, Richard G.; Nolan, Rachael H.; Hawthorn, Sandra N. D.; Lane, Patrick N. J.

2017-08-01

To better understand water and energy cycles in forests over years to decades, measurements of spatial and long-term temporal variability in evapotranspiration (Ea) are needed. In mountainous terrain, plot-level measurements are important to achieving this. Forest inventory data including tree density and size measurements, often collected repeatedly over decades, sample the variability occurring within the geographic and topographic range of specific forest types. Using simple allometric relationships, tree stocking and size data can be used to estimate variables including sapwood area index (SAI), which may be strongly correlated with annual Ea. This study analysed plot-level variability in SAI and its relationship with overstorey and understorey transpiration, interception and evaporation over a 670 m elevation gradient, in non-water-limited, even-aged stands of Eucalyptus regnans F. Muell. to determine how well spatial variation in annual Ea from forests can be mapped using SAI. Over the 3 year study, mean sap velocity in five E. regnans stands was uncorrelated with overstorey sapwood area index (SAI) or elevation: annual transpiration was predicted well by SAI (R2 0.98). Overstorey and total annual interception were positively correlated with SAI (R2 0.90 and 0.75). Ea from the understorey was strongly correlated with vapour pressure deficit (VPD) and net radiation (Rn) measured just above the understorey, but relationships between understorey Ea and VPD and Rn differed between understorey types and understorey annual Ea was not correlated with SAI. Annual total Ea was also strongly correlated with SAI: the relationship being similar to two previous studies in the same region, despite differences in stand age and species. Thus, spatial variation in annual Ea can be reliably mapped using measurements of SAI.

Spatial variation of urban soil geochemistry in a roadside sports ground in Galway, Ireland.

PubMed

Dao, Ligang; Morrison, Liam; Zhang, Chaosheng

2010-02-01

Characterization of spatial variation of urban soil geochemistry especially heavy metal pollution is essential for a better understanding of pollution sources and potential risks. A total of 294 surface soil samples were collected from a roadside sports ground in Galway, Ireland, and were analysed by ICP-OES for 23 chemical elements (Al, Ca, Ce, Co, Cu, Fe, K, La, Li, Mg, Mn, Na, Ni, P, Pb, S, Sc, Sr, Th, Ti, V, Y and Zn). Strong variations in soil geochemistry were observed and most elements, with the exception of Cu, Pb, P, S and Zn, showed multi-modal features, indicating the existence of mixed populations which proved difficult to separate. To evaluate the pollution level of the study area, the pollution index (PI) values were calculated based on a comparison with the Dutch target and intervention values. None of the concentrations of metal pollutants exceeded their intervention values, indicating the absence of serious contaminated soil, and the ratios to target values were therefore employed to produce the hazard maps. The spatial distribution and hazard maps for Cu, Pb and Zn indicated relatively high levels of pollution along the southern roadside extending almost 30m into the sports ground, revealing the strong influence of pollution from local traffic. However, heavy metal pollution was alleviated along the eastern roadside of the study area by the presence of a belt of shrubs. Therefore, in order to prevent further contamination from traffic emissions, the planting of hedging or erection of low walls should be considered as shields against traffic pollution for roadside parks. The results in this study are useful for management practices in sports and parks in urban areas. Copyright 2009 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Hasyim, Fuad; Subagio, Habib; Darmawan, Mulyanto

2016-06-01

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

Evidence for azimuthal variations of the oxygen-abundance gradient tracing the spiral structure of the galaxy HCG 91c

NASA Astrophysics Data System (ADS)

Vogt, F. P. A.; Pérez, E.; Dopita, M. A.; Verdes-Montenegro, L.; Borthakur, S.

2017-05-01

Context. The distribution of elements in galaxies forms an important diagnostic tool to characterize these systems' formation and evolution. This tool is, however, complex to use in practice, as galaxies are subject to a range of simultaneous physical processes active from pc to kpc scales. This renders observations of the full optical extent of galaxies down to sub-kpc scales essential. Aims: Using the WiFeS integral field spectrograph, we previously detected abrupt and localized variations in the gas-phase oxygen abundance of the spiral galaxy HCG 91c. Here, we follow-up on these observations to map HCG 91c's disk out to 2 Re at a resolution of 600 pc, and characterize the non-radial variations of the gas-phase oxygen abundance in the system. Methods: We obtained deep MUSE observations of the target under 0.6 arcsec seeing conditions. We perform both a spaxel-based and aperture-based analysis of the data to map the spatial variations of 12 +log (O/H) across the disk of the galaxy. Results: We confirm the presence of rapid variations of the oxygen abundance across the entire extent of the galaxy previously detected with WiFeS, for all azimuths and radii. The variations can be separated in two categories: a) localized and associated with individual H II regions; and b) extended over kpc scales, and occurring at the boundaries of the spiral structures in the galaxy. Conclusions: Our MUSE observations suggest that the enrichment of the interstellar medium in HGC 91c has proceeded preferentially along spiral structures, and less efficiently across them. Our dataset highlights the importance of distinguishing individual star-forming regions down to scales of a few 100 pc when using integral field spectrographs to spatially resolve the distribution of oxygen abundances in a given system, and accurately characterize azimuthal variations and intrinsic scatter. The movie associated to Fig. 8 is available at http://www.aanda.org

Retrieval and Mapping of Soil Texture Based on Land Surface Diurnal Temperature Range Data from MODIS

PubMed Central

Wang, De-Cai; Zhang, Gan-Lin; Zhao, Ming-Song; Pan, Xian-Zhang; Zhao, Yu-Guo; Li, De-Cheng; Macmillan, Bob

2015-01-01

Numerous studies have investigated the direct retrieval of soil properties, including soil texture, using remotely sensed images. However, few have considered how soil properties influence dynamic changes in remote images or how soil processes affect the characteristics of the spectrum. This study investigated a new method for mapping regional soil texture based on the hypothesis that the rate of change of land surface temperature is related to soil texture, given the assumption of similar starting soil moisture conditions. The study area was a typical flat area in the Yangtze-Huai River Plain, East China. We used the widely available land surface temperature product of MODIS as the main data source. We analyzed the relationships between the content of different particle soil size fractions at the soil surface and land surface day temperature, night temperature and diurnal temperature range (DTR) during three selected time periods. These periods occurred after rainfalls and between the previous harvest and the subsequent autumn sowing in 2004, 2007 and 2008. Then, linear regression models were developed between the land surface DTR and sand (> 0.05 mm), clay (< 0.001 mm) and physical clay (< 0.01 mm) contents. The models for each day were used to estimate soil texture. The spatial distribution of soil texture from the studied area was mapped based on the model with the minimum RMSE. A validation dataset produced error estimates for the predicted maps of sand, clay and physical clay, expressed as RMSE of 10.69%, 4.57%, and 12.99%, respectively. The absolute error of the predictions is largely influenced by variations in land cover. Additionally, the maps produced by the models illustrate the natural spatial continuity of soil texture. This study demonstrates the potential for digitally mapping regional soil texture variations in flat areas using readily available MODIS data. PMID:26090852

Retrieval and Mapping of Soil Texture Based on Land Surface Diurnal Temperature Range Data from MODIS.

PubMed

Wang, De-Cai; Zhang, Gan-Lin; Zhao, Ming-Song; Pan, Xian-Zhang; Zhao, Yu-Guo; Li, De-Cheng; Macmillan, Bob

2015-01-01

Numerous studies have investigated the direct retrieval of soil properties, including soil texture, using remotely sensed images. However, few have considered how soil properties influence dynamic changes in remote images or how soil processes affect the characteristics of the spectrum. This study investigated a new method for mapping regional soil texture based on the hypothesis that the rate of change of land surface temperature is related to soil texture, given the assumption of similar starting soil moisture conditions. The study area was a typical flat area in the Yangtze-Huai River Plain, East China. We used the widely available land surface temperature product of MODIS as the main data source. We analyzed the relationships between the content of different particle soil size fractions at the soil surface and land surface day temperature, night temperature and diurnal temperature range (DTR) during three selected time periods. These periods occurred after rainfalls and between the previous harvest and the subsequent autumn sowing in 2004, 2007 and 2008. Then, linear regression models were developed between the land surface DTR and sand (> 0.05 mm), clay (< 0.001 mm) and physical clay (< 0.01 mm) contents. The models for each day were used to estimate soil texture. The spatial distribution of soil texture from the studied area was mapped based on the model with the minimum RMSE. A validation dataset produced error estimates for the predicted maps of sand, clay and physical clay, expressed as RMSE of 10.69%, 4.57%, and 12.99%, respectively. The absolute error of the predictions is largely influenced by variations in land cover. Additionally, the maps produced by the models illustrate the natural spatial continuity of soil texture. This study demonstrates the potential for digitally mapping regional soil texture variations in flat areas using readily available MODIS data.

Spatial and temporal patterns of chronic wasting disease: Fine-scale mapping of a wildlife epidemic in Wisconsin

USGS Publications Warehouse

Osnas, E.E.; Heisey, D.M.; Rolley, R.E.; Samuel, M.D.

2009-01-01

Emerging infectious diseases threaten wildlife populations and human health. Understanding the spatial distributions of these new diseases is important for disease management and policy makers; however, the data are complicated by heterogeneities across host classes, sampling variance, sampling biases, and the space-time epidemic process. Ignoring these issues can lead to false conclusions or obscure important patterns in the data, such as spatial variation in disease prevalence. Here, we applied hierarchical Bayesian disease mapping methods to account for risk factors and to estimate spatial and temporal patterns of infection by chronic wasting disease (CWD) in white-tailed deer (Odocoileus virginianus) of Wisconsin, USA. We found significant heterogeneities for infection due to age, sex, and spatial location. Infection probability increased with age for all young deer, increased with age faster for young males, and then declined for some older animals, as expected from disease-associated mortality and age-related changes in infection risk. We found that disease prevalence was clustered in a central location, as expected under a simple spatial epidemic process where disease prevalence should increase with time and expand spatially. However, we could not detect any consistent temporal or spatiotemporal trends in CWD prevalence. Estimates of the temporal trend indicated that prevalence may have decreased or increased with nearly equal posterior probability, and the model without temporal or spatiotemporal effects was nearly equivalent to models with these effects based on deviance information criteria. For maximum interpretability of the role of location as a disease risk factor, we used the technique of direct standardization for prevalence mapping, which we develop and describe. These mapping results allow disease management actions to be employed with reference to the estimated spatial distribution of the disease and to those host classes most at risk. Future wildlife epidemiology studies should employ hierarchical Bayesian methods to smooth estimated quantities across space and time, account for heterogeneities, and then report disease rates based on an appropriate standardization. ?? 2009 by the Ecological Society of America.

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

NASA Technical Reports Server (NTRS)

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

2017-01-01

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

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

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

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

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

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

DOE PAGES

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

2017-01-21

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

Spatial point analysis based on dengue surveys at household level in central Brazil

PubMed Central

Siqueira-Junior, João B; Maciel, Ivan J; Barcellos, Christovam; Souza, Wayner V; Carvalho, Marilia S; Nascimento, Nazareth E; Oliveira, Renato M; Morais-Neto, Otaliba; Martelli, Celina MT

2008-01-01

Background Dengue virus (DENV) affects nonimunne human populations in tropical and subtropical regions. In the Americas, dengue has drastically increased in the last two decades and Brazil is considered one of the most affected countries. The high frequency of asymptomatic infection makes difficult to estimate prevalence of infection using registered cases and to locate high risk intra-urban area at population level. The goal of this spatial point analysis was to identify potential high-risk intra-urban areas of dengue, using data collected at household level from surveys. Methods Two household surveys took place in the city of Goiania (~1.1 million population), Central Brazil in the year 2001 and 2002. First survey screened 1,586 asymptomatic individuals older than 5 years of age. Second survey 2,906 asymptomatic volunteers, same age-groups, were selected by multistage sampling (census tracts; blocks; households) using available digital maps. Sera from participants were tested by dengue virus-specific IgM/IgG by EIA. A Generalized Additive Model (GAM) was used to detect the spatial varying risk over the region. Initially without any fixed covariates, to depict the overall risk map, followed by a model including the main covariates and the year, where the resulting maps show the risk associated with living place, controlled for the individual risk factors. This method has the advantage to generate smoothed risk factors maps, adjusted by socio-demographic covariates. Results The prevalence of antibody against dengue infection was 37.3% (95%CI [35.5–39.1]) in the year 2002; 7.8% increase in one-year interval. The spatial variation in risk of dengue infection significantly changed when comparing 2001 with 2002, (ORadjusted = 1.35; p < 0.001), while controlling for potential confounders using GAM model. Also increasing age and low education levels were associated with dengue infection. Conclusion This study showed spatial heterogeneity in the risk areas of dengue when using a spatial multivariate approach in a short time interval. Data from household surveys pointed out that low prevalence areas in 2001 surveys shifted to high-risk area in consecutive year. This mapping of dengue risks should give insights for control interventions in urban areas. PMID:18937868

Spatial forecasting of disease risk and uncertainty

USGS Publications Warehouse

De Cola, L.

2002-01-01

Because maps typically represent the value of a single variable over 2-dimensional space, cartographers must simplify the display of multiscale complexity, temporal dynamics, and underlying uncertainty. A choropleth disease risk map based on data for polygonal regions might depict incidence (cases per 100,000 people) within each polygon for a year but ignore the uncertainty that results from finer-scale variation, generalization, misreporting, small numbers, and future unknowns. In response to such limitations, this paper reports on the bivariate mapping of data "quantity" and "quality" of Lyme disease forecasts for states of the United States. Historical state data for 1990-2000 are used in an autoregressive model to forecast 2001-2010 disease incidence and a probability index of confidence, each of which is then kriged to provide two spatial grids representing continuous values over the nation. A single bivariate map is produced from the combination of the incidence grid (using a blue-to-red hue spectrum), and a probabilistic confidence grid (used to control the saturation of the hue at each grid cell). The resultant maps are easily interpretable, and the approach may be applied to such problems as detecting unusual disease occurences, visualizing past and future incidence, and assembling a consistent regional disease atlas showing patterns of forecasted risks in light of probabilistic confidence.

Use of airborne hyperspectral imagery to map soil parameters in tilled agricultural fields

USGS Publications Warehouse

Hively, W. Dean; McCarty, Gregory W.; Reeves, James B.; Lang, Megan W.; Oesterling, Robert A.; Delwiche, Stephen R.

2011-01-01

Soil hyperspectral reflectance imagery was obtained for six tilled (soil) agricultural fields using an airborne imaging spectrometer (400–2450 nm, ~10 nm resolution, 2.5 m spatial resolution). Surface soil samples (n = 315) were analyzed for carbon content, particle size distribution, and 15 agronomically important elements (Mehlich-III extraction). When partial least squares (PLS) regression of imagery-derived reflectance spectra was used to predict analyte concentrations, 13 of the 19 analytes were predicted with R2 > 0.50, including carbon (0.65), aluminum (0.76), iron (0.75), and silt content (0.79). Comparison of 15 spectral math preprocessing treatments showed that a simple first derivative worked well for nearly all analytes. The resulting PLS factors were exported as a vector of coefficients and used to calculate predicted maps of soil properties for each field. Image smoothing with a 3 × 3 low-pass filter prior to spectral data extraction improved prediction accuracy. The resulting raster maps showed variation associated with topographic factors, indicating the effect of soil redistribution and moisture regime on in-field spatial variability. High-resolution maps of soil analyte concentrations can be used to improve precision environmental management of farmlands.

Digital modelling of landscape and soil in a mountainous region: A neuro-fuzzy approach

NASA Astrophysics Data System (ADS)

Viloria, Jesús A.; Viloria-Botello, Alvaro; Pineda, María Corina; Valera, Angel

2016-01-01

Research on genetic relationships between soil and landforms has largely improved soil mapping. Recent technological advances have created innovative methods for modelling the spatial soil variation from digital elevation models (DEMs) and remote sensors. This generates new opportunities for the application of geomorphology to soil mapping. This study applied a method based on artificial neural networks and fuzzy clustering to recognize digital classes of land surfaces in a mountainous area in north-central Venezuela. The spatial variation of the fuzzy memberships exposed the areas where each class predominates, while the class centres helped to recognize the topographic attributes and vegetation cover of each class. The obtained classes of terrain revealed the structure of the land surface, which showed regional differences in climate, vegetation, and topography and landscape stability. The land-surface classes were subdivided on the basis of the geological substratum to produce landscape classes that additionally considered the influence of soil parent material. These classes were used as a framework for soil sampling. A redundancy analysis confirmed that changes of landscape classes explained the variation in soil properties (p = 0.01), and a Kruskal-Wallis test showed significant differences (p = 0.01) in clay, hydraulic conductivity, soil organic carbon, base saturation, and exchangeable Ca and Mg between classes. Thus, the produced landscape classes correspond to three-dimensional bodies that differ in soil conditions. Some changes of land-surface classes coincide with abrupt boundaries in the landscape, such as ridges and thalwegs. However, as the model is continuous, it disclosed the remaining variation between those boundaries.

Aquarius and Remote Sensing of Sea Surface Salinity from Space

NASA Technical Reports Server (NTRS)

LeVine, David M.; Lagerloef, G. S. E.; Torrusio, S.

2012-01-01

Aquarius is an L-band radiometer and scatterometer instrument combination designed to map the salinity field at the surface of the ocean from space. The instrument is designed to provide global salinity maps on a monthly basis with a spatial resolution of 150 km and an accuracy of 0.2 psu. The science objective is to monitor the seasonal and interannual variation of the large scale features of the surface salinity field in the open ocean. This data will promote understanding of ocean circulation and its role in the global water cycle and climate.

Mars Thermal Inertia

NASA Technical Reports Server (NTRS)

2001-01-01

This image shows the global thermal inertia of the Martian surface as measured by the Thermal Emission Spectrometer (TES) instrument on the Mars Global Surveyor. The data were acquired during the first 5000 orbits of the MGS mapping mission. The pattern of inertia variations observed by TES agrees well with the thermal inertia maps made by the Viking Infrared Thermal Mapper experiment, but the TES data shown here are at significantly higher spatial resolution (15 km versus 60 km).

The TES instrument was built by Santa Barbara Remote Sensing and is operated by Philip R. Christensen, of Arizona State University, Tempe, AZ.

Associations between residence at birth and mental health disorders: a spatial analysis of retrospective cohort data.

PubMed

Hoffman, Kate; Aschengrau, Ann; Webster, Thomas F; Bartell, Scott M; Vieira, Verónica M

2015-07-21

Mental health disorders impact approximately one in four US adults. While their causes are likely multifactorial, prior research has linked the risk of certain mental health disorders to prenatal and early childhood environmental exposures, motivating a spatial analysis to determine whether risk varies by birth location. We investigated the spatial associations between residence at birth and odds of depression, bipolar disorder, and post-traumatic stress disorder (PTSD) in a retrospective cohort (Cape Cod, Massachusetts, 1969-1983) using generalized additive models to simultaneously smooth location and adjust for confounders. Birth location served as a surrogate for prenatal exposure to the combination of social and environmental factors related to the development of mental illness. We predicted crude and adjusted odds ratios (aOR) for each outcome across the study area. The results were mapped to identify areas of increased risk. We observed spatial variation in the crude odds ratios of depression that was still present even after accounting for spatial confounding due to geographic differences in the distribution of known risk factors (aOR range: 0.61-3.07, P = 0.03). Similar geographic patterns were seen for the crude odds of PTSD; however, these patterns were no longer present in the adjusted analysis (aOR range: 0.49-1.36, P = 0.79), with family history of mental illness most notably influencing the geographic patterns. Analyses of the odds of bipolar disorder did not show any meaningful spatial variation (aOR range: 0.58-1.17, P = 0.82). Spatial associations exist between residence at birth and odds of PTSD and depression, but much of this variation can be explained by the geographic distributions of available risk factors. However, these risk factors did not account for all the variation observed with depression, suggesting that other social and environmental factors within our study area need further investigation.

Fine-Scale Spatial Variability of Pedestrian-Level Particulate Matters in Compact Urban Commercial Districts in Hong Kong

PubMed Central

Ng, Edward

2017-01-01

Particulate matters (PM) at the pedestrian level significantly raises the health impacts in the compact urban environment of Hong Kong. A detailed investigation of the fine-scale spatial variation of pedestrian-level PM is necessary to assess the health risk to pedestrians in the outdoor environment. However, the collection of PM data is difficult in the compact urban environment of Hong Kong due to the limited amount of roadside monitoring stations and the complicated urban context. In this study, we measured the fine-scale spatial variability of the PM in three of the most representative commercial districts of Hong Kong using a backpack outdoor environmental measuring unit. Based on the measurement data, 13 types of geospatial interpolation methods were examined for the spatial mapping of PM2.5 and PM10 with a group of building geometrical covariates. Geostatistical modelling was adopted as the basis of spatial interpolation of the PM. The results show that the original cokriging with the exponential kernel function provides the best performance in the PM mapping. Using the fine-scale building geometrical features as covariates slightly improves the interpolation performance. The study results also imply that the fine-scale, localized pollution emission sources heavily influence pedestrian exposure to PM. PMID:28869527

Environmental risk of leptospirosis infections in the Netherlands: Spatial modelling of environmental risk factors of leptospirosis in the Netherlands.

PubMed

Rood, Ente J J; Goris, Marga G A; Pijnacker, Roan; Bakker, Mirjam I; Hartskeerl, Rudy A

2017-01-01

Leptospirosis is a globally emerging zoonotic disease, associated with various climatic, biotic and abiotic factors. Mapping and quantifying geographical variations in the occurrence of leptospirosis and the surrounding environment offer innovative methods to study disease transmission and to identify associations between the disease and the environment. This study aims to investigate geographic variations in leptospirosis incidence in the Netherlands and to identify associations with environmental factors driving the emergence of the disease. Individual case data derived over the period 1995-2012 in the Netherlands were geocoded and aggregated by municipality. Environmental covariate data were extracted for each municipality and stored in a spatial database. Spatial clusters were identified using kernel density estimations and quantified using local autocorrelation statistics. Associations between the incidence of leptospirosis and the local environment were determined using Simultaneous Autoregressive Models (SAR) explicitly modelling spatial dependence of the model residuals. Leptospirosis incidence rates were found to be spatially clustered, showing a marked spatial pattern. Fitting a spatial autoregressive model significantly improved model fit and revealed significant association between leptospirosis and the coverage of arable land, built up area, grassland and sabulous clay soils. The incidence of leptospirosis in the Netherlands could effectively be modelled using a combination of soil and land-use variables accounting for spatial dependence of incidence rates per municipality. The resulting spatially explicit risk predictions provide an important source of information which will benefit clinical awareness on potential leptospirosis infections in endemic areas.

Environmental risk of leptospirosis infections in the Netherlands: Spatial modelling of environmental risk factors of leptospirosis in the Netherlands

PubMed Central

Goris, Marga G. A.; Pijnacker, Roan; Bakker, Mirjam I.; Hartskeerl, Rudy A.

2017-01-01

Leptospirosis is a globally emerging zoonotic disease, associated with various climatic, biotic and abiotic factors. Mapping and quantifying geographical variations in the occurrence of leptospirosis and the surrounding environment offer innovative methods to study disease transmission and to identify associations between the disease and the environment. This study aims to investigate geographic variations in leptospirosis incidence in the Netherlands and to identify associations with environmental factors driving the emergence of the disease. Individual case data derived over the period 1995–2012 in the Netherlands were geocoded and aggregated by municipality. Environmental covariate data were extracted for each municipality and stored in a spatial database. Spatial clusters were identified using kernel density estimations and quantified using local autocorrelation statistics. Associations between the incidence of leptospirosis and the local environment were determined using Simultaneous Autoregressive Models (SAR) explicitly modelling spatial dependence of the model residuals. Leptospirosis incidence rates were found to be spatially clustered, showing a marked spatial pattern. Fitting a spatial autoregressive model significantly improved model fit and revealed significant association between leptospirosis and the coverage of arable land, built up area, grassland and sabulous clay soils. The incidence of leptospirosis in the Netherlands could effectively be modelled using a combination of soil and land-use variables accounting for spatial dependence of incidence rates per municipality. The resulting spatially explicit risk predictions provide an important source of information which will benefit clinical awareness on potential leptospirosis infections in endemic areas. PMID:29065186

Does Walkability Contribute to Geographic Variation in Psychosocial Distress? A Spatial Analysis of 91,142 Members of the 45 and Up Study in Sydney, Australia

PubMed Central

Morgan, Geoffrey G.; Jalaludin, Bin B.; Bauman, Adrian E.

2018-01-01

Walkability describes the capacity of the built environment to promote walking, and has been proposed as a potential focus for community-level mental health planning. We evaluated this possibility by examining the contribution of area-level walkability to variation in psychosocial distress in a population cohort at spatial scales comparable to those used for regional planning in Sydney, Australia. Data on psychosocial distress were analysed for 91,142 respondents to the 45 and Up Study baseline survey between January 2006 and April 2009. We fit conditional auto regression models at the postal area level to obtain smoothed “disease maps” for psychosocial distress, and assess its association with area-level walkability after adjusting for individual- and area-level factors. Prevalence of psychosocial distress was 7.8%; similar for low (7.9%), low-medium (7.9%), medium-high (8.0%), and high (7.4%) walkability areas; and decreased with reducing postal area socioeconomic disadvantage: 12.2% (most), 9.3%, 7.5%, 5.9%, and 4.7% (least). Unadjusted disease maps indicated strong geographic clustering of psychosocial distress with 99.0% of excess prevalence due to unobserved and spatially structured factors, which was reduced to 55.3% in fully adjusted maps. Spatial and unstructured variance decreased by 97.3% and 39.8% after adjusting for individual-level factors, and another 2.3% and 4.2% with the inclusions of area-level factors. Excess prevalence of psychosocial distress in postal areas was attenuated in adjusted models but remained spatially structured. Postal area prevalence of high psychosocial distress is geographically clustered in Sydney, but is unrelated to postal area walkability. Area-level socioeconomic disadvantage makes a small contribution to this spatial structure; however, community-level mental health planning will likely deliver greatest benefits by focusing on individual-level contributors to disease burden and inequality associated with psychosocial distress. PMID:29415461

Capability of Hyperspectral data in Spatial Variability Distribution of Chlorophyll and Water Stress in Rice Agriculture System

NASA Astrophysics Data System (ADS)

Moharana, S.; Dutta, S.

2016-12-01

Abstract : The mapping and analysis of spatial variability within the field is a challenging task. However, field variability of a single vegetation cover does not give satisfactory results mainly due to low spectral resolution and non-availability of remote sensing data. From the NASA Earth Observing-1 (EO-1) satellite data, spatial distribution of biophysical parameters like chlorophyll and relative water content in a rice agriculture system is carried out in the present study. Hyperion L1R product composed of 242 spectral bands with 30m spatial resolution was acquired for Assam, India. This high dimensional data is allowed for pre-processing to get an atmospherically corrected imagery. Moreover, ground based hyperspectral measurements are collected from experimental rice fields from the study site using hand held ASD spectroradiometer (350-1050 nm). Published indices specifically designed for chlorophyll (OASVI, mSR, and MTCI indices) and water content (WI and WBI indices) are selected based on stastical performance of the in-situ hyperspectral data. Index models are established for the respective biophysical parameters and observed that the aforementioned indices followed different linear and nonlinear relationships which are completely different from the published indices. By employing the presently developed relationships, spatial variation of total chlorophyll and water stress are mapped for a rice agriculture system from Hyperion imagery. The findings showed that, the variation of chlorophyll and water content ranged from 1.77-10.61mg/g and 40-90% respectively for the studied rice agriculture system. The spatial distribution of these parameters resulted from presently developed index models are well captured from Hyperion imagery and they have good agreement with observed field based chlorophyll (1.14-7.26 mg/g) and water content (60-95%) of paddy crop. This study can be useful in providing essential information to assess the paddy field heterogeneity in an agriculture system. Keywords: Paddy crop, vegetation index, hyperspectral data, chlorophyll, water content

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

USGS Publications Warehouse

Sleeter, Rachel; Gould, Michael

2007-01-01

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

High spatial resolution mapping of folds and fractures using Unmanned Aerial Vehicle (UAV) photogrammetry

NASA Astrophysics Data System (ADS)

Cruden, A. R.; Vollgger, S.

2016-12-01

The emerging capability of UAV photogrammetry combines a simple and cost-effective method to acquire digital aerial images with advanced computer vision algorithms that compute spatial datasets from a sequence of overlapping digital photographs from various viewpoints. Depending on flight altitude and camera setup, sub-centimeter spatial resolution orthophotographs and textured dense point clouds can be achieved. Orientation data can be collected for detailed structural analysis by digitally mapping such high-resolution spatial datasets in a fraction of time and with higher fidelity compared to traditional mapping techniques. Here we describe a photogrammetric workflow applied to a structural study of folds and fractures within alternating layers of sandstone and mudstone at a coastal outcrop in SE Australia. We surveyed this location using a downward looking digital camera mounted on commercially available multi-rotor UAV that autonomously followed waypoints at a set altitude and speed to ensure sufficient image overlap, minimum motion blur and an appropriate resolution. The use of surveyed ground control points allowed us to produce a geo-referenced 3D point cloud and an orthophotograph from hundreds of digital images at a spatial resolution < 10 mm per pixel, and cm-scale location accuracy. Orientation data of brittle and ductile structures were semi-automatically extracted from these high-resolution datasets using open-source software. This resulted in an extensive and statistically relevant orientation dataset that was used to 1) interpret the progressive development of folds and faults in the region, and 2) to generate a 3D structural model that underlines the complex internal structure of the outcrop and quantifies spatial variations in fold geometries. Overall, our work highlights how UAV photogrammetry can contribute to new insights in structural analysis.

Spatial distribution of soil organic carbon and total nitrogen based on GIS and geostatistics in a small watershed in a hilly area of northern China.

PubMed

Peng, Gao; Bing, Wang; Guangpo, Geng; Guangcan, Zhang

2013-01-01

The spatial variability of soil organic carbon (SOC) and total nitrogen (STN) levels is important in both global carbon-nitrogen cycle and climate change research. There has been little research on the spatial distribution of SOC and STN at the watershed scale based on geographic information systems (GIS) and geostatistics. Ninety-seven soil samples taken at depths of 0-20 cm were collected during October 2010 and 2011 from the Matiyu small watershed (4.2 km(2)) of a hilly area in Shandong Province, northern China. The impacts of different land use types, elevation, vegetation coverage and other factors on SOC and STN spatial distributions were examined using GIS and a geostatistical method, regression-kriging. The results show that the concentration variations of SOC and STN in the Matiyu small watershed were moderate variation based on the mean, median, minimum and maximum, and the coefficients of variation (CV). Residual values of SOC and STN had moderate spatial autocorrelations, and the Nugget/Sill were 0.2% and 0.1%, respectively. Distribution maps of regression-kriging revealed that both SOC and STN concentrations in the Matiyu watershed decreased from southeast to northwest. This result was similar to the watershed DEM trend and significantly correlated with land use type, elevation and aspect. SOC and STN predictions with the regression-kriging method were more accurate than those obtained using ordinary kriging. This research indicates that geostatistical characteristics of SOC and STN concentrations in the watershed were closely related to both land-use type and spatial topographic structure and that regression-kriging is suitable for investigating the spatial distributions of SOC and STN in the complex topography of the watershed.

Spatial Distribution of Soil Organic Carbon and Total Nitrogen Based on GIS and Geostatistics in a Small Watershed in a Hilly Area of Northern China

PubMed Central

Peng, Gao; Bing, Wang; Guangpo, Geng; Guangcan, Zhang

2013-01-01

The spatial variability of soil organic carbon (SOC) and total nitrogen (STN) levels is important in both global carbon-nitrogen cycle and climate change research. There has been little research on the spatial distribution of SOC and STN at the watershed scale based on geographic information systems (GIS) and geostatistics. Ninety-seven soil samples taken at depths of 0–20 cm were collected during October 2010 and 2011 from the Matiyu small watershed (4.2 km2) of a hilly area in Shandong Province, northern China. The impacts of different land use types, elevation, vegetation coverage and other factors on SOC and STN spatial distributions were examined using GIS and a geostatistical method, regression-kriging. The results show that the concentration variations of SOC and STN in the Matiyu small watershed were moderate variation based on the mean, median, minimum and maximum, and the coefficients of variation (CV). Residual values of SOC and STN had moderate spatial autocorrelations, and the Nugget/Sill were 0.2% and 0.1%, respectively. Distribution maps of regression-kriging revealed that both SOC and STN concentrations in the Matiyu watershed decreased from southeast to northwest. This result was similar to the watershed DEM trend and significantly correlated with land use type, elevation and aspect. SOC and STN predictions with the regression-kriging method were more accurate than those obtained using ordinary kriging. This research indicates that geostatistical characteristics of SOC and STN concentrations in the watershed were closely related to both land-use type and spatial topographic structure and that regression-kriging is suitable for investigating the spatial distributions of SOC and STN in the complex topography of the watershed. PMID:24391791

Spatial Factors Play a Major Role as Determinants of Endemic Ground Beetle Beta Diversity of Madeira Island Laurisilva

PubMed Central

Boieiro, Mário; Carvalho, José C.; Cardoso, Pedro; Aguiar, Carlos A. S.; Rego, Carla; de Faria e Silva, Israel; Amorim, Isabel R.; Pereira, Fernando; Azevedo, Eduardo B.; Borges, Paulo A. V.; Serrano, Artur R. M.

2013-01-01

The development in recent years of new beta diversity analytical approaches highlighted valuable information on the different processes structuring ecological communities. A crucial development for the understanding of beta diversity patterns was also its differentiation in two components: species turnover and richness differences. In this study, we evaluate beta diversity patterns of ground beetles from 26 sites in Madeira Island distributed throughout Laurisilva – a relict forest restricted to the Macaronesian archipelagos. We assess how the two components of ground beetle beta diversity (βrepl – species turnover and βrich - species richness differences) relate with differences in climate, geography, landscape composition matrix, woody plant species richness and soil characteristics and the relative importance of the effects of these variables at different spatial scales. We sampled 1025 specimens from 31 species, most of which are endemic to Madeira Island. A spatially explicit analysis was used to evaluate the contribution of pure environmental, pure spatial and environmental spatially structured effects on variation in ground beetle species richness and composition. Variation partitioning showed that 31.9% of species turnover (βrepl) and 40.7% of species richness variation (βrich) could be explained by the environmental and spatial variables. However, different environmental variables controlled the two types of beta diversity: βrepl was influenced by climate, disturbance and soil organic matter content whilst βrich was controlled by altitude and slope. Furthermore, spatial variables, represented through Moran’s eigenvector maps, played a significant role in explaining both βrepl and βrich, suggesting that both dispersal ability and Madeira Island complex orography are crucial for the understanding of beta diversity patterns in this group of beetles. PMID:23724065

Hydrologic feasibility of artificial forestation in the semi-arid Loess Plateau of China

NASA Astrophysics Data System (ADS)

Jin, T. T.; Fu, B. J.; Liu, G. H.; Wang, Z.

2011-08-01

Hydrologic viability, in terms of moisture availability, is fundamental to ecosystem sustainability in arid and semi-arid regions. In this study, we examine the spatial distribution and after-planting variations of soil moisture content (SMC) in black locust tree (Robinia pseudoacacia L.) plantings in the Loess Plateau of China at a regional scale. Thirty sites (5 to 45 yr old) were selected, spanning an area of 300 km by 190 km in the northern region of the Shaanxi Province. The SMC was measured to a depth of 100 cm at intervals of 10 cm. Geographical, topographic and vegetation information was recorded, and soil organic matter was evaluated. The results show that, at the regional scale, SMC spatial variability was most highly correlated with rainfall. The negative relationship between the SMC at a depth of 20-50 cm and the stand age was stronger than at other depths, although this relationship was not significant at a 5 % level. Watershed analysis shows that the after-planting SMC variation differed depending upon precipitation. The SMC of plantings in areas receiving sufficient precipitation (e.g., mean annual precipitation (MAP) of 617 mm) may increase with stand age due to improvements in soil water-holding capacity and water-retention abilities after planting. For areas experiencing water shortages (e.g., MAP = 509 mm), evapotranspiration may cause planting soils to dry within the first 20 yr of growth. It is expected that, as arid and semi-arid plantings age, evapotranspiration will decrease, and the soil profile may gradually recover. In extremely dry areas (e.g., MAP = 352 mm), the variation in after-planting SMC with stand age was found to be negligible. The MAP can be used as an index to divide the study area into different ecological regions. Afforestation may sequentially exert positive, negative and negligible effects on SMCs with a decrease in the MAP. Therefore, future restoration measures should correspond to the local climate conditions, and the MAP should be a major consideration for the Loess Plateau. Large-scale and long-term research on the effects of restoration projects on SMCs is needed to support more effective restoration policies. The interaction between afforestation and local environmental conditions, particularly water availability to plants, should be taken into account in afforestation campaigns in arid and semi-arid areas.

Temporal and spatial variations of Gutenberg-Richter parameter and fractal dimension in Western Anatolia, Turkey

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.

Auditory Spatial Attention Representations in the Human Cerebral Cortex

PubMed Central

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

2014-01-01

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

Route learning in Korsakoff's syndrome: Residual acquisition of spatial memory despite profound amnesia.

PubMed

Oudman, Erik; Van der Stigchel, Stefan; Nijboer, Tanja C W; Wijnia, Jan W; Seekles, Maaike L; Postma, Albert

2016-03-01

Korsakoff's syndrome (KS) is characterized by explicit amnesia, but relatively spared implicit memory. The aim of this study was to assess to what extent KS patients can acquire spatial information while performing a spatial navigation task. Furthermore, we examined whether residual spatial acquisition in KS was based on automatic or effortful coding processes. Therefore, 20 KS patients and 20 matched healthy controls performed six tasks on spatial navigation after they navigated through a residential area. Ten participants per group were instructed to pay close attention (intentional condition), while 10 received mock instructions (incidental condition). KS patients showed hampered performance on a majority of tasks, yet their performance was superior to chance level on a route time and distance estimation tasks, a map drawing task and a route walking task. Performance was relatively spared on the route distance estimation task, but there were large variations between participants. Acquisition in KS was automatic rather than effortful, since no significant differences were obtained between the intentional and incidental condition on any task, whereas for the healthy controls, the intention to learn was beneficial for the map drawing task and the route walking task. The results of this study suggest that KS patients are still able to acquire spatial information during navigation on multiple domains despite the presence of the explicit amnesia. Residual acquisition is most likely based on automatic coding processes. © 2014 The British Psychological Society.

Using Electromagnetic Induction Technique to Detect Hydropedological Dynamics: Principles and Applications

NASA Astrophysics Data System (ADS)

Zhu, Qing; Liao, Kaihua; Doolittle, James; Lin, Henry

2014-05-01

Hydropedological dynamics including soil moisture variation, subsurface flow, and spatial distributions of different soil properties are important parameters in ecological, environmental, hydrological, and agricultural modeling and applications. However, technical gap exists in mapping these dynamics at intermediate spatial scale (e.g., farm and catchment scales). At intermediate scales, in-situ monitoring provides detailed data, but is restricted in number and spatial coverage; while remote sensing provides more acceptable spatial coverage, but has comparatively low spatial resolution, limited observation depths, and is greatly influenced by the surface condition and climate. As a non-invasive, fast, and convenient geophysical tool, electromagnetic induction (EMI) measures soil apparent electrical conductivity (ECa) and has great potential to bridge this technical gap. In this presentation, principles of different EMI meters are briefly introduced. Then, case studies of using repeated EMI to detect spatial distributions of subsurface convergent flow, soil moisture dynamics, soil types and their transition zones, and different soil properties are presented. The suitability, effectiveness, and accuracy of EMI are evaluated for mapping different hydropedological dynamics. Lastly, contributions of different hydropedological and terrain properties on soil ECa are quantified under different wetness conditions, seasons, and land use types using Classification and Regression Tree model. Trend removal and residual analysis are then used for further mining of EMI survey data. Based on these analyses, proper EMI survey designs and data processing are proposed.

Intrapixel measurement techniques on large focal plane arrays for astronomical applications: a comparative study

NASA Astrophysics Data System (ADS)

Ketchazo, C.; Viale, T.; Boulade, O.; de la Barrière, F.; Dubreuil, D.; Mugnier, L.; Moreau, V.; Guérineau, N.; Mulet, P.; Druart, G.; Delisle, C.

2017-09-01

The intrapixel response is the signal detected by a single pixel illuminated by a Dirac distribution as a function of the position of this Dirac inside this pixel. It is also known as the pixel response function (PRF). This function measures the sensitivity variation at the subpixel scale and gives a spatial map of the sensitivity across a pixel.

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

PubMed Central

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

2016-01-01

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

Average variograms to guide soil sampling

NASA Astrophysics Data System (ADS)

Kerry, R.; Oliver, M. A.

2004-10-01

To manage land in a site-specific way for agriculture requires detailed maps of the variation in the soil properties of interest. To predict accurately for mapping, the interval at which the soil is sampled should relate to the scale of spatial variation. A variogram can be used to guide sampling in two ways. A sampling interval of less than half the range of spatial dependence can be used, or the variogram can be used with the kriging equations to determine an optimal sampling interval to achieve a given tolerable error. A variogram might not be available for the site, but if the variograms of several soil properties were available on a similar parent material and or particular topographic positions an average variogram could be calculated from these. Averages of the variogram ranges and standardized average variograms from four different parent materials in southern England were used to suggest suitable sampling intervals for future surveys in similar pedological settings based on half the variogram range. The standardized average variograms were also used to determine optimal sampling intervals using the kriging equations. Similar sampling intervals were suggested by each method and the maps of predictions based on data at different grid spacings were evaluated for the different parent materials. Variograms of loss on ignition (LOI) taken from the literature for other sites in southern England with similar parent materials had ranges close to the average for a given parent material showing the possible wider application of such averages to guide sampling.

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

PubMed

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

2016-01-01

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

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

USGS Publications Warehouse

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

2008-01-01

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

Improved Satellite-based Crop Yield Mapping by Spatially Explicit Parameterization of Crop Phenology

NASA Astrophysics Data System (ADS)

Jin, Z.; Azzari, G.; Lobell, D. B.

2016-12-01

Field-scale mapping of crop yields with satellite data often relies on the use of crop simulation models. However, these approaches can be hampered by inaccuracies in the simulation of crop phenology. Here we present and test an approach to use dense time series of Landsat 7 and 8 acquisitions data to calibrate various parameters related to crop phenology simulation, such as leaf number and leaf appearance rates. These parameters are then mapped across the Midwestern United States for maize and soybean, and for two different simulation models. We then implement our recently developed Scalable satellite-based Crop Yield Mapper (SCYM) with simulations reflecting the improved phenology parameterizations, and compare to prior estimates based on default phenology routines. Our preliminary results show that the proposed method can effectively alleviate the underestimation of early-season LAI by the default Agricultural Production Systems sIMulator (APSIM), and that spatially explicit parameterization for the phenology model substantially improves the SCYM performance in capturing the spatiotemporal variation in maize and soybean yield. The scheme presented in our study thus preserves the scalability of SCYM, while significantly reducing its uncertainty.

Near real-time monitoring and mapping of specific conductivity levels across Lake Texoma, USA

USGS Publications Warehouse

Atkinson, S.F.; Mabe, J.A.

2006-01-01

A submersible sonde equipped with a specific conductivity probe, linked with a global positioning satellite receiver was developed, deployed on a small boat, and used to map spatial and temporal variations in specific conductivity in a large reservoir. 7,695 sample points were recorded during 8 sampling trips. Specific conductivity ranged from 442 uS/cm to 3,378 uS/cm over the nine-month study. The data showed five statistically different zones in the reservoir: 2 different riverine zones, 2 different riverine transition zones, and a lacustrine zone (the main lake zone). These data were imported to a geographic information system where they were spatially interpolated to generate 8 maps showing specific conductivity levels across the entire surface of the lake. The highly dynamic nature of water quality, due to the widely differing nature of the rivers that flow into the reservoir and the effect of large inflows of fresh water during winter storms is easily captured and visualized using this approach. ?? Springer Science+Business Media, Inc. 2006.

Spatial and temporal heterogeneity of water soil erosion in a Mediterranean rain-fed crop

NASA Astrophysics Data System (ADS)

López-Vicente, M.; Quijano, L.; Gaspar, L.; Machín, J.; Navas, A.

2012-04-01

Fertile soil loss by raindrop impact and runoff processes in croplands presents significant variations at temporal and spatial scales. The combined use of advanced GIS techniques and detailed databases allows high resolution mapping of runoff and soil erosion processes. In this study the monthly values of soil loss are calculated in a medium size field of rain-fed winter barley and its drainage area located in the Central Spanish Pre-Pyrenees. The field is surrounded by narrow strips of dense Mediterranean vegetation (mainly holm oaks) and grass. Man-made infrastructures (paved trails and drainage ditches) modify the overland flow pathways and the study site appears hydrologically closed in its northern and western boundaries. This area has a continental Mediterranean climate with two humid periods, one in spring and a second in autumn and a dry summer with rainfall events of high intensity from July to October. The average annual rainfall is 495 mm and the average monthly rainfall intensity ranges from 1.1 mm / h in January to 7.4 mm / h in July. The predicted rates were obtained after running the RMMF model (Morgan, 2001) with the enhancements made to this model by Morgan and Duzant (2008) to the topographic module, and by López-Vicente and Navas (2010) to the hydrological module. A total of 613 soil samples were collected and all input and output maps were generated at high spatial resolution (1 x 1 m of cell size) with ArcMapTM 10.0. A map of effective cumulative runoff was calculated for each month of the year with a weighted multiple flow algorithm and four sub-catchments were distinguished within the field. The average soil erosion in the cultivated area is 1.32 Mg / ha yr and the corresponding map shows a high spatial variability (s.d. = 7.52 Mg / ha yr). The highest values of soil erosion appear in those areas where overland flow is concentrated and slope steepness is higher. The unpaved trail present the highest values of soil erosion with an average value of 72.23 Mg / ha yr, whereas the grass and forested areas have annual rates lower than 0.1 Mg / ha yr. The highest values of soil erosion appear in March, April, May, October and November showing a very good correlation with the depth of monthly rainfall (Pearson's r = 0.97) and a good correlation with the number of rainy days per month (Pearson's r = 0.76). However, no correlation was obtained with the values of monthly rainfall intensity. The availability of a detailed database of soil properties, weather values and a high resolution DEM allows mapping and calculating the spatial and temporal variations of the soil erosion processes within the cultivated area and the area surrounding the crop. Thus, the application of soil erosion models at high spatial and temporal resolution improves their predicting capability due to the complexity and large number of relevant interactions between the different sub-factors.

A spatial haplotype copying model with applications to genotype imputation.

PubMed

Yang, Wen-Yun; Hormozdiari, Farhad; Eskin, Eleazar; Pasaniuc, Bogdan

2015-05-01

Ever since its introduction, the haplotype copy model has proven to be one of the most successful approaches for modeling genetic variation in human populations, with applications ranging from ancestry inference to genotype phasing and imputation. Motivated by coalescent theory, this approach assumes that any chromosome (haplotype) can be modeled as a mosaic of segments copied from a set of chromosomes sampled from the same population. At the core of the model is the assumption that any chromosome from the sample is equally likely to contribute a priori to the copying process. Motivated by recent works that model genetic variation in a geographic continuum, we propose a new spatial-aware haplotype copy model that jointly models geography and the haplotype copying process. We extend hidden Markov models of haplotype diversity such that at any given location, haplotypes that are closest in the genetic-geographic continuum map are a priori more likely to contribute to the copying process than distant ones. Through simulations starting from the 1000 Genomes data, we show that our model achieves superior accuracy in genotype imputation over the standard spatial-unaware haplotype copy model. In addition, we show the utility of our model in selecting a small personalized reference panel for imputation that leads to both improved accuracy as well as to a lower computational runtime than the standard approach. Finally, we show our proposed model can be used to localize individuals on the genetic-geographical map on the basis of their genotype data.

Spatial relationships between above-ground biomass and bird species biodiversity in Palawan, Philippines.

PubMed

Singh, Minerva; Friess, Daniel A; Vilela, Bruno; Alban, Jose Don T De; Monzon, Angelica Kristina V; Veridiano, Rizza Karen A; Tumaneng, Roven D

2017-01-01

This study maps distribution and spatial congruence between Above-Ground Biomass (AGB) and species richness of IUCN listed conservation-dependent and endemic avian fauna in Palawan, Philippines. Grey Level Co-Occurrence Texture Matrices (GLCMs) extracted from Landsat and ALOS-PALSAR were used in conjunction with local field data to model and map local-scale field AGB using the Random Forest algorithm (r = 0.92 and RMSE = 31.33 Mg·ha-1). A support vector regression (SVR) model was used to identify the factors influencing variation in avian species richness at a 1km scale. AGB is one of the most important determinants of avian species richness for the study area. Topographic factors and anthropogenic factors such as distance from the roads were also found to strongly influence avian species richness. Hotspots of high AGB and high species richness concentration were mapped using hotspot analysis and the overlaps between areas of high AGB and avian species richness was calculated. Results show that the overlaps between areas of high AGB with high IUCN red listed avian species richness and endemic avian species richness were fairly limited at 13% and 8% at the 1-km scale. The overlap between 1) low AGB and low IUCN richness, and 2) low AGB and low endemic avian species richness was higher at 36% and 12% respectively. The enhanced capacity to spatially map the correlation between AGB and avian species richness distribution will further assist the conservation and protection of forest areas and threatened avian species.

Regional aeolian dynamics and sand mixing in the Gran Desierto - Evidence from Landsat Thematic Mapper images

NASA Technical Reports Server (NTRS)

Blount, Grady; Greeley, Ronald; Christensen, Phillip R.; Smith, Milton O.; Adams, John B.

1990-01-01

Mesoscale mapping of spatial variations in sand composition of the Gran Desierto (Sonora, Mexico) was carried out on multispectral Landsat TM images of this region, making it possible to examine the dynamic development of sand sheets and dunes. Compositions determined from remote imagery were found to agree well with samples from selected areas. The sand populations delineated were used to describe the sediment source areas, transport paths, and deposition sites. The image analysis revealed important compositional variations aver large areas that were not readily apparent in the field data.

Passive microwave remote sensing of soil moisture - Results from HAPEX, FIFE and MONSOON 90

NASA Technical Reports Server (NTRS)

Schmugge, T.; Jackson, T. J.; Kustas, W. P.; Wang, J. R.

1992-01-01

HAPEX (Hydrologic Atmospheric Pilot Experiment), FIFE (First ISLSCP Field Experiment) and MONSOON 90 which used an imaging microwave radiometer operating at a frequency of 1.42 GHz are reported. For FIFE and MONSOON 90, a wide range of moisture conditions were present and it was possible to observe the drydown of the soil following heavy rain and to map its spatial variation. The quantitative agreement of microwave observations and ground measurements was very good. In HAPEX there were no significant rains and conditions were generally rather dry, however, moisture variations due to irrigation were observed.

Passive microwave remote sensing of soil moisture: Results from HAPEX, FIFE, and MONSOON 90

NASA Technical Reports Server (NTRS)

Schmugge, Thomas; Jackson, T. J.; Wang, J. R.

1991-01-01

HAPEX (Hydrologic Atmospheric Pilot Experiment), FIFE (First ISLSCP Field Experiment) and MONSOON 90 which used an imaging microwave radiometer operating at a frequency of 1.42 GHz are reported. For FIFE and MONSOON 90, a wide range of moisture conditions were present and it was possible to observe the drydown of the soil following heavy rain and to map its spatial variation. The quantitive agreement of microwave observations and ground measurements was very good. In HAPEX there were no significant rains and conditions were generally rather dry, however, moisture variations due to irrigation were observed.

Time Resolved Digital PIV Measurements of Flow Field Cyclic Variation in an Optical IC Engine

NASA Astrophysics Data System (ADS)

Jarvis, S.; Justham, T.; Clarke, A.; Garner, C. P.; Hargrave, G. K.; Halliwell, N. A.

2006-07-01

Time resolved digital particle image velocimetry (DPIV) experimental data is presented for the in-cylinder flow field development of a motored four stroke spark ignition (SI) optical internal combustion (IC) engine. A high speed DPIV system was employed to quantify the velocity field development during the intake and compression stroke at an engine speed of 1500 rpm. The results map the spatial and temporal development of the in-cylinder flow field structure allowing comparison between traditional ensemble average and cycle average flow field structures. Conclusions are drawn with respect to engine flow field cyclic variations.

A class of parallel algorithms for computation of the manipulator inertia matrix

NASA Technical Reports Server (NTRS)

Fijany, Amir; Bejczy, Antal K.

1989-01-01

Parallel and parallel/pipeline algorithms for computation of the manipulator inertia matrix are presented. An algorithm based on composite rigid-body spatial inertia method, which provides better features for parallelization, is used for the computation of the inertia matrix. Two parallel algorithms are developed which achieve the time lower bound in computation. Also described is the mapping of these algorithms with topological variation on a two-dimensional processor array, with nearest-neighbor connection, and with cardinality variation on a linear processor array. An efficient parallel/pipeline algorithm for the linear array was also developed, but at significantly higher efficiency.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Exploring the spatio-temporal interrelation between groundwater and surface water by using the self-organizing maps

NASA Astrophysics Data System (ADS)

Chen, I.-Ting; Chang, Li-Chiu; Chang, Fi-John

2018-01-01

In this study, we propose a soft-computing methodology to visibly explore the spatio-temporal groundwater variations of the Kuoping River basin in southern Taiwan. The self-organizing map (SOM) is implemented to investigate the interactive mechanism between surface water and groundwater over the river basin based on large high-dimensional data sets coupled with their occurrence times. We find that extracting the occurrence time from each 30-day moving average data set in the clustered neurons of the SOM is a crucial step to learn the spatio-temporal interaction between surface water and groundwater. We design 2-D Topological Bubble Map to summarize all the groundwater values of four aquifers in a neuron, which can visibly explore the major features of the groundwater in the vertical direction. The constructed SOM topological maps nicely display that: (1) the groundwater movement, in general, extends from the eastern area to the western, where groundwater in the eastern area can be easily recharged from precipitation in wet seasons and discharged into streams during dry seasons due to the high permeability in this area; (2) the water movements in the four aquifers of the study area are quite different, and the seasonal variations of groundwater in the second and third aquifers are larger than those of the others; and (3) the spatial distribution and seasonal variations of groundwater and surface water are comprehensively linked together over the constructed maps to present groundwater characteristics and the interrelation between groundwater and surface water. The proposed modeling methodology not only can classify the large complex high-dimensional data sets into visible topological maps to effectively facilitate the quantitative status of regional groundwater resources but can also provide useful elaboration for future groundwater management.

Groundwater Quality: Analysis of Its Temporal and Spatial Variability in a Karst Aquifer.

PubMed

Pacheco Castro, Roger; Pacheco Ávila, Julia; Ye, Ming; Cabrera Sansores, Armando

2018-01-01

This study develops an approach based on hierarchical cluster analysis for investigating the spatial and temporal variation of water quality governing processes. The water quality data used in this study were collected in the karst aquifer of Yucatan, Mexico, the only source of drinking water for a population of nearly two million people. Hierarchical cluster analysis was applied to the quality data of all the sampling periods lumped together. This was motivated by the observation that, if water quality does not vary significantly in time, two samples from the same sampling site will belong to the same cluster. The resulting distribution maps of clusters and box-plots of the major chemical components reveal the spatial and temporal variability of groundwater quality. Principal component analysis was used to verify the results of cluster analysis and to derive the variables that explained most of the variation of the groundwater quality data. Results of this work increase the knowledge about how precipitation and human contamination impact groundwater quality in Yucatan. Spatial variability of groundwater quality in the study area is caused by: a) seawater intrusion and groundwater rich in sulfates at the west and in the coast, b) water rock interactions and the average annual precipitation at the middle and east zones respectively, and c) human contamination present in two localized zones. Changes in the amount and distribution of precipitation cause temporal variation by diluting groundwater in the aquifer. This approach allows to analyze the variation of groundwater quality controlling processes efficiently and simultaneously. © 2017, National Ground Water Association.

A Non-parametric Approach to Constrain the Transfer Function in Reverberation Mapping

NASA Astrophysics Data System (ADS)

Li, Yan-Rong; Wang, Jian-Min; Bai, Jin-Ming

2016-11-01

Broad emission lines of active galactic nuclei stem from a spatially extended region (broad-line region, BLR) that is composed of discrete clouds and photoionized by the central ionizing continuum. The temporal behaviors of these emission lines are blurred echoes of continuum variations (I.e., reverberation mapping, RM) and directly reflect the structures and kinematic information of BLRs through the so-called transfer function (also known as the velocity-delay map). Based on the previous works of Rybicki and Press and Zu et al., we develop an extended, non-parametric approach to determine the transfer function for RM data, in which the transfer function is expressed as a sum of a family of relatively displaced Gaussian response functions. Therefore, arbitrary shapes of transfer functions associated with complicated BLR geometry can be seamlessly included, enabling us to relax the presumption of a specified transfer function frequently adopted in previous studies and to let it be determined by observation data. We formulate our approach in a previously well-established framework that incorporates the statistical modeling of continuum variations as a damped random walk process and takes into account long-term secular variations which are irrelevant to RM signals. The application to RM data shows the fidelity of our approach.

Partitioning sources of variation in vertebrate species richness

USGS Publications Warehouse

Boone, R.B.; Krohn, W.B.

2000-01-01

Aim: To explore biogeographic patterns of terrestrial vertebrates in Maine, USA using techniques that would describe local and spatial correlations with the environment. Location: Maine, USA. Methods: We delineated the ranges within Maine (86,156 km2) of 275 species using literature and expert review. Ranges were combined into species richness maps, and compared to geomorphology, climate, and woody plant distributions. Methods were adapted that compared richness of all vertebrate classes to each environmental correlate, rather than assessing a single explanatory theory. We partitioned variation in species richness into components using tree and multiple linear regression. Methods were used that allowed for useful comparisons between tree and linear regression results. For both methods we partitioned variation into broad-scale (spatially autocorrelated) and fine-scale (spatially uncorrelated) explained and unexplained components. By partitioning variance, and using both tree and linear regression in analyses, we explored the degree of variation in species richness for each vertebrate group that Could be explained by the relative contribution of each environmental variable. Results: In tree regression, climate variation explained richness better (92% of mean deviance explained for all species) than woody plant variation (87%) and geomorphology (86%). Reptiles were highly correlated with environmental variation (93%), followed by mammals, amphibians, and birds (each with 84-82% deviance explained). In multiple linear regression, climate was most closely associated with total vertebrate richness (78%), followed by woody plants (67%) and geomorphology (56%). Again, reptiles were closely correlated with the environment (95%), followed by mammals (73%), amphibians (63%) and birds (57%). Main conclusions: Comparing variation explained using tree and multiple linear regression quantified the importance of nonlinear relationships and local interactions between species richness and environmental variation, identifying the importance of linear relationships between reptiles and the environment, and nonlinear relationships between birds and woody plants, for example. Conservation planners should capture climatic variation in broad-scale designs; temperatures may shift during climate change, but the underlying correlations between the environment and species richness will presumably remain.

The 3-D collagen structure of equine articular cartilage, characterized using variable-angle-of-incidence polarization-sensitive optical coherence tomography

NASA Astrophysics Data System (ADS)

Ugryumova, Nadya; Gangnus, Sergei V.; Matcher, Stephen J.

2005-08-01

Polarization-sensitive optical coherence tomography has been used to spatially map the birefringence of equine articular cartilage. Images obtained in the vicinity of visible osteoarthritic lesions display a characteristic disruption of the regular birefringence bands shown by normal cartilage. We also note that significant (e.g. ×2) variations in the apparent birefringence of samples taken from young (18 month) animals that otherwise appear visually homogeneous are found over spatial scales of a few millimeters. We suggest that whilst some of this variation may be due to changes in the intrinsic birefringence of the tissue, the 3-D orientation of the collagen fibers relative to the plane of the joint surface should also be taken into account. We propose a method based on multiple angles of illumination to determine the polar angle of the collagen fibers.

Spatial and layer-controlled variability in fracture networks

NASA Astrophysics Data System (ADS)

Procter, Andrew; Sanderson, David J.

2018-03-01

Topological sampling, based on 1) node counting and 2) circular sampling areas, is used to measure fracture intensity in surface exposures of a layered limestone/shale sequence in north Somerset, UK. This method provides similar levels of precision as more traditional line samples, but is about 10 times quicker and allows characterization of the network topology. Georeferencing of photographs of the sample sites allows later analysis of trace lengths and orientations, and identification of joint set development. ANOVA tests support a complex interaction of within-layer, between-layer and between-location variability in fracture intensity, with the different layers showing anomalous intensity at different locations. This variation is not simply due to bed thickness, nor can it be related to any obvious compositional or textural variation between the limestone beds. These results are used to assess approaches to the spatial mapping of fracture intensity.

Study on temporal and spatial variations of urban land use based on land change data

NASA Astrophysics Data System (ADS)

Jiang, Ping; Liu, Yanfang; Fan, Min; Zhang, Yang

2009-10-01

With the rapid development of urbanization, demands of urban land increase in succession, hence, to analyze temporal and spatial variations of urban land use becomes more and more important. In this paper, the principle of trend surface analysis and formula of urban land sprawl index ( ULSI) are expatiated at first, and then based on land change data of Jiayu county, the author fits quadratic trend surface by choosing urban land area as dependent variable and urbanization and GDP as independent variables from 1996 to 2006, draws isoline of trend surface and residual values; and then urban land sprawl indexes of towns are calculated on the basis of urban land area of 1996 and 2006 and distribution map of ULSI is plotted. After analyzing those results, we can conclude that there is consanguineous relationship between urban land area and urbanization, economic level etc.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Graffiti for science - erosion painting reveals spatially variable erosivity of sediment-laden flows

NASA Astrophysics Data System (ADS)

Beer, Alexander R.; Kirchner, James W.; Turowski, Jens M.

2016-12-01

Spatially distributed detection of bedrock erosion is a long-standing challenge. Here we show how the spatial distribution of surface erosion can be visualized and analysed by observing the erosion of paint from natural bedrock surfaces. If the paint is evenly applied, it creates a surface with relatively uniform erodibility, such that spatial variability in the erosion of the paint reflects variations in the erosivity of the flow and its entrained sediment. In a proof-of-concept study, this approach provided direct visual verification that sediment impacts were focused on upstream-facing surfaces in a natural bedrock gorge. Further, erosion painting demonstrated strong cross-stream variations in bedrock erosion, even in the relatively narrow (5 m wide) gorge that we studied. The left side of the gorge experienced high sediment throughput with abundant lateral erosion on the painted wall up to 80 cm above the bed, but the right side of the gorge only showed a narrow erosion band 15-40 cm above the bed, likely due to deposited sediment shielding the lower part of the wall. This erosion pattern therefore reveals spatial stream bed aggradation that occurs during flood events in this channel. The erosion painting method provides a simple technique for mapping sediment impact intensities and qualitatively observing spatially distributed erosion in bedrock stream reaches. It can potentially find wide application in both laboratory and field studies.

Mapping tsunami impacts on land cover and related ecosystem service supply in Phang Nga, Thailand

NASA Astrophysics Data System (ADS)

Kaiser, G.; Burkhard, B.; Römer, H.; Sangkaew, S.; Graterol, R.; Haitook, T.; Sterr, H.; Sakuna-Schwartz, D.

2013-12-01

The 2004 Indian Ocean tsunami caused damages to coastal ecosystems and thus affected the livelihoods of the coastal communities who depend on services provided by these ecosystems. The paper presents a case study on evaluating and mapping the spatial and temporal impacts of the tsunami on land use and land cover (LULC) and related ecosystem service supply in the Phang Nga province, Thailand. The method includes local stakeholder interviews, field investigations, remote-sensing techniques, and GIS. Results provide an ecosystem services matrix with capacity scores for 18 LULC classes and 17 ecosystem functions and services as well as pre-/post-tsunami and recovery maps indicating changes in the ecosystem service supply capacities in the study area. Local stakeholder interviews revealed that mangroves, casuarina forest, mixed beach forest, coral reefs, tidal inlets, as well as wetlands (peat swamp forest) have the highest capacity to supply ecosystem services, while e.g. plantations have a lower capacity. The remote-sensing based damage and recovery analysis showed a loss of the ecosystem service supply capacities in almost all LULC classes for most of the services due to the tsunami. A fast recovery of LULC and related ecosystem service supply capacities within one year could be observed for e.g. beaches, while mangroves or casuarina forest needed several years to recover. Applying multi-temporal mapping the spatial variations of recovery could be visualised. While some patches of coastal forest were fully recovered after 3 yr, other patches were still affected and thus had a reduced capacity to supply ecosystem services. The ecosystem services maps can be used to quantify ecological values and their spatial distribution in the framework of a tsunami risk assessment. Beyond that they are considered to be a useful tool for spatial analysis in coastal risk management in Phang Nga.

MAPPING SPATIAL THEMATIC ACCURACY WITH FUZZY SETS

EPA Science Inventory

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

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

USGS Publications Warehouse

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

2006-01-01

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

Magnetic map of the Irish Hills and surrounding areas, San Luis Obispo County, central California

USGS Publications Warehouse

Langenheim, V.E.; Watt, J.T.; Denton, K.M.

2012-01-01

A magnetic map of the Irish Hills and surrounding areas was created as part of a cooperative research and development agreement with the Pacific Gas and Electric Company and is intended to promote further understanding of the areal geology and structure by serving as a basis for geophysical interpretations and by supporting geological mapping, mineral and water resource investigations, and other topical studies. Local spatial variations in the Earth's magnetic field (evident as anomalies on magnetic maps) reflect the distribution of magnetic minerals, primarily magnetite, in the underlying rocks. In many cases the volume content of magnetic minerals can be related to rock type, and abrupt spatial changes in the amount of magnetic minerals can be related to either lithologic or structural boundaries. Magnetic susceptibility measurements from the area indicate that bodies of serpentinite and other mafic and ultramafic rocks tend to produce the most intense magnetic anomalies, but such generalizations must be applied with caution because some sedimentary units also can produce measurable magnetic anomalies. Remanent magnetization does not appear to be a significant source for magnetic anomalies because it is an order of magnitude less than the induced magnetization. The map is a mosaic of three separate surveys collected by (1) fixed-wing aircraft at a nominal height of 305 m, (2) by boat with the sensor at sea level, and (3) by helicopter. The helicopter survey was flown by New-Sense Geophysics in October 2009 along flight lines spaced 150-m apart and at a nominal terrain clearance of 50 to 100 m. Tie lines were flown 1,500-m apart. Data were adjusted for lag error and diurnal field variations. Further processing included microleveling using the tie lines and subtraction of the reference field defined by International Geomagnetic Reference Field (IGRF) 2005 extrapolated to August 1, 2008.

Refractive-index profiling of embedded microstructures in optical materials

NASA Astrophysics Data System (ADS)

Dave, Digant P.; Milner, Thomas E.

2002-04-01

We describe use of a phase-sensitive low-coherence reflectometer to measure spatial variation of refractive index in optical materials. The described interferometric technique is demonstrated to be a valuable tool to profile the refractive index of optical elements such as integrated waveguides and photowritten optical microstructures. As an example, a refractive-index profile is mapped of a microstructure written in a microscope glass slide with an ultrashort-pulse laser.

Using a Mach-Zehnder interferometer to deduce nitrogen density mapping

NASA Astrophysics Data System (ADS)

Boudaoud, F.; Lemerini, M.

2015-07-01

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

Application of Satellite SAR Imagery in Mapping the Active Layer of Arctic Permafrost

NASA Technical Reports Server (NTRS)

Zhang, Ting-Jun; Li, Shu-Sun

2003-01-01

The objective of this project is to map the spatial variation of the active layer over the arctic permafrost in terms of two parameters: (i) timing and duration of thaw period and (ii) differential frost heave and thaw settlement of the active layer. To achieve this goal, remote sensing, numerical modeling, and related field measurements are required. Tasks for the University of Colorado team are to: (i) determine the timing of snow disappearance in spring through changes in surface albedo (ii) simulate the freezing and thawing processes of the active layer and (iii) simulate the impact of snow cover on permafrost presence.

A Holistic Landscape Description Reveals That Landscape Configuration Changes More over Time than Composition: Implications for Landscape Ecology Studies

PubMed Central

Mimet, Anne; Pellissier, Vincent; Houet, Thomas; Julliard, Romain; Simon, Laurent

2016-01-01

Background Space-for-time substitution—that is, the assumption that spatial variations of a system can explain and predict the effect of temporal variations—is widely used in ecology. However, it is questionable whether it can validly be used to explain changes in biodiversity over time in response to land-cover changes. Hypothesis Here, we hypothesize that different temporal vs spatial trajectories of landscape composition and configuration may limit space-for-time substitution in landscape ecology. Land-cover conversion changes not just the surface areas given over to particular types of land cover, but also affects isolation, patch size and heterogeneity. This means that a small change in land cover over time may have only minor repercussions on landscape composition but potentially major consequences for landscape configuration. Methods Using land-cover maps of the Paris region for 1982 and 2003, we made a holistic description of the landscape disentangling landscape composition from configuration. After controlling for spatial variations, we analyzed and compared the amplitudes of changes in landscape composition and configuration over time. Results For comparable spatial variations, landscape configuration varied more than twice as much as composition over time. Temporal changes in composition and configuration were not always spatially matched. Significance The fact that landscape composition and configuration do not vary equally in space and time calls into question the use of space-for-time substitution in landscape ecology studies. The instability of landscapes over time appears to be attributable to configurational changes in the main. This may go some way to explaining why the landscape variables that account for changes over time in biodiversity are not the same ones that account for the spatial distribution of biodiversity. PMID:26959363

Spatial distribution and influence factors of interprovincial terrestrial physical geographical names in China

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.

Analyzing existing conventional soil information sources to be incorporated in thematic Spatial Data Infrastructures

NASA Astrophysics Data System (ADS)

Pascual-Aguilar, J. A.; Rubio, J. L.; Domínguez, J.; Andreu, V.

2012-04-01

New information technologies give the possibility of widespread dissemination of spatial information to different geographical scales from continental to local by means of Spatial Data Infrastructures. Also administrative awareness on the need for open access information services has allowed the citizens access to this spatial information through development of legal documents, such as the INSPIRE Directive of the European Union, adapted by national laws as in the case of Spain. The translation of the general criteria of generic Spatial Data Infrastructures (SDI) to thematic ones is a crucial point for the progress of these instruments as large tool for the dissemination of information. In such case, it must be added to the intrinsic criteria of digital information, such as the harmonization information and the disclosure of metadata, the own environmental information characteristics and the techniques employed in obtaining it. In the case of inventories and mapping of soils, existing information obtained by traditional means, prior to the digital technologies, is considered to be a source of valid information, as well as unique, for the development of thematic SDI. In this work, an evaluation of existing and accessible information that constitutes the basis for building a thematic SDI of soils in Spain is undertaken. This information framework has common features to other European Union states. From a set of more than 1,500 publications corresponding to the national territory of Spain, the study was carried out in those documents (94) found for five autonomous regions of northern Iberian Peninsula (Asturias, Cantabria, Basque Country, Navarra and La Rioja). The analysis was performed taking into account the criteria of soil mapping and inventories. The results obtained show a wide variation in almost all the criteria: geographic representation (projections, scales) and geo-referencing the location of the profiles, map location of profiles integrated with edaphic units, description and taxonomic classification systems of soils (FAO, Soil taxonomy, etc.), amount and type of soil analysis parameters and dates of the inventories. In conclusion, the construction of thematic SDI on soil should take into account, prior to the integration of all maps and inventories, a series of processes of harmonization that allows spatial continuity between existing information and also temporal identification of the inventories and maps. This should require the development of at least two types of integration tools: (1) enabling spatial continuity without contradictions between maps made at different times and with different criteria and (2) the development of information systems data (metadata) to highlight the characteristics of information and connection possibilities with other sources that comprise the Spatial Data Infrastructure. Acknowledgements This research has financed by the European Union within the framework of the GS Soil project (eContentplus Programme ECP-2008-GEO-318004).

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Automation method to identify the geological structure of seabed using spatial statistic analysis of echo sounding data

NASA Astrophysics Data System (ADS)

Kwon, O.; Kim, W.; Kim, J.

2017-12-01

Recently construction of subsea tunnel has been increased globally. For safe construction of subsea tunnel, identifying the geological structure including fault at design and construction stage is more than important. Then unlike the tunnel in land, it's very difficult to obtain the data on geological structure because of the limit in geological survey. This study is intended to challenge such difficulties in a way of developing the technology to identify the geological structure of seabed automatically by using echo sounding data. When investigation a potential site for a deep subsea tunnel, there is the technical and economical limit with borehole of geophysical investigation. On the contrary, echo sounding data is easily obtainable while information reliability is higher comparing to above approaches. This study is aimed at developing the algorithm that identifies the large scale of geological structure of seabed using geostatic approach. This study is based on theory of structural geology that topographic features indicate geological structure. Basic concept of algorithm is outlined as follows; (1) convert the seabed topography to the grid data using echo sounding data, (2) apply the moving window in optimal size to the grid data, (3) estimate the spatial statistics of the grid data in the window area, (4) set the percentile standard of spatial statistics, (5) display the values satisfying the standard on the map, (6) visualize the geological structure on the map. The important elements in this study include optimal size of moving window, kinds of optimal spatial statistics and determination of optimal percentile standard. To determine such optimal elements, a numerous simulations were implemented. Eventually, user program based on R was developed using optimal analysis algorithm. The user program was designed to identify the variations of various spatial statistics. It leads to easy analysis of geological structure depending on variation of spatial statistics by arranging to easily designate the type of spatial statistics and percentile standard. This research was supported by the Korea Agency for Infrastructure Technology Advancement under the Ministry of Land, Infrastructure and Transport of the Korean government. (Project Number: 13 Construction Research T01)

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

PubMed

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

2016-09-01

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

Spatial Variation of Surface Wave Q and Body Wave t* in North America

NASA Astrophysics Data System (ADS)

Hwang, Y.; Ritsema, J.

2007-12-01

We estimate the spatial variation of the seismic parameter t* using teleseismic (30°--90°) P wave recordings of about 300 deep (> 200 km) earthquakes at broadband stations in North America. We determine the P wave spectral ratio Rij for about 600,000 station pairs i-j with high signal-to-noise ratio P wave signals. The linear fit to lnRij between f= 0.1--1.0 Hz is measured to estimate differential Δt* assuming that lnRij is proportional to π fΔt* (e.g., Aki and Richards, 1980). The measurements are inverted for t* at each station by least-squares inversion. Preliminary inversions indicate that the variation of t* correlate with the tectonic terrains of North America. Predominantly low values of t* are obtained for stations in the Canadian Shield and high t* values in the North American Cordillera. This variation is similar to Q variations inferred from global surface wave amplitude data (e.g., Dalton and Ekström, 2006), suggesting that intrinsic attenuation is the common cause. We will discuss the robustness of our t* estimates (including the effects of scattering on P wave ratios) and make a detailed comparison with surface wave Q maps.

The State-of-the-art HST Astro-photometric Analysis of the Core of ω Centauri. II. Differential-reddening Map

NASA Astrophysics Data System (ADS)

Bellini, A.; Anderson, J.; van der Marel, R. P.; King, I. R.; Piotto, G.; Bedin, L. R.

2017-06-01

We take advantage of the exquisite quality of the Hubble Space Telescope astro-photometric catalog of the core of ωCen presented in the first paper of this series to derive a high-resolution, high-precision, high-accuracy differential-reddening map of the field. The map has a spatial resolution of 2 × 2 arcsec2 over a total field of view of about 4.‧3 × 4.‧3. The differential reddening itself is estimated via an iterative procedure using five distinct color-magnitude diagrams, which provided consistent results to within the 0.1% level. Assuming an average reddening value E(B - V) = 0.12, the differential reddening within the cluster’s core can vary by up to ±10%, with a typical standard deviation of about 4%. Our differential-reddening map is made available to the astronomical community in the form of a multi-extension FITS file. This differential-reddening map is essential for a detailed understanding of the multiple stellar populations of ωCen, as presented in the next paper in this series. Moreover, it provides unique insight into the level of small spatial-scale extinction variations in the Galactic foreground. Based on archival observations with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by AURA, Inc., under NASA contract NAS 5-26555.

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

USGS Publications Warehouse

Langenheim, V.E.; Hill, P.L.

2010-01-01

This aeromagnetic map of Joshua Tree National Park and vicinity is intended to promote further understanding of the geology and structure in the region by serving as a basis for geophysical interpretations and by supporting geological mapping, water-resource investigations, and various topical studies. Local spatial variations in the Earth's magnetic field (evident as anomalies on aeromagnetic maps) reflect the distribution of magnetic minerals, primarily magnetite, in the underlying rocks. In many cases the volume content of magnetic minerals can be related to rock type, and abrupt spatial changes in the amount of magnetic minerals commonly mark lithologic or structural boundaries. Bodies of mafic and ultramafic rocks tend to produce the most intense magnetic anomalies, but such generalizations must be applied with caution because rocks with more felsic compositions, or even some sedimentary units, also can cause measurable magnetic anomalies. The database includes two ASCII files containing new aeromagnetic data and two ASCII files with point locations of the local maximum horizontal gradient derived from the aeromagnetic data. This metadata file describes the horizontal gradient locations derived from new and existing aeromagnetic data. This aeromagnetic map identifies magnetic features as a basis for geophysical interpretations; the gradients help define the edges of magnetic sources. This database updates geophysical information originally presented in smaller-scale formats and includes detailed aeromagnetic data collected by EON Geosciences, Inc.

4 Vesta in Color: High Resolution Mapping from Dawn Framing Camera Images

NASA Technical Reports Server (NTRS)

Reddy, V.; LeCorre, L.; Nathues, A.; Sierks, H.; Christensen, U.; Hoffmann, M.; Schroeder, S. E.; Vincent, J. B.; McSween, H. Y.; Denevi, B. W.;

Influence of land use on water quality in a tropical landscape: a multi-scale analysis

PubMed Central

Yackulic, Charles B.; Lim, Yili; Arce-Nazario, Javier A.

2015-01-01

There is a pressing need to understand the consequences of human activities, such as land transformations, on watershed ecosystem services. This is a challenging task because different indicators of water quality and yield are expected to vary in their responsiveness to large versus local-scale heterogeneity in land use and land cover (LUC). Here we rely on water quality data collected between 1977 and 2000 from dozens of gauge stations in Puerto Rico together with precipitation data and land cover maps to (1) quantify impacts of spatial heterogeneity in LUC on several water quality indicators; (2) determine the spatial scale at which this heterogeneity influences water quality; and (3) examine how antecedent precipitation modulates these impacts. Our models explained 30–58% of observed variance in water quality metrics. Temporal variation in antecedent precipitation and changes in LUC between measurements periods rather than spatial variation in LUC accounted for the majority of variation in water quality. Urbanization and pasture development generally degraded water quality while agriculture and secondary forest re-growth had mixed impacts. The spatial scale over which LUC influenced water quality differed across indicators. Turbidity and dissolved oxygen (DO) responded to LUC in large-scale watersheds, in-stream nitrogen concentrations to LUC in riparian buffers of large watersheds, and fecal matter content and in-stream phosphorus concentration to LUC at the sub-watershed scale. Stream discharge modulated impacts of LUC on water quality for most of the metrics. Our findings highlight the importance of considering multiple spatial scales for understanding the impacts of human activities on watershed ecosystem services. PMID:26146455

A spatially-variant deconvolution method based on total variation for optical coherence tomography images

NASA Astrophysics Data System (ADS)

Almasganj, Mohammad; Adabi, Saba; Fatemizadeh, Emad; Xu, Qiuyun; Sadeghi, Hamid; Daveluy, Steven; Nasiriavanaki, Mohammadreza

2017-03-01

Optical Coherence Tomography (OCT) has a great potential to elicit clinically useful information from tissues due to its high axial and transversal resolution. In practice, an OCT setup cannot reach to its theoretical resolution due to imperfections of its components, which make its images blurry. The blurriness is different alongside regions of image; thus, they cannot be modeled by a unique point spread function (PSF). In this paper, we investigate the use of solid phantoms to estimate the PSF of each sub-region of imaging system. We then utilize Lucy-Richardson, Hybr and total variation (TV) based iterative deconvolution methods for mitigating occurred spatially variant blurriness. It is shown that the TV based method will suppress the so-called speckle noise in OCT images better than the two other approaches. The performance of proposed algorithm is tested on various samples, including several skin tissues besides the test image blurred with synthetic PSF-map, demonstrating qualitatively and quantitatively the advantage of TV based deconvolution method using spatially-variant PSF for enhancing image quality.

Non-invasive imaging of the crystalline structure within a human tooth.

PubMed

Egan, Christopher K; Jacques, Simon D M; Di Michiel, Marco; Cai, Biao; Zandbergen, Mathijs W; Lee, Peter D; Beale, Andrew M; Cernik, Robert J

2013-09-01

The internal crystalline structure of a human molar tooth has been non-destructively imaged in cross-section using X-ray diffraction computed tomography. Diffraction signals from high-energy X-rays which have large attenuation lengths for hard biomaterials have been collected in a transmission geometry. Coupling this with a computed tomography data acquisition and mathematically reconstructing their spatial origins, diffraction patterns from every voxel within the tooth can be obtained. Using this method we have observed the spatial variations of some key material parameters including nanocrystallite size, organic content, lattice parameters, crystallographic preferred orientation and degree of orientation. We have also made a link between the spatial variations of the unit cell lattice parameters and the chemical make-up of the tooth. In addition, we have determined how the onset of tooth decay occurs through clear amorphization of the hydroxyapatite crystal, and we have been able to map the extent of decay within the tooth. The described method has strong prospects for non-destructive probing of mineralized biomaterials. Copyright © 2013 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Spatial prediction of Plasmodium falciparum prevalence in Somalia

PubMed Central

Noor, Abdisalan M; Clements, Archie CA; Gething, Peter W; Moloney, Grainne; Borle, Mohammed; Shewchuk, Tanya; Hay, Simon I; Snow, Robert W

2008-01-01

Background Maps of malaria distribution are vital for optimal allocation of resources for anti-malarial activities. There is a lack of reliable contemporary malaria maps in endemic countries in sub-Saharan Africa. This problem is particularly acute in low malaria transmission countries such as those located in the horn of Africa. Methods Data from a national malaria cluster sample survey in 2005 and routine cluster surveys in 2007 were assembled for Somalia. Rapid diagnostic tests were used to examine the presence of Plasmodium falciparum parasites in finger-prick blood samples obtained from individuals across all age-groups. Bayesian geostatistical models, with environmental and survey covariates, were used to predict continuous maps of malaria prevalence across Somalia and to define the uncertainty associated with the predictions. Results For analyses the country was divided into north and south. In the north, the month of survey, distance to water, precipitation and temperature had no significant association with P. falciparum prevalence when spatial correlation was taken into account. In contrast, all the covariates, except distance to water, were significantly associated with parasite prevalence in the south. The inclusion of covariates improved model fit for the south but not for the north. Model precision was highest in the south. The majority of the country had a predicted prevalence of < 5%; areas with ≥ 5% prevalence were predominantly in the south. Conclusion The maps showed that malaria transmission in Somalia varied from hypo- to meso-endemic. However, even after including the selected covariates in the model, there still remained a considerable amount of unexplained spatial variation in parasite prevalence, indicating effects of other factors not captured in the study. Nonetheless the maps presented here provide the best contemporary information on malaria prevalence in Somalia. PMID:18717998

Spatial prediction of Plasmodium falciparum prevalence in Somalia.

PubMed

Noor, Abdisalan M; Clements, Archie C A; Gething, Peter W; Moloney, Grainne; Borle, Mohammed; Shewchuk, Tanya; Hay, Simon I; Snow, Robert W

2008-08-21

Maps of malaria distribution are vital for optimal allocation of resources for anti-malarial activities. There is a lack of reliable contemporary malaria maps in endemic countries in sub-Saharan Africa. This problem is particularly acute in low malaria transmission countries such as those located in the horn of Africa. Data from a national malaria cluster sample survey in 2005 and routine cluster surveys in 2007 were assembled for Somalia. Rapid diagnostic tests were used to examine the presence of Plasmodium falciparum parasites in finger-prick blood samples obtained from individuals across all age-groups. Bayesian geostatistical models, with environmental and survey covariates, were used to predict continuous maps of malaria prevalence across Somalia and to define the uncertainty associated with the predictions. For analyses the country was divided into north and south. In the north, the month of survey, distance to water, precipitation and temperature had no significant association with P. falciparum prevalence when spatial correlation was taken into account. In contrast, all the covariates, except distance to water, were significantly associated with parasite prevalence in the south. The inclusion of covariates improved model fit for the south but not for the north. Model precision was highest in the south. The majority of the country had a predicted prevalence of < 5%; areas with > or = 5% prevalence were predominantly in the south. The maps showed that malaria transmission in Somalia varied from hypo- to meso-endemic. However, even after including the selected covariates in the model, there still remained a considerable amount of unexplained spatial variation in parasite prevalence, indicating effects of other factors not captured in the study. Nonetheless the maps presented here provide the best contemporary information on malaria prevalence in Somalia.

Impacts of Landscape Context on Patterns of Wind Downfall Damage in a Fragmented Amazonian Landscape

NASA Astrophysics Data System (ADS)

Schwartz, N.; Uriarte, M.; DeFries, R. S.; Gutierrez-Velez, V. H.; Fernandes, K.; Pinedo-Vasquez, M.

2015-12-01

Wind is a major disturbance in the Amazon and has both short-term impacts and lasting legacies in tropical forests. Observed patterns of damage across landscapes result from differences in wind exposure and stand characteristics, such as tree stature, species traits, successional age, and fragmentation. Wind disturbance has important consequences for biomass dynamics in Amazonian forests, and understanding the spatial distribution and size of impacts is necessary to quantify the effects on carbon dynamics. In November 2013, a mesoscale convective system was observed over the study area in Ucayali, Peru, a highly human modified and fragmented forest landscape. We mapped downfall damage associated with the storm in order to ask: how does the severity of damage vary within forest patches, and across forest patches of different sizes and successional ages? We applied spectral mixture analysis to Landsat images from 2013 and 2014 to calculate the change in non-photosynthetic vegetation fraction after the storm, and combined it with C-band SAR data from the Sentinel-1 satellite to predict downfall damage measured in 30 field plots using random forest regression. We then applied this model to map damage in forests across the study area. Using a land cover classification developed in a previous study, we mapped secondary and mature forest, and compared the severity of damage in the two. We found that damage was on average higher in secondary forests, but patterns varied spatially. This study demonstrates the utility of using multiple sources of satellite data for mapping wind disturbance, and adds to our understanding of the sources of variation in wind-related damage. Ultimately, an improved ability to map wind impacts and a better understanding of their spatial patterns can contribute to better quantification of carbon dynamics in Amazonian landscapes.

The change in spatial distribution of upper trapezius muscle activity is correlated to contraction duration.

PubMed

Farina, Dario; Leclerc, Frédéric; Arendt-Nielsen, Lars; Buttelli, Olivier; Madeleine, Pascal

2008-02-01

The aim of the study was to confirm the hypothesis that the longer a contraction is sustained, the larger are the changes in the spatial distribution of muscle activity. For this purpose, surface electromyographic (EMG) signals were recorded with a 13 x 5 grid of electrodes from the upper trapezius muscle of 11 healthy male subjects during static contractions with shoulders 90 degrees abducted until endurance. The entropy (degree of uniformity) and center of gravity of the EMG root mean square map were computed to assess spatial inhomogeneity in muscle activation and changes over time in EMG amplitude spatial distribution. At the endurance time, entropy decreased (mean+/-SD, percent change 2.0+/-1.6%; P<0.0001) and the center of gravity moved in the cranial direction (shift 11.2+/-6.1mm; P<0.0001) with respect to the beginning of the contraction. The shift in the center of gravity was positively correlated with endurance time (R(2)=0.46, P<0.05), thus subjects with larger shift in the activity map showed longer endurance time. The percent variation in average (over the grid) root mean square was positively correlated with the shift in the center of gravity (R(2)=0.51, P<0.05). Moreover, the shift in the center of gravity was negatively correlated to both initial and final (at the endurance) entropy (R(2)=0.54 and R(2)=0.56, respectively; P<0.01 in both cases), indicating that subjects with less uniform root mean square maps had larger shift of the center of gravity over time. The spatial changes in root mean square EMG were likely due to spatially-dependent changes in motor unit activation during the sustained contraction. It was concluded that the changes in spatial muscle activity distribution play a role in the ability to maintain a static contraction.

Residual stress characterization of steel TIG welds by neutron diffraction and by residual magnetic stray field mappings

NASA Astrophysics Data System (ADS)

Stegemann, Robert; Cabeza, Sandra; Lyamkin, Viktor; Bruno, Giovanni; Pittner, Andreas; Wimpory, Robert; Boin, Mirko; Kreutzbruck, Marc

2017-03-01

The residual stress distribution of tungsten inert gas welded S235JRC+C plates was determined by means of neutron diffraction (ND). Large longitudinal residual stresses with maxima around 600 MPa were found. With these results as reference, the evaluation of residual stress with high spatial resolution GMR (giant magneto resistance) sensors was discussed. The experiments performed indicate a correlation between changes in residual stresses (ND) and the normal component of local residual magnetic stray fields (GMR). Spatial variations in the magnetic field strength perpendicular to the welds are in the order of the magnetic field of the earth.

Spatial variability and landscape controls of near-surface permafrost within the Alaskan Yukon River Basin

USGS Publications Warehouse

Pastick, Neal J.; Jorgenson, M. Torre; Wylie, Bruce K.; Rose, Joshua R.; Rigge, Matthew; Walvoord, Michelle Ann

2014-01-01

The distribution of permafrost is important to understand because of permafrost's influence on high-latitude ecosystem structure and functions. Moreover, near-surface (defined here as within 1 m of the Earth's surface) permafrost is particularly susceptible to a warming climate and is generally poorly mapped at regional scales. Subsequently, our objectives were to (1) develop the first-known binary and probabilistic maps of near-surface permafrost distributions at a 30 m resolution in the Alaskan Yukon River Basin by employing decision tree models, field measurements, and remotely sensed and mapped biophysical data; (2) evaluate the relative contribution of 39 biophysical variables used in the models; and (3) assess the landscape-scale factors controlling spatial variations in permafrost extent. Areas estimated to be present and absent of near-surface permafrost occupy approximately 46% and 45% of the Alaskan Yukon River Basin, respectively; masked areas (e.g., water and developed) account for the remaining 9% of the landscape. Strong predictors of near-surface permafrost include climatic indices, land cover, topography, and Landsat 7 Enhanced Thematic Mapper Plus spectral information. Our quantitative modeling approach enabled us to generate regional near-surface permafrost maps and provide essential information for resource managers and modelers to better understand near-surface permafrost distribution and how it relates to environmental factors and conditions.

Mapping Electrical Crosstalk in Pixelated Sensor Arrays

NASA Technical Reports Server (NTRS)

Seshadri, S.; Cole, D. M.; Hancock, B. R.; Smith, R. M.

2008-01-01

Electronic coupling effects such as Inter-Pixel Capacitance (IPC) affect the quantitative interpretation of image data from CMOS, hybrid visible and infrared imagers alike. Existing methods of characterizing IPC do not provide a map of the spatial variation of IPC over all pixels. We demonstrate a deterministic method that provides a direct quantitative map of the crosstalk across an imager. The approach requires only the ability to reset single pixels to an arbitrary voltage, different from the rest of the imager. No illumination source is required. Mapping IPC independently for each pixel is also made practical by the greater S/N ratio achievable for an electrical stimulus than for an optical stimulus, which is subject to both Poisson statistics and diffusion effects of photo-generated charge. The data we present illustrates a more complex picture of IPC in Teledyne HgCdTe and HyViSi focal plane arrays than is presently understood, including the presence of a newly discovered, long range IPC in the HyViSi FPA that extends tens of pixels in distance, likely stemming from extended field effects in the fully depleted substrate. The sensitivity of the measurement approach has been shown to be good enough to distinguish spatial structure in IPC of the order of 0.1%.

High Spatial Resolution Europa Coverage by the Galileo Near Infrared Mapping Spectrometer (NIMS)

NASA Technical Reports Server (NTRS)

1997-01-01

The NIMS instrument on the Galileo spacecraft, which is being used to map the mineral and ice properties over the surfaces of the Jovian moons, produces global spectral images at modest spatial resolution and high resolution spectral images for small selected regions on the satellites. This map illustrates the high resolution coverage of Europa obtained by NIMS through the April 1997 G7 orbit.

The areas covered are displayed on a Voyager-derived map. A good sampling of the dark trailing-side material (180 to 360 degrees) has been obtained, with less coverage of Europa's leading side.

The false-color composites use red, green and blue to represent the infrared brightnesses at 0.7, 1.51 and 1.82 microns respectively. Considerable variations are evident and are related to the composition and sizes of the surface grains.

The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov.

Multiscale Reconstruction for Magnetic Resonance Fingerprinting

PubMed Central

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

2015-01-01

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

Modeling Photo-Bleaching Kinetics to Create High Resolution Maps of Rod Rhodopsin in the Human Retina

PubMed Central

Ehler, Martin; Dobrosotskaya, Julia; Cunningham, Denise; Wong, Wai T.; Chew, Emily Y.; Czaja, Wojtek; Bonner, Robert F.

2015-01-01

We introduce and describe a novel non-invasive in-vivo method for mapping local rod rhodopsin distribution in the human retina over a 30-degree field. Our approach is based on analyzing the brightening of detected lipofuscin autofluorescence within small pixel clusters in registered imaging sequences taken with a commercial 488nm confocal scanning laser ophthalmoscope (cSLO) over a 1 minute period. We modeled the kinetics of rhodopsin bleaching by applying variational optimization techniques from applied mathematics. The physical model and the numerical analysis with its implementation are outlined in detail. This new technique enables the creation of spatial maps of the retinal rhodopsin and retinal pigment epithelium (RPE) bisretinoid distribution with an ≈ 50μm resolution. PMID:26196397

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

NASA Astrophysics Data System (ADS)

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

2014-11-01

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

Spatial distribution of pH and organic matter in urban soils and its implications on site-specific land uses in Xuzhou, China.

PubMed

Mao, Yingming; Sang, Shuxun; Liu, Shiqi; Jia, Jinlong

2014-05-01

The spatial variation of soil pH and soil organic matter (SOM) in the urban area of Xuzhou, China, was investigated in this study. Conventional statistics, geostatistics, and a geographical information system (GIS) were used to produce spatial distribution maps and to provide information about land use types. A total of 172 soil samples were collected based on grid method in the study area. Soil pH ranged from 6.47 to 8.48, with an average of 7.62. SOM content was very variable, ranging from 3.51 g/kg to 17.12 g/kg, with an average of 8.26 g/kg. Soil pH followed a normal distribution, while SOM followed a log-normal distribution. The results of semi-variograms indicated that soil pH and SOM had strong (21%) and moderate (44%) spatial dependence, respectively. The variogram model was spherical for soil pH and exponential for SOM. The spatial distribution maps were achieved using kriging interpolation. The high pH and high SOM tended to occur in the mixed forest land cover areas such as those in the southwestern part of the urban area, while the low values were found in the eastern and the northern parts, probably due to the effect of industrial and human activities. In the central urban area, the soil pH was low, but the SOM content was high, which is mainly attributed to the disturbance of regional resident activities and urban transportation. Furthermore, anthropogenic organic particles are possible sources of organic matter after entering the soil ecosystem in urban areas. These maps provide useful information for urban planning and environmental management. Copyright © 2014 Académie des sciences. Published by Elsevier SAS. All rights reserved.

A Brief History of the use of Electromagnetic Induction Techniques in Soil Survey

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Doolittle, James

2017-04-01

Electromagnetic induction (EMI) has been used to characterize the spatial variability of soil properties since the late 1970s. Initially used to assess soil salinity, the use of EMI in soil studies has expanded to include: mapping soil types; characterizing soil water content and flow patterns; assessing variations in soil texture, compaction, organic matter content, and pH; and determining the depth to subsurface horizons, stratigraphic layers or bedrock, among other uses. In all cases the soil property being investigated must influence soil apparent electrical conductivity (ECa) either directly or indirectly for EMI techniques to be effective. An increasing number and diversity of EMI sensors have been developed in response to users' needs and the availability of allied technologies, which have greatly improved the functionality of these tools and increased the amount and types of data that can be gathered with a single pass. EMI investigations provide several benefits for soil studies. The large amount of georeferenced data that can be rapidly and inexpensively collected with EMI provides more complete characterization of the spatial variations in soil properties than traditional sampling techniques. In addition, compared to traditional soil survey methods, EMI can more effectively characterize diffuse soil boundaries and identify included areas of dissimilar soils within mapped soil units, giving soil scientists greater confidence when collecting spatial soil information. EMI techniques do have limitations; results are site-specific and can vary depending on the complex interactions among multiple and variable soil properties. Despite this, EMI techniques are increasingly being used to investigate the spatial variability of soil properties at field and landscape scales. The future should witness a greater use of multiple-frequency and multiple-coil EMI sensors and integration with other sensors to assess the spatial variability of soil properties. Data analysis will be improved with advanced processing and presentation systems and more sophisticated geostatistical modeling algorithms will be developed and used to interpolate EMI data, improve the resolution of subsurface features, and assess soil properties.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Mapping Geological Units on Mars by Analyzing the Spectral Properties of the Surface from the Mars-Express High Resolution Stereo Camera (HRSC)

NASA Astrophysics Data System (ADS)

Combe, J.; Adams, J. B.; McCord, T. B.

2006-12-01

Geological units at the surface of Mars can be investigated through the analysis of spatial changes of both its composition and its superficial structural properties. The color images provided by the High Resolution Stereo Camera (HRSC) are a multispectral dataset with an unprecedented high spatial resolution. We focused this study on the western chasmas of Valles Marineris with the neighboring plateau. Using the four-wavelength spectra of HRSC, the two types of surface color units (bright red and dark bluish material) plus a shade/shadow component can explain most of the variations [1]. An objective is to provide maps of the relative abundances that are independent of shade [2]. The spectral shape of the shade spectrum is calculated from the data. Then, Spectral Mixture Analysis of the two main materials and shade is performed. The shade gives us indications about variations in the surface roughness in the context of the mixtures of spectral/mineralogical materials. For mapping the different geological units at the surface at high spatial resolution, a correspondence between the color and the mineralogy is needed, aided by direct and more precise identifications of the composition of Mars. The joint analysis of HRSC and results from the OMEGA imaging spectrometer makes the most of their respective abilities [1]. Ferric oxides are present in bright red materials both in the chasmas and on the plateau [1] and they are often mixed with dark materials identified as basalts containing pyroxenes [4]. In Valles Marineris, salt deposits (bright) have been reported by using OMEGA [3], along with ferric oxides [4, 5] that appear relatively dark. The detailed spatial distribution of these materials is a key to understand the geology. Examples will be presented. [1] McCord T. B., et al. 2006, JGR, submitted. [2] Adams J. B. And Gillespie A. R., 2006, Cambridge University Press, 362 pp. [3] Le Mouelic S. et al., 2006, LPSC #1409. [4] Gendrin et al. (2005), LPSC #1858. [5] Gendrin A. et al., 2005, Science, 307, 1587-1591. [6] Le Deit et al., 2006, LPSC #2115.

Recovery of an evolving magnetic flux rope in the solar wind: Decomposing spatial and temporal variations from single-spacecraft data

NASA Astrophysics Data System (ADS)

Hasegawa, H.; Sonnerup, B.; Hu, Q.; Nakamura, T.

2013-12-01

We present a novel single-spacecraft data analysis method for decomposing spatial and temporal variations of physical quantities at points along the path of a spacecraft in spacetime. The method is designed for use in the reconstruction of slowly evolving two-dimensional, magneto-hydrostatic structures (Grad-Shafranov equilibria) in a space plasma. It is an extension of the one developed by Sonnerup and Hasegawa [2010] and Hasegawa et al. [2010], in which it was assumed that variations in the time series of data, recorded as the structures move past the spacecraft, are all due to spatial effects. In reality, some of the observed variations are usually caused by temporal evolution of the structure during the time it moves past the observing spacecraft; the information in the data about the spatial structure is aliased by temporal effects. The purpose here is to remove this time aliasing from the reconstructed maps of field and plasma properties. Benchmark tests are performed by use of synthetic data taken by a virtual spacecraft as it traverses, at a constant velocity, a slowly growing magnetic flux rope in a two-dimensional magnetohydrodynamic simulation of magnetic reconnection. These tests show that the new method can better recover the spacetime behavior of the flux rope than does the original version, in which time aliasing effects had not been removed. An application of the new method to a solar wind flux rope, observed by the ACE spacecraft, suggests that it was evolving in a significant way during the ~17 hour interval of the traversal. References Hasegawa, H., B. U. Ö. Sonnerup, and T. K. M. Nakamura (2010), Recovery of time evolution of Grad-Shafranov equilibria from single-spacecraft data: Benchmarking and application to a flux transfer event, J. Geophys. Res., 115, A11219, doi:10.1029/2010JA015679. Sonnerup, B. U. Ö., and H. Hasegawa (2010), On slowly evolving Grad-Shafranov equilibria, J. Geophys. Res., 115, A11218, doi:10.1029/2010JA015678. Magnetic field maps recovered from (a) the aliased (original) and (b) de-aliased (new) versions of the time evolution method. Colors show the out-of-plane (z) magnetic field component, and white arrows at points along y = 0 show the transverse velocities obtained from the reconstruction. The blue diamonds in panels (b) mark the location of the ACE spacecraft.

Spatial distribution of tropospheric ozone in national parks of California: interpretation of passive-sampler data.

PubMed

Ray, J D

2001-09-28

The National Park Service (NPS) has tested and used passive ozone samplers for several years to get baseline values for parks and to determine the spatial variability within parks. Experience has shown that the Ogawa passive samplers can provide +/-10% accuracy when used with a quality assurance program consisting of blanks, duplicates, collocated instrumentation, and a standard operating procedure that carefully guides site operators. Although the passive device does not meet EPA criteria as a certified method (mainly, that hourly values be measured), it does provide seasonal summed values of ozone. The seasonal ozone concentrations from the passive devices can be compared to other monitoring to determine baseline values, trends, and spatial variations. This point is illustrated with some kriged interpolation maps of ozone statistics. Passive ozone samplers were used to get elevational gradients and spatial distributions of ozone within a park. This was done in varying degrees at Mount Rainier, Olympic, Sequoia-Kings Canyon, Yosemite, Joshua Tree, Rocky Mountain, and Great Smoky Mountains national parks. The ozone has been found to vary by factors of 2 and 3 within a park when average ozone is compared between locations. Specific examples of the spatial distributions of ozone in three parks within California are given using interpolation maps. Positive aspects and limitations of the passive sampling approach are presented.

Atomic oxygen between 80 and 120 km: Evidence for a rapid spatial variation in vertical transport near the ionosphere

NASA Technical Reports Server (NTRS)

Donahue, T. M.; Wasser, B.

1977-01-01

Analysis of OGO-6 OI green line photometer results was carried out for 8 cases when the alignment of the spacecraft was such that local emission rates could be determined below the altitude of maximum emission and down to about 80 km. Results show a variation on a scale of 6 deg to 8 deg in latitude between regions where the emission rate increases rapidly between 90 and 95 km and regions where it increases slowly from 80 km to 95 km. Latitude-altitude maps of iso-emissivity contours and iso-density contours for oxygen concentration are presented. The latter are computed under 3 assumptions concerning excitation mechanisms. Comparisons of the spatial variations of oxygen density with the results of a time dependent theory suggest the regions of strong downward transport alternate on a scale of about 1000 km with regions of weak transport near 90 km. In the first case conversion of O to O3 at night appears to be overwhelmed by downward transport of O.

Thinner regions of intracranial aneurysm wall correlate with regions of higher wall shear stress: a 7.0 tesla MRI

PubMed Central

Blankena, Roos; Kleinloog, Rachel; Verweij, Bon H.; van Ooij, Pim; ten Haken, Bennie; Luijten, Peter R.; Rinkel, Gabriel J.E.; Zwanenburg, Jaco J.M.

2016-01-01

Purpose To develop a method for semi-quantitative wall thickness assessment on in vivo 7.0 tesla (7T) MRI images of intracranial aneurysms for studying the relation between apparent aneurysm wall thickness and wall shear stress. Materials and Methods Wall thickness was analyzed in 11 unruptured aneurysms in 9 patients, who underwent 7T MRI with a TSE based vessel wall sequence (0.8 mm isotropic resolution). A custom analysis program determined the in vivo aneurysm wall intensities, which were normalized to signal of nearby brain tissue and were used as measure for apparent wall thickness (AWT). Spatial wall thickness variation was determined as the interquartile range in AWT (the middle 50% of the AWT range). Wall shear stress was determined using phase contrast MRI (0.5 mm isotropic resolution). We performed visual and statistical comparisons (Pearson’s correlation) to study the relation between wall thickness and wall shear stress. Results 3D colored AWT maps of the aneurysms showed spatial AWT variation, which ranged from 0.07 to 0.53, with a mean variation of 0.22 (a variation of 1.0 roughly means a wall thickness variation of one voxel (0.8mm)). In all aneurysms, AWT was inversely related to WSS (mean correlation coefficient −0.35, P<0.05). Conclusions A method was developed to measure the wall thickness semi-quantitatively, using 7T MRI. An inverse correlation between wall shear stress and AWT was determined. In future studies, this non-invasive method can be used to assess spatial wall thickness variation in relation to pathophysiologic processes such as aneurysm growth and –rupture. PMID:26892986

Spatial variation of dental caries in late holocene samples of Southern South America: A geostatistical study.

PubMed

Menéndez, Lumila Paula

2016-11-01

The spatial variation of dental caries in late Holocene southern South American populations will be analyzed using geostatistical methods. The existence of a continuous geographical pattern of dental caries variation will be tested. The author recorded dental caries in 400 individuals, collated this information with published caries data from 666 additional individuals, and calculated a Caries Index. The caries spatial distribution was evaluated by means of 2D maps and scatterplots. Geostatistical analyses were performed by calculating Moran's I, correlograms and a Procrustes analysis. There is a relatively strong latitudinal continuous gradient of dental caries variation, especially in the extremes of the distribution. Moreover, the association between dental caries and geography was relatively high (m 12  = 0.6). Although northern and southern samples had the highest and lowest frequencies of dental caries, respectively, the central ones had the largest variation and had lower rates of caries than expected. The large variation in frequencies of dental caries in populations located in the center of the distribution could be explained by their subsistence strategies, characterized either by the consumption of wild cariogenic plants or cultigens (obtained locally or by exchange), a reliance on fishing, or the incorporation of plants rich in starch rather than carbohydrates. It is suggested that dental caries must be considered a multifactorial disease which results from the interaction of cultural practices and environmental factors. This can change how we understand subsistence strategies as well as how we interpret dental caries rates. Am. J. Hum. Biol., 2016. © 2016 Wiley Periodicals, Inc. Am. J. Hum. Biol. 28:825-836, 2016. © 2016Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A spatially resolved radio spectral index study of the dwarf irregular galaxy NGC 1569

NASA Astrophysics Data System (ADS)

Westcott, Jonathan; Brinks, Elias; Hindson, Luke; Beswick, Robert; Heesen, Volker

2018-04-01

We study the resolved radio continuum spectral energy distribution of the dwarf irregular galaxy, NGC 1569, on a beam-by-beam basis to isolate and study its spatially resolved radio emission characteristics. Utilizing high-quality NRAO Karl G. Jansky Very Large Array observations that densely sample the 1-34 GHz frequency range, we adopt a Bayesian fitting procedure, where we use H α emission that has not been corrected for extinction as a prior, to produce maps of how the separated thermal emission, non-thermal emission, and non-thermal spectral index vary across NGC 1569's main disc. We find a higher thermal fraction at 1 GHz than is found in spiral galaxies (26^{+2}_{-3} {per cent}) and find an average non-thermal spectral index α = -0.53 ± 0.02, suggesting that a young population of cosmic ray electrons is responsible for the observed non-thermal emission. By comparing our recovered map of the thermal radio emission with literature H α maps, we estimate the total reddening along the line of sight to NGC 1569 to be E(B - V) = 0.49 ± 0.05, which is in good agreement with other literature measurements. Spatial variations in the reddening indicate that a significant portion of the total reddening is due to internal extinction within NGC 1569.

Impact of land-use on groundwater quality: GIS-based study from an alluvial aquifer in the western Ganges basin

NASA Astrophysics Data System (ADS)

Khan, Arina; Khan, Haris Hasan; Umar, Rashid

2017-12-01

In this study, groundwater quality of an alluvial aquifer in the western Ganges basin is assessed using a GIS-based groundwater quality index (GQI) concept that uses groundwater quality data from field survey and laboratory analysis. Groundwater samples were collected from 42 wells during pre-monsoon and post-monsoon periods of 2012 and analysed for pH, EC, TDS, Anions (Cl, SO4, NO3), and Cations (Ca, Mg, Na). To generate the index, several parameters were selected based on WHO recommendations. The spatially variable grids of each parameter were modified by normalizing with the WHO standards and finally integrated into a GQI grid. The mean GQI values for both the season suggest good groundwater quality. However, spatial variations exist and are represented by GQI map of both seasons. This spatial variability was compared with the existing land-use, prepared using high-resolution satellite imagery available in Google earth. The GQI grids were compared to the land-use map using an innovative GIS-based method. Results indicate that the spatial variability of groundwater quality in the region is not fully controlled by the land-use pattern. This probably reflects the diffuse nature of land-use classes, especially settlements and plantations.

Dimensionality-varied deep convolutional neural network for spectral-spatial classification of hyperspectral data

NASA Astrophysics Data System (ADS)

Qu, Haicheng; Liang, Xuejian; Liang, Shichao; Liu, Wanjun

2018-01-01

Many methods of hyperspectral image classification have been proposed recently, and the convolutional neural network (CNN) achieves outstanding performance. However, spectral-spatial classification of CNN requires an excessively large model, tremendous computations, and complex network, and CNN is generally unable to use the noisy bands caused by water-vapor absorption. A dimensionality-varied CNN (DV-CNN) is proposed to address these issues. There are four stages in DV-CNN and the dimensionalities of spectral-spatial feature maps vary with the stages. DV-CNN can reduce the computation and simplify the structure of the network. All feature maps are processed by more kernels in higher stages to extract more precise features. DV-CNN also improves the classification accuracy and enhances the robustness to water-vapor absorption bands. The experiments are performed on data sets of Indian Pines and Pavia University scene. The classification performance of DV-CNN is compared with state-of-the-art methods, which contain the variations of CNN, traditional, and other deep learning methods. The experiment of performance analysis about DV-CNN itself is also carried out. The experimental results demonstrate that DV-CNN outperforms state-of-the-art methods for spectral-spatial classification and it is also robust to water-vapor absorption bands. Moreover, reasonable parameters selection is effective to improve classification accuracy.

Anti-impulse-noise Edge Detection via Anisotropic Morphological Directional Derivatives.

PubMed

Shui, Peng-Lang; Wang, Fu-Ping

2017-07-13

Traditional differential-based edge detection suffers from abrupt degradation in performance when images are corrupted by impulse noises. The morphological operators such as the median filters and weighted median filters possess the intrinsic ability to counteract impulse noise. In this paper, by combining the biwindow configuration with weighted median filters, anisotropic morphological directional derivatives (AMDD) robust to impulse noise are proposed to measure the local grayscale variation around a pixel. For ideal step edges, the AMDD spatial response and directional representation are derived. The characteristics and edge resolution of two kinds of typical biwindows are analyzed thoroughly. In terms of the AMDD spatial response and directional representation of ideal step edges, the spatial matched filter is used to extract the edge strength map (ESM) from the AMDDs of an image. The spatial and directional matched filters are used to extract the edge direction map (EDM). Embedding the extracted ESM and EDM into the standard route of the differential-based edge detection, an anti-impulse-noise AMDD-based edge detector is constructed. It is compared with the existing state-of-the-art detectors on a recognized image dataset for edge detection evaluation. The results show that it attains competitive performance in noise-free and Gaussian noise cases and the best performance in impulse noise cases.

Remotely estimating photosynthetic capacity, and its response to temperature, in vegetation canopies using imaging spectroscopy

DOE PAGES

Serbin, Shawn P.; Singh, Aditya; Desai, Ankur R.; ...

2015-06-11

To date, the utility of ecosystem and Earth system models (EESMs) has been limited by poor spatial and temporal representation of critical input parameters. For example, EESMs often rely on leaf-scale or literature-derived estimates for a key determinant of canopy photosynthesis, the maximum velocity of RuBP carboxylation (Vcmax, μmol m –2 s –1). Our recent work (Ainsworth et al., 2014; Serbin et al., 2012) showed that reflectance spectroscopy could be used to estimate Vcmax at the leaf level. Here, we present evidence that imaging spectroscopy data can be used to simultaneously predict Vcmax and its sensitivity to temperature (E V)more » at the canopy scale. In 2013 and 2014, high-altitude Airborne Visible/Infrared Imaging Spectroscopy (AVIRIS) imagery and contemporaneous ground-based assessments of canopy structure and leaf photosynthesis were acquired across an array of monospecific agroecosystems in central and southern California, USA. A partial least-squares regression (PLSR) modeling approach was employed to characterize the pixel-level variation in canopy V cmax (at a standardized canopy temperature of 30 °C) and E V, based on visible and shortwave infrared AVIRIS spectra (414–2447 nm). Our approach yielded parsimonious models with strong predictive capability for Vcmax (at 30 °C) and E V (R 2 of withheld data = 0.94 and 0.92, respectively), both of which varied substantially in the field (≥ 1.7 fold) across the sampled crop types. The models were applied to additional AVIRIS imagery to generate maps of V cmax and E V, as well as their uncertainties, for agricultural landscapes in California. The spatial patterns exhibited in the maps were consistent with our in-situ observations. As a result, these findings highlight the considerable promise of airborne and, by implication, space-borne imaging spectroscopy, such as the proposed HyspIRI mission, to map spatial and temporal variation in key drivers of photosynthetic metabolism in terrestrial vegetation.« less

Mapping the Risk of Snakebite in Sri Lanka - A National Survey with Geospatial Analysis.

PubMed

Ediriweera, Dileepa Senajith; Kasturiratne, Anuradhani; Pathmeswaran, Arunasalam; Gunawardena, Nipul Kithsiri; Wijayawickrama, Buddhika Asiri; Jayamanne, Shaluka Francis; Isbister, Geoffrey Kennedy; Dawson, Andrew; Giorgi, Emanuele; Diggle, Peter John; Lalloo, David Griffith; de Silva, Hithanadura Janaka

2016-07-01

There is a paucity of robust epidemiological data on snakebite, and data available from hospitals and localized or time-limited surveys have major limitations. No study has investigated the incidence of snakebite across a whole country. We undertook a community-based national survey and model based geostatistics to determine incidence, envenoming, mortality and geographical pattern of snakebite in Sri Lanka. The survey was designed to sample a population distributed equally among the nine provinces of the country. The number of data collection clusters was divided among districts in proportion to their population. Within districts clusters were randomly selected. Population based incidence of snakebite and significant envenoming were estimated. Model-based geostatistics was used to develop snakebite risk maps for Sri Lanka. 1118 of the total of 14022 GN divisions with a population of 165665 (0.8%of the country's population) were surveyed. The crude overall community incidence of snakebite, envenoming and mortality were 398 (95% CI: 356-441), 151 (130-173) and 2.3 (0.2-4.4) per 100000 population, respectively. Risk maps showed wide variation in incidence within the country, and snakebite hotspots and cold spots were determined by considering the probability of exceeding the national incidence. This study provides community based incidence rates of snakebite and envenoming for Sri Lanka. The within-country spatial variation of bites can inform healthcare decision making and highlights the limitations associated with estimates of incidence from hospital data or localized surveys. Our methods are replicable, and these models can be adapted to other geographic regions after re-estimating spatial covariance parameters for the particular region.

Spatial relationships between above-ground biomass and bird species biodiversity in Palawan, Philippines

PubMed Central

Singh, Minerva; Friess, Daniel A.; Vilela, Bruno; Alban, Jose Don T. De; Monzon, Angelica Kristina V.; Veridiano, Rizza Karen A.; Tumaneng, Roven D.

2017-01-01

This study maps distribution and spatial congruence between Above-Ground Biomass (AGB) and species richness of IUCN listed conservation-dependent and endemic avian fauna in Palawan, Philippines. Grey Level Co-Occurrence Texture Matrices (GLCMs) extracted from Landsat and ALOS-PALSAR were used in conjunction with local field data to model and map local-scale field AGB using the Random Forest algorithm (r = 0.92 and RMSE = 31.33 Mg·ha-1). A support vector regression (SVR) model was used to identify the factors influencing variation in avian species richness at a 1km scale. AGB is one of the most important determinants of avian species richness for the study area. Topographic factors and anthropogenic factors such as distance from the roads were also found to strongly influence avian species richness. Hotspots of high AGB and high species richness concentration were mapped using hotspot analysis and the overlaps between areas of high AGB and avian species richness was calculated. Results show that the overlaps between areas of high AGB with high IUCN red listed avian species richness and endemic avian species richness were fairly limited at 13% and 8% at the 1-km scale. The overlap between 1) low AGB and low IUCN richness, and 2) low AGB and low endemic avian species richness was higher at 36% and 12% respectively. The enhanced capacity to spatially map the correlation between AGB and avian species richness distribution will further assist the conservation and protection of forest areas and threatened avian species. PMID:29206228

Coastal areas mapping using UAV photogrammetry

NASA Astrophysics Data System (ADS)

Nikolakopoulos, Konstantinos G.; Kozarski, Dimitrios; Kogkas, Stefanos

2017-10-01

The coastal areas in the Patras Gulf suffer degradation due to the sea action and other natural and human-induced causes. Changes in beaches, ports, and other man made constructions need to be assessed, both after severe events and on a regular basis, to build models that can predict the evolution in the future. Thus, reliable spatial data acquisition is a critical process for the identification of the coastline and the broader coastal zones for geologists and other scientists involved in the study of coastal morphology. High resolution satellite data, airphotos and airborne Lidar provided in the past the necessary data for the coastline monitoring. High-resolution digital surface models (DSMs) and orthophoto maps had become a necessity in order to map with accuracy all the variations in costal environments. Recently, unmanned aerial vehicles (UAV) photogrammetry offers an alternative solution to the acquisition of high accuracy spatial data along the coastline. This paper presents the use of UAV to map the coastline in Rio area Western Greece. Multiple photogrammetric aerial campaigns were performed. A small commercial UAV (DJI Phantom 3 Advance) was used to acquire thousands of images with spatial resolutions better than 5 cm. Different photogrammetric software's were used to orientate the images, extract point clouds, build a digital surface model and produce orthoimage mosaics. In order to achieve the best positional accuracy signalised ground control points were measured with a differential GNSS receiver. The results of this coastal monitoring programme proved that UAVs can replace many of the conventional surveys, with considerable gains in the cost of the data acquisition and without any loss in the accuracy.

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

USGS Publications Warehouse

Bennion, David

2009-01-01

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

Improving urban land use and land cover classification from high-spatial-resolution hyperspectral imagery using contextual information

NASA Astrophysics Data System (ADS)

Yang, He; Ma, Ben; Du, Qian; Yang, Chenghai

2010-08-01

In this paper, we propose approaches to improve the pixel-based support vector machine (SVM) classification for urban land use and land cover (LULC) mapping from airborne hyperspectral imagery with high spatial resolution. Class spatial neighborhood relationship is used to correct the misclassified class pairs, such as roof and trail, road and roof. These classes may be difficult to be separated because they may have similar spectral signatures and their spatial features are not distinct enough to help their discrimination. In addition, misclassification incurred from within-class trivial spectral variation can be corrected by using pixel connectivity information in a local window so that spectrally homogeneous regions can be well preserved. Our experimental results demonstrate the efficiency of the proposed approaches in classification accuracy improvement. The overall performance is competitive to the object-based SVM classification.

Stochastic Geometric Models with Non-stationary Spatial Correlations in Lagrangian Fluid Flows

NASA Astrophysics Data System (ADS)

Gay-Balmaz, François; Holm, Darryl D.

2018-01-01

Inspired by spatiotemporal observations from satellites of the trajectories of objects drifting near the surface of the ocean in the National Oceanic and Atmospheric Administration's "Global Drifter Program", this paper develops data-driven stochastic models of geophysical fluid dynamics (GFD) with non-stationary spatial correlations representing the dynamical behaviour of oceanic currents. Three models are considered. Model 1 from Holm (Proc R Soc A 471:20140963, 2015) is reviewed, in which the spatial correlations are time independent. Two new models, called Model 2 and Model 3, introduce two different symmetry breaking mechanisms by which the spatial correlations may be advected by the flow. These models are derived using reduction by symmetry of stochastic variational principles, leading to stochastic Hamiltonian systems, whose momentum maps, conservation laws and Lie-Poisson bracket structures are used in developing the new stochastic Hamiltonian models of GFD.

Stochastic Geometric Models with Non-stationary Spatial Correlations in Lagrangian Fluid Flows

NASA Astrophysics Data System (ADS)

Gay-Balmaz, François; Holm, Darryl D.

2018-06-01

Inspired by spatiotemporal observations from satellites of the trajectories of objects drifting near the surface of the ocean in the National Oceanic and Atmospheric Administration's "Global Drifter Program", this paper develops data-driven stochastic models of geophysical fluid dynamics (GFD) with non-stationary spatial correlations representing the dynamical behaviour of oceanic currents. Three models are considered. Model 1 from Holm (Proc R Soc A 471:20140963, 2015) is reviewed, in which the spatial correlations are time independent. Two new models, called Model 2 and Model 3, introduce two different symmetry breaking mechanisms by which the spatial correlations may be advected by the flow. These models are derived using reduction by symmetry of stochastic variational principles, leading to stochastic Hamiltonian systems, whose momentum maps, conservation laws and Lie-Poisson bracket structures are used in developing the new stochastic Hamiltonian models of GFD.

The effects of spatial population dataset choice on estimates of population at risk of disease

PubMed Central

2011-01-01

Background The spatial modeling of infectious disease distributions and dynamics is increasingly being undertaken for health services planning and disease control monitoring, implementation, and evaluation. Where risks are heterogeneous in space or dependent on person-to-person transmission, spatial data on human population distributions are required to estimate infectious disease risks, burdens, and dynamics. Several different modeled human population distribution datasets are available and widely used, but the disparities among them and the implications for enumerating disease burdens and populations at risk have not been considered systematically. Here, we quantify some of these effects using global estimates of populations at risk (PAR) of P. falciparum malaria as an example. Methods The recent construction of a global map of P. falciparum malaria endemicity enabled the testing of different gridded population datasets for providing estimates of PAR by endemicity class. The estimated population numbers within each class were calculated for each country using four different global gridded human population datasets: GRUMP (~1 km spatial resolution), LandScan (~1 km), UNEP Global Population Databases (~5 km), and GPW3 (~5 km). More detailed assessments of PAR variation and accuracy were conducted for three African countries where census data were available at a higher administrative-unit level than used by any of the four gridded population datasets. Results The estimates of PAR based on the datasets varied by more than 10 million people for some countries, even accounting for the fact that estimates of population totals made by different agencies are used to correct national totals in these datasets and can vary by more than 5% for many low-income countries. In many cases, these variations in PAR estimates comprised more than 10% of the total national population. The detailed country-level assessments suggested that none of the datasets was consistently more accurate than the others in estimating PAR. The sizes of such differences among modeled human populations were related to variations in the methods, input resolution, and date of the census data underlying each dataset. Data quality varied from country to country within the spatial population datasets. Conclusions Detailed, highly spatially resolved human population data are an essential resource for planning health service delivery for disease control, for the spatial modeling of epidemics, and for decision-making processes related to public health. However, our results highlight that for the low-income regions of the world where disease burden is greatest, existing datasets display substantial variations in estimated population distributions, resulting in uncertainty in disease assessments that utilize them. Increased efforts are required to gather contemporary and spatially detailed demographic data to reduce this uncertainty, particularly in Africa, and to develop population distribution modeling methods that match the rigor, sophistication, and ability to handle uncertainty of contemporary disease mapping and spread modeling. In the meantime, studies that utilize a particular spatial population dataset need to acknowledge the uncertainties inherent within them and consider how the methods and data that comprise each will affect conclusions. PMID:21299885

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

USGS Publications Warehouse

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

2011-01-01

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

Mapping of the Ronda peridotite massif (Spain) from AVIRIS spectro-imaging survey: A first attempt

NASA Technical Reports Server (NTRS)

Pinet, P. C.; Chabrillat, S.; Ceuleneer, G.

1993-01-01

In both AVIRIS and ISM data, through the use of mixing models, geological boundaries of the Ronda massif are identified with respect to the surrounding rocks. We can also yield first-order vegetation maps. ISM and AVIRIS instruments give consistent results. On the basis of endmember fraction images, it is then possible to discard areas highly vegetated or not belonging to the peridotite massif. Within the remaining part of the mosaic, spectro-mixing analysis reveals spectral variations in the peridotite massif between the well-exposed areas. Spatially organized units are depicted, related to differences in the relative depth of the absorption band at 1 micron, and it may be due to a different pyroxene content. At this stage, it is worth noting that, although mineralogical variations observed in the rocks are at a sub-pixel scale for the airborne analysis, we see an emerging spatial pattern in the distribution of spectral variations across the massif which might be prevailingly related to mineralogy. Although it is known from fieldwork that the Ronda peridotite massif exhibits mineralogical variations at local scale in the content of pyroxene, and at regional scale in different mineral facies, ranging from garnet-, to spinel- to plagioclase-lherzolites, no attempt has been done yet to produce a synoptic map relating the two scales of analysis. The present work is a first attempt to reach this objective, though a lot more work is still required. In particular, for the purpose of mineralogical interpretation, it is critical to relate the airborne observation to field work and laboratory spectra of Ronda rocks already obtained, with the use of image endmembers and associated reference endmembers. Also, the pretty rough linear mixing model used here is taken as a 'black-box' process which does not necessarily apply correctly to the physical situation at the sub-pixel level. One may think of using the ground-truth observations bearing on the sub-pixel statistical characteristics (texture, structural pattern, surface distribution and vegetation contribution (grass,..)) to produce a more advanced mixing model, physically appropriate to the geologic and environmental contexts.

Statistical mapping of count survey data

USGS Publications Warehouse

Royle, J. Andrew; Link, W.A.; Sauer, J.R.; Scott, J. Michael; Heglund, Patricia J.; Morrison, Michael L.; Haufler, Jonathan B.; Wall, William A.

2002-01-01

We apply a Poisson mixed model to the problem of mapping (or predicting) bird relative abundance from counts collected from the North American Breeding Bird Survey (BBS). The model expresses the logarithm of the Poisson mean as a sum of a fixed term (which may depend on habitat variables) and a random effect which accounts for remaining unexplained variation. The random effect is assumed to be spatially correlated, thus providing a more general model than the traditional Poisson regression approach. Consequently, the model is capable of improved prediction when data are autocorrelated. Moreover, formulation of the mapping problem in terms of a statistical model facilitates a wide variety of inference problems which are cumbersome or even impossible using standard methods of mapping. For example, assessment of prediction uncertainty, including the formal comparison of predictions at different locations, or through time, using the model-based prediction variance is straightforward under the Poisson model (not so with many nominally model-free methods). Also, ecologists may generally be interested in quantifying the response of a species to particular habitat covariates or other landscape attributes. Proper accounting for the uncertainty in these estimated effects is crucially dependent on specification of a meaningful statistical model. Finally, the model may be used to aid in sampling design, by modifying the existing sampling plan in a manner which minimizes some variance-based criterion. Model fitting under this model is carried out using a simulation technique known as Markov Chain Monte Carlo. Application of the model is illustrated using Mourning Dove (Zenaida macroura) counts from Pennsylvania BBS routes. We produce both a model-based map depicting relative abundance, and the corresponding map of prediction uncertainty. We briefly address the issue of spatial sampling design under this model. Finally, we close with some discussion of mapping in relation to habitat structure. Although our models were fit in the absence of habitat information, the resulting predictions show a strong inverse relation with a map of forest cover in the state, as expected. Consequently, the results suggest that the correlated random effect in the model is broadly representing ecological variation, and that BBS data may be generally useful for studying bird-habitat relationships, even in the presence of observer errors and other widely recognized deficiencies of the BBS.

Repeated electromagnetic induction measurements for mapping soil moisture at the field scale: validation with data from a wireless soil moisture monitoring network

NASA Astrophysics Data System (ADS)

Martini, Edoardo; Werban, Ulrike; Zacharias, Steffen; Pohle, Marco; Dietrich, Peter; Wollschläger, Ute

2017-01-01

Electromagnetic induction (EMI) measurements are widely used for soil mapping, as they allow fast and relatively low-cost surveys of soil apparent electrical conductivity (ECa). Although the use of non-invasive EMI for imaging spatial soil properties is very attractive, the dependence of ECa on several factors challenges any interpretation with respect to individual soil properties or states such as soil moisture (θ). The major aim of this study was to further investigate the potential of repeated EMI measurements to map θ, with particular focus on the temporal variability of the spatial patterns of ECa and θ. To this end, we compared repeated EMI measurements with high-resolution θ data from a wireless soil moisture and soil temperature monitoring network for an extensively managed hillslope area for which soil properties and θ dynamics are known. For the investigated site, (i) ECa showed small temporal variations whereas θ varied from very dry to almost saturation, (ii) temporal changes of the spatial pattern of ECa differed from those of the spatial pattern of θ, and (iii) the ECa-θ relationship varied with time. Results suggest that (i) depending upon site characteristics, stable soil properties can be the major control of ECa measured with EMI, and (ii) for soils with low clay content, the influence of θ on ECa may be confounded by changes of the electrical conductivity of the soil solution. Further, this study discusses the complex interplay between factors controlling ECa and θ, and the use of EMI-based ECa data with respect to hydrological applications.

Mapping Spatial Variability in Health and Wealth Indicators in Accra, Ghana Using High Spatial Resolution Imagery

NASA Astrophysics Data System (ADS)

Engstrom, R.; Ashcroft, E.

2014-12-01

There has been a tremendous amount of research conducted that examines disparities in health and wealth of persons between urban and rural areas however, relatively little research has been undertaken to examine variations within urban areas. A major limitation to elucidating differences with urban areas is the lack of social and demographic data at a sufficiently high spatial resolution to determine these differences. Generally the only available data that contain this information are census data which are collected at most every ten years and are often difficult to obtain at a high enough spatial resolution to allow for examining in depth variability in health and wealth indicators at high spatial resolutions, especially in developing countries. High spatial resolution satellite imagery may be able to provide timely and synoptic information that is related to health and wealth variability within a city. In this study we use two dates of Quickbird imagery (2003 and 2010) classified into the vegetation-impervious surface-soil (VIS) model introduced by Ridd (1995). For 2003 we only have partial coverage of the city, while for 2010 we have a mosaic, which covers the entire city of Accra, Ghana. Variations in the VIS values represent the physical variations within the city and these are compared to variations in economic, and/or sociodemographic data derived from the 2000 Ghanaian census at two spatial resolutions, the enumeration area (approximately US Census Tract) and the neighborhood for the city. Results indicate a significant correlation between both vegetation and impervious surface to type of cooking fuel used in the household, population density, housing density, availability of sewers, cooking space usage, and other variables. The correlations are generally stronger at the neighborhood level and the relationships are stable through time and space. Overall, the results indicate that information derived from high resolution satellite data is related to indicators of health and wealth within a developing world city and that the even if the imagery is collected 10 years after the census information, the relationships are still significant.

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

NASA Astrophysics Data System (ADS)

Lu, Bing; He, Yuhong

2017-06-01

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

A Combined EOF/Variational Approach for Mapping Radar-Derived Sea Surface Currents

DTIC Science & Technology

2011-01-13

characterized by specific structure of the artificial gaps introduced into the simulated data set assess the benefits of the gap-filling technique. These...15 minutes and 1-2 km respectively. However, the back-scattered HFR signals suffer from to numerous distortions of artificial and natural origin. As a...data because information on the spatial structure of the velocity field within the gap is implicitly drawn from the idealized covariance function

Estimation of austral summer net community production in the Amundsen Sea: Self-organizing map analysis approach

NASA Astrophysics Data System (ADS)

Park, K.; Hahm, D.; Lee, D. G.; Rhee, T. S.; Kim, H. C.

2014-12-01

The Amundsen Sea, Antarctica, has been known for one of the most susceptible region to the current climate change such as sea ice melting and sea surface temperature change. In the Southern Ocean, a predominant amount of primary production is occurring in the continental shelf region. Phytoplankton blooms take place during the austral summer due to the limited sunlit and sea ice cover. Thus, quantifying the variation of summer season net community production (NCP) in the Amundsen Sea is essential to analyze the influence of climate change to the variation of biogeochemical cycle in the Southern Ocean. During the past three years of 2011, 2012 and 2014 in austral summer, we have conducted underway observations of ΔO2/Ar and derived NCP of the Amundsen Sea. Despite the importance of NCP for understanding biological carbon cycle of the ocean, the observations are rather limited to see the spatio-temporal variation in the Amundsen Sea. Therefore, we applied self-organizing map (SOM) analysis to expand our observed data sets and estimate the NCP during the summer season. SOM analysis, a type of artificial neural network, has been proved to be a useful method for extracting and classifying features in geoscience. In oceanography, SOM has applied for the analysis of various properties of the seawater such as sea surface temperature, chlorophyll concentration, pCO2, and NCP. Especially it is useful to expand a spatial coverage of direct measurements or to estimate properties whose satellite observations are technically or spatially limited. In this study, we estimate summer season NCP and find a variables set which optimally delineates the NCP variation in the Amundsen Sea as well. Moreover, we attempt to analyze the interannual variation of the Amundsen Sea NCP by taking climatological factors into account for the SOM analysis.

Carbon economics of LAI drive photosynthesis patterns across an Amazonian precipitation gradient

NASA Astrophysics Data System (ADS)

Flack, Sophie; Williams, Mathew; Meir, Patrick; Malhi, Yadvinder

2017-04-01

The Amazon rainforest is an integral part of the terrestrial carbon cycle, yet whilst the physiological response of its plants to water availability is increasingly well quantified, constraints to photosynthesis through adaptive response to precipitation regime have received little attention. We use the Soil Plant Atmosphere model to apportion variation in photosynthesis to individual drivers for plots with detailed measurements of carbon cycling, leaf traits and canopy properties, along an Amazonian mean annual precipitation (MAP) gradient. We hypothesised that leaf area index (LAI) would be the principal driver of variation in photosynthesis. Differences in LAI are predicted to result from economic factors; plants balance the carbon cost of leaf construction and maintenance with assimilation potential, to maximise canopy carbon export. Model analysis showed that LAI was the primary driver of differences in GPP along the precipitation gradient, accounting for 49% of observed variation. Meteorology accounted for 19%, whilst plant traits accounted for only 5%. To explain the observed spatial trends in LAI we undertook model experiments. For each plot the carbon budget was quantified iteratively using the field measured LAI time-series of the other plots, keeping meteorology, soil and plant traits constant. The mean annual LAI achieving maximum photosynthesis and net canopy carbon export increased with MAP, reflecting observed LAI trends. At the driest site, alternative, higher LAI strategies were unsustainable. The carbon cost of leaf construction and maintenance was disproportional to GPP achieved. At high MAP, increased foliar carbon costs were remunerative and GPP was maximised by high LAI. Our evidence therefore suggests that observed LAI trends across the precipitation gradient are driven by carbon economics. Forests LAI response to temporal changes in precipitation reflects trends observed across spatial gradients, identifying LAI as a key mechanism for plant response to water availability. This research improves our understanding of the constraints on photosynthesis through plants' adaptive response to precipitation, which in light of precipitation projections, has implications for the future Amazon carbon balance.

Mapping child maltreatment risk: a 12-year spatio-temporal analysis of neighborhood influences.

PubMed

Gracia, Enrique; López-Quílez, Antonio; Marco, Miriam; Lila, Marisol

2017-10-18

'Place' matters in understanding prevalence variations and inequalities in child maltreatment risk. However, most studies examining ecological variations in child maltreatment risk fail to take into account the implications of the spatial and temporal dimensions of neighborhoods. In this study, we conduct a high-resolution small-area study to analyze the influence of neighborhood characteristics on the spatio-temporal epidemiology of child maltreatment risk. We conducted a 12-year (2004-2015) small-area Bayesian spatio-temporal epidemiological study with all families with child maltreatment protection measures in the city of Valencia, Spain. As neighborhood units, we used 552 census block groups. Cases were geocoded using the family address. Neighborhood-level characteristics analyzed included three indicators of neighborhood disadvantage-neighborhood economic status, neighborhood education level, and levels of policing activity-, immigrant concentration, and residential instability. Bayesian spatio-temporal modelling and disease mapping methods were used to provide area-specific risk estimations. Results from a spatio-temporal autoregressive model showed that neighborhoods with low levels of economic and educational status, with high levels of policing activity, and high immigrant concentration had higher levels of substantiated child maltreatment risk. Disease mapping methods were used to analyze areas of excess risk. Results showed chronic spatial patterns of high child maltreatment risk during the years analyzed, as well as stability over time in areas of low risk. Areas with increased or decreased child maltreatment risk over the years were also observed. A spatio-temporal epidemiological approach to study the geographical patterns, trends over time, and the contextual determinants of child maltreatment risk can provide a useful method to inform policy and action. This method can offer a more accurate description of the problem, and help to inform more localized prevention and intervention strategies. This new approach can also contribute to an improved epidemiological surveillance system to detect ecological variations in risk, and to assess the effectiveness of the initiatives to reduce this risk.

Mapping populations at risk: improving spatial demographic data for infectious disease modeling and metric derivation

PubMed Central

2012-01-01

The use of Global Positioning Systems (GPS) and Geographical Information Systems (GIS) in disease surveys and reporting is becoming increasingly routine, enabling a better understanding of spatial epidemiology and the improvement of surveillance and control strategies. In turn, the greater availability of spatially referenced epidemiological data is driving the rapid expansion of disease mapping and spatial modeling methods, which are becoming increasingly detailed and sophisticated, with rigorous handling of uncertainties. This expansion has, however, not been matched by advancements in the development of spatial datasets of human population distribution that accompany disease maps or spatial models. Where risks are heterogeneous across population groups or space or dependent on transmission between individuals, spatial data on human population distributions and demographic structures are required to estimate infectious disease risks, burdens, and dynamics. The disease impact in terms of morbidity, mortality, and speed of spread varies substantially with demographic profiles, so that identifying the most exposed or affected populations becomes a key aspect of planning and targeting interventions. Subnational breakdowns of population counts by age and sex are routinely collected during national censuses and maintained in finer detail within microcensus data. Moreover, demographic and health surveys continue to collect representative and contemporary samples from clusters of communities in low-income countries where census data may be less detailed and not collected regularly. Together, these freely available datasets form a rich resource for quantifying and understanding the spatial variations in the sizes and distributions of those most at risk of disease in low income regions, yet at present, they remain unconnected data scattered across national statistical offices and websites. In this paper we discuss the deficiencies of existing spatial population datasets and their limitations on epidemiological analyses. We review sources of detailed, contemporary, freely available and relevant spatial demographic data focusing on low income regions where such data are often sparse and highlight the value of incorporating these through a set of examples of their application in disease studies. Moreover, the importance of acknowledging, measuring, and accounting for uncertainty in spatial demographic datasets is outlined. Finally, a strategy for building an open-access database of spatial demographic data that is tailored to epidemiological applications is put forward. PMID:22591595

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

ERIC Educational Resources Information Center

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

2017-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Impact of anatomical parameters on optical coherence tomography retinal nerve fiber layer thickness abnormality patterns

NASA Astrophysics Data System (ADS)

Baniasadi, Neda; Wang, Mengyu; Wang, Hui; Jin, Qingying; Mahd, Mufeed; Elze, Tobias

2017-02-01

Purpose: To evaluate the effects of four anatomical parameters (angle between superior and inferior temporal retinal arteries [inter-artery angle, IAA], optic disc [OD] rotation, retinal curvature, and central retinal vessel trunk entry point location [CRVTL]) on retinal nerve fiber layer thickness (RNFLT) abnormality marks by OCT machines. Methods: Cirrus OCT circumpapillary RNFLT measurements and Humphrey visual fields (HVF 24-2) of 421 patients from a large glaucoma clinic were included. Ellipses were fitted to the OD borders. Ellipse rotation relative to the vertical axis defined OD rotation. CRVTL was manually marked on the horizontal axis of the ellipse on the OCT fundus image. IAA was calculated between manually marked retinal artery locations at the 1.73mm radius around OD. Retinal curvature was determined by the inner limiting membrane on the horizontal B-scan closest to the OD center. For each location on the circumpapillary scanning area, logistic regression was used to determine if each of the four parameters had a significant impact on RNFLT abnormality marks independent of disease severity. The results are presented on spatial maps of the entire scanning area. Results: Variations in IAA significantly influenced abnormality marks on 38.8% of the total scanning area, followed by CRVTL (19.2%) and retinal curvature (18.7%). The effect of OD rotation was negligible (<1%). Conclusions: A natural variation in IAA, retinal curvature, and CRVTL can affect OCT abnormality ratings, which may bias clinical diagnosis. Our spatial maps may help OCT manufacturers to introduce location specific norms to ensure that abnormality marks indicate ocular disease instead of variations in eye anatomy.

Spatial, seasonal and climatic predictive models of Rift Valley fever disease across Africa.

PubMed

Redding, David W; Tiedt, Sonia; Lo Iacono, Gianni; Bett, Bernard; Jones, Kate E

2017-07-19

Understanding the emergence and subsequent spread of human infectious diseases is a critical global challenge, especially for high-impact zoonotic and vector-borne diseases. Global climate and land-use change are likely to alter host and vector distributions, but understanding the impact of these changes on the burden of infectious diseases is difficult. Here, we use a Bayesian spatial model to investigate environmental drivers of one of the most important diseases in Africa, Rift Valley fever (RVF). The model uses a hierarchical approach to determine how environmental drivers vary both spatially and seasonally, and incorporates the effects of key climatic oscillations, to produce a continental risk map of RVF in livestock (as a proxy for human RVF risk). We find RVF risk has a distinct seasonal spatial pattern influenced by climatic variation, with the majority of cases occurring in South Africa and Kenya in the first half of an El Niño year. Irrigation, rainfall and human population density were the main drivers of RVF cases, independent of seasonal, climatic or spatial variation. By accounting more subtly for the patterns in RVF data, we better determine the importance of underlying environmental drivers, and also make space- and time-sensitive predictions to better direct future surveillance resources.This article is part of the themed issue 'One Health for a changing world: zoonoses, ecosystems and human well-being'. © 2017 The Authors.

Spatial, seasonal and climatic predictive models of Rift Valley fever disease across Africa

PubMed Central

2017-01-01

Understanding the emergence and subsequent spread of human infectious diseases is a critical global challenge, especially for high-impact zoonotic and vector-borne diseases. Global climate and land-use change are likely to alter host and vector distributions, but understanding the impact of these changes on the burden of infectious diseases is difficult. Here, we use a Bayesian spatial model to investigate environmental drivers of one of the most important diseases in Africa, Rift Valley fever (RVF). The model uses a hierarchical approach to determine how environmental drivers vary both spatially and seasonally, and incorporates the effects of key climatic oscillations, to produce a continental risk map of RVF in livestock (as a proxy for human RVF risk). We find RVF risk has a distinct seasonal spatial pattern influenced by climatic variation, with the majority of cases occurring in South Africa and Kenya in the first half of an El Niño year. Irrigation, rainfall and human population density were the main drivers of RVF cases, independent of seasonal, climatic or spatial variation. By accounting more subtly for the patterns in RVF data, we better determine the importance of underlying environmental drivers, and also make space- and time-sensitive predictions to better direct future surveillance resources. This article is part of the themed issue ‘One Health for a changing world: zoonoses, ecosystems and human well-being’. PMID:28584173

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Linear functional minimization for inverse modeling

DOE PAGES

Barajas-Solano, David A.; Wohlberg, Brendt Egon; Vesselinov, Velimir Valentinov; ...

2015-06-01

In this paper, we present a novel inverse modeling strategy to estimate spatially distributed parameters of nonlinear models. The maximum a posteriori (MAP) estimators of these parameters are based on a likelihood functional, which contains spatially discrete measurements of the system parameters and spatiotemporally discrete measurements of the transient system states. The piecewise continuity prior for the parameters is expressed via Total Variation (TV) regularization. The MAP estimator is computed by minimizing a nonquadratic objective equipped with the TV operator. We apply this inversion algorithm to estimate hydraulic conductivity of a synthetic confined aquifer from measurements of conductivity and hydraulicmore » head. The synthetic conductivity field is composed of a low-conductivity heterogeneous intrusion into a high-conductivity heterogeneous medium. Our algorithm accurately reconstructs the location, orientation, and extent of the intrusion from the steady-state data only. Finally, addition of transient measurements of hydraulic head improves the parameter estimation, accurately reconstructing the conductivity field in the vicinity of observation locations.« less

Mapping the spatial and temporal dynamics of the velvet mesquite with MODIS and AVIRIS: Case study at the Santa Rita Experimental Range

NASA Astrophysics Data System (ADS)

Kaurivi, Jorry Zebby Ujama

The general objective of this research is to develop a methodology that will allow mapping and quantifying shrub encroachment with remote sensing. The multitemporal properties of the Moderate Resolution Imaging Spectroradiometer (MODIS) -250m, 16-day vegetation index products were combined with the hyperspectral and high spatial resolution (3.6m) computation of the Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) to detect the dynamics of mesquite and grass/soil matrix at two sites of high (19.5%) and low (5.7%) mesquite cover in the Santa Rita Experimental Range (SRER). MODIS results showed separability between grassland and mesquite based on phenology. Mesquite landscapes had longer green peak starting in April through February, while the grassland only peaked during the monsoon season (July through October). AVIRIS revealed spectral separability, but high variation in the data implicated high heterogeneity in the landscape. Nonetheless, the methodology for larger data was developed in this study and combines ground, air and satellite data.

Detecting the spatial and temporal variability of chlorophylla concentration and total suspended solids in Apalachicola Bay, Florida using MODIS imagery

USGS Publications Warehouse

Wang, Hongqing; Hladik, C.M.; Huang, W.; Milla, K.; Edmiston, L.; Harwell, M.A.; Schalles, J.F.

2010-01-01

Apalachicola Bay, Florida, accounts for 90% of Florida's and 10% of the nation's eastern oyster (Crassostrea virginica) harvesting. Chlorophyll-a concentration and total suspended solids (TSS) are two important water quality variables, among other environmental factors such as salinity, for eastern oyster production in Apalachicola Bay. In this research, we developed regression models of the relationships between the reflectance of the Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra 250 m data and the two water quality variables based on the Bay-wide field data collected during 14-17 October 2002, a relatively dry period, and 3-5 April 2006, a relatively wet period, respectively. Then we selected the best regression models (highest coefficient of determination, R2) to derive Bay-wide maps of chlorophylla concentration and TSS for the two periods. The MODIS-derived maps revealed large spatial and temporal variations in chlorophylla concentration and TSS across the entire Apalachicola Bay. ?? 2010 Taylor & Francis.

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

PubMed Central

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

2014-01-01

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

The Recombination Landscape in Wild House Mice Inferred Using Population Genomic Data.

PubMed

Booker, Tom R; Ness, Rob W; Keightley, Peter D

2017-09-01

Characterizing variation in the rate of recombination across the genome is important for understanding several evolutionary processes. Previous analysis of the recombination landscape in laboratory mice has revealed that the different subspecies have different suites of recombination hotspots. It is unknown, however, whether hotspots identified in laboratory strains reflect the hotspot diversity of natural populations or whether broad-scale variation in the rate of recombination is conserved between subspecies. In this study, we constructed fine-scale recombination rate maps for a natural population of the Eastern house mouse, Mus musculus castaneus We performed simulations to assess the accuracy of recombination rate inference in the presence of phase errors, and we used a novel approach to quantify phase error. The spatial distribution of recombination events is strongly positively correlated between our castaneus map, and a map constructed using inbred lines derived predominantly from M. m. domesticus Recombination hotspots in wild castaneus show little overlap, however, with the locations of double-strand breaks in wild-derived house mouse strains. Finally, we also find that genetic diversity in M. m. castaneus is positively correlated with the rate of recombination, consistent with pervasive natural selection operating in the genome. Our study suggests that recombination rate variation is conserved at broad scales between house mouse subspecies, but it is not strongly conserved at fine scales. Copyright © 2017 by the Genetics Society of America.

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

ERIC Educational Resources Information Center

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

2006-01-01

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

Spatial variability of total carbon and soil organic carbon in agricultural soils in Baranja region, Croatia

NASA Astrophysics Data System (ADS)

Bogunović, Igor; Trevisani, Sebastiano; Pereira, Paulo; Šeput, Miranda

2017-04-01

Climate change is expected to have an important influence on the crop production in agricultural regions. Soil carbon represents an important soil property that contributes to mitigate the negative influence of climate change on intensive cropped areas. Based on 5063 soil samples sampled from soil top layer (0-30 cm) we studied the spatial distribution of total carbon (TC) and soil organic carbon (SOC) content in various soil types (Anthrosols, Cambisols, Chernozems, Fluvisols, Gleysols, Luvisols) in Baranja region, Croatia. TC concentrations ranged from 2.10 to 66.15 mg/kg (with a mean of 16.31 mg/kg). SOC concentrations ranged from 1.86 to 58.00 mg/kg (with a mean of 13.35 mg/kg). TC and SOC showed moderate heterogeneity with coefficient of variation (CV) of 51.3% and 33.8%, respectively. Average concentrations of soil TC vary in function of soil types in the following decreasing order: Anthrosols (20.9 mg/kg) > Gleysols (19.3 mg/kg) > Fluvisols (15.6 mg/kg) > Chernozems (14.2 mg/kg) > Luvisols (12.6 mg/kg) > Cambisols (11.1 mg/kg), while SOC concentrations follow next order: Gleysols (15.4 mg/kg) > Fluvisols (13.2 mg/kg) = Anthrosols (13.2 mg/kg) > Chernozems (12.6 mg/kg) > Luvisols (11.4 mg/kg) > Cambisols (10.5 mg/kg). Performed geostatistical analysis of TC and SOC; both the experimental variograms as well as the interpolated maps reveal quite different spatial patterns of the two studied soil properties. The analysis of the spatial variability and of the spatial patterns of the produced maps show that SOC is likely influenced by antrophic processes. Spatial variability of SOC indicates soil health deterioration on an important significant portion of the studied area; this suggests the need for future adoption of environmentally friendly soil management in the Baranja region. Regional maps of TC and SOC provide quantitative information for regional planning and environmental monitoring and protection purposes.

Does spatial variation in environmental conditions affect recruitment? A study using a 3-D model of Peruvian anchovy

NASA Astrophysics Data System (ADS)

Xu, Yi; Rose, Kenneth A.; Chai, Fei; Chavez, Francisco P.; Ayón, Patricia

2015-11-01

We used a 3-dimensional individual-based model (3-D IBM) of Peruvian anchovy to examine how spatial variation in environmental conditions affects larval and juvenile growth and survival, and recruitment. Temperature, velocity, and phytoplankton and zooplankton concentrations generated from a coupled hydrodynamic Nutrients-Phytoplankton-Zooplankton-Detritus (NPZD) model, mapped to a three dimensional rectangular grid, were used to simulate anchovy populations. The IBM simulated individuals as they progressed from eggs to recruitment at 10 cm. Eggs and yolk-sac larvae were followed hourly through the processes of development, mortality, and movement (advection), and larvae and juveniles were followed daily through the processes of growth, mortality, and movement (advection plus behavior). A bioenergetics model was used to grow larvae and juveniles. The NPZD model provided prey fields which influence both food consumption rate as well as behavior mediated movement with individuals going to grids cells having optimal growth conditions. We compared predicted recruitment for monthly cohorts for 1990 through 2004 between the full 3-D IBM and a point (0-D) model that used spatially-averaged environmental conditions. The 3-D and 0-D versions generated similar interannual patterns in monthly recruitment for 1991-2004, with the 3-D results yielding consistently higher survivorship. Both versions successfully captured the very poor recruitment during the 1997-1998 El Niño event. Higher recruitment in the 3-D simulations was due to higher survival during the larval stage resulting from individuals searching for more favorable temperatures that lead to faster growth rates. The strong effect of temperature was because both model versions provided saturating food conditions for larval and juvenile anchovies. We conclude with a discussion of how explicit treatment of spatial variation affected simulated recruitment, other examples of fisheries modeling analyses that have used a similar approach to assess the influence of spatial variation, and areas for further model development.

Assessment of spatial variation in drinking water iodine and its implications for dietary intake: a new conceptual model for Denmark.

PubMed

Voutchkova, Denitza Dimitrova; Ernstsen, Vibeke; Hansen, Birgitte; Sørensen, Brian Lyngby; Zhang, Chaosheng; Kristiansen, Søren Munch

2014-09-15

Iodine is essential for human health. Many countries have therefore introduced universal salt iodising (USI) programmes to ensure adequate intake for the populations. However, little attention has been paid to subnational differences in iodine intake from drinking water caused by naturally occurring spatial variations. To address this issue, we here present the results of a Danish nationwide study of spatial trends of iodine in drinking water and the relevance of these trends for human dietary iodine intake. The data consist of treated drinking water samples from 144 waterworks, representing approx. 45% of the groundwater abstraction for drinking water supply in Denmark. The samples were analysed for iodide, iodate, total iodine (TI) and other major and trace elements. The spatial patterns were investigated with Local Moran's I. TI ranges from <0.2 to 126 μg L(-1) (mean 14.4 μg L(-1), median 11.9 μg L(-1)). Six speciation combinations were found. Half of the samples (n = 71) contain organic iodine; all species were detected in approx. 27% of all samples. The complex spatial variation is attributed both to the geology and the groundwater treatment. TI >40 μg L(-1) originates from postglacial marine and glacial meltwater sand and from Campanian-Maastrichtian chalk aquifers. The estimated drinking water contribution to human intake varies from 0% to >100% of the WHO recommended daily iodine intake for adults and from 0% to approx. 50% for adolescents. The paper presents a new conceptual model based on the observed clustering of high or low drinking-water iodine concentrations, delimiting zones with potentially deficient, excessive or optimal iodine status. Our findings suggest that the present coarse-scale nationwide programme for monitoring the population's iodine status may not offer a sufficiently accurate picture. Local variations in drinking-water iodine should be mapped and incorporated into future adjustment of the monitoring and/or the USI programmes. Copyright © 2014 Elsevier B.V. All rights reserved.

Estimation of the high-spatial-resolution variability in extreme wind speeds for forestry applications

NASA Astrophysics Data System (ADS)

Venäläinen, Ari; Laapas, Mikko; Pirinen, Pentti; Horttanainen, Matti; Hyvönen, Reijo; Lehtonen, Ilari; Junila, Päivi; Hou, Meiting; Peltola, Heli M.

2017-07-01

The bioeconomy has an increasing role to play in climate change mitigation and the sustainable development of national economies. In Finland, a forested country, over 50 % of the current bioeconomy relies on the sustainable management and utilization of forest resources. Wind storms are a major risk that forests are exposed to and high-spatial-resolution analysis of the most vulnerable locations can produce risk assessment of forest management planning. In this paper, we examine the feasibility of the wind multiplier approach for downscaling of maximum wind speed, using 20 m spatial resolution CORINE land-use dataset and high-resolution digital elevation data. A coarse spatial resolution estimate of the 10-year return level of maximum wind speed was obtained from the ERA-Interim reanalyzed data. Using a geospatial re-mapping technique the data were downscaled to 26 meteorological station locations to represent very diverse environments. Applying a comparison, we find that the downscaled 10-year return levels represent 66 % of the observed variation among the stations examined. In addition, the spatial variation in wind-multiplier-downscaled 10-year return level wind was compared with the WAsP model-simulated wind. The heterogeneous test area was situated in northern Finland, and it was found that the major features of the spatial variation were similar, but in some locations, there were relatively large differences. The results indicate that the wind multiplier method offers a pragmatic and computationally feasible tool for identifying at a high spatial resolution those locations with the highest forest wind damage risks. It can also be used to provide the necessary wind climate information for wind damage risk model calculations, thus making it possible to estimate the probability of predicted threshold wind speeds for wind damage and consequently the probability (and amount) of wind damage for certain forest stand configurations.

The underlying processes of a soil mite metacommunity on a small scale.

PubMed

Dong, Chengxu; Gao, Meixiang; Guo, Chuanwei; Lin, Lin; Wu, Donghui; Zhang, Limin

2017-01-01

Metacommunity theory provides an understanding of how ecological processes regulate local community assemblies. However, few field studies have evaluated the underlying mechanisms of a metacommunity on a small scale through revealing the relative roles of spatial and environmental filtering in structuring local community composition. Based on a spatially explicit sampling design in 2012 and 2013, this study aims to evaluate the underlying processes of a soil mite metacommunity on a small spatial scale (50 m) in a temperate deciduous forest located at the Maoershan Ecosystem Research Station, Northeast China. Moran's eigenvector maps (MEMs) were used to model independent spatial variables. The relative importance of spatial (including trend variables, i.e., geographical coordinates, and broad- and fine-scale spatial variables) and environmental factors in driving the soil mite metacommunity was determined by variation partitioning. Mantel and partial Mantel tests and a redundancy analysis (RDA) were also used to identify the relative contributions of spatial and environmental variables. The results of variation partitioning suggested that the relatively large and significant variance was a result of spatial variables (including broad- and fine-scale spatial variables and trend), indicating the importance of dispersal limitation and autocorrelation processes. The significant contribution of environmental variables was detected in 2012 based on a partial Mantel test, and soil moisture and soil organic matter were especially important for the soil mite metacommunity composition in both years. The study suggested that the soil mite metacommunity was primarily regulated by dispersal limitation due to broad-scale and neutral biotic processes at a fine-scale and that environmental filtering might be of subordinate importance. In conclusion, a combination of metacommunity perspectives between neutral and species sorting theories was suggested to be important in the observed structure of the soil mite metacommunity at the studied small scale.

The underlying processes of a soil mite metacommunity on a small scale

PubMed Central

Guo, Chuanwei; Lin, Lin; Wu, Donghui; Zhang, Limin

2017-01-01

Metacommunity theory provides an understanding of how ecological processes regulate local community assemblies. However, few field studies have evaluated the underlying mechanisms of a metacommunity on a small scale through revealing the relative roles of spatial and environmental filtering in structuring local community composition. Based on a spatially explicit sampling design in 2012 and 2013, this study aims to evaluate the underlying processes of a soil mite metacommunity on a small spatial scale (50 m) in a temperate deciduous forest located at the Maoershan Ecosystem Research Station, Northeast China. Moran’s eigenvector maps (MEMs) were used to model independent spatial variables. The relative importance of spatial (including trend variables, i.e., geographical coordinates, and broad- and fine-scale spatial variables) and environmental factors in driving the soil mite metacommunity was determined by variation partitioning. Mantel and partial Mantel tests and a redundancy analysis (RDA) were also used to identify the relative contributions of spatial and environmental variables. The results of variation partitioning suggested that the relatively large and significant variance was a result of spatial variables (including broad- and fine-scale spatial variables and trend), indicating the importance of dispersal limitation and autocorrelation processes. The significant contribution of environmental variables was detected in 2012 based on a partial Mantel test, and soil moisture and soil organic matter were especially important for the soil mite metacommunity composition in both years. The study suggested that the soil mite metacommunity was primarily regulated by dispersal limitation due to broad-scale and neutral biotic processes at a fine-scale and that environmental filtering might be of subordinate importance. In conclusion, a combination of metacommunity perspectives between neutral and species sorting theories was suggested to be important in the observed structure of the soil mite metacommunity at the studied small scale. PMID:28481906

The ST environment: Expected charged particle radiation levels

NASA Technical Reports Server (NTRS)

Stassinopoulos, E. G.

1978-01-01

The external (surface incident) charged particle radiation, predicted for the ST satellite at the three different mission altitudes, was determined in two ways: (1) by orbital flux-integration and (2) by geographical instantaneous flux-mapping. The latest standard models of the environment were used in this effort. Magnetic field definitions for three nominal circular trajectories and for the geographic mapping positions were obtained from a current field model. Spatial and temporal variations or conditions affecting the static environment models were considered and accounted for, wherever possible. Limited shielding and dose evaluations were performed for a simple geometry. Results, given in tabular and graphical form, are analyzed, explained, and discussed. Conclusions are included.

Clinical high-resolution mapping of the proteoglycan-bound water fraction in articular cartilage of the human knee joint.

PubMed

Bouhrara, Mustapha; Reiter, David A; Sexton, Kyle W; Bergeron, Christopher M; Zukley, Linda M; Spencer, Richard G

2017-11-01

We applied our recently introduced Bayesian analytic method to achieve clinically-feasible in-vivo mapping of the proteoglycan water fraction (PgWF) of human knee cartilage with improved spatial resolution and stability as compared to existing methods. Multicomponent driven equilibrium single-pulse observation of T 1 and T 2 (mcDESPOT) datasets were acquired from the knees of two healthy young subjects and one older subject with previous knee injury. Each dataset was processed using Bayesian Monte Carlo (BMC) analysis incorporating a two-component tissue model. We assessed the performance and reproducibility of BMC and of the conventional analysis of stochastic region contraction (SRC) in the estimation of PgWF. Stability of the BMC analysis of PgWF was tested by comparing independent high-resolution (HR) datasets from each of the two young subjects. Unlike SRC, the BMC-derived maps from the two HR datasets were essentially identical. Furthermore, SRC maps showed substantial random variation in estimated PgWF, and mean values that differed from those obtained using BMC. In addition, PgWF maps derived from conventional low-resolution (LR) datasets exhibited partial volume and magnetic susceptibility effects. These artifacts were absent in HR PgWF images. Finally, our analysis showed regional variation in PgWF estimates, and substantially higher values in the younger subjects as compared to the older subject. BMC-mcDESPOT permits HR in-vivo mapping of PgWF in human knee cartilage in a clinically-feasible acquisition time. HR mapping reduces the impact of partial volume and magnetic susceptibility artifacts compared to LR mapping. Finally, BMC-mcDESPOT demonstrated excellent reproducibility in the determination of PgWF. Published by Elsevier Inc.

Multi-isotope tracers to investigate processes in the Elbe, Weser and Ems river catchment using B, Mo, Sr, and Pb isotope ratios assessed by MC ICP-MS

NASA Astrophysics Data System (ADS)

Irrgeher, Johanna; Reese, Anna; Zimmermann, Tristan; Prohaska, Thomas; Retzmann, Anika; Wieser, Michael E.; Zitek, Andreas; Proefrock, Daniel

2017-04-01

Environmental monitoring of complex ecosystems requires reliable sensitive techniques based on sound analytical strategies to identify the source, fate and sink of elements and matter. Isotopic signatures can serve to trace pathways by making use of specific isotopic fingermarks or to distinguish between natural and anthropogenic sources. The presented work shows the potential of using the isotopic variation of Sr, Pb (as well-established isotopic systems), Mo and B (as novel isotopic system) assessed by MC ICP-MS in water and sediment samples to study aquatic ecosystem transport processes. The isotopic variation of Sr, Pb, Mo and B was determined in different marine and estuarine compartments covering the catchment of the German Wadden Sea and its main tributaries, the Elbe, Weser and Ems River. The varying elemental concentrations, the complex matrix and the expected small variations in the isotopic composition required the development and application of reliable analytical measurement approaches as well as suited metrological data evaluation strategies. Aquatic isoscapes were created using ArcGIS® by relating spatial isotopic data with geographical and geological maps. The elemental and isotopic distribution maps show large variation for different parameters and also reflect the numerous impact factors (e.g. geology, anthropogenic sources) influencing the catchment area.

Lidar Investigation of Aerosol Pollution Distribution near a Coal Power Plant

NASA Technical Reports Server (NTRS)

Mitsev, TS.; Kolarov, G.

1992-01-01

Using aerosol lidars with high spatial and temporal resolution with the possibility of real-time data interpretation can solve a large number of ecological problems related to the aerosol-field distribution and variation and the structure of convective flows. Significantly less expensive specialized lidars are used in studying anthropogenic aerosols in the planetary boundary layer. Here, we present results of lidar measurements of the mass-concentration field around a coal-fired power plant with intensive local aerosol sources. We studied the pollution evolution as a function of the emission dynamics and the presence of retaining layers. The technique used incorporates complex analysis of three types of lidar mapping: horizontal map of the aerosol field, vertical cross-section map, and a series of profiles along a selected path. The lidar-sounding cycle was performed for the time of atmosphere's quasi-stationarity.

Hydrological networks and associated topographic variation as templates for the spatial organization of tropical forest vegetation.

PubMed

Detto, Matteo; Muller-Landau, Helene C; Mascaro, Joseph; Asner, Gregory P

2013-01-01

An understanding of the spatial variability in tropical forest structure and biomass, and the mechanisms that underpin this variability, is critical for designing, interpreting, and upscaling field studies for regional carbon inventories. We investigated the spatial structure of tropical forest vegetation and its relationship to the hydrological network and associated topographic structure across spatial scales of 10-1000 m using high-resolution maps of LiDAR-derived mean canopy profile height (MCH) and elevation for 4930 ha of tropical forest in central Panama. MCH was strongly associated with the hydrological network: canopy height was highest in areas of positive convexity (valleys, depressions) close to channels draining 1 ha or more. Average MCH declined strongly with decreasing convexity (transition to ridges, hilltops) and increasing distance from the nearest channel. Spectral analysis, performed with wavelet decomposition, showed that the variance in MCH had fractal similarity at scales of ∼30-600 m, and was strongly associated with variation in elevation, with peak correlations at scales of ∼250 m. Whereas previous studies of topographic correlates of tropical forest structure conducted analyses at just one or a few spatial grains, our study found that correlations were strongly scale-dependent. Multi-scale analyses of correlations of MCH with slope, aspect, curvature, and Laplacian convexity found that MCH was most strongly related to convexity measured at scales of 20-300 m, a topographic variable that is a good proxy for position with respect to the hydrological network. Overall, our results support the idea that, even in these mesic forests, hydrological networks and associated topographical variation serve as templates upon which vegetation is organized over specific ranges of scales. These findings constitute an important step towards a mechanistic understanding of these patterns, and can guide upscaling and downscaling.

Accelerated high-resolution photoacoustic tomography via compressed sensing

NASA Astrophysics Data System (ADS)

Arridge, Simon; Beard, Paul; Betcke, Marta; Cox, Ben; Huynh, Nam; Lucka, Felix; Ogunlade, Olumide; Zhang, Edward

2016-12-01

Current 3D photoacoustic tomography (PAT) systems offer either high image quality or high frame rates but are not able to deliver high spatial and temporal resolution simultaneously, which limits their ability to image dynamic processes in living tissue (4D PAT). A particular example is the planar Fabry-Pérot (FP) photoacoustic scanner, which yields high-resolution 3D images but takes several minutes to sequentially map the incident photoacoustic field on the 2D sensor plane, point-by-point. However, as the spatio-temporal complexity of many absorbing tissue structures is rather low, the data recorded in such a conventional, regularly sampled fashion is often highly redundant. We demonstrate that combining model-based, variational image reconstruction methods using spatial sparsity constraints with the development of novel PAT acquisition systems capable of sub-sampling the acoustic wave field can dramatically increase the acquisition speed while maintaining a good spatial resolution: first, we describe and model two general spatial sub-sampling schemes. Then, we discuss how to implement them using the FP interferometer and demonstrate the potential of these novel compressed sensing PAT devices through simulated data from a realistic numerical phantom and through measured data from a dynamic experimental phantom as well as from in vivo experiments. Our results show that images with good spatial resolution and contrast can be obtained from highly sub-sampled PAT data if variational image reconstruction techniques that describe the tissues structures with suitable sparsity-constraints are used. In particular, we examine the use of total variation (TV) regularization enhanced by Bregman iterations. These novel reconstruction strategies offer new opportunities to dramatically increase the acquisition speed of photoacoustic scanners that employ point-by-point sequential scanning as well as reducing the channel count of parallelized schemes that use detector arrays.

Spatial variability of soil carbon, pH, available phosphorous and potassium in organic farm located in Mediterranean Croatia

NASA Astrophysics Data System (ADS)

Bogunović, Igor; Pereira, Paulo; Šeput, Miranda

2016-04-01

Soil organic carbon (SOC), pH, available phosphorus (P), and potassium (K) are some of the most important factors to soil fertility. These soil parameters are highly variable in space and time, with implications to crop production. The aim of this work is study the spatial variability of SOC, pH, P and K in an organic farm located in river Rasa valley (Croatia). A regular grid (100 x 100 m) was designed and 182 samples were collected on Silty Clay Loam soil. P, K and SOC showed moderate heterogeneity with coefficient of variation (CV) of 21.6%, 32.8% and 51.9%, respectively. Soil pH record low spatial variability with CV of 1.5%. Soil pH, P and SOC did not follow normal distribution. Only after a Box-Cox transformation, data respected the normality requirements. Directional exponential models were the best fitted and used to describe spatial autocorrelation. Soil pH, P and SOC showed strong spatial dependence with nugget to sill ratio with 13.78%, 0.00% and 20.29%, respectively. Only K recorded moderate spatial dependence. Semivariogram ranges indicate that future sampling interval could be 150 - 200 m in order to reduce sampling costs. Fourteen different interpolation models for mapping soil properties were tested. The method with lowest Root Mean Square Error was the most appropriated to map the variable. The results showed that radial basis function models (Spline with Tension and Completely Regularized Spline) for P and K were the best predictors, while Thin Plate Spline and inverse distance weighting models were the least accurate. The best interpolator for pH and SOC was the local polynomial with the power of 1, while the least accurate were Thin Plate Spline. According to soil nutrient maps investigated area record very rich supply with K while P supply was insufficient on largest part of area. Soil pH maps showed mostly neutral reaction while individual parts of alkaline soil indicate the possibility of penetration of seawater and salt accumulation in the soil profile. Future research should focus on spatial patterns on soil pH, electrical conductivity and sodium adsorption ratio. Keywords: geostatistics, semivariogram, interpolation models, soil chemical properties

A variational image-based approach to the correction of susceptibility artifacts in the alignment of diffusion weighted and structural MRI.

PubMed

Tao, Ran; Fletcher, P Thomas; Gerber, Samuel; Whitaker, Ross T

2009-01-01

This paper presents a method for correcting the geometric and greyscale distortions in diffusion-weighted MRI that result from inhomogeneities in the static magnetic field. These inhomogeneities may due to imperfections in the magnet or to spatial variations in the magnetic susceptibility of the object being imaged--so called susceptibility artifacts. Echo-planar imaging (EPI), used in virtually all diffusion weighted acquisition protocols, assumes a homogeneous static field, which generally does not hold for head MRI. The resulting distortions are significant, sometimes more than ten millimeters. These artifacts impede accurate alignment of diffusion images with structural MRI, and are generally considered an obstacle to the joint analysis of connectivity and structure in head MRI. In principle, susceptibility artifacts can be corrected by acquiring (and applying) a field map. However, as shown in the literature and demonstrated in this paper, field map corrections of susceptibility artifacts are not entirely accurate and reliable, and thus field maps do not produce reliable alignment of EPIs with corresponding structural images. This paper presents a new, image-based method for correcting susceptibility artifacts. The method relies on a variational formulation of the match between an EPI baseline image and a corresponding T2-weighted structural image but also specifically accounts for the physics of susceptibility artifacts. We derive a set of partial differential equations associated with the optimization, describe the numerical methods for solving these equations, and present results that demonstrate the effectiveness of the proposed method compared with field-map correction.

MAPPING SPATIAL ACCURACY AND ESTIMATING LANDSCAPE INDICATORS FROM THEMATIC LAND COVER MAPS USING FUZZY SET THEORY

EPA Science Inventory

The accuracy of thematic map products is not spatially homogenous, but instead variable across most landscapes. Properly analyzing and representing the spatial distribution (pattern) of thematic map accuracy would provide valuable user information for assessing appropriate applic...

Combining XCO2 Measurements Derived from SCIAMACHY and GOSAT for Potentially Generating Global CO2 Maps with High Spatiotemporal Resolution

PubMed Central

Wang, Tianxing; Shi, Jiancheng; Jing, Yingying; Zhao, Tianjie; Ji, Dabin; Xiong, Chuan

2014-01-01

Global warming induced by atmospheric CO2 has attracted increasing attention of researchers all over the world. Although space-based technology provides the ability to map atmospheric CO2 globally, the number of valid CO2 measurements is generally limited for certain instruments owing to the presence of clouds, which in turn constrain the studies of global CO2 sources and sinks. Thus, it is a potentially promising work to combine the currently available CO2 measurements. In this study, a strategy for fusing SCIAMACHY and GOSAT CO2 measurements is proposed by fully considering the CO2 global bias, averaging kernel, and spatiotemporal variations as well as the CO2 retrieval errors. Based on this method, a global CO2 map with certain UTC time can also be generated by employing the pattern of the CO2 daily cycle reflected by Carbon Tracker (CT) data. The results reveal that relative to GOSAT, the global spatial coverage of the combined CO2 map increased by 41.3% and 47.7% on a daily and monthly scale, respectively, and even higher when compared with that relative to SCIAMACHY. The findings in this paper prove the effectiveness of the combination method in supporting the generation of global full-coverage XCO2 maps with higher temporal and spatial sampling by jointly using these two space-based XCO2 datasets. PMID:25119468

Resource Needs and Pedagogical Value of Web Mapping for Spatial Thinking

ERIC Educational Resources Information Center

Manson, Steven; Shannon, Jerry; Eria, Sami; Kne, Len; Dyke, Kevin; Nelson, Sara; Batra, Lalit; Bonsal, Dudley; Kernik, Melinda; Immich, Jennifer; Matson, Laura

2014-01-01

Web mapping involves publishing and using maps via the Internet, and can range from presenting static maps to offering dynamic data querying and spatial analysis. Web mapping is seen as a promising way to support development of spatial thinking in the classroom but there are unanswered questions about how this promise plays out in reality. This…

Plant-based plume-scale mapping of tritium contamination in desert soils

USGS Publications Warehouse

Andraski, Brian J.; Stonestrom, David A.; Michel, R.L.; Halford, K.J.; Radyk, J.C.

2005-01-01

Plant-based techniques were tested for field-scale evaluation of tritium contamination adjacent to a low-level radioactive waste (LLRW) facility in the Amargosa Desert, Nevada. Objectives were to (i) characterize and map the spatial variability of tritium in plant water, (ii) develop empirical relations to predict and map subsurface contamination from plant-water concentrations, and (iii) gain insight into tritium migration pathways and processes. Plant sampling [creosote bush, Larrea tridentata (Sessé & Moc. ex DC.) Coville] required one-fifth the time of soil water vapor sampling. Plant concentrations were spatially correlated to a separation distance of 380 m; measurement uncertainty accounted for <0.1% of the total variability in the data. Regression equations based on plant tritium explained 96 and 90% of the variation in root-zone and sub-root-zone soil water vapor concentrations, respectively. The equations were combined with kriged plant-water concentrations to map subsurface contamination. Mapping showed preferential lateral movement of tritium through a dry, coarse-textured layer beneath the root zone, with concurrent upward movement through the root zone. Analysis of subsurface fluxes along a transect perpendicular to the LLRW facility showed that upward diffusive-vapor transport dominates other transport modes beneath native vegetation. Downward advective-liquid transport dominates at one endpoint of the transect, beneath a devegetated road immediately adjacent to the facility. To our knowledge, this study is the first to document large-scale subsurface vapor-phase tritium migration from a LLRW facility. Plant-based methods provide a noninvasive, cost-effective approach to mapping subsurface tritium migration in desert areas.

Residual delay maps unveil global patterns of atmospheric nonlinearity and produce improved local forecasts

PubMed Central

Sugihara, George; Casdagli, Martin; Habjan, Edward; Hess, Dale; Dixon, Paul; Holland, Greg

1999-01-01

We use residual-delay maps of observational field data for barometric pressure to demonstrate the structure of latitudinal gradients in nonlinearity in the atmosphere. Nonlinearity is weak and largely lacking in tropical and subtropical sites and increases rapidly into the temperate regions where the time series also appear to be much noisier. The degree of nonlinearity closely follows the meridional variation of midlatitude storm track frequency. We extract the specific functional form of this nonlinearity, a V shape in the lagged residuals that appears to be a basic feature of midlatitude synoptic weather systems associated with frontal passages. We present evidence that this form arises from the relative time scales of high-pressure versus low-pressure events. Finally, we show that this nonlinear feature is weaker in a well regarded numerical forecast model (European Centre for Medium-Range Forecasts) because small-scale temporal and spatial variation is smoothed out in the grided inputs. This is significant, in that it allows us to demonstrate how application of statistical corrections based on the residual-delay map may provide marked increases in local forecast accuracy, especially for severe weather systems. PMID:10588685

Surficial geology, structure, and thickness of selected geohydrologic units in the Columbia Plateau, Washington

USGS Publications Warehouse

Drost, B.W.; Whiteman, K.J.

1986-01-01

A 2-1/2 year study of the Columbia Plateau in Washington was begun in March 1982 to define spatial and temporal variations in dissolved sodium in the Columbia River Basalt Group aquifers and to relate these variations to the groundwater system and its geologic framework. This report describes the geologic framework , including the vertical and areal extent of the major basalt units, interbeds, and overlying materials. Thickness and structure of the Grande Ronde, Wanapum, and Saddle Mountains Basalts, thickness of the interbeds between the Grande Ronde and Wanapum, and Wanapum and Saddle Mountains Basalts, and thickness of the overburden were mapped at a scale of 1:500,000. Information was compiled from 2,500 well records using chemical analyses of core or drill chips, geophysical logs, and driller 's logs, in decreasing order of reliability. Surficial geology and surficial expression of structural features were simplified from published maps to provide maps with this information at the 1:500,000 scale. This report is intended to serve as a base for evaluating the distribution of dissolved sodium in basalt aquifers and as a base for future water resource studies. (USGS)

Association analysis between spatiotemporal variation of vegetation greenness and precipitation/temperature in the Yangtze River Basin (China).

PubMed

Cui, Lifang; Wang, Lunche; Singh, Ramesh P; Lai, Zhongping; Jiang, Liangliang; Yao, Rui

2018-05-23

The variation in vegetation greenness provides good understanding of the sustainable management and monitoring of land surface ecosystems. The present paper discusses the spatial-temporal changes in vegetation and controlling factors in the Yangtze River Basin (YRB) using Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) for the period 2001-2013. Theil-Sen Median trend analysis, Pearson correlation coefficients, and residual analysis have been used, which shows decreasing trend of the annual mean NDVI over the whole YRB. Spatially, the regions with significant decreasing trends were mainly located in parts of central YRB, and pronounced increasing trends were observed in parts of the eastern and western YRB. The mean NDVI during spring and summer seasons increased, while it decreased during autumn and winter seasons. The seasonal mean NDVI shows spatial heterogeneity due to the vegetation types. The correlation analysis shows a positive relation between NDVI and temperature over most of the YRB, whereas NDVI and precipitation show a negative correlation. The residual analysis shows an increase in NDVI in parts of eastern and western YRB and the decrease in NDVI in the small part of Yangtze River Delta (YRD) and the mid-western YRB due to human activities. In general, climate factors were the principal drivers of NDVI variation in YRB in recent years.

Ortho-Babinet polarization-interrogating filter: an interferometric approach to polarization measurement.

PubMed

Van Delden, Jay S

2003-07-15

A novel, interferometric, polarization-interrogating filter assembly and method for the simultaneous measurement of all four Stokes parameters across a partially polarized irradiance image in a no-moving-parts, instantaneous, highly sensitive manner is described. In the reported embodiment of the filter, two spatially varying linear retarders and a linear polarizer comprise an ortho-Babinet, polarization-interrogating (OBPI) filter. The OBPI filter uniquely encodes the incident ensemble of electromagnetic wave fronts comprising a partially polarized irradiance image in a controlled, deterministic, spatially varying manner to map the complete state of polarization across the image to local variations in a superposed interference pattern. Experimental interferograms are reported along with a numerical simulation of the method.

Inverse algorithms for 2D shallow water equations in presence of wet dry fronts: Application to flood plain dynamics

NASA Astrophysics Data System (ADS)

Monnier, J.; Couderc, F.; Dartus, D.; Larnier, K.; Madec, R.; Vila, J.-P.

2016-11-01

The 2D shallow water equations adequately model some geophysical flows with wet-dry fronts (e.g. flood plain or tidal flows); nevertheless deriving accurate, robust and conservative numerical schemes for dynamic wet-dry fronts over complex topographies remains a challenge. Furthermore for these flows, data are generally complex, multi-scale and uncertain. Robust variational inverse algorithms, providing sensitivity maps and data assimilation processes may contribute to breakthrough shallow wet-dry front dynamics modelling. The present study aims at deriving an accurate, positive and stable finite volume scheme in presence of dynamic wet-dry fronts, and some corresponding inverse computational algorithms (variational approach). The schemes and algorithms are assessed on classical and original benchmarks plus a real flood plain test case (Lèze river, France). Original sensitivity maps with respect to the (friction, topography) pair are performed and discussed. The identification of inflow discharges (time series) or friction coefficients (spatially distributed parameters) demonstrate the algorithms efficiency.

Identifying high production, low production and degraded rangelands in Senegal with normalized difference vegetation index data

USGS Publications Warehouse

Tappan, G. Gray; Wood, Lynette; Moore, Donald G.

1993-01-01

Seasonal herbaceous vegetation production on Senegal's native rangelands exhibits high spatial and temporal variability. This variability can be monitored using normalized difference vegetation index (NDVI) data computed from 1-km resolution Advanced Very High Resolution Radiometer (AVHRR) image data. Although annual fluctuations in rainfall account for some of the variability, numerous long-term production patterns are evident in the AVHRR time-series data. Different n productivity reflect variations in the region's climate, topography, soils, and land use. Areas of overgrazing and intensive cultivation have caused long-term soil and vegetation degradation. Rangelands of high and low productivity, and degraded rangelands were identified using NDVI. Time-series image data from 1987 though 1992 were used to map relative rangeland productivity. The results were compared to detailed resource maps on soils, vegetation and land use. Much of the variation in rangeland productivity correlated well to the known distribution of resources. The study developed an approach that identified a number of areas of degraded soils and low vegetation production.

Nature, formation, and distribution of carbonates on Ceres.

PubMed

Carrozzo, Filippo Giacomo; De Sanctis, Maria Cristina; Raponi, Andrea; Ammannito, Eleonora; Castillo-Rogez, Julie; Ehlmann, Bethany L; Marchi, Simone; Stein, Nathaniel; Ciarniello, Mauro; Tosi, Federico; Capaccioni, Fabrizio; Capria, Maria Teresa; Fonte, Sergio; Formisano, Michelangelo; Frigeri, Alessandro; Giardino, Marco; Longobardo, Andrea; Magni, Gianfranco; Palomba, Ernesto; Zambon, Francesca; Raymond, Carol A; Russell, Christopher T

2018-03-01

Different carbonates have been detected on Ceres, and their abundance and spatial distribution have been mapped using a visible and infrared mapping spectrometer (VIR), the Dawn imaging spectrometer. Carbonates are abundant and ubiquitous across the surface, but variations in the strength and position of infrared spectral absorptions indicate variations in the composition and amount of these minerals. Mg-Ca carbonates are detected all over the surface, but localized areas show Na carbonates, such as natrite (Na 2 CO 3 ) and hydrated Na carbonates (for example, Na 2 CO 3 ·H 2 O). Their geological settings and accessory NH 4 -bearing phases suggest the upwelling, excavation, and exposure of salts formed from Na-CO 3 -NH 4 -Cl brine solutions at multiple locations across the planet. The presence of the hydrated carbonates indicates that their formation/exposure on Ceres' surface is geologically recent and dehydration to the anhydrous form (Na 2 CO 3 ) is ongoing, implying a still-evolving body.

Spatial and seasonal characterization of net primary productivity and climate variables in southeastern China using MODIS data*

PubMed Central

Peng, Dai-liang; Huang, Jing-feng; Huete, Alfredo R.; Yang, Tai-ming; Gao, Ping; Chen, Yan-chun; Chen, Hui; Li, Jun; Liu, Zhan-yu

2010-01-01

We developed a sophisticated method to depict the spatial and seasonal characterization of net primary productivity (NPP) and climate variables. The role of climate variability in the seasonal variation of NPP exerts delayed and continuous effects. This study expands on this by mapping the seasonal characterization of NPP and climate variables from space using geographic information system (GIS) technology at the pixel level. Our approach was developed in southeastern China using moderate-resolution imaging spectroradiometer (MODIS) data. The results showed that air temperature, precipitation and sunshine percentage contributed significantly to seasonal variation of NPP. In the northern portion of the study area, a significant positive 32-d lagged correlation was observed between seasonal variation of NPP and climate (P<0.01), and the influences of changing climate on NPP lasted for 48 d or 64 d. In central southeastern China, NPP showed 16-d, 48-d, and 96-d lagged correlation with air temperature, precipitation, and sunshine percentage, respectively (P<0.01); the influences of air temperature and precipitation on NPP lasted for 48 d or 64 d, while sunshine influence on NPP only persisted for 16 d. Due to complex topography and vegetation distribution in the southern part of the study region, the spatial patterns of vegetation-climate relationship became complicated and diversiform, especially for precipitation influences on NPP. In the northern part of the study area, all vegetation NPP had an almost similar response to seasonal variation of air temperature except for broad crops. The impacts of seasonal variation of precipitation and sunshine on broad and cereal crop NPP were slightly different from other vegetation NPP. PMID:20349524

Spatial Mapping of the Mobility-Lifetime (microtau) Production in Cadmium Zinc Telluride Nuclear Radiation Detectors Using Transport Imaging

DTIC Science & Technology

2013-06-01

Under the influence of an electrical field, these electrons and holes migrate to their respective electrodes, where they are collected and...an electrical response which translates to an intensity reading on the detector’s readout meter. Since high-resolution detector materials are the...magnitude of three factors: inherent statistical variation of the electric signal measured at the detector’s contacts (Fano noise ∆EF), random electron

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Evidence of Water Quality Degradation in Lower Mekong Basin Revealed by Self-Organizing Map

PubMed Central

Chea, Ratha; Grenouillet, Gaël; Lek, Sovan

2016-01-01

To reach a better understanding of the spatial variability of water quality in the Lower Mekong Basin (LMB), the Self-Organizing Map (SOM) was used to classify 117 monitoring sites and hotspots of pollution within the basin identified according to water quality indicators and US-EPA guidelines. Four different clusters were identified based on their similar physicochemical characteristics. The majority of sites in upper (Laos and Thailand) and middle part (Cambodia) of the basin were grouped in two clusters, considered as good quality water with high DO and low nutrient levels. The other two clusters were mostly composed of sites in Mekong delta (Vietnam) and few sites in upstream tributaries (i.e., northwestern Thailand, Tonle Sap Lake, and swamps close to Vientiane), known for moderate to poor quality of water and characterized by high nutrient and dissolved solid levels. Overall, we found that the water in the mainstream was less polluted than its tributaries; eutrophication and salinity could be key factors affecting water quality in LMB. Moreover, the seasonal variation of water quality seemed to be less marked than spatial variation occurring along the longitudinal gradient of Mekong River. Significant degradations were mainly associated with human disturbance and particularly apparent in sites distributed along the man-made canals in Vietnam delta where population growth and agricultural development are intensive. PMID:26731522

Towards a street-level pollen concentration and exposure forecast

NASA Astrophysics Data System (ADS)

van der Molen, Michiel; Krol, Maarten; van Vliet, Arnold; Heuvelink, Gerard

2015-04-01

Atmospheric pollen are an increasing source of nuisance for people in industrialised countries and are associated with significant cost of medication and sick leave. Citizen pollen warnings are often based on emission mapping based on local temperature sum approaches or on long-range atmospheric model approaches. In practise, locally observed pollen may originate from both local sources (plants in streets and gardens) and from long-range transport. We argue that making this distinction is relevant because the diurnal and spatial variation in pollen concentrations is much larger for pollen from local sources than for pollen from long-range transport due to boundary layer processes. This may have an important impact on exposure of citizens to pollen and on mitigation strategies. However, little is known about the partitioning of pollen into local and long-range origin categories. Our objective is to study how the concentrations of pollen from different sources vary temporally and spatially, and how the source region influences exposure and mitigation strategies. We built a Hay Fever Forecast system (HFF) based on WRF-chem, Allergieradar.nl, and geo-statistical downscaling techniques. HFF distinguishes between local (individual trees) and regional sources (based on tree distribution maps). We show first results on how the diurnal variation of pollen concentrations depends on source proximity. Ultimately, we will compare the model with local pollen counts, patient nuisance scores and medicine use.

Multiscale reconstruction for MR fingerprinting.

PubMed

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

2016-06-01

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

Spatial variations in the incidence of breast cancer and potential risks associated with soil dioxin contamination in Midland, Saginaw, and Bay Counties, Michigan, USA

PubMed Central

Dai, Dajun; Oyana, Tonny J

2008-01-01

Background High levels of dioxins in soil and higher-than-average body burdens of dioxins in local residents have been found in the city of Midland and the Tittabawassee River floodplain in Michigan. The objective of this study is threefold: (1) to evaluate dioxin levels in soils; (2) to evaluate the spatial variations in breast cancer incidence in Midland, Saginaw, and Bay Counties in Michigan; (3) to evaluate whether breast cancer rates are spatially associated with the dioxin contamination areas. Methods We acquired 532 published soil dioxin data samples collected from 1995 to 2003 and data pertaining to female breast cancer cases (n = 4,604) at ZIP code level in Midland, Saginaw, and Bay Counties for years 1985 through 2002. Descriptive statistics and self-organizing map algorithm were used to evaluate dioxin levels in soils. Geographic information systems techniques, the Kulldorff's spatial and space-time scan statistics, and genetic algorithms were used to explore the variation in the incidence of breast cancer in space and space-time. Odds ratio and their corresponding 95% confidence intervals, with adjustment for age, were used to investigate a spatial association between breast cancer incidence and soil dioxin contamination. Results High levels of dioxin in soils were observed in the city of Midland and the Tittabawassee River 100-year floodplain. After adjusting for age, we observed high breast cancer incidence rates and detected the presence of spatial clusters in the city of Midland, the confluence area of the Tittabawassee, and Saginaw Rivers. After accounting for spatiotemporal variations, we observed a spatial cluster of breast cancer incidence in Midland between 1985 and 1993. The odds ratio further suggests a statistically significant (α = 0.05) increased breast cancer rate as women get older, and a higher disease burden in Midland and the surrounding areas in close proximity to the dioxin contaminated areas. Conclusion These findings suggest that increased breast cancer incidences are spatially associated with soil dioxin contamination. Aging is a substantial factor in the development of breast cancer. Findings can be used for heightened surveillance and education, as well as formulating new study hypotheses for further research. PMID:18939976

Visualising recalcitrance by colocalisation of cellulase, lignin and cellulose in pretreated pine biomass using fluorescence microscopy

NASA Astrophysics Data System (ADS)

Donaldson, Lloyd; Vaidya, Alankar

2017-03-01

Mapping the location of bound cellulase enzymes provides information on the micro-scale distribution of amenable and recalcitrant sites in pretreated woody biomass for biofuel applications. The interaction of a fluorescently labelled cellulase enzyme cocktail with steam-exploded pine (SEW) was quantified using confocal microscopy. The spatial distribution of Dylight labelled cellulase was quantified relative to lignin (autofluorescence) and cellulose (Congo red staining) by measuring their colocalisation using Pearson correlations. Correlations were greater in cellulose-rich secondary cell walls compared to lignin-rich middle lamella but with significant variations among individual biomass particles. The distribution of cellulose in the pretreated biomass accounted for 30% of the variation in the distribution of enzyme after correcting for the correlation between lignin and cellulose. For the first time, colocalisation analysis was able to quantify the spatial distribution of amenable and recalcitrant sites in relation to the histochemistry of cellulose and lignin. This study will contribute to understanding the role of pretreatment in enzymatic hydrolysis of recalcitrant softwood biomass.

Low-Energy Electron Potentiometry: Contactless Imaging of Charge Transport on the Nanoscale.

PubMed

Kautz, J; Jobst, J; Sorger, C; Tromp, R M; Weber, H B; van der Molen, S J

2015-09-04

Charge transport measurements form an essential tool in condensed matter physics. The usual approach is to contact a sample by two or four probes, measure the resistance and derive the resistivity, assuming homogeneity within the sample. A more thorough understanding, however, requires knowledge of local resistivity variations. Spatially resolved information is particularly important when studying novel materials like topological insulators, where the current is localized at the edges, or quasi-two-dimensional (2D) systems, where small-scale variations can determine global properties. Here, we demonstrate a new method to determine spatially-resolved voltage maps of current-carrying samples. This technique is based on low-energy electron microscopy (LEEM) and is therefore quick and non-invasive. It makes use of resonance-induced contrast, which strongly depends on the local potential. We demonstrate our method using single to triple layer graphene. However, it is straightforwardly extendable to other quasi-2D systems, most prominently to the upcoming class of layered van der Waals materials.

Spatial resolution enhancement of satellite image data using fusion approach

NASA Astrophysics Data System (ADS)

Lestiana, H.; Sukristiyanti

2018-02-01

Object identification using remote sensing data has a problem when the spatial resolution is not in accordance with the object. The fusion approach is one of methods to solve the problem, to improve the object recognition and to increase the objects information by combining data from multiple sensors. The application of fusion image can be used to estimate the environmental component that is needed to monitor in multiple views, such as evapotranspiration estimation, 3D ground-based characterisation, smart city application, urban environments, terrestrial mapping, and water vegetation. Based on fusion application method, the visible object in land area has been easily recognized using the method. The variety of object information in land area has increased the variation of environmental component estimation. The difficulties in recognizing the invisible object like Submarine Groundwater Discharge (SGD), especially in tropical area, might be decreased by the fusion method. The less variation of the object in the sea surface temperature is a challenge to be solved.

Assessment of the spatio-temporal distribution of soil properties in East Kolkata wetland ecosystem (A Ramsar site: 1208)

NASA Astrophysics Data System (ADS)

Pal, S.; Manna, S.; Aich, A.; Chattopadhyay, B.; Mukhopadhyay, S. K.

2014-06-01

The present investigation was made to characterize spatial and temporal variations in soil properties and to evaluate possible differences that could be dependent on the tannery effluent discharges, municipal sewage discharges, vegetation cover, soil settlement rate, crop rotation, etc. Soil total organic matter (TOM), cations like, Sodium (Na), Ammonium (NH4), Potassium (K), Calcium (Ca) and Magnesium (Mg) contents in the bank soils and bottom sediments were recorded from seven different characteristic sites in East Kolkata wetland ecosystem, a Ramsar site (Ramsar site No. 1208). The profile maps were constructed by geostatistical methods to describe the spatial distribution as well as temporal variations of all the factors to identify the influences of composite wastewaters. The work was initiated to identify causes and consequences of the waste dumping in the concerned region for the past hundred years and thereby to suggest necessary precautionary measures to prevent further loss of soil quality.

Structured Spatial Modeling and Mapping of Domestic Violence Against Women of Reproductive Age in Rwanda.

PubMed

Habyarimana, Faustin; Zewotir, Temesgen; Ramroop, Shaun

2018-03-01

The main objective of this study was to assess the risk factors and spatial correlates of domestic violence against women of reproductive age in Rwanda. A structured spatial approach was used to account for the nonlinear nature of some covariates and the spatial variability on domestic violence. The nonlinear effect was modeled through second-order random walk, and the structured spatial effect was modeled through Gaussian Markov Random Fields specified as an intrinsic conditional autoregressive model. The data from the Rwanda Demographic and Health Survey 2014/2015 were used as an application. The findings of this study revealed that the risk factors of domestic violence against women are the wealth quintile of the household, the size of the household, the husband or partner's age, the husband or partner's level of education, ownership of the house, polygamy, the alcohol consumption status of the husband or partner, the woman's perception of wife-beating attitude, and the use of contraceptive methods. The study also highlighted the significant spatial variation of domestic violence against women at district level.

Spatial-temporal dynamics of NDVI and Chl-a concentration from 1998 to 2009 in the East coastal zone of China: integrating terrestrial and oceanic components.

PubMed

Hou, Xiyong; Li, Mingjie; Gao, Meng; Yu, Liangju; Bi, Xiaoli

2013-01-01

Annual normalized difference vegetation index (NDVI) and chlorophyll-a (Chl-a) concentration are the most important large-scale indicators of terrestrial and oceanic ecosystem net primary productivity. In this paper, the Sea-viewing Wide Field-of-view Sensor level 3 standard mapped image annual products from 1998 to 2009 are used to study the spatial-temporal characters of terrestrial NDVI and oceanic Chl-a concentration on two sides of the coastline of China by using the methods of mean value (M), coefficient of variation (CV), the slope of unary linear regression model (Slope), and the Hurst index (H). In detail, we researched and analyzed the spatial-temporal dynamics, the longitudinal zonality and latitudinal zonality, the direction, intensity, and persistency of historical changes. The results showed that: (1) spatial patterns of M and CV between NDVI and Chl-a concentration from 1998 to 2009 were very different. The dynamic variation of terrestrial NDVI was much mild, while the variation of oceanic Chl-a concentration was relatively much larger; (2) distinct longitudinal zonality was found for Chl-a concentration and NDVI due to their hypersensitivity to the distance to shoreline, and strong latitudinal zonality existed for Chl-a concentration while terrestrial NDVI had a very weak latitudinal zonality; (3) overall, the NDVI showed a slight decreasing trend while the Chl-a concentration showed a significant increasing trend in the past 12 years, and both of them exhibit strong self-similarity and long-range dependence which indicates opposite future trends between land and ocean.

Distribution and spatial variation of hydrothermal faunal assemblages at Lucky Strike (Mid-Atlantic Ridge) revealed by high-resolution video image analysis

NASA Astrophysics Data System (ADS)

Cuvelier, Daphne; Sarrazin, Jozée; Colaço, Ana; Copley, Jon; Desbruyères, Daniel; Glover, Adrian G.; Tyler, Paul; Serrão Santos, Ricardo

2009-11-01

Whilst the fauna inhabiting hydrothermal vent structures in the Atlantic Ocean is reasonably well known, less is understood about the spatial distributions of the fauna in relation to abiotic and biotic factors. In this study, a major active hydrothermal edifice (Eiffel Tower, at 1690 m depth) on the Lucky Strike vent field (Mid-Atlantic Ridge (MAR)) was investigated. Video transects were carried out by ROV Victor 6000 and complete image coverage was acquired. Four distinct assemblages, ranging from dense larger-sized Bathymodiolus mussel beds to smaller-sized mussel clumps and alvinocaridid shrimps, and two types of substrata were defined based on high definition photographs and video imagery. To evaluate spatial variation, faunal distribution was mapped in three dimensions. A high degree of patchiness characterizes this 11 m high sulfide structure. The differences observed in assemblage and substratum distribution were related to habitat characteristics (fluid exits, depth and structure orientation). Gradients in community structure were observed, which coincided with an increasing distance from the fluid exits. A biological zonation model for the Eiffel Tower edifice was created in which faunal composition and distribution can be visually explained by the presence/absence of fluid exits.

A robust multi-shot scan strategy for high-resolution diffusion weighted MRI enabled by multiplexed sensitivity-encoding (MUSE)

PubMed Central

Chen, Nan-kuei; Guidon, Arnaud; Chang, Hing-Chiu; Song, Allen W.

2013-01-01

Diffusion weighted magnetic resonance imaging (DWI) data have been mostly acquired with single-shot echo-planar imaging (EPI) to minimize motion induced artifacts. The spatial resolution, however, is inherently limited in single-shot EPI, even when the parallel imaging (usually at an acceleration factor of 2) is incorporated. Multi-shot acquisition strategies could potentially achieve higher spatial resolution and fidelity, but they are generally susceptible to motion-induced phase errors among excitations that are exacerbated by diffusion sensitizing gradients, rendering the reconstructed images unusable. It has been shown that shot-to-shot phase variations may be corrected using navigator echoes, but at the cost of imaging throughput. To address these challenges, a novel and robust multi-shot DWI technique, termed multiplexed sensitivity-encoding (MUSE), is developed here to reliably and inherently correct nonlinear shot-to-shot phase variations without the use of navigator echoes. The performance of the MUSE technique is confirmed experimentally in healthy adult volunteers on 3 Tesla MRI systems. This newly developed technique should prove highly valuable for mapping brain structures and connectivities at high spatial resolution for neuroscience studies. PMID:23370063

A weighted variational gradient-based fusion method for high-fidelity thin cloud removal of Landsat images

NASA Astrophysics Data System (ADS)

Huang, Wei; Chen, Xiu; Wang, Yueyun

2018-03-01

Landsat data are widely used in various earth observations, but the clouds interfere with the applications of the images. This paper proposes a weighted variational gradient-based fusion method (WVGBF) for high-fidelity thin cloud removal of Landsat images, which is an improvement of the variational gradient-based fusion (VGBF) method. The VGBF method integrates the gradient information from the reference band into visible bands of cloudy image to enable spatial details and remove thin clouds. The VGBF method utilizes the same gradient constraints to the entire image, which causes the color distortion in cloudless areas. In our method, a weight coefficient is introduced into the gradient approximation term to ensure the fidelity of image. The distribution of weight coefficient is related to the cloud thickness map. The map is built on Independence Component Analysis (ICA) by using multi-temporal Landsat images. Quantitatively, we use R value to evaluate the fidelity in the cloudless regions and metric Q to evaluate the clarity in the cloud areas. The experimental results indicate that the proposed method has the better ability to remove thin cloud and achieve high fidelity.

Joint reconstruction of dynamic PET activity and kinetic parametric images using total variation constrained dictionary sparse coding

NASA Astrophysics Data System (ADS)

Yu, Haiqing; Chen, Shuhang; Chen, Yunmei; Liu, Huafeng

2017-05-01

Dynamic positron emission tomography (PET) is capable of providing both spatial and temporal information of radio tracers in vivo. In this paper, we present a novel joint estimation framework to reconstruct temporal sequences of dynamic PET images and the coefficients characterizing the system impulse response function, from which the associated parametric images of the system macro parameters for tracer kinetics can be estimated. The proposed algorithm, which combines statistical data measurement and tracer kinetic models, integrates a dictionary sparse coding (DSC) into a total variational minimization based algorithm for simultaneous reconstruction of the activity distribution and parametric map from measured emission sinograms. DSC, based on the compartmental theory, provides biologically meaningful regularization, and total variation regularization is incorporated to provide edge-preserving guidance. We rely on techniques from minimization algorithms (the alternating direction method of multipliers) to first generate the estimated activity distributions with sub-optimal kinetic parameter estimates, and then recover the parametric maps given these activity estimates. These coupled iterative steps are repeated as necessary until convergence. Experiments with synthetic, Monte Carlo generated data, and real patient data have been conducted, and the results are very promising.

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

Li, Yan-Rong; Wang, Jian-Min; Bai, Jin-Ming, E-mail: liyanrong@mail.ihep.ac.cn

Broad emission lines of active galactic nuclei stem from a spatially extended region (broad-line region, BLR) that is composed of discrete clouds and photoionized by the central ionizing continuum. The temporal behaviors of these emission lines are blurred echoes of continuum variations (i.e., reverberation mapping, RM) and directly reflect the structures and kinematic information of BLRs through the so-called transfer function (also known as the velocity-delay map). Based on the previous works of Rybicki and Press and Zu et al., we develop an extended, non-parametric approach to determine the transfer function for RM data, in which the transfer function ismore » expressed as a sum of a family of relatively displaced Gaussian response functions. Therefore, arbitrary shapes of transfer functions associated with complicated BLR geometry can be seamlessly included, enabling us to relax the presumption of a specified transfer function frequently adopted in previous studies and to let it be determined by observation data. We formulate our approach in a previously well-established framework that incorporates the statistical modeling of continuum variations as a damped random walk process and takes into account long-term secular variations which are irrelevant to RM signals. The application to RM data shows the fidelity of our approach.« less

Sun-induced fluorescence - a new probe of photosynthesis: First maps from the imaging spectrometer HyPlant.

PubMed

Rascher, U; Alonso, L; Burkart, A; Cilia, C; Cogliati, S; Colombo, R; Damm, A; Drusch, M; Guanter, L; Hanus, J; Hyvärinen, T; Julitta, T; Jussila, J; Kataja, K; Kokkalis, P; Kraft, S; Kraska, T; Matveeva, M; Moreno, J; Muller, O; Panigada, C; Pikl, M; Pinto, F; Prey, L; Pude, R; Rossini, M; Schickling, A; Schurr, U; Schüttemeyer, D; Verrelst, J; Zemek, F

2015-12-01

Variations in photosynthesis still cause substantial uncertainties in predicting photosynthetic CO2 uptake rates and monitoring plant stress. Changes in actual photosynthesis that are not related to greenness of vegetation are difficult to measure by reflectance based optical remote sensing techniques. Several activities are underway to evaluate the sun-induced fluorescence signal on the ground and on a coarse spatial scale using space-borne imaging spectrometers. Intermediate-scale observations using airborne-based imaging spectroscopy, which are critical to bridge the existing gap between small-scale field studies and global observations, are still insufficient. Here we present the first validated maps of sun-induced fluorescence in that critical, intermediate spatial resolution, employing the novel airborne imaging spectrometer HyPlant. HyPlant has an unprecedented spectral resolution, which allows for the first time quantifying sun-induced fluorescence fluxes in physical units according to the Fraunhofer Line Depth Principle that exploits solar and atmospheric absorption bands. Maps of sun-induced fluorescence show a large spatial variability between different vegetation types, which complement classical remote sensing approaches. Different crop types largely differ in emitting fluorescence that additionally changes within the seasonal cycle and thus may be related to the seasonal activation and deactivation of the photosynthetic machinery. We argue that sun-induced fluorescence emission is related to two processes: (i) the total absorbed radiation by photosynthetically active chlorophyll; and (ii) the functional status of actual photosynthesis and vegetation stress. © 2015 John Wiley & Sons Ltd.

Imaging viscoelastic properties of live cells by AFM: power-law rheology on the nanoscale.

PubMed

Hecht, Fabian M; Rheinlaender, Johannes; Schierbaum, Nicolas; Goldmann, Wolfgang H; Fabry, Ben; Schäffer, Tilman E

2015-06-21

We developed force clamp force mapping (FCFM), an atomic force microscopy (AFM) technique for measuring the viscoelastic creep behavior of live cells with sub-micrometer spatial resolution. FCFM combines force-distance curves with an added force clamp phase during tip-sample contact. From the creep behavior measured during the force clamp phase, quantitative viscoelastic sample properties are extracted. We validate FCFM on soft polyacrylamide gels. We find that the creep behavior of living cells conforms to a power-law material model. By recording short (50-60 ms) force clamp measurements in rapid succession, we generate, for the first time, two-dimensional maps of power-law exponent and modulus scaling parameter. Although these maps reveal large spatial variations of both parameters across the cell surface, we obtain robust mean values from the several hundreds of measurements performed on each cell. Measurements on mouse embryonic fibroblasts show that the mean power-law exponents and the mean modulus scaling parameters differ greatly among individual cells, but both parameters are highly correlated: stiffer cells consistently show a smaller power-law exponent. This correlation allows us to distinguish between wild-type cells and cells that lack vinculin, a dominant protein of the focal adhesion complex, even though the mean values of viscoelastic properties between wildtype and knockout cells did not differ significantly. Therefore, FCFM spatially resolves viscoelastic sample properties and can uncover subtle mechanical signatures of proteins in living cells.

Estimating temporal changes in soil carbon stocks at ecoregional scale in Madagascar using remote-sensing

NASA Astrophysics Data System (ADS)

Grinand, C.; Maire, G. Le; Vieilledent, G.; Razakamanarivo, H.; Razafimbelo, T.; Bernoux, M.

2017-02-01

Soil organic carbon (SOC) plays an important role in climate change regulation notably through release of CO2 following land use change such a deforestation, but data on stock change levels are lacking. This study aims to empirically assess SOC stocks change between 1991 and 2011 at the landscape scale using easy-to-access spatially-explicit environmental factors. The study area was located in southeast Madagascar, in a region that exhibits very high rate of deforestation and which is characterized by both humid and dry climates. We estimated SOC stock on 0.1 ha plots for 95 different locations in a 43,000 ha reference area covering both dry and humid conditions and representing different land cover including natural forest, cropland, pasture and fallows. We used the Random Forest algorithm to find out the environmental factors explaining the spatial distribution of SOC. We then predicted SOC stocks for two soil layers at 30 cm and 100 cm over a wider area of 395,000 ha. By changing the soil and vegetation indices derived from remote sensing images we were able to produce SOC maps for 1991 and 2011. Those estimates and their related uncertainties where combined in a post-processing step to map estimates of significant SOC variations and we finally compared the SOC change map with published deforestation maps. Results show that the geologic variables, precipitation, temperature, and soil-vegetation status were strong predictors of SOC distribution at regional scale. We estimated an average net loss of 10.7% and 5.2% for the 30 cm and the 100 cm layers respectively for deforested areas in the humid area. Our results also suggest that these losses occur within the first five years following deforestation. No significant variations were observed for the dry region. This study provides new solutions and knowledge for a better integration of soil threats and opportunities in land management policies.

Spatial-Temporal Dynamics of Urban Fire Incidents: a Case Study of Nanjing, China

NASA Astrophysics Data System (ADS)

Yao, J.; Zhang, X.

2016-06-01

Fire and rescue service is one of the fundamental public services provided by government in order to protect people, properties and environment from fires and other disasters, and thus promote a safer living environment. Well understanding spatial-temporal dynamics of fire incidents can offer insights for potential determinants of various fire events and enable better fire risk estimation, assisting future allocation of prevention resources and strategic planning of mitigation programs. Using a 12-year (2002-2013) dataset containing the urban fire events in Nanjing, China, this research explores the spatial-temporal dynamics of urban fire incidents. A range of exploratory spatial data analysis (ESDA) approaches and tools, such as spatial kernel density and co-maps, are employed to examine the spatial, temporal and spatial-temporal variations of the fire events. Particular attention has been paid to two types of fire incidents: residential properties and local facilities, due to their relatively higher occurrence frequencies. The results demonstrated that the amount of urban fire has greatly increased in the last decade and spatial-temporal distribution of fire events vary among different incident types, which implies varying impact of potential influencing factors for further investigation.

Geographic Information System and Geoportal «River basins of the European Russia»

NASA Astrophysics Data System (ADS)

Yermolaev, O. P.; Mukharamova, S. S.; Maltsev, K. A.; Ivanov, M. A.; Ermolaeva, P. O.; Gayazov, A. I.; Mozzherin, V. V.; Kharchenko, S. V.; Marinina, O. A.; Lisetskii, F. N.

2018-01-01

Geographic Information System (GIS) and Geoportal with open access «River basins of the European Russia» were implemented. GIS and Geoportal are based on the map of basins of small rivers of the European Russia with information about natural and anthropogenic characteristics, namely geomorphometry of basins relief; climatic parameters, representing averages, variation, seasonal variation, extreme values of temperature and precipitation; land cover types; soil characteristics; type and subtype of landscape; population density. The GIS includes results of spatial analysis and modelling, in particular, assessment of anthropogenic impact on river basins; evaluation of water runoff and sediment runoff; climatic, geomorphological and landscape zoning for the European part of Russia.

Principal component and spatial correlation analysis of spectroscopic-imaging data in scanning probe microscopy.

PubMed

Jesse, Stephen; Kalinin, Sergei V

2009-02-25

An approach for the analysis of multi-dimensional, spectroscopic-imaging data based on principal component analysis (PCA) is explored. PCA selects and ranks relevant response components based on variance within the data. It is shown that for examples with small relative variations between spectra, the first few PCA components closely coincide with results obtained using model fitting, and this is achieved at rates approximately four orders of magnitude faster. For cases with strong response variations, PCA allows an effective approach to rapidly process, de-noise, and compress data. The prospects for PCA combined with correlation function analysis of component maps as a universal tool for data analysis and representation in microscopy are discussed.

Map Showing Seacliff Response to Climatic and Seismic Events, Seacliff State Beach, Santa Cruz County, California

USGS Publications Warehouse

Hapke, Cheryl J.; Richmond, Bruce M.; D'Iorio, Mimi M.

2002-01-01

INTRODUCTION The coastal cliffs along much of the central California coast are actively retreating. Large storms and periodic earthquakes are responsible for most of the documented seacliff slope failures. Long-term average erosion rates calculated for this section of coast (Moore and others, 1999) do not provide the spatial or temporal data resolution necessary to identify the processes responsible for retreat of the seacliffs, where episodic retreat threatens homes and community infrastructure. Research suggests that more erosion occurs along the California coast over a short time scale, during periods of severe storms or seismic activity, than occurs during decades of normal weather or seismic quiescence (Griggs and Scholar, 1998; Griggs, 1994; Plant and Griggs, 1990; Griggs and Johnson, 1979 and 1983; Kuhn and Shepard, 1979). This is the second map in a series of maps documenting the processes of short-term seacliff retreat through the identification of slope failure styles, spatial variability of failures, and temporal variation in retreat amounts in an area that has been identified as an erosion hotspot (Moore and others, 1999; Griggs and Savoy, 1985). This map presents seacliff failure and retreat data from Seacliff State Beach, California, which is located seven kilometers east of Santa Cruz (fig. 1) along the northern Monterey Bay coast. The data presented in this map series provide high-resolution spatial and temporal information on the location, amount, and processes of seacliff retreat in Santa Cruz, California. These data show the response of the seacliffs to both large magnitude earthquakes and severe climatic events such as El Ni?os; this information may prove useful in predicting the future response of the cliffs to events of similar magnitude. The map data can also be incorporated into Global Information System (GIS) for use by researchers and community planners. Four sets of vertical aerial photographs (Oct. 18, 1989; Jan. 27, 1998; Feb. 9, 1998; and March 6, 1998) were orthorectified and digital terrain models (DTMs) were generated and edited for this study (see Hapke and Richmond, 2000, for description of techniques). The earliest set of photography is from 1989, taken immediately following the Loma Prieta earthquake. These photographs are used to document the response of the seacliffs to seismic shaking, as well as to establish a baseline cliff-edge position to measure the amount of retreat of the cliff edge over the following decade. The remaining three sets of photographs were collected using the U.S. Geological Survey Coastal Aerial Mapping System (CAMS) during the 1997-98 El Ni?o (see Hapke and Richmond, 1999; 2000). The CAMS photographs were taken before, during, and after severe storms and are used to examine seacliff response to these storms. In addition to the analyses of photogrammetrically processed data, field mapping identified joints, faults, and lithologic variations along this section of seacliff.

Map Showing Seacliff Response to Climatic and Seismic Events, Depot Hill, Santa Cruz County, California

USGS Publications Warehouse

Hapke, Cheryl J.; Richmond, Bruce M.; D'Iorio, Mimi M.

2002-01-01

INTRODUCTION The coastal cliffs along much of the central California coast are actively retreating. Large storms and periodic earthquakes are responsible for most of the documented seacliff slope failures. Long-term average erosion rates calculated for this section of coast (Moore and others, 1999) do not provide the spatial or temporal data resolution necessary to identify the processes responsible for retreat of the seacliffs, where episodic retreat threatens homes and community infrastructure. Research suggests that more erosion occurs along the California coast over a short time scale, during periods of severe storms or seismic activity, than occurs during decades of normal weather or seismic quiescence (Griggs and Scholar, 1998; Griggs, 1994; Plant and Griggs, 1990; Griggs and Johnson, 1979 and 1983; Kuhn and Shepard, 1979). This is the first map in a series of maps documenting the processes of short-term seacliff retreat through the identification of slope failure styles, spatial variability of failures, and temporal variation in retreat amounts in an area that has been identified as an erosion hotspot (Moore and others, 1999; Griggs and Savoy, 1985). This map presents seacliff failure and retreat data from Depot Hill, California, which is located five kilometers east of Santa Cruz (fig.1) near the town of Capitola, along the northern Monterey Bay coast. The data presented in this map series provide high-resolution spatial and temporal information on the location, amount, and processes of seacliff retreat in Santa Cruz, California. These data show the response of the seacliffs to both large magnitude earthquakes and severe climatic events such as El NiOos; this information may prove useful in predicting the future response of the cliffs to events of similar magnitude. The map data can also be incorporated into Global Information System (GIS) for use by researchers and community planners. Four sets of vertical aerial photographs (Oct. 18, 1989; Jan. 27, 1998; Feb. 9, 1998; and March 6, 1998) were orthorectified and digital terrain models (DTMs) were generated and edited for this study (see Hapke and Richmond, 2000, for description of techniques). The earliest set of photography is from 1989, taken immediately following the Loma Prieta earthquake. These photographs are used to document the response of the seacliffs to seismic shaking, as well as to establish an initial cliff-edge position to measure the amount of retreat of the cliff edge over the following decade. The remaining three sets of photographs were collected using the U.S. Geological Survey Coastal Aerial Mapping System (CAMS) during the 1997-98 El NiOo (see Hapke and Richmond, 1999, 2000). The CAMS photographs were taken before, during, and after severe storms and are used to examine seacliff response to these storms. In addition to the analyses of photogrammetrically processed data, field mapping identified joints, faults, and lithologic variations along this section of seacliff.

Distribution of heavy metals in agricultural soils near a petrochemical complex in Guangzhou, China.

PubMed

Li, Junhui; Lu, Ying; Yin, Wei; Gan, Haihua; Zhang, Chao; Deng, Xianglian; Lian, Jin

2009-06-01

The aim of the study was to investigate influence of an industrialized environment on the accumulation of heavy metals in agricultural soils. Seventy soil samples collected from surface layers (0-20 cm) and horizons of five selected pedons in the vicinity area of petrochemical complex in Guangzhou, China were analyzed for Zn, Cu, Pb, Cd, Hg and As concentrations, the horizontal and vertical variation of these metals were studied and geographic information system (GIS)-based mapping techniques were applied to generate spatial distribution maps. The mean concentrations of these heavy metals in the topsoils did not exceed the maximum allowable concentrations in agricultural soil of China with the exception of Hg. Significant differences between land-use types showed that Cu, Pb, Cd, Hg and As concentrations in topsoils were strongly influenced by agricultural practices and soil management. Within a radius of 1,300 m there were no marked decreasing trends for these element concentrations (except for Zn) with the increase of distance from the complex boundary, which reflected little influence of petroleum air emission on soil heavy metal accumulation. Concentrations of Zn, Cu, Pb, Cd, Hg and As in the five pedons, particularly in cultivated vegetable field and orchard, decreased with soil depth, indicating these elements mainly originated from anthropogenic sources. GIS mapping was a useful tool for evaluating spatial variability of heavy metals in the affected soil. The spatial distribution maps allowed the identification of hot-spot areas with high metal concentration. Effective measures should be taken to avoid or minimize heavy metal further contamination of soils and to remediate the contaminated areas in order to prevent pollutants affecting human health through agricultural products.

A map of human impacts to a ``pristine'' coral reef ecosystem, the Papahānaumokuākea Marine National Monument

NASA Astrophysics Data System (ADS)

Selkoe, K. A.; Halpern, B. S.; Ebert, C. M.; Franklin, E. C.; Selig, E. R.; Casey, K. S.; Bruno, J.; Toonen, R. J.

2009-09-01

Effective and comprehensive regional-scale marine conservation requires fine-grained data on the spatial patterns of threats and their overlap. To address this need for the Papahānaumokuākea Marine National Monument (Monument) in Hawaii, USA, spatial data on 14 recent anthropogenic threats specific to this region were gathered or created, including alien species, bottom fishing, lobster trap fishing, ship-based pollution, ship strike risks, marine debris, research diving, research equipment installation, research wildlife sacrifice, and several anthropogenic climate change threats i.e., increase in ultraviolet (UV) radiation, seawater acidification, the number of warm ocean temperature anomalies relevant to disease outbreaks and coral bleaching, and sea level rise. These data were combined with habitat maps and expert judgment on the vulnerability of different habitat types in the Monument to estimate spatial patterns of current cumulative impact at 1 ha (0.01 km2) resolution. Cumulative impact was greatest for shallow reef areas and peaked at Maro Reef, where 13 of the 14 threats overlapped in places. Ocean temperature variation associated with disease outbreaks was found to have the highest predicted impact overall, followed closely by other climate-related threats, none of which have easily tractable management solutions at the regional scale. High impact threats most tractable to regional management relate to ship traffic. Sensitivity analyses show that the results are robust to both data availability and quality. Managers can use these maps to (1) inform management and surveillance priorities based on the ranking of threats and their distributions, (2) guide permitting decisions based on cumulative impacts, and (3) choose areas to monitor for climate change effects. Furthermore, this regional analysis can serve as a case study for managers elsewhere interested in assessing and mapping region-specific cumulative human impacts.

Hierarchical spatial models of abundance and occurrence from imperfect survey data

USGS Publications Warehouse

Royle, J. Andrew; Kery, M.; Gautier, R.; Schmid, Hans

2007-01-01

Many estimation and inference problems arising from large-scale animal surveys are focused on developing an understanding of patterns in abundance or occurrence of a species based on spatially referenced count data. One fundamental challenge, then, is that it is generally not feasible to completely enumerate ('census') all individuals present in each sample unit. This observation bias may consist of several components, including spatial coverage bias (not all individuals in the Population are exposed to sampling) and detection bias (exposed individuals may go undetected). Thus, observations are biased for the state variable (abundance, occupancy) that is the object of inference. Moreover, data are often sparse for most observation locations, requiring consideration of methods for spatially aggregating or otherwise combining sparse data among sample units. The development of methods that unify spatial statistical models with models accommodating non-detection is necessary to resolve important spatial inference problems based on animal survey data. In this paper, we develop a novel hierarchical spatial model for estimation of abundance and occurrence from survey data wherein detection is imperfect. Our application is focused on spatial inference problems in the Swiss Survey of Common Breeding Birds. The observation model for the survey data is specified conditional on the unknown quadrat population size, N(s). We augment the observation model with a spatial process model for N(s), describing the spatial variation in abundance of the species. The model includes explicit sources of variation in habitat structure (forest, elevation) and latent variation in the form of a correlated spatial process. This provides a model-based framework for combining the spatially referenced samples while at the same time yielding a unified treatment of estimation problems involving both abundance and occurrence. We provide a Bayesian framework for analysis and prediction based on the integrated likelihood, and we use the model to obtain estimates of abundance and occurrence maps for the European Jay (Garrulus glandarius), a widespread, elusive, forest bird. The naive national abundance estimate ignoring imperfect detection and incomplete quadrat coverage was 77 766 territories. Accounting for imperfect detection added approximately 18 000 territories, and adjusting for coverage bias added another 131 000 territories to yield a fully corrected estimate of the national total of about 227 000 territories. This is approximately three times as high as previous estimates that assume every territory is detected in each quadrat.

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

PubMed

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

2018-05-30

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

Mapping the Risk of Snakebite in Sri Lanka - A National Survey with Geospatial Analysis

PubMed Central

Ediriweera, Dileepa Senajith; Kasturiratne, Anuradhani; Pathmeswaran, Arunasalam; Gunawardena, Nipul Kithsiri; Wijayawickrama, Buddhika Asiri; Jayamanne, Shaluka Francis; Isbister, Geoffrey Kennedy; Dawson, Andrew; Giorgi, Emanuele; Diggle, Peter John; Lalloo, David Griffith; de Silva, Hithanadura Janaka

2016-01-01

Background There is a paucity of robust epidemiological data on snakebite, and data available from hospitals and localized or time-limited surveys have major limitations. No study has investigated the incidence of snakebite across a whole country. We undertook a community-based national survey and model based geostatistics to determine incidence, envenoming, mortality and geographical pattern of snakebite in Sri Lanka. Methodology/Principal Findings The survey was designed to sample a population distributed equally among the nine provinces of the country. The number of data collection clusters was divided among districts in proportion to their population. Within districts clusters were randomly selected. Population based incidence of snakebite and significant envenoming were estimated. Model-based geostatistics was used to develop snakebite risk maps for Sri Lanka. 1118 of the total of 14022 GN divisions with a population of 165665 (0.8%of the country’s population) were surveyed. The crude overall community incidence of snakebite, envenoming and mortality were 398 (95% CI: 356–441), 151 (130–173) and 2.3 (0.2–4.4) per 100000 population, respectively. Risk maps showed wide variation in incidence within the country, and snakebite hotspots and cold spots were determined by considering the probability of exceeding the national incidence. Conclusions/Significance This study provides community based incidence rates of snakebite and envenoming for Sri Lanka. The within-country spatial variation of bites can inform healthcare decision making and highlights the limitations associated with estimates of incidence from hospital data or localized surveys. Our methods are replicable, and these models can be adapted to other geographic regions after re-estimating spatial covariance parameters for the particular region. PMID:27391023

High-Energy X-Ray Imaging of the Pulsar Wind Nebula MSH 15-52: Constraints on Particle Acceleration and Transport

NASA Technical Reports Server (NTRS)

An, Hongjun; Madsen, Kristin K.; Reynolds, Stephen P.; Kaspi, Victoria M.; Harrison, Fiona A.; Boggs, Steven E.; Christensen, Finn E.; Craig, William W.; Fryer, Chris L.; Grefenstette, Brian W.;

High-energy X-ray imaging of the pulsar wind nebula MSH 15–52: constraints on particle acceleration and transport

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

An, Hongjun; Kaspi, Victoria M.; Madsen, Kristin K.

2014-10-01

We present the first images of the pulsar wind nebula (PWN) MSH 15–52 in the hard X-ray band (≳8 keV), as measured with the Nuclear Spectroscopic Telescope Array (NuSTAR). Overall, the morphology of the PWN as measured by NuSTAR in the 3-7 keV band is similar to that seen in Chandra high-resolution imaging. However, the spatial extent decreases with energy, which we attribute to synchrotron energy losses as the particles move away from the shock. The hard-band maps show a relative deficit of counts in the northern region toward the RCW 89 thermal remnant, with significant asymmetry. We find thatmore » the integrated PWN spectra measured with NuSTAR and Chandra suggest that there is a spectral break at 6 keV, which may be explained by a break in the synchrotron-emitting electron distribution at ∼200 TeV and/or imperfect cross calibration. We also measure spatially resolved spectra, showing that the spectrum of the PWN softens away from the central pulsar B1509–58, and that there exists a roughly sinusoidal variation of spectral hardness in the azimuthal direction. We discuss the results using particle flow models. We find non-monotonic structure in the variation with distance of spectral hardness within 50'' of the pulsar moving in the jet direction, which may imply particle and magnetic-field compression by magnetic hoop stress as previously suggested for this source. We also present two-dimensional maps of spectral parameters and find an interesting shell-like structure in the N {sub H} map. We discuss possible origins of the shell-like structure and their implications.« less

Spatial distribution of podoconiosis in relation to environmental factors in Ethiopia: a historical review.

PubMed

Deribe, Kebede; Brooker, Simon J; Pullan, Rachel L; Hailu, Asrat; Enquselassie, Fikre; Reithinger, Richard; Newport, Melanie; Davey, Gail

2013-01-01

An up-to-date and reliable map of podoconiosis is needed to design geographically targeted and cost-effective intervention in Ethiopia. Identifying the ecological correlates of the distribution of podoconiosis is the first step for distribution and risk maps. The objective of this study was to investigate the spatial distribution and ecological correlates of podoconiosis using historical and contemporary survey data. Data on the observed prevalence of podoconiosis were abstracted from published and unpublished literature into a standardized database, according to strict inclusion and exclusion criteria. In total, 10 studies conducted between 1969 and 2012 were included, and data were available for 401,674 individuals older than 15 years of age from 229 locations. A range of high resolution environmental factors were investigated to determine their association with podoconiosis prevalence, using logistic regression. The prevalence of podoconiosis in Ethiopia was estimated at 3.4% (95% CI 3.3%-3.4%) with marked regional variation. We identified significant associations between mean annual Land Surface Temperature (LST), mean annual precipitation, topography of the land and fine soil texture and high prevalence of podoconiosis. The derived maps indicate both widespread occurrence of podoconiosis and a marked variability in prevalence of podoconiosis, with prevalence typically highest at altitudes >1500 m above sea level (masl), with >1500 mm annual rainfall and mean annual LST of 19-21°C. No (or very little) podoconiosis occurred at altitudes <1225 masl, with annual rainfall <900 mm, and mean annual LST of >24°C. Podoconiosis remains a public health problem in Ethiopia over considerable areas of the country, but exhibits marked geographical variation associated in part with key environmental factors. This is work in progress and the results presented here will be refined in future work.

Abundance Variations and Flows in Plage Regions Observed with CDS/SOHO

NASA Astrophysics Data System (ADS)

Rank, G.; Bagalá, L. G.; Czaykowska, A.; Haerendel, G.

1999-10-01

We present results from CDS/SOHO observations of the spotless active region NOAA-8208, obtained on 28th April 1998 near disk center. MDI images show a bipolar magnetic configuration. The regions of enhanced He I emission correspond to the areas with strong magnetic flux and also with bright plage areas seen in Ca II and H-alpha images. A high correlation is found between intensity maps of the transition region lines He I (logTmax = 4.3), O III (logTmax = 5.0), and O V (logTmax = 5.4). The line-of-sight velocities of He I reveal a strong downflow in the plage areas. Further, the line-of-sight velocities of He I, O III, and O V are well correlated, showing that the downflow pattern exists up to temperatures of about 0.25 MK. At higher temperatures (Mg VIII at logTmax = 5.8) this flow is not detected, suggesting that material streams into the plage region from sideways in the high transition region. Maps of the electron density in the transition region have been constructed from several line ratios yielding densities of about 9.0 cm-3 in the plage regions, about dex 0.5 cm-3 higher compared to the surrounding. To study the spatial variation of the first ionization potential (FIP) effect, the abundance ratio has been mapped for the ion ratio MgVI/NeVI. The ratio is highly variable on spatial scales down to a few arcsec from photospheric values to enhancements of a factor of 10. The strongest FIP enhancements are not correlated with transition region line emission, but are found outside of the plage regions. Some areas of strong FIP enhancement appear stretched and elongated, suggesting that the material is confined in loop-like structures.

Neutron Absorption Measurements Constrain Eucrite-Diogenite Mixing in Vesta's Regolith

NASA Technical Reports Server (NTRS)

Prettyman, T. H.; Mittlefehldt, D. W.; Feldman, W. C.; Hendricks, J. S.; Lawrence, D. J.; Peplowski, P. N.; Toplis, M. J.; Yamashita, N.; Beck, A.; LeCorre, L.;

Automated delineation and characterization of drumlins using a localized contour tree approach

NASA Astrophysics Data System (ADS)

Wang, Shujie; Wu, Qiusheng; Ward, Dylan

2017-10-01

Drumlins are ubiquitous landforms in previously glaciated regions, formed through a series of complex subglacial processes operating underneath the paleo-ice sheets. Accurate delineation and characterization of drumlins are essential for understanding the formation mechanism of drumlins as well as the flow behaviors and basal conditions of paleo-ice sheets. Automated mapping of drumlins is particularly important for examining the distribution patterns of drumlins across large spatial scales. This paper presents an automated vector-based approach to mapping drumlins from high-resolution light detection and ranging (LiDAR) data. The rationale is to extract a set of concentric contours by building localized contour trees and establishing topological relationships. This automated method can overcome the shortcomings of previously manual and automated methods for mapping drumlins, for instance, the azimuthal biases during the generation of shaded relief images. A case study was carried out over a portion of the New York Drumlin Field. Overall 1181 drumlins were identified from the LiDAR-derived DEM across the study region, which had been underestimated in previous literature. The delineation results were visually and statistically compared to the manual digitization results. The morphology of drumlins was characterized by quantifying the length, width, elongation ratio, height, area, and volume. Statistical and spatial analyses were conducted to examine the distribution pattern and spatial variability of drumlin size and form. The drumlins and the morphologic characteristics exhibit significant spatial clustering rather than randomly distributed patterns. The form of drumlins varies from ovoid to spindle shapes towards the downstream direction of paleo ice flows, along with the decrease in width, area, and volume. This observation is in line with previous studies, which may be explained by the variations in sediment thickness and/or the velocity increases of ice flows towards ice front.

Environmental flow assessments for transformed estuaries

NASA Astrophysics Data System (ADS)

Sun, Tao; Zhang, Heyue; Yang, Zhifeng; Yang, Wei

2015-01-01

Here, we propose an approach to environmental flow assessment that considers spatial pattern variations in potential habitats affected by river discharges and tidal currents in estuaries. The approach comprises four steps: identifying and simulating the distributions of critical environmental factors for habitats of typical species in an estuary; mapping of suitable habitats based on spatial distributions of the Habitat Suitability Index (HSI) and adopting the habitat aggregation index to understand fragmentation of potential suitable habitats; defining variations in water requirements for a certain species using trade-off analysis for different protection objectives; and recommending environmental flows in the estuary considering the compatibility and conflict of freshwater requirements for different species. This approach was tested using a case study in the Yellow River Estuary. Recommended environmental flows were determined by incorporating the requirements of four types of species into the assessments. Greater variability in freshwater inflows could be incorporated into the recommended environmental flows considering the adaptation of potential suitable habitats with variations in the flow regime. Environmental flow allocations should be conducted in conjunction with land use conflict management in estuaries. Based on the results presented here, the proposed approach offers flexible assessment of environmental flow for aquatic ecosystems that may be subject to future change.

Geographic analysis of species richness and community attributes of forest birds from survey data in the mid-Atlantic integrated assessment region

USGS Publications Warehouse

Cam, E.; Sauer, J.R.; Nichols, J.D.; Hines, J.E.; Flather, C.H.

2000-01-01

Species richness of local communities is a state variable commonly used in community ecology and conservation biology. Investigation of spatial and temporal variations in richness and identification of factors associated with these variations form a basis for specifying management plans, evaluating these plans, and for testing hypotheses of theoretical interest. However, estimation of species richness is not trivial: species can be missed by investigators during sampling sessions. Sampling artifacts can lead to erroneous conclusions on spatial and temporal variation in species richness. Here we use data from the North American Breeding Bird Survey to estimate parameters describing the state of bird communities in the Mid-Atlantic Assessment (MAIA) region: species richness, extinction probability, turnover and relative species richness. We use a recently developed approach to estimation of species richness and related parameters that does not require the assumption that all the species are detected during sampling efforts. The information presented here is intended to visualize the state of bird communities in the MAIA region. We provide information on 1975 and 1990. We also quantified the changes between these years. We summarized and mapped the community attributes at a scale of management interest (watershed units).

Interpreting the Subtle Spectral Variations of the 11.2 and 12.7 μm Polycyclic Aromatic Hydrocarbon Bands

NASA Astrophysics Data System (ADS)

Shannon, M. J.; Stock, D. J.; Peeters, E.

2016-06-01

We report new properties of the 11 and 12.7 μm emission complexes of polycyclic aromatic hydrocarbons (PAHs) by applying a Gaussian-based decomposition technique. Using high-resolution Spitzer Space Telescope data, we study in detail the spectral and spatial characteristics of the 11 and 12.7 μm emission bands in maps of reflection nebulae NGC 7023 and NGC 2023 (north and south) and the star-forming region M17. Profile variations are observed in both the 11 and 12.7 μm emission bands. We identify a neutral contribution to the traditional 11.0 μm PAH band and a cationic contribution to the traditional 11.2 μm band, the latter of which affects the PAH class of the 11.2 μm emission in our sample. The peak variations of the 12.7 μm complex are explained by the competition between two underlying blended components. The spatial distributions of these components link them to cations and neutrals. We conclude that the 12.7 μm emission originates in both neutral and cationic PAHs, lending support to the use of the 12.7/11.2 intensity ratio as a charge proxy.

Simulating climate change impact on soil erosion using RUSLE model - A case study in a watershed of mid-Himalayan landscape

NASA Astrophysics Data System (ADS)

Gupta, Surya; Kumar, Suresh

2017-06-01

Climate change, particularly due to the changed precipitation trend, can have a severe impact on soil erosion. The effect is more pronounced on the higher slopes of the Himalayan region. The goal of this study was to estimate the impact of climate change on soil erosion in a watershed of the Himalayan region using RUSLE model. The GCM (general circulation model) derived emission scenarios (HadCM3 A2a and B2a SRES) were used for climate projection. The statistical downscaling model (SDSM) was used to downscale the precipitation for three future periods, 2011-2040, 2041-2070, and 2071-2099, at large scale. Rainfall erosivity ( R) was calculated for future periods using the SDSM downscaled precipitation data. ASTER digital elevation model (DEM) and Indian Remote Sensing data - IRS LISS IV satellite data were used to generate the spatial input parameters required by RUSLE model. A digital soil-landscape map was prepared to generate spatially distributed soil erodibility ( K) factor map of the watershed. Topographic factors, slope length ( L) and steepness ( S) were derived from DEM. Normalised difference vegetation index (NDVI) derived from the satellite data was used to represent spatial variation vegetation density and condition under various land use/land cover. This variation was used to represent spatial vegetation cover factor. Analysis revealed that the average annual soil loss may increase by 28.38, 25.64 and 20.33% in the 2020s, 2050s and 2080s, respectively under A2 scenario, while under B2 scenario, it may increase by 27.06, 25.31 and 23.38% in the 2020s, 2050s and 2080s, respectively, from the base period (1985-2013). The study provides a comprehensive understanding of the possible future scenario of soil erosion in the mid-Himalaya for scientists and policy makers.

Regional assessment of boreal forest productivity using an ecological process model and remote sensing parameter maps.

PubMed

Kimball, J. S.; Keyser, A. R.; Running, S. W.; Saatchi, S. S.

2000-06-01

An ecological process model (BIOME-BGC) was used to assess boreal forest regional net primary production (NPP) and response to short-term, year-to-year weather fluctuations based on spatially explicit, land cover and biomass maps derived by radar remote sensing, as well as soil, terrain and daily weather information. Simulations were conducted at a 30-m spatial resolution, over a 1205 km(2) portion of the BOREAS Southern Study Area of central Saskatchewan, Canada, over a 3-year period (1994-1996). Simulations of NPP for the study region were spatially and temporally complex, averaging 2.2 (+/- 0.6), 1.8 (+/- 0.5) and 1.7 (+/- 0.5) Mg C ha(-1) year(-1) for 1994, 1995 and 1996, respectively. Spatial variability of NPP was strongly controlled by the amount of aboveground biomass, particularly photosynthetic leaf area, whereas biophysical differences between broadleaf deciduous and evergreen coniferous vegetation were of secondary importance. Simulations of NPP were strongly sensitive to year-to-year variations in seasonal weather patterns, which influenced the timing of spring thaw and deciduous bud-burst. Reductions in annual NPP of approximately 17 and 22% for 1995 and 1996, respectively, were attributed to 3- and 5-week delays in spring thaw relative to 1994. Boreal forest stands with greater proportions of deciduous vegetation were more sensitive to the timing of spring thaw than evergreen coniferous stands. Similar relationships were found by comparing simulated snow depth records with 10-year records of aboveground NPP measurements obtained from biomass harvest plots within the BOREAS region. These results highlight the importance of sub-grid scale land cover complexity in controlling boreal forest regional productivity, the dynamic response of the biome to short-term interannual climate variations, and the potential implications of climate change and other large-scale disturbances.

Spatial variation in mortality risk for haematological malignancies near a petrochemical refinery: a population-based case-control study

PubMed Central

Di Salvo, Francesca; Meneghini, Elisabetta; Vieira, Veronica; Baili, Paolo; Mariottini, Mauro; Baldini, Marco; Micheli, Andrea; Sant, Milena

2015-01-01

Introduction The study investigated the geographic variation of mortality risk for hematological malignancies (HMs) in order to identify potential high-risk areas near an Italian petrochemical refinery. Material and methods A population-based case-control study was conducted and residential histories for 171 cases and 338 sex- and age-matched controls were collected. Confounding factors were obtained from interviews with consenting relatives for 109 HM deaths and 267 controls. To produce risk mortality maps, two different approaches were applied. We mapped (1) adptive kernel density relative risk estimation (KDE) for case-control studies which estimates a spatial relative risk function using the ratio between cases and controls’ densities, and (2) estimated odds ratios for case-control study data using generalized additive models (GAMs) to smooth the effect of location, a proxy for exposure, while adjusting for confounding variables. Results No high-risk areas for HM mortality were identified among all subjects (men and women combined), by applying both approaches. Using the adaptive KDE approach, we found a significant increase in death risk only among women in a large area 2–6 km southeast of the refinery and the application of GAMs also identified a similarly-located significant high-risk area among women only (global p-value<0.025). Potential confounding risk factors we considered in the GAM did not alter the results. Conclusion Both approaches identified a high-risk area close to the refinery among women only. Those spatial methods are useful tools for public policy management to determine priority areas for intervention. Our findings suggest several directions for further research in order to identify other potential environmental exposures that may be assessed in forthcoming studies based on detailed exposure modeling. PMID:26073202

Mapping Active Stream Lengths as a Tool for Understanding Spatial Variations in Runoff Generation

NASA Astrophysics Data System (ADS)

Erwin, E. G.; Gannon, J. P.; Zimmer, M. A.

2016-12-01

Recent studies have shown temporary stream channels respond in complex ways to precipitation. By investigating how stream networks expand and recede throughout rain events, we may further develop our understanding of runoff generation. This study focused on mapping the expansion and contraction of the stream network in two headwater catchments characterized by differing soil depths and slopes, located in North Carolina, USA. The first is a 43 ha catchment located in the Southern Appalachian region, characterized by incised, steep slopes and soils of varying thickness. The second is a 3.3 ha catchment located in the Piedmont region, characterized as low relief with deep, highly weathered soils. Over a variety of flow conditions, surveys of the entire stream network were conducted at 10 m intervals to determine presence or absence of surface water. These surveys revealed several reaches within the networks that were intermittent, with perennial flow upstream and downstream. Furthermore, in some tributaries, the active stream head moved up the channel in response to precipitation and at others it remained anchored in place. Moreover, when repeat surveys were performed during the same storm, hysteresis was observed in active stream length variations: stream length was not the same on the rising limb and falling limb of the hydrograph. These observations suggest there are different geomorphological controls or runoff generation processes occurring spatially throughout these catchments. Observations of wide spatial and temporal variability of active stream length over a variety of flow conditions suggest runoff dynamics, generation mechanisms, and contributing flowpath depths producing streamflow may be highly variable and not easily predicted from streamflow observations at a fixed point. Finally, the observation of similar patterns in differing geomorphic regions suggests these processes extend beyond unique site characterizations.

Three-dimensional digital mapping of the optic nerve head cupping in glaucoma

NASA Astrophysics Data System (ADS)

Mitra, Sunanda; Ramirez, Manuel; Morales, Jose

1992-08-01

Visualization of the optic nerve head cupping is clinically achieved by stereoscopic viewing of a fundus image pair of the suspected eye. A novel algorithm for three-dimensional digital surface representation of the optic nerve head, using fusion of stereo depth map with a linearly stretched intensity image of a stereo fundus image pair, is presented. Prior to depth map acquisition, a number of preprocessing tasks including feature extraction, registration by cepstral analysis, and correction for intensity variations are performed. The depth map is obtained by using a coarse to fine strategy for obtaining disparities between corresponding areas. The required matching techniques to obtain the translational differences in every step, uses cepstral analysis and correlation-like scanning technique in the spatial domain for the finest details. The quantitative and precise representation of the optic nerve head surface topography following this algorithm is not computationally intensive and should provide more useful information than just qualitative stereoscopic viewing of the fundus as one of the diagnostic criteria for diagnosis of glaucoma.

Application of the Risk-Based Early Warning Method in a Fracture-Karst Water Source, North China.

PubMed

Guo, Yongli; Wu, Qing; Li, Changsuo; Zhao, Zhenhua; Sun, Bin; He, Shiyi; Jiang, Guanghui; Zhai, Yuanzheng; Guo, Fang

2018-03-01

  The paper proposes a risk-based early warning considering characteristics of fracture-karst aquifer in North China and applied it in a super-large fracture-karst water source. Groundwater vulnerability, types of land use, water abundance, transmissivity and spatial temporal variation of groundwater quality were chosen as indexes of the method. Weights of factors were obtained by using AHP method based on relative importance of factors, maps of factors were zoned by GIS, early warning map was conducted based on extension theory with the help of GIS, ENVI+IDL. The early warning map fused five factors very well, serious and tremendous warning areas are mainly located in northwest and east with high or relatively high transmissivity and groundwater pollutant loading, and obviously deteriorated or deteriorated trend of petroleum. The early warning map warns people where more attention should be paid, and the paper guides decision making to take appropriate protection actions in different warning levels areas.

Mapping Malaria Transmission Risk in Northern Morocco Using Entomological and Environmental Data

PubMed Central

Adlaoui, E.; Faraj, C.; El Bouhmi, M.; El Aboudi, A.; Ouahabi, S.; Tran, A.; Fontenille, D.; El Aouad, R.

2011-01-01

Malaria resurgence risk in Morocco depends, among other factors, on environmental changes as well as the introduction of parasite carriers. The aim of this paper is to analyze the receptivity of the Loukkos area, large wetlands in Northern Morocco, to quantify and to map malaria transmission risk in this region using biological and environmental data. This risk was assessed on entomological risk basis and was mapped using environmental markers derived from satellite imagery. Maps showing spatial and temporal variations of entomological risk for Plasmodium vivax and P. falciparum were produced. Results showed this risk to be highly seasonal and much higher in rice fields than in swamps. This risk is lower for Afrotropical P. falciparum strains because of the low infectivity of Anopheles labranchiae, principal malaria vector in Morocco. However, it is very high for P. vivax mainly during summer corresponding to the rice cultivation period. Although the entomological risk is high in Loukkos region, malaria resurgence risk remains very low, because of the low vulnerability of the area. PMID:22312566

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

USGS Publications Warehouse

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

2007-01-01

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

Depth Estimation of Submerged Aquatic Vegetation in Clear Water Streams Using Low-Altitude Optical Remote Sensing

PubMed Central

Visser, Fleur; Buis, Kerst; Verschoren, Veerle; Meire, Patrick

2015-01-01

UAVs and other low-altitude remote sensing platforms are proving very useful tools for remote sensing of river systems. Currently consumer grade cameras are still the most commonly used sensors for this purpose. In particular, progress is being made to obtain river bathymetry from the optical image data collected with such cameras, using the strong attenuation of light in water. No studies have yet applied this method to map submergence depth of aquatic vegetation, which has rather different reflectance characteristics from river bed substrate. This study therefore looked at the possibilities to use the optical image data to map submerged aquatic vegetation (SAV) depth in shallow clear water streams. We first applied the Optimal Band Ratio Analysis method (OBRA) of Legleiter et al. (2009) to a dataset of spectral signatures from three macrophyte species in a clear water stream. The results showed that for each species the ratio of certain wavelengths were strongly associated with depth. A combined assessment of all species resulted in equally strong associations, indicating that the effect of spectral variation in vegetation is subsidiary to spectral variation due to depth changes. Strongest associations (R2-values ranging from 0.67 to 0.90 for different species) were found for combinations including one band in the near infrared (NIR) region between 825 and 925 nm and one band in the visible light region. Currently data of both high spatial and spectral resolution is not commonly available to apply the OBRA results directly to image data for SAV depth mapping. Instead a novel, low-cost data acquisition method was used to obtain six-band high spatial resolution image composites using a NIR sensitive DSLR camera. A field dataset of SAV submergence depths was used to develop regression models for the mapping of submergence depth from image pixel values. Band (combinations) providing the best performing models (R2-values up to 0.77) corresponded with the OBRA findings. A 10% error was achieved under sub-optimal data collection conditions, which indicates that the method could be suitable for many SAV mapping applications. PMID:26437410

Depth Estimation of Submerged Aquatic Vegetation in Clear Water Streams Using Low-Altitude Optical Remote Sensing.

PubMed

Visser, Fleur; Buis, Kerst; Verschoren, Veerle; Meire, Patrick

2015-09-30

UAVs and other low-altitude remote sensing platforms are proving very useful tools for remote sensing of river systems. Currently consumer grade cameras are still the most commonly used sensors for this purpose. In particular, progress is being made to obtain river bathymetry from the optical image data collected with such cameras, using the strong attenuation of light in water. No studies have yet applied this method to map submergence depth of aquatic vegetation, which has rather different reflectance characteristics from river bed substrate. This study therefore looked at the possibilities to use the optical image data to map submerged aquatic vegetation (SAV) depth in shallow clear water streams. We first applied the Optimal Band Ratio Analysis method (OBRA) of Legleiter et al. (2009) to a dataset of spectral signatures from three macrophyte species in a clear water stream. The results showed that for each species the ratio of certain wavelengths were strongly associated with depth. A combined assessment of all species resulted in equally strong associations, indicating that the effect of spectral variation in vegetation is subsidiary to spectral variation due to depth changes. Strongest associations (R²-values ranging from 0.67 to 0.90 for different species) were found for combinations including one band in the near infrared (NIR) region between 825 and 925 nm and one band in the visible light region. Currently data of both high spatial and spectral resolution is not commonly available to apply the OBRA results directly to image data for SAV depth mapping. Instead a novel, low-cost data acquisition method was used to obtain six-band high spatial resolution image composites using a NIR sensitive DSLR camera. A field dataset of SAV submergence depths was used to develop regression models for the mapping of submergence depth from image pixel values. Band (combinations) providing the best performing models (R²-values up to 0.77) corresponded with the OBRA findings. A 10% error was achieved under sub-optimal data collection conditions, which indicates that the method could be suitable for many SAV mapping applications.

Mapping power-law rheology of living cells using multi-frequency force modulation atomic force microscopy

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

Takahashi, Ryosuke; Okajima, Takaharu, E-mail: okajima@ist.hokudai.ac.jp

We present multi-frequency force modulation atomic force microscopy (AFM) for mapping the complex shear modulus G* of living cells as a function of frequency over the range of 50–500 Hz in the same measurement time as the single-frequency force modulation measurement. The AFM technique enables us to reconstruct image maps of rheological parameters, which exhibit a frequency-dependent power-law behavior with respect to G{sup *}. These quantitative rheological measurements reveal a large spatial variation in G* in this frequency range for single cells. Moreover, we find that the reconstructed images of the power-law rheological parameters are much different from those obtained inmore » force-curve or single-frequency force modulation measurements. This indicates that the former provide information about intracellular mechanical structures of the cells that are usually not resolved with the conventional force measurement methods.« less

Tectonic implications of Mars crustal magnetism

PubMed Central

Connerney, J. E. P.; Acuña, M. H.; Ness, N. F.; Kletetschka, G.; Mitchell, D. L.; Lin, R. P.; Reme, H.

2005-01-01

Mars currently has no global magnetic field of internal origin but must have had one in the past, when the crust acquired intense magnetization, presumably by cooling in the presence of an Earth-like magnetic field (thermoremanent magnetization). A new map of the magnetic field of Mars, compiled by using measurements acquired at an ≈400-km mapping altitude by the Mars Global Surveyor spacecraft, is presented here. The increased spatial resolution and sensitivity of this map provide new insight into the origin and evolution of the Mars crust. Variations in the crustal magnetic field appear in association with major faults, some previously identified in imagery and topography (Cerberus Rupes and Valles Marineris). Two parallel great faults are identified in Terra Meridiani by offset magnetic field contours. They appear similar to transform faults that occur in oceanic crust on Earth, and support the notion that the Mars crust formed during an early era of plate tectonics. PMID:16217034

Tectonic implications of Mars crustal magnetism.

PubMed

Connerney, J E P; Acuña, M H; Ness, N F; Kletetschka, G; Mitchell, D L; Lin, R P; Reme, H

2005-10-18

Mars currently has no global magnetic field of internal origin but must have had one in the past, when the crust acquired intense magnetization, presumably by cooling in the presence of an Earth-like magnetic field (thermoremanent magnetization). A new map of the magnetic field of Mars, compiled by using measurements acquired at an approximately 400-km mapping altitude by the Mars Global Surveyor spacecraft, is presented here. The increased spatial resolution and sensitivity of this map provide new insight into the origin and evolution of the Mars crust. Variations in the crustal magnetic field appear in association with major faults, some previously identified in imagery and topography (Cerberus Rupes and Valles Marineris). Two parallel great faults are identified in Terra Meridiani by offset magnetic field contours. They appear similar to transform faults that occur in oceanic crust on Earth, and support the notion that the Mars crust formed during an early era of plate tectonics.

Sci—Thur PM: Imaging — 01: Position-sensitive noise characteristics in multi-pinhole cardiac SPECT imaging

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

Cuddy-Walsh, SG; University of Ottawa Heart Institute; Wells, RG

2014-08-15

Myocardial perfusion imaging (MPI) with Single Photon Emission Computed Tomography (SPECT) is invaluable in the diagnosis and management of heart disease. It provides essential information on myocardial blood flow and ischemia. Multi-pinhole dedicated cardiac-SPECT cameras offer improved count sensitivity, and spatial and energy resolutions over parallel-hole camera designs however variable sensitivity across the field-of-view (FOV) can lead to position-dependent noise variations. Since MPI evaluates differences in the signal-to-noise ratio, noise variations in the camera could significantly impact the sensitivity of the test for ischemia. We evaluated the noise characteristics of GE Healthcare's Discovery NM530c camera with a goal of optimizingmore » the accuracy of our patient assessment and thereby improving outcomes. Theoretical sensitivity maps of the camera FOV, including attenuation effects, were estimated analytically based on the distance and angle between the spatial position of a given voxel and each pinhole. The standard deviation in counts, σ was inferred for each voxel position from the square root of the sensitivity mapped at that position. Noise was measured experimentally from repeated (N=16) acquisitions of a uniform spherical Tc-99m-water phantom. The mean (μ) and standard deviation (σ) were calculated for each voxel position in the reconstructed FOV. Noise increased ∼2.1× across a 12 cm sphere. A correlation of 0.53 is seen when experimental noise is compared with theory suggesting that ∼53% of the noise is attributed to the combined effects of attenuation and the multi-pinhole geometry. Further investigations are warranted to determine the clinical impact of the position-dependent noise variation.« less

Mapping the distribution of Loa loa in Cameroon in support of the African Programme for Onchocerciasis Control

PubMed Central

Thomson, Madeleine C; Obsomer, Valérie; Kamgno, Joseph; Gardon, Jacques; Wanji, Samuel; Takougang, Innocent; Enyong, Peter; Remme, Jan H; Molyneux, David H; Boussinesq, Michel

2004-01-01

Background Loa loa has recently emerged as a filarial worm of significant public health importance as a consequence of its impact on the African Programme for Onchocerciasis Control (APOC). Severe, sometimes fatal, encephalopathic reactions to ivermectin (the drug of choice for onchocerciasis control) have occurred in some individuals with high Loa loa microfilarial counts. Since high density of Loa loa microfilariae is known to be associated with high prevalence rates, a distribution map of the latter may determine areas where severe reactions might occur. The aim of the study was to identify variables which were significantly associated with the presence of a Loa microfilaraemia in the subjects examined, and to develop a spatial model predicting the prevalence of the Loa microfilaraemia. Methods Epidemiological data were collected from 14,225 individuals living in 94 villages in Cameroon, and analysed in conjunction with environmental data. A series of logistic regression models (multivariate analysis) was developed to describe variation in the prevalence of Loa loa microfilaraemia using individual level co-variates (age, sex, μl of blood taken for examination) and village level environmental co-variates (including altitude and satellite-derived vegetation indices). Results A spatial model of Loa loa prevalence was created within a geographical information system. The model was then validated using an independent data set on Loa loa distribution. When considering both data sets as a whole, and a prevalence threshold of 20%, the sensitivity and the specificity of the model were 81.7 and 69.4%, respectively. Conclusions The model developed has proven very useful in defining the areas at risk of post-ivermectin Loa-related severe adverse events. It is now routinely used by APOC when projects of community-directed treatment with ivermectin are examined. PMID:15298709

Mapping the distribution of Loa loa in Cameroon in support of the African Programme for Onchocerciasis Control.

PubMed

Thomson, Madeleine C; Obsomer, Valérie; Kamgno, Joseph; Gardon, Jacques; Wanji, Samuel; Takougang, Innocent; Enyong, Peter; Remme, Jan H; Molyneux, David H; Boussinesq, Michel

2004-08-06

BACKGROUND: Loa loa has recently emerged as a filarial worm of significant public health importance as a consequence of its impact on the African Programme for Onchocerciasis Control (APOC). Severe, sometimes fatal, encephalopathic reactions to ivermectin (the drug of choice for onchocerciasis control) have occurred in some individuals with high Loa loa microfilarial counts. Since high density of Loa loa microfilariae is known to be associated with high prevalence rates, a distribution map of the latter may determine areas where severe reactions might occur. The aim of the study was to identify variables which were significantly associated with the presence of a Loa microfilaraemia in the subjects examined, and to develop a spatial model predicting the prevalence of the Loa microfilaraemia. METHODS: Epidemiological data were collected from 14,225 individuals living in 94 villages in Cameroon, and analysed in conjunction with environmental data. A series of logistic regression models (multivariate analysis) was developed to describe variation in the prevalence of Loa loa microfilaraemia using individual level co-variates (age, sex, microl of blood taken for examination) and village level environmental co-variates (including altitude and satellite-derived vegetation indices). RESULTS: A spatial model of Loa loa prevalence was created within a geographical information system. The model was then validated using an independent data set on Loa loa distribution. When considering both data sets as a whole, and a prevalence threshold of 20%, the sensitivity and the specificity of the model were 81.7 and 69.4%, respectively. CONCLUSIONS: The model developed has proven very useful in defining the areas at risk of post-ivermectin Loa-related severe adverse events. It is now routinely used by APOC when projects of community-directed treatment with ivermectin are examined.

Use of a forest sapwood area index to explain long-term variability in mean annual evapotranspiration and streamflow in moist eucalypt forests

NASA Astrophysics Data System (ADS)

Benyon, Richard G.; Lane, Patrick N. J.; Jaskierniak, Dominik; Kuczera, George; Haydon, Shane R.

2015-07-01

Mean sapwood thickness, measured in fifteen 73 year old Eucalyptus regnans and E. delegatensis stands, correlated strongly with forest overstorey stocking density (R2 0.72). This curvilinear relationship was used with routine forest stocking density and basal area measurements to estimate sapwood area of the forest overstorey at various times in 15 research catchments in undisturbed and disturbed forests located in the Great Dividing Range, Victoria, Australia. Up to 45 years of annual precipitation and streamflow data available from the 15 catchments were used to examine relationships between mean annual loss (evapotranspiration estimated as mean annual precipitation minus mean annual streamflow), and sapwood area. Catchment mean sapwood area correlated strongly (R2 0.88) with catchment mean annual loss. Variation in sapwood area accounted for 68% more variation in mean annual streamflow than precipitation alone (R2 0.90 compared with R2 0.22). Changes in sapwood area accounted for 96% of the changes in mean annual loss observed after forest thinning or clear-cutting and regeneration. We conclude that forest inventory data can be used reliably to predict spatial and temporal variation in catchment annual losses and streamflow in response to natural and imposed disturbances in even-aged forests. Consequently, recent advances in mapping of sapwood area using airborne light detection and ranging will enable high resolution spatial and temporal mapping of mean annual loss and mean annual streamflow over large areas of forested catchment. This will be particularly beneficial in management of water resources from forested catchments subject to disturbance but lacking reliable long-term (years to decades) streamflow records.

Microbial biogeography: putting microorganisms on the map.

PubMed

Martiny, Jennifer B Hughes; Bohannan, Brendan J M; Brown, James H; Colwell, Robert K; Fuhrman, Jed A; Green, Jessica L; Horner-Devine, M Claire; Kane, Matthew; Krumins, Jennifer Adams; Kuske, Cheryl R; Morin, Peter J; Naeem, Shahid; Ovreås, Lise; Reysenbach, Anna-Louise; Smith, Val H; Staley, James T

2006-02-01

We review the biogeography of microorganisms in light of the biogeography of macroorganisms. A large body of research supports the idea that free-living microbial taxa exhibit biogeographic patterns. Current evidence confirms that, as proposed by the Baas-Becking hypothesis, 'the environment selects' and is, in part, responsible for spatial variation in microbial diversity. However, recent studies also dispute the idea that 'everything is everywhere'. We also consider how the processes that generate and maintain biogeographic patterns in macroorganisms could operate in the microbial world.

Effect of Variation of Silicon Nitride Passivation Layer on Electron Irradiated Aluminum Gallium Nitride/Gallium Nitride HEMT Structures

DTIC Science & Technology

2014-06-19

the AlGaN is unintentionally doped . Figure 2.3. AlGaN/GaN band diagram showing polarization charges. The band diagram in Figure 2.3 shows...intentionally doped as are MESFETS, and the channel gets its electrons from the unintentional doping . There is less Coulomb scattering in the...temperature measurements are often used to provide spatial PL maps of doping and trap densities. Laser excitation (quasi-monochromatic) is

Improving snow density estimation for mapping SWE with Lidar snow depth: assessment of uncertainty in modeled density and field sampling strategies in NASA SnowEx

NASA Astrophysics Data System (ADS)

Raleigh, M. S.; Smyth, E.; Small, E. E.

2017-12-01

The spatial distribution of snow water equivalent (SWE) is not sufficiently monitored with either remotely sensed or ground-based observations for water resources management. Recent applications of airborne Lidar have yielded basin-wide mapping of SWE when combined with a snow density model. However, in the absence of snow density observations, the uncertainty in these SWE maps is dominated by uncertainty in modeled snow density rather than in Lidar measurement of snow depth. Available observations tend to have a bias in physiographic regime (e.g., flat open areas) and are often insufficient in number to support testing of models across a range of conditions. Thus, there is a need for targeted sampling strategies and controlled model experiments to understand where and why different snow density models diverge. This will enable identification of robust model structures that represent dominant processes controlling snow densification, in support of basin-scale estimation of SWE with remotely-sensed snow depth datasets. The NASA SnowEx mission is a unique opportunity to evaluate sampling strategies of snow density and to quantify and reduce uncertainty in modeled snow density. In this presentation, we present initial field data analyses and modeling results over the Colorado SnowEx domain in the 2016-2017 winter campaign. We detail a framework for spatially mapping the uncertainty in snowpack density, as represented across multiple models. Leveraging the modular SUMMA model, we construct a series of physically-based models to assess systematically the importance of specific process representations to snow density estimates. We will show how models and snow pit observations characterize snow density variations with forest cover in the SnowEx domains. Finally, we will use the spatial maps of density uncertainty to evaluate the selected locations of snow pits, thereby assessing the adequacy of the sampling strategy for targeting uncertainty in modeled snow density.

Mapping Atmospheric Ammonia Emissions Using a Mobile Quantum Cascade Laser-based Open-path Sensor

NASA Astrophysics Data System (ADS)

Sun, K.; Tao, L.; Miller, D. J.; Khan, M. A.; Zondlo, M. A.

2012-12-01

Ammonia (NH3) is a key precursor to atmospheric fine particulate matter, with strong implications for regional air quality and global climate change. Despite the importance of atmospheric ammonia, its spatial/temporal variation is poorly characterized, and the knowledge of its sources, sinks, and transport is severely limited. Existing measurements suggest that traffic exhaust may provide significant amounts of ammonia in urban areas, which cause greater impacts on particulate matter formation and urban air quality. To capture the spatial and temporal variation of ammonia emissions, a portable, low power sensor with high time resolution is necessary. We have developed a portable open-path ammonia sensor with a detection limit of 0.5 ppbv ammonia for 1 s measurements. The sensor has a power consumption of about 60 W and is capable of running on a car battery continuously for 24 hours. An additional laser has been coupled to the sensor to yield concurrent N2O and CO measurements as tracers for determining various sources. The overall sensor prototype fits on a 60 cm × 20 cm aluminum breadboard. Roadside measurements indicated NH3/CO emission ratios of 4.1±5.4 ppbv/ppmv from a fleet of 320 vehicles, which agree with existing on-ramp measurements. Urban measurements in the Baltimore and Washington, DC metropolitan areas have shown significant ammonia mixing ratios concurrent with carbon monoxide levels from the morning and evening rush hours. On-road measurements of our open-path sensor have also been performed continuously from the Midwest to Princeton, NJ including urban areas such as Pittsburgh, tunnels, and relatively clean conditions. The emission ratios of ammonia against CO and/or CO2 help identify the sources and amounts of both urban and agricultural ammonia emissions. Preliminary data from both spatial mapping, monitoring, and vehicle exhaust measurements suggest that urban ammonia emissions from fossil fuel combustion are significant and may provide an unrecognized source in the atmospheric ammonia budget. Ongoing efforts include spatial mapping of ammonia and other tracers in the New York City and Philadelphia metropolitan areas. Further comparison with TES satellite ammonia retrieval will help to put the measurements into a larger geographical and temporal context.

The Herschel Planetary Nebula Survey (HerPlaNS). I. Data overview and analysis demonstration with NGC 6781

NASA Astrophysics Data System (ADS)

Ueta, T.; Ladjal, D.; Exter, K. M.; Otsuka, M.; Szczerba, R.; Siódmiak, N.; Aleman, I.; van Hoof, P. A. M.; Kastner, J. H.; Montez, R.; McDonald, I.; Wittkowski, M.; Sandin, C.; Ramstedt, S.; De Marco, O.; Villaver, E.; Chu, Y.-H.; Vlemmings, W.; Izumiura, H.; Sahai, R.; Lopez, J. A.; Balick, B.; Zijlstra, A.; Tielens, A. G. G. M.; Rattray, R. E.; Behar, E.; Blackman, E. G.; Hebden, K.; Hora, J. L.; Murakawa, K.; Nordhaus, J.; Nordon, R.; Yamamura, I.

2014-05-01

Context. This is the first of a series of investigations into far-IR characteristics of 11 planetary nebulae (PNe) under the Herschel Space Observatory open time 1 program, Herschel Planetary Nebula Survey (HerPlaNS). Aims: Using the HerPlaNS data set, we look into the PN energetics and variations of the physical conditions within the target nebulae. In the present work, we provide an overview of the survey, data acquisition and processing, and resulting data products. Methods: We performed (1) PACS/SPIRE broadband imaging to determine the spatial distribution of the cold dust component in the target PNe and (2) PACS/SPIRE spectral-energy-distribution and line spectroscopy to determine the spatial distribution of the gas component in the target PNe. Results: For the case of NGC 6781, the broadband maps confirm the nearly pole-on barrel structure of the amorphous carbon-rich dust shell and the surrounding halo having temperatures of 26-40 K. The PACS/SPIRE multiposition spectra show spatial variations of far-IR lines that reflect the physical stratification of the nebula. We demonstrate that spatially resolved far-IR line diagnostics yield the (Te, ne) profiles, from which distributions of ionized, atomic, and molecular gases can be determined. Direct comparison of the dust and gas column mass maps constrained by the HerPlaNS data allows to construct an empirical gas-to-dust mass ratio map, which shows a range of ratios with the median of 195 ± 110. The present analysis yields estimates of the total mass of the shell to be 0.86 M⊙, consisting of 0.54 M⊙ of ionized gas, 0.12 M⊙ of atomic gas, 0.2 M⊙ of molecular gas, and 4 × 10-3 M⊙ of dust grains. These estimates also suggest that the central star of about 1.5 M⊙ initial mass is terminating its PN evolution onto the white dwarf cooling track. Conclusions: The HerPlaNS data provide various diagnostics for both the dust and gas components in a spatially resolved manner. In the forthcoming papers of the HerPlaNS series we will explore the HerPlaNS data set fully for the entire sample of 11 PNe. Herschel is an ESA Space Observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA.Table 2 and appendices are available in electronic form at http://www.aanda.org

Indoor radon variations in central Iran and its geostatistical map

NASA Astrophysics Data System (ADS)

Hadad, Kamal; Mokhtari, Javad

2015-02-01

We present the results of 2 year indoor radon survey in 10 cities of Yazd province in Central Iran (covering an area of 80,000 km2). We used passive diffusive samplers with LATEX polycarbonate films as Solid State Nuclear Track Detector (SSNTD). This study carried out in central Iran where there are major minerals and uranium mines. Our results indicate that despite few extraordinary high concentrations, average annual concentrations of indoor radon are within ICRP guidelines. When geostatistical spatial distribution of radon mapped onto geographical features of the province it was observed that risk of high radon concentration increases near the Saqand, Bafq, Harat and Abarkooh cities, this depended on the elevation and vicinity of the ores and mines.

Exploring the spatial variability of soil properties in an Alfisol Catena

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

Rosemary, F.; Vitharana, U. W. A.; Indraratne, S. P.

Detailed digital soil maps showing the spatial heterogeneity of soil properties consistent with the landscape are required for site-specific management of plant nutrients, land use planning and process-based environmental modeling. We characterized the short-scale spatial heterogeneity of soil properties in an Alfisol catena in a tropical landscape of Sri Lanka. The impact of different land-uses (paddy, vegetable and un-cultivated) was examined to assess the impact of anthropogenic activities on the variability of soil properties at the catenary level. Conditioned Latin hypercube sampling was used to collect 58 geo-referenced topsoil samples (0–30 cm) from the study area. Soil samples were analyzedmore » for pH, electrical conductivity (EC), organic carbon (OC), cation exchange capacity (CEC) and texture. The spatial correlation between soil properties was analyzed by computing crossvariograms and subsequent fitting of theoretical model. Spatial distribution maps were developed using ordinary kriging. The range of soil properties, pH: 4.3–7.9; EC: 0.01–0.18 dS m –1 ; OC: 0.1–1.37%; CEC: 0.44– 11.51 cmol (+) kg –1 ; clay: 1.5–25% and sand: 59.1–84.4% and their coefficient of variations indicated a large variability in the study area. Electrical conductivity and pH showed a strong spatial correlation which was reflected by the cross-variogram close to the hull of the perfect correlation. Moreover, cross-variograms calculated for EC and Clay, CEC and OC, CEC and clay and CEC and pH indicated weak positive spatial correlation between these properties. Relative nugget effect (RNE) calculated from variograms showed strongly structured spatial variability for pH, EC and sand content (RNE < 25%) while CEC, organic carbon and clay content showed moderately structured spatial variability (25% < RNE < 75%). Spatial dependencies for examined soil properties ranged from 48 to 984 m. The mixed effects model fitting followed by Tukey's post-hoc test showed significant effect of land use on the spatial variability of EC. Our study revealed a structured variability of topsoil properties in the selected tropical Alfisol catena. Except for EC, observed variability was not modified by the land uses. Investigated soil properties showed distinct spatial structures at different scales and magnitudes of strength. Our results will be useful for digital soil mapping, site specific management of soil properties, developing appropriate land use plans and quantifying anthropogenic impacts on the soil system.« less

Spatial imaging of UV emission from Jupiter and Saturn

NASA Technical Reports Server (NTRS)

Clarke, J. T.; Moos, H. W.

1981-01-01

Spatial imaging with the IUE is accomplished both by moving one of the apertures in a series of exposures and within the large aperture in a single exposure. The image of the field of view subtended by the large aperture is focussed directly onto the detector camera face at each wavelength; since the spatial resolution of the instrument is 5 to 6 arc sec and the aperture extends 23.0 by 10.3 arc sec, imaging both parallel and perpendicular to dispersion is possible in a single exposure. The correction for the sensitivity variation along the slit at 1216 A is obtained from exposures of diffuse geocoronal H Ly alpha emission. The relative size of the aperture superimposed on the apparent discs of Jupiter and Saturn in typical observation is illustrated. By moving the planet image 10 to 20 arc sec along the major axis of the aperture (which is constrained to point roughly north-south) maps of the discs of these planets are obtained with 6 arc sec spatial resolution.

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

PubMed Central

Slater, Hannah; Michael, Edwin

2013-01-01

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

ALMA MEASUREMENTS OF THE HNC AND HC{sub 3}N DISTRIBUTIONS IN TITAN'S ATMOSPHERE

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

Cordiner, M. A.; Nixon, C. A.; Serigano, J.

2014-11-10

We present spectrally and spatially resolved maps of HNC and HC{sub 3}N emission from Titan's atmosphere, obtained using the Atacama Large Millimeter/submillimeter Array on 2013 November 17. These maps show anisotropic spatial distributions for both molecules, with resolved emission peaks in Titan's northern and southern hemispheres. The HC{sub 3}N maps indicate enhanced concentrations of this molecule over the poles, consistent with previous studies of Titan's photochemistry and atmospheric circulation. Differences between the spectrally integrated flux distributions of HNC and HC{sub 3}N show that these species are not co-spatial. The observed spectral line shapes are consistent with HNC being concentrated predominantlymore » in the mesosphere and above (at altitudes z ≳ 400 km), whereas HC{sub 3}N is abundant at a broader range of altitudes (z ≈ 70-600 km). From spatial variations in the HC{sub 3}N line profile, the locations of the HC{sub 3}N emission peaks are shown to be variable as a function of altitude. The peaks in the integrated emission from HNC and the line core (upper atmosphere) component of HC{sub 3}N (at z ≳ 300 km) are found to be asymmetric with respect to Titan's polar axis, indicating that the mesosphere may be more longitudinally variable than previously thought. The spatially integrated HNC and HC{sub 3}N spectra are modeled using the NEMESIS planetary atmosphere code and the resulting best-fitting disk-averaged vertical mixing ratio profiles are found to be in reasonable agreement with previous measurements for these species. Vertical column densities of the best-fitting gradient models for HNC and HC{sub 3}N are 1.9 × 10{sup 13} cm{sup –2} and 2.3 × 10{sup 14} cm{sup –2}, respectively.« less

Coastal fog and low cloud spatial patterns: do they indicate potential biodiversity refugia?

NASA Astrophysics Data System (ADS)

Torregrosa, A.

2016-12-01

Marine fog and low clouds transfer water and nutrients to coastal ecosystems through advection from the ocean and reduce heat effects by reflecting incoming shortwave radiation. These effects are known to benefit many species, vegetation communities, and habitats such as coastal redwood trees and their understory, maritime chaparral, and coastal streams harboring endangered salmon species. The California floristic region is the highest ranked hotspot in the U.S. and ranked 7th of 35 biodiversity hotspots worldwide in terms of the percent of its plant species that are found nowhere else (endemic). Many environmental drivers have been identified as contributing to California's remarkably high endemism and biodiversity, however, coastal low clouds have not typically been included. This could be due to the lack of data such as high resolution maps of coastal low cloud occurrence or the lack of long term records. Using a recent analysis of hourly National Weather Service satellite data, a stability index (SI) for coastal fog and low cloud cover was derived using two measures of variation and average summertime cloud cover to quantify long term spatial stability trends. Several discrete spatial clumps were identified that had both high temporal stability and high coastal low cloud cover. These areas show a strong correlation with a specific topographic landscape configuration with respect to wind direction. Point occurrence distribution maps of endemic coastal species were overlain with the SI to explore spatial correlation. The federally endangered species that showed very high spatial correlation included Yadon's Rein-orchid (Piperia yadonii), Monterey Spineflower (Chorizanthe pungens var. pungens), and Seaside Bird's-beak (Cordylanthus rigidus ssp. littoralis). Current estimated range maps are not consistent with the SI results suggesting a need to update estimated ranges. Biodiversity measures are being investigated in these areas to explore the hypothesis that they can be considered paleorefugia for species that have persisted over millennia in spite of a general increase in the aridity and temperature of the California climate.

Assessing spatial heterogeneity of MDR-TB in a high burden country

PubMed Central

Jenkins, Helen E.; Plesca, Valeriu; Ciobanu, Anisoara; Crudu, Valeriu; Galusca, Irina; Soltan, Viorel; Serbulenco, Aliona; Zignol, Matteo; Dadu, Andrei; Dara, Masoud; Cohen, Ted

2013-01-01

Multidrug-resistant tuberculosis (MDR-TB) is a major concern in countries of the former Soviet Union. The reported risk of resistance among TB cases in the Republic of Moldova is among the highest in the world. We aimed to produce high-resolution spatial maps of MDR-TB risk and burden in this setting. We analyzed national TB surveillance data collected between 2007 and 2010 in Moldova. High drug susceptibility testing coverage and detailed location data permitted identification of sub-regional areas of higher MDR-TB risk. We investigated whether the distribution of cases with MDR-TB risk factors could explain this observed spatial variation in MDR-TB. 3,447 MDR-TB cases were notified during this period; 24% of new and 62% of previously treated patients had MDR-TB. Nationally, the estimated annual MDR-TB incidence was 54 cases/100,000 persons and >1,000 cases/100,000 persons within penitentiaries. We identified substantial geographic variation in MDR-TB burden and hotspots of MDR-TB. Locations with a higher percentage of previously incarcerated TB cases were at greater risk of being MDR-TB hotspots. Spatial analyses revealed striking geographic heterogeneity of MDR-TB. Methods to identify locations of high MDR-TB risk and burden should allow for better resource allocation and more appropriate targeting of studies to understand local mechanisms driving resistance. PMID:23100496

Dynamic and Inherent B0 Correction for DTI Using Stimulated Echo Spiral Imaging

PubMed Central

Avram, Alexandru V.; Guidon, Arnaud; Truong, Trong-Kha; Liu, Chunlei; Song, Allen W.

2013-01-01

Purpose To present a novel technique for high-resolution stimulated echo (STE) diffusion tensor imaging (DTI) with self-navigated interleaved spirals (SNAILS) readout trajectories that can inherently and dynamically correct for image artifacts due to spatial and temporal variations in the static magnetic field (B0) resulting from eddy currents, tissue susceptibilities, subject/physiological motion, and hardware instabilities. Methods The Hahn spin echo formed by the first two 90° radio-frequency pulses is balanced to consecutively acquire two additional images with different echo times (TE) and generate an inherent field map, while the diffusion-prepared STE signal remains unaffected. For every diffusion-encoding direction, an intrinsically registered field map is estimated dynamically and used to effectively and inherently correct for off-resonance artifacts in the reconstruction of the corresponding diffusion-weighted image (DWI). Results After correction with the dynamically acquired field maps, local blurring artifacts are specifically removed from individual STE DWIs and the estimated diffusion tensors have significantly improved spatial accuracy and larger fractional anisotropy. Conclusion Combined with the SNAILS acquisition scheme, our new method provides an integrated high-resolution short-TE DTI solution with inherent and dynamic correction for both motion-induced phase errors and off-resonance effects. PMID:23630029

Automated mineralogy based on micro-energy-dispersive X-ray fluorescence microscopy (µ-EDXRF) applied to plutonic rock thin sections in comparison to a mineral liberation analyzer

NASA Astrophysics Data System (ADS)

Nikonow, Wilhelm; Rammlmair, Dieter

2017-10-01

Recent developments in the application of micro-energy-dispersive X-ray fluorescence spectrometry mapping (µ-EDXRF) have opened up new opportunities for fast geoscientific analyses. Acquiring spatially resolved spectral and chemical information non-destructively for large samples of up to 20 cm length provides valuable information for geoscientific interpretation. Using supervised classification of the spectral information, mineral distribution maps can be obtained. In this work, thin sections of plutonic rocks are analyzed by µ-EDXRF and classified using the supervised classification algorithm spectral angle mapper (SAM). Based on the mineral distribution maps, it is possible to obtain quantitative mineral information, i.e., to calculate the modal mineralogy, search and locate minerals of interest, and perform image analysis. The results are compared to automated mineralogy obtained from the mineral liberation analyzer (MLA) of a scanning electron microscope (SEM) and show good accordance, revealing variation resulting mostly from the limit of spatial resolution of the µ-EDXRF instrument. Taking into account the little time needed for sample preparation and measurement, this method seems suitable for fast sample overviews with valuable chemical, mineralogical and textural information. Additionally, it enables the researcher to make better and more targeted decisions for subsequent analyses.

Soil Parameter Mapping and Ad Hoc Power Analysis to Increase Blocking Efficiency Prior to Establishing a Long-Term Field Experiment.

PubMed

Collins, Doug; Benedict, Chris; Bary, Andy; Cogger, Craig

2015-01-01

The spatial heterogeneity of soil and weed populations poses a challenge to researchers. Unlike aboveground variability, below-ground variability is more difficult to discern without a strategic soil sampling pattern. While blocking is commonly used to control environmental variation, this strategy is rarely informed by data about current soil conditions. Fifty georeferenced sites were located in a 0.65 ha area prior to establishing a long-term field experiment. Soil organic matter (OM) and weed seed bank populations were analyzed at each site and the spatial structure was modeled with semivariograms and interpolated with kriging to map the surface. These maps were used to formulate three strategic blocking patterns and the efficiency of each pattern was compared to a completely randomized design and a west to east model not informed by soil variability. Compared to OM, weeds were more variable across the landscape and had a shorter range of autocorrelation, and models to increase blocking efficiency resulted in less increase in power. Weeds and OM were not correlated, so no model examined improved power equally for both parameters. Compared to the west to east blocking pattern, the final blocking pattern chosen resulted in a 7-fold increase in power for OM and a 36% increase in power for weeds.

Discriminating Natural Variation from Legacies of Disturbance in Semi-Arid Forests, Southwestern USA

NASA Astrophysics Data System (ADS)

Swetnam, T. L.; Lynch, A. M.; Falk, D. A.; Yool, S. R.; Guertin, D. P.

2014-12-01

Characterizing differences in existing vegetation driven by natural variation versus disturbance legacies could become a critical component of applied forest management practice with important implications for monitoring ecologic succession and eco-hydrological interactions within the critical zone. Here we characterize variations in aerial LiDAR derived forest structure at individual tree scale in Arizona and New Mexico. Differences in structure result from both topographic and climatological variations and from natural and human related disturbances. We chose a priori undisturbed and disturbed sites that included preservation, development, logging and wildfire as exemplars. We compare two topographic indices, the topographic position index (TPI) and topographic wetness index (TWI), to two local indicators of spatial association (LISA): the Getis-Ord Gi and Anselin's Moran I. We found TPI and TWI correlate well to positive z-scores (tall trees in tall neighborhoods) in undisturbed areas and that disturbed areas are clearly defined by negative z-scores, in some cases better than what is visible from traditional orthophotography and existing GIS maps. These LISA methods also serve as a robust technique for creating like-clustered stands, i.e. common stands used in forest inventory monitoring. This research provides a significant advancement in the ability to (1) quantity variation in forest structure across topographically complex landscapes, (2) identify and map previously unrecorded disturbance locations, and (3) quantify the different impacts of disturbance within the perimeter of a stand or event at ecologically relevant scale.

Separating the effects of environment and space on tree species distribution: from population to community.

PubMed

Lin, Guojun; Stralberg, Diana; Gong, Guiquan; Huang, Zhongliang; Ye, Wanhui; Wu, Linfang

2013-01-01

Quantifying the relative contributions of environmental conditions and spatial factors to species distribution can help improve our understanding of the processes that drive diversity patterns. In this study, based on tree inventory, topography and soil data from a 20-ha stem-mapped permanent forest plot in Guangdong Province, China, we evaluated the influence of different ecological processes at different spatial scales using canonical redundancy analysis (RDA) at the community level and multiple linear regression at the species level. At the community level, the proportion of explained variation in species distribution increased with grid-cell sizes, primarily due to a monotonic increase in the explanatory power of environmental variables. At the species level, neither environmental nor spatial factors were important determinants of overstory species' distributions at small cell sizes. However, purely spatial variables explained most of the variation in the distributions of understory species at fine and intermediate cell sizes. Midstory species showed patterns that were intermediate between those of overstory and understory species. At the 20-m cell size, the influence of spatial factors was stronger for more dispersal-limited species, suggesting that much of the spatial structuring in this community can be explained by dispersal limitation. Comparing environmental factors, soil variables had higher explanatory power than did topography for species distribution. However, both topographic and edaphic variables were highly spatial structured. Our results suggested that dispersal limitation has an important influence on fine-intermediate scale (from several to tens of meters) species distribution, while environmental variability facilitates species distribution at intermediate (from ten to tens of meters) and broad (from tens to hundreds of meters) scales.

The collagen structure of equine articular cartilage characterized using polarization-sensitive optical coherence tomography and non-linear microscopy

NASA Astrophysics Data System (ADS)

Mansfield, Jessica C.; Ugryumova, Nadya; Knapp, Karen M.; Matcher, Stephen J.

2006-09-01

Equine articular cartilage has been imaged using both polarization-sensitive optical coherence tomography (PS-OCT) and non-linear microscopy. PS-OCT has been used to spatially map the birefringence in the cartilage and we have found that in the vicinity of the lesion the images display a characteristic disruption in the regular birefringence bands shown by normal cartilage. We also note that significant (e.g. x2) variations in the apparent birefringence of samples taken from young (18 month) animals that otherwise appear visually homogeneous are found over spatial scales of a few millimeters. We have also imaged the cartilage using non-linear microscopy and compare the scans taken with second harmonic generation (SHG) light and the two photon fluorescence (TPF) light. SHG images collected using 800 nm excitation reveals the spatial distribution of collagen fibers, whilst TPF images clearly shows the distribution of intracellular and pericellular fluorophores.

Changes in population and agricultural land in conterminous United States counties, 1790 to 1997

USGS Publications Warehouse

Waisanen, Pamela J.; Bliss, Norman B.

2002-01-01

We have developed a data set of changes in population and agricultural land for the conterminous United States at the county level, resulting in more spatial detail than in previously available compilations. The purpose was to provide data on the timing of land conversion as an input to dynamic models of the carbon cycle, although a wide variety of applications exist for the physical, biological, and social sciences. The spatial data represent the appropriate county boundaries for each census year between 1790 and 1997, and the census attributes are attached to the appropriate spatial region. The resulting time series and maps show the history of population (1790-1990) and the history of agricultural development (1850-1997). The patterns of agricultural development reflect the influences of climate, soil productivity, increases in population size, variations in the general economy, and technological changes in the energy, transportation, and agricultural sectors.

Spatial variations in estimated chronic exposure to traffic-related air pollution in working populations: A simulation

PubMed Central

Setton, Eleanor M; Keller, C Peter; Cloutier-Fisher, Denise; Hystad, Perry W

2008-01-01

Background Chronic exposure to traffic-related air pollution is associated with a variety of health impacts in adults and recent studies show that exposure varies spatially, with some residents in a community more exposed than others. A spatial exposure simulation model (SESM) which incorporates six microenvironments (home indoor, work indoor, other indoor, outdoor, in-vehicle to work and in-vehicle other) is described and used to explore spatial variability in estimates of exposure to traffic-related nitrogen dioxide (not including indoor sources) for working people. The study models spatial variability in estimated exposure aggregated at the census tracts level for 382 census tracts in the Greater Vancouver Regional District of British Columbia, Canada. Summary statistics relating to the distributions of the estimated exposures are compared visually through mapping. Observed variations are explored through analyses of model inputs. Results Two sources of spatial variability in exposure to traffic-related nitrogen dioxide were identified. Median estimates of total exposure ranged from 8 μg/m3 to 35 μg/m3 of annual average hourly NO2 for workers in different census tracts in the study area. Exposure estimates are highest where ambient pollution levels are highest. This reflects the regional gradient of pollution in the study area and the relatively high percentage of time spent at home locations. However, for workers within the same census tract, variations were observed in the partial exposure estimates associated with time spent outside the residential census tract. Simulation modeling shows that some workers may have exposures 1.3 times higher than other workers residing in the same census tract because of time spent away from the residential census tract, and that time spent in work census tracts contributes most to the differences in exposure. Exposure estimates associated with the activity of commuting by vehicle to work were negligible, based on the relatively short amount of time spent in this microenvironment compared to other locations. We recognize that this may not be the case for pollutants other than NO2. These results represent the first time spatially disaggregated variations in exposure to traffic-related air pollution within a community have been estimated and reported. Conclusion The results suggest that while time spent in the home indoor microenvironment contributes most to between-census tract variation in estimates of annual average exposures to traffic-related NO2, time spent in the work indoor microenvironment contributes most to within-census tract variation, and time spent in transit by vehicle makes a negligible contribution. The SESM has potential as a policy evaluation tool, given input data that reflect changes in pollution levels or work flow patterns due to traffic demand management and land use development policy. PMID:18638398

High-resolution maps of real and illusory tactile activation in primary somatosensory cortex in individual monkeys with functional magnetic resonance imaging and optical imaging.

PubMed

Chen, Li M; Turner, Gregory H; Friedman, Robert M; Zhang, Na; Gore, John C; Roe, Anna W; Avison, Malcolm J

2007-08-22

Although blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) has been widely used to explore human brain function, questions remain regarding the ultimate spatial resolution of positive BOLD fMRI, and indeed the extent to which functional maps revealed by positive BOLD correlate spatially with maps obtained with other high-spatial-resolution mapping techniques commonly used in animals, such as optical imaging of intrinsic signal (OIS) and single-unit electrophysiology. Here, we demonstrate that the positive BOLD signal at 9.4T can reveal the fine topography of individual fingerpads in single-condition activation maps in nonhuman primates. These digit maps are similar to maps obtained from the same animal using intrinsic optical imaging. Furthermore, BOLD fMRI reliably resolved submillimeter spatial shifts in activation in area 3b previously identified with OIS (Chen et al., 2003) as neural correlates of the "funneling illusion." These data demonstrate that at high field, high-spatial-resolution topographic maps can be achieved using the positive BOLD signal, weakening previous notions regarding the spatial specificity of the positive BOLD signal.

Remote sensing and geographic information system for appraisal of salt-affected soils in India.

PubMed

Singh, Gurbachan; Bundela, D S; Sethi, Madhurama; Lal, Khajanchi; Kamra, S K

2010-01-01

Quantification of the nature, extent, and spatial distribution of salt-affected soils (SAS) for India and the world is essential for planning and implementing reclamation programs in a timely and cost-effective manner for sustained crop production. The national extent of SAS for India over the last four decades was assessed by conventional and remote sensing approaches using diverse methodologies and class definitions and ranged from 6.0 to 26.1 million hectares (Mha) and 1.2 to 10.1 Mha, respectively. In 1966, an area of 6 Mha under SAS was first reported using the former approach. Three national estimates, obtained using remote sensing, were reconciled using a geographic information system, resulting in an acceptable extent of 6.73 Mha. Moderately and severely salt-encrusted lands having large contiguous area have been correctly mapped, but slightly salt-encrusted land having smaller affected areas within croplands has not been accurately mapped. Recent satellite sensors (e.g., Resourcesat-1, Cartosat-2, IKONOS-II, and RISAT-2), along with improved image processing techniques integrated with terrain and other spatial data using a geographic information system, are enabling mapping at large scale. Significant variations in salt encrustation at the surface caused by soil moisture, waterlogging conditions, salt-tolerant crops, and dynamics of subsurface salts present constraints in appraisal, delineation, and mapping efforts. The article provides an overview of development, identification, characterization, and delineation of SAS, past and current national scenarios of SAS using conventional and remote sensing approaches, reconciliation of national estimates, issues of SAS mapping, and future scope.

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

PubMed

Lipiec, Jerzy; Usowicz, Bogusław

2018-08-15

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

A Method of Spatial Mapping and Reclassification for High-Spatial-Resolution Remote Sensing Image Classification

PubMed Central

Wang, Guizhou; Liu, Jianbo; He, Guojin

2013-01-01

This paper presents a new classification method for high-spatial-resolution remote sensing images based on a strategic mechanism of spatial mapping and reclassification. The proposed method includes four steps. First, the multispectral image is classified by a traditional pixel-based classification method (support vector machine). Second, the panchromatic image is subdivided by watershed segmentation. Third, the pixel-based multispectral image classification result is mapped to the panchromatic segmentation result based on a spatial mapping mechanism and the area dominant principle. During the mapping process, an area proportion threshold is set, and the regional property is defined as unclassified if the maximum area proportion does not surpass the threshold. Finally, unclassified regions are reclassified based on spectral information using the minimum distance to mean algorithm. Experimental results show that the classification method for high-spatial-resolution remote sensing images based on the spatial mapping mechanism and reclassification strategy can make use of both panchromatic and multispectral information, integrate the pixel- and object-based classification methods, and improve classification accuracy. PMID:24453808

Minimizing Spatial Variability of Healthcare Spatial Accessibility-The Case of a Dengue Fever Outbreak.

PubMed

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.

Comparing the performance of geostatistical models with additional information from covariates for sewage plume characterization.

PubMed

Del Monego, Maurici; Ribeiro, Paulo Justiniano; Ramos, Patrícia

2015-04-01

In this work, kriging with covariates is used to model and map the spatial distribution of salinity measurements gathered by an autonomous underwater vehicle in a sea outfall monitoring campaign aiming to distinguish the effluent plume from the receiving waters and characterize its spatial variability in the vicinity of the discharge. Four different geostatistical linear models for salinity were assumed, where the distance to diffuser, the west-east positioning, and the south-north positioning were used as covariates. Sample variograms were fitted by the Matèrn models using weighted least squares and maximum likelihood estimation methods as a way to detect eventual discrepancies. Typically, the maximum likelihood method estimated very low ranges which have limited the kriging process. So, at least for these data sets, weighted least squares showed to be the most appropriate estimation method for variogram fitting. The kriged maps show clearly the spatial variation of salinity, and it is possible to identify the effluent plume in the area studied. The results obtained show some guidelines for sewage monitoring if a geostatistical analysis of the data is in mind. It is important to treat properly the existence of anomalous values and to adopt a sampling strategy that includes transects parallel and perpendicular to the effluent dispersion.

Targeting trachoma control through risk mapping: the example of Southern Sudan.

PubMed

Clements, Archie C A; Kur, Lucia W; Gatpan, Gideon; Ngondi, Jeremiah M; Emerson, Paul M; Lado, Mounir; Sabasio, Anthony; Kolaczinski, Jan H

2010-08-17

Trachoma is a major cause of blindness in Southern Sudan. Its distribution has only been partially established and many communities in need of intervention have therefore not been identified or targeted. The present study aimed to develop a tool to improve targeting of survey and control activities. A national trachoma risk map was developed using Bayesian geostatistics models, incorporating trachoma prevalence data from 112 geo-referenced communities surveyed between 2001 and 2009. Logistic regression models were developed using active trachoma (trachomatous inflammation follicular and/or trachomatous inflammation intense) in 6345 children aged 1-9 years as the outcome, and incorporating fixed effects for age, long-term average rainfall (interpolated from weather station data) and land cover (i.e. vegetation type, derived from satellite remote sensing), as well as geostatistical random effects describing spatial clustering of trachoma. The model predicted the west of the country to be at no or low trachoma risk. Trachoma clusters in the central, northern and eastern areas had a radius of 8 km after accounting for the fixed effects. In Southern Sudan, large-scale spatial variation in the risk of active trachoma infection is associated with aridity. Spatial prediction has identified likely high-risk areas to be prioritized for more data collection, potentially to be followed by intervention.

Targeting Trachoma Control through Risk Mapping: The Example of Southern Sudan

PubMed Central

Clements, Archie C. A.; Kur, Lucia W.; Gatpan, Gideon; Ngondi, Jeremiah M.; Emerson, Paul M.; Lado, Mounir; Sabasio, Anthony; Kolaczinski, Jan H.

2010-01-01

Background Trachoma is a major cause of blindness in Southern Sudan. Its distribution has only been partially established and many communities in need of intervention have therefore not been identified or targeted. The present study aimed to develop a tool to improve targeting of survey and control activities. Methods/Principal Findings A national trachoma risk map was developed using Bayesian geostatistics models, incorporating trachoma prevalence data from 112 geo-referenced communities surveyed between 2001 and 2009. Logistic regression models were developed using active trachoma (trachomatous inflammation follicular and/or trachomatous inflammation intense) in 6345 children aged 1–9 years as the outcome, and incorporating fixed effects for age, long-term average rainfall (interpolated from weather station data) and land cover (i.e. vegetation type, derived from satellite remote sensing), as well as geostatistical random effects describing spatial clustering of trachoma. The model predicted the west of the country to be at no or low trachoma risk. Trachoma clusters in the central, northern and eastern areas had a radius of 8 km after accounting for the fixed effects. Conclusion In Southern Sudan, large-scale spatial variation in the risk of active trachoma infection is associated with aridity. Spatial prediction has identified likely high-risk areas to be prioritized for more data collection, potentially to be followed by intervention. PMID:20808910

Development and testing of a contamination potential mapping system for a portion of the General Separations Area, Savannah River Site, South Carolina

USGS Publications Warehouse

Rine, J.M.; Berg, R.C.; Shafer, J.M.; Covington, E.R.; Reed, J.K.; Bennett, C.B.; Trudnak, J.E.

1998-01-01

A methodology was developed to evaluate and map the contamination potential or aquifer sensitivity of the upper groundwater flow system of a portion of the General Separations Area (GSA) at the Department of Energy's Savannah River Site (SRS) in South Carolina. A Geographic Information System (GIS) was used to integrate diverse subsurface geologic data, soils data, and hydrology utilizing a stack-unit mapping approach to construct mapping layers. This is the first time that such an approach has been used to delineate the hydrogeology of a coastal plain environment. Unit surface elevation maps were constructed for the tops of six Tertiary units derived from over 200 boring logs. Thickness or isopach maps were created for five hydrogeologic units by differencing top and basal surface elevations. The geologic stack-unit map was created by stacking the five isopach maps and adding codes for each stack-unit polygon. Stacked-units were rated according to their hydrogeologic properties and ranked using a logarithmic approach (utility theory) to establish a contamination potential index. Colors were assigned to help display relative importance of stacked-units in preventing or promoting transport of contaminants. The sensitivity assessment included the effects of surface soils on contaminants which are particularly important for evaluating potential effects from surface spills. Hydrogeologic/hydrologic factors did not exhibit sufficient spatial variation to warrant incorporation into contamination potential assessment. Development of this contamination potential mapping system provides a useful tool for site planners, environmental scientists, and regulatory agencies.A methodology was developed to evaluate and map the contamination potential or aquifer sensitivity of the upper groundwater flow system of a portion of the General Separations Area (GSA) at the Department of Energy's Savannah River Site (SRS) in South Carolina. A Geographic Information System (GIS) was used to integrate diverse subsurface geologic data, soils data, and hydrology utilizing a stack-unit mapping approach to construct mapping layers. This is the first time that such an approach has been used to delineate the hydrogeology of a coastal plain environment. Unit surface elevation maps were constructed for the tops of six Tertiary units derived from over 200 boring logs. Thickness or isopach maps were created for five hydrogeologic units by differencing top and basal surface elevations. The geologic stack-unit map was created by stacking the five isopach maps and adding codes for each stack-unit polygon. Stacked-units were rated according to their hydrogeologic properties and ranked using a logarithmic approach (utility theory) to establish a contamination potential index. Colors were assigned to help display relative importance of stacked-units in preventing or promoting transport of contaminants. The sensitivity assessment included the effects of surface soils on contaminants which are particularly important for evaluating potential effects from surface spills. Hydrogeologic/hydrologic factors did not exhibit sufficient spatial variation to warrant incorporation into contamination potential assessment. Development of this contamination potential mapping system provides a useful tool for site planners, environmental scientists, and regulatory agencies.

Parabolic Systems with p, q-Growth: A Variational Approach

NASA Astrophysics Data System (ADS)

Bögelein, Verena; Duzaar, Frank; Marcellini, Paolo

2013-10-01

We consider the evolution problem associated with a convex integrand {f : {R}^{Nn}to [0,infty)} satisfying a non-standard p, q-growth assumption. To establish the existence of solutions we introduce the concept of variational solutions. In contrast to weak solutions, that is, mappings {u\\colon Ω_T to {R}^n} which solve partial_tu-div Df(Du)=0 weakly in {Ω_T}, variational solutions exist under a much weaker assumption on the gap q - p. Here, we prove the existence of variational solutions provided the integrand f is strictly convex and 2n/n+2 < p le q < p+1. These variational solutions turn out to be unique under certain mild additional assumptions on the data. Moreover, if the gap satisfies the natural stronger assumption 2le p le q < p+ minbig \\{1,4/n big \\}, we show that variational solutions are actually weak solutions. This means that solutions u admit the necessary higher integrability of the spatial derivative Du to satisfy the parabolic system in the weak sense, that is, we prove that uin L^q_locbig(0,T; W^{1,q}_loc(Ω,{R}^N)big).

Color variations on Victoria quadrangle: support for the geological mapping

NASA Astrophysics Data System (ADS)

Zambon, F.; Galluzzi, V.; Carli, C.; Giacomini, L.; Massironi, M.; Palumbo, P.; Guzzetta, L.; Mancinelli, P.; Vivaldi, V.; Ferranti, L.; Pauselli, C.; Frigeri, A.; Zusi, M.; Pozzobon, R.; Cremonese, G.; Ferrari, S.; Capaccioni, F.

2015-10-01

Mercury is the closest planet to the Sun. Its extreme thermal environment makes it difficult to explore onsite. In 1974, Mariner 10, the first mission dedicated to Mercury, covered 45% of the surface during of the three Hermean flybys [1]. For about 30 years after Mariner 10, no other mission has flownto Mercury. Many unresolved issues need an answer, and in recent years the interest about Mercury has increased. MESSENGER mission contributed to understand Mercury's origin, its surface structure, and the nature of its magnetic field, exosphere, and magnetosphere [1]. The Mercury Dual Imaging System (MDIS) provided a global coverage of Mercury surface with variable spatial resolution. MDIS is equipped with a narrow angle camera (NAC), dedicated to the study of the geology and a wide angle camera (WAC) with 12 filters useful to investigate the surface composition[2]. Mercury has been divided into 15 quadrangles for mapping purposes [3]. The mapping process permits integration of different geological surface information to better understand the planet crust formation and evolution. Merging spectroscopically data is a poorly followed approach in planetary mapping, but it gives additional information about lithological composition, contributing to the construction of a more complete geological map [e.g. 4]. Recently, [5] proposed a first detailed map of all the Victoria quadrangle (H2). Victoria quadrangle is located in a longitude range between 270°E and 360°E and a latitude range of 22.5°N and 65°N,and itwas only partially mapped by Mariner 10 data[3]. Here we investigate the lithological variation by using the MDIS-WAC data to produce a set of color map products which could be asupport to the geological mapping [5]. The future ESA-JAXA mission to Mercury, BepiColombo, will soon contribute to improve the knowledge of Mercury surface composition and geology thanks to the Spectrometer and Imagers for MPO BepiColombo-Integrated Observatory SYStem (SIMBIO-SYS)[6].

Spatial variation of dosimetric leaf gap and its impact on dose delivery

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

Kumaraswamy, Lalith K., E-mail: Lalith.Kumaraswamy@roswellpark.org; Schmitt, Jonathan D.; Bailey, Daniel W.

Purpose: During dose calculation, the Eclipse treatment planning system (TPS) retracts the multileaf collimator (MLC) leaf positions by half of the dosimetric leaf gap (DLG) value (measured at central axis) for all leaf positions in a dynamic MLC plan to accurately model the rounded leaf ends. The aim of this study is to map the variation of DLG along the travel path of each MLC leaf pair and quantify how this variation impacts delivered dose. Methods: 6 MV DLG values were measured for all MLC leaf pairs in increments of 1.0 cm (from the line intersecting the CAX and perpendicularmore » to MLC motion) to 13.0 cm off axis distance at dmax. The measurements were performed on two Varian linear accelerators, both employing the Millennium 120-leaf MLCs. The measurements were performed at several locations in the beam with both a Sun Nuclear MapCHECK device and a PTW pinpoint ion chamber. Results: The measured DLGs for the middle 40 MLC leaf pairs (each 0.5 cm width) at positions along a line through the CAX and perpendicular to MLC leaf travel direction were very similar, varying maximally by only 0.2 mm. The outer 20 MLC leaf pairs (each 1.0 cm width) have much lower DLG values, about 0.3–0.5 mm lower than the central MLC leaf pair, at their respective central line position. Overall, the mean and the maximum variation between the 0.5 cm width leaves and the 1.0 cm width leaf pairs are 0.32 and 0.65 mm, respectively. Conclusions: The spatial variation in DLG is caused by the variation of intraleaf transmission through MLC leaves. Fluences centered on the CAX would not be affected since DLG does not vary; but any fluences residing significantly off axis with narrow sweeping leaves may exhibit significant dose differences. This is due to the fact that there are differences in DLG between the true DLG exhibited by the 1.0 cm width outer leaves and the constant DLG value utilized by the TPS for dose calculation. Since there are large differences in DLG between the 0.5 cm width leaf pairs and 1.0 cm width leaf pairs, there is a need to correct the TPS plans, especially those with high modulation (narrow dynamic MLC gap), with 2D variation of DLG.« less

Preschool children use space, rather than counting, to infer the numerical magnitude of digits: Evidence for a spatial mapping principle.

PubMed

Sella, Francesco; Berteletti, Ilaria; Lucangeli, Daniela; Zorzi, Marco

2017-01-01

A milestone in numerical development is the acquisition of counting principles which allow children to exactly determine the numerosity of a given set. Moreover, a canonical left-to-right spatial layout for representing numbers also emerges during preschool. These foundational aspects of numerical competence have been extensively studied, but there is sparse knowledge about the interplay between the acquisition of the cardinality principle and spatial mapping of numbers in early numerical development. The present study investigated how these skills concurrently develop before formal schooling. Preschool children were classified according to their performance in Give-a-Number and Number-to-position tasks. Experiment 1 revealed three qualitatively different groups: (i) children who did not master the cardinality principle and lacked any consistent spatial mapping for digits, (ii) children who mastered the cardinality principle and yet failed in spatial mapping, and (iii) children who mastered the cardinality principle and displayed consistent spatial mapping. This suggests that mastery of the cardinality principle does not entail the emergence of spatial mapping. Experiment 2 confirmed the presence of these three developmental stages and investigated their relation with a digit comparison task. Crucially, only children who displayed a consistent spatial mapping of numbers showed the ability to compare digits by numerical magnitude. A congruent (i.e., numerically ordered) positioning of numbers onto a visual line as well as the concept that moving rightwards (in Western cultures) conveys an increase in numerical magnitude mark the mastery of a spatial mapping principle. Children seem to rely on this spatial organization to achieve a full understanding of the magnitude relations between digits. Copyright © 2016 Elsevier B.V. All rights reserved.

Temperature Variations from HST Imagery of NGC 7009

NASA Astrophysics Data System (ADS)

Rubin, R. H.; Bhatt, N.; Dufour, R. J.; Buckalew, B.; Barlow, M. J.; Liu, X.; Storey, P. J.; Balick, B.; Ferland, G. J.; Harrington, J. P.; Martin, P. G.

2000-12-01

We present new HST/WFPC2 imagery for the planetary nebula (PN) NGC 7009. Observations were made in line filters F437N, F487N, F502N, and F656N plus continuum filter F547M. The primary goal was to develop a high spatial resolution ( ~0.1'') map of the intrinsic line ratio [O 3] 4363/5007 and thereby evaluate the electron temperature (Te) and the mean-square Te variation (t2) across the nebula. In this process we developed an extinction map from the F487N (Hβ ) and F656N (Hα ) images by comparing the observed line ratios in each pixel to the theoretical ratio and computing a c(Hβ ) map which was used to correct the observed 4363/5007 ratios for reddening. As has been known, extinction is not large for this PN as we further demonstrate in our reddening map. The most difficult and uncertain step is to extract the flux for [O 3] 4363 from the F437N data. Because this line is relatively weak, the continuum contribution to the observed F437N filter data is not negligible. Additionally, it is necessary to adjust for Hγ ``leakage" in the F437N bandpass. Because the dominant contribution to the nebular continuum for NGC 7009 is recombination processes, we correct for the continuum emission as well as the Hγ ``leakage" into the F437N bandpass using our F487N (Hβ ) image. A preliminary tie-in with ground-based spectra indicates this is best done by subtracting 0.012*F487N from F437N. We present a picture of the [O 3] Te map, as well as our determinations of t2. The preliminary map is rather uniform; almost all values are between 9000 -- 10500 K, with the higher Tes closely coinciding with the inner He++-zone as seen in blue in the WFPC2 image of Balick et al. (1998, AJ, 116, 360). Improvements are in progress that utilize our recent HST/STIS long-slit spectra to provide excellent co-spatial registration with the WFPC2 data to test/refine our methodology and analysis. Supported by AURA/STScI grant related to GO-8114.

Comparison of CO2 Emissions Data for 30 Cities from Different Sources

NASA Astrophysics Data System (ADS)

Nakagawa, Y.; Koide, D.; Ito, A.; Saito, M.; Hirata, R.

2017-12-01

Many sources suggest that cities account for a large proportion of global anthropogenic greenhouse gas emissions. Therefore, in search for the best ways to reduce total anthropogenic greenhouse gas emissions, a focus on the city emission is crucial. In this study, we collected CO2 emissions data in 30 cities during 1990-2015 and evaluated the degree of variance between data sources. The CO2 emissions data were obtained from academic papers, municipal reports, and high-resolution emissions maps (CIDIACv2016, EDGARv4.2, ODIACv2016, and FFDASv2.0). To extract urban CO2 emissions from the high-resolution emissions maps, urban fraction ranging from 0 to 1 was calculated for each 1×1 degree grid cell using the global land cover data (SYNMAP). Total CO2 emissions from the grid cells in which urban fraction occupies greater than or equal to 0.9 were regarded as urban CO2 emissions. The estimated CO2 emissions varied greatly depending on the information sources, even in the same year. There was a large difference between CO2 emissions collected from academic papers, municipal reports, and those extracted from high-resolution emissions maps. One reason is that they use different city boundaries. That is, the city proper (i.e. the political city boundary) is often defined as the city boundary in academic papers and municipal reports, whereas the urban area is used in the high-resolution emissions maps. Furthermore, there was a large variation in CO2 emissions collected from academic papers and municipal reports. These differences may be due to the difference in the assumptions such as allocation ratio of CO2 emissions to producers and consumers. In general, the consumption-based assignment of emissions gives higher estimates of urban CO2 emission in comparison with production-based assignment. Furthermore, there was also a large variation in CO2 emissions extracted from high-resolution emissions maps. This difference would be attributable to differences in information used in the spatial disaggregation of emissions. To identify the CO2 emissions from cities, it is necessary to determine common definitions of city boundaries, allocation ratio of CO2 emissions to consumption and production, and refined approach of the spatial disaggregation of CO2 emissions in high-resolution emissions maps.

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

PubMed

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

2018-05-07

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

Conservatism and novelty in the genetic architecture of adaptation in Heliconius butterflies.

PubMed

Huber, B; Whibley, A; Poul, Y L; Navarro, N; Martin, A; Baxter, S; Shah, A; Gilles, B; Wirth, T; McMillan, W O; Joron, M

2015-05-01

Understanding the genetic architecture of adaptive traits has been at the centre of modern evolutionary biology since Fisher; however, evaluating how the genetic architecture of ecologically important traits influences their diversification has been hampered by the scarcity of empirical data. Now, high-throughput genomics facilitates the detailed exploration of variation in the genome-to-phenotype map among closely related taxa. Here, we investigate the evolution of wing pattern diversity in Heliconius, a clade of neotropical butterflies that have undergone an adaptive radiation for wing-pattern mimicry and are influenced by distinct selection regimes. Using crosses between natural wing-pattern variants, we used genome-wide restriction site-associated DNA (RAD) genotyping, traditional linkage mapping and multivariate image analysis to study the evolution of the architecture of adaptive variation in two closely related species: Heliconius hecale and H. ismenius. We implemented a new morphometric procedure for the analysis of whole-wing pattern variation, which allows visualising spatial heatmaps of genotype-to-phenotype association for each quantitative trait locus separately. We used the H. melpomene reference genome to fine-map variation for each major wing-patterning region uncovered, evaluated the role of candidate genes and compared genetic architectures across the genus. Our results show that, although the loci responding to mimicry selection are highly conserved between species, their effect size and phenotypic action vary throughout the clade. Multilocus architecture is ancestral and maintained across species under directional selection, whereas the single-locus (supergene) inheritance controlling polymorphism in H. numata appears to have evolved only once. Nevertheless, the conservatism in the wing-patterning toolkit found throughout the genus does not appear to constrain phenotypic evolution towards local adaptive optima.

Expression and Organization of Geographic Spatial Relations Based on Topic Maps

NASA Astrophysics Data System (ADS)

Liang, H. J.; Wang, H.; Cui, T. J.; Guo, J. F.

2017-09-01

Spatial Relation is one of the important components of Geographical Information Science and Spatial Database. There have been lots of researches on Spatial Relation and many different spatial relations have been proposed. The relationships among these spatial relations such as hierarchy and so on are complex and this brings some difficulties to the applications and teaching of these spatial relations. This paper summaries some common spatial relations, extracts the topic types, association types, resource types of these spatial relations using the technology of Topic Maps, and builds many different relationships among these spatial relations. Finally, this paper utilizes Java and Ontopia to build a topic map among these common spatial relations, forms a complex knowledge network of spatial relations, and realizes the effective management and retrieval of spatial relations.

The importance of regional models in assessing canine cancer incidences in Switzerland

PubMed Central

Leyk, Stefan; Brunsdon, Christopher; Graf, Ramona; Pospischil, Andreas; Fabrikant, Sara Irina

2018-01-01

Fitting canine cancer incidences through a conventional regression model assumes constant statistical relationships across the study area in estimating the model coefficients. However, it is often more realistic to consider that these relationships may vary over space. Such a condition, known as spatial non-stationarity, implies that the model coefficients need to be estimated locally. In these kinds of local models, the geographic scale, or spatial extent, employed for coefficient estimation may also have a pervasive influence. This is because important variations in the local model coefficients across geographic scales may impact the understanding of local relationships. In this study, we fitted canine cancer incidences across Swiss municipal units through multiple regional models. We computed diagnostic summaries across the different regional models, and contrasted them with the diagnostics of the conventional regression model, using value-by-alpha maps and scalograms. The results of this comparative assessment enabled us to identify variations in the goodness-of-fit and coefficient estimates. We detected spatially non-stationary relationships, in particular, for the variables related to biological risk factors. These variations in the model coefficients were more important at small geographic scales, making a case for the need to model canine cancer incidences locally in contrast to more conventional global approaches. However, we contend that prior to undertaking local modeling efforts, a deeper understanding of the effects of geographic scale is needed to better characterize and identify local model relationships. PMID:29652921

The importance of regional models in assessing canine cancer incidences in Switzerland.

PubMed

Boo, Gianluca; Leyk, Stefan; Brunsdon, Christopher; Graf, Ramona; Pospischil, Andreas; Fabrikant, Sara Irina

2018-01-01

Fitting canine cancer incidences through a conventional regression model assumes constant statistical relationships across the study area in estimating the model coefficients. However, it is often more realistic to consider that these relationships may vary over space. Such a condition, known as spatial non-stationarity, implies that the model coefficients need to be estimated locally. In these kinds of local models, the geographic scale, or spatial extent, employed for coefficient estimation may also have a pervasive influence. This is because important variations in the local model coefficients across geographic scales may impact the understanding of local relationships. In this study, we fitted canine cancer incidences across Swiss municipal units through multiple regional models. We computed diagnostic summaries across the different regional models, and contrasted them with the diagnostics of the conventional regression model, using value-by-alpha maps and scalograms. The results of this comparative assessment enabled us to identify variations in the goodness-of-fit and coefficient estimates. We detected spatially non-stationary relationships, in particular, for the variables related to biological risk factors. These variations in the model coefficients were more important at small geographic scales, making a case for the need to model canine cancer incidences locally in contrast to more conventional global approaches. However, we contend that prior to undertaking local modeling efforts, a deeper understanding of the effects of geographic scale is needed to better characterize and identify local model relationships.

The feature-weighted receptive field: an interpretable encoding model for complex feature spaces.

PubMed

St-Yves, Ghislain; Naselaris, Thomas

2017-06-20

We introduce the feature-weighted receptive field (fwRF), an encoding model designed to balance expressiveness, interpretability and scalability. The fwRF is organized around the notion of a feature map-a transformation of visual stimuli into visual features that preserves the topology of visual space (but not necessarily the native resolution of the stimulus). The key assumption of the fwRF model is that activity in each voxel encodes variation in a spatially localized region across multiple feature maps. This region is fixed for all feature maps; however, the contribution of each feature map to voxel activity is weighted. Thus, the model has two separable sets of parameters: "where" parameters that characterize the location and extent of pooling over visual features, and "what" parameters that characterize tuning to visual features. The "where" parameters are analogous to classical receptive fields, while "what" parameters are analogous to classical tuning functions. By treating these as separable parameters, the fwRF model complexity is independent of the resolution of the underlying feature maps. This makes it possible to estimate models with thousands of high-resolution feature maps from relatively small amounts of data. Once a fwRF model has been estimated from data, spatial pooling and feature tuning can be read-off directly with no (or very little) additional post-processing or in-silico experimentation. We describe an optimization algorithm for estimating fwRF models from data acquired during standard visual neuroimaging experiments. We then demonstrate the model's application to two distinct sets of features: Gabor wavelets and features supplied by a deep convolutional neural network. We show that when Gabor feature maps are used, the fwRF model recovers receptive fields and spatial frequency tuning functions consistent with known organizational principles of the visual cortex. We also show that a fwRF model can be used to regress entire deep convolutional networks against brain activity. The ability to use whole networks in a single encoding model yields state-of-the-art prediction accuracy. Our results suggest a wide variety of uses for the feature-weighted receptive field model, from retinotopic mapping with natural scenes, to regressing the activities of whole deep neural networks onto measured brain activity. Copyright © 2017. Published by Elsevier Inc.

SOFIA/FORCAST Observations of the Arched Filamentary Region in the Galactic Center

NASA Astrophysics Data System (ADS)

Hankins, Matthew; Lau, Ryan M.; Morris, Mark; Herter, Terry L.

2016-06-01

Abstract: We present 19.7, 25.2, 31.5, and 37.1 μm maps of the Thermal Arched Filament region in the Galactic Center taken with the Faint Object Infrared Camera for the SOFIA Telescope (FORCAST) with an angular resolution of 3.2-3.8". We calculate the integrated infrared luminosity of the Arched Filaments and show that they are consistent with being heated by the nearby Arches cluster. Additionally, using our observations, we infer dust temperatures (75 - 90 K) across the Arched Filaments which are remarkably consistent over large spatial scales (˜ 25 pc). We discuss the possible geometric effects needed to recreate this temperature structure. Additionally, we compare the observed morphology of the Arches in the FORCAST maps with the Paschen-α emission in the region to study what fraction of the infrared emission may be coming from dust in the HII region versus the PDR beneath it. Finally, we use Spitzer/IRAC 8 μm data to look for spatial variations in PAH abundance in the rich UV environment of the young (~2-4 Myr) and massive Arches cluster.

Hydroacoustic estimation of zooplankton biomass at two shoal complexes in the Apostle Islands Region of Lake Superior

USGS Publications Warehouse

Holbrook, B.V.; Hrabik, T.R.; Branstrator, D.K.; Yule, D.L.; Stockwell, J.D.

2006-01-01

Hydroacoustics can be used to assess zooplankton populations, however, backscatter must be scaled to be biologically meaningful. In this study, we used a general model to correlate site-specific hydroacoustic backscatter with zooplankton dry weight biomass estimated from net tows. The relationship between zooplankton dry weight and backscatter was significant (p < 0.001) and explained 76% of the variability in the dry weight data. We applied this regression to hydroacoustic data collected monthly in 2003 and 2004 at two shoals in the Apostle Island Region of Lake Superior. After applying the regression model to convert hydroacoustic backscatter to zooplankton dry weight biomass, we used geostatistics to analyze the mean and variance, and ordinary kriging to create spatial zooplankton distribution maps. The mean zooplankton dry weight biomass estimates from plankton net tows and hydroacoustics were not significantly different (p = 0.19) but the hydroacoustic data had a significantly lower coefficient of variation (p < 0.001). The maps of zooplankton distribution illustrated spatial trends in zooplankton dry weight biomass that were not discernable from the overall means.

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

PubMed

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

2004-06-11

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

Roles of Fog and Topography in Redwood Forest Hydrology

NASA Astrophysics Data System (ADS)

Francis, E. J.; Asner, G. P.

2017-12-01

Spatial variability of water in forests is a function of both climatic gradients that control water inputs and topo-edaphic variation that determines the flows of water belowground, as well as interactions of climate with topography. Coastal redwood forests are hydrologically unique because they are influenced by coastal low clouds, or fog, that is advected onto land by a strong coastal-to-inland temperature difference. Where fog intersects the land surface, annual water inputs from summer fog drip can be greater than that of winter rainfall. In this study, we take advantage of mapped spatial gradients in forest canopy water storage, topography, and fog cover in California to better understand the roles and interactions of fog and topography in the hydrology of redwood forests. We test a conceptual model of redwood forest hydrology with measurements of canopy water content derived from high-resolution airborne imaging spectroscopy, topographic variables derived from high-resolution LiDAR data, and fog cover maps derived from NASA MODIS data. Landscape-level results provide insight into hydrological processes within redwood forests, and cross-site analyses shed light on their generality.

Landsat-Derived, Time-Series Remote Sensing Analysis of Fire Regime, Microclimate, and Urbanization's Influence on Biodiversity in the Santa Monica Mountain Coastal Range

NASA Astrophysics Data System (ADS)

Ma, J.; Dmochowski, J. E.

2016-12-01

Southern California's Santa Monica Mountain coastal range hosts chaparral and coastal sage scrub ecosystems with distinct, local variations in their fire regime, microclimate, and proximity to urbanization. The high biodiversity combined with ongoing human impact make monitoring the ecological and land cover changes crucial. Due to their extensive, continuous temporal coverage and high spatial resolution, Landsat data are well suited to this purpose. Landsat-derived time-series NDVI data and classification maps have been compiled to identify regions most sensitive to change in order to determine the effects of fire regime, geography, and urbanization on vegetative changes; and assess the encroachment of non-native grasses. Spatial analysis of the classification maps identified the factors more conducive to land-cover changes as native shrubs were replaced with non-native grasses. Understanding the dynamics that govern semi-arid resilience, overall greening, and fire regime is important to predicting and managing large scale ecosystem changes as pressures from global climate change and urbanization intensify.

Spatially resolved mapping of electrical conductivity across individual domain (grain) boundaries in graphene.

PubMed

Clark, Kendal W; Zhang, X-G; Vlassiouk, Ivan V; He, Guowei; Feenstra, Randall M; Li, An-Ping

2013-09-24

All large-scale graphene films contain extended topological defects dividing graphene into domains or grains. Here, we spatially map electronic transport near specific domain and grain boundaries in both epitaxial graphene grown on SiC and CVD graphene on Cu subsequently transferred to a SiO2 substrate, with one-to-one correspondence to boundary structures. Boundaries coinciding with the substrate step on SiC exhibit a significant potential barrier for electron transport of epitaxial graphene due to the reduced charge transfer from the substrate near the step edge. Moreover, monolayer-bilayer boundaries exhibit a high resistance that can change depending on the height of substrate step coinciding at the boundary. In CVD graphene, the resistance of a grain boundary changes with the width of the disordered transition region between adjacent grains. A quantitative modeling of boundary resistance reveals the increased electron Fermi wave vector within the boundary region, possibly due to boundary induced charge density variation. Understanding how resistance change with domain (grain) boundary structure in graphene is a crucial first step for controlled engineering of defects in large-scale graphene films.

Hydrological model uncertainty due to spatial evapotranspiration estimation methods

NASA Astrophysics Data System (ADS)

Yu, Xuan; Lamačová, Anna; Duffy, Christopher; Krám, Pavel; Hruška, Jakub

2016-05-01

Evapotranspiration (ET) continues to be a difficult process to estimate in seasonal and long-term water balances in catchment models. Approaches to estimate ET typically use vegetation parameters (e.g., leaf area index [LAI], interception capacity) obtained from field observation, remote sensing data, national or global land cover products, and/or simulated by ecosystem models. In this study we attempt to quantify the uncertainty that spatial evapotranspiration estimation introduces into hydrological simulations when the age of the forest is not precisely known. The Penn State Integrated Hydrologic Model (PIHM) was implemented for the Lysina headwater catchment, located 50°03‧N, 12°40‧E in the western part of the Czech Republic. The spatial forest patterns were digitized from forest age maps made available by the Czech Forest Administration. Two ET methods were implemented in the catchment model: the Biome-BGC forest growth sub-model (1-way coupled to PIHM) and with the fixed-seasonal LAI method. From these two approaches simulation scenarios were developed. We combined the estimated spatial forest age maps and two ET estimation methods to drive PIHM. A set of spatial hydrologic regime and streamflow regime indices were calculated from the modeling results for each method. Intercomparison of the hydrological responses to the spatial vegetation patterns suggested considerable variation in soil moisture and recharge and a small uncertainty in the groundwater table elevation and streamflow. The hydrologic modeling with ET estimated by Biome-BGC generated less uncertainty due to the plant physiology-based method. The implication of this research is that overall hydrologic variability induced by uncertain management practices was reduced by implementing vegetation models in the catchment models.

An improved geographically weighted regression model for PM2.5 concentration estimation in large areas

NASA Astrophysics Data System (ADS)

Zhai, Liang; Li, Shuang; Zou, Bin; Sang, Huiyong; Fang, Xin; Xu, Shan

2018-05-01

Considering the spatial non-stationary contributions of environment variables to PM2.5 variations, the geographically weighted regression (GWR) modeling method has been using to estimate PM2.5 concentrations widely. However, most of the GWR models in reported studies so far were established based on the screened predictors through pretreatment correlation analysis, and this process might cause the omissions of factors really driving PM2.5 variations. This study therefore developed a best subsets regression (BSR) enhanced principal component analysis-GWR (PCA-GWR) modeling approach to estimate PM2.5 concentration by fully considering all the potential variables' contributions simultaneously. The performance comparison experiment between PCA-GWR and regular GWR was conducted in the Beijing-Tianjin-Hebei (BTH) region over a one-year-period. Results indicated that the PCA-GWR modeling outperforms the regular GWR modeling with obvious higher model fitting- and cross-validation based adjusted R2 and lower RMSE. Meanwhile, the distribution map of PM2.5 concentration from PCA-GWR modeling also clearly depicts more spatial variation details in contrast to the one from regular GWR modeling. It can be concluded that the BSR enhanced PCA-GWR modeling could be a reliable way for effective air pollution concentration estimation in the coming future by involving all the potential predictor variables' contributions to PM2.5 variations.

Spatially resolved near infrared observations of Enceladus' tiger stripe eruptions from Cassini VIMS

NASA Astrophysics Data System (ADS)

Dhingra, Deepak; Hedman, Matthew M.; Clark, Roger N.; Nicholson, Philip D.

2017-08-01

Particle properties of individual fissure eruptions within Enceladus' plume have been analyzed using high spatial resolution Visible and Infrared Mapping Spectrometer (VIMS) observations from the Cassini mission. To first order, the spectra of the materials emerging from Cairo, Baghdad and Damascus sulci are very similar, with a strong absorption band around 3 μm due to water-ice. The band minimum position indicates that the ice grains emerging from all the fissures are predominantly crystalline, which implies that the water-ice particles' formation temperatures are likely above 130 K. However, there is also evidence for subtle variations in the material emerging from the different source fissures. Variations in the spectral slope between 1-2.5 μm are observed and probably reflect differences in the size distributions of particles between 0.5 and 5 μm in radius. We also note variations in the shape of the 3 μm water-ice absorption band, which are consistent with differences in the relative abundance of > 5 μm particles. These differences in the particle size distribution likely reflect variations in the particle formation conditions and/or their transport within the fissures. These observations therefore provide strong motivation for detailed modeling to help place important constraints on the diversity of the sub-surface environmental conditions at the geologically active south-pole of Enceladus.